Broker’s Edge Calculator Binary Trading

No gods, no kings, only NOPE - or divining the future with options flows. [Part 2: A Random Walk and Price Decoherence]

tl;dr -
1) Stock prices move continuously because different market participants end up having different ideas of the future value of a stock.
2) This difference in valuations is part of the reason we have volatility.
3) IV crush happens as a consequence of future possibilities being extinguished at a binary catalyst like earnings very rapidly, as opposed to the normal slow way.
I promise I'm getting to the good parts, but I'm also writing these as a guidebook which I can use later so people never have to talk to me again.
In this part I'm going to start veering a bit into the speculation territory (e.g. ideas I believe or have investigated, but aren't necessary well known) but I'm going to make sure those sections are properly marked as speculative (and you can feel free to ignore/dismiss them). Marked as [Lily's Speculation].
As some commenters have pointed out in prior posts, I do not have formal training in mathematical finance/finance (my background is computer science, discrete math, and biology), so often times I may use terms that I've invented which have analogous/existing terms (e.g. the law of surprise is actually the first law of asset pricing applied to derivatives under risk neutral measure, but I didn't know that until I read the papers later). If I mention something wrong, please do feel free to either PM me (not chat) or post a comment, and we can discuss/I can correct it! As always, buyer beware.
This is the first section also where you do need to be familiar with the topics I've previously discussed, which I'll add links to shortly (my previous posts:
1) https://www.reddit.com/thecorporation/comments/jck2q6/no_gods_no_kings_only_nope_or_divining_the_future/
2) https://www.reddit.com/thecorporation/comments/jbzzq4/why_options_trading_sucks_or_the_law_of_surprise/
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A Random Walk Down Bankruptcy
A lot of us have probably seen the term random walk, maybe in the context of A Random Walk Down Wall Street, which seems like a great book I'll add to my list of things to read once I figure out how to control my ADD. It seems obvious, then, what a random walk means - when something is moving, it basically means that the next move is random. So if my stock price is $1 and I can move in $0.01 increments, if the stock price is truly randomly walking, there should be roughly a 50% chance it moves up in the next second (to $1.01) or down (to $0.99).
If you've traded for more than a hot minute, this concept should seem obvious, because especially on the intraday, it usually isn't clear why price moves the way it does (despite what chartists want to believe, and I'm sure a ton of people in the comments will tell me why fettucini lines and Batman doji tell them things). For a simple example, we can look at SPY's chart from Friday, Oct 16, 2020:

https://preview.redd.it/jgg3kup9dpt51.png?width=1368&format=png&auto=webp&s=bf8e08402ccef20832c96203126b60c23277ccc2
I'm sure again 7 different people can tell me 7 different things about why the chart shape looks the way it does, or how if I delve deeply enough into it I can find out which man I'm going to marry in 2024, but to a rationalist it isn't exactly apparent at why SPY's price declined from 349 to ~348.5 at around 12:30 PM, or why it picked up until about 3 PM and then went into precipitous decline (although I do have theories why it declined EOD, but that's for another post).
An extremely clever or bored reader from my previous posts could say, "Is this the price formation you mentioned in the law of surprise post?" and the answer is yes. If we relate it back to the individual buyer or seller, we can explain the concept of a stock price's random walk as such:
Most market participants have an idea of an asset's true value (an idealized concept of what an asset is actually worth), which they can derive using models or possibly enough brain damage. However, an asset's value at any given time is not worth one value (usually*), but a spectrum of possible values, usually representing what the asset should be worth in the future. A naive way we can represent this without delving into to much math (because let's face it, most of us fucking hate math) is:
Current value of an asset = sum over all (future possible value multiplied by the likelihood of that value)
In actuality, most models aren't that simple, but it does generalize to a ton of more complicated models which you need more than 7th grade math to understand (Black-Scholes, DCF, blah blah blah).
While in many cases the first term - future possible value - is well defined (Tesla is worth exactly $420.69 billion in 2021, and maybe we all can agree on that by looking at car sales and Musk tweets), where it gets more interesting is the second term - the likelihood of that value occurring. [In actuality, the price of a stock for instance is way more complicated, because a stock can be sold at any point in the future (versus in my example, just the value in 2021), and needs to account for all values of Tesla at any given point in the future.]
How do we estimate the second term - the likelihood of that value occurring? For this class, it actually doesn't matter, because the key concept is this idea: even with all market participants having the same information, we do anticipate that every participant will have a slightly different view of future likelihoods. Why is that? There's many reasons. Some participants may undervalue risk (aka WSB FD/yolos) and therefore weight probabilities of gaining lots of money much more heavily than going bankrupt. Some participants may have alternative data which improves their understanding of what the future values should be, therefore letting them see opportunity. Some participants might overvalue liquidity, and just want to GTFO and thereby accept a haircut on their asset's value to quickly unload it (especially in markets with low liquidity). Some participants may just be yoloing and not even know what Fastly does before putting their account all in weekly puts (god bless you).
In the end, it doesn't matter either the why, but the what: because of these diverging interpretations, over time, we can expect the price of an asset to drift from the current value even with no new information added. In most cases, the calculations that market participants use (which I will, as a Lily-ism, call the future expected payoff function, or FEPF) ends up being quite similar in aggregate, and this is why asset prices likely tend to move slightly up and down for no reason (or rather, this is one interpretation of why).
At this point, I expect the 20% of you who know what I'm talking about or have a finance background to say, "Oh but blah blah efficient market hypothesis contradicts random walk blah blah blah" and you're correct, but it also legitimately doesn't matter here. In the long run, stock prices are clearly not a random walk, because a stock's value is obviously tied to the company's fundamentals (knock on wood I don't regret saying this in the 2020s). However, intraday, in the absence of new, public information, it becomes a close enough approximation.
Also, some of you might wonder what happens when the future expected payoff function (FEPF) I mentioned before ends up wildly diverging for a stock between participants. This could happen because all of us try to short Nikola because it's quite obviously a joke (so our FEPF for Nikola could, let's say, be 0), while the 20 or so remaining bagholders at NikolaCorporation decide that their FEPF of Nikola is $10,000,000 a share). One of the interesting things which intuitively makes sense, is for nearly all stocks, the amount of divergence among market participants in their FEPF increases substantially as you get farther into the future.
This intuitively makes sense, even if you've already quit trying to understand what I'm saying. It's quite easy to say, if at 12:51 PM SPY is worth 350.21 that likely at 12:52 PM SPY will be worth 350.10 or 350.30 in all likelihood. Obviously there are cases this doesn't hold, but more likely than not, prices tend to follow each other, and don't gap up/down hard intraday. However, what if I asked you - given SPY is worth 350.21 at 12:51 PM today, what will it be worth in 2022?
Many people will then try to half ass some DD about interest rates and Trump fleeing to Ecuador to value SPY at 150, while others will assume bull markets will continue indefinitely and SPY will obviously be 7000 by then. The truth is -- no one actually knows, because if you did, you wouldn't be reading a reddit post on this at 2 AM in your jammies.
In fact, if you could somehow figure out the FEPF of all market participants at any given time, assuming no new information occurs, you should be able to roughly predict the true value of an asset infinitely far into the future (hint: this doesn't exactly hold, but again don't @ me).
Now if you do have a finance background, I expect gears will have clicked for some of you, and you may see strong analogies between the FEPF divergence I mentioned, and a concept we're all at least partially familiar with - volatility.
Volatility and Price Decoherence ("IV Crush")
Volatility, just like the Greeks, isn't exactly a real thing. Most of us have some familiarity with implied volatility on options, mostly when we get IV crushed the first time and realize we just lost $3000 on Tesla calls.
If we assume that the current price should represent the weighted likelihoods of all future prices (the random walk), volatility implies the following two things:
  1. Volatility reflects the uncertainty of the current price
  2. Volatility reflects the uncertainty of the future price for every point in the future where the asset has value (up to expiry for options)
[Ignore this section if you aren't pedantic] There's obviously more complex mathematics, because I'm sure some of you will argue in the comments that IV doesn't go up monotonically as option expiry date goes longer and longer into the future, and you're correct (this is because asset pricing reflects drift rate and other factors, as well as certain assets like the VIX end up having cost of carry).
Volatility in options is interesting as well, because in actuality, it isn't something that can be exactly computed -- it arises as a plug between the idealized value of an option (the modeled price) and the real, market value of an option (the spot price). Additionally, because the makeup of market participants in an asset's market changes over time, and new information also comes in (thereby increasing likelihood of some possibilities and reducing it for others), volatility does not remain constant over time, either.
Conceptually, volatility also is pretty easy to understand. But what about our friend, IV crush? I'm sure some of you have bought options to play events, the most common one being earnings reports, which happen quarterly for every company due to regulations. For the more savvy, you might know of expected move, which is a calculation that uses the volatility (and therefore price) increase of at-the-money options about a month out to calculate how much the options market forecasts the underlying stock price to move as a response to ER.
Binary Catalyst Events and Price Decoherence
Remember what I said about price formation being a gradual, continuous process? In the face of special circumstances, in particularly binary catalyst events - events where the outcome is one of two choices, good (1) or bad (0) - the gradual part gets thrown out the window. Earnings in particular is a common and notable case of a binary event, because the price will go down (assuming the company did not meet the market's expectations) or up (assuming the company exceeded the market's expectations) (it will rarely stay flat, so I'm not going to address that case).
Earnings especially is interesting, because unlike other catalytic events, they're pre-scheduled (so the whole market expects them at a certain date/time) and usually have publicly released pre-estimations (guidance, analyst predictions). This separates them from other binary catalysts (e.g. FSLY dipping 30% on guidance update) because the market has ample time to anticipate the event, and participants therefore have time to speculate and hedge on the event.
In most binary catalyst events, we see rapid fluctuations in price, usually called a gap up or gap down, which is caused by participants rapidly intaking new information and changing their FEPF accordingly. This is for the most part an anticipated adjustment to the FEPF based on the expectation that earnings is a Very Big Deal (TM), and is the reason why volatility and therefore option premiums increase so dramatically before earnings.
What makes earnings so interesting in particular is the dramatic effect it can have on all market participants FEPF, as opposed to let's say a Trump tweet, or more people dying of coronavirus. In lots of cases, especially the FEPF of the short term (3-6 months) rapidly changes in response to updated guidance about a company, causing large portions of the future possibility spectrum to rapidly and spectacularly go to zero. In an instant, your Tesla 10/30 800Cs go from "some value" to "not worth the electrons they're printed on".
[Lily's Speculation] This phenomena, I like to call price decoherence, mostly as an analogy to quantum mechanical processes which produce similar results (the collapse of a wavefunction on observation). Price decoherence occurs at a widespread but minor scale continuously, which we normally call price formation (and explains portions of the random walk derivation explained above), but hits a special limit in the face of binary catalyst events, as in an instant rapid portions of the future expected payoff function are extinguished, versus a more gradual process which occurs over time (as an option nears expiration).
Price decoherence, mathematically, ends up being a more generalizable case of the phenomenon we all love to hate - IV crush. Price decoherence during earnings collapses the future expected payoff function of a ticker, leading large portions of the option chain to be effectively worthless (IV crush). It has interesting implications, especially in the case of hedged option sellers, our dear Market Makers. This is because given the expectation that they maintain delta-gamma neutral, and now many of the options they have written are now worthless and have 0 delta, what do they now have to do?
They have to unwind.
[/Lily's Speculation]
- Lily
submitted by the_lilypad to thecorporation [link] [comments]

Greed is Subtle

The morning alarm woke up Ghen. With an annoyed sigh, he stretched out his arm and silenced the foul-sounding chirps. Slowly sitting up in bed, he let out a deep yawn and got to his feet.
Running a couple of chitinous fingers along his antennae to stimulate them to life, he made his bed and then went to his closet. Today was a work day, so he needed his suit. Once the pants were on, he stretched out his wings so that he could button up the shirt, then relaxing them once all the buttons were secured.
Dressing for the day was done, now for the morning meal. Entering his kitchen, he took out the chilled leftovers of the evening meal last night and popped it into the radiator, first defrosting and then slightly cooking it.
During that process, he also fished out a ceramic cup and placed it in his brewer, serving himself some synthesized caffeine. His idle thought led him to being amused that, when eaten directly off a plant, it has a concentration that could kill him three times over. But after going through some refinement and roasting, all it does is make him hyper.
Once the meal was put together, his plate of heated leftovers and a cup of almost-piping-hot cup of Xia's, he took his time to enjoy it. His communicator vibrated. When he looked, he found it was from his boss.
"Hello?" Ghen answered.
"Ghen, the meeting's been moved up to a few minutes from now." His boss, Xkik, announced. "Apparently higher up has something important they want to say. We have a terminal ready for you, I'll message the login details."
"Wha-, what's so important?" Ghen asked in bewilderment. "Did a water line rupture or something?"
"No, nothing like that." Xkik replied with a slight chuckle. "It's actually about the rumors we've been hearing. That human corporation wanting to acquire us? That's what they're talking about."
Ghen could feel everything inside his thorax drop to the floor. "That must mean it's true then, right? Did we get sold off by the Queen to this company then?"
"Show up to the meeting and you'll get your answer." Xkik said simply. When he finished, Ghen got the notification on his communicator. There's the login details, allowing him to remotely attend the meeting. "They're about to start, hurry up."
Once Xkik disconnected, Ghen worked fast to login and set up the remote viewing. Once everything was done, his screen started transmitting the meeting room. It was already packed. And off by the main board, he saw his answer. There was a human, resting against the wall on his two legs. Standing right in the center of everyone's view was the coordinator, Tizx, watching the clock periodically.
As soon as the meeting's start time was reached, the coordinator began. "Alright everyone. I realize that this was rather short notice, so I want to say how appreciative I am that you made it. Now then, let's just get right to it. For some time now, many of you have been hearing rumors that a human corporation has been interested in us. Why? We never really knew. We're just an organization responsible for finding, extracting and providing water to the colony here all under the direction of the Queen herself. Well, as of now, I have the answer for you. Why don't I let Ryan say that?"
Stepping back, Tizx motioned for the human, Ryan, to take over. With a nod, Ryan practically bounced over and then took the position. "Good morning to you all. I hope my Zazk is passable, heh. Anyways, the answer to those rumors, is yes. Terran Galactic Company is indeed interested in you all. Which now leads to me. I'm here to announce that, effective yesterday evening, this water company is now a subsidiary of Terran Galactic Company, under the name of Zilia Water Delivery."
Many other sub-coordinators broke into hushed conversation, no doubt speaking their thoughts with each other about this move. Ghen could only wonder if this was even a good thing. What will the humans do? Will he still have his job? Will he have to learn how to deal with the ruthless humans?
"Now, I am well aware this is quite the...uh, change." Ryan continued. "That's why I'm happy to inform you that, no, nothing negative or detrimental will happen to you. You just have new people to answer to. Operations will continue as normal, everybody here will still keep their jobs. The only real change any of you will personally experience is that Coordinator Tizx here will now report to someone else. On behalf of the Terran Galactic Company, we are extremely excited and are looking forward to working with you all. Thank you for your time."
A week later.
At least Ryan wasn't lying. After the initial shock wore off, things went back as they normally did. There were no terminations, no reductions in annual pay or anything. Nothing really changed. At least until this new meeting was called. Ghen was at the worksite this time, so he took his seat and watched as, once again, Ryan led the meeting.
"Hello again, everyone!" He said cheerfully, his Zazk noticeably improved. "I hope I didn't end up looking like a liar, right? Everything's still normal, all that?"
All the zazk in the room confirmed, providing comments to their pleasant surprise as well as lingering thoughts.
"Awesome! Awesome." Ryan said jubilantly, his fleshy mouth revealing his bone-white teeth. "Now then, you're probably wondering why I'm here again, right? Well, I got another fantastic piece of news for you all! Two, actually. I'll start with the first: Zilia Water Delivery has just completed its IPO. The company is now publicly traded!"
Ghen and the others voiced their confusion, having no idea what in the name of the Queen Ryan was talking about. What was Ryan talking about? What's an IPO? And why exactly is being publicly traded such a significant thing?
"Oh, you guys don't know any of that?" Ryan asked in surprised confusion. After everybody confirmed, he let out a quick huff as he began his explanation. "Well, to begin, IPO is short for Initial Public Offering. Basically what that means is that, before today, Zilia was privately held. Only certain individuals could buy and sell shares here. But now that we're public? Literally anyone can buy and sell shares in the company, hence us being publicly traded."
"Uh, what's a share?" Ghen asked, still completely lost.
"Oh, boy..." Ryan muttered under his breath before returning to his peppy image. "To simply put it, a share is short for having a share of ownership in a company. When you buy a share, you're buying a piece of ownership, and when you sell, you're selling that amount."
"So wait...if someone buys a share, they're a co-owner then?" One of the other team coordinators asked.
"If they get enough, yeah." Ryan nodded. "You need a lot though, and that really depends on the company. If I had to give an answer though? I'd say usually you need to have a lot more shares than a lot of people combined to be officially a co-owner, but we call that being a majority shareholder."
"And how do we do that?" Ghen asked, now growing curious but still not understanding why such a concept exists.
"Simple. Buy shares." Ryan said simply. "And that leads into the second piece of awesome news. Zilia's corporate has a product in mind, a premium-package of water delivery. Instead of the usual water that you pump out, filter and ensure its potable before delivery, with the premium package, not only will you get that, but you'll also get all of the required nutrients and vitamins the zazk body requires! And they feel you guys have the best expertise and understanding to pull it off! So, here's what we're offering as a good-faith bonus: A 25% increase to your annual salary as well as being given stock options."
Ghen wasn't sure about the second part, but the salary definitely got his attention, as well as everyone else's. Although his job was considered to have a good pay, Ghen isn't going to say no to a higher salary. In fact, he's been focusing his work on getting a promotion so he can come home with even more credits in pocket.
"What do you mean by stock options?" Ghen asked after some time.
Ryan let out that smile again, the one that revealed his teeth. "If you choose to transfer over to the new group, you'll be provided 50,000 shares in Zilia itself. Why's that awesome? Let me walk you through it. Right now, our last closing price per share was 3.02 credits. And if you have 50,000 shares during that time, you're sitting on 151,000 credits, if you cash it out immediately."
"And why shouldn't we?" One of the coordinators demanded in an ambiguous tone.
"Because the price per share changes a lot." Ryan explained promptly. "When we got done with the IPO? It closed at 2.73 a share. Right now? My money's on the closing price being 2.99 a share. However, we are extremely confident in this premium package being successful. If it does? Well, my bet is that the share price will skyrocket to 3.12 a share. If you hold those shares and the price gets to what my bet was? You'll instead get 156,000 credits. Just by holding onto them, you just made an additional 5,000 credits!"
"And what if we have more shares?" Ghen questioned, now getting excited at the prospect of free money.
"Even more money!" Ryan laughed a bit. "And don't forget about dividends, but that's for another time. The premium group is gearing up right now, we just need the workforce. If any of you wants in, I'll be back tomorrow with all the forms needed to make it official. Take the day and tonight to think it over, yeah?"
Everything else melted into a blur. Ghen was practically on autopilot that whole day. Was this the secret to the humans' incredibly massive economy? How so many of them have amassed so much money out of nowhere? All you had to do was just buy this share out of a company and you get more money without even working?
As soon as he got home, Ghen knew what he was going to do during the night. After feverishly looking through the galnet, now having the human race connected to it, he looked and gathered up as many books that were translated into zazk as he could find, all talking about the human economic system. The last time he undertook such an intensive study was during his primary education phase.
And during his search, he even found forums on the galnet that were completely dedicated to the human's economy. All of them talking about strategies on what company, or stock, to pick. How to analyze a company's performance to determine if it was worth the money, or it had potential to grow over time. And that was when he discovered the humans found another method to the extremely simple buying and selling process. There were humans and some other immigrated aliens who made five times what Ghen could receive over a simple month just by watching the share prices during trading hours, and then buying and selling them at the proper times.
Ghen's mind was just absolutely flabbergasted. He thought it was just some strange concept only aliens could make, but no, not with the humans. They've practically made their economy into an art or a science. No, not even their economy. Everything. If humans can see a way to make money off of it, they'll do it. And if there isn't, they'll look for a way.
Healthcare was monetized. Galnet services, transportation, shopping at the store, they even made all of their utilities into profit-oriented companies.
And it was there that Ghen paused, the realization slamming into him. Everything was monetized. Which means, if you don't have the money for it, you're not getting it. Right? Are the humans truly that ruthless? So obsessed with making money? To the point that they're willing to deprive their own people of the absolute necessities if it's a source of credits?
Ghen let out a scoff. There's no way. Nobody is that cruel and callous. He's never been to the United Nations. He can't rely on what a bunch of random people on the galnet says. He decided that from here on out, he'll only go as far as saying that humans are a little obsessed with credits, nothing more.
...
There he was. Ryan, sitting in the office provided to him. And there was a rather large line leading to him. Looks like word got around. Although, the line wasn't as large as he expected it to be. Maybe the others thought it was just a ruse? That there's no such thing as making free money by spending it on such a made-up concept?
Ghen only knows that, if it is a ruse, it's an extremely elaborate one, where all of the humans are in on it. And he believes that's just extremely ridiculous. At the end, if he's unsure, he'll just take the transfer for the very real increase in his very real salary. And although he spent a very good chunk of the night reading up on how humans do things, he's still going to play it smart. He'll leave his 50,000 shares alone and see where it goes from there.
"Good morning sir." Ryan greeted warmly once Ghen took his seat. "Now, name please?"
"Ghen." He answered, barely keeping his nerves down.
"Alright...and what's your position at this location?" Ryan questioned after scribbling on his form.
"I monitor the pumping stations near the extraction sites." Ghen explained, staying on point. "To be more specific, I check to see if they're in need of maintenance, as well as reading the flow rate that's determined by the calculators installed there. If there's too little for what's needed, I pump out more. And if there's too much, I pull it back a little."
"Nice...and how long have you been doing it for?" Ryan complimented with a nod.
"As of tomorrow, ten years." Ghen replied, voice quickly changing to minor awe once he realized that fact.
"Excellent. Do you have anyone in mind you'd like to replace you here?" Ryan questioned after another scribble. "If you don't have anyone, you're free to say so."
Ghen took a moment to think it over. A bunch of names went through his mind, but one stuck with him. "Tilik. He's just been accepted here, but he's learned quickly. Very attentive and he always catches something subtle. I think he'll do really well in my position, even better actually."
"Tilik, really?" Ryan questioned with a little shock, going through his completed forms. Ghen felt a short sense of panic in him. Did something happen, or was Tilik actually transferring? His answer didn't take long to reveal itself. "Right, Tilik was actually one of the first people to want to transfer here. He's actually requested to be part of the testing teams specifically. Do you have a second choice?"
"Um...no, actually." Ghen replied, feeling a little ashamed. "Tilik was my only choice, to be honest."
"Hey, don't worry." Ryan said assuringly with his hands raised. "Nothing wrong with that. Sometimes, there's just nobody up to snuff, right? 'Kay, so, last question. Is there anything specific you'd like to do when given the transfer?"
"If you need someone monitoring new pumps, I'd be happy to do that." Ghen stated.
"So basically same job but with better payoff, am I right?" Ryan grinned. "I hear you. Sometimes, we're just not paid enough for what we're doing. I know I think that sometimes. Uh, our secret, yeah?"
"Yeah, our secret." Ghen nodded, thinking it'd be better to have friendly relations with the human, just in case.
"Awesome. Back on topic, that's it." Ryan announced, placing the form on his pile. "We'll give you a call when you're accepted."
"Oh, uh, that's it?" Ghen questioned with a shrug in shocked surprise.
"What, expecting a question like, why do you want to transfer?" Ryan chuckled a bit as he leaned in his seat. "You can bullshit all you want, but we both know the answer. Sweet money and stock options. Not saying that's a bad answer of course, just that it's pretty obvious."
"I suppose it is." Ghen commented, realizing the point. "Also, you mentioned this...dividend? Is that for Zilia shares?"
Ryan laughed a little bit before nodding. "Yep, announced before I came here. About 0.43 per share. Want to know why that's awesome? Instead of waiting for the proper price to cash out your shares, now? The company pays you for each share you hold."
"A...Are you serious?" Ghen demanded, flabbergasted.
Ryan nodded with his now-trademark grin. "Dead serious. If you get the transfer, and get those 50,000 shares? A little head math...right, if you hold onto those, in addition to your salary, you'll now annually be paid 21,500 credits, if you keep it at 50,000 shares. Only you can decide to sell or buy shares."
Ghen just stood there silent and motionless, no idea of whether to believe it or not, to which Ryan just laughed. Once he walked out of the room, he managed to snap back to reality. Again, just focus on the very real pay-raise. He'll deal with the other parts later.
After he returned to his spot, he spotted Tizx approaching by his desk. The coordinator seems to be as casual as always.
"I saw you in that line a bit ago, Ghen." He said as he leaned on the desk. "Guess you're really taking that human's word?"
"I mean, I don't know about all this share business or what not." Ghen began with a shrug, his tone sounding a little defensive. "But I mean, having a bigger salary? Course I'm going for it when I can. And if all this magic credits turn out to be real? You realize we can live like the royal servants, right? Get the best cars, the nicest food and all that?"
"I'd be very careful, Ghen." Tizx warned in a sudden shift in tone. "Don't trust those humans. The way they just...obsess over money? Come up with more and more insane ways of getting credits? I don't know, it just makes my wings twitch."
"You think this is a bad idea?" Ghen asked with a little surprise at the change-in-demeanor.
"I think you should be careful, with the humans, and with what you're saying." Tizx replied, straightening his posture. "I wouldn't put it past those Earthmen to backstab you if it gets them a few more credits. And we all know how the royal servants get if any of us lowly commoners start thinking we can break into their circle."
"I hear you, I'll be on my guard, promise." Ghen stated with a nod. With a confirming nod of his own, Tizx returned back to his duty, walking past Ghen's desk.
Several weeks later.
Everything became so much better. Ghen got the transfer. He didn't need to relocate to a new residence either. And after he was walked through into learning how to manage his stock account, and seeing that new form of payment in his hands, he already felt as though he made the best decision. But it was only when he decided to take those shares more seriously that he became privy to what he was given. After receiving the dividend payment, and actually seeing it was real, valid credits after transferring it to his main bank account, all he could describe was the most powerful high he ever felt.
While his first thoughts were to buy himself a royalty-class car, some nicer furnishings for his home, or even a better home entirely, he ended up going the smarter route.
After going back to his stock account, he discovered that Zilia's shares rose to about 3.22 credits in price. Knowing that this was the easiest money he could ever make, he took all of his dividend earnings and bought more shares in Zilia, bringing him to owning 56,891.
And from his new regional coordinator, a human named Dylan, tomorrow is the grand release of the premium package. For just a monthly rate of 14.99 credits, the tap water will now include a sizeable portion of all nutrients and vitamins required in the zazk physiology. Still, Ghen has to admit. He's not entirely sure why anybody would want such a thing, if they'd even go for it. But, as long as he's practically swimming in easy credits, he won't pay much attention to it.
And just like when he was intensively studying the basics of how the human economy worked, he barely got any sleep. His mind was constantly thinking about the things he would buy. Or rather, what other stocks to put his credits into. Even now he can still hardly believe it. Just spend your money on some, make-believe thing and, if you wait long enough and picked the right stock, you'll get more than you spent back?
His mind even wandered onto what human colonies, or even their homeworld, Earth, was like. If everybody was making so much money, what kind of things would they offer? What kind of ridiculous service or product or item can you get? He's even debating on joining some forum and just asking around. Explain how he's new to how humans do things and was wondering what he should expect if he's successful.
By the time he felt like he can go to sleep, the binary-stars of the system were rising from the horizon. After getting out of his bed and changing to clean clothes, his mind returned onto what-ifs.
What if he bought better clothes? He's had his eye on that human brand of luxury clothes, Tessuti di Venezia, that's been all the rage amongst the royal servants. Or maybe he can go on vacation and just check out Earth for real?
It was a short ride to his workplace from his home. After getting stuff his stuff and preparing to walk through the doors, he heard the roar of a car grow louder. When he looked, he saw the sleekest and quite possibly the coolest looking car he's ever seen. Each time the engine revved it would startle him, both from how harsh it sounded as well as just how intense it sounded. And after it parked, he saw the doors pop out and then slide along the body back. And there, he saw Tilik, the seat literally turning and extending out a bit before he got off.
As soon as he saw Ghen staring, he struck a rather prideful pose after putting on his lab coat and then sauntered over to Ghen.
"What do you think?" Tilik said, without any doubt inviting praise or compliments.
"D...Did you actually buy that?" Ghen asked, unable to tear his eyes away from the car.
"You're Queens-damn right I did!" Tilik laughed happily. "Thing takes off like a starship, has temperature-controlled seating, all-in-one center console, barely any bouncing on rough roads. Hoof, best decision I've ever made!"
"How much did that thing cost?" Ghen asked after letting out an incredulous laugh.
"Five million credits." Tilik replied, earning an absolutely shocked stare from Ghen. "And thanks to the incredible salary I have, in addition to all these shares and dividends, I'll pay back the credits I borrowed in no time!"
Ghen needed a few moments before he could speak again. "All I've been doing is buying more shares."
Tilik laughed and then patted the now-envious monitor's back. "Smart man. I got a little carried away, yeah, but not anymore. Any spending credits I got, going right back to investing. That's what it's called right, investing?"
"Yeah, it is." Ghen nodded, feeling a fire light up in his thorax. "And also? Today's the day that the premium water thing is being released. Here's hoping it starts out well, right?"
"Oh it will, trust me." Tilik chuckled as they both began making their way inside the workplace. "Lots of research, lots of study. By the Queen, so much of it...it'll make your head spin."
And after hearing that, Ghen had a moment of realization. "Hey, Tilik? How did you get such a nice position anyways? Weren't you just studying under me before the humans came along?"
Tilik let out a sigh after opening the door. "I'll be honest, I never wanted your job. Not because it's boring or terrible, just...I didn't suffer so many sleepless nights in the science academy just to be a glorified button pusher. This is what I've always wanted. Doing science, solving problems rather than just applying the solution, you know?"
"Wait, you got an academic certificate?" Ghen questioned, completely floored. "How did you end up beneath me then? I should've been answering to you!"
"Simple." Tilik gave a heavier sigh. "A royal servant was asking for the same job I was. Take a guess at who got it."
"Ouch. Good thing the humans came along when they did, yeah?" Ghen was taken aback. He never heard anything about a servant taking a job at his place. "Looks like you're proving yourself to be well suited."
"By the Queen, of course I am." Tilik nodded. "Like I said, I nearly broke my wings through so many nights, got certified top of my class, all just to get pushed to the dirt because someone who was born into a particular family wanted the same thing I did? I know I'm smarter than any of those empty-skull servants back in the Center. I know that, whatever, uh...corporate? Yeah, whatever corporate wants out of science, I will xeek give it to them."
"Well, let me know how things go in the lab." Ghen said, admiring his drive as they neared the main office floor. "Because this is where the button pusher needs to go."
Tilik let out a laugh as he nodded. "Hey, how about we meet up at Queen's Fine Eatery tonight. I'll pay, yeah?"
Ghen, at first, wanted to admonish him for choosing such an outrageously expensive place to go. But he quickly realized that, he truly is good for it, thanks to the humans. "Well, hey, if you're paying for it."
...
It was a fantastic opening. After being told what news sites to keep in mind for stocks, he first heard it from Dylan, and then got more detail on Business Today. There was such a massive demand right from the start that Zilia needs to increase extraction just to meet it. But what really got his attention was the effect it had. Zilia Water Delivery's share price just blasted off. After seemingly holding steady at about 3.15, by the time he got home and logged onto his account, it already reached 7.04 a share. The calculator on his account told him that he got a value-gain of 54.26%.
Never in his entire life had he felt such...joy. With all of the shares he currently has? He's sitting at 400,512.64 credits. He knows that it is woefully pathetic compared to what the royal servants have just in their pockets, but the fact that he has such money, just by owning some intangible concept? Why even work at Zilia? Why doesn't he just sit at home, figure out what companies to invest in and make his money that way?
What's even the point in working a real job, getting a pathetic pay when you can just take the money you have, determine where to spend it, and get triple back? All just sitting on your wings at home, researching?
He was so wrapped up in his excited high that he completely forgot he was going to meet Tilik at Queen's. After quickly and haphazardly putting on his nicer clothes, he got to the place only a few minutes late.
Tilik was there by the guide, no doubt having been waiting for him. As soon as he strode up, Tilik's wings stiffned out some. No doubt he must've seen the numbers as well.
"I can see your wings, Ghen." Tilik began with an excited chuckle. "Made some serious credits?"
Ghen let out an incredulous scoff, struggling to find the words for a moment. "Incredible. All I'm going to say."
"Likewise." Tilik chortled some before nodding to the table guide. "All here. Table please?"
"Right this way, sir." The guide said politely. It was a short walk, travelling between round tables. The vast majority were populated by zazk, but Ghen was surprised at seeing a few humans here as well. No doubt corporate workers checking out the local food. He did spot them having bowls filled with some kind of mass. Some were brown, others white with what looks to be black specks on them.
They arrived at their table. A rather nice one, affording a view out the windows into the busy colony streets. Once Tilik and Ghen settled in, the guide handed out the menus.
"May I suggest our rather popular option for tonight?" The guide began. "Human ice-cream. Ingredients sourced from Earth itself. Very cold, but incredibly sweet, and coming in many flavors. The most popular amongst us is called vanilla-bean. The vanilla itself soaks in the cream for much of the process, and then the innards sprinkled on top of it near the end. Rumor has it that the Queen herself has demanded personal shipments of such a treat straight from the home of vanilla, an island on Earth named Madagascar."
Ghen didn't even spare a single thought. "Vanilla bean ice cream then, please."
"Same." Tilik seconded when the guide glanced to him. With a slight bow, the guide proceeded to ferry their orders to the kitchen. Thankfully it was just a short wait before the guide returned, carrying a large plate containing bowls of ice cream. Ghen could feel the saliva on his mandibles as the bowl was placed before them. He could just feel the cold air around that glistening mass of sugary goodness. The white snow decorated with the black dots of vanilla bean.
Once the guide left them, Tilik and Ghen both dived in at the same time. As soon as the ice cream entered his mouth, touched his tongue, he exploded in incomprehensible bliss. The sweetness, the smooth and creamy mass, even the taste of vanilla he wasn't sure about was just absolutely delightful. It was so overwhelming that his entire body limped, slumping in his seat as he was forced to ride on the surging tide of joy and happiness sweeping over him.
Tilik was no different. He too was taken completely by the effects of the ice cream, his wings fluttering some against the seat. Ghen could hear some noise. It was the humans they passed by. They were chuckling, grinning, and glancing over at them discreetly. Unlike the two zazk, the humans seemingly just enjoyed the ice cream as if it was just another nice dessert to them. Or perhaps they couldn't allow themselves to succumb to the high?
And as soon as the wave of indescribable bliss and happiness subsided, Ghen knew. He just knew. This was the life. He wanted this. The ice cream was just the beginning. So many things denied because he didn't have the credits, or worse, not the blood. Because he was just a drone in the great Collective, even if he had the credits, he wasn't allowed because of what caste he was born in. That fire that sparked in him when he saw Tilik's new car? It exploded into a raging firestorm.
And when looking into Tilik's eyes, Ghen could see the same. He was on the same page as Ghen was. Both of them were sold. They have the credits. And the humans? If you can pay for it, they'll never discriminate. All they cared about is if you have the money.
And by the Queen, Ghen and Tilik will endeavor to amass as much credits as physically possible.
The rest of the night faded into a blur. A blur that evokes only one thing. Bliss. It was only when he walked through the door of his pathetic hut that Ghen's mind snapped back to focus. His mandibles felt sticky. And he felt a weight in his stomach. How much ice cream did he eat? Whatever it was, he ate such volume that the lower-section of his throax extended and rounded out, visible even under his shirt. He felt something odd in his pocket. It was a receipt. 43,000 credits for ten bowls of vanilla bean ice cream. Was that ten bowls for both of them? Or individually? Ghen didn't care. He's good for it.
Returning back to his calculator, he acted upon the decision that he had made at that eatery. He's acquiring as many books about investing and stock trading as he could find, frequent and study all the discussions and arguments presented by other like-minded individuals such as he, all to ensure he can live the good life. And he had a very good feeling Tilik was doing the exact same thing.
Well, first, the gurgling in his stomach, as well as the feeling of something rising demanded his attention. Looks like he'll need to take the night off to let his stomach get back to normal.
Three Years Later.
Ghen looked out beyond the horizon, seeing the colony that he grew up in. On the far side was where his old house was. With only a simple robe on, made from the finest silk from Earth's nation-state of China, he relaxed in his seat.
It was a long road. Stockpiling credits from pre-existing investments and from subsequent pays, he and Tilik made it. From having only half a million in assets and cash, now transformed to over eight-hundred million. And now, his call contracts on American Interstellar? They've just announced a breakthrough in their next generation of warp drives, reducing the speed coefficient even further, resulting in far faster travel. And with that, their stock price climbed sharply.
Another hundred million credits in the bank. Soon, very soon, he and Tilik are about to become the galaxy's first zazk billionares. But that's not enough. There are many humans who are billionares. Only those he can count on one hand are considered trillionares. He's going to break into that circle. He and Tilik.
Looking beyond the colony, he saw the abandoned building of the workplace he transferred to when the humans arrived. Turns out, the reason for such a high demand was that the humans also slipped in sugar to the tap water. As soon as that broke, many influential royal servants demanded investigations and outright banning of Terran Galactic Company's influence over the former government division. Zilia's stock price plummeted. But thanks to an advance tip from his human coordinator, Dylan, he and Tilik made a put contract. And that's where they struck gold, as the human saying goes.
Dylan warned that if they were citizens of the United Nations, they'd be investigated and convicted for insider trading. But, since they weren't, and the Collective were only just introduced to capitalism, there's no risk at all. Now the colony is going through a withdrawal phase, Zilia has been dissolved and reformed back as a government division and are currently at work re-establishing the standard, plain water delivery.
"Well, shit." Tilik muttered as he walked up to Ghen's side, taking well to human speech. "Looks like you win. American Interstellar's announcement really was a good thing. There goes a million credits. Ah well, the Royal Shipyards will make it back for me soon."
"Oh? Did they just go corporate?" Ghen asked curiously, glancing to Tilik.
"Hell yeah they did." Tilik chuckled, sitting down. "Queen and her retard servants fought it hard, but Royal Shipyards is now officially a human-style corporation. And, to a surprise to all the xenophobes in the galaxy, they're already being offered contracts for ship production. That'll raise the stock price pretty good."
"What's that human word...?" Ghen muttered, already having a reply in mind. "Dick? Yeah, calls or suck my dick, Tilik."
Tilik roared in laughter. "Already made them. Forty credits a share by this day next month."
"I have half a mind to go thirty." Ghen chuckled. "Either way, until then, I heard from Dylan that he knows a guy who knows several prime human women who happen to be into zazk."
"You're interested in women?" Tilik said as his wings fluttered. "With how often you tell me to suck you off, I'd have thought differently."
"Oh, I always thought it was you who was into men." Ghen responded dryly. "Just wanted to be a good friend, you know? Considering how you never seem to make it past, Hey sweet thing, I'm rich you know."
"Oh, go fuck yourself." Tilik countered with a little laugh. After he stopped, wings stiffened, he looked to Ghen. "So, know any royal servants we can put the squeeze on for more revenue streams?"
"I got just the one." Ghen nodded, sitting up. "Fzik. He's been fighting to control the ice cream trade. Worried it's a corrupting influence. Got done talking with the human CEO of Nestle earlier. If we clear the way, he'll know how to squeeze a little more gains in stock price when he makes the announcement."
Tilik's wings stiffened even more, signaling his approval. "Alright, time to throw some credits around, yeah?"
AN: Sorry for the period of no updates. College is starting up, lots of stuff to clear and work out. Not sure why but I just got a bug up my butt about incorporating money and the stock market into a short. Here it is. Sorry if it seems abrupt, character limit fast approaching. Let me know how you guys think about it!
submitted by SynthoStellar to HFY [link] [comments]

No gods, no kings, only NOPE - or divining the future with options flows. [Part 3: Hedge Winding, Unwinding, and the NOPE]

Hello friends!
We're on the last post of this series ("A Gentle Introduction to NOPE"), where we get to use all the Big Boy Concepts (TM) we've discussed in the prior posts and put them all together. Some words before we begin:
  1. This post will be massively theoretical, in the sense that my own speculation and inferences will be largely peppered throughout the post. Are those speculations right? I think so, or I wouldn't be posting it, but they could also be incorrect.
  2. I will briefly touch on using the NOPE this slide, but I will make a secondary post with much more interesting data and trends I've observed. This is primarily for explaining what NOPE is and why it potentially works, and what it potentially measures.
My advice before reading this is to glance at my prior posts, and either read those fully or at least make sure you understand the tl;drs:
https://www.reddit.com/thecorporation/collection/27dc72ad-4e78-44cd-a788-811cd666e32a
Depending on popular demand, I will also make a last-last post called FAQ, where I'll tabulate interesting questions you guys ask me in the comments!
---
So a brief recap before we begin.
Market Maker ("Mr. MM"): An individual or firm who makes money off the exchange fees and bid-ask spread for an asset, while usually trying to stay neutral about the direction the asset moves.
Delta-gamma hedging: The process Mr. MM uses to stay neutral when selling you shitty OTM options, by buying/selling shares (usually) of the underlying as the price moves.
Law of Surprise [Lily-ism]: Effectively, the expected profit of an options trade is zero for both the seller and the buyer.
Random Walk: A special case of a deeper probability probability called a martingale, which basically models stocks or similar phenomena randomly moving every step they take (for stocks, roughly every millisecond). This is one of the most popular views of how stock prices move, especially on short timescales.
Future Expected Payoff Function [Lily-ism]: This is some hidden function that every market participant has about an asset, which more or less models all the possible future probabilities/values of the assets to arrive at a "fair market price". This is a more generalized case of a pricing model like Black-Scholes, or DCF.
Counter-party: The opposite side of your trade (if you sell an option, they buy it; if you buy an option, they sell it).
Price decoherence ]Lily-ism]: A more generalized notion of IV Crush, price decoherence happens when instead of the FEPF changing gradually over time (price formation), the FEPF rapidly changes, due usually to new information being added to the system (e.g. Vermin Supreme winning the 2020 election).
---
One of the most popular gambling events for option traders to play is earnings announcements, and I do owe the concept of NOPE to hypothesizing specifically about the behavior of stock prices at earnings. Much like a black hole in quantum mechanics, most conventional theories about how price should work rapidly break down briefly before, during, and after ER, and generally experienced traders tend to shy away from playing earnings, given their similar unpredictability.
Before we start: what is NOPE? NOPE is a funny backronym from Net Options Pricing Effect, which in its most basic sense, measures the impact option delta has on the underlying price, as compared to share price. When I first started investigating NOPE, I called it OPE (options pricing effect), but NOPE sounds funnier.
The formula for it is dead simple, but I also have no idea how to do LaTeX on reddit, so this is the best I have:

https://preview.redd.it/ais37icfkwt51.png?width=826&format=png&auto=webp&s=3feb6960f15a336fa678e945d93b399a8e59bb49
Since I've already encountered this, put delta in this case is the absolute value (50 delta) to represent a put. If you represent put delta as a negative (the conventional way), do not subtract it; add it.
To keep this simple for the non-mathematically minded: the NOPE today is equal to the weighted sum (weighted by volume) of the delta of every call minus the delta of every put for all options chains extending from today to infinity. Finally, we then divide that number by the # of shares traded today in the market session (ignoring pre-market and post-market, since options cannot trade during those times).
Effectively, NOPE is a rough and dirty way to approximate the impact of delta-gamma hedging as a function of share volume, with us hand-waving the following factors:
  1. To keep calculations simple, we assume that all counter-parties are hedged. This is obviously not true, especially for idiots who believe theta ganging is safe, but holds largely true especially for highly liquid tickers, or tickers will designated market makers (e.g. any ticker in the NASDAQ, for instance).
  2. We assume that all hedging takes place via shares. For SPY and other products tracking the S&P, for instance, market makers can actually hedge via futures or other options. This has the benefit for large positions of not moving the underlying price, but still makes up a fairly small amount of hedges compared to shares.

Winding and Unwinding

I briefly touched on this in a past post, but two properties of NOPE seem to apply well to EER-like behavior (aka any binary catalyst event):
  1. NOPE measures sentiment - In general, the options market is seen as better informed than share traders (e.g. insiders trade via options, because of leverage + easier to mask positions). Therefore, a heavy call/put skew is usually seen as a bullish sign, while the reverse is also true.
  2. NOPE measures system stability
I'm not going to one-sentence explain #2, because why say in one sentence what I can write 1000 words on. In short, NOPE intends to measure sensitivity of the system (the ticker) to disruption. This makes sense, when you view it in the context of delta-gamma hedging. When we assume all counter-parties are hedged, this means an absolutely massive amount of shares get sold/purchased when the underlying price moves. This is because of the following:
a) Assume I, Mr. MM sell 1000 call options for NKLA 25C 10/23 and 300 put options for NKLA 15p 10/23. I'm just going to make up deltas because it's too much effort to calculate them - 30 delta call, 20 delta put.
This implies Mr. MM needs the following to delta hedge: (1000 call options * 30 shares to buy for each) [to balance out writing calls) - (300 put options * 20 shares to sell for each) = 24,000 net shares Mr. MM needs to acquire to balance out his deltas/be fully neutral.
b) This works well when NKLA is at $20. But what about when it hits $19 (because it only can go down, just like their trucks). Thanks to gamma, now we have to recompute the deltas, because they've changed for both the calls (they went down) and for the puts (they went up).
Let's say to keep it simple that now my calls are 20 delta, and my puts are 30 delta. From the 24,000 net shares, Mr. MM has to now have:
(1000 call options * 20 shares to have for each) - (300 put options * 30 shares to sell for each) = 11,000 shares.
Therefore, with a $1 shift in price, now to hedge and be indifferent to direction, Mr. MM has to go from 24,000 shares to 11,000 shares, meaning he has to sell 13,000 shares ASAP, or take on increased risk. Now, you might be saying, "13,000 shares seems small. How would this disrupt the system?"
(This process, by the way, is called hedge unwinding)
It won't, in this example. But across thousands of MMs and millions of contracts, this can - especially in highly optioned tickers - make up a substantial fraction of the net flow of shares per day. And as we know from our desk example, the buying or selling of shares directly changes the price of the stock itself.
This, by the way, is why the NOPE formula takes the shape it does. Some astute readers might notice it looks similar to GEX, which is not a coincidence. GEX however replaces daily volume with open interest, and measures gamma over delta, which I did not find good statistical evidence to support, especially for earnings.
So, with our example above, why does NOPE measure system stability? We can assume for argument's sake that if someone buys a share of NKLA, they're fine with moderate price swings (+- $20 since it's NKLA, obviously), and in it for the long/medium haul. And in most cases this is fine - we can own stock and not worry about minor swings in price. But market makers can't* (they can, but it exposes them to risk), because of how delta works. In fact, for most institutional market makers, they have clearly defined delta limits by end of day, and even small price changes require them to rebalance their hedges.
This over the whole market adds up to a lot shares moving, just to balance out your stupid Robinhood YOLOs. While there are some tricks (dark pools, block trades) to not impact the price of the underlying, the reality is that the more options contracts there are on a ticker, the more outsized influence it will have on the ticker's price. This can technically be exactly balanced, if option put delta is equal to option call delta, but never actually ends up being the case. And unlike shares traded, the shares representing the options are more unstable, meaning they will be sold/bought in response to small price shifts. And will end up magnifying those price shifts, accordingly.

NOPE and Earnings

So we have a new shiny indicator, NOPE. What does it actually mean and do?
There's much literature going back to the 1980s that options markets do have some level of predictiveness towards earnings, which makes sense intuitively. Unlike shares markets, where you can continue to hold your share even if it dips 5%, in options you get access to expanded opportunity to make riches... and losses. An options trader betting on earnings is making a risky and therefore informed bet that he or she knows the outcome, versus a share trader who might be comfortable bagholding in the worst case scenario.
As I've mentioned largely in comments on my prior posts, earnings is a special case because, unlike popular misconceptions, stocks do not go up and down solely due to analyst expectations being meet, beat, or missed. In fact, stock prices move according to the consensus market expectation, which is a function of all the participants' FEPF on that ticker. This is why the price moves so dramatically - even if a stock beats, it might not beat enough to justify the high price tag (FSLY); even if a stock misses, it might have spectacular guidance or maybe the market just was assuming it would go bankrupt instead.
To look at the impact of NOPE and why it may play a role in post-earnings-announcement immediate price moves, let's review the following cases:
  1. Stock Meets/Exceeds Market Expectations (aka price goes up) - In the general case, we would anticipate post-ER market participants value the stock at a higher price, pushing it up rapidly. If there's a high absolute value of NOPE on said ticker, this should end up magnifying the positive move since:
a) If NOPE is high negative - This means a ton of put buying, which means a lot of those puts are now worthless (due to price decoherence). This means that to stay delta neutral, market makers need to close out their sold/shorted shares, buying them, and pushing the stock price up.
b) If NOPE is high positive - This means a ton of call buying, which means a lot of puts are now worthless (see a) but also a lot of calls are now worth more. This means that to stay delta neutral, market makers need to close out their sold/shorted shares AND also buy more shares to cover their calls, pushing the stock price up.
2) Stock Meets/Misses Market Expectations (aka price goes down) - Inversely to what I mentioned above, this should push to the stock price down, fairly immediately. If there's a high absolute value of NOPE on said ticker, this should end up magnifying the negative move since:
a) If NOPE is high negative - This means a ton of put buying, which means a lot of those puts are now worth more, and a lot of calls are now worth less/worth less (due to price decoherence). This means that to stay delta neutral, market makers need to sell/short more shares, pushing the stock price down.
b) If NOPE is high positive - This means a ton of call buying, which means a lot of calls are now worthless (see a) but also a lot of puts are now worth more. This means that to stay delta neutral, market makers need to sell even more shares to keep their calls and puts neutral, pushing the stock price down.
---
Based on the above two cases, it should be a bit more clear why NOPE is a measure of sensitivity to system perturbation. While we previously discussed it in the context of magnifying directional move, the truth is it also provides a directional bias to our "random" walk. This is because given a price move in the direction predicted by NOPE, we expect it to be magnified, especially in situations of price decoherence. If a stock price goes up right after an ER report drops, even based on one participant deciding to value the stock higher, this provides a runaway reaction which boosts the stock price (due to hedging factors as well as other participants' behavior) and inures it to drops.

NOPE and NOPE_MAD

I'm going to gloss over this section because this is more statistical methods than anything interesting. In general, if you have enough data, I recommend using NOPE_MAD over NOPE. While NOPE in theory represents a "real" quantity (net option delta over net share delta), NOPE_MAD (the median absolute deviation of NOPE) does not. NOPE_MAD simply answecompare the following:
  1. How exceptional is today's NOPE versus historic baseline (30 days prior)?
  2. How do I compare two tickers' NOPEs effectively (since some tickers, like TSLA, have a baseline positive NOPE, because Elon memes)? In the initial stages, we used just a straight numerical threshold (let's say NOPE >= 20), but that quickly broke down. NOPE_MAD aims to detect anomalies, because anomalies in general give you tendies.
I might add the formula later in Mathenese, but simply put, to find NOPE_MAD you do the following:
  1. Calculate today's NOPE score (this can be done end of day or intraday, with the true value being EOD of course)
  2. Calculate the end of day NOPE scores on the ticker for the previous 30 trading days
  3. Compute the median of the previous 30 trading days' NOPEs
  4. From the median, find the 30 days' median absolute deviation (https://en.wikipedia.org/wiki/Median_absolute_deviation)
  5. Find today's deviation as compared to the MAD calculated by: [(today's NOPE) - (median NOPE of last 30 days)] / (median absolute deviation of last 30 days)
This is usually reported as sigma (σ), and has a few interesting properties:
  1. The mean of NOPE_MAD for any ticker is almost exactly 0.
  2. [Lily's Speculation's Speculation] NOPE_MAD acts like a spring, and has a tendency to reverse direction as a function of its magnitude. No proof on this yet, but exploring it!

Using the NOPE to predict ER

So the last section was a lot of words and theory, and a lot of what I'm mentioning here is empirically derived (aka I've tested it out, versus just blabbered).
In general, the following holds true:
  1. 3 sigma NOPE_MAD tends to be "the threshold": For very low NOPE_MAD magnitudes (+- 1 sigma), it's effectively just noise, and directionality prediction is low, if not non-existent. It's not exactly like 3 sigma is a play and 2.9 sigma is not a play; NOPE_MAD accuracy increases as NOPE_MAD magnitude (either positive or negative) increases.
  2. NOPE_MAD is only useful on highly optioned tickers: In general, I introduce another parameter for sifting through "candidate" ERs to play: option volume * 100/share volume. When this ends up over let's say 0.4, NOPE_MAD provides a fairly good window into predicting earnings behavior.
  3. NOPE_MAD only predicts during the after-market/pre-market session: I also have no idea if this is true, but my hunch is that next day behavior is mostly random and driven by market movement versus earnings behavior. NOPE_MAD for now only predicts direction of price movements right between the release of the ER report (AH or PM) and the ending of that market session. This is why in general I recommend playing shares, not options for ER (since you can sell during the AH/PM).
  4. NOPE_MAD only predicts direction of price movement: This isn't exactly true, but it's all I feel comfortable stating given the data I have. On observation of ~2700 data points of ER-ticker events since Mar 2019 (SPY 500), I only so far feel comfortable predicting whether stock price goes up (>0 percent difference) or down (<0 price difference). This is +1 for why I usually play with shares.
Some statistics:
#0) As a baseline/null hypothesis, after ER on the SPY500 since Mar 2019, 50-51% price movements in the AH/PM are positive (>0) and ~46-47% are negative (<0).
#1) For NOPE_MAD >= +3 sigma, roughly 68% of price movements are positive after earnings.
#2) For NOPE_MAD <= -3 sigma, roughly 29% of price movements are positive after earnings.
#3) When using a logistic model of only data including NOPE_MAD >= +3 sigma or NOPE_MAD <= -3 sigma, and option/share vol >= 0.4 (around 25% of all ERs observed), I was able to achieve 78% predictive accuracy on direction.

Caveats/Read This

Like all models, NOPE is wrong, but perhaps useful. It's also fairly new (I started working on it around early August 2020), and in fact, my initial hypothesis was exactly incorrect (I thought the opposite would happen, actually). Similarly, as commenters have pointed out, the timeline of data I'm using is fairly compressed (since Mar 2019), and trends and models do change. In fact, I've noticed significantly lower accuracy since the coronavirus recession (when I measured it in early September), but I attribute this mostly to a smaller date range, more market volatility, and honestly, dumber option traders (~65% accuracy versus nearly 80%).
My advice so far if you do play ER with the NOPE method is to use it as following:
  1. Buy/short shares approximately right when the market closes before ER. Ideally even buying it right before the earnings report drops in the AH session is not a bad idea if you can.
  2. Sell/buy to close said shares at the first sign of major weakness (e.g. if the NOPE predicted outcome is incorrect).
  3. Sell/buy to close shares even if it is correct ideally before conference call, or by the end of the after-market/pre-market session.
  4. Only play tickers with high NOPE as well as high option/share vol.
---
In my next post, which may be in a few days, I'll talk about potential use cases for SPY and intraday trends, but I wanted to make sure this wasn't like 7000 words by itself.
Cheers.
- Lily
submitted by the_lilypad to thecorporation [link] [comments]

New to deep learning, trying to understand how to approach a network I have in mind

Hey all! I've been fascinated with machine/deep learning for years now, and am finally taking my first steps into this world. I want to take a stab at creating a stock trading AI, and came across this fantastic article that outlines one approach. The goal of the network described in the article is to predict the price on a day-to-day basis, which seems like an obvious starting point. It uses a LSTM network as the generator in a GAN. The first image in the article outlines how the approach is structured.
The thing is, I'm not very interested in predicting the stock price. My ideal system would instead output a "conviction" value for a variety of financial instruments. These would include holding cash, stocks, and options (both calls and puts, likely with a variety of strike prices and time horizons). A higher value would represent a stronger conviction that holding that financial instrument would be more profitable than not. The network would not be optimizing for raw numerical accuracy, but profitability. There would be non-machine learning based logic that translates the conviction values into actions (buy/sell/hold), with the outcome of those actions determining profitability.
An example of the conviction values it might return for a given day are as follows:
If I look at this, it tells me that the network thinks the stock is more likely to go up than not (stock and calls having higher percentages than cash and puts), but that it thinks there's enough of a chance it'll go down that buying some puts to hedge is worth their loss in value if it goes up instead. What to do with this information will depend on each person individually, but let's assume the action logic is pretty basic and allocates the funds proportionally based on the percentages. One note: the percentages don't have to add up to 100%. If it is 100% convinced the stock will go up, the conviction for both stock and calls would be 100%, while cash and puts would be 0%. In that case, with this super naive logic, it would split funds 50/50 between stocks and calls.
That leads me to my question: what would you use as the baseline-truth that the LSTM generator output gets compared to in the discriminator? With stock price it's obviously just the real stock price, but when we're talking about profitability across several financial instruments it's less so. My first thought is to use a 0/1 value based on whether or not holding that instrument through the next day was actually profitable, but it's important to me that the conviction value isn't just a binary YES/NO. I'm not familiar enough with GANs to know if it's possible to have it optimize towards an answer that doesn't necessarily match the baseline-truth it's being discriminated against. My gut reaction based on the little I know tells me it wouldn't be possible. I'm also not familiar enough with deep learning generally to know if another training methodology would be more appropriate in my situation.
How would you approach this?
EDIT: Been mulling this over a bit more and realized that I need to nail down what my ideal end result would be. I said I'd want it to optimize for profit, which means that I would need to calculate the maximum potential profit for each day and use that value as the baseline-truth that the results from the LSTM generator gets compared to. So, we can imagine a day where the stock went up 2%. If going all in on calls would result in $1 more in profit compared to going all in on stock, the maximum potential profit value for that day would be based on going 100% in on calls and 0% in on stocks. As a result, the perfectly optimal conviction values from the LSTM generator would be:
Now, the chance of making a model that predicts/matches this perfectly in a situation where you'd make $1 more going all in on calls is essentially 0. The next best case scenario is the generator acknowledging the fact that it can't predict it perfectly by giving calls a much lower weight and shares a higher weight (the reason being, calls generally lose value every single day you hold them if all else is equal and the price doesn't change). During training, it will run into situations like I described above where there's almost equal profit potential from holding stocks and calls. When it makes the wrong judgement call and says that going all in on calls is the way to go when stocks were actually better, the discrepancy in profit will be higher since the calls actually lost value. Over the training period, it should learn that it needs to be more conservative and allocate more funds to stocks in those situations. In other situations when it's REALLY sure the stock will go up, it will learn that it's safemore profitable to prioritize calls over stock.
Actually, instead of calculating an actual dollar value and using that as the base-line truth, it should be enough to instead choose one financial instrument to have a conviction value of 1 for that day (representing that it's the most profitable instrument), while all the others get a value of 0. This is different to what I said in my original post, which was that I would set the conviction value for each instrument that would produce some profit to 1. In that situation the sum of the convictions could very well be over 100%; whereas, if only one instrument is given a value of 1 in the baseline-truth data, the sum of the conviction values should be close to 100%.
Now that I've written that out, I feel like I have a clearer path forward. If anything I said sounds wrong, please let me know. It's based off of assumptions I'm making about how GANs work, without having any real experience with them.
submitted by EdvardDashD to MLQuestions [link] [comments]

New to deep learning, trying to understand how to approach a network I have in mind

Hey all! I've been fascinated with machine/deep learning for years now, and am finally taking my first steps into this world. I want to take a stab at creating a stock trading AI, and came across this fantastic article that outlines one approach. The goal of the network described in the article is to predict the price on a day-to-day basis, which seems like an obvious starting point. It uses a LSTM network as the generator in a GAN. The first image in the article outlines how the approach is structured.
The thing is, I'm not very interested in predicting the stock price. My ideal system would instead output a "conviction" value for a variety of financial instruments. These would include holding cash, stocks, and options (both calls and puts, likely with a variety of strike prices and time horizons). A higher value would represent a stronger conviction that holding that financial instrument would be more profitable than not. The network would not be optimizing for raw numerical accuracy, but profitability. There would be non-machine learning based logic that translates the conviction values into actions (buy/sell/hold), with the outcome of those actions determining profitability.
An example of the conviction values it might return for a given day are as follows:
If I look at this, it tells me that the network thinks the stock is more likely to go up than not (stock and calls having higher percentages than cash and puts), but that it thinks there's enough of a chance it'll go down that buying some puts to hedge is worth their loss in value if it goes up instead. What to do with this information will depend on each person individually, but let's assume the action logic is pretty basic and allocates the funds proportionally based on the percentages. One note: the percentages don't have to add up to 100%. If it is 100% convinced the stock will go up, the conviction for both stock and calls would be 100%, while cash and puts would be 0%. In that case, with this super naive logic, it would split funds 50/50 between stocks and calls.
That leads me to my question: what would you use as the baseline-truth that the LSTM generator output gets compared to in the discriminator? With stock price it's obviously just the real stock price, but when we're talking about profitability across several financial instruments it's less so. My first thought is to use a 0/1 value based on whether or not holding that instrument through the next day was actually profitable, but it's important to me that the conviction value isn't just a binary YES/NO. I'm not familiar enough with GANs to know if it's possible to have it optimize towards an answer that doesn't necessarily match the baseline-truth it's being discriminated against. My gut reaction based on the little I know tells me it wouldn't be possible. I'm also not familiar enough with deep learning generally to know if another training methodology would be more appropriate in my situation.
How would you approach this?
EDIT: Been mulling this over a bit more and realized that I need to nail down what my ideal end result would be. I said I'd want it to optimize for profit, which means that I would need to calculate the maximum potential profit for each day and use that value as the baseline-truth that the results from the LSTM generator gets compared to. So, we can imagine a day where the stock went up 2%. If going all in on calls would result in $1 more in profit compared to going all in on stock, the maximum potential profit value for that day would be based on going 100% in on calls and 0% in on stocks. As a result, the perfectly optimal conviction values from the LSTM generator would be:
Now, the chance of making a model that predicts/matches this perfectly in a situation where you'd make $1 more going all in on calls is essentially 0. The next best case scenario is the generator acknowledging the fact that it can't predict it perfectly by giving calls a much lower weight and shares a higher weight (the reason being, calls generally lose value every single day you hold them if all else is equal and the price doesn't change). During training, it will run into situations like I described above where there's almost equal profit potential from holding stocks and calls. When it makes the wrong judgement call and says that going all in on calls is the way to go when stocks were actually better, the discrepancy in profit will be higher since the calls actually lost value. Over the training period, it should learn that it needs to be more conservative and allocate more funds to stocks in those situations. In other situations when it's REALLY sure the stock will go up, it will learn that it's safemore profitable to prioritize calls over stock.
Actually, instead of calculating an actual dollar value and using that as the base-line truth, it should be enough to instead choose one financial instrument to have a conviction value of 1 for that day (representing that it's the most profitable instrument), while all the others get a value of 0. This is different to what I said in my original post, which was that I would set the conviction value for each instrument that would produce some profit to 1. In that situation the sum of the convictions could very well be over 100%; whereas, if only one instrument is given a value of 1 in the baseline-truth data, the sum of the conviction values should be close to 100%.
Now that I've written that out, I feel like I have a clearer path forward. If anything I said sounds wrong, please let me know. It's based off of assumptions I'm making about how GANs work, without having any real experience with them.
submitted by EdvardDashD to learnmachinelearning [link] [comments]

TMC5041: Dual stepper motor *controller*

This is a magic box. You send it either a location or a velocity (via SPI), and it manages _everything_. Computes and controls lovely velocity curves. Works hard to avoid step loss. Runs your steppers "silently". All of this without your uC wasting time calculating and banging STEP/DIR pins like a caveperson.
https://www.trinamic.com/products/integrated-circuits/details/tmc5041-la/
The 5041 can drive 5-26V and 2x 1.1A with no additional FETs. It's the dual driver P/N, though they also have other options in the family for single and/or higher amperage. I'd start with this one because there's a 5041-BOB available on Digikey ($19).
The upsides are hard to overstate. The downsides are... nontrivial. First, it's too expensive to use for most consumer products- lowest price is around $4.50. There are no knockoff, drop-in substitutes I've found.
Second, you have to learn the datasheet. For real. There are a lot of config registers, all need to be set, many of the settings need to be calculated in relation to others beforehand, many of the modes are incompatible despite being on different bits so they can be set simultaneously. It is a mess. They included a couple of flowcharts, but... someone needs to build a calculator for this with a nice UI. Their examples are misleading (though they work) because they've chosen to write the config registers in hex, and the bits that need to be set don't line up with the 4-bit hex blocks... so a setting will have it's high bit and low bit broken across two hex chars. If you choose to use this IC, you will be much better off writing them out in binary.
I started writing a library for this to make it easier, but didn't finish it. Lmk if you want to make a go of it: https://hackaday.io/project/158935-haroco-the-designlab/log/149276-fancy-stepper-motor-controller-update
In contrast to the last two posts, this IC is not cheap. It is not easy to use. But it *is* a fundamental improvement to how you've used stepper motors before.
submitted by jenesaisdiq to nicechips [link] [comments]

New to deep learning, trying to understand how to approach a network I have in mind

Hey all! I've been fascinated with machine/deep learning for years now, and am finally taking my first steps into this world. I want to take a stab at creating a stock trading AI, and came across this fantastic article that outlines one approach. The goal of the network described in the article is to predict the price on a day-to-day basis, which seems like an obvious starting point. It uses a LSTM network as the generator in a GAN. The first image in the article outlines how the approach is structured.
The thing is, I'm not very interested in predicting the stock price. My ideal system would instead output a "conviction" value for a variety of financial instruments. These would include holding cash, stocks, and options (both calls and puts, likely with a variety of strike prices and time horizons). A higher value would represent a stronger conviction that holding that financial instrument would be more profitable than not. The network would not be optimizing for raw numerical accuracy, but profitability. There would be non-machine learning based logic that translates the conviction values into actions (buy/sell/hold), with the outcome of those actions determining profitability.
An example of the conviction values it might return for a given day are as follows:
If I look at this, it tells me that the network thinks the stock is more likely to go up than not (stock and calls having higher percentages than cash and puts), but that it thinks there's enough of a chance it'll go down that buying some puts to hedge is worth their loss in value if it goes up instead. What to do with this information will depend on each person individually, but let's assume the action logic is pretty basic and allocates the funds proportionally based on the percentages. One note: the percentages don't have to add up to 100%. If it is 100% convinced the stock will go up, the conviction for both stock and calls would be 100%, while cash and puts would be 0%. In that case, with this super naive logic, it would split funds 50/50 between stocks and calls.
That leads me to my question: what would you use as the baseline-truth that the LSTM generator output gets compared to in the discriminator? With stock price it's obviously just the real stock price, but when we're talking about profitability across several financial instruments it's less so. My first thought is to use a 0/1 value based on whether or not holding that instrument through the next day was actually profitable, but it's important to me that the conviction value isn't just a binary YES/NO. I'm not familiar enough with GANs to know if it's possible to have it optimize towards an answer that doesn't necessarily match the baseline-truth it's being discriminated against. My gut reaction based on the little I know tells me it wouldn't be possible. I'm also not familiar enough with deep learning generally to know if another training methodology would be more appropriate in my situation.
How would you approach this?
EDIT: Been mulling this over a bit more and realized that I need to nail down what my ideal end result would be. I said I'd want it to optimize for profit, which means that I would need to calculate the maximum potential profit for each day and use that value as the baseline-truth that the results from the LSTM generator gets compared to. So, we can imagine a day where the stock went up 2%. If going all in on calls would result in $1 more in profit compared to going all in on stock, the maximum potential profit value for that day would be based on going 100% in on calls and 0% in on stocks. As a result, the perfectly optimal conviction values from the LSTM generator would be:
Now, the chance of making a model that predicts/matches this perfectly in a situation where you'd make $1 more going all in on calls is essentially 0. The next best case scenario is the generator acknowledging the fact that it can't predict it perfectly by giving calls a much lower weight and shares a higher weight (the reason being, calls generally lose value every single day you hold them if all else is equal and the price doesn't change). During training, it will run into situations like I described above where there's almost equal profit potential from holding stocks and calls. When it makes the wrong judgement call and says that going all in on calls is the way to go when stocks were actually better, the discrepancy in profit will be higher since the calls actually lost value. Over the training period, it should learn that it needs to be more conservative and allocate more funds to stocks in those situations. In other situations when it's REALLY sure the stock will go up, it will learn that it's safemore profitable to prioritize calls over stock.
Actually, instead of calculating an actual dollar value and using that as the base-line truth, it should be enough to instead choose one financial instrument to have a conviction value of 1 for that day (representing that it's the most profitable instrument), while all the others get a value of 0. This is different to what I said in my original post, which was that I would set the conviction value for each instrument that would produce some profit to 1. In that situation the sum of the convictions could very well be over 100%; whereas, if only one instrument is given a value of 1 in the baseline-truth data, the sum of the conviction values should be close to 100%.
Now that I've written that out, I feel like I have a clearer path forward. If anything I said sounds wrong, please let me know. It's based off of assumptions I'm making about how GANs work, without having any real experience with them.
submitted by EdvardDashD to deeplearning [link] [comments]

OBLIGATORY FILLER MATERIAL – Breaking Bad, Part 3

Continuing
“Hello and good day, gentlemen”, I say. “I am Doctor Rocknocker. You may and will refer to me as ‘Rock’. OK? None of this ‘Doctor’ or ‘Sir’ guff. We green here?”
There was a buzz of voices but no direct answers.
“OK. Let’s get a few things down right here and now.
(1.) Call me Rock.
(b.) Answer me loudly. I will need to hear you loud and clear. Best get used to that now.
(iii.) “We green?” means “Are we in agreement?” It’s a form of shorthand I use here and in the field.
(⍾.) “You diggin’ me, Beaumont? means you’ve really done gone and pissed me off; you’ve done something untoward. Pray you never hear that phrase, and,
(∞.) I’m the boss. The top dog. The hookin’ bull. The Maharaja here. I possess the first, final and only words you’re going to listen to for the next couple of weeks. What I say, goes. Any problem, please let me know now so we can replace you most quickly.”
A gentle buzz, but no replies.
“Gentlemen. Do we agree?” I ask.
“Yes, Rock.” Was the reply.
OK, there might be some form of a societal prohibition against making loud noises. That’s the first thing that has to go.
“Gentlemen, we will be working in the great outdoors where there are wind, rain, waves, and other environmental nonsense making all sorts of unrequited noise. We need clear and proper lines of communication. I need to hear you clearly and vice-versa. When speaking, you will speak slowly, clearly, and loudly. “
DO WE AGREE!?!” I yell, rather deafeningly.
“YES, ROCK!” came the eventual reply.
“Outstanding”. I ponder.
Continuing…
“Mr. Sanjay is my de facto second in command. If I’m out having a smoke, taking a piss, or having a snort, he’s in charge. Listen to him as if I suddenly lost 150 pounds, shaved my beard, and inexplicably become Indian.” I chuckled.
They seemed to enjoy that. I actually elicited a few chuckles.
“Mr. Sanjay will now distribute to you your locker boxes. You will wait until he hands you yours. Do not get up and mill around the room. We green?” I ask.
“Green! Doctor Rock.” Came the noisy reply.
“Progress. Marvelous.”, I reflect.
“I’ll be right back. Mr. Sanjay, the room is yours.” I note. I might need to cut back on the coffee.
I slope off to the loo and it’s just as horrible as you can imagine an outdoor communal shithouse in sunny India attended by 30,000 Indian gentlemen could be.
Fuck COVID-19. I’m thinking hot and cold running dysentery, dengue, and death here. Ick.
Glad I have a highly functioning immune system.
I retrieve a shiny aluminum Halliburton™ case from Headquarters and ease off to an unused office space to change.
I went from my usual field garb to full PPEs. It was quite a sight.
I’ll be telling you about it in mere moments. Contain the excitement.
I’m walking back to Outbuilding #2 and damned if my get-up didn’t elicit a few gasps, shielded guffaws, and a salute or two. I have to admit, to the uninitiated, I was a sight right out of Area 52, the more secret one, west by northeast of Roswell, New Mexico.
I get back to the outbuilding and enter. Everyone was looking through their locker boxes, chuckling about their good fortune and wondering with Joker-like glee what the hell all these wonderful gizmos were and where did I get them? They all stopped dead in their tracks when I walked in.
Their silence was palpable.
“Gentlemen”, I said, “Here’s how you are going to look at work tomorrow. Revel in its utility, comfort, and extreme fashion sense.” I did a quick spin like I used to on the runway.
At O’Hare when we were doing field geostatic tests. Whatever were you thinking?
Anyways…
I was wearing a pair of size 66-XTall NFPA 70E blaze orange Carhartt Nomex coveralls. I had on a Dax carbon-fiber blaze orange “Coal Scuttle” hardhat with swing-away hearing protection keyed into your personal communications module, and a gold-anodized, pull-down full face shield. The helmet was designed to drain away falling water down over one’s back and not down one’s neck.
I had a pair of ‘wet’ gloves under the snap retainer on my left shoulder, a pair of ‘dry’ gloves on my right. I was wearing an orange CMC Safety 9-point safety and rescue harness, good to well over 1,500 pounds. Over both shoulders, around the crotch, up the front, and around the back, X-style. This popular harness features multiple D-ring attachment points and the patented JackBack removable padding with breathable D-3 cloth, which keeps shoulder straps separated and makes donning and doffing a breeze. It had several catch-points where one could easily and readily attach to the snap carabiners and get bodily dragged out of a nasty situation by rope or chain. The front waist D-ring allows a comfortable, stable sitting position for rappels and the sternum D-ring works well for helicopter or crane-assist hoists. Gear loops offer easy access to equipment, and quick-connect-disconnect shoulder straps and leg loops make the harness quick to don or doff. It could be used for impromptu spelunking on days off.
I had on Size 16 EEE Gear Box 8088 Men's 8 inch Black Leather intrinsically-safe hard-toed lace-up black turned-heel leather work boots with the new self-cleaning, oil-and chemical resistant Vibram soles.
They couldn’t see, but I was also wearing a cotton-Nomex blend wifebeater and boxers as well. Nomex tends to chafe. Best be safe.
I had a powerful Maglite flashlight clipped to my rescue harness, as well as my mini Air Horn; a blaster’s must. I also had a mobile VHF-Commslink™ radio in a pocket on the back of my coveralls on the left shoulder. I had the microphone for it Velcro-ed to my rescue harness within easy reach. Very cop like. Very cool. Very necessary.
I had a traditional Zippo and Bic Butane lighters in my right-hand chest pocket and a brace of cigars, though these were optional, in my left pocket. I carried a bespoke constructed Swiss Army Knife on a lanyard in my right front pocket and had a custom Bears Paw Leatherman hanging on the left of my rescue harness.
Also clipped to the harness was a Silva orienteering compass. There was a selection of NASA write anywhere pens, Sharpies, and oil-writing chalk pencils in my other front pockets. I had an oil industry tally book in my other front pocket.
Why blaze orange? Well, Red Adair already co-opted bright red, and fluorescent green wasn’t available in my size.
So, we’re now ready to plant explosives in West India or go deer hunting in the Northwoods of Baja Canada.
“Questions, Gentlemen?” I asked.
I explained that in their locker boxes were purchase orders, POs, for every bit of kit I was wearing. They were to take these POs to the Company Store and get, well, kitted out in their own sizes and preferences. I wanted to see everyone back here tomorrow at 1300 hours looking as I do now. Well, maybe skip the cigar and be not quite so large.
I sat down on the table in front of the crowd and had Sanjay bring over the demo locker box.
“OK, gents,” I said, “This locker box is yours and is numbered as such. They will be stored here in Outbuilding #2. Each of you will receive a key for this building as it is now your headquarters. We’ll get back to locker boxes in a minute. Anyone need a break for a few minutes?” I asked.
No one dared answer at this magical juncture in the narrative.
“Well, I do”, I said, “Meet back here in twenty minutes. Sanjay?”
The class wandered out and I conversed with Sanjay. We found the maps I had ordered.
They were an aerial view of the breaking yard and it was split into 6 zones, all a different color. There was one master for the wall and 28 copies for the guys. I also had a log-in/log-out board made. Vertically numbered 1 to 28. There were also 7 vertical bars labeled Zone 1 through Zone 6, and one for ‘in dispose’; i.e., in Latrin-e Land. This was so I’d know where my guys were at all times.
There was a hook for each one of these areas to log in, and to let anyone know where a certain person was during the day or night. You’re number 10? And you’re going to be wielding a torch over in Zone 5? Your brass tag goes right there. You’re going to skip over to Zone 3? Get your ass back here and swap it over to where you’re going. There is no excuse for being where you haven’t said you were, short of active accident or dismemberment.
Everyone shuffles back in and I explain the tote board.
“Notice there’s no spot to leave your brass chit if you’ve gone off the reservation?” I asked. “Why do you suppose that is?”
Confused looks all around.
“Because you keep that brass token with you when you’re not on the job. Lose it, lose your job. Sounds harsh, but so is getting your fucking hands blown off. Think of it as an exercise in discipline.”
There was a very little rebuttal.
“When you are on location, your brass token will reflect where you are. You are off-site, put the brass token in your wallet next to your lucky ‘circular impression’.
There were several knowing grins in my cadets.
Wear it around your neck on a chain. Keep it on your keyring. You can wrap it up in ribbons, you can slip it in your sock; I don’t care. Thing is, it is your ticket to this job. Hold on to it, there will be no replacements. We green?”
“Green, Doctor!”
“Outstanding.”
“Now, locker boxes. Gentlemen”, I continued. “These are your personal boxes that will be archived here. They will contain everything that you will need to carry out the job initially and help you with training the next crew that comes through after I leave. Keep them neat and tidy. I like to pull unannounced locker box inspections, gentlemen. Be forewarned.”
The sound of active scribbling is music to my tinny ears.
“Now, as such”, I continue, “Each locker box, at this point, is identical. Please follow along with me as we do inventory: Each gets locker box will contain (as I pull out the item for identification):
• 1- set Purchase Orders (POs) for PPEs
• 1- Galvanometer
• 2- Blaster’s pliers
• 1- Custom Leatherman
• 1- Metal clipboard
• Various Pens, pencils, paper, etc.
• 5- Sharpies
• 1 copy: Blasters Protocols Handbook, 15th Edition
• 1 copy: Blasting and explosives safety training manual by the IEE.
• 1 copy: Theory and practice of blasting, by Hino (A classic)
• 1 copy: Blasters Handbook, 17th Edition
• Various Explosives catalogs
• 1- Custom Swiss Army Knife
• Several Butane lighters
“Are we in agreement, gentlemen?” I ask. “Please check to be certain you have what the manifest states.”
“As long as we’re going over locker boxes, let’s look at our set of PPE purchase orders. Each locker box will contain POs for:
• 1 pair Orange Nomex coveralls, in your size
• 1 Dax carbon-fibre blaze orange hardhat with ear protection, gold face shield
• 1- CMC Safety 9-point extraction harness with carabiners
• 2- pairs Safety Glasses
• 2- pairs of gloves –wet & dry
• 1- pair Gear Box 8088 hard-toed intrinsically safe 8” work boots
• 1- Silva Orienteering Compass
• 3- pairs of cotton WaterWick socks
• 1- CommsLink™ VHF radio with microphone
• 1- Maglight power flashlight
• 1- Rain suit – also Nomex, bibs and outer shell
• 1- Mini Air Horn Power Tootler
• 1- Pair cotton/Nomex blende underwear – anti-chafe, wifebeateboxer: 3 sets.
• 1- 16-ounce container ‘Babies Bottom’ Talcum powder. Nomex chafes.
“Well, that’s a lot of gear; you best become real familiar with it as soon as you can. You are responsible for your PPEs. Lose them and replace them at your own cost. Wear them out? No problem. We will replace them. Get caught on location without your proper PPEs? Alavida. Goodbye. There is no second try. Fuck up once, and you’re gone. I am here for a limited time to try and teach you characters how to blast boats. I am not here to be your wet-nurse or mother. We green?” I ask.
“YES! Green! Rock!”
“Outstanding!”
We spend about an hour going over the various contents of the locker boxes and I answer general questions about blasting and explosives.
“We will use Primacord by the mile and tons of C-4 primarily. I might introduce you to binary explosives if there’s time. We might also get into PETN and RDX. Dynamite for training. But that’s about it.”
“We will use demolition wire and electrically fired blasting caps and boosters. We might have some time to look at set-pull-forget mechanicochemical fuses. But you’ll all learn some basic electrical wiring and how to design a circuit.”
“Tomorrow, given it doesn’t rain and the creek don’t rise.”
“Time, gentlemen!” I said. It’s been a long day and I’m a bit jet-lagged knackered. Besides, I wanted to give that Jacuzzi a spin.
“OK, remember: get your PPEs tomorrow morning at the Company Store. I expect to see each and every one of you here tomorrow, kitted out and ready to go, at 1300 sharp. That’s it. See you tomorrow. Susandhya. [Good evening.]” I said.
Locker boxes are locked and stowed in an orderly fashion. Each and everyone one of my 24 acolytes come to me before he leaves work to thank me personally and shake my hand.
“This might just work out”, I say to no one in particular.
Sanjay and I head back to the Raj for the night. I’m really tired, finally feeling the jet travel hit, and not the least bit hungry.
However, I do ring up the 214 cigar dude and relieve him of a selection of fine smokes. I drop by the bar for a couple of barley-pops before I retire to my capacious room for the night.
“Sanjay”, I say, “I’m knackered. If anyone wants me, head them off until tomorrow. It can wait. I’m going to get some kip and don’t want to be disturbed. No maids, no Majordomo, no butler. I just want to get unconscious for a while.”
“No problem, Rock”, Sanjay assures me, “I’ll tell them you’ve gone bush and haven’t left a forwarding address.”
“Good man”, I say, patting him on the shoulder. Hell, I must be getting old. Shit like teaching a band of newbies and whooping a little ass would have never as much as caused me a short breath. Then again, it’s probably not the years, it’s really the mileage…
After a quick light breakfast come morning, Sanjay and I are back on location. I’m being given a tour of the place by the day-shift foreman, one Mr. Vikramaditya Shrivastava.
“Yikes”, I say to Sanjay, “You characters really go for your 11-syllable names.”
“Call him ‘Vik’, Rock”, Sanjay smiles, “Good thing you’ve never asked about my last name.”
“Probably is”, I snicker back. I’m not getting roped into this little tussle.
Vik speaks fairly passable English, but I’m still glad Sanjay is here. The first order of business is to see the explosives bunker I sent plans for and how that’s coming along. They tell me it’s almost finished and ready to be stocked with what I’ve ordered.
“Outstanding, let’s have a look,” I say.
Into the Citation Golf Cart, we go. None of this plebian walking shit. We’re MIPs, Monstrously Important People.
Plebes walk, we ride.
We drive around the piles of rusty scrap, huge hunks of bulkhead, and disconcertingly quickly through polychromatic puddles of who-knows-what to slide to a stop in front of a large canvas tent.
Think M *A *S *H-type mess tent.
“What’s this?” I ask, “Commissary? First Aid?”
“No, Dr. Rock”, Vik explains, “Here are your explosives.”
My eyes grow large.
“What do you mean?” I ask. What the fuck do you mean? I mean.
“Building of your bunker is taking more time than we expected what with your design imperatives. But your order was filled most expediently. We are storing it here until the bunker is complete.” He smiles in that inimitable Indian manner that is so irritating when they don’t realize the major fuck-up they’ve just committed.
“OK. Simmer down, Rock.” I say to myself. “Sanjay, ask him again what’s in that tent. That bottomless tent that’s just a sheet of tarpaulin held up by metal poles.”
“He says that’s your explosives order, Rock,” Sanjay says. His demeanor went from perky and helpful to terrified as he saw me turn several shades of crimson and begin to emit wisps of steam.
“Sanjay”, I said in calm, calculated terms. “You are telling me there are over 9 tons of high explosives, blasting caps, boosters, demo wire, and ANFO sitting on wet sand in this heat under a sheet of fucking tarpaulin?”
“Yes?” he stammered, with a squeak.
“OK.”, I said. “We need to keep very calm and not go completely apeshit; and I’m telling you, right now, that’s taking Augean-level effort. We have a situation here, Mr. Sanjay. A very, very dangerous and very deadly situation. Let’s above all, remain calm.”
“Right, Rock”, he replies.
I turn to Vik and say in a calm and collected tone, “YOU STUPID MOTHERFUCKER! WHAT HAVE YOU DONE?
“Calm and collected, right, Rock?” Sanjay smirks and Mr. Vik withers under my verbal assault.
“Sorry, I had to get that one out.”, I apologized, “Mr. Vik. You have created a real blockbuster here. Quite literally. I figured, erroneously it seems, that you would not take delivery of over 9 TONS of high explosives before you had a very safe and secure place to store such.”
“It arrived sooner than we thought. We got a good price on it,” he explained.
You did? Fucking great! Holy mothering fuck!
Now I was even more worried. One does not get discounts or bargain-basement deals on quality high explosives.
“Pray, Mr. Vik”, I entreated, “From where did you source these detonic components?”
“From Best Blast and Supply Llc of Hong Kong Enterprises.” He replied, “Bulk discount quantities, quick delivery bonus. Saved crore rupee.”
No. I was wrong, it could get worse.
Not only 9 tons of high explosives, 9 tons of counterfeit, knock-off, and non-regulated manufacturer explosives.
“OK”, I said, “Let’s take stock here. My bunker isn’t finished yet? Correct? So you and the company meatheads ordered 9 tons of knock-off explosives from some shady and cheesy Chinese dealer and you stored them on wet beach sand, in this heat, under a tarp? Have I got all that right?”
“Oh, yes Doctor Rock.”, he smiled.
“Sanjay”, I said in a low, firm tone, “We have a…situation. We need to cordon this area off and build an exclusion zone as far as we can around it. No one, and I mean no one, gets within what, 10 kilometers? of the tent. This thing goes off, it’s going to leave a much larger than that cone of devastation. Then we need to visit with the management of this place and have a few thousand well-chosen four-letter words. Then I can think about what the fuck we’re going to do about this situation. I’m struggling to remain calm so everyone else will, but this is just a wee bit tetchy. Find me some red flags and start planting them around the tent, working our way out. Let’s go. Calmly, collectively, and with purpose.”
We find a source of 2-meter poles with red pennants. Sanjay also finds a few miles of yellow “Danger: Stay The Fuck Away” tape. We gather then and head back to the tent. We start to spiral out from it planting flags and running tape.
We did the best we could, but we were disrupting daily business activities. Good. Let the head idiots in charge know they’ve fucked up and grandly.
Back at headquarters, I’m fuming. I’m damn mad. I’m loud and being all extremely American about all this.
“You fucking idiots! 9 tons of cheap-shit high explosives? From China? Stored on wet sand in this heat? Under a benchod tarp? Why the flying fuck do you think I sent such detailed plans for a storage bunker? Do you assholes even think?” I railed on like this for at least half an hour, going all Gene Wilder in ‘Young Frankenstein’.
“Yes, Doctor”, one Mr. Karam Kanungo, the local boss and company president said, “That is all true and steps will be taken to redress the situation. But that doesn’t address the issue at hand. What do you suggest?”
“I suggest you are all taken out and given hot coffee high colonics to clear out your thinking processes”, I spit, “But that still leaves us with a nine-ton headache out there waiting to bloom into something even more aggravating.”
The entire assembled board agreed.
I calm down a bit and have a think. Fuck your boardroom, I’m having a cigar.
“You need a licensed, certified, master blaster to go and sort that out. Do you happen to have one handy?” I asked, sweeter than clover honey.
“Ah, yes, you are…oh.”, was the collective realization.
“Yeah, I know. It’s me. I’m the only one that can sort this shit out. We can’t even wait until we find someone from the world to assist. We are sitting on a literal time bomb, gentlemen.” I reply.
They all agreed and were relieved I was going to take on the challenge.
What else could I do? That stuff lights off and we’re talking easily hundreds if not thousands of fatalities and countless injuries. Fuck that. Not on my watch.
I tells ya’ what. The fucking Karma Fairy better shower me with gifts and accolades, blowjobs and candy corn after all this.
In a metaphorical sense, of course.
“OK, Mr. Sanjay, you’re with me.” I say, “Now look, Herr Macs”, I address the collective board, “Before I had carte blanche. Now, if I even think we might need something, it appears. We’ll sort out our honoraria and bonuses for this after we get back.”
Everyone present agreed most hastily. Handshakes all around and apologies from the board cemented the issue.
“OK, Sanjay. I need a bus. At least 24-seater. With a driver than knows how, when, and where to stop. OK?” I ask.
“24, Rock?”, Sanjay asks, “You’re not thinking of including the recruits now, are you?”
“Yes I am, Mr. Sanjay.”, I replied sternly, “On the job training. Meet me at outbuilding #2 at 1300 as per plan. Order a bus and arrange the largest forklift that can manage beach sand, about 100 wooden pallets, plastic wrap, and sandbags. Lots and lots of sandbags. Have them stockpiled away from the tent in a muster area. OK. You got all that?”
“Yes, Rock”, he said, “I’ll be there in a couple of hours. It will only take a few phone calls.”
“Marvelous.”
Not even 1000 in the fucking morning and I’m facing life and death decisions once again. I dig an emergency flask out of my field vest. If this doesn’t qualify as an emergency, what the fuck does?
A tot or two later, I change into my PPEs, and light a cigar. I catch a tap-tap to the region of the tent. I need to reconnoiter the area and figure out what sort of dragon I have to slay and the best way of going about slaughtering the sumbitch.
I’m standing alone, about 250 meters from the tent of death.
I’m puzzling and puzzling; but I can’t allow for my puzzler to go sore. Not this early, anyway.
“OK, me ol’ mucker”, I sigh, “It’s me or thee. Pucker up, Buckwheat. Here I come.”
A blast suit like the ones bomb disposal dudes wear wouldn’t help in the least. All it would do is hold the mashed body parts together to make for easier disposal. I’m anywhere within a kilometer or so of this pile of Chinese counterfeit boom-makers and it decides to let go; I’m lunchmeat. That’s it. Alive one second; kerpow, splat, instantaneously zonked into component particles the next. That’s the long and short of it. No ‘thank you’s. No ‘good bye’s. Just existing here one minute and in an alternate dimension the next.
Doesn't that just take the biscuit? Funny old thing, life.
I trod onwards.
For a moment, nothing happened. Then, after a second or so, nothing continued to happen.
I was walking up to the tent, clearing a path for the forklift. No fucking way I’m schlepping nine tons of dodgy explosives out of here, over wet beach sand, by hand and hoof.
Sand. I’m with young Anakin on this one. I hate sand. I hate walking in dry sand, hiking in wet sand. It makes for a wonderful oil reservoir and I love its porosity and permeability at depth. But at the surface, forget it. Yow! Let me tell you about the time I was out in the Rub al-Khali desert. The great Sand Erg. Wind blowing a force 9 gale! Seif dunes 1,000 meters high…
Yeah. I know. I’m stalling.
I’m approaching the tent. Carefully. I pause to light a new cigar. You might think that daft, but it’s really not. None of the stuff inside is heat-sensitive; let me clarify. None of the stuff is going to go off if hit by errant ash or even a sustained flame. But sitting out in the 30C+ heat? OK, that makes it twitchier. Cigars do the opposite for me. Give me something to concentrate upon and it calms me down.
I need calm now. By the bucketful. Where’s a monsoon when you really need one?
OK, I made it. I’m at the tent. Got to hand it to the workers around here, they respect authority and don’t come anywhere near the tent. They also don’t apparently give a shit as there no crowd gathered filming me with their iPhones to post to You Tube© if the tent decides to go all detonic.
Good. I couldn’t yell anything at them they’d understand to clear out anyway.
I open the hole in the side of the tent and pause. I’m hit with a wave of hot air. And the heady redolence of onions, sewer gas, and dog farts.
Sorry, that’s just me. Weird midnight snack last night. Frozen durian. What a treat.
Anyways.
I smell kerosene. Old wood pulp, like musty magazines. And an undercurrent of almonds.
“Oh, treble fuck me,” I say to no one within 100 square kilometers.
Kerosene is sweaty C-4. Old wood pulp is dynamite. Almonds? My old friend, nitroglycerine.
Things, if possible, went from real to super-uber major-league holy-fuck real.
“OK”, I say, as I dig out my phone and begin to snap pictures at a frantic rate.
Luckily, all the ordnance was piled like-with-like. Blasting caps? All over here. C-4, all along this ‘wall’. Dynamite? All over here. Non-explosives? Right over here.
I was mentally running like a squadron of overclocked Crays, wondering what I need to do to sort out this little situation. I’m so deep in thought, someone would need to throw me a rope to get my attention.
Or, just tap me on the shoulder.
Once I returned from low earth orbit, I turn to see a little wisp of an Indian feller, who had to be at least 27 years Methuselah’s senior.
“What? THE? Actual? Fuck? Are? You? DOING? Here?” I screamed.
“A thousand pardons, Sahib.”, the ancient one said, “I saw you working alone. Salim wonders if you need some help? Salim is good helper. Salim will help you good.”
“Yes, Salim. Oh, hello by the way.”, I said, calming a bit, forcing myself to smile so I didn’t kill him on the spot, “I do need your help. I need you to go, very slowly, out of this tent and to where the flags begin. Stand there and allow access to no one. OK. We green?”
Salim smiles broadly revealing both teeth. I slowly usher him out and remind myself to order a few new pairs of boxers before the day is out.
Back to the problem at hand. There are some salvageable items here. But the most the C-4, all the dynamite and every sack of ANFO has to go. And by ‘go’, I mean be disposed of. How?
By blowing it up, how else?
An idea creeps into my skull. I puff and puff while it grows and finally, I’ve a plan of attack.
I close the tent and slowly walk away. I hand Salim 1000 rupees and tell him that no one, I don’t care if it was Mahatma Gandhi reincarnate, goes anywhere near that tent.
“You savvy?” I ask.
“Oh, Sahib! I savvy! Thank you! Salaam! I savvy!” he is beside himself with joy, 13 bucks, and a task.
I look at my watch. It’s just gone noon. Good. I need a sandwich, some fluid replacement, as I’ve probably literally sweated off 5 kilos in the last hour and a half, and some time to jot down my plans.
I catch a tap-tap, geez, these things are everywhere around here. They form an unsanctioned, but necessary, sort of intradepartmental transport system here. I tip a couple of hundred rupees for every trip. They see blaze orange and they have this Pavlovian reaction. I sometimes need to break up fist-fights over which driver arrived first.
“Commissary”, I say, sit down, let the tap-tap, which is really nothing more than a glorified golf cart, adjust to my Western bulk and away we zip.
Salim is waving to me as we depart.
I shudder to think if I hadn’t had a tot or two and was a bit jumpier from the morning’s caffeine. Here's to alcohol: the cause of, and solution to, all of life's problems.
At the commissary, I grab a tall iced, fruit cocktail juice; a slurry of mixed dragon fruit, kiwi, carambola, blood orange, green apple, watermelon, bitter melon, sweet melon, & bailan melon fruity essence. I’m incredibly thirsty and I need some calories, but not in bulk and not from onion bhajis, mutton kabobs, or something claiming to be grilled chicken on a stick.
The last thing I need today is a case of the trots or even sharp gas pains in the next few hours. I add about 5 fingers of Old Fornicator Vodka to the juice and sip it slowly as my biometric rhythms return from the ionosphere and back to more normal levels.
Remember, I’m EtOh-based. I need to control my various fluid levels very carefully.
The blasting muse is upon me. In less than 30 minutes, I have a plan. Both a written out procedure and a map of what needs to be done.
I finish off another tall, icy glass of potato and various fruit juices, venture outside feeling almost like I’ve once again regained the illusion of control of the situation and my life.
I fire up a heater and decide to walk the approximately 1100 meters to outbuilding #2. I’m thinking as I sashay along; figuring this and calculating that.
I round the corner and see Outbuilding #2 and a bus parked next to it.
The bus looks like a refugee from Sgt. Pepper’s Lonely Hearts Club Band. The movie and album.
I go into Outbuilding #2 and see about half the class has arrived, and they are all kitted out in their new, stiff, and scratchy PPEs.
I nod hello to all and see Sanjay over across the room.
“Mr. Sanjay”, I say, “Nice bus. What’s the story?”
“Only one I could find that was a 24 seater, not actively falling apart, and with an English speaking driver. Rock. Mr. Maha, owneoperator.” He replied.
“Mr. Maha”, I said, shaking his hand. “Love the bus. Some sort of passion project?”
Mr. Maha laughs. “I was city bus driver for 39 years. I retire and go nuts. I buy old bus and fix up mechanicals. Runs all like excellently. Looks like dung heap. I begin to paint and never quite knew when to stop.”
“I like it. Adds a sense of surrealism to the day, as if it really needs more.” I reply, “However, I do hope you know how to stop. I mean that sincerely. We have a literal bomb to defuse. Does that bother you?”
“No, Doctor”, he says, “Nothing much bothers me anymore. I know. You are here. You are to make safe. I feel safe that you’re here. Let us go to work.”
“Outstanding”. I say.
I tell him that a fat bonus will be his when this is all over if all goes to plan.
“Unnecessary.”, he replies, “Mr. Sanjay has already paid me.”
“Paid? Perhaps”, I reply, “You are going to get danger money whether you like it or not.”
“I guess I will like it, Doctor.” He smiles.
“Marvelous.”
I look at the clock, it’s 1256. Almost showtime.
1300 on the spot. I pick up the microphone and address the assembled 24.
“Gentlemen”, I say, “Very good. You all look like late October in the United States. Very festive.” as all are kitted out in their respective PPEs.
“We have a little matter to handle. One that has just cropped up and one you’re certainly not ready for, but I have no other choice. Does that bother anyone here?” I ask.
Head shakes and questions arise.
“OK, class”, I say, “For your first training exercise, we’re going to defuse a 9-ton bomb. Let’s go.”
The collective gasp drew my cigar smoke in another direction, right towards them.
“Doctor…Ah, Rock. Really?” one brave soul asked for the crowd.
“Yes”, I said, “seems your company officials got a ‘real deal’ on some dodgy Chinese explosives. They didn’t wait until they finished the storage bunker I had designed, so they simply set the stuff on the beach and covered it with a canvas tent.”
There were more gasps.
“Indeed”, I said, “We need to neutralize this threat. Sanjay is passing out copies of my plan and designs on just how to do this. Read them over and let me know what you think. You have 5 minutes. We’re out of here at 1330 on the nose.”
They read quickly, cogitated over the plans and as I had assumed, didn’t find any flaws within.
“OK”, I say after an inch of cigar had passed, “You follow my directions, directly and without question, there’s no reason you can’t come out of this alive and happy, free to pursue a life of religious fulfillment.”
There was a chuckle or two at that last line. ‘Airplane’ is such a classic movie.
“Now I know”, I continued, “That this is pretty scary shit. Especially for you guys, being tossed in the deep end like this. I know because I’m scared to death.”
“Oh, Doctor Rock”, one of my acolytes said, “We do not believe this is so.”
“I stay alive by being scared to death”, I replied. “You will learn this as well.”
Sanjay checks out everyone’s PPE and all appear in good order. They are happy to have such nice, new equipment.
And that’s a problem. People used to ragged and ratty shit with which to work will go to extraordinary lengths to not filthy-up brand new working gear. This is one little bugaboo I’m going to settle here and now.
“One thing, gentlemen”, I note, “You all have nice, clean, and new PPEs. You look great. You come back to Outbuilding #2 looking as pristine, you’re gone. Keeping clean is not a part of your training. You’re going to sweat and stink. You keep to clean and it tells me you’re goldbricking, that is, not doing your job.” I say as I surreptitiously unscrew the top of my travel mug, ‘accidentally’ trip and shower the front row with Greenland coffee, lukewarm.
“See?”, I saw, “They were totally protected. That’s what PPEs are all about. We green?”
“Somewhat brown, Rock”, a couple of the guys in the front row reply without a hint of irony.
“Outstanding.”
“Gentlemen, it is time. Take what you think you’ll need and leave the rest in your locker box. Brass tags to Sector 4. On the bus, we leave in 5 minutes.”
I move my brass marker to Zone 4, puff a blue cloud for all to see, and head out to the bus.
We’re loaded and headed to Sector 4 in less than 5 minutes.
“OK”, I say”, I’m going to break you up into groups of 4. Tags number 1 to 4, you’re group 1. 5-8, group 2, and so on. OK?”
All respond in the affirmative.
OK. Six groups of four, Sanjay and me to lead the pack. We roll up to just outside the exclusion zone. With a squeal of brakes, we grind to a halt.
“Outside”, I command, “Assemble in your groups next to the bus. Go!”.
Like a well-oiled team, they de-bus and stand together in 6 groups. Sanjay and I walk along, inspecting the troops.
“OK”, I say, “This may seem like a shit job, but group 4. Back on the bus. To the commissary. Water, juice, and whatever else you think we’ll need to stay hydrated out there. Don’t worry, we’re going on rotation once you get back. You’ll all get a chance to do the exciting stuff. Now, move it.”
I say something to Sanjay, he jots it down in his book, certain to remind me later.
“OK, let’s see. Group 1. Storage detail. Build the temporary in-ground storage locker like it’s shown in the plan. Get help and have them source the manpower and materials. It needs to be done in the next 2 hours. Go!”
There are some explosives that can be salvaged. I need a place to store them. I’ve scouted and laid out a spot away from prying eyes where they can build an 8x8x8 hole in the ground, line it with marine plywood, and store whatever we can salvage. A plywood roof over the thing, a couple of locks, and well, Robert’s your Mother’s Sister’s Husband.
Next, I send group 3 to build a road from the tent to an area on the beach sourced as Disposal Area #1. They will take flags and tape and run a road, of sorts, from the tent to the beach; cordoning it off so we can take the forklift and its loads of dodgy high explosives to the disposal area.
The other groups are doing needful and necessary things as well. I tell Sanjay to keep a lid on things, I’m going to bring the forklift, a few pallets, sandbags and such in for the first run.
I find the forklift, and it’s a huge old Hyster 52-ton truck.
It’ll do.
The keys are in, so I drop in and fire it up. It catches on the first twirl and I pick up a half-dozen wooden pallets, a bunch of sandbags, and a few huge rolls of plastic wrapping. It’s like driving a tank, but it has plenty of power and just a low gear range.
I drive it back to Sector 4 and almost rum over Salim. He was taking my previous orders very seriously, indeed.
“All cool, Salim”, I say over the roar of the forklift, “It’s just me.”
He waves and lets me pass. He’s serious as a heart attack about keeping people out.
I drive and realize that I can’t drive ‘gingerly’ in a conveyance such as this. I can drive deliberately and with forethought, but it rumbles and shudders the ground. Best to slide in, drop the load, and shut her down while I figure out what’s next.
I do so and drop the pallets, etc., just outside the flap of the tent. I back off a few feet, drop the forks, and shut the noisy machine down for the time being.
Sanjay appears. As does Crew #5. I motion them to come over, slowly and with forethought.
We’re all standing outside the tent flap. I raise an index finger, right, of course, to get their attention.
“Gentlemen, first lesson. What says these explosives have gone bad? Answer:” and I open the tent flap.
“Take a whiff. What do you smell?” I instruct.
“Old paper?” was one answer.
“Oil? Petrol? Something petrochemical?” was the next.
“Almonds?” Sanjay says.
“Highest marks. We’ve old C-4. It sweats and smells like kerosene. Old paper or pulp? Dynamite gone wet and bad. Almonds? Bitter, bitter almonds? Nitroglycerine. Yes, guys. We’ve got rogue nitro inside. Anyone want to quit? Now’s your chance.” I ask, being deadly serious.
One looks to another; then they all look to me…eyes wide…
To be continued…
submitted by Rocknocker to Rocknocker [link] [comments]

MAME 0.220

[ Removed by reddit in response to a copyright notice. ]
submitted by cuavas to emulation [link] [comments]

Configuring strategy tester for binary options?

Hi! I am hoping someone could lend some advice re how to configure the strategy tester to work with binary options style trading.
In case you're not familiar with binary options, a few notes:
- There is no stop loss, take profit
- There are no spreads/commissions
- I must set an expiry time in minutes or candles
- Simply, if I go "long" (called a CALL) and the expiry price > strike price, that's a win (and < would be a loss); if I go "short" (called a PUT) AND the expiry price < strike price, that's a win (and > would be a loss). Also I could "Push", meaning the strike price = the expiry price. These should be disregarded from the calculations as there is no loss or gain of $.
- As such, I just need a W/L/P (P being 'Push', meaning strike price = expiry price)
Thanks! Welcome any advice. 😀
submitted by ddcred to TradingView [link] [comments]

ORICO 16GB USB Flash Drive USB 3.0 £2.70 Delivered @ AliExpress Deals / ORICO SSD Store

The description of this deal was not provided by this subreddit and it's contributors.
£2.70 - AliExpress
Always handy to have, and at this price i've ordered a few for the house / keys etc. Used ORICO products before and been impressed, so figured it was worth a go!
Use the 79p coupon on the page to get the advertised price :)
Features:
  1. Supports hot plug & play, High speed USB 3.0 port 2. No physical drive required 3. Plug-and-play; no external power supply required, USB bus-powered 4. Support all current computer systems 5. Speeds vary depending on types of file being transferred and computer configuration. 6. Read Rate: 95Mb-125Mb/S Write Rate: 16-30Mb/S 7. Interface USB 3.0 8. Support OTG function 9.Zinc alloy design,anti-fall and durable
    About capacity:
    16GB=approximately 14.5GB-14.9GB 32GB=approximately 28.5GB-30GB 64GB=approximately 58.5GB-60GB 128GB=approximately 114.2GB-124GB Vendors are using Flash memory decimal arithmetic: 1 MB = 1000KB, 1G = 1000 MB Calculated, operating system with binary arithmetic: 1 MB = 1024KB, 1 GB = 1024 MB; So there are some differences between display capacity and nominal capacity of flash memory products
    Few things to consider before you go ahead
submitted by SuperHotUKDeals to HotUKGamingDeals [link] [comments]

Looking for practice? Want to expand your AHK knowledge? I got you covered.

I made a reply a while ago to Swaggurttt (could you give us an update of how things have been going?)
He wanted to learn more about AHK. So I provided him a list of new things to learn past just "press button > send keys".
Hopefully, some people reading will take this opportunity to branch out and learn some new things that AHK is capable of. From stepping into the aesthetically pleasing world of GUIs to using RegEx to become a string manipulating master. From braving the cryptic DllCall() command that lets you embrace code from other files thus making your scripts much more robust and useful, to having a whole slew of problems and puzzles that will test your ability to utilize AHK's capabilities.

Practice, Problems, and Challenges - It's like fun homework

Let's start with 4 websites that will give you tons of practice. From easy to insanely difficult. Between these 4 sites, you should have more things to do than you could ever finish.
Code Abbey
The site I've spent the most time on. From the easiest "add two variables" all the way to "write an AI". It's a good place to learn core programming skills and develop logic. Parsing through data, calculating variables, using arrays, etc...
Funny thing is this website is the reason I'm making this post. It has been a while since I used this site and I couldn't remember the address. So I looked up this post and...here we are!
Rosetta Code
Another good site, though I like Code Abbey's layout, sorting, and input/output method more. Rosetta has its own pros, like showing you solutions in TONS of different languages. Very helpful if you're familiar with other programming languages.
Code Chef
This was suggested to me a while ago and I've only done a couple of problems. Not because it's a bad site, but because I just haven't had the time to try and nuke the list. I figured it was worth including.
Those 3 should keep you busy for quite some time. Plus...
The AHK Subreddit
This subreddit is a treasure trove of problems! I used to spend a ton of time just trying other people's problems, coming up with my own solutions, and comparing what I come up with to others. You can learn a TON doing it this way. And comparing answers afterward only teaches you newer and better ways of doing things. Consider the unbelievable amount of backlogged posts you can go through. Years and years worth.

How about some suggestions for parts of AHK to learn?

RegEx (Regular Expressions) - Master of Strings

This is a mini-language for manipulating strings. Learn it! If there's a discernible pattern to what you're looking for, you definitely can write a RegEx to find it. See: RegExMatch and RegExReplace. Bonus: It should be noted that RegEx is its own little mini-language with its own rules and syntax. BUT, once you learn it, you now know it for almost every other programming language (minus some discrepancies between flavors).
RegEx Resources:

COMs - Letting you interface with other shit one command at a time!

COMs are pretty amazing. They let you interact with lots of different things on windows. Microsoft lets you access things like Internet Explorer, Excel, Word, Access, (literally the entire office suite), shell, WIN HTTP, VBScript, etc... It lets you use those programs directly from AHK. This increases reliability near infinitesimally compared to blind clicking and typing. You can web scrape like a boss using the IE COM. You can manipulate Excel spreadsheets, get data from them, update them, and whatever else you want. COMs are handy.
Resources:
There are also quite a few videos on YouTube that you can also check out.

GUIs - I feel pretty. Oh so pretty....

Learn to make and manipulate Graphical User Interfaces or GUIs. When you want user-friendly interaction with the users of your code, GUIs can be the perfect answer. A non-programmer isn't going to want to run scripts with switches or open up .ahk file or edit code to change settings. Enter the GUI!
The "Read This Before Posting!" stickied tutorial post has some good WYSIWYG suggestions. And it stands for What You See Is What You Get...that's really what they're called. Personally, I'm a fan of GUI Creator by Maestrith.
You'll spend a LOT of time trying to learn all the different things GUIs can do.
The AHK docs are the go-to for this stuff. Here are the pages you'll be visiting quite often:
I'd like to add a neat method I've started doing for tracking elements because it used to be a struggle for me. When I create a GUI, I like to keep everything inside of functions and I really don't want to create global variables for everything. I find myself making a single global Object in the AES. Then, whenever I create a GUI element, I always add the hwnd option to it and then immediately save that HWND to the array. Plus, you can logically name it so it's much easier to recall.
Example:
Global guiHwnd := {} NewGUI() MsgBox, % "Cancel Btn: " guiHwnd.CancelBtn "`nOK Btn: " guiHwnd.OKBtn ExitApp NewGUI(){ Gui, New Gui, Add, Button, hwndBtn gOKBtn, OK guiHwnd.okBtn := btn Gui, Add, Button, hwndBtn gCancelBtn, Cancel guiHwnd.cancelBtn := btn Gui, Show Return } 
GUIs are an excellent segue into DllCalls. Why? Because DllCall can let you fine-tune a GUI.

DllCall - Rule #1 of coding: Don't reinvent the wheel!

One thing we learn real quick in programming is you don't rewrite code that's already been created and thoroughly tested. It's a waste of time! That's why people will bundle up their code into these neat packages called DLLs (Dynamic Link Libraries) and then publish them for others to use. These let you call commands and functions outside of the native AHK language. Meaning you can interact with Window's internal functions directly from your script! This opens up a TON of possibilities for any script and unlocks some of the restrictions that come with AHK. Like changing things about GUIs that AHK doesn't have an option for. Or getting info directly from the operating system because we don't have an AHK command or function created to do so.
It's not just limited to Windows functions. It can access any DLL. As long as you know how to interface with it.
This MSDN link has a top-level link to all of the core things you need to learn about DLLCalling to windows.

GDI+ - Giving you the ability to create and manipulate graphics on the Windows level

GDI is Window's Graphics Device Interface. A user named Tic (Tariq Porter) wrote GDI+ for AHK. It handles ALL the DllCalls you need to make to the GDI to manipulate graphics, draw shapes and objects, import pictures, etc. You know all the stuff you can do in Paint? You can do ALL that anywhere at any time on the screen using AHK & GDIP. Without having to ever load Paint. Please note the GDI+ repo also includes tutorials on how to use the library. It doesn't cover everything quite as in-depth as I'd like it to, but the examples will give you plenty to go off of.
Why are you still reading this? You should have gotten distracted way up top and started trying stuff on Code Abbey!
OK, one challenge I always like to give people.
Recreate the Window's calculator. And make it work exactly the same. Initially, it sounds easy! But, duplicating the functionality AND the aesthetics can be pretty tricky. This is actually a tough challenge with lots of parts. You'll have to make a GUI that looks as close as possible to calc.exe. Make the display function the same, make every button work correctly, calculations should work, memory buttons should function, etc. Don't forget to make an icon for it and also to disable the AHK system tray icon, just like the real thing. Oh! And recreate the menu, too. This will give you practice on TONS of different aspects. It's complex enough to be challenging but not so complex no one would ever want to do it.
If you can get this done and want to extend things further, try making the scientific version of the calculator!! There's a real challenge. The extra advanced math buttons each have to work correctly.
Go, try, learn. If you get stuck, come back to the sub and ask for help. Or hit up the Discord crew. While you're waiting for an answer, you can always go through some of the current questions on the sub.
I hope you guys enjoy this post.
submitted by GroggyOtter to AutoHotkey [link] [comments]

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