Options Volatility Trading: Concepts and Strategies-Section: 16 - Volatility Forecasting

Options & Futures
1

Hi Team ,



While testing with the code presented in "Options Volatility Trading: Concepts and Strategies-Section: 16 - Volatility Forecasting-Trading with GARCH Forecast" , Majority of the trades in NSE is getting as Short Straddle . 



Is it the case or I am doing Something Wrong.



Attaching the sample Code I am using along with the data for One Symbol .



Please guide me .



Thank You !!!

With Warm Regards

Nandagopal

2

Hello Nandagopal, could you please share access to the file attached to the query? Thanks

3

access to the Share provided

4

Hello Nandagopal,



Thanks for sharing the code file. Although I couldn't run the file since I don't have access to the database you are using, the occurrence of more short-volatility trades than long-volatility trades is somewhat expected. Let me explain.



As per the strategy logic, we are taking a short position when the forecasted volatility is less than the implied volatility. The important thing to note here is that we are forecasting the realized volatility (since we are using realized volatility as an input to the GARCH model). Historically, in most cases, the implied volatility tends to be higher than the realized volatility. This generally holds true in both low-volatile and high-volatile markets.



However, there are specific instances where realized volatility might exceed implied volatility, particularly during periods of market stress or unexpected events.



For a deeper understanding of the relationship between implied volatility (IV) and realised volatility (RV), you can refer to this study here.



Please let me know if you have any further queries.

5

Hi Varun ,



Thank you !!! Let me check again . As per the course , the below was the condition:



forecasted_volatility * np.sqrt(12) > options_data.iloc[index_].C_IV) and (forecasted_volatility * np.sqrt(12)> options_data.iloc[index_].P_IV) and (options_data.loc[index_]['index'].month == options_data.loc[index_+4]['index'].month



But in Capstone project this condition was changed . Any specific reason.



Also when i run the captstone project , I am not getting any output as you have got in course . Can you please help me undertand. In Capstone are we trying for straddle or Strangle.



A weekend call where i can share the screen would be of great help .



Thank you!!!

Wih Warm Regards

Nandagopal



 

6

Hello Nandagopal,



You can use the same condition for the capstone project as well. However, you will notice a difference in the outputs due to the different types of volatilities we are considering for the forecast. Based on the volatility forecast and implied volatility, you can deploy a long/short straddle.



Let me know if you have any queries on this.

7

Hi Varun ,



Thank you !!!



One more thing . I tried to execute the Captstone Project locally . The code didn't give any error . But i didn't get the output which you have mentioned in the course . Can you please help on this .





Thank you !!!

With Warm Regards

Nandagopal

8

Hello Nandagopal, 

The notebook in the course uses Parkinson volatility whereas the capstone uses an average of three volatilities (close to close, Parkinson and Garman-Klass). Because of this reason, you see different results. 



However, if you are comparing any other scenario, could you please provide more details so that I can check from my end?



Thank you!

9

Hi Varun ,



I just copy pasted the course code from capstone Project . It didn't give any error . But i didn't get the output which you have displayed in the capstone code .





Thank you!!!

With Warm Regards

Nandagopal

10

Hello Nandagopal, I will check and get back to you on this. 

11

Hello Nandagopal,



The capstone project files and solution have been updated. Please check Section 21 and let me know if you face any issues.



Thank you.