- 1 Intro
- 2 My Original Strategy:
- 3 My Tweaked Strategy:
- 4 Conclusion
- 5 The Data
I’m just a humble conservative Theta Farmer and this is one of my theta farming techniques. Theta farming can be quite boring, but it can grow consistent income over time.
This is one of my weekly/bi-weekly paycheck trades that I have been doing for a couple of years off and on.
Well, to be honest, I do not put this trade on weekly/bi-weekly. I have a basket of short strangle trades that I select from to trade every Friday based on a few other factors to give me a trading edge.
This backtesting tool is just one more tool to add to my trading edge arsenal.
Why AAPL? Because it has done nothing but gone up over the years and has paid out decent premiums. I also like that the stock has consistently split. This is good so I can keep placing short naked strangle trades on it without having to use up too much buying power.
I am finally getting around to backtesting some of my strategies. Why? In order to tweak them, weed out what does and does not work, and look for how I can potentially squeeze a bit more profit from my trades with the same or less risk. In other words to gain an edge on trading a particular strategy for a particular stock.
As I start to analyze the data I am beginning to see patterns evolving especially when the return on capital is plotted.
My bottom line for using these backtests, is to find a sweet spot where the return on capital is high, drawdowns are small, buying power is minimal, profit/loss ratio is 2:1 or better, and to decrease the average time in the trade. What I found to be the easiest to tweak my strategy is to do a quick look at the return on capital graphs below and find the one that chart that rises smoothly over time. All the other factors appear to fall in line.
I have backtested this trade for the years 2016-2020.
For all my strategies, I paper trade first or will trade live with very limited capital in order to test the functionality of the strategy before I commit fully to it. I believe that backtesting is a necessary tool, but not sufficient to reach any conclusions about a strategy.
All my backtests are based on a starting capital of $100,000.
The cons of backtesting:
- In live trading, you typically will not get filled at mid-prices (So, I set the software between mid-price and market price which is a more realistic trade)
- Backtests are mechanical. I am a real human with real human emotions and will trade on fear and greed and will never trade like a robot.
- My current backtesting does not account for adjusting trades such as rolling. I probably could test for this, but am still learning the software. Maybe at a later date.
- I will make human errors while entering trades. I have fat fingered trades and also have reversed selling and buying puts by accident. I do this the worst on mobile platforms.
- I will never make 100% of what the backtest shows. I would say 70-80% is probably more of a realistic assumption.
- Backtesting does not take into account that I sometimes skew strangles up or down on delta depending on my assumption of the stocks underlying movement and what premium I want to collect.
The pros of Backtesting:
- Backtesting is a tool to help with my assumptions while looking for patterns and cycles of trading.
- Backtesting helps me to weed out poor strategies that do not work
- Backtesting helps me to shape strategies or to tweak what I am already doing in live trading
My Original Strategy:
AAPL 14 dte 7 Delta Strangle
Note: The below numbers would be my original strategy if I traded this every 2 weeks like a robot starting on Jan 21, 2016. This trade is actually terrible until the end of 2019.
For this particular trade, taking Max Profit at 90% with a stop-loss set at 3 times credit received has some pretty big drawdowns and the return on capital was choppy over the years. AAPL gave an overall 44% return on capital over 5 years, but mainly at the end of 2019.
My Tweaked Strategy:
This is the tweaked strategy that I have come up with after analyzing the data.
AAPL 14 dte 7 Delta
Looking at the return on the capital chart, return rises much smoother over time with not many large drawdows. I would have been stopped out more but incurred less loss and would have received more profit over the 5 years tested.
After analyzing the data, I conclude that I will adjust and start trading the AAPL Strangle exiting at 90% Maximum Profit and setting the stop-loss to 150% or 1.5 times credit received. This appears to be the sweet spot with this stock and strategy. It historically would have given me a decent return on capital and drawdowns were not bad, as seen in the corresponding chart below.
My original profit per day, on one option contract, would have been $1.42. My profit using the new strategy is $2.59 per day.
For comparison, I always run the first backtest with no max profit nor stop losses in place. I just let the trade run to expiration. The only time I would ever do this is if I owned the stock. If not, my broker would force me to close this trade out before expiration unless I had the capital to buy the stock. As you can see, placing this trade with no max profit exit or stops in place really does not net much and takes large drawdowns.
5 Year Stats
Closing at 50% Max Profit
The first set of tests I ran was to close out the trade with 50% max profit with comparison stop losses of none, 50, 100, 150, 200, 250, and 300 percent.
I am taking note that the return on capital decreases as the Stop loss increases.
You will see in the chart profile that taking 50% maximum profit and at a 50% stop loss gives smaller drawdowns and better overall return on capital. It smooths out the overall trade.
The trade duration was an average of 6 days which gives us less market exposure. The trade-off is that I have to manage these a little closer.
50% Max Profit, No Stop
50% Max Profit, 50% Stop
50% Max Profit, 100% Stop
50% Max Profit, 150% Stop
50% Max Profit, 200% Stop
50% Max Profit, 250% Stop
50% Max Profit, 300% Stop
Closing at 60% Max Profit
60% Max Profit, No Stop
60% Max Profit, 50% Stop
60% Max Profit, 100% Stop
60% Max Profit, 150% Stop
60% Max Profit, 250% Stop
60% Max Profit, 300% Stop
Closing at 70% Max Profit
70% Max Profit, 300% Stop
Closing at 80% Max Profit
Closing at 90% Max Profit
90% Max Profit, No Stop
90% Max Profit, 50% Stop
90% Max Profit, 100% Stop
90% Max Profit, 150% Stop
90% Max Profit, 200% Stop
90% Max Profit, 250% Stop
90% Max Profit, 300% Stop
Of course, backtesting does not predict future results, but it appears that I left a lot of money on the table with how I was originally trading. Only time will tell while I put these trades on and collect live data results.