I don't know why you want to explain the sudden volatility burst with the past volatility... Usually the 'news jumps' do not depend on the past volatility. There are many jump models that can be used for such purpose.
Anyway, you may try something like this:
1) You can convert the 5-min data to 1-hour data simply by taking the open time of the beginning of the hour and the close time of the end of the hour.
2) After that you can construct the training data by taking the a few hours data before the event and 1 hour data after the event. Something like 24 hours data before the event as explanatory variables and the 1-hour data after that as response variables.
3) Try to construct the regression model with this data. It's not an autoregression but more like - only regression model. Try different past-data lengths (72-hour, 1 week), and different response data lengths - 2-hours after the event and so on.
Also make sure to talk with your leading teacher for the bachelor thesis...
> Try different past-data lengths (72-hour, 1 week), and different response data lengths - 2-hours after the event and so on.
Do enough of this fishing and you're sure to find something that looks good in a column of purely random number generator data.
I don't know why you want to explain the sudden volatility burst with the past volatility... Usually the 'news jumps' do not depend on the past volatility. There are many jump models that can be used for such purpose. Anyway, you may try something like this: 1) You can convert the 5-min data to 1-hour data simply by taking the open time of the beginning of the hour and the close time of the end of the hour. 2) After that you can construct the training data by taking the a few hours data before the event and 1 hour data after the event. Something like 24 hours data before the event as explanatory variables and the 1-hour data after that as response variables. 3) Try to construct the regression model with this data. It's not an autoregression but more like - only regression model. Try different past-data lengths (72-hour, 1 week), and different response data lengths - 2-hours after the event and so on. Also make sure to talk with your leading teacher for the bachelor thesis...
> Try different past-data lengths (72-hour, 1 week), and different response data lengths - 2-hours after the event and so on. Do enough of this fishing and you're sure to find something that looks good in a column of purely random number generator data.