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172
Implied Volatility Functions: Empirical Tests
, 1995
"... Black and Scholes (1973) implied volatilities tend to be systematically related to the option's exercise price and time to expiration. Derman and Kani (1994), Dupire (1994), and Rubinstein (1994) attribute this behavior to the fact that the Black/Scholes constant volatility assumption is violated in ..."
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Cited by 167 (2 self)
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Black and Scholes (1973) implied volatilities tend to be systematically related to the option's exercise price and time to expiration. Derman and Kani (1994), Dupire (1994), and Rubinstein (1994) attribute this behavior to the fact that the Black/Scholes constant volatility assumption is violated in practice. These authors hypothesize that the volatility of the underlying asset's return is a deterministic function of the asset price and time. Since the volatility function in their model has an arbitrary specification, the deterministic volatility (DV) option valuation model has the potential of fitting the observed crosssection of option prices exactly. Using a sample of S&P 500 index options during the period June 1988 and December 1993, we attempt to evaluate the economic significance of the implied volatility function by examining the predictive and hedging performance of the DV option valuation model. Discussion draft: September 8, 1995 ____________________________________________...
Post'87 Crash Fears in the S&P 500 Futures Option Market
, 1998
"... Postcrash distributions inferred from S ..."
Recovering Risk Aversion from Option Prices and Realized Returns. Manuscript
, 1998
"... A relationship exists between aggregate riskneutral and subjective probability distributions and risk aversion functions. Using a variation of the method developed by Jackwerth and Rubinstein (1996), we estimate riskneutral probabilities reliably from option prices. Subjective probabilities are es ..."
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Cited by 104 (3 self)
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A relationship exists between aggregate riskneutral and subjective probability distributions and risk aversion functions. Using a variation of the method developed by Jackwerth and Rubinstein (1996), we estimate riskneutral probabilities reliably from option prices. Subjective probabilities are estimated from realized returns. This paper then introduces a technique to empirically derive risk aversion functions implied by option prices and realized returns simultaneously. These risk aversion functions dramatically change shapes around the 1987 crash: Precrash, they are positive and decreasing in wealth and thus consistent with standard economic theory. Postcrash, they are partially negative and increasing and irreconcilable with the theory. Overpricing of outofthemoney puts is the most likely cause. A simulated trading strategy exploiting this overpricing shows excess returns even after accounting for the possibility of further crashes and transaction costs. * Jens Carsten Jackwerth is a visiting assistant professor at the London Business School. For helpful discussions I
Do stock prices and volatility jump? Reconciling evidence from spot and option prices
, 2001
"... This paper studies the empirical performance of jumpdiffusion models that allow for stochastic volatility and correlated jumps affecting both prices and volatility. The results show that the models in question provide reasonable fit to both option prices and returns data in the insample estimation ..."
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Cited by 97 (2 self)
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This paper studies the empirical performance of jumpdiffusion models that allow for stochastic volatility and correlated jumps affecting both prices and volatility. The results show that the models in question provide reasonable fit to both option prices and returns data in the insample estimation period. This contrasts previous findings where stochastic volatility paths are found to be too smooth relative to the option implied dynamics. While the models perform well during the high volatility estimation period, they tend to overprice long dated contracts outofsample. This evidence points towards a too simplistic specification of the mean dynamics of volatility.
A Study towards a Unified Approach to the Joint Estimation of Objective and Risk Neutral Measures for the Purpose of Options Valuation
, 1999
"... The purpose of this paper is to bridge two strands of the literature, one pertaining to the objectiveorphysical measure used to model the underlying asset and the other pertaining to the riskneutral measure used to price derivatives. We propose a generic procedure using simultaneously the fundame ..."
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Cited by 74 (4 self)
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The purpose of this paper is to bridge two strands of the literature, one pertaining to the objectiveorphysical measure used to model the underlying asset and the other pertaining to the riskneutral measure used to price derivatives. We propose a generic procedure using simultaneously the fundamental price S t and a set of option contracts ### I it # i=1;m # where m # 1 and # I it is the BlackScholes implied volatility.We use Heston's #1993# model as an example and appraise univariate and multivariate estimation of the model in terms of pricing and hedging performance. Our results, based on the S&P 500 index contract, show that the univariate approach only involving options by and large dominates. Abyproduct of this #nding is that we uncover a remarkably simple volatility extraction #lter based on a polynomial lag structure of implied volatilities. The bivariate approachinvolving both the fundamental and an option appears useful when the information from the cash market ...
The Dynamics of Stochastic Volatility: Evidence from Underlying and Option Markets
, 2000
"... This paper proposes and estimates a more general parametric stochastic variance model of equity index returns than has been previously considered using data from both underlying and options markets. The parameters of the model under both the objective and riskneutral measures are estimated simultane ..."
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Cited by 72 (1 self)
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This paper proposes and estimates a more general parametric stochastic variance model of equity index returns than has been previously considered using data from both underlying and options markets. The parameters of the model under both the objective and riskneutral measures are estimated simultaneously. I conclude that the square root stochastic variance model of Heston (1993) and others is incapable of generating realistic returns behavior and find that the data are more accurately represented by a stochastic variance model in the CEV class or a model that allows the price and variance processes to have a timevarying correlation. Specifically, I find that as the level of market variance increases, the volatility of market variance increases rapidly and the correlation between the price and variance processes becomes substantially more negative. The heightened heteroskedasticity in market variance that results generates realistic crash probabilities and dynamics and causes returns to display values of skewness and kurtosis much more consistent with their sample values. While the model dramatically improves the fit of options prices relative to the square root process, it falls short of explaining the implied volatility smile for shortdated options.
Multivariate Density Forecast Evaluation and Calibration
 in Financial Risk Management: HighFrequency Returns on Foreign Exchange,” Review of Economics and Statistics
, 1999
"... educational and research purposes, so long as it is not altered, this copyright notice is reproduced with it, and it is not sold for profit. Abstract: We provide a framework for evaluating and improving multivariate density forecasts. Among other things, the multivariate framework lets us evaluate t ..."
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Cited by 72 (15 self)
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educational and research purposes, so long as it is not altered, this copyright notice is reproduced with it, and it is not sold for profit. Abstract: We provide a framework for evaluating and improving multivariate density forecasts. Among other things, the multivariate framework lets us evaluate the adequacy of density forecasts involving crossvariable interactions, such as timevarying conditional correlations. We also provide conditions under which a technique of density forecast “calibration ” can be used to improve deficient density forecasts. Finally, motivated by recent advances in financial risk management, we provide a detailed application to multivariate highfrequency exchange rate density forecasts.
Empirical pricing kernels
, 2001
"... This paper investigates the empirical characteristics of investor risk aversion over equity return states by estimating a timevarying pricing kernel, which we call the empirical pricing kernel (EPK). We estimate the EPK on a monthly basis from 1991 to 1995, using S&P 500 index option data and a sto ..."
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Cited by 70 (1 self)
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This paper investigates the empirical characteristics of investor risk aversion over equity return states by estimating a timevarying pricing kernel, which we call the empirical pricing kernel (EPK). We estimate the EPK on a monthly basis from 1991 to 1995, using S&P 500 index option data and a stochastic volatility model for the S&P 500 return process. We find that the EPK exhibits countercyclical risk aversion over S&P 500 return states. We also find that hedging performance is significantly improved when we use hedge ratios based the EPK rather than a timeinvariant pricing kernel.
Density Forecasting: A Survey
 Journal of Forecasting
, 2000
"... A density forecast of the realization of a random variable at some future time is an estimate of the probability distribution of the possible future values of that variable. This chapter presents a selective survey of applications of density forecasting in macroeconomics and finance, and discusses s ..."
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Cited by 65 (9 self)
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A density forecast of the realization of a random variable at some future time is an estimate of the probability distribution of the possible future values of that variable. This chapter presents a selective survey of applications of density forecasting in macroeconomics and finance, and discusses some issues concerning the production, presentation, and evaluation of density forecasts. This chapter first appeared as an article with the same title in Journal of Forecasting, 19 (2000), 235254. The helpful comments and suggestions of Frank Diebold, Stewart Hodges and two anonymous referees are gratefully acknowledged. Subsequent editorial changes have been made following suggestions from the editors of this volume. Responsibility for errors remains with the authors. 2 1. INTRODUCTION A density forecast of the realization of a random variable at some future time is an estimate of the probability distribution of the possible future values of that variable. It thus provides a complet...
Evaluating Density Forecasts of Inflation: The Survey of Professional Forecasters
 in Cointegration, Causality, and Forecasting: A Festschrift in Honour of Clive
, 1999
"... educational and research purposes, so long as it is not altered, this copyright notice is reproduced with it, and it is not sold for profit. Abstract: Since 1968, the Survey of Professional Forecasters has asked respondents to provide a complete probability distribution of expected future inflation. ..."
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Cited by 56 (15 self)
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educational and research purposes, so long as it is not altered, this copyright notice is reproduced with it, and it is not sold for profit. Abstract: Since 1968, the Survey of Professional Forecasters has asked respondents to provide a complete probability distribution of expected future inflation. We evaluate the adequacy of those density forecasts using the framework of Diebold, Gunther and Tay (1998). The analysis reveals several interesting features of the density forecasts in relation to realized inflation, including several deficiencies of the forecasts. The probability of a large negative inflation shock is generally overestimated, and in more recent years the probability of a large shock of either sign is overestimated. Inflation surprises are serially correlated, although agents eventually adapt. Expectations of low inflation are associated with reduced uncertainty. The results suggest several promising directions for future research.