Options Trading Strategy Development And The SafeDayTrading Podcast

Options strategy optimization involves a knowledge of risk return goals, use of backtesting parallel infrastructure, and high quality data to use a timing triggers.

Summary

Matt Amberson of ORATS joined the SafeDay Trading podcast to discuss options trading strategy development. Steps include knowing risk return objectives, testing strategies, identifying possible strategies and applying timing triggers, re-testing strategies, paper trading, and gradually building to a size appropriate for risk return goals. ORATS has developed an optimized backtester to help clients find strategies, with tools to analyze and compare backtest results. Trigger optimization involves testing tens of thousands of indicators and simulating backtests before running a full backtest. ORATS also has an integrated paper trading system to test strategies.

Matt Amberson of ORATS joined Mark Stowers of the SafeDay Trading podcast to discuss options trading strategy development. Here's a link to the podcast or search for it in your podcast provider of choice.

Finding an options strategy that meet your investment objectives involves the following steps:

Knowing your risk return objectives

Testing strategies

Identifying possible strategies and applying timing triggers

Re-testing strategies

Paper trading

Going live small and gradually building to a size appropriate for your risk return goals.

Understanding your risk return objectives is a critical step and will define the types of options strategy you can do. For example, if you are risk averse you will prefer long or low risk strategies.

Once you have identified strategies and tickers that meet your objectives, it is time to backtest the parameters of the strategies. ORATS has a backtester with many popular strategies and the ability to combine strategies to structure an infinite number of trading approaches.

ORATS has developed an optimized backtester to help our clients find strategies. For each strategy, the range of acceptable parameters are determined. For example, if you know you would not trade any call butterfly over 90 days you would limit the days to expiration (DTE) to 90. Once you get a range for DTE, delta, other entry criteria, exit criteria, the optimizer arranges all the possible combinations of parameters into many backtests and runs them in parallel.

ORATS has tools to help analyze and compare backtest results.

When all the tests have completed for a strategy, there is a tool in the optimizer process that gives weights to each return statistic for each backtest. This tool scores and sorts the backtests to help you analyze which strategy is best for your objectives. For example, you may value a high annual return and a low worst year return as in the weighted score above. See how the best annual return of 8.55% is scored less than the one with 6.59% because the worst year of -5.56% is better than -18.95%.

Next take the 6.59% strategy and see if applying timing triggers can produce better results. ORATS has tens of thousands of indicators and the moving average of indicators. Testing these indicators can get computationally expensive, so techniques are used to simulate a backtest. After good looking simulations are found, a full backtest can be run to confirm the results.

After a strategy with triggers is found that works as expected in the trigger simulation and in the backtest, paper trading can be started. ORATS has an integrated paper trading system to test strategies.

Once paper trading is found to be consistent with backtests, trading small in the market can be started and finally trading a size that is consistent with risk return objectives.