ChapterEvaluating Volatility and Correlation ForecastsAndrew J. Patton2009Evaluating Volatility and Correlation ForecastsAndrew J. Patton, Kevin Keith Sheppard2009-01-01chapterSpringer eBooks244 citationsclosedNo readable copy stored yet — this record is metadata only.Financial Risk and Volatility ModelingForecasting Techniques and ApplicationsStock Market Forecasting MethodsAbstractNo abstract was published for this record.Citations in this libraryStored only when both papers are in the corpus — 244 citations exist upstream.References2012The Econometrics of Financial Markets1994Comparing Predictive Accuracy1997The Econometrics of Financial Markets2003Modeling and Forecasting Realized Volatility1998Answering the Skeptics: Yes, Standard Volatility Models do Provide Accurate Forecasts1988A Capital Asset Pricing Model with Time-Varying Covariances2004CAViaR2003Panel Data EconometricsCited by2011On the forecasting accuracy of multivariate GARCH models2011Multivariate high‐frequency‐based volatility (HEAVY) models2010Quantiles as optimal point forecasts2017Elicitability and backtesting: Perspectives for banking regulation2009Forecasting S&P 500 volatility: Long memory, level shifts, leverage effects, day-of-the-week seasonality, and macroeconomic announcements2019Two are better than one: Volatility forecasting using multiplicative component GARCH‐MIDAS models2009Optimal combinations of realised volatility estimators2012On loss functions and ranking forecasting performances of multivariate volatility models