Kris Jacobs

The Determinants of Credit Default Swap Premia

Variables that in theory determine credit spreads have limited explanatory power in existing empirical work on corporate bond data. We investigate the linear relationship between theoretical determinants of default risk and default swap spreads. We find that estimated coefficients for a minimal set of theoretical determinants of default risk are consistent with theory and are significant statistically and economically. Volatility and leverage have substantial explanatory power in univariate and multivariate regressions. A principal component analysis of residuals and spreads indicates limited evidence for a residual common factor, confirming that the theoretical variables explain a significant amount of the variation in the data.

Which GARCH Model for Option Valuation

Characterizing asset return dynamics using volatility models is an important part of empirical finance. The existing literature on GARCH models favors some rather complex volatility specifications whose relative performance is usually assessed through their likelihood based on a time series of asset returns. This paper compares a range of GARCH models along a different dimension, using option prices and returns under the risk-neutral as well as the physical probability measure. We judge the relative performance of various models by evaluating an objective function based on option prices. In contrast with returns-based inference, we find that our option-based objective function favors a relatively parsimonious model. Specifically, when evaluated out-of-sample, our analysis favors a model that, besides volatility clustering, only allows for a standard leverage effect.

Is the Potential for International Diversification Disappearing? A Dynamic Copula Approach

International equity markets are characterized by nonlinear dependence and asymmetries. We propose a new dynamic asymmetric copula model to capture long-run and short-run dependence, multivariate nonnormality, and asymmetries in large cross-sections. We find that copula correlations have increased markedly in both developed markets (DMs) and emerging markets (EMs), but they are much lower for EMs than for DMs. Tail dependence has also increased but its level is still relatively low for EMs. We propose new measures of dynamic diversi?cation bene?ts that take into account higher order moments and nonlinear dependence. The bene?fits from international diversi?cation have reduced over time, drastically so for DMs. EMs still offer signi?cant diversi?cation bene?ts, especially during large market downturns.

Volatility Dynamics for the S&P500: Evidence from Realized Volatility, Daily Returns and Option Prices

Most recent empirical option valuation studies build on the affine square root (SQR) stochastic volatility model. The SQR model is a convenient choice, because it yields closed-form solutions for option prices. We investigate alternatives to the SQR model, by comparing its empirical performance with that of five different but equally parsimonious stochastic volatility models. We provide empirical evidence from three different sources: realized volatilities, S&P500 returns, and an extensive panel of option data. The three sources of data all point to the same conclusion: the best volatility specification is one with linear rather than square root diffusion for variance. This model captures the stylized facts in realized volatilities, it performs well in fitting various samples of index returns, andit has the lowest option implied volatility mean squared error in and out of sample. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.

Capturing Option Anomalies with a Variance-Dependent Pricing Kernel

We develop a GARCH option model with a new pricing kernel allowing for a variance premium. While the pricing kernel is monotonic in the stock return and in variance, its projection onto the stock return is nonmonotonic. A negative variance premium makes it U shaped. We present new semiparametric evidence to confirm this U-shaped relationship between the risk-neutral and physical probability densities. The new pricing kernel substantially improves our ability to reconcile the time-series properties of stock returns with the cross-section of option prices. It provides a unified explanation for the implied volatility puzzle, the overreaction of long-term options to changes in short-term variance, and the fat tails of the risk-neutral return distribution relative to the physical distribution. The Author 2013. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com., Oxford University Press.

Idiosyncratic Consumption Risk and the Cross-Section of Asset Returns

This paper investigates the importance of idiosyncratic consumption risk for the cross-sectional variation in asset returns. We find that besides the rate of aggregate consumption growth, the cross-sectional variance of consumption growth is also a priced factor. This suggests that consumers are not fully insured against idiosyncratic consumption risk, and that asset returns reflect their attempts to reduce their exposure to this risk. The resulting two-factor consumption-based asset pricing model significantly outperforms the CAPM, and its performance compares favorably with that of the Fama-French three-factor model. Copyright 2004 by The American Finance Association.

Option-Implied Measures of Equity Risk

Equity risk measured by beta is of great interest to both academics and practitioners. Existing estimates of beta use historical returns. Many studies have found option-implied volatility to be a strong predictor of future realized volatility. We find that option-implied volatility and skewness are also good predictors of future realized beta. Motivated by this finding, we establish a set of assumptions needed to construct a beta estimate from option-implied return moments using equity and index options. This beta can be computed using only option data on a single day. It is therefore potentially able to reflect sudden changes in the structure of the underlying company. Copyright 2011, Oxford University Press.

Is the Potential for International Diversification Disappearing

Quantifying the evolution of security co-movements is critical for asset pricing and portfolio allocation, and so we investigate patterns and trends in correlations and tail dependence over time using weekly returns for developed markets (DMs) and emerging markets (EMs) during the period 1973-2009. We use the DECO, DCC, and BEKK correlation models, and develop a novel dynamic t-copula to allow for dynamic tail dependence. We show that it is possible to characterize co-movements for many countries simultaneously. Correlations have significantly trended upward for both DMs and EMs, but correlations between EMs are lower than between DMs. Further, our evidence clearly contradicts the decoupling hypothesis. The tail dependence has also increased for both EMs and DMs, but its level is still very low for EMs as compared to DMs. Thus, while our correlation analysis suggests that the diversification potential of EMs has reduced over time, the tail dependence analysis suggests that EMs offer diversification benefits during large market moves.

Volatility Components, Affine Restrictions, and Nonnormal Innovations

Recent work by Engle and Lee (1999) shows that allowing for long-run and short-run components greatly enhances a GARCH model’s ability fit daily equity return dynamics. Using the risk-neutralization in Duan (1995), we assess the option valuation performance of the Engle-Lee model and compare it to the standard one-component GARCH(1,1) model. We also compare these non-affine GARCH models to one- and two- component models from the class of affine GARCH models developed in Heston and Nandi (2000). Using the option pricing methodology in Duan (1999), we then compare the four conditionally normal GARCH models to four conditionally non-normal versions. As in Hsieh and Ritchken (2005), we find that non-affine models dominate affine models both in terms of fitting return and in terms of option valuation. For the affine models we find strong evidence in favor of the component structure for both returns and options, but for the non-affine models the evidence is much less strong in option valuation. The evidence in favor of the non-normal models is strong when fitting daily returns, but the non-normal models do not provide much improvement when valuing options.

Incomplete Markets and Security Prices: Do Asset-Pricing Puzzles Result from Aggregation Problems?

This paper investigates Euler equations involving security prices and household-level consumption data. It provides a useful complement to many existing studies of consumption-based asset pricing models that use a representative-agent framework, because the Euler equations under investigation hold even if markets are incomplete. It also provides a useful complement to simulation-based studies of market incompleteness. The empirical evidence indicates that the theory is rejected by the data along several dimensions. The results therefore indicate that some well-documented asset-pricing puzzles do not result from aggregation problems for the preferences under investigation. Copyright The American Finance Association 1999.