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Low and high prices can improve volatility forecasts during periods of turmoil · Study

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ArticleLow and high prices can improve volatility forecasts during periods of turmoil

Piotr Fiszeder2016

Article2016

Low and high prices can improve volatility forecasts during periods of turmoil

Piotr Fiszeder · Grzegorz Perczak

31 citations·0/0 files stored·International Journal of Forecasting

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Financial Risk and Volatility Modeling Stochastic processes and financial applications Stock Market Forecasting Methods

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References

2003Modeling and Forecasting Realized Volatility 2004Power and Bipower Variation with Stochastic Volatility and Jumps 1980The Extreme Value Method for Estimating the Variance of the Rate of Return 1980On the Estimation of Security Price Volatilities from Historical Data 2010Volatility forecast comparison using imperfect volatility proxies 2005A Test for Superior Predictive Ability 2002Range‐Based Estimation of Stochastic Volatility Models 2006Realized Variance and Market Microstructure Noise

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2019Improving forecasts with the co-range dynamic conditional correlation model 2024Robust estimation of the range-based GARCH model: Forecasting volatility, value at risk and expected shortfall of cryptocurrencies

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Year2016

Typearticle

Published2016-01-21

VenueInternational Journal of Forecasting

ISSN-L0169-2070

Languageen

Citations31

Files0 public / 0

ShelfFinancial Risk and Volatility Modeling

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doi10.1016/j.ijforecast.2015.07.003

openalex_workW2284763420

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