Greg N. Gregoriou

An input-oriented super-efficiency measure in stochastic data envelopment analysis: Evaluating chief executive officers of US public banks and thrifts

We develop an input-oriented super-efficiency measure in stochastic data envelopment analysis. A deterministic equivalent of the stochastic super-efficiency model is given. It is shown that this deterministic model can be converted to a quadratic program. Sensitivity analysis of the proposed super-efficiency model is discussed. The SNL Executive Compensation database is used to illustrate the methods developed in this article.

Assessing The Relative Efficiency Of Credit Unionbranches Using Data Envelopment Analysis

Abstract Dala envelopment analysis (DEA) is a linear programming-based technique developed to evaluate the relative efficiency of non-profit and public sector decision-making units that use multiple inputs to produce multiple outputs. Technically, as pointed out by Joro, Korhonen and Wallemius( 1998), DEA and Multiple Objective Linear Programming (MOLP) aim at suggesting improvements for inefficient units based on the identification of efficient units in a certain space. In this study, DEA is used as a managerial audit tool to identify and measure inefficiencies among a set of 73 independent decision-making units within one federation of the “Caisses Populaires Desjardins” in Québec. The DEA results were compared with the federation’s traditional accounting ratio measures. Management found that the DEA results confirmed most of their intuition on which units were unprofitable, and also pinpointed units that made a profit but were operationally inefficient. Overall, they agree with our results and on the benefits of using DEA to complement their accounting ratio analysis for improving the efficiency of some of their “caisses”.

Does CTA Size Erode Performance

The author examines the returns of commodity trading advisers (CTAs) from August 1995 to July 2005 to determine whether the size of a CTA affects its performance. Size is often quoted by academics as a restraint to performance improvement, in particular when a considerable amount of capital is constantly injected into a fund. Do CTAs with such inflows of capital neglect their daily trading behavior? The findings suggest that the size of a CTA may have an impact on its performance. Furthermore, the author believes that investors who want to incorporate CTAs into their portfolios should concentrate on performance measurements such as risk-adjusted return rather than fund size.

Is Greed Still Good? What Have HedgeFund Managers and Investors Learnedfrom the 2008 Crisis?

Have investors and hedge fund managers learned anything from their recent mistakes? One can doubt it. While each financial crisis has its unique features, common traits and warning signals surface repeatedly. In this article, the authors have chosen to discuss six of them, namely (a) the belief that the current situation bears little similarity to past disasters; (b) the misalignment of interests between principals and agents; (c) the mismatch of liquidity between assets and liabilities; (d) the increased use of leverage when returns are disappointing; (e) the increased complexity of the strategies and instruments traded; and (f) the lack of reliability of external due diligence providers. They conclude that, unfortunately, many of these signs seem to be back again in the world of hedge funds.

Nonlinear Financial Econometrics: Forecasting Models, Computational and Bayesian Models

1. The Yield of Constant Maturity 10-Year US Treasury Notes: Stumbling Toward an Accurate Forecast Rafael Weißbach, Wladyslaw Poniatowski, and Guido Zimmermann This chapter assesses three simple transformation methods to achieve the best fit for forecasting constant maturity yields of 10-year US Treasury notes (T-notes) with the self-exciting threshold autoregressive (SETAR) model. It shows that the Box–Cox transformation proves to be superior to the difference filter. However, dividing the sample of T-note yields, dating from 1962 to 2009 into a training sample and a test sample reveals the forecast to be biased. A new bias-corrected version of the SETAR model is developed, and forecasts for March 2008 to February 2009 are delivered. In addition to point estimates, forecast limits are also given. 2. Estimating the Arbitrage Pricing Theory Factor Sensitivities Using Quantile Regression Zeno Adams, Roland Füss, Philipp Grüber, Ulrich Hommel, and Holger Wohlenberg In this chapter, we apply the quantile regression technique within an arbitrage pricing theory (APT) framework to show that risk premiums may not only be negative but may also have different signs depending on the quantile of the return distribution, that is, they depend on the asset return relative to the return of the overall market. When bearing additional risk to a common factor, investors should therefore not only concentrate on the shifting of their risk exposure but also draw their attention to the selection of assets that (1) yield a positive risk premium on average and (2) still generate a positive risk premium when underperforming the market to ensure partial compensation for investors. In addition, we can also show that by replacing OLS with the quantile regression approach leads to a much better model fit of the APT for the lower-end quantiles. The usage of this estimation technique is therefore particularly advisable for periods of high volatility such as the 2007/2008 financial crisis.

Financial Econometrics Modeling: Market Microstructure, Factor Models and Financial Risk Measures

PART I: MARKET MICROSTRUCTURE DYNAMICS Fourier Method for Covariance Estimation and Dynamic Asset Allocation Under Microstructure Effects M.E.Mancino& S.Sanfelici Market Liquidity, Stock Characteristics and Order Cancellations: The Case of Fleeting Orders B.Chakrabarty& K.Tyurin Market Microstructure of Foreign Exchange Markets Y.Hashimoto& T.Ito The Intraday Analysis of Volatility, Volume and Spreads: A Review with Applications to Futures Markets D.Fantazzini PART II: PRICING MODELS AND FINANCIAL RISK MEASURES The Consumption-Based Capital Asset Pricing Model (CCAPM), habit-based consumption, and the Equity Premium in an Australian Context D.E.Allen& L. Demello Testing the Lower Partial Moment Asset Pricing Models in Emerging Markets J.Iqbal, R.D.Brooks& D.U.A.Galagedera Asset Pricing, the Fama-French Factor Model and the implications of Quantile Regression Analysis D.E.Allen, A.Kumar Singh & R.Powell On the Effects of Liquidity and Trading Activity to Forecast Downside Risk L. Sanchis-Marco& A.Rubia Econometric Methods for Portfolio Selection with Time Varying Value-At-Risk E.W.Rengifo& J.V.K.Rombouts A Risk and Forecasting Analysis of West Texas Intermediate Prices D.E.Allen & A.K.Singh