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Volatility Processes and Volatility Forecast with Long Memory
SSRN Electronic Journal, 2002We introduce a new family of processes that include the long memory (power law) in the volatility correlation. This is achieved by measuring the historical volatility on a set of increasing time horizons and by computing the resulting effective volatility by a sum with power law weights. In the limit where only one component is included, the models are
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Earnings forecasts and idiosyncratic volatilities
International Review of Financial Analysis, 2008Abstract We test the theoretical relation between idiosyncratic return volatilities and the volatilities of cash-flow news based on the expected returns on equity (ROE) for CRSP stocks over the period 1977–2008. Consistent with economic intuition, we find that using analyst forecasts of earnings is superior to using realized earnings to proxy for ...
Lawrence Kryzanowski, sana mohsni
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Volatility forecasting: combinations of realized volatility measures and forecasting models
Applied Economics, 2017This article examines financial time series volatility forecasting performance. Different from other studies which either focus on combining individual realized measures or combining forecasting mo...
Linlan Xiao +3 more
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International Review of Economics and Finance, 2019
GARCH-type models are frequently used to forecast crude oil price volatility, and whether we should consider multiple regimes for the GARCH-type models is of great significance for the forecasting work but does not have a final conclusion yet.
Yue‐Jun Zhang +3 more
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GARCH-type models are frequently used to forecast crude oil price volatility, and whether we should consider multiple regimes for the GARCH-type models is of great significance for the forecasting work but does not have a final conclusion yet.
Yue‐Jun Zhang +3 more
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Forecasting Volatility with Many Predictors
Journal of Forecasting, 2013ABSTRACTThis study investigates the forecasting performance of the GARCH(1,1) model by adding an effective covariate. Based on the assumption that many volatility predictors are available to help forecast the volatility of a target variable, this study shows how to construct a covariate from these predictors and plug it into the GARCH(1,1) model.
Ke, Tsung-Han, Hu, Yu-Pin
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Climate policy uncertainty and world renewable energy index volatility forecasting
Technological forecasting & social change, 2022Chao Liang +3 more
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Intraday volatility forecasting from implied volatility
International Journal of Managerial Finance, 2011Purpose The purpose of this paper is to examine whether the superiority of the implied volatility from a stochastic volatility model over the implied volatility from the Black and Scholes model on the forecasting performance of future realized volatility still holds when intraday data are analyzed.
Byun, S.J. Byun, Suk Joon +2 more
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The North American journal of economics and finance, 2019
This paper investigates whether iVX, the newly launched implied volatility index in China contains incremental information about volatility forecasting.
Gaoxiu Qiao +3 more
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This paper investigates whether iVX, the newly launched implied volatility index in China contains incremental information about volatility forecasting.
Gaoxiu Qiao +3 more
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Forecasting realized volatility: A review
Journal of the Korean Statistical Society, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Do Jumps and Co-jumps Improve Volatility Forecasting of Oil and Currency Markets?
Energy Journal, 2019This paper aims at modeling and forecasting volatility in both oil and USD exchange rate markets using high frequency data. We test whether extreme co-move-ments (co-jumps) between these markets, as well as intraday unexpected news, help to improve ...
Fredj Jawadi +3 more
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