Please use this identifier to cite or link to this item: http://arks.princeton.edu/ark:/88435/dsp01rb68xf28z
 Title: Forecasting Equity Index Volatility Spreads Authors: Huang, Eric Advisors: Cheridito, Patrick Department: Operations Research and Financial Engineering Class Year: 2016 Abstract: Equity market indices such as the S&P500, Dow Jones Industrial Average, NASDAQ Composite, and Russell 2000 have become some of the world’s most heavily traded financial products through their related ETFs, futures, and derivatives. While much work has been done on modelling relative returns and forecasting individual index volatilities, there has been little research into the relationship between index volatilities. We apply the established methodologies of volatility forecasting such as univariate and multivariate GARCH and ARFIMA modelling in order to generate forecasts for equity index volatility spreads. While this approach emphasizes the dynamics of individual volatility time series such as persistence in volatility shocks and asymmetrical reaction to return shocks, we find that these models produce forecasts that are less or about equal in accuracy to simpler moving average models. Extent: 65 pages URI: http://arks.princeton.edu/ark:/88435/dsp01rb68xf28z Type of Material: Princeton University Senior Theses Language: en_US Appears in Collections: Operations Research and Financial Engineering, 2000-2016

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