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Practical Issues in Forecasting Volatility
CFA Digest, 2005A comparison is presented of 93 studies that conducted tests of volatility-forecasting methods on a wide range of financial asset returns. The survey found that option-implied volatility provides more accurate forecasts than time-series models.
Poon, Ser Huang, Granger, Clive
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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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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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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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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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Automated Volatility Forecasting
Management ScienceWe develop an automated system to forecast volatility by leveraging more than 100 features and five machine learning algorithms. Considering the universe of S&P 100 stocks, our system results in superior out-of-sample volatility forecasts compared with existing risk models across forecast horizons.
Sophia Zhengzi Li, Yushan Tang
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Forecasting Stock Market Volatility Using Implied Volatility
2007 American Control Conference, 2007We explored the firm-level forecasting power of implied volatility on realized volatility over various horizons. All existing literatures focused on examining forecasting power over the remaining life of options. We built a linear regression model using implied volatility series to forecast future volatility of various horizons.
Peng He, Stephen Shing-Toung Yau
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Forecasting Volatility with Time-Varying Leverage and Volatility of Volatility Effects
SSRN Electronic Journal, 2018Abstract Predicting volatility is of primary importance for business applications in risk management, asset allocation, and the pricing of derivative instruments. This paper proposes a measurement model that considers the possibly time-varying interaction of realized volatility and asset returns according to a bivariate model to capture its major ...
Catania, L, Proietti, T
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