Journal of Financial Econometrics - recent issues

The JFEC Invited Lecture at the 2008 SoFiE Conference

Garcia, R., Ghysels, E., Renault, E. — 2009-06-24

Inference on Risk-Neutral Measures for Incomplete Markets

Kaido, H., White, H. — 2009-06-24

This paper proposes an econometric framework to estimate market risk prices associated with risk-neutral measures Q under incomplete markets. We show that, under incomplete markets, the market price of risk is not point-identified but is instead identified as a bounded subset of an affine subspace. On the other hand, a structural assumption fully identifies diffusion coefficients for the data-generating probability measure P. We apply Kaido and White's (2008, Discussion Paper, University of California, San Diego) two-stage extension of Chernozhukov, Hong, and Tamer's (2007, Econometrica, 75(5), 1243–1284) partial identification framework to construct a set estimator and confidence regions for the identified set of market risk prices and to test hypotheses. We apply our results to study international risk sharing and risk premiums for market cap range indexes.

A Dynamic Asset Pricing Model with Time-Varying Factor and Idiosyncratic Risk

Glabadanidis, P. — 2009-06-24

This paper uses a multivariate GARCH model to account for time variation in factor loadings and idiosyncratic risk in improving the performance of the CAPM and the three-factor Fama–French model. I show how to incorporate time variation in betas and the second moments of the residuals in a very general way. Both the static and conditional CAPM substantially outperform the three-factor model in pricing industry portfolios. Using a dynamic CAPM model results in a 30% reduction in the average absolute pricing error of size/book-to-market portfolios. Ad hoc analysis shows that the market beta of a value-minus-growth portfolio decreases whenever the default premium increases as well as during economic recessions.

Measuring Event Risk

Nyberg, P., Wilhelmsson, A. — 2009-06-24

This paper decomposes the popular risk measure Value-at-Risk (VaR) into one jump- and one continuous component. The continuous component corresponds to general market risk and the jump component is proportional to the event risk as defined in the Basel II accord. We find that event risk, which is currently not incorporated into most banks' VaR models, comprises a substantial part of total VaR. It constitutes 30% of the risk for a portfolio of small cap stocks but less than 1% for a portfolio of large cap stocks. The national supervising agency in each membership country is advised by the Basel rules to add an additional capital charge to a bank whose models do not capture event risk. The large variation in event risk, also found across 10 individual stocks, suggests that an approach that varies the capital surcharge, based on the type of asset, should be used by the supervisors.

Using High-Frequency Transaction Data to Estimate the Probability of Informed Trading

Tay, A., Ting, C., Tse, Y. K., Warachka, M. — 2009-06-24

This paper applies the asymmetric autoregressive conditional duration (AACD) model of Bauwens and Giot (2003) to estimate the probability of informed trading (PIN) using irregularly spaced transaction data. We model trade direction (buy versus sell orders) and the duration between trades jointly. Unlike the Easley, Hvidkjaer, and O'Hara (2002) approach, which uses the aggregate numbers of daily buy and sell orders to estimate PIN, our methodology allows for interactions between consecutive buy-sell orders and accounts for the duration between trades and the volume of trade. We extend the Easley–Hvidkjaer–O'Hara framework by allowing the probabilities of good news and bad news to vary each day. Our PIN estimates can be computed daily as well as over intraday intervals.

A New Look at the Forward Premium Puzzle

Gospodinov, N. — 2009-06-24

This paper analyzes the sampling properties of the widely documented large negative slope estimates in regressions of future exchange returns on current forward premium. We argue that the abnormal behavior of the slope estimators in these regressions arises from the simultaneous presence of high persistence, low signal-to-noise ratio, strong endogeneity, and an omitted variable problem. The paper develops the limiting theory for the slope parameter estimators in the levels and differenced forward premium regressions under some assumptions that match the empirical properties of the data. The asymptotic results derived in the paper help to reconcile the findings from the levels and difference specifications and provide important insights about the time-series properties of the implied risk premium.

Nonparametric Option Pricing with No-Arbitrage Constraints

Birke, M., Pilz, K. F. — 2009-03-12

We propose a completely kernel based method of estimating the call price function or the state price density of options. The new estimator of the call price function fulfills the constraints like monotonicity and convexity given in Breeden and Litzenberger (1978) without necessarily estimating the state price density for an underlying asset price from its option prices. It can be shown that the call price estimator is pointwise consistent and asymptotically normal. The estimator of the state price density is also consistent. In a simulation study we compare the new estimators to the estimators given in Aït-Sahalia and Duarte (2003).

The Impact of Shocks on Higher Moments

Jondeau, E., Rockinger, M. — 2009-03-12

In this paper, we extend the concept of the news impact curve of volatility developed by Engle and Ng (1993) to the higher moments and co-moments of the multivariate generalized autoregressive conditional heteroskedasticity (GARCH) model with non-normal innovations. For this purpose, we present a new methodology to describe the joint distribution of GARCH processes in a non-normal setting. Then, we provide expressions for the response of the moments of the subsequent distribution to a shock. This tool enhances the understanding of the temporal evolution of the joint distribution. We use our methodology to provide stylized facts for the four largest international stock markets. In particular, we document the persistence of large (positive or negative) daily returns. In a multivariate setting , we find that foreign holdings provide a good hedge against changes in domestic volatility after good shocks but a bad hedge after crashes. Finally, using generalized impulse responses, we show that the effect of shocks on the higher moments of the distribution is short-lasting.

Estimation and Testing for Dependence in Market Microstructure Noise

Ubukata, M., Oya, K. — 2009-03-12

This paper proposes new test statistics for the dependence and cross and auto covariance estimators of bivariate noise processes. It derives their asymptotic distributions and provides additional tests for the statistical significance of covariance estimators. Monte Carlo simulation shows that the covariance estimators and test statistics perform better in a finite sample. Further evidence from empirical illustration suggests that the covariance estimators and proposed test statistics are capable of capturing various dependence patterns in market microstructure noise. These results can shed more light on the sign of noise autocorrelation in the presence of market microstructure frictions such as bid-ask bounces and the clustering of order flow.

Estimation Risk-Adjusted Sharpe Ratio and Fund Performance Ranking under a General Return Distribution

Bao, Y. — 2009-03-12

We study the sample estimation risk of the traditional Sharpe ratio without the restrictive assumption of normality for return series. We derive analytical results for the approximate bias and variance of the sample Sharpe ratio in terms of the underlying distribution parameters. The results clarify several misinterpretations existing in the literature. A Monte Carlo study shows that our bias and variance formulae approximate the true moments of the sample Sharpe ratio remarkably well. We propose using the analytical results to design an estimation risk-adjusted Sharpe ratio. An empirical study of mutual fund performance shows that using the adjusted Sharpe ratio gives a quite different performance ranking of those traditionally top-ranked funds.

A Simple Approximate Long-Memory Model of Realized Volatility

Corsi, F. — 2009-03-12

The paper proposes an additive cascade model of volatility components defined over different time periods. This volatility cascade leads to a simple AR-type model in the realized volatility with the feature of considering different volatility components realized over different time horizons and thus termed Heterogeneous Autoregressive model of Realized Volatility (HAR-RV). In spite of the simplicity of its structure and the absence of true long-memory properties, simulation results show that the HAR-RV model successfully achieves the purpose of reproducing the main empirical features of financial returns (long memory, fat tails, and self-similarity) in a very tractable and parsimonious way. Moreover, empirical results show remarkably good forecasting performance.

The Society for Financial Econometrics (SoFiE) Inaugural Conference: New York, June 4-6, 2008

Ghysels, E. — 2008-12-18

Financial Econometrics, Financial Innovation, and Financial Stability

Plosser, C. I. — 2008-12-18

Innovation in financial markets, spurred to a significant extent by developments in finance theory and financial econometrics, has played a critical role in spurring economic growth. However, the current turmoil in financial markets raises fundamental questions about the nature of financial innovation and the role of policymakers in maintaining financial stability. This paper explores these questions, focusing on the complexities of modeling financial risk and the potential trade-off between policies aimed at combating short-run financial instability on the one hand and the potential financial market distortions and moral hazard that can result from such policies on the other.

A Short Introduction to Correlation Markets

Collin-Dufresne, P. — 2008-12-18

This short note gives a short overview of correlation markets and was prepared for the "Roundtable Discussion on Default Risk Correlation Models" given at the inaugural SoFiE-Conference in June 2008.

Linear Correlation and EVT: Properties and Caveats

Embrechts, P. — 2008-12-18

Due to the current credit crisis, critical questions are being asked concerning some of the quantitative methods used in risk management under the Basel II proposals. In this paper I have given a critical look at Extreme Value Theory and Copulas. Both their potential applications and the possible caveats are discussed, and this mainly with the subprime crisis as a background.

Correlation, Models, and Risk Management in Challenging Times

Lumsdaine, R. L. — 2008-12-18

This paper considers correlation, models, and risk management in light of recent financial market events. It begins with a review of key contributing factors, then considers the role of liquidity in measuring default risk, and highlights some lessons learned from the experience as events continue to unfold. It concludes by discussing some key ways in which regulators are moving forward to address the current situation, mitigate future risk, and strengthen the resiliency of the global financial system.