Nonparametric estimation and testing of stochastic discount factor

This paper attempts to estimate stochastic discount factor (SDF) proxies nonparametrically using the conditional Hansen–Jagannathan distance. Nonparametric estimation can not only avoid misspecification when dealing with nonlinearity in the model but also provide more precise information about the local properties of the estimators. Empirical studies show that our method performs better than the alternative parametric polynomial models, and furthermore, we find that the return on aggregate wealth can sufficiently explain the SDF proxies when one deals with nonlinearity appropriately.     

Intertemporal efficiency analysis of sales teams of a bank: Stochastic semi-nonparametric approach

The primary role of a bank branch is evolving from a service provider towards a sales channel. Previous branch-level studies of sales efficiency consider a static setting of a single time period, ignoring the stochastic nature of sales outcomes. In this paper, we examine efficiency and performance of sales teams in a bank branch network over time, taking into account the changing demand and operational conditions, as well as random disturbances. The intertemporal sales frontier is estimated from the panel of monthly data over the years 2007–2010 using the stochastic semi-nonparametric envelopment of data (StoNED) method. The efficiency scores of sales teams and the trajectories of performance over time allow managers and the sales force to learn from past events and to develop the managerial and work practices across the network. While this study focuses on the case of a specific bank, some of the innovative features of our approach are applicable to sales efficiency assessment in other banks and financial institutions, as well as other network-based sales organizations.     

Productivity and efficiency at large and community banks in the US: A Bayesian true random effects stochastic distance frontier analysis

This paper compares the productivity and efficiency of large banks and community banks in the United States over the period 1997–2006. This comparison is performed by estimating a true random effects stochastic distance frontier model—a model that is capable of disentangling unobserved heterogeneity from inefficiency—within a Bayesian framework. We find that failure to consider unobserved heterogeneity results in a misleading ranking of banks and mismeasured technical efficiency, productivity growth, and returns to scale. Our results show that, compared with community banks, large banks have experienced much higher productivity growth and higher levels of returns to scale. Our estimates of total factor productivity growth show a clear downward trend for both large and community banks, and our decomposition of the output-distance-function-based Divisia productivity index indicates that technical change is the driving force behind this trend.     

Detecting abnormal credit union performance

Credit unions are an important financial intermediary, but little credit union research is done. A primary reason for the lack of research is the cooperative nature of the industry, making traditional methods of detecting abnormal performance inappropriate. This paper proposes two methods of detecting abnormal performance, one parametric, the other non-parametric. Instead of testing the efficiency of the institution, this paper proposes testing the return vector, as indicated in the theoretical objective function of the member. Simulations demonstrate that both methods are correctly specified and powerful.     

Bank loan recovery rates: Measuring and nonparametric density estimation

In this paper we analyse a comprehensive database of 149,378 recovery rates on Italian bank loans. We investigate a new methodology to compute the recovery percentage that we suggest to consider as a mixed random variable. To estimate the probability density function of such a mixture, we propose the mixture of beta kernels estimator and we analyse its performance by Monte Carlo simulations. The application of these proposals to the Bank of Italy’s data shows that, even if we remove the endpoints from the support of the recovery rate, the density function estimate is far from being a beta function.     

Stockholding: Participation, location, and spillovers

This paper provides the first joint analysis of household stockholding participation, location among stockholding modes, and participation spillovers. Our model matches observed participation, conditional and unconditional, and asset location patterns. We find that financial sophistication correlates strongly only with direct stockholding and mutual fund participation, while social interactions mainly influence stockholding through retirement accounts. Whether retirement account owners include stocks in their accounts strongly depends on owner characteristics, which is not the case with mutual fund owners and investment in stock funds. Stockholding is more common among retirement account owners, but mainly because of owner characteristics rather than of any participation spillovers from retirement account ownership.     

The evolution of cost-productivity and efficiency among US credit unions

Advances in information-processing technology have eroded the advantages of small scale and proximity to customers that traditionally enabled small lenders to thrive. Nonetheless, the membership and market share of US credit unions have increased, though their average size has also risen. We investigate changes in the efficiency and productivity of US credit unions during 1989–2006 by benchmarking the performance of individual firms against an estimated order-α quantile lying “near” the efficient frontier. We construct a cost analog of the Malmquist productivity index, which we decompose to estimate changes in cost and scale efficiency, and changes in technology. We find that cost-productivity fell on average across all credit unions but especially among smaller credit unions. Smaller credit unions confronted a shift in technology that increased the minimum cost required to produce given amounts of output. All but the largest credit unions also became less scale efficient over time.     

Estimating and testing beta pricing models: Alternative methods and their performance in simulations

We conduct a simulation analysis of the Fama and MacBeth[1973. Risk, returns and equilibrium: empirical tests. Journal of Political Economy 71, 607–636.] two-pass procedure, as well as maximum likelihood (ML) and generalized method of moments estimators of cross-sectional expected return models. We also provide some new analytical results on computational issues, the relations between estimators, and asymptotic distributions under model misspecification. The generalized least squares estimator is often much more precise than the usual ordinary least squares (OLS) estimator, but it displays more bias as well. A “truncated” form of ML performs quite well overall in terms of bias and precision, but produces less reliable inferences than the OLS estimator.     

Estimating the degree of operating efficiency gains from a potential bank merger and acquisition: A DEA bootstrapped approach

We propose a bootstrapped Data Envelopment Analysis (DEA)-based procedure to pre-calculate and pre-evaluate the short-run operating efficiency gains of a potential bank merger or acquisition (M&A). As an illustrative example, we apply our proposed procedure to investigate the degree of operating efficiency gains of 45 possible bank M&As in the Greek banking industry over the period from 2007 to 2011. The results reveal that a year before and a year after the initiation of the Greek fiscal crisis, the majority of the potential bank M&As under examination were unable to generate short-run operating efficiency gains. In addition, our results for 2011 indicate that the majority of bank M&As can lead to short-run operating efficiency gains. Finally, the empirical findings support the view that a merger or acquisition between efficient banks does not ensure an efficient bank M&A.     

Productivity and efficiency analysis of Shinkin banks: Evidence from bootstrap and Bayesian approaches

This paper analyzes the productivity and efficiency of Shinkin banks and the various prefectures in Japan, over the period from 2000 to 2006. We obtain estimates of efficiency growth and productivity growth, using the bootstrapped Malmquist index, and estimates of efficiency using the Bayesian distance frontier approach. We confirm that the efficiency growth and productivity growth of Shinkin banks did not improve significantly over the period of this study. In addition, we show that the efficiency of Shinkin banks is homogenous, with little variation across the banks analyzed. Methodologically, we also prove that a failure to impose theoretical regularity on the distance function could lead to false conclusions about the average efficiency or efficiency ranking of Shinkin banks. The study also includes an analysis of the correlates of productivity and efficiency growth, and provides efficiency and productivity estimates of the prefectures in which the banks are located.     

Liquidity and market efficiency: A large sample study

Chordia et al. (2008, hereafter CRS) examine short horizon return predictability from past order flows of large, actively traded NYSE firms across three tick size regimes and conclude that higher liquidity facilitates arbitrage trading which enhances market efficiency. We extend CRS to a comprehensive sample of all NYSE firms and examine the dynamics between liquidity and market efficiency during informational periods. Our results indicate that although all NYSE firms experience an overall improvement in market efficiency across periods of different tick size regimes, this improvement varies significantly across the portfolios of sample companies formed on the basis of trading frequency, market capitalization, and trading volume. After controlling for these factors, we further document a positive association between a continuous measure of liquidity and market efficiency, and show that this effect is amplified during periods that contain new information, as reflected in high adverse selection component of the bid-ask spread.     

Corporate social responsibility in the banking industry: Motives and financial performance

The current study investigates the association between corporate social responsibility (CSR) and financial performance (FP), and discusses the driving motives of banks to engage in CSR. Three motives, namely, strategic choices, altruism, and greenwashing, suggest that the relationship between CSR and FP is positive, non-negative, and non-existent, respectively. We obtained our sample, which covered 2003–2009, from the Ethical Investment Research Service (EIRIS) databank and Bankscope database. The data consists of 162 banks in 22 countries. We then classified the banks into four types based on their degree of engagement in CSR. This study proposes the use of an extended version of the Heckman two-step regression, in which the first step adopts a multinomial logit model, and the second step estimates the performance equation with the inverse Mills ratio generated by the first step. The empirical results show that CSR positively associates with FP in terms of return on assets, return on equity, net interest income, and non-interest income. In contrast, CSR negatively associates with non-performing loans. Hence, strategic choice is the primary motive of banks to engage in CSR.     

Nonparametric,conditional pricing of higher order multivariate contingent claims

This paper describes and applies a nonparametric model for pricing multivariate contingent claims. Multivariate contingent claims are contracts whose payoffs depend on the future prices of more than one underlying variable. The pricing however of these kinds of contracts represents a challenge. All known models are adaptations of earlier ones that have been introduced to price plain vanilla calls and puts. They are imposing strong assumptions on the distributional properties of the underlying variables. In contrast, this study adopts a methodology that relaxes such restrictions. Following [Barone-Adesi, G., Bourgoin, F., Giannopoulos, K., 1998. Don’t Look Back, Risk 11 (August), 100–104; Barone-Adesi, G., Engle, R., Mancini, L., 2004. GARCH Options in Incomplete Markets, mimeo, University of Applied Sciences of Southern Switzerland; Long, X., 2004. Semiparametric Multivariate GARCH Model, mimeo, University of California, Riverside], multivariate pathways for a set of underlying variables are constructed before the option payoffs are computed. This enables the covariances, in addition to the means and variances, to be modelled in a dynamic and nonparametric manner. The model is particular suitable for options whose payoffs depend on variables that are characterised by high nonlinearities and extremes and on higher order multivariate options whose underlying variables are more unlikely to conform to a common theoretical distribution.     

Arrogance can be a virtue: Overconfidence,information acquisition,and market efficiency

In behavioral finance, overconfidence has been established as a prevalent psychological bias, which can make markets less efficient by creating mispricing in the form of excess volatility and return predictability. In this paper, we develop a model in which overconfidence causes investors to overinvest in information acquisition when this information could improve market efficiency by driving prices closer to true values. We study the impact of overconfidence on mispricing and information acquisition, comparing their net effect on prices. We derive several novel implications. First, overconfidence generally improves market pricing provided the level of overconfidence is not too high. Pricing can also improve even when overconfidence is arbitrarily high, depending on the amount of private information acquired relative to publicly available information.     

Exchange-rate return predictability and the adaptive markets hypothesis: Evidence from major foreign exchange rates

This study examines return predictability of major foreign exchange rates by testing for martingale difference hypothesis (MDH) using daily and weekly nominal exchange rates from 1975 to 2009. We use three alternative tests for the MDH, which include the wild bootstrap automatic variance ratio test, generalized spectral test, and Dominguez–Lobato consistent tests. We evaluate time-varying return predictability by applying these tests with fixed-length moving sub-sample windows. While exchange rate returns are found to be unpredictable most of times, we do observe a number of episodes of statistically significant return predictability. They are mostly associated with the major events such as coordinated central bank interventions and financial crises. This finding suggests that return predictability of foreign exchange rates occurs from time to time depending on changing market conditions, consistent with the implications of the adaptive markets hypothesis.     

Market structure and the efficiency of European insurance companies: A stochastic frontier analysis

This paper is motivated by the progressive liberalisation of the European insurance market in recent years. It uses stochastic frontier analysis to estimate Flexible Fourier cost functions for European insurance companies. Separate frontiers are estimated for life, non-life and composite companies. We adopt a maximum likelihood approach to estimation in which the variance of both one-sided and two-sided error terms is modelled jointly with the frontiers. This approach allows us to simultaneously control for the impact of heteroskedasticity on the estimation of scale economies as well as estimating the effect of firm size and market structure on X-inefficiency. The study draws on Standard & Poor’s Eurothesys data set of financial reports for the period 1995 to 2001. This provides technical and non-technical accounts at year-end for life, non-life and composite insurance businesses in 14 major European countries. Our estimates suggest that over this period most European insurers were operating under conditions of decreasing costs (increasing returns to scale), and that company size and domestic market share were significant factors determining X-inefficiency. Larger firms, and those with high market shares, tend to have higher levels of cost inefficiency.     

The impact of banking regulations on banks' cost and profit efficiency: Cross-country evidence

This paper uses stochastic frontier analysis to provide international evidence on the impact of the regulatory and supervision framework on bank efficiency. Our dataset consists of 2853 observations from 615 publicly quoted commercial banks operating in 74 countries during the period 2000-2004. We investigate the impact of regulations related to the three pillars of Basel II (i.e. capital adequacy requirements, official supervisory power, and market discipline mechanisms), as well as restrictions on bank activities, on cost and profit efficiency of banks, while controlling for other country-specific characteristics. Our results suggest that banking regulations that enhance market discipline and empower the supervisory power of the authorities increase both cost and profit efficiency of banks. In contrast, stricter capital requirements improve cost efficiency but reduce profit efficiency, while restrictions on bank activities have the opposite effect, reducing cost efficiency but improving profit efficiency.     

Bank ownership,privatization, and performance: Evidence from a transition country

This paper combines the static effect of ownership and the dynamic effect of privatization on bank performance in China over 1995–2010, reporting a significantly higher performance by private intermediaries – joint stock commercial banks and city commercial banks – relative to state-owned commercial banks. However, publicly traded banks, subject to multiple monitoring and vetting in capital markets, perform better regardless of ownership status. The privatization of banks has improved performance with respect to revenue inflow and efficiency gains in the short- or long-run (initial public offerings). The positive long-run effect is more relevant and significant for banking institutions with minority foreign ownership. Moreover, this paper innovatively estimates interest income efficiency and non-interest income efficiency at the same time. The results suggest that Chinese banks are much more efficient in generating interest income than raising non-interest revenue, although the latter aspect has improved significantly during the sample period.     

A comprehensive analysis of the effects of risk measures on bank efficiency: Evidence from emerging Asian countries

This study investigates the role of risk in determining the cost efficiency of international banks in eight emerging Asian countries. Researchers of this paper consider three distinct risk aspects under a total of eight risk measures: credit risk, operational risk, and market risk. We apply a heteroscedastic stochastic frontier model to estimate bank cost efficiency in our analysis. Additionally, this study analyzes the marginal effects of all risk measures on the inefficiency effect in order to explore a more detailed relationship between risks and efficiency. The empirical results indicate that the risk measures represent significant effects on both the level and variability of bank efficiency. We also find that these effects vary across countries and over time.     

Overnight information and stochastic volatility: A study of European and US stock exchanges

This paper provides a comprehensive evaluation of the predictive ability of information accumulated during nontrading hours for a set of European and US stock indexes. We introduce a stochastic volatility model, which conditions on lagged overnight information, distinguishes between the nontrading periods of weeknights, weekends, holidays and long weekends, and allows for an asymmetric leverage effect on the impact of overnight news. We implement Bayesian methods for estimation and ranking of the empirical models, and find two key results: (i) there is substantial predictive ability in financial information accumulated during nontrading hours; and (ii) the performance of stochastic volatility models improves considerably by separating the asymmetric impact of positive and negative news made available over weeknights, weekends, holidays and long weekends.