IWM Short Put 7 DTE Leveraged Options Backtest

7 min read

In this post we’ll take a look at the backtest results of opening one IWM short put 7 DTE leveraged position each trading day from Jan 3 2007 through Jun 30 2020 and see if there are any discernible trends. We’ll also explore the profitable strategies to see if any outperform buy-and-hold IWM.

There are 10 backtests in this study evaluating over 28,300 IWM short put 7 DTE leveraged trades.

Let’s dive in!

Prior Research

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.

• AMZN Short Put 45 DTE Cash-Secured

BTC – Bitcoin

• BTC Long Day Trade

C – Citigroup Inc.

• C Short Put 45 DTE Cash-Secured

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

• DIS Short Put 0 DTE Cash-Secured
• DIS Short Put 45 DTE Cash-Secured

EEM – MSCI Emerging Markets Index

• EEM Short Put 45 DTE Cash-Secured
• EEM Short Put 45 DTE Leveraged

GE – General Electric Company

• GE Short Put 45 DTE Cash-Secured

GLD – SPDR Gold Trust

• GLD Short Put 45 DTE Cash-Secured
• GLD Short Put 45 DTE Leveraged

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.

• MU Short Put 45 DTE Cash-Secured

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.

• T Short Put 45 DTE Cash-Secured
• T Short Put 45 DTE Leveraged

TLT – Barclays 20+ Yr Treasury Bond

• TLT Short Put 45 DTE Cash-Secured
• TLT Short Put 45 DTE Leveraged

TSLA – Tesla, Inc.

• TSLA Short Put 45 DTE Cash-Secured

USO – United States Oil Fund

• USO Short Put 45 DTE Cash-Secured
• USO Short Put 45 DTE Leveraged
• USO Short Call 45 DTE Cash-Secured

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.

• VZ Short Put 45 DTE Cash-Secured
• VZ Short Put 45 DTE Leveraged

Other

• Cumulative Income: Investing in Preferred Shares

Methodology

Core Strategy

• Symbol IWM
• Strategy Short Put
• Start Date 2007-01-10
• End Date 2020-06-30
• Positions opened 1
• Entry Days every trading day in which entry criteria is satisfied
• Timing 3:46pm 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 expiration, 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 by recording the profit or loss as positions are closed, if any, each day.

Margin Collateral

Portfolio capital is held in cash and earns daily interest at the prevailing 3-month treasury bill rate each day throughout the backtest. The Daily Treasury Yield Curve Rates at the US Department of The Treasury website lists the daily interest rates used in the backtest.

Days for which there are no interest rates available, such as weekends and bank holidays, utilize the last published interest rate. For example, Saturday January 6 2007 and Sunday January 7 2007 do not have interest rates published. The backtest utilizes the rates published on Friday January 5 2007 for both these days.

Calculating Margin Utilization

A running total of the P/L is measured each day and tracks the portfolio performance. Meanwhile, a running total of the notional exposure is measured each trading day and tracks the daily margin utilization.

Margin utilization is estimated as 20% of notional. For example, if there is $100,000 of notional exposure the margin requirement would be $20,000.

Determining Starting Capital

Short Option Strategies

Backtests are run using an arbitrary amount of starting capital to generate a max margin utilization value. Starting capital is then adjusted in $100 increments such that max margin utilization is between 99% and 100%.

To compare the option strategy against the benchmark, an equal starting capital is allocated to a hypothetical buy-and-hold total-return portfolio.

Long Option Strategies

Backtests are run using an arbitrary amount of starting capital to generate a max drawdown value. Starting capital is then adjusted in $100 increments such that max drawdown is between -99% and -100%

To compare the option strategy against the benchmark, an equal starting capital is allocated to a hypothetical buy-and-hold total-return portfolio.

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 in a compound fashion using the monthly values.

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.

Starting Capital

This specifies the minimum portfolio size necessary to successfully execute the trading strategy from the beginning of the backtest.

Average Margin Utilization

Margin utilization ebbs and flows throughout the backtest. This averages the daily margin utilization values.

AVERAGE(daily margin utilization)

Max Margin Utilization

This is the highest recorded daily margin utilization value throughout the backtest. Starting capital is specified to ensure this value resides between 99-100%.

MAX( daily margin utilization )

Max Margin Utilization Date

This is the date in which the highest margin utilization occurs. The formula is an index-match statement to lookup and return the date value associated with the max margin utilization value.

INDEX( all trade dates, MATCH( max daily margin utilization ) )

Premium Capture

This is the percent of premium captured throughout the strategy.

SUM( premium received ) - SUM( options bought back ) - SUM ( losses from immediately selling assigned shares )

Win Rate

Trades that were closed at management targets (profit, DTE) as winners but became unprofitable due to commissions are still considered winning trades. This phenomenon is typically observed when managing 2.5D and 5D trades early.

( count of trades with positive P/L before commissions > 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 )

Average Monthly Return

Identify the average monthly returns.

AVERAGE( monthly return values )

Best Monthly Return

Identify the largest value among the monthly returns.

MAX( monthly return values )

Worst Monthly Return

Identify the smallest value among the monthly returns.

MIN( monthly return values )

Max Drawdown

This measures the greatest peak-to-trough decline, described as a percentage of the portfolio’s end-of-day value (open positions / unrealized P/L is not factored into end-of-day P/L value).

MIN( daily drawdown values )

Drawdown Days

This measures, using nominal (non-inflation adjusted) dollars, the duration in days from the max drawdown trough to previous high.

If portfolio never returns to the high before the max drawdown, “No Recover” is displayed.

ABS( Date of Max Drawdown - Date of Recovery )

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 option positions and will interpret the results from the lens of income generation relative to buy-and-hold.

The utility or effectiveness of options as a hedging tool or other use will not be discussed and is out of scope.

Results

Starting Capital

Early management allows a smaller starting portfolio value since the maxim number of concurrent positions is capped. Less capital is “turned over” faster vs holding till expiration.

Margin Utilization

Early management yielded a lower average margin utilization vs holding till expiration.

Hindsight bias was used to maximize Reg-T margin utilization for each strategy. This allows a “best case” scenario for the option strategy to outperform the benchmark.

Also displayed is the date in which each strategy experienced maximum margin utilization.

Premium Capture

Early management had lower rates of premium capture vs holding till expiration.

The higher the delta the lower the premium capture.

Win Rate

Managing trades early outperformed holding till expiration with regard to win rate.

The higher the delta the lower the win rate.

Monthly Returns

Max Drawdown

Max Drawdown Duration

Average Trade Duration

Managing trades at 50% max profit yielded trade durations roughly half the duration of hold-till-expiration.

Compound Annual Growth Rate

Annual Volatility

Sharpe Ratio

Profit Spent on Commission

23.29% – the blended average percent of profits spent on commission across all option strategies.

Total P/L

Early management underperformed holding till expiration with regard to total P/L.

Higher delta strategies yielded greater total P/L than lower delta strategies.

Overall

All option strategies were profitable.

All hold-till-expiration strategies, as well as 30D and 50D early-management strategies, outperformed buy-and-hold IWM with regard to both risk-adjusted and total return.

Discussion

At face value it appears there may be some opportunities with IWM short put 7 DTE leveraged positions to challenge buy-and-hold IWM. Let me debunk those initial thoughts.

Timing Luck

Timing luck, P/L variance associated with sheer luck, is afoot with this study.

For example, a 45 DTE short put can have the following outcomes:

Similarly, by participating in or abstaining from the market through lucky or unlucky events can also yield material variances in backtest performance.

A popular backtest approach is to open a position then open a new position after the current position is closed – this is known as “rolling.” One can get very lucky or unlucky based on when such a strategy is started. In fact, with a 45 DTE strategy it’s possible to have ~32 different return profiles – one for each trading day in the roll cycle. If you’re pushing a narrative, simply select the return profile that best matches your message and no one’s the wiser.

To mitigate this potential “lying with data” opportunity, two approaches exist: open a position daily which essentially eliminates timing luck or publish a portfolio variance statistic that provides a +/- standard deviation against reported performance. I do the former.

Great, so what does any of this have to do with the backtest results? Glad you asked. Let’s take a look at the number of occurrences by year.

Time in the Market

Looking at the 16D strategy, there were only 100 trades in 2007; monthlies was the only option product that existed at this time for IWM. Consequently, the backtest avoided most of the 2007 global financial crisis. By “luckily” not participating in the market during this time the strategy had a leg up on the buy-and-hold approach.

The options strategy experienced more occurrences as new options products came to market. On June 4 2010 CBOE released Friday-expiring weekly options on IWM.

Due to the lack of product availability during the first few years of the study and thus the inability to execute the option strategy (open a new 7 DTE position daily) for more than 5 trading days per month during and after the GFC, we are forced to accept a material amount of timing luck in the performance results; take these numbers with a grain of salt.

Potential Workaround

What if we start the study at a time when timing luck isn’t a material factor – i.e. after June 4 2010?

We end up with the following P/L curves:

At a glance only the 50D strategies outperform buy/hold on a total return perspective. This however doesn’t take in effect changes in starting capital that occur by shifting the start date.

It could be argued that this is an unfair backtest since it both skips the largest IWM drawdown in recent history and compares a limited-upside strategy (short puts) against the longest bull market in history. This also doesn’t take into effect the differences in margin utilization associated with skipping the GFC.

However, working with the data that’s available should be ample to paint a “good enough” picture to gauge strategy performance and determine whether there are specific strategies worth diving into a little deeper. After all, broad backtests such as what this study contains is an activity of exploration. If something piques one’s interest then a closer look with more refined assumptions can be performed.

Summary

Systematically opening IWM short put 7 DTE leveraged positions was profitable no matter which strategy was selected.

The “10D hold-till-expiration” strategy had the greatest risk-adjusted return among the option strategies.

All hold-till-expiration strategies, as well as 30D and 50D early-management strategies, outperformed buy-and-hold IWM with regard to both risk-adjusted and total return.

Thanks for reading 🙂

Thoughts? Feedback? Dedications? Shoutouts? Leave a message in the comments below!

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