EEM Short Put 45 DTE Cash-Secured Options Backtest
In this post we’ll take a look at the backtest results of opening one EEM short put each trading day from Jan 3 2007 through August 6 2019 and see if there are any discernible trends. We’ll also explore the profitable strategies to see if any outperform buy-and-hold EEM.
There are 10 backtests in this study evaluating over 31,200 EEM short put trades.
Let’s dive in!
Contents
Prior Research
Basics
How to Trade Options Efficiently Mini-Series
Backtesting Concepts
Building a Research Framework
AAPL – Apple Inc.
- AAPL Short Put 0 DTE Cash-Secured
- AAPL Short Put 45 DTE Cash-Secured
- AAPL Short Put 45 DTE Leveraged
- AAPL Long Day Trade
AMZN – Amazon.com, Inc.
BTC – Bitcoin
C – Citigroup Inc.
DIA – SPDR Dow Jones Industrial Average
- DIA Short Put 7 DTE Cash-Secured (coming soon)
- DIA Short Put 7 DTE Leveraged (coming soon)
- DIA Short Put 45 DTE Cash-Secured (coming soon)
- DIA Short Put 45 DTE Leveraged (coming soon)
DIS – Walt Disney Co
EEM – MSCI Emerging Markets Index
GE – General Electric Company
GLD – SPDR Gold Trust
IWM – Russel 2000 Index
- IWM Short Put 7 DTE Cash-Secured
- IWM Short Put 7 DTE Leveraged
- IWM Short Put 45 DTE Cash-Secured
- IWM Short Put 45 DTE Leveraged
- IWM Long Day Trade
MU – Micron Technology, Inc.
QQQ – Nasdaq 100 Index
- QQQ Short Put 7 DTE Cash-Secured
- QQQ Short Put 7 DTE Leveraged
- QQQ Short Put 45 DTE Cash-Secured
- QQQ Short Put 45 DTE Leveraged
SLV – iShares Silver Trust
- SLV Short Put 45 DTE Cash-Secured
- SLV Short Put 45 DTE Leveraged (coming soon)
SPY – S&P 500 Index
- SPY Long Put 45 DTE Optimal Hedging
- SPY Long Call 45 DTE
- SPY Long Call 730 DTE LEAPS
- SPY Short Put 0 DTE Cash-Secured
- SPY Short Put 0 DTE Leveraged
- SPY Short Put 0, 7, 45 DTE Leveraged Comparison
- SPY Short Put 2-3 DTE M,W,F “BigERN Strategy” (guest post)
- SPY Short Put 7 DTE Cash-Secured (coming soon)
- SPY Short Put 7 DTE Leveraged
- SPY Short Put 45 DTE Cash-Secured
- SPY Short Put 45 DTE Leveraged
- SPY Short Put 45 DTE Leveraged binned by IVR (coming soon)
- SPY Short Vertical Put Spread 0 DTE (coming soon)
- SPY Short Vertical Put Spread 45 DTE
- SPY Short Call 0 DTE Cash-Secured
- SPY Short Call 0 DTE Leveraged
- SPY Short Call 45 DTE Cash-Secured
- SPY Short Call 45 DTE Leveraged
- SPY Short Straddle 45 DTE
- SPY Short Strangle 45 DTE
- SPY Short Iron Condor 45 DTE
- SPY Wheel 45DTE
- Making Money in Your Sleep: A Look at Overnight Returns
- A Bad Case of the Fridays: A Look at Daily Market Returns
T – AT&T Inc.
TLT – Barclays 20+ Yr Treasury Bond
TSLA – Tesla, Inc.
USO – United States Oil Fund
VXX – S&P 500 VIX Short-Term Futures
- VXX Short Call 45 DTE Cash-Secured
- VXX Short Call 45 DTE Leveraged
- VXX Short Vertical Call Spread 45 DTE
VZ – Verizon Communications Inc.
Other
Methodology
Core Strategy
- Symbol EEM
- Strategy Short Put
- Start Date 2007-01-03
- End Date 2019-08-06
- Positions opened 1
- Entry Days every trading day
- Timing 4pm ET (EOD pricing)
- 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
Days Till Expiration
Some studies look at ultra-short-duration option strategies while others explore longer durations. The nuances and range for each approach are summarized below.
0 DTE Strategies
Between 0 and 3, closest to 0.
The range is up to 3 days from expiration for two reasons: to allow opening positions on Friday that have a Monday expiration and to allow more opportunities for occurrences of strategies focused in the 10-40 delta range. As expiration nears, it becomes increasingly difficult to open positions in this range.
This visual from Options Playbook does a great job illustrating the concept. Notice how at 1 DTE delta jumps from .50 to .10 with a single dollar change in the underlying. Compare this to the 60 DTE scenario where the change in delta for a $1 change in underlying is much smaller. By allowing positions to be opened as far out as 3 DTE, delta sensitivity to $1 differences in strikes becomes muted.
7 DTE Strategies
Between 3 and 11, closest to 7.
The range is 4 days either side of 7 to ensure a position can be opened each trading day while remaining true to the duration target. For example, opening a position Wednesday will have either a 2 DTE horizon (next Friday) or a 9-DTE horizon (the Friday after next). In this scenario the 9-DTE position would be selected.
45 DTE Strategies
Between 28 and 62, closest to 45.
The range is 17 days either side of 45 to account for quadruple witching. As the end of each calendar quarter approaches, namely during the last 7-10 days of Mar, Jun, Sep and Dec, the expiration dates of option contracts widen significantly.
730 DTE Strategies (LEAPS)
Between 550 and 910, closest to 730.
The range is 180 days either side of 730 to account for underlying that have LEAPS expirations in 6-month increments.
Calculating Returns
Returns are calculated daily using notional returns. The change in daily values of the option is divided by the stock price at the time of order entry.
The formula for daily return is:
option profit / opening stock price.
For example, suppose we opened a XYZ short put at $1.10 on 1/3/2007 with a stock price of $50:
- On 1/4/2007, our option increased to $1.50. The notional daily return calculation would be ( $1.10 – $1.50 ) / $50 = -.008 which is -.8% daily return on 1/4/2007
- On 1/5/2007 our option decreased to $0.80. The notional daily return calculation would be ( $1.10 – $0.80 ) / $50 = .006 which is .6% daily return on 1/5/2007
By using notional returns on daily stock values when calculating returns we isolate the performance of the option strategy from the effects of leverage. This allows us to identify strategy performance in a non-margin context such as in a US-based retirement account.
By measuring strategy performance as a daily percentage change we abstract the strategy performance from absolute dollar gain/loss to a relative percentage value. This is a fancy way of saying the strategy becomes capital agnostic. In other words, think of an ETF that executes the respective option strategy. We can allocate $100 to the “option ETF” and $100 to the underlying and have an apples-to-apples, dollar-for-dollar comparison.
Monthly and Annual Returns
To identify the monthly and/or annual returns for an option strategy, the respective daily returns are summed.
Graphing Underlying and Option Curves
The underlying position derives its monthly performance values from Portfolio Visualizer. Portfolio returns are calculated in a compound fashion using this monthly data.
Option strategies derive monthly performance values from the backtesting tool by summing the respective daily returns. Portfolio returns are calculated using the following formula:
( backtest starting capital * monthly return ) + portfolio balance
Margin
Margin requirements and margin calls are assumed to always be satisfied and never occur, respectively.
In practice the option strategy may experience varied performance, particularly during high-volatility periods, than what’s depicted. Margin requirements may prevent the portfolio from sustaining the number of concurrent open positions the strategy demands.
Moneyness
Positions that become ITM during the life of the trade are assumed to never experience early assignment.
In practice early assignment may impact performance positively (assigned then position experiences greater losses) or negatively (assigned then position recovers).
Commission
The following commission structure is used throughout the backtest:
- 1 USD, all in, per contract:
- to open
- to close early
- expired ITM
- 0 USD, all in, per contract expired OTM / worthless
While these costs are competitive at the time of writing, trade commissions were significantly more expensive in the late 2000s and early 2010s.
In practice strategy performance may be lower than what’s depicted due to elevated trading fees in the earlier years of the backtest.
Slippage
Slippage is factored into all trade execution prices accordingly:
- Buy: Bid + (Ask – Bid) * slippage%
- Sell: Ask – (Ask – Bid) * slippage%
The following table outlines the slippage values used and example calculations:
- A slippage % of .50 = midpoint
- A slippage % of 1.00 = market maker’s price
Inflation
All values depicted are in nominal dollars. In other words, values shown are not adjusted for inflation.
In practice this may influence calculations that are anchored to a particular value in time such as the last “peak” when calculating drawdown days.
Calculating Strategy Statistics
Automated backtesters are generally great tools for generating trade logs but dismal tools to generate statistics. Therefore, I build all strategy performance statistics directly from the trade logs. Below is a breakdown on how I calculate each stat and the associated formula behind the calculation.
Win Rate
Trades that were closed at management targets (profit, DTE) as winners but became unprofitable due to commissions are considered non-winning trades. This phenomenon is typically observed when managing 2.5D and 5D trades early.
( count of trades with P/L > 0 ) / count of all trades
Annual Volatility
The standard deviation of all the monthly returns are calculated then multiplied the by the square root of 12.
STDEV.S(monthly return values) * SQRT(12)
Worst Monthly Return
Identify the smallest value among the monthly returns:
MIN(monthly return values)
Average P/L per Day
This measures changes in capital efficiency due to early management.
( average P/L per trade ) / average trade duration
Average Trade Duration
This measures the average number of days each position remains open, rounded to the nearest whole day.
ROUND ( AVERAGE ( trade duration values ) , 0 )
Compound Annual Growth Rate
This measures the compounded annual rate of return, sometimes referred to as the geometric return. The following formula is used:
Sharpe Ratio
Total P/L alone is not enough to determine whether a strategy outperforms. To get the complete picture, volatility must be taken into account. By dividing the compound annual growth rate by the volatility we identify the risk-adjusted return, known as the Sharpe ratio.
strategy CAGR / strategy volatility
Profit Spent on Commission
The following formula is used to calculate the percent of profits spent on commissions:
If a strategy is depicted as having percent greater than 100, this means the strategy is unprofitable due to commissions but would have been profitable if trades were commission free throughout the duration of the backtest.
If a strategy is depicted as “unprofitable” this means the strategy lost money even if trades were commission free throughout the duration of the backtest.
Total P/L
How much money is in the portfolio after the study? This stat answers that question and depicts it as a %
( portfolio end value / portfolio start value ) - 1
Scope
This study seeks to measure the performance of opening short put positions and will interpret the results from the lens of income generation relative to buy-and-hold EEM.
The utility of the short put strategy as a portfolio hedging tool or other use will not be discussed and is out of scope.
Results
Win Rate
Managing trades early lowered the win rate.
The riskier the trade the lower the win rate.
Annual Volatility
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Worst Monthly Return
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Average P/L Per Day
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Average Trade Duration
Earlier management results in shorter trade duration.
Lower-risk trades reach profit targets faster than higher-risk trades.
Compound Annual Growth Rate
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Profit Spent on Commission
18.83% – the blended average percent of profits spent on commission across all short put strategies.
Total P/L
The riskier the trade the greater the P/L.
Early management caused underperformance across all strategies.
Overall
Five of the short put option strategies outperformed the buy-and-hold approach.
Discussion
This is the first study conducted where a basic, systematic, cash-secured (i.e. non-leveraged) option strategy outperforms the underlying across both the greatest drawdown and greatest rally in recent history.
If you’re looking to gain exposure to ex-US / emerging markets, this appears be a viable approach with potential opportunity.
As for why this works and hasn’t been arbitraged away, well, I’m not sure. I’ll be happy to speculate and participate in that conversation in the comment section below. If you’re looking for a data-supported answer, I unfortunately don’t have it.
Something I intend to do in the near future is look at leveraged implementations of the best performing, on a risk-adjusted basis, strategy from each study and see how they would have performed.
Summary
Systematically selling short puts on EEM is profitable.
Five of the EEM short put option strategies outperformed the buy-and-hold approach both on a risk-adjusted and absolute basis. Adding leverage may further enhance performance and will be evaluated in future studies.
The 16D strategy held till expiration had the best risk-adjusted return of all short put strategies.
Thanks for reading 🙂
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Thoughts? Feedback? Dedications? Shoutouts? Leave a message in the comments below!
August 30, 2019 @ 7:00 am
Interestingly, you can tell me how much margin is needed for this approach?
45 days to execution = 6.4 weeks.
This is again 32 trading days.
One EEM = 40$
Volume at peak is therefore 32*40$*100 pieces = 128k
Margin 20% = 26k
So doubled for safety = 52k
Is that right?
August 30, 2019 @ 8:37 am
Sure!
Using the 16D hold-till-expiration strategy, the maximum number of open positions at any time was 44. This occurred twice: Nov 20 2009 and Nov 19 2010. On those days the notional exposure was $154,200 and $182,800 respectively. These would be your stress points, ignoring any buying power expansion risk due to iv fluctuations. Assuming 20% margin requirement, we’re looking at $30,840 and $36,560 + any buffer / safety margin.
August 30, 2019 @ 9:38 am
Thank you so much for your super work.
When I think about it, the question is why.
You have tested the same strategy on several underlyings EEM, IWM, SPY… these are all big indices… the results go in a similar direction – but vary slightly.
Now we have an overperformance.
Why should the EEM be better than the other in the future?
There is no rational explanation for that, is there?
I think the short put strategy is pretty good in itself.
Proposition: Because the strategy is so good and you test different underlyings, there will always be some that outperform over long periods of time. But I think that these changes will… maybe in the next 10 years the SPY will be the Winner
August 30, 2019 @ 10:34 am
My thought is 1) EEM experienced enough volatility to keep premium received relatively high, particularly from Jan 2012 through Jan 2015 while 2) the movements up or down were short in duration. These two attributes appeared to allow the option strategy to outperform while the underlying essentially went nowhere.
Over the course of 2017 alone EEM closed the gap and eventually outperformed the 16D strategy. From 2018 onward it again begin to underperform.
You’re on to something with the testing of different underlying. Indeed, some will simply outperform while others will underperform. My hypothesis was all the indices would underperform; we now see that hypothesis is false.
I’ll eventually start exploring individual stocks. Curious to see whether the general trend for the option strategies is to outperform, underperform, or yield comparable performance relative to buy/hold.
August 31, 2019 @ 7:24 am
In my opinion, individual stocks could be just as interesting, even if the analyses are more elaborate.
Will you test David’s SPY Put Write Stop strategy? I read about it in the Ern blog comments. With the stops at 2x,3x and 5x premium…?
We have only 1 year so far… Does not say so much so far…
September 3, 2019 @ 3:24 pm
Yes, I’ll add it to the list. Looking to get the TLT and VXX studies out the door this and next Friday, respectively. I may be able to make it for the following Friday.
David’s strategy revolves around VIX – when below a given threshold trade ~2DTE and when above a given threshold trade ~45DTE.
Keeping consistent with previous methodology, I’ll test the 45DTE strategy with 1-5x stop losses and compare against early mgmt with no stop losses and holding till expiration. That should cover all the bases.
Let me know if I’m overlooking anything or if there are any adjustments I should make to the approach.
September 9, 2019 @ 2:11 pm
The SPY short put study has been updated with 1x-5x stop loss details.
https://spintwig.com/spy-short-put-strategy-performance
September 11, 2019 @ 4:39 am
Great, there’s another thing. DTE! ERN is a big follower always only the shortest distance to act, so 2 days. You are relatively fixed in your evaluations on 21 days. He explains why shorter periods are better. Whether then each day must be acted is questionable. Interesting is from Friday on Monday on Wednesday on Friday… This evaluation would be in my eyes the final examination.
September 11, 2019 @ 4:43 am
Sorry not 21 – i meant 45 Days
September 23, 2019 @ 12:16 am
It’s on the list 🙂
February 22, 2020 @ 10:28 am
Premiums on lower deltas are pretty low. Its even worth doing it for such a low premium. Looks like 16D is sweetspot. Comments?
February 22, 2020 @ 3:57 pm
Agree. 16D has the best risk-adjusted returns so it’s a great starting point for implementing int’l exposure in a portfolio.
The nice thing is, if you’re targeting a specific amount of volatility as opposed to a specific amount of return (great for managing sequence of returns risk), there are several strategies to choose from that outperform buy/hold without using leverage. It all comes down to your goal(s).
January 28, 2021 @ 1:47 pm
I’ve been looking at a strategy that can be applied in an IRA where margin cannot be used (were generating any alpha with cash secured options is almost impossible) so this would be a good possible option to look more into. Any other recommendations based on your studies?
January 28, 2021 @ 7:45 pm
Yes, this would be a viable choice if the portfolio seeks exposure to international equities. Alternatively, I’m partial to an allocation toward individual mREIT preferred shares.
https://spintwig.com/cumulative-income-investing-in-preferred-shares/