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[Learn more about Teams](https://stackoverflow.co/teams/) # [realized volatility calculation in python](https://quant.stackexchange.com/questions/70122/realized-volatility-calculation-in-python) [Ask Question](https://quant.stackexchange.com/questions/ask) Asked 3 years, 6 months ago Modified [3 years, 6 months ago](https://quant.stackexchange.com/questions/70122/realized-volatility-calculation-in-python?lastactivity "2022-03-10 14:58:21Z") Viewed 3k times 0 \$\\begingroup\$ I am trying to do a standard realized volatility calculation in python using daily log returns, like so: ``` window = 21 trd_days = 252 ann_factor = window/trd_days rlz_var = underlying_df['log_ret'].rolling(window).var() * ann_factor rlz_vol = np.sqrt(rlz_var) ``` I am essentially getting a realized vol value for each day in my dataset, hence the rolling window over roughly the past month (21 days), and then multiplying the var of this by the annualization factor. Output with some SPY data: [](https://i.sstatic.net/C3gFv.png) Is this a sensible and industry way of going about calculating realized vol? If not, what would be a more appropriate calculation be? - [volatility](https://quant.stackexchange.com/questions/tagged/volatility "show questions tagged 'volatility'") - [programming](https://quant.stackexchange.com/questions/tagged/programming "show questions tagged 'programming'") [Share](https://quant.stackexchange.com/q/70122 "Short permalink to this question") [Improve this question](https://quant.stackexchange.com/posts/70122/edit) Follow [edited Mar 10, 2022 at 14:58](https://quant.stackexchange.com/posts/70122/revisions "show all edits to this post") des224[des224](https://quant.stackexchange.com/users/55055/des224) asked Mar 10, 2022 at 14:52 [](https://quant.stackexchange.com/users/55055/des224) [des224](https://quant.stackexchange.com/users/55055/des224)des224 8322 silver badges99 bronze badges \$\\endgroup\$ 4 - 1 \$\\begingroup\$ IMO, there is generally no "industry" preferred way of calculating realized vol. Volatility is a latent process and there exists many different schemes trying to get the most accurate estimate out of the information you have available. If you are working with OHLC the Garman-Klass estimator (or slight modifications) seems "popular". If you have access to high-frequency data then you can utilize the increased informational gain to your advantage and produce better estimates using the realized variance estimator or eg. the Subsampled approach (ie. more information = better estimates). \[1/2\] \$\\endgroup\$ Pleb – [Pleb](https://quant.stackexchange.com/users/51407/pleb "4,951 reputation") 2022-03-10 15:47:48 +00:00 Commented Mar 10, 2022 at 15:47 - 1 \$\\begingroup\$ Within the area of financial econometrics, it is still a hot topic trying to find better estimators for realized volatility/variance with applications toward risk management or portfolio construction. If you only have daily log-returns available your method will likely get you some adequate results. You can try and play around with the window-length and see how your end results differ. Alternative suggestions *might* not get you much further of producing better end results. \[2/2\] \$\\endgroup\$ Pleb – [Pleb](https://quant.stackexchange.com/users/51407/pleb "4,951 reputation") 2022-03-10 15:50:47 +00:00 Commented Mar 10, 2022 at 15:50 - \$\\begingroup\$ thanks! will definitely look into the GK estimator. However is the rolling window approach a common way to get a daily value for realized vol? i.e. if I implement the GK estimator and calculate realized vol in the same rolling manner to get daily values, is it sensible? \$\\endgroup\$ des224 – [des224](https://quant.stackexchange.com/users/55055/des224 "83 reputation") 2022-03-10 16:01:20 +00:00 Commented Mar 10, 2022 at 16:01 - 1 \$\\begingroup\$ From a research perspective, this is fine when realized volatility is not your main focus and you're just trying to explain key concepts of your paper. As an example, take a look at this [applied paper](https://bit.ly/3CvbdAF) produced by people from Man AHL. Here, they're plotting the rolling standard deviation in Exhibit 6 & 10. Also, in one of DE Shaws [research paper](https://bit.ly/368cjpV) (figure 3) they are using rolling standard deviations. When realized vol has a significant matter, they usually do something different, since they have access to much more data of better quality. \$\\endgroup\$ Pleb – [Pleb](https://quant.stackexchange.com/users/51407/pleb "4,951 reputation") 2022-03-10 19:20:26 +00:00 Commented Mar 10, 2022 at 19:20 [Add a comment](https://quant.stackexchange.com/questions/70122/realized-volatility-calculation-in-python "Use comments to ask for more information or suggest improvements. 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