I have several weeks of minute-by-minute stock data (start and end prices, volume). Everything I've read so far leads me to believe there isn't a standard method for volatility, which is leaving me confused on what to use.
I want to calculate the volatility for each minute so I can see how volatility is changing through the day and whether there is a correlation with other variables. What methods would apply here?
Answer
Financial modeling is often considered as a mixture of art and science. That is a way how you model your data depends on you. You can choose several approaches, for example:
- calculate max - min price for a given minute data - a very simple approach,
- calculate the standard deviation of minute-by-minute stock data,
- calculate GARCH family models for measuring the volatility. This is a more complicated approach but gives you the most adapting models which can detect volatility clustering and thanks to it you can make volatility forecasts. You do not have to implement these models. They are implemented in a dedicated software (ox-metrics, gretl) or implemented in some open source libraries.
To sum up. There is no final answer. Try to use different approaches and decide which suits best for you. Probably in the end of the day GARCH family models will appear the best.
For more information, see:
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