# SPY Long Call 730 DTE Options Backtest (LEAPS)

In this post we’ll take a look at the backtest results of opening one SPY long call 730 DTE position (LEAPS) each trading day from Jan 3 2007 through May 5 2020 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 10 backtests in this study evaluating over 30,000 SPY long call 730 DTE (LEAPS) 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 Long Call
- Start Date 2007-01-03
- End Date 2020-05-05
- 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 long call
- 10D long call
- 16D long call
- 30D long call
- 50D long call

- Trade Exit
- 50% increase in option value 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

All backtests started with a hypothetical $1 million portfolio.

### Win Rate Statistics

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

Higher delta positions had higher win rates than lower delta positions; 5D early management was an exception.

Worth noting is that the number of positions closed differs between exit strategies even though the entry criteria is identical. This is because trades are counted only when they are exited [due reaching a profit target or when the option contract expires].

Since these are 2-year LEAPS positions, hold-till-expiration positions opened after Q1 2018 have not yet expired and therefore are not counted since it’s unknown whether they will be profitable or expire worthless. Meanwhile, positions opened after Q1 2018 that are part of the early-management strategy reach profit targets after roughly 9 months per the table below. This means early-management positions opened at late as Q2 2019 count toward the total number of occurrences.

Managing trades at 50% increase in value yielded trade durations less than half the duration of hold-till-expiration.

### Performance Statistics

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### P/L Statistics

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### Risk Management

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### Overall

All of the option strategies were profitable.

## Discussion

LEAPS provide an interesting proposition: make money so long as the future is swell.

It took the 50D hold-till-expiration strategy 9 years and nearly $1M to finally outperform buy/hold SPY.

A major risk of LEAPS is the duration capital is at risk. The GFC caused the strategy to be unprofitable for 4 years then flounder around for another 3 before finally getting a huge bump to *almost* be on par with buy/hold.

I have no doubts the recent market turmoil will have a similar effect, causing 3-6 months worth of LEAPS to miss profitability targets and expire worthless due to poor timing luck. That is, LEAPS on SPY typically expire in a cadence similar to futures – quarterly every March, Jun, September and December. Had the pandemic occurred 90 days earlier or later, much damage could potentially have been avoided.

## Summary

Systematically opening 730 DTE long call positions on SPY was profitable no matter which strategy was selected.

The 50D hold-till-expiration strategy outperformed buy/hold SPY with regard to total return.

Thanks for reading 🙂

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

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EStaples

May 9, 2020 @ 8:24 am

What do you use for 50% max profit on a LEAP call; wouldn’t it be unlimited? Also, if the max loss is the purchase value, how can the 50D account go negative? Thanks!

EStaples

May 10, 2020 @ 11:46 am

Looks like all the charts & post was corrected. Please ignore my questions. All makes sense now. Thanks!

spintwig.com

May 10, 2020 @ 12:08 pm

Yes, sorry about that. This was my first study consisting of 100% long positions so identifying a respective methodology and ensuring accurate code may take a few iterations.

The reporting templates I use are designed for short strategies; I updated it to “50% increase in option value”. Also, my code had a bug that manifest when a strategy is 100% long positions. This has been corrected and the updated data has been republished.

Feedback and questions like yours help tremendously. Thanks for reading and commenting!

JEI

May 14, 2020 @ 6:00 pm

This is a good one. I’m trying to figure out how LEAPs should fit into a portfolio. Seems overly aggressive to buy one every day, but maybe a strategy of buying during corrections would be a big winner.

spintwig.com

May 17, 2020 @ 12:13 am

That’s a good idea. I may add that to the list of backtests – opening a SPY LEAP when VIX is above or below “x”. The downside in practice is that one won’t know if they’re right or wrong for a while. They’ll have to wait for expiration (or a VIX pop if taking profits early).

bobby

October 25, 2020 @ 1:03 am

So leaps did fine during the march 2020 crash? Looks like it stayed profitable, was it bc IV increased so much?

spintwig.com

October 25, 2020 @ 10:40 pm

Need more data points to tell. LEAPS have a 3-6mo expiration cycle. If I reran this with data through June 30 or later we’d be able to see whether the LEPAS for this cycle were still profitable despite the drop (and sharp recovery).

I’ve been meaning to redo this study to align it with the other debit strategies, so will likely have an answer soon.

doug

January 13, 2021 @ 6:04 am

Based on your analysis, I would be interested to know how the simulation would look if the scenarios were expanded to include 70D, 84D, 90D, and 95D compared against the information above. (My hypothesis is that those strategies would perform better than the <=50D scenarios).

Great modeling, information and analysis! I greatly appreciate all of your efforts and willingness to publish results. In attempting to gather information on SPY vs. SPX LEAP returns in taxable vs. non-tax accounts, I luckily came across your work. Thank you!

spintwig.com

January 14, 2021 @ 10:07 am

Thanks for stopping by Doug! Good question; my hypothesis is similar. If you like I can run those backtests for you – can do SPY and/or SPX. Send me a PM using the “Contact” page and I can send a scope of work for your review.

Glad to hear this information was helpful!