# SLV Short Put 45 DTE Cash-Secured Options Backtest

In this post we’ll take a look at the backtest results of opening one SLV short put 45 DTE cash-secured position each trading day from Dec 8 2008 through November 8 2019 and see if there are any discernible trends. We’ll also explore the profitable strategies to see if any outperform buy-and-hold SLV.

There are 10 backtests in this study evaluating over 26,500 SLV short put 45 DTE cash-secured 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 SLV
- Strategy Short Put
- Start Date 2008-12-08
- End Date 2019-11-08
- 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 daily using **notional** returns. The change in daily values of the option is divided by the stock price at the time of order entry.

The formula for daily return is:

`option profit / opening stock price`

.

For example, suppose we opened a XYZ short put at $1.10 on 1/3/2007 with a stock price of $50:

- On 1/4/2007, our option increased to $1.50. The notional daily return calculation would be ( $1.10 – $1.50 ) / $50 = -.008 which is -.8% daily return on 1/4/2007
- On 1/5/2007 our option decreased to $0.80. The notional daily return calculation would be ( $1.10 – $0.80 ) / $50 = .006 which is .6% daily return on 1/5/2007

By using notional returns on daily stock values when calculating returns we isolate the performance of the option strategy from the effects of leverage. This allows us to identify strategy performance in a non-margin context such as in a US-based retirement account.

By measuring strategy performance as a daily percentage change we abstract the strategy performance from absolute dollar gain/loss to a relative percentage value. This is a fancy way of saying the strategy becomes **capital agnostic**. In other words, think of an ETF that executes the respective option strategy. We can allocate $100 to the “option ETF” and $100 to the underlying and have an apples-to-apples, dollar-for-dollar comparison.

### 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 using the following formula:

`( backtest starting capital * monthly return ) + portfolio balance`

### 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.

#### Win Rate

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

`( count of trades with P/L > 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)`

#### Worst Monthly Return

Identify the smallest value among the monthly returns:

`MIN(monthly return values)`

#### Average P/L per Day

This measures changes in capital efficiency due to early management.

`( average P/L per trade ) / average trade duration`

#### 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

### Win Rate

Managing trades early lowered the win rate for all strategies.

Baring the 5D and 10D early management strategies which suffered from commission drag, the riskier the trade the lower the win rate.

### Annual Volatility

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### Worst Monthly Return

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### Average P/L Per Day

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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

25.3% – the blended average percent of profits spent on commission across strategies with profits.

### Total P/L

Higher-delta strategies yielded greater profits than lower delta strategies.

Holding till expiration yielded greater profits than managing early.

### Overall

Most option strategies were profitable.

## Discussion

Early management hurt performance across the board. Yes, daily P/L is higher on some strategies as a result of the much shorter trade durations. However, that’s more than offset by every other metric. This is a scenario where the best approach historically has been to simply place a trade then walk away.

A notable observation is the sharp increase in SLV late 2010 / early 2011 and subsequent price collapse early-to-mid 2013. Short put options missed out on the steep gains yet also absorbed the losses quite well. With Sharpe ratios over 2.7x the buy-and-hold strategy, this is an underlying where leveraged strategies may outperform on both a total return and risk-adjusted basis.

## Summary

Systematically opening cash-secured short put positions on SLV was profitable for all hold-till-expiration strategies and the 30D and 50D early-management strategies.

All of the cash-secured SLV hold-till-expiration short put strategies outperformed buy-and-hold SLV on a risk-adjusted return basis. However, none outperformed on a total return basis.

The 5D and 10D @ hold-till-expiration strategies had the greatest risk-adjusted return.

Thanks for reading 🙂

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