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Does oil price uncertainty matter in stock market volatility forecasting? [PDF]
PLoS One, 2022 We analyze whether oil price uncertainty and U.S. stock uncertainty can simultaneously provide additional information to volatility forecast of six major stock indexes. For model settings, we find not only the uncertainty information of previous day, but
Qin P, Bai M.
europepmc +3 more sources
Traffic Volatility Forecasting Using an Omnibus Family GARCH Modeling Framework. [PDF]
Entropy (Basel), 2022 Traffic volatility modeling has been highly valued in recent years because of its advantages in describing the uncertainty of traffic flow during the short-term forecasting process.
Ou J, Huang X, Zhou Y, Zhou Z, Nie Q.
europepmc +2 more sources
Liquidity effects on oil volatility forecasting: From fintech perspective. [PDF]
PLoS One, 2021 Fin-tech is an emerging field, inspiring revolutionary innovations in the financial field. It may initiate the evolutionary episode of the financial research, where volatility forecasting is a crucial topic in finance.
Ding S, Cui T, Zhang Y, Li J.
europepmc +2 more sources
Entropy, 2021 This study uses the fourteen stock indices as the sample and then utilizes eight parametric volatility forecasting models and eight composed volatility forecasting models to explore whether the neural network approach and the settings of leverage effect ...
Jung-Bin Su
doaj +1 more source
"Investor attention fluctuation and stock market volatility: Evidence from China".
PLoS ONE, 2023 This paper examines the linkage between Chinese stock market volatility and investor attention fluctuation. In Heterogeneous autoregressive (HAR) model, first, we analyzed the linkage between both decomposed and undecomposed stock market realized ...
Taiji Yang, Siqi Zhuo, Yongsheng Yang
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SSRN Electronic Journal, 2005 Volatility has been one of the most active and successful areas of research in time series econometrics and economic forecasting in recent decades. This chapter provides a selective survey of the most important theoretical developments and empirical insights to emerge from this burgeoning literature, with a distinct focus on forecasting applications ...
Andersen, Torben G. +3 more
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Journal of Futures Markets, 1999 The forecasting ability of the most popular volatility forecasting models is examined and an alternative model developed. Existing models are compared in terms of four attributes: (1) the relative weighting of recent versus older observations, (2) the estimation criterion, (3) the trade-off in terms of out-of-sample forecasting error between simple and
Ederington, Louis H., Guan, Wei
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Volatility Forecasting for Low-Volatility Investing
SSRN Electronic Journal, 2022 Low-volatility investing often involves sorting and selecting stocks based on retrospective risk measures, for example, the historical standard deviation of returns. In this paper, we use the volatility forecasts from a wide spectrum of volatility models to sort and select stocks and estimate portfolio weights.
Christian Conrad +2 more
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Management forecasts of volatility [PDF]
Review of Accounting Studies, 2019 AbstractWe examine the predictive information content of the management forecasts of stock return volatility (i.e., expected volatility) that are disclosed in annual reports. We find that expected volatility predicts near-term and longer-term stock return volatility and earnings volatility incremental to implied volatility, historical volatility, firm ...
Atif Ellahie, Xiaoxia Peng
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Forecasting multifractal volatility [PDF]
Journal of Econometrics, 2001 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Laurent Calvet, Adlai Fisher
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