[PDF] Yes Historical Volatility Does Contain Incremental Information Beyond Option Implied Volatility eBook

Author : Louis H. Ederington
Publisher :
Page : pages
File Size : 23,42 MB
Release : 1998
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This paper examines (1) whether implied volatility is an unbiased informationally efficient predictor of actual future volatility and (2) its predictive power. If markets are efficient and the option pricing model is correct, then the implied volatility calculated from option prices should be an unbiased and informationally efficient estimator of future volatility, that is, it should correctly impound all available information including the asset's price history. However, numerous studies have found that implied volatility is not informationally efficient and that historical volatilities have incremental predictive power -- often out-predicting implied volatilities. For the Samp;P 500 options on futures we find the following. One, at least part of the apparent inefficiency of implied volatility from past studies stems from measurement error which biases estimates of the importance of implied volatility downward and of the importance of historical volatility upward. Once we correct for this error, there is no significant inefficiency. Two, implied volatility has strong predictive power -- considerably stronger than found by previous equity index studies. Three, stock market volatility prediction results are quite sensitive to (1) the forecasting horizon and (2) whether the data period covers the October 1987 stock market crash.

Author : Martin Martens
Publisher :
Page : 0 pages
File Size : 22,37 MB
Release : 2008
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Recent evidence suggests option implied volatility provides better forecasts of financial volatility than time-series models based on historical daily returns. In particular it is found that daily GARCH forecasts have no or little incremental information over that already contained in implied volatilities. In this study both the measurement and the forecasting of financial volatility is improved using high-frequency data and the latest proposed model for volatility, a long memory model. The results indicate that volatility forecasts based on historical intraday returns do provide good volatility forecasts that can compete with implied volatility and sometimes even outperform implied volatility.

Author : Shiu-yan Eddie Pong
Publisher :
Page : 40 pages
File Size : 13,2 MB
Release : 2003
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We compare forecasts of the realized volatility of the pound, mark and yen exchange rates against the dollar, calculated from intraday rates, over horizons ranging from one day to three months. Our forecasts are obtained from a short memory ARMA model, a long memory ARFIMA model, a GARCH model and option implied volatilities. We find intraday rates provide the most accurate forecasts for the one-day and one-week forecast horizons while implied volatilities are at least as accurate as the historical forecasts for the one-month and three-month horizons. The superior accuracy of the historical forecasts, relative to implied volatilities, comes from the use of high frequency returns, and not from a long memory specification. We find significant incremental information in historical forecasts, beyond the implied volatility information, for forecast horizons up to one week.

Author : Bent Jesper Christensen
Publisher :
Page : 52 pages
File Size : 33,3 MB
Release : 2008
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A new research design is introduced for the empirical analysis of the relationship between implied volatility and ex-post realized volatility. The dynamics of volatility are emphasized, and the analysis is cast in terms of non-overlapping data, so that exactly one implied and one realized volatility estimate pertain to each period under consideration. The conclusions from the empirical analysis when using our design are significantly different from those previously reached. Recent literature indicates that implied volatility contains little information about future volatility, beyond that contained in the history of realized volatility. We show that on the contrary, implied volatility efficiently predicts future realized volatility and in particular subsumes the information content of past realized volatility.

Author : Ser-Huang Poon
Publisher : John Wiley & Sons
Page : 236 pages
File Size : 38,45 MB
Release : 2005-08-19
Category : Business & Economics
ISBN : 0470856157

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Financial market volatility forecasting is one of today's most important areas of expertise for professionals and academics in investment, option pricing, and financial market regulation. While many books address financial market modelling, no single book is devoted primarily to the exploration of volatility forecasting and the practical use of forecasting models. A Practical Guide to Forecasting Financial Market Volatility provides practical guidance on this vital topic through an in-depth examination of a range of popular forecasting models. Details are provided on proven techniques for building volatility models, with guide-lines for actually using them in forecasting applications.

Author : Emanuel Derman
Publisher : John Wiley & Sons
Page : 528 pages
File Size : 35,75 MB
Release : 2016-09-06
Category : Business & Economics
ISBN : 1118959167

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The Volatility Smile The Black-Scholes-Merton option model was the greatest innovation of 20th century finance, and remains the most widely applied theory in all of finance. Despite this success, the model is fundamentally at odds with the observed behavior of option markets: a graph of implied volatilities against strike will typically display a curve or skew, which practitioners refer to as the smile, and which the model cannot explain. Option valuation is not a solved problem, and the past forty years have witnessed an abundance of new models that try to reconcile theory with markets. The Volatility Smile presents a unified treatment of the Black-Scholes-Merton model and the more advanced models that have replaced it. It is also a book about the principles of financial valuation and how to apply them. Celebrated author and quant Emanuel Derman and Michael B. Miller explain not just the mathematics but the ideas behind the models. By examining the foundations, the implementation, and the pros and cons of various models, and by carefully exploring their derivations and their assumptions, readers will learn not only how to handle the volatility smile but how to evaluate and build their own financial models. Topics covered include: The principles of valuation Static and dynamic replication The Black-Scholes-Merton model Hedging strategies Transaction costs The behavior of the volatility smile Implied distributions Local volatility models Stochastic volatility models Jump-diffusion models The first half of the book, Chapters 1 through 13, can serve as a standalone textbook for a course on option valuation and the Black-Scholes-Merton model, presenting the principles of financial modeling, several derivations of the model, and a detailed discussion of how it is used in practice. The second half focuses on the behavior of the volatility smile, and, in conjunction with the first half, can be used for as the basis for a more advanced course.