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Author: Adamstheinvestor
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Pairs trading, not currencies – Like any other relationship, you should be aware of both sides. Success or failure in Binary Options trading depends on correct your estimates on both currencies components of the husband and how both affect on one another, not just one of them.
Knowledge is power – when it begins Binary Options Trading on the Internet, it is essential that you understand the basics of this market if you want to achieve the maximum benefit from your investment.
The main index in the Binary Options market is global events and news. For example, if we assume that the European Central Bank will issue a statement regarding the interest rates, the euro usually this event will cause a wave of activity in the market. Most of the new arrivals seem a backlash to such news as they close their trading positions to miss one of the best trading opportunities with a preference to wait until the market once again restless. The possibility of real profit in the Binary Options appear in times of volatility, not in the quiet times.
Trade is ambitious – many new traders are putting too restrictive orders in order to reap a very small profit. This approach is not desirable in options trading because despite being profitable in the short term (that is if you are lucky asset), you run the risk to be a loser in the long run because it will have to cover the difference between the prices of the question-and-take before they start making any profits, a which it is more difficult when you are a small trading at him when the biggest trades.
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Binary Options Trading are all shortcuts for common foreign exchange market exchange. In fact, it is the largest financial market in the world where they are buying and selling currencies freely. On the current situation, the Binary Options Trading market was launched in the seventies of the last century and that while the liberalization of exchange rates so that the participants in this market are now only determine the price of any currency against other currencies based on supply and demand levels. When it comes to freedom and to stay away from any external control is to achieve free competition, the Binary Options Trading is is the perfect place to achieve all these things. This is because the daily trading volume in the Binary Options of several trillion dollars, which means that the currency market in more than three times the size of the total size of the US stock market and bond together. Binary Options market is the exchange of cross-communication networks where buyers and sellers meet to conduct treatment using technological means communication market.
Unlike other financial markets, the Binary Options Trading has no central exchange or a physical entity. Since this market is not expressed as a physical place, the exchange trades take place on an ongoing basis on the four and twenty hours a day saluting moving from time zone to another by navigating across the major financial centers in the world and that on a daily basis. Trillions of dollars of foreign currency exchange activities occur on a daily basis in Options trading. Since 1997 and until the end of 2000, the Binary Options daily trading volumes almost increased from five billion to $1.5 trillion, and perhaps more (according to some recent studies, the trading volumes touched the level of $1.7 trillion in today is superior to all other financial markets combined). I think it’s really difficult, if not impossible .- to determine an exact figure because the absolute Binary Options trading is not through a central exchange, but certain thing is that the Binary Assassin Software continues to grow at rates amazing.
Before the advent of the Internet and e-commerce, the big multinational companies, banks and high net worth individuals they are entitled to trading in the Binary Options market through the use of bank-owned trading systems. These systems were required as a minimum to open a trading account about one million dollars. Thanks to new technology developments, especially with regard to the internet today, the investors can use a few thousand dollars that go into the Binary Options market on the four and twenty hours a day, five days a week throughout.
Forex market is a nonstop cash market where the currencies of countries trading in connection with and usually through intermediaries who call them mediators Binary Options. Foreign currencies are continuously sold and purchased through local and global markets in more than investors or detract from the value of an investment based on currency movements. Binary Options market conditions may change at any moment in response to current events and this ranks as one of the more volatile Binary Options and the fragility of markets. Also, the conditions of the Binary Options Trading does not remain the same, but never changed in almost every second. Trading volumes in the foreign exchange market than all the combined transactions that occur in the stock markets and futures markets in both London and Tokyo. According to its size and scope, the Binary Options market times other markets sizes. Statistics indicate that the immediate and directed trades that occur in the interbank market is divided as follows. 51% in the form of an Instant Forex transactions, followed by 32% in the form of currency swap operations, Binary Assassin Software transactions explicit also represents 5% of daily turnover, while the “interbank” equal to the other about 8% and therefore, the interbank market accounts allocated of which about 96% transactions Options the foreign exchange market as the exchange of 4% in the other, divided between global futures exchanges.
For Binary Assassin traders, the Binary Options Trading represent an alternative to trading in the stock market. While there are thousands of stocks to choose them, there are a number of key stocks that are traded in the Binary Options market (the US dollar and the Japanese yen and the British pound, Swiss franc and the euro currency is the most famous). Binary Options Trading also allows the trader crane outweigh what is happening in the stock market as well as a minimum level of investment in order to start trade. Add to that the ability to choose the appropriate trading Times ( Binary Options conducted on twenty-four hours) over here and perhaps might be known the reason why many stock traders to abandon their fields and arriving about Forex Trading.
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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.
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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]

AMZN Trade Retrospective: Collecting a $.37 Credit for the Potential to Make Another $50

AMZN Trade Retrospective: Collecting a $.37 Credit for the Potential to Make Another $50
There are different ways to trade in a choppy environment. Here’s a deep dive on how I attempted to use weekly options to trade a potential bounce in AMZN, and collected $.37 initially, for the possibility of making $50 more, even though the trade ended up being only an $.81 winner.

The Entry

Last Thursday, 9/24, when $AMZN was trading at about $3000 a share, I was looking for a cheap way to play a bounce in the stock. During that time, my bias in the markets had begun to shift to a more bullish stance after seeing how the market had difficulty grinding lower. With that in mind, I wanted to play a potential bounce in tech. But I knew I didn’t want to pay a debit at all to play for a bounce that might not even happen, given how uncertain and choppy the markets had been, but I still wanted to set myself up to capture some large gains if AMZN did indeed bounce. Therefore, the strategy that made the most sense to me, was a Call broken wing butterfly.
Given that I’m a very short-term options trader who loves trading weeklies, I was trying to look for a cheap butterfly for the upcoming week that I could put on for a net credit. After exploring the options chain, I came across the +1/-2/+1 3300/3350/3450 call broken wing butterfly for the Oct 2 series. This fly, at the time (on Sept 24), was trading for a total of $.37 credit. Meaning, by putting on that butterfly, I would get paid $.37, and the following scenarios could happen:
  1. If AMZN decided to tank or hang out sideways and never get up close enough to the butterfly to expand the spread in my favor, then I’d walk away pocketing the $.37 credit
  2. If AMZN slowly crept up to reach exactly 3350 by expiration, I’d not only get to keep the credit, but also be able to sell the butterfly back out for $50. Of course, it doesn’t need to reach exactly 3350 by expiration. If AMZN slowly worked its way up to near 3300, then the butterfly would expand very nicely as well.
  3. If AMZN blew past 3400 by expiration, I’d see a loss, up to a maximum of $50 / spread (if $AMZN moves past 3450). That’s because the 3300/3350 long call vertical of the fly provides 50 points of coverage before I essentially start losing money from the 3350/3450 short vertical, up until that 3450 kicks in to cap off further upside losses.
So that is a rough outline of the potential scenarios that would happen with this trade.
Given the choppy market conditions, I was ok with risking $50/spread (point #3), in order to not lose money if I’m wrong on direction (point #1), while at the same time, keeping myself open to the possibility of the butterfly expanding in my favor (point #2) for some potentially very large gains.
But satisfying point #3 is tricky. I needed more data points suggesting that $AMZN wouldn’t surge higher early on in the trade. Because if $AMZN did surge higher early on in the trade, then while the 3300 long call would rise in value, those two 3350 short calls would also rise in value, and because there’d still be some time value left, they could be very juiced up and eat away at the profits of that 3300 long call, so much so that the 3450 long call won’t even be able to offset those losses, especially given how far out of the money that 3450 call is.

AMZN on 9/24, daily timeframe
Looking at the chart above on 9/24, we can see that AMZN was trading at around $3000/share. In order to reach $3300 (where the first long call of the broken wing butterfly is), the stock would need to
  1. Breach the 38% fib retracement (~AMZN=3131) of the move from the 9/2 high to the 9/21 low,
  2. Breach the 20MA and 50MA
  3. Breach the 50% fib retracement (~AMZN=3211)
  4. Breach the 61.8% fib retracement (~AMZN=3292)
before finally reaching the 3300 long call. All of these levels, I felt, should provide some resistance for AMZN to have to chew thru over the following week, before it even gets to the long call. And by that time, if AMZN did reach 3300, then the 3300 long call would still have a lot of extrinsic value left (somewhere around $20 on the last day), while the 3350 short calls would be very cheap (each around $5), so the entire spread could be roughly worth $10. Which would be great, because that means I’d be getting paid $.37 to make another $10.
So with all of the above considered, I chose to take on that upside risk, for a chance to make potentially $50 (realistically I try to aim for just half of the max profit: $25, and start harvesting profits and peeling off the flies at around $5-$10), and that day on 9/24, entered the Oct2 3300/3350/3450 call broken wing butterfly for a $.37 credit.
After entry, on Friday 9/25 and Monday 9/28, AMZN made steady progress upwards, from 3000 to 3175, breaching the 31.8% retracement and tagging the 20MA and 50MA from below.

AMZN on 9/28, daily timeframe
but this move wasn’t large and fast enough to expand the value of the 3350 short calls. In fact, theta did a great job draining those short calls, while the 3300 long call did a good job retaining its premium, so the butterfly had already expanded a bit in my favor, and I was sitting at about a small $1.00 profit.

The Adjustment

However, on Tuesday and Wednesday, AMZN began to stall out. By the end of Wednesday 9/30, when it looked like AMZN was putting in a topping tail, I decided that AMZN might not be able to make it near 3300 by expiration Friday, so I wanted to take in a bit more credit while I still could, before theta drained more of that 3300 long call. At the time, the spread was trading for almost $2.
That’s when I made a slight adjustment to the spread and sold the 3300/3310 call vertical.

AMZN on 9/30, daily timeframe
This essentially rolled the 3300 long call up to 3310, and I was able to collect a small $.44 credit for it. However, this adjustment did open me up to an additional $10 of risk to the upside, because now, the long call vertical portion of the butterfly is only $40 wide (instead of $50). Still, with only 2 days left for AMZN to go higher, I felt comfortable taking on a bit more upside risk knowing that theta is going to be working hard to drain those 3350 short calls if AMZN did decide to surge higher. And at that moment, I actually wanted AMZN to move more towards my fly. My deltas were still positive, and the risk graph showed that a move towards the short strikes of the fly would expand it by another $4-5 by Thursday.
So after this adjustment, the trade stood at a $.81 credit, and the profit potential on the fly was now $40 instead of $50. Which is still pretty good.

The Tease

On Thursday, AMZN showed some strength and closed above the 50% fib (3211), which meant that if on Friday, AMZN worked its way up to around 3300, the fly could potentially be worth $5-10. Things were looking good (on any continued bullishness, the next target for AMZN was the 61.8% fib retracement at ~3300). So I left the trade alone without making any more adjustments.

AMZN on 10/1, daily timeframe

The Flop

Unfortunately, on Thursday night, news broke out that Trump was diagnosed with Coronavirus, and the market fell lower. By the open, AMZN was already trading at around 3150, roughly 150 points below the fly. The spread had instantly lost all of its value, so I basically let it expire worthless and walked away pocketing the $.81 credit.

https://preview.redd.it/mpwrkjpk6xq51.png?width=4096&format=png&auto=webp&s=8dd7f4da7b000b2266ab57a3c23c1863f9423704
While the trade did not work out as well as I had liked, the important thing to note is that I was able to get paid even when the trade didn’t go in my favor. With options, there are ways to trade an underlying to a certain target without ponying up a debit, albeit at the cost of introducing tail risk, while offering the possibility of very large upside. This may be a style of trading that one can consider employing when the outlook of the markets is uncertain, as long as the trader is willing to make the necessary adjustments to control risk.
Which leads me to the following section:

FAQ

What if AMZN decided to surge very early on during the trade? What if AMZN had surged to 3300 with 4-5 DTE, hence juicing up the short calls and causing the butterfly to take on large negative deltas?
Even though the position would be very theta positive, I would pony up the debit to cap off the upside risk by buying the 3400/3450 call vertical, hence turning the 3300/3350/3450 broken wing butterfly into the 3300/3350/3400 balanced butterfly. From there on out until expiration, I would look for ways to reduce the debit incurred from that adjustment.

But what if AMZN tanked afterwards? You could end up getting whipsawed.
I’d rather be safe than sorry and make the necessary adjustments to avoid getting run over, because I don’t like playing the hope card. I could always undo the adjustment and look for ways to collect back more credit (at the cost of introducing risk elsewhere), depending on my new directional bias on AMZN at the time.

Your maximum loss is so large, $5000. I’d never make that bet, I would never risk $5000 to make $5000.
This style of trading is not for everyone. There are different ways to perceive risk. I don't really think of risk as binary as “max gain vs max loss”. If the trade goes against me, I’m not going to open myself up to the possibility of eating the maximum loss. I’m going to manage that risk and make sure that I don’t lose any money at all on the trade. Basically, I’m not going to just put on the trade, walk away to the prayer room, and come back at expiration and hope that AMZN expired at 3350.

Why not just join thetagang and slap on iron condors / credit spreads in this environment? You could’ve collected more credit by selling a 50 point wide put vertical with your bounce thesis.
Different traders have different styles. I personally don’t like pure premium selling strategies. I’d rather have long options in front of the shorts to open myself up for some large upside and convexity in the P/L curve, rather than limit myself to the concavity of pure premium selling strategies. Having long options in front of the shorts also helps me sleep better at night.

It’s hard to read this. Is there a more visual explanation?
Here’s a video on it: https://www.youtube.com/watch?v=8uq76fZ3EME

TL;DR - I used weekly options to trade a potential bounce in AMZN, and got paid $.37 initially to do so, for the possibility of making $50 more. While the trade did not pan out, I walked away pocketing $.81 for being wrong.
submitted by OptionsBrewers to options [link] [comments]

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