Journal ArticleDOI
Forecasting S&P 100 volatility: the incremental information content of implied volatilities and high frequency index returns
TLDR
In this article, the information content of implied volatilities and intraday returns is compared in the context of forecasting index volatility over horizons from 1 to 20 days, and it is shown that the VIX index provides the most accurate forecasts for all forecast horizons and performance measures considered.About:
This article is published in Journal of Econometrics.The article was published on 2001-11-01. It has received 529 citations till now. The article focuses on the topics: Implied volatility & Realized variance.read more
Citations
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Journal ArticleDOI
Forecasting Volatility in Financial Markets: A Review
Abstract: Financial market volatility is an important input for investment, option pricing, and financial market regulation. The emphasis of this review article is on forecasting instead of modelling; it compares the volatility forecasting findings in 93 papers published and written in the last two decades. Provided in this paper as well are volatility definitions, insights into problematic issues of forecast evaluation, data frequency, extreme values and the measurement of "actual" volatility. We compare volatility forecasting performance of two main approaches; historical volatility models and volatility implied from options. Forecasting results are compared across different asset classes and geographical regions.
Posted Content
The Model-Free Implied Volatility and Its Information Content
George J. Jiang,Yisong S. Tian +1 more
TL;DR: In this paper, the authors extend the model-free implied volatility to asset price processes with jumps and develop a simple method for implementing it using observed option prices, and perform a direct test of the informational efficiency of the option market using the model free implied volatility.
Journal ArticleDOI
The Model-Free Implied Volatility and Its Information Content
George J. Jiang,Yisong S. Tian +1 more
TL;DR: In this article, the authors extend the model-free implied volatility to asset price processes with jumps and develop a simple method for implementing it using observed option prices, and perform a direct test of the informational efficiency of the option market using the model free implied volatility.
Journal ArticleDOI
Stock Market Uncertainty and the Stock-Bond Return Relation
TL;DR: This article examined whether time variation in the comovements of daily stock and Treasury bond returns can be linked to measures of stock market uncertainty, specifically the implied volatility from equity index options and detrended stock turnover.
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The dynamics of stochastic volatility: evidence from underlying and options markets
TL;DR: In this article, a more general parametric stochastic variance model of equity index returns is proposed and estimates using data from both underlying and options markets, and the model fails to explain the implied volatility smile for short-dated options and conditional higher moments in returns.
References
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Journal ArticleDOI
Conditional heteroskedasticity in asset returns: a new approach
TL;DR: In this article, an exponential ARCH model is proposed to study volatility changes and the risk premium on the CRSP Value-Weighted Market Index from 1962 to 1987, which is an improvement over the widely-used GARCH model.
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On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks
TL;DR: In this article, a modified GARCH-M model was used to find a negative relation between conditional expected monthly return and conditional variance of monthly return, using seasonal patterns in volatility and nominal interest rates to predict conditional variance.
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ARCH modeling in finance: A review of the theory and empirical evidence
TL;DR: An overview of some of the developments in the formulation of ARCH models and a survey of the numerous empirical applications using financial data can be found in this paper, where several suggestions for future research, including the implementation and tests of competing asset pricing theories, market microstructure models, information transmission mechanisms, dynamic hedging strategies, and pricing of derivative assets, are also discussed.
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Quasi-maximum likelihood estimation and inference in dynamic models with time-varying covariances
TL;DR: In this paper, the authors study the properties of the quasi-maximum likelihood estimator and related test statistics in dynamic models that jointly parameterize conditional means and conditional covariances, when a normal log-likelihood is maximized but the assumption of normality is violated.
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Answering the skeptics: yes, standard volatility models do provide accurate forecasts*
TL;DR: In this article, a voluminous literature has emerged for modeling the temporal dependencies in financial market volatility using ARCH and stochastic volatility models and it has been shown that volatility models produce strikingly accurate inter-daily forecasts for the latent volatility factor that would be of interest in most financial applications.