AAPL Short Put 45 DTE Cash-Secured Options Backtest
In this post we’ll take a look at the backtest results of opening one AAPL short put 45 DTE cash-secured position each trading day from January 3 2007 through August 30 2019 and see if there are any discernible trends. We’ll also explore the profitable strategies to see if any outperform buy-and-hold AAPL.
There are 10 backtests in this study evaluating over 31,700 AAPL short put 45 DTE cash-secured trades.
Let’s dive in!
Contents
Summary
Systematically opening short put positions on AAPL was profitable no matter which strategy was selected.
All AAPL short put strategies underperformed buy-and-hold AAPL with regard to total return.
Methodology
Strategy Details
- Symbol: AAPL
- Strategy: Short Put
- Days Till Expiration: 45 DTE +/- 17, closest to 45
- Start Date: 2007-01-03
- End Date: 2019-08-30
- Positions opened per trade: 1
- Entry Days: daily
- Entry Signal: N/A
- Timing: 3:46 ET
- Strike Selection
- 5 delta +/- 4.5 delta, closest to 5
- 10 delta +/- 5 delta, closest to 10
- 16 delta +/- 6 delta, closest to 16
- 30 delta +/- 8 delta, closest to 30
- 50 delta +/- 8 delta, closest to 50
- Trade Entry
- 5D short put
- 10D short put
- 16D short put
- 30D short put
- 50D short put
- Trade Exit
- 50% max profit or 21 DTE, whichever occurs first
- Hold till expiration
- Max Margin Utilization Target (short option strats only): 20% | 1x leverage
- Max Drawdown Target: 99% | account value shall not go negative
Assumptions
- Margin requirements are always satisfied
- Margin calls never occur
- Margin requirement for short CALL and PUT positions is 20% of notional
- Margin requirement for short STRADDLE and STRANGLE positions is 20% of the larger strike
- Margin requirement for short VERTICAL SPREAD positions is the difference between the strikes
- Early assignment never occurs
Mechanics
- Prices are in USD
- Prices are nominal (not adjusted for inflation)
- All statistics are pre-tax, where applicable
- Margin collateral is held as cash and earns no interest
- Assignment P/L is calculated by closing the ITM position at 3:46pm ET the day of expiration / position exit
- Commission to open, close early, or expire ITM is 1.00 USD per contract
- Commission to expire worthless is 0.00 USD per contract
- Commission to open or close non-option positions, if applicable, is 0.00 USD
- Slippage is calculated according to the slippage table
- For comprehensive details, visit the methodology page
Results
Win Rate
Managing trades early lowered the win rate.
The higher the delta the lower the win rate. 5D was an exception due to commission drag.
Annual Volatility
An active subscription is needed to view this content. Already a subscriber? Log in. Not a subscriber? Sign up for just 99 USD a year. Learn more.
Worst Monthly Return
An active subscription is needed to view this content. Already a subscriber? Log in. Not a subscriber? Sign up for just 99 USD a year. Learn more.
Average P/L Per Day
An active subscription is needed to view this content. Already a subscriber? Log in. Not a subscriber? Sign up for just 99 USD a year. Learn more.
Average Trade Duration
Managing trades at 50% max profit or 21 DTE yielded average trade durations less than half those of holding till expiration.
Higher-delta positions took longer to reach profit targets than lower-delta positions.
Compound Annual Growth Rate
An active subscription is needed to view this content. Already a subscriber? Log in. Not a subscriber? Sign up for just 99 USD a year. Learn more.
Sharpe Ratio
An active subscription is needed to view this content. Already a subscriber? Log in. Not a subscriber? Sign up for just 99 USD a year. Learn more.
Profit Spent on Commission
10.98% – the blended average percent of profits spent on commission across all short put strategies.
Total P/L
Early management outperformed holding till expiration with regard to total return. 5D and 10D were exceptions.
The higher the delta the higher the total return.
Overall
All short put strategies were profitable.
Discussion
AAPL is one of the largest companies, as measured by market cap, in the S&P 500 at the time of writing. It’s no surprise the strong performance of AAPL left the 45 DTE option strategies in the dust. Of course, hindsight is 20/20.
By implementing an early management mechanic we were able to “cycle” capital much faster than a hold-till-expiration approach. By implementing shorter-dated strategies, such as 2-DTE options, it may be possible to capture more of the upside despite the additional gamma and whipsaw risks inherent with short-duration trades.
Update: the AAPL short put 0-DTE Cash Secured study is now available.
Additional Resources
Private, Custom Backtests
Discover your edge with private, custom backtests for as little as 99 USD. Learn more or contact us for a quote.
Trade Logs
Visit the trade log store and download the data used in this and other backtests.
s1 signal
Trade S&P 500 options more efficiently using the s1 signal. Learn more.
s2 signal
Trade GLD options more efficiently using the s2 signal. Learn more.
s4 signal
Trade Russell 2000 options more efficiently using the s4 signal. Learn more.
mREIT Preferred Share Dashboard
High-yield, low-beta alternatives to cash or treasury bills. Learn more.
Consultations
Schedule a consultation to review your specific scenario and get direct answers to your questions.
-
AAPL short put 45 DTE Bundle$49.99
October 4, 2019 @ 8:52 am
Not that it makes a huge difference here, but your commission numbers are now high. $0.65 per contract is the new new, as of this week.
October 4, 2019 @ 3:44 pm
Maybe. Given the much higher commission costs during the mid-to-late 2000s, I think the blended average of $1/trade is still an optimistic approach for at least another few years.
I’m loving the new cost structures at IBKR, Schwab, TD and E-Trade. It’s nice to see things get shaken up.
October 4, 2019 @ 7:05 pm
Oh interesting, the historical commission rates hadn’t occurred to me. I think I disagree. The value of the backtest is to show what you might expect your results to be going forward, so it makes sense to me to use current (or even optimistic) prices. I would also be in favor of simulating weekly and M/W expiration for years where they didn’t exist.
Here’s something else I’ve been thinking about:
What about a backtester that shuffles actual stock market moves? Normalize the stock prices, and shuffle them up by quarter. That way you’re defeating any curve fitting, and at the same time you’re using data that’s similar to real data rather than completely random.
October 6, 2019 @ 12:11 pm
I’ve been building a turnkey spreadsheet model for backtesting leveraged strategies that I intend to publish in the coming days via an announcement post. Commissions are fixed at $1 each way as this is how the source data in the trade logs is calculated and delivered. I can override this by building an “adjustable commission cost” feature. This should take care of the commission preference 🙂
Interesting idea. I’m not sure I understand the intent though. One could argue a shuffled return profile of an actual underlying is the actual return profile of a hypothetical (or by chance a different actual) underlying. If the goal is to evaluate option strategy performance in aggregate as opposed to seeing isolated performance on a single underlying, we would want to execute the same strategy on multiple underlying and compare results.
This probably is a good segway into the scorecard I’ll be publishing and announcing in the next update post.
October 16, 2019 @ 7:51 pm
Question: what does removing the effects of leverage from an options backtest demonstrate? I’m not a mathematician. The whole point of options is leverage, right? So…if you take that out, then what is being demonstrated. I ask because I’m wondering what I’m missing here that I should be taking away…
October 17, 2019 @ 1:21 pm
Not necessarily. For most retail traders it is indeed about leverage. However, options also serve as hedging instruments and tools to potentially lower portfolio volatility. The latter is the chief focus when it comes to mitigating sequence of returns risk.
For our purposes here:
-It demonstrates performance in a non-margin account such as US-based retirement accounts and other cash-secured scenarios around the world.
-It allows us to identify which strategy is worth leveraging. Because applying leverage [usually negatively] impacts the Sharpe ratio due to the friction costs and mechanics of leverage, we want to identify strategies that already outperform the underlying on a risk-adjusted basis before scaling up.
-It allows us to compare an option strategy against a non-leveraged buy/hold portfolio of different asset allocations. For example, if a traditional 80/20 stock/bond portfolio matches the Sharpe ratio of a non-leveraged option strategy, we can then ask which yields a greater return.
Now that I finally have the backtest builder launched, we can start plugging in the risk-adjusted winners and see how they stack up. Tomorrow’s post will be the first to include results from the new backtest builder. I’ll be eager to hear your thoughts and feedback.