Course Name: Options Volatility Trading: Concepts and Strategies, Section No: 19, Unit No: 16, Unit type: Notebook
Revisiting this section, I´m wondering when this is useful or not vs the backtesting methodology discussed in previous sections. Could you elaborate on a practical example of implementing these two approaches? I guess I could first use this P/L distribution to get optimal parameters of options to use and then backtest based on my signals or how? Thanks
Hello Jorge,
You can use simulations, such as Monte Carlo simulation, to understand the potential outcomes of the strategy. This would help you grasp the probability distribution of returns, enabling you to design effective risk management for the strategy. Additionally, it will aid in comprehending the dynamics of the strategy.
On the other hand, backtesting will assist you in assessing how your strategy would have performed under historical market conditions. This is valuable for identifying patterns, validating assumptions, and gaining insights into the historical risk and return characteristics of the strategy.
To implement both approaches, you can conduct the simulation, determine the optimal parameters of the strategy by analysing the distribution of returns, design entry and exit points based on this analysis, and finally, backtest the strategy.
Happy learning! Please let me know if you have any more queries.
Many thanks Varun for your response, now I see the potential of the combination.
First, using simulation to assess different option parameters of the option structure (i.e. strangle, straddle, vertical spread,…). Then based on my observed entry/exit parameter backtest through historical data.
Cool!
Hello Jorge, yes, your understanding is right! Keep practising and let us know if you have any queries.
Happy learning!