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99
Forecasting future volatility from option prices, Working
, 2000
"... Weisbach are gratefully acknowledged. I bear full responsibility for all remaining errors. Forecasting Future Volatility from Option Prices Evidence exists that option prices produce biased forecasts of future volatility across a wide variety of options markets. This paper presents two main results. ..."
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Cited by 21 (1 self)
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Weisbach are gratefully acknowledged. I bear full responsibility for all remaining errors. Forecasting Future Volatility from Option Prices Evidence exists that option prices produce biased forecasts of future volatility across a wide variety of options markets. This paper presents two main results. First, approximately half of the forecasting bias in the S&P 500 index (SPX) options market is eliminated by constructing measures of realized volatility from five minute observations on SPX futures rather than from daily closing SPX levels. Second, much of the remaining forecasting bias is eliminated by employing an option pricing model that permits a nonzero market price of volatility risk. It is widely believed that option prices provide the best forecasts of the future volatility of the assets which underlie them. One reason for this belief is that option prices have the ability to impound all publicly available information – including all information contained in the history of past prices – about the future volatility of the underlying assets. A second related reason is that option pricing theory maintains that if an option prices fails to embody optimal forecasts of the future volatility of the underlying asset, a profitable trading strategy should be available whose implementation would push the option price to the level that reflects the best possible forecast of future volatility.
Stochastic Volatility
, 2005
"... Stochastic volatility (SV) is the main concept used in the fields of financial economics and mathematical finance to deal with the endemic timevarying volatility and codependence found in financial markets. Such dependence has been known for a long time, early comments include Mandelbrot (1963) and ..."
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Cited by 19 (0 self)
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Stochastic volatility (SV) is the main concept used in the fields of financial economics and mathematical finance to deal with the endemic timevarying volatility and codependence found in financial markets. Such dependence has been known for a long time, early comments include Mandelbrot (1963) and Officer (1973). It was also clear to the founding fathers of modern continuous time finance that homogeneity was an unrealistic if convenient simplification, e.g. Black and Scholes (1972, p. 416) wrote “... there is evidence of nonstationarity in the variance. More work must be done to predict variances using the information available. ” Heterogeneity has deep implications for the theory and practice of financial economics and econometrics. In particular, asset pricing theory is dominated by the idea that higher rewards may be expected when we face higher risks, but these risks change through time in complicated ways. Some of the changes in the level of risk can be modelled stochastically, where the level of volatility and degree of codependence between assets is allowed to change over time. Such models allow us to explain, for example, empirically observed departures from BlackScholesMerton prices for options and understand why we should expect to see occasional dramatic moves in financial markets. The outline of this article is as follows. In section 2 I will trace the origins of SV and provide links with the basic models used today in the literature. In section 3 I will briefly discuss some of the innovations in the second generation of SV models. In section 4 I will briefly discuss the literature on conducting inference for SV models. In section 5 I will talk about the use of SV to price options. In section 6 I will consider the connection of SV with realised volatility. A extensive reviews of this literature is given in Shephard (2005). 2 The origin of SV models The origins of SV are messy, I will give five accounts, which attribute the subject to different sets of people.
An adaptive evolutionary approach to option pricing via genetic programming
 Proceedings of the 6th International Conference on Computational Finance
, 1998
"... Please do not quote without permission * Chidambaran is visiting at NYU, on leave from Tulane. Lee holds joint appointments at Tulane and HKUST. Trigueros is at Tulane. We are grateful for the comments from participants at seminars at Tulane ..."
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Cited by 16 (0 self)
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Please do not quote without permission * Chidambaran is visiting at NYU, on leave from Tulane. Lee holds joint appointments at Tulane and HKUST. Trigueros is at Tulane. We are grateful for the comments from participants at seminars at Tulane
Conditional Risk and Performance Evaluation: Volatility Timing, Overconditioning, and New Estimates of Momentum Alphas
, 2009
"... Unconditional alpha estimates are biased when conditional beta covaries with market risk premia (“markettiming”) or volatility (“volatilitytiming”). We demonstrate an additional bias (“overconditioning”) that can occur any time an empiricist uses a risk proxy not in the investor information set — ..."
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Cited by 12 (2 self)
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Unconditional alpha estimates are biased when conditional beta covaries with market risk premia (“markettiming”) or volatility (“volatilitytiming”). We demonstrate an additional bias (“overconditioning”) that can occur any time an empiricist uses a risk proxy not in the investor information set — for example when asset payoffs are nonlinear and the conditional loading is proxied by contemporaneous realized beta. Calibrating to U.S. equity returns, volatilitytiming and overconditioning plausibly impact alphas much more than markettiming, which has been the focus of prior literature. A variety of instrumental variables estimators using realized betas can substantially correct market and volatilitytiming biases, while eliminating overconditioning. Empirically, appropriate instrumentation reduces momentum alphas by 2040 % relative to unconditional, whereas overconditioned alphas overstate performance by up to 2.5 times. Volatilitytiming inflates unconditionally estimated momentum alpha because the formationperiod market return (i) positively predicts holdingperiod beta (Grundy and Martin, 2001) and (ii) negatively predicts holdingperiod market volatility (French, Schwert, and Stambaugh,
Stochastic volatility: origins and overview
 Handbook of Financial Time Series
, 2008
"... Stochastic volatility (SV) models are used heavily within the fields of financial economics and mathematical finance to capture the impact of timevarying volatility on financial markets and decision making. The development of the subject has been highly multidisciplinary, with results drawn from fi ..."
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Cited by 11 (0 self)
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Stochastic volatility (SV) models are used heavily within the fields of financial economics and mathematical finance to capture the impact of timevarying volatility on financial markets and decision making. The development of the subject has been highly multidisciplinary, with results drawn from financial economics, probability theory and econometrics blending to produce methods that
Using Implied Volatility to Measure Uncertainty About Interest Rates.” Federal Reserve
 Bank of St. Louis Review, May/June
"... Option prices can be used to infer the level of uncertainty about future asset prices. The first two parts of this article explain such measures (implied volatility) and how they can differ from the market’s true expectation of uncertainty. The third then estimates the implied volatility of threemon ..."
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Cited by 9 (3 self)
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Option prices can be used to infer the level of uncertainty about future asset prices. The first two parts of this article explain such measures (implied volatility) and how they can differ from the market’s true expectation of uncertainty. The third then estimates the implied volatility of threemonth eurodollar interest rates from 1985 to 2001 and evaluates its ability to predict realized volatility. Implied volatility shows that uncertainty about shortterm interest rates has been falling for almost 20 years, as the levels of interest rates and inflation have fallen. And changes in implied volatility are usually coincident with major news about the stock market, the real economy, and monetary policy. Federal Reserve Bank of St. Louis Review, May/June 2005, 87(3), pp. 40725. Economists often use asset prices along with models of their determination to derive financial markets ’ expectations of events. For example, monetary economists use federal funds futures prices to measure expectations of interest rates (Krueger and Kuttner, 1995; Pakko and Wheelock, 1996). Similarly, a large literature on fixed and target zone exchange rates has used forward exchange rates to measure the credibility of exchange rate regimes or to predict their collapse (Svensson,
Improving portfolio selection using optionimplied volatility and skewness, Working Paper
, 2009
"... Our objective in this paper is to examine whether one can use optionimplied information to improve the selection of portfolios with a large number of stocks, and to document which aspects of optionimplied information are most useful for improving their outofsample performance. Portfolio performa ..."
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Cited by 7 (2 self)
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Our objective in this paper is to examine whether one can use optionimplied information to improve the selection of portfolios with a large number of stocks, and to document which aspects of optionimplied information are most useful for improving their outofsample performance. Portfolio performance is measured in terms of four metrics: volatility, Sharpe ratio, certaintyequivalent return, and turnover. Our empirical evidence shows that, while using optionimplied volatility and correlation does not improve significantly the portfolio volatility, Sharpe ratio, and certaintyequivalent return, exploiting information contained in the volatility risk premium and optionimplied skewness increases substantially both the Sharpe ratio and certaintyequivalent return, although this is accompanied by higher turnover. And, the volatility risk premium and optionimplied skewness help improve not just the performance of meanvariance portfolios, but also the performance of parametric portfolios developed in Brandt, SantaClara, and Valkanov (2009).
A Dual Russian Option for Selling Short
 Proc. Kolmogorov Probability Seminar
, 1993
"... We propose a new call option where the option seller pays the minimum price (in inflated dollars) that the asset has ever traded at during the time period (which may be indefinitely long) between the selling time and the delivery time (to be chosen by the seller). This option is the dual of the put ..."
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Cited by 7 (1 self)
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We propose a new call option where the option seller pays the minimum price (in inflated dollars) that the asset has ever traded at during the time period (which may be indefinitely long) between the selling time and the delivery time (to be chosen by the seller). This option is the dual of the put option where the option buyer receives the maximum price (in discounted dollars) that the asset has ever traded at during the time period (which may be indefinitely long) between the buying time and the exercise time (to be chosen by the buyer). Because the settlement payoff is at the minimum (for the call) or the maximum (for the put) there is reduced regret in the sense that it is not necessary for the option holder to worry about missing a good price in the recent past (of course he may regret not holding on longer) since he gets the best price up to the settlement time. We give the exact simple formula for the optimal expected present value (fair price) that can be derived from the opt...