MODELING TIME SERIES OF ATM LOCAL VOLATILITY FOR MICROSOFT STOCKS
DOI:
https://doi.org/10.30888/2663-5712.2021-07-02-084Keywords:
Local volatility, Dupire local volatility process, genetic algorithm, autocorrelation, polynomial regression, statistical significance, forecast.Abstract
In this work we apply simple linear and polynomial regression to model the time series of at-the-money (ATM) local volatility of Microsoft stocks and predict its out-of-sample values. Multiple researches consider ATM local volatility to be a good measureMetrics
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