Examining Asset Pricing Anomalies: Evidence from Europe

We examine five important asset pricing anomalies, namely, size, value, momentum, profitability, and investment rate to evaluate their efficacy in major West European economies, that is, France, Germany, Italy, and Spain. We employ four prominent asset pricing models, namely Capital Asset Pricing Model (CAPM), Fama–French three-factor (FF3) model, Carhart model and Fama–French five-factor (FF5) model to evaluate whether portfolio managers can create trading strategies to generate risk-adjusted extra normal returns for their investors. We also examine the prominent anomalies which pass the test of asset pricing in our sample countries and evaluate the best performing asset pricing model in explaining returns in each of these countries. We find that in spite of being matured markets, these countries provide portfolio managers with opportunities to exploit these strategies to generate extra normal returns for their investors. Momentum anomaly for Germany and profitability anomaly for Italy can be exploited by fund managers for generating risk-adjusted returns. For France, except for net investment rate anomaly, all the other anomalies remained unexplained by asset pricing models. We also find CAPM to be the better model in explaining returns of Italy and Spain. While FF3 factor and FF5 factor models explain returns in Germany, our sample asset pricing models failed to work for France. Our study has implications for portfolio managers, academia, and policymakers.

Pricing Anomalies and Arbitrage in Container Transport in India

Intermodal transportation requires multiple entities to manage diverse resources under complex regulations and contracts. In this paper, we carry out a multidisciplinary cross-functional analysis of container rail haulage pricing and operations in India. We discover that the total haulage cost of a container train unduly depends on the position of the containers within the train, which is referred to here as position arbitrage. The main objective of this paper is to introduce and analyze this new concept of arbitrage for the first time in the literature. We derive the limits to the arbitrage, present management insights and empirical results, and explain that the arbitrage is undesirable because of its adverse effects on the efficiency of the container supply chain. With a real case, we empirically show that container train operators can save an average of 450 million INR annually by exploiting the arbitrage. On completion of dedicated freight corridors, the annual total value of the arbitrage can increase by one billion Indian rupees. This research is also beneficial for the railways to understand the implications of haulage pricing on operational efficiency and also for the port operators and shippers to understand the implications of the arbitrage for their operations.

Mutual fund performance: Some recent evidence from European equity funds

This paper studies the performance of mutual funds that specialise in equity investment. We use a sample of the top sixteen actively managed European equity funds operating in the United States between July 1990 and November 2020. Using standard factor models, we show that none of our sample funds generated a positive and significant alpha. The observed funds could not outperform a simple passive strategy that involves tradeable European benchmark portfolios in the longer run. As a rule, the funds in our sample did not exploit the known asset pricing anomalies.

Hedge Funds, Arbitrage, and Timing

This paper is an extension of the work of Lawson and Schwartz (2018) which analyzes the risk-adjusted performance of hedge funds by employing a collection of four, five, seven, and eight-factor models. The purpose is to evaluate how well the top and bottom performing subset of hedge fund strategies have profited on known asset pricing anomalies during two unique time periods, 1994 to 2000 and 2001 to 2008. The bifurcation of the data into two distinct periods allows for a deeper exploration of the potential time-varying significance of estimated factor arbitrage. Our empirical testing suggests that both the top and bottom performing funds did utilize the asset growth anomaly to generate abnormal profits. Top performers tended to invest with a long emphasis on low asset growth, value firms while the bottom-five performing hedge fund strategies tested positive for a predilection towards going long small firms with low asset growth characteristics. Arguably, these outcomes probably align with the nature of the investment philosophy of each fund strategy. Interestingly, however, the time-varying significance of estimated coefficients for the value and returns momentum factors between the two distinct timeframes suggests either intentional or unintentional rotation between the use of available pricing anomalies and risk premiums.

Characteristic-Sorted Portfolios: Estimation and Inference

Portfolio sorting is ubiquitous in the empirical finance literature, where it has been widely used to identify pricing anomalies. Despite its popularity, little attention has been paid to the statistical properties of the procedure. We develop a general framework for portfolio sorting by casting it as a nonparametric estimator. We present valid asymptotic inference methods and a valid mean square error expansion of the estimator leading to an optimal choice for the number of portfolios. In practical settings, the optimal choice may be much larger than the standard choices of five or ten. To illustrate the relevance of our results, we revisit the size and momentum anomalies.