Using information quality for volatility model combinations |
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| Authors: | Vasyl Golosnoy |
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| Institution: | Department of Economics and Social Sciences, Helmut Schmidt University Hamburg, Germany. |
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| Abstract: | This paper proposes updated methodology for volatility model combinations which account for the informational content of innovations. An adaptive measure of information quality serves for the selection of model weights in order to improve daily volatility forecasts. The information quality proxy is related to the size of unexpected shocks in the volatility process. Our approach is illustrated in an empirical study with German stock market data. |
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| Keywords: | Forecast combination Model uncertainty Quality of information Volatility forecasts |
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