This issue of The Journal of Risk contains papers that focus on modeling dependence via copulas and on identifying independent risk factors for better portfolio risk attribution. It also includes an extension of a classical portfolio selection problem to account for bond default, as well as an approach to compare mutual funds on the basis of hard-to-measure social and environmental criteria.
In the first paper of this issue, "Impact of nonstationarity on estimating and modeling empirical copulas of daily stock returns", Marcel Wollschläger and Rudi Schäfer conduct an empirical study that systematically distinguishes between local and global behavior of correlated time series. Their findings suggest copulas that best capture asymmetry in the tails when dependence is not stationary, especially during periods of high volatility.
In "Path-consistent wrong-way risk: a structural model approach", the second paper in the issue, Markus Hofer considers wrong way risk, which is present when the probability of default of a counterparty increases with the value of a credit portfolio. Here, too, the author uses copulas to capture dependence in a way that is useful for credit valuation adjustment, satisfying a path-consistent weight requirement, which in turn provides a framework for model calibration.
In our third paper, "Decomposition of portfolio risk into independent factors using an inductive causal search algorithm", Brian Deaton applies a search method to identify the set of independent factors affecting the returns of a portfolio. As a consequence, risk attribution and decomposition in portfolio strategies is better conducted.
The issue concludes with two short notes.
In "Optimal asset management for defined-contribution pension funds with default risk", Shibo Bian, James Cicon and Yi Zhang extend the classical portfolio selection problem involving a bond and a stock in the presence of a risk-free rate. They provide closed-form solutions for non-self-financing strategies in the presence of defaultable bonds. They show, in particular, that investment in the defaultable bond increases with the jump-risk premium and time to maturity.
In the second note, "A fuzzy data envelopment analysis model for evaluating the efficiency of socially responsible and conventional mutual funds", I. Baeza-Sampere, V. Coll-Serrano, B. M'zali and P. Méndez-Rodríguez show how data envelopment analysis can be used to assess the performance of mutual funds along a dimension that goes beyond standard measures: namely, that of a social and environmental index, for which fuzzy set theory is useful given the difficulty in measuring the index inputs.
University of Florida
This paper investigates the extent to which the nonstationarity of financial time series affects both the estimation and the modeling of empirical copulas.
The author of this paper presents a general and path-consistent wrong-way risk (WWR) model that does not require simulation of credit and market variables simultaneously.
This paper presents a method to estimate and decompose a portfolio’s risk along independent factors.
This paper explores how a defined-contribution pension fund optimally distributes wealth between a defaultable bond, a stock and a bank account, given that a salary is a stochastic process.
A fuzzy data envelopment analysis model for evaluating the efficiency of socially responsible and conventional mutual funds
The authors of this paper use data envelopment analysis (DEA) to assess the relative efficiency of a sample of US equity mutual funds.