The one-trading-day-ahead forecast errors of intra-day realized volatility |
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| Institution: | 1. Department of Economic and Regional Development, Panteion University, 136 Syngrou Av., Athens, 176 71, Greece;2. Postgraduate Department of Business Administration, Hellenic Open University, Aristotelous 18, 26 335, Greece;1. DRM Finance, Université Paris Dauphine, Place du Maréchal de Lattre de Tassigny, 75775 Paris Cedex 16, France;2. IPAG Business School (IPAG Lab), 184 Boulevard Saint-Germain, 75006 Paris, France;3. Université Paris 8 (LED), 2 rue de la Liberté, 93526 Saint-Denis Cedex, France;1. University of Sousse, Sousse 4054, Tunisia;2. IPAG Business School, Paris 75006, France;3. University of Manouba, Manouba 2010, Tunisia;1. ISG International Business School (GrIIsG), Paris, France;2. CNRS (EUROFIDAI) and Léonard de Vinci Pôle Universitaire, Finance Lab, Paris La Défense, France;1. IESEG School of Management (LEM-CNRS), Rue de la Digue 3, F-59000 Lille, France;2. University of Liège HEC Management School, Rue Louvrex 14, B-4000 Liège, Belgium;1. Complex Systems Community, University of Siena, Italy;2. Department of Information Engineering and Mathematics, University of Siena, via Roma 56, 53100 Siena, Italy;3. Department of Management and Quantitative Sciences, University of Naples “Parthenope”, via A. Ferdinando Acton 38, 80133 Naples, Italy |
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| Abstract: | Two volatility forecasting evaluation measures are considered; the squared one-day-ahead forecast error and its standardized version. The mean squared forecast error is the widely accepted evaluation function for the realized volatility forecasting accuracy. Additionally, we explore the forecasting accuracy based on the squared distance of the forecast error standardized with its volatility. The statistical properties of the forecast errors point the standardized version as a more appropriate metric for evaluating volatility forecasts.We highlight the importance of standardizing the forecast errors with their volatility. The predictive accuracy of the models is investigated for the FTSE100, DAX30 and CAC40 European stock indices and the exchange rates of Euro to British Pound, US Dollar and Japanese Yen. Additionally, a trading strategy defined by the standardized forecast errors provides higher returns compared to the strategy based on the simple forecast errors. The exploration of forecast errors is paving the way for rethinking the evaluation of ultra-high frequency realized volatility models. |
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| Keywords: | ARFIMA model HAR model Intra-day data Predictive ability Realized volatility Ultra-high frequency modelling |
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