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19
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 10 (4 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).
Estimating option implied riskneutral densities using spline and hypergeometric functions
, 2007
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The Generalized Extreme Value (GEV) Distribution, Implied Tail Index and Option Pricing 1
, 2005
"... Crisis events such as the 1987 stock market crash, the Asian Crisis and the bursting of the DotCom bubble have radically changed the view that extreme events in financial markets have negligible probability. This paper argues that the use of the Generalized Extreme Value (GEV) distribution to model ..."
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Cited by 6 (2 self)
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Crisis events such as the 1987 stock market crash, the Asian Crisis and the bursting of the DotCom bubble have radically changed the view that extreme events in financial markets have negligible probability. This paper argues that the use of the Generalized Extreme Value (GEV) distribution to model the Risk Neutral Density (RND) function provides a flexible framework that captures the negative skewness and excess kurtosis of returns, and also delivers the market implied tail index of asset returns. We obtain an original analytical closed form solution for the Harrison and Pliska (1981) no arbitrage equilibrium price for the European option in the case of GEV asset returns. The GEV based option prices successfully remove the well known pricing bias of the BlackScholes model. We explain how the implied tail index is efficacious at identifying the fat tailed behaviour of losses and hence the left skewness of the price RND functions, particularly around crisis events.
The Impact of Overnight Periods on Option Pricing
, 2006
"... This paper investigates the effect of closed overnight exchanges on option prices. During the trading day asset prices follow the literature’s standard affine model which allows for stochastic volatility and random jumps. Independently, the overnight asset price process is modelled by a single jump. ..."
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Cited by 4 (0 self)
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This paper investigates the effect of closed overnight exchanges on option prices. During the trading day asset prices follow the literature’s standard affine model which allows for stochastic volatility and random jumps. Independently, the overnight asset price process is modelled by a single jump. We find that the overnight component reduces the variation in the random jump process significantly. However, neither the random jumps nor the overnight jumps alone are able to empirically describe all features of option prices. We conclude that both random jumps during the day and overnight jumps are important in explaining option prices, where the latter account for about one quarter of total jump risk.
DYNAMIC DENSITY ESTIMATION WITH FINANCIAL APPLICATIONS
"... Empirical distributions in finance and economics might show heavy tails, volatility clustering, varying mean returns and multimodality as part of their features. However, most statistical models available in the literature assume some kind of parametric form (clearly neglecting important characteris ..."
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Cited by 1 (0 self)
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Empirical distributions in finance and economics might show heavy tails, volatility clustering, varying mean returns and multimodality as part of their features. However, most statistical models available in the literature assume some kind of parametric form (clearly neglecting important characteristics of the data) or focus on modeling extreme events (therefore, providing no information about the rest of the distribution). In this paper we develop a Bayesian nonparametric prior for a collection of distributions evolving in discrete time that is dense on the space of absolutely continuous distributions, and therefore allows for the special features mentioned above. The prior is constructed by defining the distribution at any time point as a Dirichlet process mixture of Gaussian distributions, and inducing dependence through the atoms of their stickbreaking decomposition. A general construction, which allows for trends, periodicities and regressors is described, but special emphasis is placed on developing autoregressive processes (AR) for sequences of distributions. The resulting model, labeled Distribution Autoregressive process (DAR) are applied to the estimation of the optionimplied risk neutral distribution of the S&P500 index.
Asset Allocation with OptionImplied Distributions: A ForwardLooking Approach *
, 2008
"... We address the empirical implementation of the static asset allocation problem by developing a forwardlooking approach that uses information from market option prices. To this end, constant maturity S&P 500 implied distributions are extracted and subsequently transformed to the corresponding ri ..."
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We address the empirical implementation of the static asset allocation problem by developing a forwardlooking approach that uses information from market option prices. To this end, constant maturity S&P 500 implied distributions are extracted and subsequently transformed to the corresponding riskadjusted ones. Then, optimal portfolios consisting of a risky and a riskfree asset are formed and their outofsample performance is evaluated. We find that the use of riskadjusted implied distributions makes the investor significantly better off compared with the case where she uses the historical distribution of returns to calculate her optimal strategy. The results hold under a number of evaluation metrics and utility functions and carry through even when transaction costs are taken into account. An extension of the approach to a dynamic asset allocation setting is also presented.
IN BOND MARKET EXPECTATIONS AROUND MONETARY POLICY ACTIONS OF THE ECB 1
, 2004
"... In 2004 all publications will carry a motif taken from the €100 banknote. This paper can be downloaded without charge from ..."
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In 2004 all publications will carry a motif taken from the €100 banknote. This paper can be downloaded without charge from
1 The Informational Content of Financial Options for Quantitative Asset Management: A Review
"... The view that informed investors might choose to trade derivatives has been shared by both academics and practitioners from as early as the introduction of options trading in the early 1970s. Black (1975) claims that “...Since an investor can get more action for a given investment in options than he ..."
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The view that informed investors might choose to trade derivatives has been shared by both academics and practitioners from as early as the introduction of options trading in the early 1970s. Black (1975) claims that “...Since an investor can get more action for a given investment in options than he can by investing directly in the underlying stock, he may choose
Dynamics of Implied Distributions: Evidence from the CAC 40 Options Market
, 2009
"... This paper discusses the dynamics of the entire riskneutral density, based on a Principal Component Analysis (PCA) of distribution curves calculated using a moneyness metric. The PCA revealed a limited number of factors that influence these dynamics. This paper outlines the time series of these fac ..."
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This paper discusses the dynamics of the entire riskneutral density, based on a Principal Component Analysis (PCA) of distribution curves calculated using a moneyness metric. The PCA revealed a limited number of factors that influence these dynamics. This paper outlines the time series of these factors and shows that at least one of them, displaying a strong correlation with the distribution variance, contains jumps. These findings are consistent with recent research showing that a jump component exists in the shock factors affecting implied volatility surfaces. Finally, this paper gives an example of how these findings can be applied to options portfolio hedging.