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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
Peng Qin, Manying Bai
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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.
Shusheng Ding +3 more
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Traffic Volatility Forecasting Using an Omnibus Family GARCH Modeling Framework [PDF]
Entropy, 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.
Jishun Ou +4 more
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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 ...
Andersen, Torben G. +3 more
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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
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"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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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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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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Forecasting Coherent Volatility Breakouts [PDF]
SSRN Electronic Journal, 2014 The paper develops an algorithm for making long-term (up to three months ahead) predictions of volatility reversals based on long memory properties of financial time series. The approach for computing fractal dimension using sequence of the minimal covers with decreasing scale (proposed in [1]) is used to decompose volatility into two0dynamic ...
Didenko, Alexander +2 more
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