In our capstone project on option volatility trading strategies, we chose a 5-day holding period for trades when the GARCH model’s predicted volatility exceeds the implied volatility. However, I’m unsure why we specifically wait 5 days before closing the position in a long straddle strategy. Is there a particular reason for this duration? Can we adjust this time frame—either extending or shortening it?
Hi,
Here, the point is to capitalise on the prediction before closing it too soon and also keeping the characteristics of volatility in mind.
You can change the time frame but make sure you backtest thoroughly as extending the period might give you more time to capitalise on large moves and lower transaction costs but increase the exposure to unexpected market moves. Hope this helps.
Thank you. I would like to extend the backtest time period since the ‘options_daily_sp500_2018_2022.csv’ has only Jan-2018 to Sep-2022. May I ask if I would like to add more time period, how can I select the C_IV , P_IV , C_Last and P_Last from the dataset downloaded from OptionDX?
Hello, can anyone answer this question?
“would like to extend the backtest time period since the ‘options_daily_sp500_2018_2022.csv’ has only Jan-2018 to Sep-2022. May I ask if I would like to add more time period, how can I select the C_IV , P_IV , C_Last and P_Last from the dataset downloaded from OptionDX?”
Hello Kevin, here are the steps involved.
Step-1. Download options data from OptionsDx. You can refer to this unit for instructions on how to download the data.
Step-2. Once the data is stored in the form of zip files, you can use the code in this
unit to extract the data from multiple zip files and store it in a single dataframe.
Step-3. The dataframe created in step-2 will have information of IV and last traded prices in the columns [C_IV], [P_IV], [C_LAST], [P_LAST]. You can rename the columns for better readability and use the dataframe for further analysis.
If you have any additional queries on this, feel free to share them in this thread.
Thank you for your response. I’d like to first clarify my question. Regarding the file options_daily_sp500_2018_2022.csv, it contains daily records of STRIKE, C_IV, P_IV, C_LAST, and P_LAST. From the dataset downloaded via OptionDX, I noticed that there are multiple strike prices for the same day. My question is: how should I select the appropriate STRIKE, C_IV, P_IV, C_LAST, and P_LAST values for each day? I’m aiming to extend the dataset to cover the period from 2015 to 2023 for backtesting purposes. To clarify, I’m not asking about how to extract the zip files from OptionDX. Thank you.