Volatility Forcasting and Portfolio Optimization
Master thesis
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https://hdl.handle.net/11250/2823635Utgivelsesdato
2021Metadata
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Sammendrag
This thesis investigates the relationship between volatility forecasting and portfolio
performance. The aim is to use stylized facts about financial asset returns to improve the
accuracy of volatility forecasts and see if better forecasts can improve portfolio selection –
and performance. GARCH type models are used in order to forecast volatility over a rolling
period of 1,008 trading days (4 years). The volatility forecasts are used to construct
Markowitz mean-variance optimal portfolios by maximizing the Sharpe Ratio of the portfolios.
We find that the ability to forecast volatility is linked with portfolio performance. The strategies
that are able to forecast the volatilities with highest accuracy outperforms the other strategies
in terms of cumulative returns and standard deviation of the returns.