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GLD Short Put 45 DTE Leveraged Options Backtest

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GLD-Total-Return-vs-GLD-45-DTE-Short-Put-L-overall
5 min read

In this post we’ll take a look at the backtest results of opening one GLD short put 45 DTE leveraged position each trading day from Jun 3 2008 through Nov 4 2019 and see if there are any discernible trends. We’ll also explore the profitable strategies to see if any outperform buy-and-hold GLD.

There are 10 backtests in this study evaluating over 28,566 GLD short put 45 DTE leveraged 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.

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

MU – Micron Technology, Inc.

QQQ – Nasdaq 100 Index

SLV – iShares Silver Trust

SPY – S&P 500 Index

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

VZ – Verizon Communications Inc.

Other

Methodology

Core Strategy

  • Symbol GLD
  • Strategy Short Put
  • Start Date 2008-06-03
  • End Date 2019-11-04
  • 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 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.

Delta sensitivity at different expiration horizons.

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

GLD Short Put 45 DTE L 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

GLD Short Put 45 DTE L margin utilization

Early management yielded a lower average margin utilization across all strategies when compared to 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

GLD Short Put 45 DTE L 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

GLD Short Put 45 DTE L win rate

Managing trades early underperformed holding till expiration with regard to win rate; 50D was an exception.

The higher the delta, the lower the win rate.

Annual Volatility

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Monthly Returns

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Max Drawdown

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Drawdown Days

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Average Trade Duration

Managing trades at 50% max profit or 21 DTE yielded trade durations less than half the duration of hold-till-expiration.

Compound Annual Growth Rate

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Sharpe Ratio

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Profit Spent on Commission

GLD Short Put 45 DTE L profit spent on commission

13.99% – the blended average percent of profits spent on commission across all option strategies.

Total P/L

GLD Short Put 45 DTE L total profit and loss

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

GLD Short Put 45 DTE L overall performance

All option strategies were profitable.

Discussion

Let’s take a look at the total and risk-adjusted returns from this strategy and compare them against a cash-secured implementation.

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Unlike the trend among leveraged equity backtests performed to date, applying leverage to GLD doesn’t appear to create the same material widening of sharpe ratios across strategies.

However, what does seem to be consistent is that lower delta strategies get a boost in risk adjusted returns while higher delta strategies experience a loss in risk-adjusted returns.

Summary

Systematically opening 45 DTE leveraged short put positions on GLD was profitable no matter which strategy was selected.

The 5D @ 50% max profit or 21 DTE strategy had the greatest risk-adjusted return among the option strategies.

The 16D @ hold-till-expiration and both 30D strategies outperformed buy-and-hold on both total and risk-adjusted return.

50D @ 50% max profit or 21 DTE outperformed buy-and-hold on total return and matched risk-adjusted returns.

Thanks for reading 🙂

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

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2 Comments

  1. Alex
    April 27, 2020 @ 2:02 am

    Thanks a lot for these backtests. They are the best I’ve seen on the internet.

    Is it possible to do a long call backtest on SPY?

    Reply

    • spintwig.com
      April 27, 2020 @ 12:44 pm

      You’re welcome! Happy to hear they’re of value.

      Sure — I’ll add it to the list!

      Reply

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