Skip to main content

Improving Volatility Risk Premium with Trailing Stops

· 4 min read

Overview​

Writing options is a common and straightforward method for generating income from derivatives, often referred to as Volatility Risk Premium (VRP) harvesting.

Selling put options is akin to operating an insurance business:

the option seller is rewarded with the premium (option price) in exchange for taking the risk of assignment if the market moves below the strike price at expiration.

This simple strategy can be highly profitable in bull markets, but it can result in significant losses during bear markets and sudden down moves.

SPX Short Put Bull Market Simulation
SPX Short Put Bear Market Simulation

Simulating Option Writing on SPX​

MesoSim was created to study options trading strategies. It offers numerous built-in templates demonstrating key features as well as ready-to-use strategies. 

For simulating Option Writing, we will utilize the [SPX-ShortPut] built-in template.

The above screenshots capture the overview of two runs for different time periods:

Trailing Stops​

In general​

Trailing Stops are well known to equity, futures and options traders alike. The idea is simple: As the profit increases we store the highest profit achieved (high watermark) and create a stop order relative to the high watermark. This way, our stop loss will not be fixed, but it will continuously move higher as the strategy gains.

Programatically it can be described as:

  1. At entry:
    Set pnl_high_watermark to 0.

  2. When current_pnl > pnl_high_watermark:
    Set pnl_high_watermark to current_pnl.

  3. When current_pnl < pnl_high_watermark * x%:
    Exit the position.

Implementing in MesoSim​

To explore how a trailing stop could enhance a trading strategy - such as option writing-  in different market conditions, we will implement it in MesoSim. The above logic can be translated into a Strategy Definition as follows:

  1. At entry initialize pnl_high_watermark variable to 0:
"Entry": {
  ...
  "VarDefines": {
      "pnl_high_watermark": "0"
  }
},
  1. Increase pnl_high_watermark when we reach a new high of pnl:
"Adjustment": {
  ...
  "ConditionalAdjustments": {
    "pos_pnl > pnl_high_watermark -- record new high watermark": {
      "UpdateVarsAdjustment": {
        "VarDefines": {
          "pnl_high_watermark": "pos_pnl"
        }
      }
    }
  }
},
  1. Exit when the current pnl falls below the 75% of the high watermark:
"Exit": {
  ...
  "Conditions": [
    "pos_pnl < (pnl_high_watermark * 0.75) -- Exit if pnl drops 25pct from high water mark"
  ]
},

Trailing Stop with SPX Short Put results​

Incorporating the trailing stop snippets into the Short Put template and re-running the tests produces the following results:

SPX Trailing Stop Bull Market Simulation
SPX Trailing Stop Bear Market Simulation

The above runs can be accessed in the following URLs:

Summarizing the results​

When comparing the original Short Put runs with the Trailing Stop version, we can conclude that the trailing stop signifficantly improved the strategy performance in Bear market. In contrast, the results in bull market became more modest, although it remains fairly good (with a sharpe ratio around 2).

SPX Trailing Stop vs Short Put Comparison

Conclusion​

Trailing stop is a dynamic approach to increase strategy performance. It has proven to be beneficial for the simple SPX Put Writing strategy by locking in gains without sacrificing much upside potential. 

Someone interested in this approach should try different relative ranges from the high watermark to see how it affects her strategy performance.

MesoSim v3 Migration Note

This article was originally written for MesoSim v2. The examples and terminology have been updated to match the MesoSim v3 Strategy Definition format. For details, see the MesoSim v3.0 release announcement and the v2→v3 migration guide. The performance metrics, described behavior, and referenced run results reflect the original v2 behavior. If you rerun the referenced strategies on MesoSim v3, results may differ slightly due to behavioral changes in the simulator.