IV has contracted across all sectors over the past few months, and post-Brexit, IV is at 52-week lows in a lot of areas. China has an IVP of ZERO (as measured from FXI). Oil's IV is sitting at lows, Brazil, the EURO for Pete's sake! One of the only areas that still has room for IV to fall is gold.
So, knowing my methods and processes, what do you think I have acted on? Ah yes, betting on IV contraction and expansion based on IVP.
So first, GDX. Straightforward: GDX looks a little extended up around 30, and IVP sits around 50. A simple bear call vertical was placed for Aug-26 expiration at the 32/34 strikes and collected a 0.50 premium. PoP = ~72%
Next is USO. Oil looks like it could continue to climb, but more importantly, IV definitely looks like it could expand over the medium term. Thus, a call diagonal was placed at the Aug/Sep expirations at the 10.5/11 strikes which cost a debit of 0.46. PoP = ~62%
Last is XOP. Once again, oil's IV looks like it could expand over the medium term, but XOP doesn't appear that it will move much in either direction, so I stayed delta neutral with a put calendar for Aug/Sep at the 34 strike and paid 0.60. PoP = ~40%.
These three positions are much smaller in risk compared to previous trades because their PoP is not fantastic and low IV environments do not provide the edge that I seek with my processes. I await earnings season once again.
Additionally, I would like to report on the performance of my virtual calendars and diagonals. With more attention paid to their profitability, they would have had more ... profitability. Of 5 total placed, 3 were delta neutral and 2 were delta negative. 3 were winners, 1 was a scratch, and 1 was a decent loser. Overall, a profit of 0.32% on capital was realized. Not too shabby but could have been better.
Friday, July 15, 2016
Friday, June 24, 2016
You've Heard What Happened.
I'm sorry, I think the reaction to the news is a bit overdone. The Pound is tanking, the Dollar is surging, and stock markets around the world are plummeting. For ... what? Anything beaten up that badly will likely rebound strongly over the next few months. People were looking for a reason to sell, I guess. I fail to see how this is a HUGE deal for the European economy, on its own, and doubly how it remotely affects our own economy, on its own. What results in terms of potential domino effects, etc, are all speculative. The event on its own ... I don't see it having much of a real, lasting impact. However, I have conducted little research on the topic. From what I can tell by the reaction of the losing side, the decision was made based on immigration policy disputes, not of anything economic.
So, the VIX is up to 25 again, the highest it has been since January and February. Well, I got what I wanted, increased volatility! So come Monday, I'll be out on the hunt for good opportunities once again using my traditional techniques.
With the Fed very, very likely to avoid a rate hike for the next 6 months (December would be the time to do it...?), volatility should contract somewhat swiftly. I don't see it taking the stairs down, so to speak, as it did from February to April.
It's good to be back; I haven't originated a new position since April 28th. Wow!
So, the VIX is up to 25 again, the highest it has been since January and February. Well, I got what I wanted, increased volatility! So come Monday, I'll be out on the hunt for good opportunities once again using my traditional techniques.
With the Fed very, very likely to avoid a rate hike for the next 6 months (December would be the time to do it...?), volatility should contract somewhat swiftly. I don't see it taking the stairs down, so to speak, as it did from February to April.
It's good to be back; I haven't originated a new position since April 28th. Wow!
Tuesday, June 7, 2016
An Outline of My Process
I am going to assume that the reader of this post has at least a rudimentary understanding of statistical concepts and an intermediate comprehension of the vocabulary of options as an asset class. It was written for reference for my own personal purposes, and is a massive simplification of what it is that I do in total. Consequentially, it was not written for educational purposes.
I trade options as if they were insurance products for two outcomes; protection against loss of opportunity (calls) and protection against loss of capital (puts). In this way, options should be more expensive the greater the risk to the issuer/writer of them expiring in-the-money (ITM). This is because the writer shoulders the risk of having to go into the market and buy shares or lose his already owned shares should he be called away, which can happen at any time before or upon expiration. The same goes for puts, instead the writer would have to buy shares at a huge premium to the current price should his contract be exercised. In exchange, the writer collects a premium, which should be higher the greater the risk of assignment.
If option prices are conceptually priced based on their probability of expiring ITM, how does one determine that probability and therefore a specific price? Well, Black-Scholes for one, but you don't need to know anything about that formula to understand the probabilities.
There are five sensitivities that option prices react to, known as the Greeks. Only three of them are of any real importance, with one of them only coming in to play when there is a short time before expiration. They are delta, theta, vega, gamma, and rho. Delta, theta, and vega play the largest role in determining the probability of options expiring ITM.
In order to demonstrate this precisely, I will use graphics of Normal Distributions:
Standard Distribution
The standard normal distribution is nothing more than a simplified histogram, in which the curve seen above is just "draped" on top of random observances. The gray line shows where the mean of the data lie, which is always the center so that 50% of observances are above the mean and 50% are below. The shape of the curve is determined by the standard deviation (sigma) of the data. The larger the value of sigma, the shorter and fatter the distribution will be, as there is a greater chance of observing a value that is more distant from the mean value.
Delta
Delta has the effect of shifting where the distribution lies on the number line by changing the mean value. When evaluating probabilities in the stock market, I always use the current going price of the stock as the mean value, with trading software calculating the value of sigma. When the price of the stock goes down, the mean value does too, and so the entire distribution of observances over a given periodicity moves accordingly. However, all else equal, the shape of the distribution is unchanged because the value of sigma remains constant. You will notice this effect with no math behind it by simply observing the graphic above. Notice how the old mean value (through the light blue curve) lies at the tail end of the new distribution. Whereas under the old distribution this value was the mean, now it is a distant outlier under the new distribution, and therefore under said new distribution, the likelihood of observing that value in the data is diminished. Thus, that value as represented as a call strike price should now be much lower under the new distribution than under the old distribution, as the likelihood of said strike becoming ITM upon expiration has been reduced greatly.
Theta
Out-of-the-money strikes (OTM) have no intrinsic value, only extrinsic value, sometimes referred to as time value. The longer the periodicity of expiration, the greater the probability that the underlying stock will move far enough to become ITM and/or expire ITM. Thus, options with longer dated expirations should, and do, have higher premiums than do those with shorter expirations. These premiums for OTM strikes decay geometrically and at an increasing rate as expiration approaches, with the most rapid decay occuring once the expiration date becomes the "front month" contract, i.e. with 45-30 days to expiration (DTE). Because observances that are farther from the mean are more likely to be seen with a longer periodicity than with a shorter periodicity, the value of sigma changes over time, all else equal, and this changes the shape of the distribution. As seen above, the distribution appears as short and fat with say, 90 DTE, whereas the distribution appears tall and skinny with 30 DTE. Observances far from the mean become ever more unlikely to be seen as the distribution is squeezed, and thus the premium on those OTM strikes decreases over time.
Vega
Vega refers to implied volatility (IV or vol) of the underlying, which is essentially the same thing as variance, which is used to calculate sigma. Higher IV = higher variance = larger sigma = short and fat distribution. Thus, because observances farther from the mean become increasingly likely to be seen as IV increases, the premium of those strikes (really ALL strikes) increases. This is separate from the effect of theta that continuosly squeezes the distribution, and will most of the time supercede said effect. This is because time decay happens at a predictable rate whereas IV changes constantly from day to day. Therefore, even though there may only be 10 or 15 DTE, the distribution can be relatively short and fat, so long as IV is high. And again, as IV contracts, all else equal, the premium of strikes declines, and vise versa.
Calculating Probability of Profit (PoP)
Simultaneously to calculating the probability of an option expiring ITM, one can calculate their PoP with the simple Z-score method. It only depends on which side of the transaction one is on, buyer or writer. Because this is so rudimentary, a single, short example will suffice:
My Process - Outlined
I trade options as if they were insurance products for two outcomes; protection against loss of opportunity (calls) and protection against loss of capital (puts). In this way, options should be more expensive the greater the risk to the issuer/writer of them expiring in-the-money (ITM). This is because the writer shoulders the risk of having to go into the market and buy shares or lose his already owned shares should he be called away, which can happen at any time before or upon expiration. The same goes for puts, instead the writer would have to buy shares at a huge premium to the current price should his contract be exercised. In exchange, the writer collects a premium, which should be higher the greater the risk of assignment.
If option prices are conceptually priced based on their probability of expiring ITM, how does one determine that probability and therefore a specific price? Well, Black-Scholes for one, but you don't need to know anything about that formula to understand the probabilities.
There are five sensitivities that option prices react to, known as the Greeks. Only three of them are of any real importance, with one of them only coming in to play when there is a short time before expiration. They are delta, theta, vega, gamma, and rho. Delta, theta, and vega play the largest role in determining the probability of options expiring ITM.
In order to demonstrate this precisely, I will use graphics of Normal Distributions:
Standard Distribution
The standard normal distribution is nothing more than a simplified histogram, in which the curve seen above is just "draped" on top of random observances. The gray line shows where the mean of the data lie, which is always the center so that 50% of observances are above the mean and 50% are below. The shape of the curve is determined by the standard deviation (sigma) of the data. The larger the value of sigma, the shorter and fatter the distribution will be, as there is a greater chance of observing a value that is more distant from the mean value.
Delta
Delta has the effect of shifting where the distribution lies on the number line by changing the mean value. When evaluating probabilities in the stock market, I always use the current going price of the stock as the mean value, with trading software calculating the value of sigma. When the price of the stock goes down, the mean value does too, and so the entire distribution of observances over a given periodicity moves accordingly. However, all else equal, the shape of the distribution is unchanged because the value of sigma remains constant. You will notice this effect with no math behind it by simply observing the graphic above. Notice how the old mean value (through the light blue curve) lies at the tail end of the new distribution. Whereas under the old distribution this value was the mean, now it is a distant outlier under the new distribution, and therefore under said new distribution, the likelihood of observing that value in the data is diminished. Thus, that value as represented as a call strike price should now be much lower under the new distribution than under the old distribution, as the likelihood of said strike becoming ITM upon expiration has been reduced greatly.
Theta
Out-of-the-money strikes (OTM) have no intrinsic value, only extrinsic value, sometimes referred to as time value. The longer the periodicity of expiration, the greater the probability that the underlying stock will move far enough to become ITM and/or expire ITM. Thus, options with longer dated expirations should, and do, have higher premiums than do those with shorter expirations. These premiums for OTM strikes decay geometrically and at an increasing rate as expiration approaches, with the most rapid decay occuring once the expiration date becomes the "front month" contract, i.e. with 45-30 days to expiration (DTE). Because observances that are farther from the mean are more likely to be seen with a longer periodicity than with a shorter periodicity, the value of sigma changes over time, all else equal, and this changes the shape of the distribution. As seen above, the distribution appears as short and fat with say, 90 DTE, whereas the distribution appears tall and skinny with 30 DTE. Observances far from the mean become ever more unlikely to be seen as the distribution is squeezed, and thus the premium on those OTM strikes decreases over time.
Vega
Vega refers to implied volatility (IV or vol) of the underlying, which is essentially the same thing as variance, which is used to calculate sigma. Higher IV = higher variance = larger sigma = short and fat distribution. Thus, because observances farther from the mean become increasingly likely to be seen as IV increases, the premium of those strikes (really ALL strikes) increases. This is separate from the effect of theta that continuosly squeezes the distribution, and will most of the time supercede said effect. This is because time decay happens at a predictable rate whereas IV changes constantly from day to day. Therefore, even though there may only be 10 or 15 DTE, the distribution can be relatively short and fat, so long as IV is high. And again, as IV contracts, all else equal, the premium of strikes declines, and vise versa.
Calculating Probability of Profit (PoP)
Simultaneously to calculating the probability of an option expiring ITM, one can calculate their PoP with the simple Z-score method. It only depends on which side of the transaction one is on, buyer or writer. Because this is so rudimentary, a single, short example will suffice:
Z = (X - mean)/sigma
A Z-score is a value that represents how far your observance is from the mean, as measured by the number of standard deviations (sigmas) it is from the mean. In this case, Z = 1.25, meaning 110 is 1.25 sigmas from the mean. We can then use this to calculate the PoP for both the writer and buyer of the 110 strike call using a Z-score calculator online, which is 89.43% for the writer and 10.56% for the buyer. For the seller, we use the area to the left of the strike for such a calculation, because the writer does not want the price to exceed 110 upon expiration. For the buyer, the right side is used, because he wants to see the price of the underlying exceed 110 upon expiration. However, it should be noted that this simple example is not perfect as it does not account for the premium of the hypothetical 110 strike call. To really calculate the PoP, you would need to find your break even point upon expiration and use that value as your observation in the Z-score formula.
From Understanding to Trading
The process then for trading options follows directly from these statistical concepts, but first you have to make one assumption; stock prices are random and unpredictable, thus we are able to use normal distribution in evaluating probabilities of prices occurring in the future. In short, what I do is sell OTM strikes when IV is high relative to itself with about 45 DTE in liquid underlyings, and in doing so I attempt to remain "delta neutral" on said underlyings.
Now for the explanation. First, you have to start with what "IV high relative to itself" means. IV is a percentage value that reflects how much the underlying is expected to range from the current price over the next 52 week period. This percentage value of course has its own normal distribution, as IV percentages are random if we assume that stock prices are random. Because of this, I seek to sell IV when it is high, i.e. when it is on the tail end of the distribution (above the 50th percentile). Doing so provides ample premium, due to the vega effect. As time passes, IV is more likely to contract towards the 50th percentile, or the mean, than it is to continue to increase. This process is known as "mean reversion," and is explained by simply re-explaining what a mean is. The mean is the most frequent occurrence/observation in a distribution, hence why it is located in the center and at the peak of the distribution. Because it is the most frequent observation, as time progresses, observances are more likely to come down towards the mean than they are to go up away from it, and vise versa. Thus, the premium for the OTM strikes declines and as the writer, I gain from IV contraction.
In that explanation, I mentioned the passage of time twice. As the writer of the contract, I gain from the passage of time. So, simultaneously, I gain from time passing and IV contracting. I look to sell as close to 45 DTE as possible because, as outlined earlier, that is when the time decay accelerates the most.
Liquid underlyings simply refers to underlyings where the spread between the bid and ask quotes on the contracts is not so large that I cannot quickly and "painlessly" enter and exit into positions. You don't want to end up with large unrealized gains, measured by your cost basis against the mid-price of the contract or spread, only to have them eaten away when attempt to realize them by exiting the position at a price inevitably higher or lower than the mid-price.
Remaining "delta neutral" is paramount to my strategies because as noted earlier, I assume stock prices are random and unpredictable. Because I don't know where the price of a stock is going to go for any periodicity, it is best to remain delta neutral and profit from the passage of time and the contraction of volatility, as those two processes are much more reliable. In doing so, the discretionary element of which trade to take is completely removed. One can easily screen with proper software for stocks with high IV and 45 DTE, whereas searching for directional opportunities will inevitably require your own interpretation. Often times, you will see patterns that don't actually exist, and attempting to trade from that perspective will only result in maybe a 50% success rate, if you're decent and a 55-60% success rate if you are great. With my process, success rates are likely to range from 70-80% over the long term. Why?
Returning to statistical analysis, we know that roughly 68% of all observances fall between the -1 and +1 sigma values for any normal distribution, regardless of shape. So, selling a +1 sigma strike call and a -1 sigma strike put to form a "strangle" spread will have a 68% PoP at current IV levels and DTE. As time passes and IV contracts, all else equal, the PoP of such spread can dramatically increase, as illustrated below:
The red lines mark the +1/-1 sigma range under the light blue distribution, where IV and DTE are both higher than under the dark blue distribution. As both IV and DTE decrease, the distribution becomes taller and skinnier and, all else equal, the probability of observing the light blue +1/-1 sigma values under the dark blue distribution decreases. Ergo, what was once a 68% probability range becomes much higher.
Doing this process over and over is a practical application of the "central limit theorem." A single sample of 10 trades that, regardless of IV, are 1 sigma strangles should have a success rate of 68%. However, due to the randomness of markets, it may only be that 4 were successful as opposed to the anticipated 6.8 or 7. The next sample of 10 such trades may produce 6 successful trades, and the next after that produces 9, then 5, then 7, and so on. In essence, it is more likely that 100 such trades will be closer to the anticipated 68% success rate than a sample of 10. If such trades are done in underlyings with high and then contracting IV, the success rate will inevitably increase from 68%. That is the edge of my process, plain and simple.
In order to apply the CLT, lots of trades have to be made over the course of time. Each position should risk a small and consistent portion of the capital at hand, which could be measured with margin requirements for the positions or by their defined risks if such spreads are made. It should then be expected that over time you will have more "winners" than "losers." And finally, due to the possible utilities of options, one can reduce the amount lost from the losing trades so that the overall process is quite profitable over time.
Wrapping Up
There are many more elements to my process in regards to trade selection and risk management, but this is only an outline. None of the information expressed above is stolen from any investor in some book or trading course found online. It is just the application of statistical analysis in trading assets that, in my view, were designed with such analysis in mind. It is purely quantitative and eliminates the discretionary element from trading, which means that I do not rely on chart patterns or indicators. I put this understanding of options trading together myself with the assistance of supplemental educational material found online. None of it is plagiarized. Please do not plagiarize this work yourself.
Written by Brandon Powers, Bachelor of Arts in Economics, Ohio State University
June 7, 2016
Monday, June 6, 2016
In Times of Low Volatility, You Have to Get Creative ...
I've been active for almost two months now, due mostly to the lack of volatility across the markets but also due to personal reasons. Most of my experience in tradin options is in strategies that are utilized in times of high IV. The rest of it is in directional swing trading. However, directional opportunities are hard to spot and scan for, plus their PoP is inherently 50%. High IV strategies fare much better, but not when IV is low!
So now I'm experimenting with calendar spreads in paper trading. Calendar spreads involve selling a call or put in a month closer to expiration while simultaneously buying a call or put (correspondingly) in a month further from expiration at the same strike. This allows the spread to benefit from the passage of time and the increase of volatility over the life of the short leg. While PoP may initially be low, as IV increases, PoP also increases. This is because the back month long leg benefits more from an increase in IV than the front month short leg is harmed by increasing IV. Calendar spreads are also delta neutral, but can be tailored to be slightly delta positive or negative. This is done by "mismatching" the strikes. For example, instead of selling the July 200 and buying the August 200 call, one would sell the July 98 and buy the August 102 call, thereby collecting a credit instead of paying a debit and therefore profiting from down moves in the underlying.
Observe these risk profiles:
The top profile is of a calendar and the bottom is of a bearish diagonal. Which one to choose depends on risk tolerance and on your directional assumption. Calendars require less capital than (credit) diagonals because calendars are debit spreads, meaning their maximum loss is capped. This is not so for a credit diagonal, and therefore at the expense of higher PoP, diagonals require more margin ~ about double that of a calendar.
You may be asking, "if diagonals collect a credit AND have a slightly higher PoP, why not always use them over calendars?" The answer is that diagonals have a very close break even point to where the current underlying is trading, so you are in effect trying to pick the peak of a move and catch a downswing. If the underlying moves much higher, you're sunk. In addition, because of the strike and expiration mismatch, the effects of the delta and gamma cause the price of the spread to vary more than does a calendar on a day to day basis. If after a week you decide that you in fact did not call the top, the spread would be trading at more of a discount to your cost basis than would a calendar, of which the price of the spread does not vary much over the course of time.
For these reasons, it would be wise to use calendars over diagonals most of the time, unless the underlying is significantly overbought or oversold. (as measured by Bollinger Bands and RSI correspondence). And even then, it might be more advantageous to just buy a put spread with a 50% PoP rather than sell a diagonal, but that's up to you whether you want theta on your side, which depends on your view of the velocity of the potential downswing, and if you think vol will expand significantly enough to warrant the extra margin.
OK this is getting complicated. Basically, it's best to remain delta neutral as much as possible unless otherwise signaled by measurements of price. Ergo, calendars > diagonals in most situations. Both are outmatched by the iron condor, however, it is unwise to trade iron condors in times of low IV because they benefit from contracting IV, not expanding.
So now I'm experimenting with calendar spreads in paper trading. Calendar spreads involve selling a call or put in a month closer to expiration while simultaneously buying a call or put (correspondingly) in a month further from expiration at the same strike. This allows the spread to benefit from the passage of time and the increase of volatility over the life of the short leg. While PoP may initially be low, as IV increases, PoP also increases. This is because the back month long leg benefits more from an increase in IV than the front month short leg is harmed by increasing IV. Calendar spreads are also delta neutral, but can be tailored to be slightly delta positive or negative. This is done by "mismatching" the strikes. For example, instead of selling the July 200 and buying the August 200 call, one would sell the July 98 and buy the August 102 call, thereby collecting a credit instead of paying a debit and therefore profiting from down moves in the underlying.
Observe these risk profiles:
The top profile is of a calendar and the bottom is of a bearish diagonal. Which one to choose depends on risk tolerance and on your directional assumption. Calendars require less capital than (credit) diagonals because calendars are debit spreads, meaning their maximum loss is capped. This is not so for a credit diagonal, and therefore at the expense of higher PoP, diagonals require more margin ~ about double that of a calendar.
You may be asking, "if diagonals collect a credit AND have a slightly higher PoP, why not always use them over calendars?" The answer is that diagonals have a very close break even point to where the current underlying is trading, so you are in effect trying to pick the peak of a move and catch a downswing. If the underlying moves much higher, you're sunk. In addition, because of the strike and expiration mismatch, the effects of the delta and gamma cause the price of the spread to vary more than does a calendar on a day to day basis. If after a week you decide that you in fact did not call the top, the spread would be trading at more of a discount to your cost basis than would a calendar, of which the price of the spread does not vary much over the course of time.
For these reasons, it would be wise to use calendars over diagonals most of the time, unless the underlying is significantly overbought or oversold. (as measured by Bollinger Bands and RSI correspondence). And even then, it might be more advantageous to just buy a put spread with a 50% PoP rather than sell a diagonal, but that's up to you whether you want theta on your side, which depends on your view of the velocity of the potential downswing, and if you think vol will expand significantly enough to warrant the extra margin.
OK this is getting complicated. Basically, it's best to remain delta neutral as much as possible unless otherwise signaled by measurements of price. Ergo, calendars > diagonals in most situations. Both are outmatched by the iron condor, however, it is unwise to trade iron condors in times of low IV because they benefit from contracting IV, not expanding.
Thursday, April 28, 2016
LNKD and STX Earnings
LNKD and STX both announce(d) earnings on 4/28 post market and 4/29 pre market. LNKD beat expectations, and at first the stock launched higher from 123 at the close to I think a 142 handle at its peak! Then, it took a dive and last I saw it was around 131. My range is 107 - 140, and they expire at the end of the day on 4/29. It will probably have a volatile open tomorrow, and I hope it remains in that range, however I'm not afraid to pay commissions to lock it in.
STX had a big down move about a month ago, but surprisingly IVP has dropped considerably heading into earnings. Because the OTM contracts have non-existent liquidity, I sold an ATM iron condor, and the position has a 1:1 risk/reward ratio. I don't have a lot of confidence in this position, and honestly I probably should not have put it on, but it will serve as a hopefully cheap experiment on using ATM iron condors in earnings.
STX had a big down move about a month ago, but surprisingly IVP has dropped considerably heading into earnings. Because the OTM contracts have non-existent liquidity, I sold an ATM iron condor, and the position has a 1:1 risk/reward ratio. I don't have a lot of confidence in this position, and honestly I probably should not have put it on, but it will serve as a hopefully cheap experiment on using ATM iron condors in earnings.
Tuesday, April 19, 2016
Woa! It's Been Awhile!
Over the past month I've been busy with "life" stuff and have neglected to post on the blog about my recent trades. I went dormant from March 16 onwards. I had a profitable GDX iron condor and 3 earnings trades two weeks ago, of which two were profitable and one was a scratch.
The account is now up 1.12% which is great since at one time it was down 2.24%. That's not great but it's also not terrible. I had to climb out of that hole while simultaneously dealing with declining volatility across markets, giving me fewer opportunities to make up ground.
Now that it is earnings season, there are some opportunities to sell high IV. Although I prefer not to trade events/earnings, you have to go where the vol is when you're and options trader. So today I took off a profitable trade in HOG after they reported earnings this morning and also just put on an earnings position in TXT. [Stocktwits stream]
The idea behind earnings trades is to capture the collapse in IV that occurs right after earnings are announced. To best capture this phenomena, sell premium on both sides to be delta neutral. Then, when IV collapses, take the position off the next morning. It's usually a fairly easy way to make quick money, however, sometimes stocks can move wildly and outside their expected ranges if they miss or beat earnings estimates significantly. Additionally, in order to best capture the IV collapse, the shortest available DTE contracts should be traded. This means that position sizing should be a fraction of what it is on a normal position, because stocks can move larger than expected and there is little time to adjust a losing position, if it can be adjusted properly whatsoever.
With the VIX trading around 13.5, it looks as though earnings trades are going to be what I'm doing for the remainder of the season. I don't think volatility across the market will pick up until June, maybe, if the Fed decides to hike rates. Or there is more bad news out of China ... you never know. But through most of 2015 the VIX remained low ... that is until it spiked to FIFTY in late August, a level not seen since 2011/2008. When vol comes back into the market it is more than likely to do so in a big way.
The account is now up 1.12% which is great since at one time it was down 2.24%. That's not great but it's also not terrible. I had to climb out of that hole while simultaneously dealing with declining volatility across markets, giving me fewer opportunities to make up ground.
Now that it is earnings season, there are some opportunities to sell high IV. Although I prefer not to trade events/earnings, you have to go where the vol is when you're and options trader. So today I took off a profitable trade in HOG after they reported earnings this morning and also just put on an earnings position in TXT. [Stocktwits stream]
The idea behind earnings trades is to capture the collapse in IV that occurs right after earnings are announced. To best capture this phenomena, sell premium on both sides to be delta neutral. Then, when IV collapses, take the position off the next morning. It's usually a fairly easy way to make quick money, however, sometimes stocks can move wildly and outside their expected ranges if they miss or beat earnings estimates significantly. Additionally, in order to best capture the IV collapse, the shortest available DTE contracts should be traded. This means that position sizing should be a fraction of what it is on a normal position, because stocks can move larger than expected and there is little time to adjust a losing position, if it can be adjusted properly whatsoever.
With the VIX trading around 13.5, it looks as though earnings trades are going to be what I'm doing for the remainder of the season. I don't think volatility across the market will pick up until June, maybe, if the Fed decides to hike rates. Or there is more bad news out of China ... you never know. But through most of 2015 the VIX remained low ... that is until it spiked to FIFTY in late August, a level not seen since 2011/2008. When vol comes back into the market it is more than likely to do so in a big way.
Wednesday, March 16, 2016
EWZ Crashes, and I'm out
Closed EWZ call spread today for 0.20 profit around 9:45am. Now the only position left on is GDX. Volatility is down across all markets, so it might be a little while before I reload and take on more trades. The only place you will see high vol right now is in individual stocks due to earnings season. I have not decided whether I will play earnings at all in this account, as they can be frustrating and stressful. I may place some paper trades and see how they do, and might change my mind going into Q2 earnings season.
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