# SPY Short Put 0, 7, and 45 DTE Leveraged Options Backtest

In this post we’ll compare and contrast the leveraged 0 DTE, leveraged 7 DTE and leveraged 45 DTE SPY short put options strategies, after normalizing for the effects of market exposure and timing luck, from Feb 16 2018 through May 29 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 20 backtests in this study evaluating over 11,100 SPY short put 0 DTE, 7 DTE and 45 DTE leveraged trades.

The 0 DTE and 7 DTE strategies will have all their positions held till expiration. Prior research has shown this exit strategy consistently yielded higher total and risk-adjusted return vs early management.

The 45 DTE strategy will utilize “50% max profit or 21 DTE” and “hold-till-expiration” exit strategies. Prior research has shown either exit strategy may outperform.

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 (coming soon)
- QQQ Short Put 7 DTE Leveraged (coming soon)
- 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 2018-02-16
- End Date 2020-06-03
- 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.

#### 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.

`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

Shorter-duration strategies allows a smaller starting portfolio value since the maxim number of concurrent positions is capped. Less capital is “turned over” faster vs longer-duration strategies.

### Margin Utilization

The 0 DTE and early management strategies yielded a lower average margin utilization across all deltas when compared to longer-duration strategies / 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

Shorter-duration strategies had higher rates of premium capture vs longer-duration strategies.

The higher the delta the lower the premium capture. 50D was an exception in some scenarios.

### Win Rate

Shorter-duration strategies outperformed longer-duration strategies with regard to win rate. 45 DTE w/ early management was an exception.

The higher the delta the lower the win rate.

### Monthly Returns

Shorter duration strategies outperformed longer duration strategies with regard to average monthly return.

The higher the delta the higher the average monthly return.

Also displayed is the best and worst monthly returns for each strategy.

### Max Drawdown

Shorter duration strategies had mixed results vs longer duration strategies with regard to max drawdown.

The higher the delta the greater the max drawdown. The 0 DTE strategy was an exception.

### Max Drawdown Date

The 0 DTE strategies experienced their max drawdown during the Dec 2018 correction. Meanwhile, all the other strategies were experienced their max drawdown after the bull market ended in March 2020.

Notice the longer duration strategies reached their max drawdown only after two events occurred: VIX stopped climbing and the majority of open positions where VIX was “normal” at the time of order entry were closed.

### Average Trade Duration

Managing 45 DTE trades at 50% max profit or 21 DTE yielded trade durations roughly half the duration of hold-till-expiration.

### Compound Annual Growth Rate

Shorter duration strategies outperformed, in general, longer duration strategies with regard to compound annual growth rate.

In general, the higher the delta the higher the CAGR.

### Annual Volatility

Shorter-duration strategies yielded mixed results with regard to volatility vs longer-duration strategies.

The higher the delta the higher the volatility.

### Sharpe Ratio

Shorter duration strategies outperformed, in general, longer duration strategies with regard to sharpe ratio.

In general, the higher the delta the lower the sharpe ratio.

The 5D 0 DTE strategy had the greatest risk-adjusted return among the option strategies.

### Profit Spent on Commission

18.18% – the average percent of profits spent on commission across all profitable option strategies.

### Total P/L

Shorter-duration strategies outperformed longer-duration strategies with regard to total P/L.

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

### Overall

Half of the option strategies were profitable.

The 10, 16, 30 and 50D 0-DTE strategies and 5D 7-DTE strategy all outperformed buy-and-hold SPY with regard to both total and risk-adjusted return.

## Discussion

Let’s take a closer look at the equity curves for each of the DTE targets.

We can see that the 0-DTE strategies have smooth curves / is less volatile relative to the 45 DTE strategies. The longer-duration strategies outperform leading up to the March 2020 drop but then underperform after.

One critique that may be said about this study is the limited duration: 27 months.

Keeping in mind that 1) the backtest seeks to open a position daily in order to mitigate timing luck (crude visual of concept) and 2) the 0-DTE strategy is only able to achieve daily order entry as early as Feb 16 2018, this is the longest backtest duration possible.

Quoting from the SPY Short Put 0 DTE Leveraged study:

On June 4 2010 CBOE released Friday-expiring weekly options on SPY. About 6 years later on August 30 2016 CBOE released Wednesday-expiring weekly options on SPY (see SEC release 34-78686). About 18 months later on February 16 2018 CBOE released Monday-expiring weekly options on SPY (see SEC release 34-82733).

It wasn’t until the introduction of Monday-expiring weekly options that the 0-DTE strategy could support opening a position daily (tolerances for 0 DTE is 0-3 DTE, closest to 0 – explained in more detail the methodology section above the studies).

While the backtest duration may leave some desiring a longer track record, the span of time covers one of the fastest transitions to a bear market in recent history (VIX even set a new record) along with one of the best one-month returns in recent history.

## Summary

Systematically opening SPY short put 0 DTE leveraged positions was profitable no matter which strategy was selected.

The “5D 0-DTE” strategy had the greatest risk-adjusted return among the option strategies.

The 10, 16, 30 and 50D 0-DTE strategies and 5D 7-DTE strategy all outperformed buy-and-hold SPY with regard to both total and risk-adjusted return.

Thanks for reading 🙂

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

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uno

July 10, 2020 @ 8:21 am

Nice. 0 DTE -16D seems to be the sweetspot from risk-reward point of view. Is 0 DTE is opening a day before expiration before market close? BigErn does 3 DTE

uno

July 10, 2020 @ 8:23 am

Forgot to ask is this backtest applicable to SPX?

spintwig.com

July 10, 2020 @ 11:12 am

0 DTE is opening the day of expiration. Indeed, he does.

Yes, SPX results should be very similar.

Matty G

July 10, 2020 @ 2:53 pm

Isn’t SPX quite a bit more dangerous because the options expire on a Thursday but are priced based on Friday’s opening?

Russell

July 10, 2020 @ 4:44 pm

I think AM-settlement is for SPX options rather than the SPX weeklies (SPXW) which are PM-settled. Maybe I’m misunderstanding?

Steve

July 10, 2020 @ 3:56 pm

How did the algorithm work on the 0 DTE? For instance, if you were looking for a 16D and it wasn’t available because of the high Gamma did you go out to the next expiration and look there up to the 3 DTE or was 3 DTE only for Fridays? Since you were only holding one position at a time, is it safe to assume you waited until near close on the next day to look for your next position?

On the 0 DTE, 16D and 30D what was your average premium collected?

spintwig.com

July 11, 2020 @ 11:53 am

When looking for a 16D position, the tolerance is +/- 6 delta. So anywhere between 10-22, closest to 16. Tolerances are different for different delta targets.

The approach is to first look at DTE targets then look at a delta targets. If a 0DTE position with a delta between 10-22 doesn’t exist, then look at a 1DTE position with the a delta in the range and choosing the one closest to 16D. Repeat this process until all DTE targets within the range have been explored. If after all DTE positions have been explored and there is not a suitable position, take no action – a new position is not opened that day.

There are scenarios where more than one position is open at a time. For example, if on Friday only a 3DTE / Monday-expiring position satisfies the requirements, such a position is opened. Then on Monday the 0DTE same-day expiring positing satisfies the requirements, that position is opened. At this time there are now two open positions.

Avg premium collected is in the “Premium Capture“ chart and table in the results section.

Eric

July 14, 2020 @ 4:30 pm

I’m curious if the results would be similar using put credit spreads with the 0 DTE strategies. For someone with a small account this is more appealing to me and I’m wondering what the downsides of doing a spread would be opposed to just selling a put. Is this something you would look into in a future study?

spintwig.com

July 18, 2020 @ 7:44 pm

Sure! I’ll add it to the list.

_Eric_

July 21, 2020 @ 2:55 pm

Hi. Awesome stuff! I was wondering if you could provide more context around the drawdown percentages. I want to make sure I understand this correctly and put a dollar amount to the drawdown.

Lets say the SPY is trading for 326. You are running a campaign, selling the 0 DTE, 16 Delta puts everyday. Would the notional value be $32,600 per put sold? Since the max drawdown for 0DTE, 16D is 9.36%, does this equate to a draw down of $3051.36 per option sold?

Thanks!

spintwig.com

July 22, 2020 @ 1:06 pm

Yes, notional on a 326 SPY put would be $32,600.

Drawdowns are measured as a portfolio performance metric as opposed to an option position performance metric. That is, 9.36% max drawdown is the difference between the portfolio value at the bottom of the drawdown and portfolio value at the peak from which the portfolio fell.

There are many drawdowns as the portfolio ebbs and flows. 9.36% happened to be the largest drawdown in this example.

Because the drawdown is relative (i.e. a percentage) and not absolute (i.e. a specific dollar amount), it’s not possible to put a specific dollar amount to it given the data available. For example, a 10% drawdown would be viewed as more severe than an 8% drawdown. However, more dollars in an absolute sense could be lost on an 8% drawdown.

Suppose a 10% drawdown occurred early when the portfolio was, say, 10k which results in a 1k loss. The portfolio eventually recovers and grows to 100k then experiences an 8% drawdown. This results in an 8k loss – more dollars were lost but it represents a smaller percentage.

_Eric_

July 22, 2020 @ 5:21 pm

Thanks for the detailed reply. I’m trying to figure out how I would size this strategy. I guess a better question would have been, if notional value is 32,600, how many puts are you selling per 32,600 in your test? i.e. What is the leverage factor?

Sticking w/ the 0 DTE, 16 delta:

I see the minimum starting capital was 11,000. I’m assuming this minimum number is the margin required + a drawdown buffer that would allow you to keep trading. Is it safe to say this is 3x to 5x leverage? When would you add more contracts? every time the account increased by 11 k?

Is 11k the starting number that the CAGR was calculated on?

Thanks and sorry for all of the questions. Maybe I’m just having a dense day.

spintwig.com

July 23, 2020 @ 11:38 am

Correct – assuming a start in Feb 16 2018, $11k was the minimum amount of capital needed to write a 0-3 DTE short put every day without blowing up [within the assumptions of the backtest].

Max margin utilization is essentially 100% or 5x leverage, whereas the average margin utilization is essentially 30% or 1.5x leverage. From time to time there would be 3 concurrent positions open. More often then not, there would be only 1-2 positions open at any given time with the 0-3 DTE strategy. This is why the max margin utilization and average margin utilization are so far apart for this particular strategy.

Yes, the CAGR was calculated on the 11k starting capital.

TFJ

July 27, 2020 @ 12:15 am

I’m having trouble understanding your 45 DTE curves. What is the difference between the 5D-50 (red here) and 5D (purple)?

spintwig.com

July 29, 2020 @ 5:11 pm

The 5D-50 is managed (closed) at “50% max profit or 21 DTE, whichever comes first” whereas the 5D is held till expiration.

RI

August 2, 2020 @ 5:28 pm

For 0DTE – 5D, is there a reason the premium capture is around 56% even with a 98.5% win-rate – does the 1.5% loss rate reduce the premium capture so significantly?

spintwig.com

August 2, 2020 @ 5:57 pm

Yes, the 1.5% of trades that were losers offset nearly half of the profits earned from all the profitable trades.

Joe Jefferson

August 4, 2020 @ 12:25 pm

I see “Timing 3:46pm ET” — does that mean for the 0 DTE strategy, the following statements are true?

On Friday, 3:46PM a short put is opened with a Monday expiry

On Monday, 3:46PM a short put is opened with a Wednesday expiry

On Tuesday, 3:46PM a short put is opened with a Wednesday expiry

On Wednesday, 3:46PM a short put is opened with a Friday expiry

etc…

Forgive me if I just missed it in your amazing writeup!

Joe Jefferson

August 4, 2020 @ 12:26 pm

Oh man, the formatting did not come through, sorry!

spintwig.com

August 6, 2020 @ 3:46 pm

No worries – it came through formatted when I received the email alert 🙂

For the 0 DTE strategy, a position is opened Mon @ 3:46pm with a Mon expiration (it’s essentially a 14-minute option, ignoring after-hours trading).

There are no Tuesday-expiration options so on Tues a position is opened 3:46pm and are generally a Wed expiration. I use tolerances on the delta and DTE targets to help ensure a position is opened daily. This mitigates much of the timing luck issue while also capturing the “intent” or “spirit” of the backtest.

Wed comes around and a new position is opened at 3:46pm for expiration in 14 min (and there’s also Tuesday’s position that’s expiring).

Suppose Friday comes around and there’s no position that can be opened within the specified delta target range. I allow up to 3 DTE of tolerance so the strategy can open a position that expires Monday. Also, various holidays and quadruple witching can force a non-same-day-expiring position to be opened.

The methodology you cited is BigERN’s strategy – I backtested that as a guest post on his site: https://earlyretirementnow.com/2020/06/17/passive-income-through-option-writing-part-5/

William

August 8, 2020 @ 6:07 am

Hi Spintwig,

Thanks for the great work as always, really appreciated the insight. However, I suspect the outperformance could be due to the timing of the position opening – the last 14 minutes of the day could be more tranquil than other periods in the day.

Would it be possible to run the 0-DTE backtest by opening positions at the start of the trading day?

spintwig.com

August 9, 2020 @ 11:32 am

Great point William! This is a fine example of timing luck potentially impacting results.

Short answer is unfortunately “not at this time.” It turns out my data sources only offer a single price snapshot for a given day. There are data sources that have 1-minute granularity but they’re expensive to acquire and crunch. Perhaps one day this will be a backtest configuration I can accommodate.

Semper

November 2, 2020 @ 10:50 pm

Does 25% profit apply to if it declines by a value of 25% profit as well too?

spintwig.com

November 3, 2020 @ 4:21 am

Positions were not exited based on losses. An exit on a 25% decline in value would be synonymous to a 0.25x stop loss.

Ed

November 20, 2020 @ 7:35 am

Just came across this – thank you for the great work. I haven’t seen anyone really talk about this strategy or similar elsewhere (other than ERN blog). Is be interested to hear if you have any thoughts about the mechanism or an explanation for the success of the shorter Dte strategies?

I am somewhat new to options trading so forgive me if this makes little sense, but do you think it could have to do with the expansion in implied volatility during turbulent markets? Ie the time value of longer dated options rises far more than it does for shorter dated ones, causing bigger drawdowns and margin hits.

spintwig.com

November 22, 2020 @ 10:26 am

Thanks for stopping by! I don’t have a definitive reason, but my speculation is that

1) the 0DTE play is less saturated and thus has less structural arb happening to keep prices exactly where they should be (as compared to, say, 30DTE or 7DTE horizons) and

2) if the trade goes “bad” in that realized vol exceeds implied vol, the amount of vol that can happen in a day is less than that of a week or 45DTE. Thus, losses are capped to a single day’s worst move. Yes, longe-dated options are priced efficiently with more premium to account for this and have a longer runway before the position goes ITM. However, if a substantial fat tail happens like Feb/March 2020 then the 0DTE options can only lose for a day and the next trade takes advantage of the now-significantly-different greeks.