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Options System Readout YTD To Labor Day And Trade Management Techniques

Updated: Jan 13, 2022

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The August 20 rollous and subsequent weeks really picked the system up, and the current numbers look great. We grabbed more than $100 of premium across the board ($10,000+), not counting the subsequent rolls of QFIN and WPG to October. Our new GTC rollout feature makes some of these rolls easier -- we get them done early for a strong credit when we know we are going to be rolling anyway.

Below are the numbers for all trades year to date through September 3, 2021. That is, all closed trades, but also all of the open ones. We regularly provide stats for our closed trades in our daily emails and on Twitter, but some of you have asked us what the stats would look like if we marked all of our open positions and included them as well. We have now done this below

For the 254 trades that were open on September 3, 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 through September 3 are below:

As you can see, with all 1956 trades signalled in 2021 and marked to market last Friday, we are showing substantial overall returns. Our average trade is 1.94% and average duration 14.0 trading days. 95.09% of all trades were either closed wins or are open trades currently showing a positive cushion (cushion is calculated as (stock price ÷ breakeven) - 1.) By contrast, only 4.91% of all trades were either a closed loss or are open trades currently have a negative cushion.

"Win Factor" and "Win Rate Factor" -- Vital Signs Of The Trading System

When we go to the doctor for a check, they take our blood pressure, heart rate, etc. to see if we are healthy. The "win factor" and "win rate factor" in the table above are vital signs for our trading system. 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. 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; if we win less often than the win factor, then we are unprofitable. 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: 13.93% ÷ 2.76% = 5.05. Our win rate factor is: 95.09% ÷ 4.91% = 19.38. Given the sizes of our wins and losses, we only need to win 5.05 times for every loss, but we are winning 19.38 times for every loss, on average. On the whole, therefore, the system has been very profitable indeed.

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

As we noted in our most recent Seeking Alpha article published last week, 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. Because this is not at all how we trade our system, we don't really observe this metric. It's artifical and doesn't reflect the reality of our trading style. (Nevertheless, it's still high for our system: 1.94% average trade ÷ 14 days average duration x 250 days per year = 34.6% annualized returns, if traded consecutively.)

The metric that better reflects our reality is the one on the right, where we average each P/L per day and then multiply by 250 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 0.4518% per day is fabulous; the system has been working quite well so far this year. You can calculate an annualized return rate by multiplying APLD by 250: this gives 112.96%. You can interpolate a year-to-date (YTD) return as: APLD x number of trading days from January 1 to September 3 = 79.52%.

Below is a histogram showing the number of trades (both open and closed) according to the percentage gain or loss as of September 3, 2021:

Managing and exiting positions

There is a lot of advice out there on how to exit short options trades "correctly." We have found that this "correct" approach can lead to sub-optimal set-ups. That is not to say it is wrong to follow the herd, as these approaches can be good in many circumstances. We feel, however, that following these myths can lead traders to avoid better situations that would provide a higher Expected Value. As we have discussed, "Expected Value" is a mathematical concept used by gamblers to determine whether a bet is worthwhile. We apply this concept to options trading, and you can read more about that in our gambler's post here.

Below are the common myths that we read often about trade exits:

  • Myth #1: Let your winners run. In other words, don't exit your trade early if the stock is moving in the right direction. Let it go to expiry.

  • Myth #2: Cut your losses early. The converse of Myth #1, it is often said that you should cut and run if you're in a losing trade.

  • Myth #3: Avoid assignment of shares when your short puts go in the money. Buy back those puts before expiration so you don't end up holding naked shares of a sinking company.

  • Myth #4: Never sell covered calls at a strike below your cost basis. This locks in a loss if the stock goes up, as your max profit is the strike price.

We disagree with these so-called "rules" of trading, and we violate them all the time.

Here is an example of Myths 1 and 2 being taught:

"Let your profits run" is an expression that encourages traders to resist the tendency to sell profitable positions too early. The flipside of letting profits run is to cut losses early. The way to make money as a trader, according to many, is to follow both of these pieces of advice: to let winners (profits) run their course, and to cut losing bets before they spiral into deep losses.

(Source: While this seems like good advice for exiting a long stock position, when it comes to short options, it isn't always optimal.

Myth 3 relates to assignment of shares from selling puts that have gone in the money. Most people who sell puts hate to have the shares assigned to them, because suddenly cash is taken from their accounts and used to buy shares above the market price. It feels like another loss, but actually it isn't. It's a zero sum event. By the time your short put is in the money, you're already facing a loss. The assignment simply converts your position from a short put into long shares without changing your total account value. As we discuss below, assignment can often be a good thing, rather than something to avoid.

Finally, with Myth 4, we are told not to roll a covered call below the breakeven price because this "locks in a loss":

In a covered call, for instance, we don't want to roll the short call option below the trade's breakeven price. Having the call option's strike price below the breakeven price means we agree to potentially sell stock for less than we bought it for, which would lock in a loss. So, we always want to sell an out of the money call whose strike is above the breakeven price.

(Source: Doughtrading.) We disagree with this myth as well, as rolling a covered call below your cost basis can sometimes be a great tool for repairing a trade gone bad.

Busting Myth 1: Set Tight Exits

You might be surprised by this, but cutting your profits short (like taking 50% profits) can provide a better risk/return profile than letting your positions run until expiry. This is because when you take profits early, you generally have a decent cushion remaining between your strike price and the stock price, whereas if you wait until you hit max profit, then you expose yourself to a greater risk that the cushion falls below your strike.

To be sure, if you set a tight profit taking order, you limit your upside. But you actually improve the Expected Value of the trade. If the stock goes up, you will exit the trade before you get to the option's half-life, so you will earn your profits in less time. That means a higher return rate, than if you waited until expiry. And if the trade goes down, then your profit-taking exit order means you reduce the chance that the put goes all the way in the money before expiration. You can still get out sooner.

Time is the enemy of the short options trader, and the main thing you want to avoid when selling options far below the money, as we do, is what we call "dump risk," i.e., a one-time event that obliterates your position. (In fact, this might be the only risk to our style of options trading.) Thus, we want the least amount of time in the trade to get the highest return per unit time.

As discussed, to measure the performance of our system, we rely on APLD, which is a return per unit time. It is an interesting metric. If your average trade return is 1%, that doesn't tell you much about a trading system. If that 1% trade lasts only one week (5 days) on average, then that's far superior to a trading system with a 5% average trade that lasts two months (40 days). The 1% system has a rate of return of about 50%/year while the 5% system has a rate of return of about 30%/year. Big difference. So you can see that the metric that counts is profits per time. This is why we track APLD as our main performance metric.

Setting exit prices to take profits early has been shown to increase your returns per time. We found this interesting study of 16-delta short puts on SPY over a long period of time. The study found that while absolute profit/loss per trade was lower for trades where 25% or 50% of profits were taken early, there were many more of these trades because they had shorter durations. Making two 2% trades is better than making one 3% trade. The upshot is that when you look at their P/L per 45-day period, you see the maximum returns-per-time occurred with the tightest profit take level of 25%. The 50% profit take level also showed higher returns-per-time than the 75% and 100% profit levels. We found this a bit counterintuitive, but it's one of the main reasons why we take profits early:

(Source: Short Put Management Results from 41,600 Trades | projectoption)

Of course, there are tradeoffs. One might ask: why not close your trade when you've only made 5% of your max profits? In theory, this might be great, but it's not doable in the real world. There is a point of diminishing returns, because the quicker you take profits, the quicker you must trade. Your tiny absolute trade size also makes the bid/ask spreads far more significant.

We have found that a 50% profit-take strikes the best balance between the theory of improved returns-per-time and the practicality of trading in the real world. With our trade selections and using the 50% profit-take, we have seen an average trade duration of 10.9 trading days in 2021.

Don't let your winners run. Cut them short, and replace them with brand new trade set-ups.

Busting Myths 2, 3 and 4: Don't Be So Quick To Cut Your Losses And Run

Remember our blog post about Agent Fast and Agent Slow? We talked about how options selling is unique; it is completely unlike being long on stock. When you sell options, you're like an insurance provider for the underlying stock. Whoever buys your options pays you a premium for that insurance, and you only pay out on the policy if the stock falls below the strike. In our NGT system, we insure two categories of companies: (i) those that are extremely volatile and offering premiums so high that we can sell options with strikes way below the stock's price; or (ii) solid companies for whom people are willing to pay a larger premium than is justified. If the stock does not fall below the strike, then we keep all the premium. If the stock does fall below the strike, then we have to pay out on the policy and we lose.

Actually, we don't have to pay out on the policy if we don't want to. Recall from the blog post how Agent Fast handles all the intake, picking companies and collecting the premium. And recall that Agent Slow waited for one of the companies we trades to fall below the strike. Then she can renegotiate the deal.

Agent Slow can do this with a bunch of tools. Below is a summary of some trade management tools for turning losers into smaller losers or even winners:

(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 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.

(2) The rollout and down. This is when you buy back the old option and sell a new one that expires later, but 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, you still have a tool to improve the trade. You can buy back the old options and sell twice as many (in dollars) 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 -- it is a double-down -- 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.

Real Examples Of Trade Management In Action

We want to recap some examples of trade management that we've been through with you during the year, to show you how it has really worked.

While we discuss these stocks and how we repaired the trades, please keep in mind that we are talking about a small minority of trades. Only 12.3% of our trades have been rolled out, and only 140 of these rollouts -- just 7.16% -- remain open. For our closed rollouts, here are some more stats as of September 3. The stats show that when we have to repair trades that have gone south, more often then note we eventually end up making money:

NEGG: stock fell more than 50%; we still made a 6.6% profit.

On July 9, 2021, we sold $20 puts on NEGG expiring August 20 for $1.65 of premium. At the time, NEGG closed above $46, but by August 2 it hit a low of $16.50. That is a decline of nearly 65%. NEGG then fluttered around $20 and eventually sank to $16.17 the day before our puts were set to expire, and we were facing a 12% loss. Rather than book the loss, we rolled the option out one week to August 27 for a net credit of $0.35 (tool #1). The total premium collected by now was $2, and this let us set a high exit order of $0.80, which we set for "good-until-cancelled" or GTC. NEGG then popped up into the low 20s and we closed out on August 27 for a total gain of 6.6% over 36 trading days. That was a 46.3% annualized return rate. From entry to exit, NEGG fell more than 50%, and we still made 6.6%. The trade repairs tools above allowed us to collect enough premium and renegotiate our deal so we could get out without NEGG having to come all the way back up.

BEKE: stock fell about 25%; we still made a 4.1% profit.

On July 28, we sold BEKE $17.50 August 20 puts for $1.65. BEKE closed at $26.81 that day, but BEKE then cratered in August, falling almost 60% to a low of $15.82 on expiry day. We rolled our puts to September (tool #1) for another $1.25 in credit, which reduced our cost basis to $14.85. This reduction allowed us to set an exit order for the put at a relatively high level ($1.00) so we could exit the trade without needing BEKE to fully recover. BEKE came back up to about $20 by August 26 and our exit order was triggered. From entry to exit, BEKE fell about 25%, but we made 4.1% in 22 trading days, which is an annual return rate of about 46%.

BIG: stock fell 13%; we still made a 3.2% profit.

This shows a longer-term campaign. On April 28, 2021, we bought BIG $65 May 21 covered calls for a net debit of $63.95. At the time, BIG was trading at almost $70. BIG then fell significantly over the next few months. We rolled to May, June, July, and August using rollouts and rollout-and-downs (tools 1 & 2). We collected so much premium, that our cost basis fell to $54.45. On August 20, our calls expired out of the money, but BIG had closed at $56.07, which was above our cost basis. We then sold the shares outright the following Monday at $56.20 for a 3.2% profit over a whopping 84 trading days, for an annualized return rate of 9.6%. BIG fell 13.5% and we made a 3.2% profit: trade management tools allow your bad trades to make good money.

QFIN: stock went nowhere; we made a 5.87% profit.

When QFIN was around $22 in late-July 2021, we bought $20 covered calls for a net debit of $18.90. QFIN then fell more than 25% to as low as $16.01 on August 17, opening a loss on this position of more than 15%. We rolled to September (tool #1) for a net credit of $1.35. Then QFIN went back up to $20 and we rolled again to October for a net credit of $0.50. Our total cost basis was reduced to $17.05, which allowed us to close the trade at $18.05 on August 26 for a gain of 5.87% over 22 trading days, an annualized return rate of about 70%. QFIN closed that day at around $22. Thus, QFIN went nowhere, but we made 5.87%.

EBIX: stock went up 3%; we made an 8% profit.

On April 5, 2021 we sold EBIX April $30 puts for $0.70. At the time, EBIX was trading around $32. EBIX then fell into the 20s, so we rolled to May and then to June. We collected a total premium of $3.15 and were able to close the trade by buying back the June puts for $1.00 on June 8, when EBIX shot back up into the low-30s. In the same time period, EBIX went up about 3%, but we made an 8% profit.

Some trades we have been manading for a long time, but we still haven't closed them. Agent Slow is aptly named; sometimes she takes a while. Sometimes more than a year. But so long as she is making good money repairing trades, we will let her run. Consider IDRA. We sold $3 puts on IDRA back in March when IDRA was trading around $5. IDRA has since fallen 80%. But our IDRA trades are not down 80%. Through trade management we have reduced our cost basis month after month by taking in 5% to 10% returns each month. That is a whopping 60% to 120% annualized return rate. That's why we stick with IDRA. Because ths stock has held a steady floow around $1, we expect to be able to continue rolling until we breakeven around January 2022. If IDRA is still showing good premiums, we may continue to roll it and grab a gain. Again, so long as IDRA stays around $1 and premiums stay as they are, we can get this done. Imagine turning a stock that fell 80% into a breakeven or winner. That is trade management magic.

Similarly, back in July, we sold GOTU $7.50 puts when the stock was trading above $10. GOTU since fell to about $3 and closed at $3.15 on Friday. We allowed GOTU shares to be assigned to us so we could sell calls using the "wheel" (tool #4). Then we sold three times as many $3 puts, which was only a slight increase in our position size (from $750 per contract to $900), and this greatly reduced our cost basis. Then we rolled again to October for a net credit. Now our cost basis is about $3.57, just a 12% loss (even though GOTU fell nearly 70%). So long as GOTU can hold around $3, we expect to be able to roll to the end of the year and reduce this loss more, and perhaps even turn it into a win.

If you got this far, thank you for reading! As always, we welcome questions or comments, so please feel free to email us any time at

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