论文信息 - Volatility and risk estimation with linear and nonlinear methods based on high frequency data

Volatility and risk estimation with linear and nonlinear methods based on high frequency data

Accurate volatility predictions are crucial for the successful implementation of risk management. The use of high frequency data approximately renders volatility from a latent to an observable quantity, and opens new directions to forecast future volatilities. Our goals in this paper are to find a general powerful forecasting procedure for volatilities based on high frequency data, to evaluate the predictive potential of volatility forecasts for the true latent volatility, and to analyze the impact of more reliable volatility predictions on the quality of two widely used risk measures. For that purpose, we explore the performance of various models and modern prediction tools. JEL Classification: C22; C52; G10

Peter Bühlmann | Marcel Dettling

[1] Irène Gijbels,et al. Understanding exponential smoothing via kernel regression , 1999 .

[2] A. McNeil,et al. Estimation of tail-related risk measures for heteroscedastic financial time series: an extreme value approach , 2000 .

[3] P Bühlmann,et al. What is a linear process? , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[4] F. Diebold,et al. The Distribution of Exchange Rate Volatility , 1999 .

[5] Stephen L Taylor,et al. The incremental volatility information in one million foreign exchange quotations , 1997 .

[6] Yoshua Bengio,et al. Pattern Recognition and Neural Networks , 1995 .

[7] T. Bollerslev,et al. ANSWERING THE SKEPTICS: YES, STANDARD VOLATILITY MODELS DO PROVIDE ACCURATE FORECASTS* , 1998 .

[8] Francis X. Diebold,et al. Modeling and Forecasting Realized Volatility , 2001 .

[9] Richard A. Davis,et al. Time Series: Theory and Methods , 2013 .

[10] M. Dacorogna,et al. Consistent High-Precision Volatility from High-Frequency Data , 2001 .

[11] R. C. Merton,et al. On Estimating the Expected Return on the Market: An Exploratory Investigation , 1980 .

[12] P. Bühlmann. LOCALLY ADAPTIVE LAG‐WINDOW SPECTRAL ESTIMATION , 1996 .

[13] G. Schwert. Stock Market Volatility: Ten Years after the Crash , 1997 .

[14] H. Künsch. Discrimination between monotonic trends and long-range dependence , 1986 .

[15] Philippe Artzner,et al. Coherent Measures of Risk , 1999 .