# SPY Short Put 45 DTE Leveraged Options Backtest

In this post we’ll take a look at the backtest results of opening one SPY short put 45 DTE leveraged position each trading day from January 3 2007 through July 26 2019 and see if there are any discernible trends. We’ll also explore the profitable strategies to see if any outperform buy-and-hold SPY.

There are 40 backtests in this study evaluating over 75,300 SPY 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.

- 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 SPY
- Strategy Short Put
- Start Date 2007-01-03
- End Date 2019-07-26
- Positions opened 1
- Entry Days every trading day in which entry criteria is satisfied
- Timing 3:46pm ET
- Strike Selection
- 2.5 delta +/- 2 delta, closest to 2.5
- 5 delta +/- 2 delta, closest to 5
- 10 delta +/- 2.5 delta, closest to 10
- 16 delta +/- 3 delta, closest to 16
- 30 delta +/- 3.5 delta, closest to 30
- 50 delta +/- 4 delta, closest to 50

- Trade Entry
- 2.5D short put
- 5D short put
- 10D short put
- 16D short put
- 30D short put
- 50D short put

- Trade Exit
- 25% max profit or 21 DTE, whichever occurs first
- 50% max profit or 21 DTE, whichever occurs first
- 75% 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 than holding till expiration.

### Margin Utilization

Early management yielded a lower average margin utilization.

Hindsight bias was used in to maximize Reg-T margin utilization for each strategy. This allows for a “best case” scenario, baring the limitations of backtesting such as no margin calls, for the option strategy to outperform relative to the benchmark.

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

### Premium Capture

The higher the delta, the lower the premium capture.

Early management yielded lower rates of premium capture than holding till expiration.

### Win Rate

Managing trades early provided mixed results for the win rate and tended to perform better with higher-delta positions.

The riskier the trade the lower the win rate.

### Annual Volatility

Volatility increases as delta increases.

Holding till expiration yielded lower volatility on the 50D strategies.

### Monthly Returns

Early management improves average monthly returns in most scenarios.

The less risky the strategy the softer the best and worst months.

### Max Drawdown

Managing at 75% max profit or expiration yielded the most severe drawdowns. Looking at the 10D strategy, there’s a 3.66x difference in max drawdown between managing at 25D & 21 DTE vs 75% & expiration.

### Drawdown Days

Early management reduces the drawdown duration compared to holding till expiration. Managing at 75% max profit yielded the longest drawdown duration.

### 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

Managing trades early outperformed holding till expiration for the 30D and 50D strategies.

### Sharpe Ratio

The 2.5D @ 50% max profit or 21 DTE strategy had the greatest risk-adjusted return.

### Profit Spent on Commission

8.95% – the blended average percent of profits spent on commission across all option strategies.

### Total P/L

Higher delta strategies yielded more profit than lower delta strategies.

Holding till expiration yielded greater profits than managing early on the 2.5D, 5D, 10D and 16D strategies.

### Overall

All option strategies were profitable.

## Discussion

By applying leverage to the SPY short put 45 DTE trade one is able to generate total returns in excess of buy and hold. In contrast, the cash-secured SPY short put 45 DTE strategies were not able to achieve total returns in excess of buy-and-hold SPY.

While we’re talking about performance, let’s compare the Sharpe ratio between the leveraged and cash-secured strategies.

By applying leverage we experience a wider distribution of Sharpe ratios vs a cash-secured implementation.

Since SPY represents the market performance of the ~500 largest companies in the US, I hypothesize this phenomenon of wider Sharpe ratios for leveraged option strategies will manifest itself in backtests of other large-cap underlying.

The best news thus far is that the **16D hold-till-expiration strategy outperforms buy-and-hold SPY on both a risk-adjusted and total return basis AND the strategy is net profitable** (not to be confused with USO, for example, which outperforms in both categories but is overall unprofitable). A runner up is the 30D 25% max profit or 21 DTE strategy, which matches risk-adjusted performance but outperforms on total return.

## Summary

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

**For risk-parity and total return outperformance** of buy-and-hold SPY, implement the **30D 25% max profit or 21 DTE** leveraged short put strategy.

**For a smoother ride and total return outperformance** of buy-and-hold SPY, implement the **16D hold-till-expiration 45 DTE** leveraged short put strategy.

Thanks for reading 🙂

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

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Tomaz

March 13, 2020 @ 6:00 am

Thanks for this study. One question/suggestion which I think could help leverage and simple strategy a lot. Selling only when price above SMA200. Can you do a backtest on this? A lot of trendfollowers and also big institutions use this and if you check back, biggest drawdowns always happen with price below SMA200 (or any similar number).. If one stops selling or / and immediately exits all open positions when price is below SMA200 or maybe when end of month it is below etc.. There are many variations but if you look at 2008 selloff for example, most of the carnage and VIX spike happened when price was already below SMA200 for quite some time…

Could you test something like that?

spintwig.com

March 13, 2020 @ 2:14 pm

You’re welcome!

I could, but I think the results will be similar to selling IV is at or above/below “x” value. While working on this study I explored selling in various IV environments and no matter how I binned the results (note: manipulating the bins to yield a desired outcome is precisely why I avoid studies based on indicators – it’s curve fitting and enables manipulating results to match a narrative) there was no particular strategy that was above the rest.

I realize me stating this outcome is quite different from me publishing a study that shows the outcome. Once I’m able to produce and publish studies using automation, variations similar to what you mentioned might be on the roadmap.

pdadi

March 13, 2020 @ 12:30 pm

I couldn’t figure out optimal leverage ratio from your research. Am I missing something?

spintwig.com

March 13, 2020 @ 2:35 pm

I’d use the respective

average margin utilizationas the recommended leverage ceiling. For example, a 50% average margin utilization equates to 2.5x leverage; each position assumes the margin requirement is 20% of notional exposure.The optimal leverage ratio in hindsight will be different depending on the point in time being evaluated. The average margin utilization values are the result of tuning each strategy such that it brushes up against a potential margin call but never breaches Reg-T limits (assumes no VIX expansion risk or broker policy changes during times of market stress).

Tomaz

March 17, 2020 @ 6:13 am

I have problems understanding leverage returns here too. 30 delta leveraged return vs unleveraged managed at 25 % or 21DTE show very different results, 56 % vs 247 % total return. But lets say you starti with 100.000 USD account and use unleveraged version. Because you open positions every day, would you not tap into leveraged with that too? I mean after 10 days you can have 10 short SPY positions open and on 100.000 account that is already using leverage, because you can only have 3-4 if you take 100.000$ account.

So my question would be ok normal version just sold 1 SPY 30 delta option each day. Leveraged version sold how many? 2-3 options each day? I know this can change how many options were opened at any different time because of closing at 25 % profit, but if I want to use this strategy of 30 delta with leveraged version, becuase is recovers 3x faster, has shallower drawdowns and better returns, how many options would I have to sell each day on 100.000 USD account? I think 100.000 USD is just barely enough for unlevered version if one sells option each day, let alone to use leveraged verison. But at your end grapf with leveraged and unleveraged both start at 100.000 USD.

maybe you can dumb this down for some of us readers that have problems understanding this. Also as you wrote for some other reader, margin is calculated as 20 % of notional and when I look at 30 delta option with 25 % profit target, it uses about 27 % which would again indicate no leverage most of the time. If you stay below 30 % average margin utilisation and 20 % is anyway used as soon as you open even 1 position, then I see no leverage usege. Or maybe just slight to get from 20 % to 27 % margin utilisation, but then how can returns be so different compared to “normal” version where also no leverage is used but returns are substantially less.. And if version one sells one option each day, how many does version 2 sell for 30 delta for example..

I think I am missing something here please help me out 🙂

spintwig.com

March 25, 2020 @ 2:05 pm

If starting with a 100k portfolio and opening a position daily, yes, one will eventually become leveraged (and/or the account will fail to support additional positions). Similarly, suppose you have enough capital for “half” an option contract – do we calculate a return on idle cash or do we find a creative way to obtain exposure to half an option contract via delta hedging?

The solution to both of these issues is to calculate returns using a “daily average.” I speak to it in the methodology section of the cash-secured studies. The takeaway is that the results should be viewed as if you’re investing in an ETF that implements the given strategy. In practice, the larger the portfolio the closer the results will be to what’s shown in the calculations, and similarly, the smaller the portfolio the greater the potential variance from the depicted results.

Agree – at today’s prices 100k would only be able to support 3-4 positions at a time, at which point one would have cease opening new positions until the existing ones are closed due to leverage. Individually it may be difficult to mirror the strategy and consequently the results. I do have some institutional subscribers so they may be better positioned to realize the returns.

As for the 27% average margin utilization, that implies a 1.35x ( 27 / 20 ) leverage factor which is in the ballpark of TastyTrade research (see slides 4 and 5 for 1ST strangles at https://www.tastytrade.com/tt/shows/market-measures/episodes/pushing-the-limit-capital-allocation-05-17-2018).

Something to keep in mind is that 27% (1.35x) is the

averageutilization. It will dip lower as multiple positions close during an upswing / vol crush event and will be higher during times of market stress. In general we’re maintaining ~35% more exposure / returns and at times the margin utilization is 100% or 5x, so this is where the outsized gains come from vs a cash-secured strategy. Both strategies open a single position daily.Hopefully this helps!

Ivan

May 12, 2020 @ 12:03 pm

Hi there,

When you say ‘manage’ the trade at 21 DTE, what does this exactly entail? Closing the trade and opening a new one, or rolling further out or up/down strikes?

Thanks

spintwig.com

May 12, 2020 @ 3:25 pm

“Managing” the trade means closing the position.

For order entry, the strategy opens a new position daily. For order exit, the position is closed when the respective criteria is met.

Noobie

May 14, 2020 @ 9:35 pm

Wonderful analysis , thanks spintwig! If one were to remove the emotionality from the picture and acknowledge the higher volatility, would the 50D with 25% exit make the most sense from a CAGR perspective?

spintwig.com

May 17, 2020 @ 12:18 am

Thanks, glad to hear it’s useful! It would (assuming short puts are your tool of choice to generate returns)!

Just keep in mind the backtest was run with highlight bias. During times of drawdowns the portfolio was within $100 or less of getting margin called.

Noobie

May 19, 2020 @ 5:12 pm

Thank you, that is something to think about in these black swan event times. If I were to hazard a guess, would put spreads be a viable alternative? Those drawdown risks don’t exist albeit at a significant hit to maximum profit. Would you have any backtested wisdom about that?

spintwig.com

May 22, 2020 @ 3:33 pm

There are a several ways to approach risk management.

One strategy is to start at order entry by selecting a delta that aligns with your risk profile. Another is to change the option strategy from short puts to spreads. In both scenarios, position sizing (number of open positions) as well as % of margin utilization is important. The margin collateral itself – whether it’s held in SPY or BIL positions – makes a material difference too.

There are a a lot of variables that go into optimizing a strategy. If the goal is total returns at the expense of an increase in volatility, have you considered a simple 1.25x leveraged play by purchasing SPY on margin or using futures such as /ES or MES? It will roughly match the CAGR of the 30D @ 25% max profit strategy while requiring significantly less time on your part as well as substantially lower amounts of leverage and consequently lower margin call risk. Tax efficiency will also be superior.