Rajna Gibson

Financial Integration, Economic Instability and Trade Structure in Emerging Markets

In this study, we estimate the level of financial integration using a multivariate GARCH(1,1)-M return generating model allowing for partial market integration as well as for the pricing of systematic emerging market risk. We find that emerging markets still remain to a large extent segmented and that financial integration has decreased during the financial crises of the 1990s. We next investigate the relationship between a countrys trade concentration and its level of financial integration. We find that countries with an undiversified trade structure have more integrated financial markets. Finally, our results suggest that countries less open to trade are more segmented.

The pricing of systematic liquidity risk: Empirical evidence from the US stock market

Abstract In this study, we examine whether aggregate market liquidity risk is priced in the US stock market. We define a bivariate Garch (1,1)-in-mean specification for the market portfolio excess returns and the changes in the standardized number of shares in the S&P 500 Index, the aggregate market liquidity proxy. The findings, based on monthly data, suggest that systematic liquidity risk is priced in the US over the period January 1973–December 1997. The liquidity premium represents a non-negligible, negative and time-varying component of the total market risk premium whose magnitude is not influenced by the October’87 Crash.

Performance in the Hedge Funds Industry: An Analysis of Short- and Long-Term Persistence

In this study, we analyze the performance persistence of hedge funds over short- and long-term horizons. Using a non-parametric test, we first observe that the Relative Value and the Specialist Credit strategies contain the highest proportion of outperforming managers. We next analyze the performance persistence of portfolios ranked according to their average past returns. Persistence is mainly observed over one- to three-month holding periods but rapidly vanishes as the formation or the holding period is lengthened. We finally examine long-term risk-adjusted returns persistence of hedge fund portfolio within an APT framework. This leads us to detect a slight overreaction pattern that is more pronounced among the directional hedge fund strategies.

Model Risk for European-Style Stock Index Options

In empirical modeling, there have been two strands for pricing in the options literature, namely the parametric and nonparametric models. Often, the support for the nonparametric methods is based on a benchmark such as the Black-Scholes (BS) model with constant volatility. In this paper, we study the stochastic volatility (SV) and stochastic volatility random jump (SVJ) models as parametric benchmarks against feedforward neural network (FNN) models, a class of neural network models. Our choice for FNN models is due to their well-studied universal approximation properties of an unknown function and its partial derivatives. Since the partial derivatives of an option pricing formula are risk pricing tools, an accurate estimation of the unknown option pricing function is essential for pricing and hedging. Our findings indicate that FNN models offer themselves as robust option pricing tools, over their sophisticated parametric counterparts in predictive settings. There are two routes to explain the superiority of FNN models over the parametric models in forecast settings. These are nonnormality of return distributions and adaptive learning

Stock Market Performance and the Term Structure of Credit Spreads

We build a structural two-factor model of default where the stock market index is one of the stochastic factors. We allow the firm to adjust its leverage ratio in response to changes in the business climate for which the past performance of the stock market index acts as a proxy. We assume that the firms log-leverage ratio follows a mean-reverting process and that the past performance of the stock index negatively affects the firms target leverage ratio. We show that for most credit ratings our model may explain actual yield spreads better than other well-known structural credit risk models. Also, our model shows that the past performance of the stock index returns and the firms assets beta have a significant impact on credit spreads. Hence, our model can explain why credit spreads may be different within the same credit rating groups and why spreads are lower during economic expansions and higher during recessions.

Interest rate model risk: an overview

Model risk is becoming an increasingly important concept not only in ®nancial valuation but also for risk management issues and capital adequacy purposes. Model risk arises as a consequence of incorrect modeling, model identi®cation or speci®cation errors, and inadequate estimation procedures, as well as from the application of mathematical and statistical properties of ®nancial models in imperfect ®nancial markets. In this paper, the authors provide a de®nition of model risk, identify its possible origins, and list the potential problems, before ®nally illustrating some of its consequences in the context of the valuation and risk management of interest rate contingent claims.

Hedge fund alphas: do they reflect managerial skills or mere compensation for liquidity risk bearing?

In this article, we study the effect of liquidity risk on the performance of various hedge fund portfolio strategies. The portfolio strategies in each hedge fund style are formed by incorporating predictability in: (i) managerial skills, (ii) fund risk loadings, and (iii) benchmark returns. As in Avramov et al. (2007), we find that, before taking into account the effect of liquidity risk, long-only constrained hedge fund style portfolios that incorporate predictability in managerial skills generate superior performance. However, the outperformance disappears or weakens dramatically for seven out of ten types of hedge fund style portfolios once the effect of liquidity risk is incorporated into the performance evaluation framework. Hence, for most hedge fund style-based portfolio strategies, “alphas” to a large extend reflect mere compensation for liquidity risk bearing. These results are robust to: (i) an alternative performance evaluation model (ii) an alternative liquidity risk proxy, (iii) the exclusion of the January effect on the liquidity premium and (iv) the exclusion of the recent financial crises data.

Margining in derivatives markets and the stability of the banking sector

We investigate the effects of margining, a widely-used mechanism to attach collateral to derivatives contracts, on derivatives’ trading volume, default risk, and on the welfare in the banking sector. First, we develop a stylized banking sector equilibrium model to derive a set of testable hypotheses. Subsequently, we test these hypotheses with a simulation model that captures some of the essential characteristics of over-the-counter derivatives markets. Contrarily to the common belief that margining always reduces default risk, we find that there exist situations in which margining increases default risk, reduces aggregate derivatives’ trading volume, and has an ambiguous effect on welfare in the banking sector. The negative effects of margining are exacerbated during periods of market stress when margin rates are high and collateral is scarce. We also find that central counterparties only lift some of the inefficiencies caused by margining.

Technical Analysis Techniques versus Mathematical Models: Boundaries of Their Validity Domains

We aim to compare financial technical analysis techniques to strategies which depend on a mathematical model. In this paper, we consider the moving average indicator and an investor using a risky asset whose instantaneous rate of return changes at an unknown random time. We construct mathematical strategies. We compare their performances to technical analysis techniques when the model is misspecified. The comparisons are based on Monte Carlo simulations.

Recovery Risk in Stock Returns

The authors provide evidence that the power of book–to–market and size attributes in explaining the cross–section of stock returns may, in part, lie in the fact that these concepts subsume useful information regarding both the probability of bankruptcy and recovery rates. Other research that focuses primarily on the probability of default concludes that investors do not care about financial distress risk. The authors argue, however, that this conclusion may be premature, as the evidence suggests that investors are concerned, ex ante, about recovery rate risk as well. The findings here have important portfolio management implications.