Analytic Evaluation of Volatility Forecasts

2002

169 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/c5f86041dffe8855464711d22f1a041e35b68168

Citations in the corpus

• Exploiting the errors: A simple approach for improved volatility forecasting (2016, unknown): “…time-varying variance of themeasurement errors into the parameterization of themodel, the estimated HARQ models exhibit more persistence in ‘‘normal 2 Andersen et al. (2004) and Sizova (2011) show how minor model misspecification can adversely affect the forecasts from tightly parameterized…”
• Garch forecasting performance under different distribution assumptions (2006, unknown): “Since the S&P 500 Future is not traded 24 hours a day this measure q q q q q 3 1 2 2 3 1 + - - 4 Of course, even higher frequencies could be examined but the noise reduction from using even higher frequencies is minuscule, as shown in Andersen et al. (2004).”
• The role of implied volatility in forecasting future realized volatility and jumps in foreign exchange, stock, and bond markets (2007, unknown): “Andersen, Bollerslev, Diebold & Labys (2003) and Andersen, Bollerslev & Meddahi (2004) show that simple reduced form time series models for realized volatility (RV ) outperform commonly used GARCH and related stochastic volatility models in forecasting future volatility.”
• Volatility Forecast Comparison Using Imperfect Volatility Proxies (2006, unknown): “This point was compellingly presented in Andersen and Bollerslev (1998) and Andersen et al. (2004).”
• Measuring Downside Risk - Realised Semivariance (2008, unknown): “5Leading references include Andersen, Bollerslev, Diebold, and Labys (2001) and Andersen, Bollerslev, and Meddahi (2004).”
• Do High-Frequency Measures of Volatility Improve Forecasts of Return Distributions? (2011, unknown): “Examples include Andersen, Bollerslev, Diebold, and Labys (2003), Andersen, Bollerslev, and Diebold (2007), Andersen, Bollerslev, and Meddahi (2004), Ghysels and Sinko (2006), Ghysels, Santa-Clara, and Valkanov (2006), Koopman, Jungbacker, and Hol (2005), Maheu and McCurdy (2002, 2007), Martens,…”
• Semi-Parametric Comparison of Stochastic Volatility Models using Realized Measures (2006, unknown): “The suggested test statistics do not require the knowledge of the drift component, but the analytical expressions for the moments of integrated volatility were derived by Andersen et al. (2004) under the maintained hypothesis of a constant drift.”
• A Reduced Form Framework for Modeling Volatility of Speculative Prices Based on Realized Variation Measures (2007, unknown): “26 As discussed in Andersen et al. (2004, 2005), the reported R2 ’s understate the true degree of predictability due to themeasurement errors in the realized volatility proxies.”