Good Volatility, Bad Volatility: Signed Jumps and The Persistence of Volatility

By Andrew J. Patton, Kevin Sheppard. Review of Economics and Statistics, 2015

640 citations recorded by the source corpus.

Subfields: Economics and Econometrics, Finance

View Paper: https://www.semanticscholar.org/paper/f7f305b5c5ad17dd957f27c473833acf2bca72ff

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Citations in the corpus

Risk Everywhere: Modeling and Managing Volatility (2018, positive): “In addition to the different formulations discussed above, we also explored models that decompose the daily RV ’s into continuous and jump components (Andersen, Bollerslev, and Diebold, 2007), and formulations that differentiate between up and down realized semi-variances corresponding to the summat”
Downside Variance Risk Premium (2015, positive): “Hence, RV Dt,h(0) and RV U t,h(0) provide a new source of information, which focuses on squared negative and positive jumps, as pointed out by Patton and Sheppard (2015).”
Does Anything Beat 5-Minute RV? A Comparison of Realized Measures Across Multiple Asset Classes (2015, positive): “) The sixth class of estimators are pre-averaged realized variances (RVpa) estimators first introduced by Podolskij and Vetter (2009a) and further studied in Jacod et al. (2009). Pre-averaging applies a kernel-like weighting function to observed returns to construct pre-averaged returns.”
Volatility Spillovers Across Petroleum Markets (2015, background): “Besides being used in risk management for a long time, volatility has recently become even more important as it is now directly tradable using swaps and futures (Patton and Sheppard, 2014).”
Do Jumps Matter for Volatility Forecasting? Evidence from Energy Markets (2016, methodology): “Patton and Sheppard (2015) argue that because the dependent variable in the models is volatility, the OLS estimation may put too much weight on highly volatile periods.”
Asymmetric Connectedness on the U.S. Stock Market: Bad and Good Volatility Spillovers (2015, positive): “In addition, negative jumps also contribute to future volatility more than their positive counterparts (Patton and Sheppard, 2015).”
Semiparametric Conditional Quantile Models for Financial Returns and Realized Volatility (2013, result): “Similar results have been recently obtained by Patton & Sheppard (2009).”
Forecasting the realized volatility of the oil futures market: A regime switching approach (2017, positive): “…HAR-RV-J and HAR-RV-CJ (Andersen et al., 2007a, 2007b), HAR-RV-TJ (Corsi et al., 2010), HAR-S-RV-J (Chen and Ghysels, 2011), HAR-RV-PS2 and HAR-RV-PS3 (Patton and Sheppard, 2015), HAR-CSJ and HAR-CSJd (Sévi, 2014), HAR-ARJ (Prokopczuk et al., 2016), HAR-RV-JLM and HAR-S-RV-J-JLM (Liu et al., 2016).”