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Option System: 2021 Year-End Review

The 2021 metrics still show good system health! January is already looking strong, and we have some amazing success stories below of trades we repaired in 2021.


The Readout.


Below are the numbers for all trades in 2021. That includes all closed trades as well as all of the open ones. We regularly provide stats for our closed trades in our daily emails and on Twitter, but we know that our subscribers are curious about what the stats would look like if we marked all of our open positions as of the last closing price. We have done this below.


For the 317 trades that were open on December 31, we acted as though the option expired on that date. That is, we marked each position to the current stock price at the close. If the stock price was 5% below our breakeven on a trade, then we marked a 5% loss for that trade. If the stock price was above the strike, then we marked a gain according to our GTC exit. If the stock was between the breakeven and the strike, then we marked a proportional gain (stock price ÷ breakeven - 1).


The results of all trades (closed and open) in 2021 are below:

As you can see, with all 3183 trades that closed in 2021 and marked to market on December 31, we are showing substantial overall returns. Our average trade was 0.44% and average duration was 24.9 calendar days. Out of all trades, 93.18% were either closed wins or were open trades showing a positive cushion on December 31 (cushion is calculated as (stock price ÷ breakeven) - 1.) By contrast, only 6.82% of all trades were either a closed loss or were open trades having a negative cushion on December 31.


The median trade was a gain of 1.80% -- the median being the number where half of the trades were higher and half were lower. Below is a histogram showing that the vast majority of trades are grouped around the 1% to 5% range:



To note, only 25 of our trades were actually closed losses in 2021. The remaining "losses" in the histogram were actually open trades that were still under repair as of December 31. We invite you to review our blog post on trade repair showing how we do trade repairs. For example, we had seven different trades on BBIG $4 J21 puts that were showing losses of more than 20% as of December 31. However, we closed these BBIG $4 puts on Friday (January 14, 2022) for gains ranging from 6% to 11%! And BBIG is still down nearly 50% from when we entered the trade back in October. The magic of selling options!


A breakdown of the deciles of trade returns is also illuminating:

This means that 10% of all trades were below 0.51%, and 10% of all trades were above 4.66%. The remaining 80% all fell between those numbers.


The Vital Signs: "Win Factor" and "Win Rate Factor"


When we go to the doctor for a check-up, they take our blood pressure, heart rate, etc. These "vital signs" are critical for determining your overall health. We have vital signs for our trading system: the "win factor" and "win rate factor." They tell us whether the system as a whole is making money or not.


Win factor is the ratio of the average loss size (in %) to the average win size (in %). Conceptually, this tells us how often we need to win in order to be profitable, given the average sizes of our wins and losses. For example, if our average win is 2% and our average loss is 10%, then we must win at least 5 times as often as we lose in order to break even, i.e., the five wins (2% x 5) would counteract the one loss (-10%). If we win more often than the win factor, then we are profitable. Conversely, if we win less often than the win factor, then we are not profitable. We want the win factor to be as small as possible so that we don't have to win very often in order to make money.


"Win factor" must be compared to the "win rate factor," which is the ratio of the win rate (in %) to the loss rate (in %). If a trading system wins 80% of the time, then its win rate factor is 80%/20% = 4.0.


Simply put, if the win rate factor is bigger than the win factor, then we are profitable because it means we are winning more often than we need to, given the size of our wins and losses. In our system, our win factor is: 27.87% ÷ 2.51% = 11.11. That's a lot higher than it was in September and it shows how difficult December has been. However, our win rate factor is even higher: 93.18% ÷ 6.82% = 13.67. Given the sizes of our wins and losses, we only need to win 11.11 times for every loss, but we are winning 13.67 times for every loss, on average. This means the system is overall profitable.


Average Profit/Loss Per Day Is A Critical Metric For Measuring Performance


As we noted in our Seeking Alpha article, the most important metric for measuring system performance is average P/L per day. Many people caluclate this by dividing the average trade size (in %) by the average trade duration (in days). Another way to measure performance is to calulate the P/L per day for each trade separately and then take the average of those values. Each of these provides a metric for annualized rate of return, but they are very different. Below is a mathmatical expression showing the difference in the calculations:

The metric on the left measures the annual rate of return assuming that one places each trade consecutively, i.e., one after the other. All of your money is fully invested in each trade until the trade ends, and then the next trade is done, etc. This is not at all how we trade our system, so we don't observe this metric. It's artifical and doesn't reflect the reality of trading, in our opinion.


The metric that better reflects our view of reality is the one on the right, where we average each P/L per day and then multiply by 365 to get an average of annualized rate of return. This reflects the average of the all the annualized return rates for each trade, and is a far more accurate metric for our system because we make many trades at the same time. This metric assumes that all the trades are done as they are signaled. On a daily level, we measure "Avererage P/L per day" or "APLD."


We use APLD as our main indicator of returns. Our APLD of 0.266% per day is amazing. You can calculate an annualized return rate by multiplying APLD by 365: this gives 97.17% as the average annualized rate of return for all trades in 2021. The median is still a high 54%.


Managing and exiting positions: trade management/repair tools


As we explained in our last blog post, selling options uniquely gives us an advantage versus holding shares. We get to renegotiate our contracts every time they come up for expiration. What we find is that in most cases, we are able to roll our trades out even if the underlying stock has moved strongly against us and even pushing us into the money.


The main tools that we use are:


(1) The rollout. This is when you buy back the old option and sell a new one at the same strike that expires later. You can almost always do this for a "net credit," meaning you sell the new option for more than you pay to buy back the old one. Money comes in the door, rather than goes out, and the trade stays open. If the stock recovers, then you win. If the stock keeps falling, then you can keep rolling. Unless the stock goes to zero, you will eventually catch it. In fact, all the stock has to do is level out somewhere, because every time you roll for a credit, you lower your cost basis.


(2) The rollout and down. This is when you buy back the old option and sell a new one that expires later, and also at a lower strike. If you can move your strike lower for a net credit, you get money and a bigger cushion too.


(3) The rollout, down, and double. If a trade has gone really sour, like if your underlying stock fell by 50% or more (like our winning BBIG trade described below), you still have a tool to improve the trade. You can buy back the old options and sell twice as many contracts of a new option at a lower strike and a later expiration, again for a net credit. This means you have to invest more in the trade but it can dramatically lower your costs basis. From the new lower strikes, you can then use rollouts to potentially turn your mega loss into a mini loss or a win.


(4) The wheel. For puts that go deep in the money, it can be hard to rollout for a credit. In this case, you can permit assignment of shares, and then write calls on those shares to earn more premium and continue to reduce your costs basis. This is known as "the wheel." If your call strikes are below your cost basis, you must continue to roll them to avoid losses. As you roll them, you can collect more premium until your cost basis falls below the strikes.


More Real Examples Of Trade Management In Action


About 12.9% of our trades in 2021 had to be rolled out. Half of them closed out in 2021 and the other half continued into 2022. Of the rollouts that closed in 2021, 88.4% of them were winners. The average closed roll lasted almost 75 days and had an average annualized rate of return of about 20%. The table below has more details:

We gave a number of examples in our last blog post of trades we were able to turn into wins even though the underlying stock fell substantially and never recovered. Below are other examples that occurred since Labor Day (these are just examples; there are more):


BBIG. stock fell more than 50% and we made 6% to 11% profit. In mid-October, over the course of several days, we signalled seven different trades to sell $4 puts on BBIG expiring in November. BBIG was trading over $8 per share at the time. December arrived and BBIG tanked below $3 to a low of $2.54, a decline of nearly 70%! We rolled to November, to December, and again to January, collecting $1 or more of credit (per contract) along the way, lowering our cost basis dramatically. Eventually, just in the past week, BBIG jumped up to about $4.2 and our trade exited for wins ranging from 6% to 11% profit over about 90 days, for an annualized rate of return of about 25% to 43%. We didn't have to wait for BBIG to fully recover -- it is still nearly 50% lower than when we entered.


VIVO: stock fell nearly 25% and we made 4.73% profit. This is one of our longest repairs of the year, but we still made an 11.8% annualized rate of return. On April 1, we signalled to enter covered calls on VIVO with a $25 strike expiring April 16. VIVO was trading over $28 that day, but then VIVO began a rapid decline into and during the summer, reaching a low around $17.35 in July. That's a fall of nearly 40%. We rolled the calls to May, June, July, August, September, October, and November, lowering our cost basis every step of the way. On November 18, the trade closed when VIVO was just over $20 for a profit of 7.5% over 232 days. VIVO fell 19.5% from trade entry to exit and we still made off with 11.8% annualized return.


VLTA: stock fell about 15% and we made more than 5% profit. In mid-September when VLTA was trading over $13, we signalled four trades to sell $7 and $9 puts expiring in October. VLTA fell into the $6s in mid-October, a drop of more than 50%! But we rolled to November and collected more premium. VLTA popped back over $11 and we exitted with a 5% profit over about 60 days for a 30%+ annualized rate of return, even though VLTA had still declined 15%.


RXT: stock fell about 12% and we made a 5% profit. In mid-July, when RXT was over $19 per share, we signalled to sell $17.50 puts expiring in August. RXT fell down to about $13 in August, and we signalled a double down on the $17.50 puts, given the enormous premium at the time. Then in September, we allowed the shares to be assigned and we wrote calls on the shares at the $15 strike, collecting more premium. We rolled again to October and November, lowering our basis each time. Finally, we closed for a profit of 4.95% when the stock was around $16.70. Thus, the stock fell 12%, but we made a profit of nearly 5% over over 118 days for an annualized rate of return of 15.3%.


QFIN: stock fell more than 15% and we made a 2% to 6% profit. QFIN was one of our most popular stocks to trade last summer. From July 2 to July 22, we signalled 21 trades on QFIN of various puts and calls, all while QFIN was trading around $28 to $35 per share. QFIN then fell below $17 in August, and then hovered around $20 for a few months. We rolled out each month, patiently lowering our cost basis. Then in mid-November QFIN bounced over $23 and we closed for profits ranging from 2.21% to 6.7% over 112 to 132 days for annualized rates of return of 6.1% to 21.4%. QFIN never fully recovered, but we still made money.


These are just a few examples of how we handle the small minorty of trades that go against us. For the vast majority of winners, we set the GTC exits and forget about them.


For our open rollouts, we will continue to stay patient and roll, roll, roll...


Every Trade In 2021


Below is a spreadsheet showing each and every trade in 2021, with the open trades marked to market price of the underlying on December 31:

NGT 2021 YE Readout
.xlsx
Download XLSX • 1.42MB

Cheers and happy trading!

NGT





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