Article2003

Forecasting Volatility in Financial Markets: A Review

1,373 citations0/0 files storedJournal of Economic Literature

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Financial Risk and Volatility Modeling Stochastic processes and financial applications Forecasting Techniques and Applications

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.

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References

1973The Pricing of Options and Corporate Liabilities 1986Generalized autoregressive conditional heteroskedasticity 1982Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation 1991Conditional Heteroskedasticity in Asset Returns: A New Approach 1989A New Approach to the Economic Analysis of Nonstationary Time Series and the Business Cycle 1993On the Relation between the Expected Value and the Volatility of the Nominal Excess Return on Stocks 1993A Closed-Form Solution for Options with Stochastic Volatility with Applications to Bond and Currency Options 2007Brownian Motion and Stochastic Calculus

Cited by

2010Volatility forecast comparison using imperfect volatility proxies 2018Financial time series forecasting model based on CEEMDAN and LSTM 2005Value-at-Risk Prediction: A Comparison of Alternative Strategies 2005Forecasting daily variability of the S&P 100 stock index using historical, realised and implied volatility measurements 2001Uncovering the Risk-Return Relation in the Stock Market

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