Firm characteristics and audit committees complying with ’best practice‘ membership guidelines

This study investigates demand and supply characteristics associated with firms that voluntarily established audit committees meeting ‘best practice’ membership guidelines. We focus on a set of best practice criteria rather than on the separate elements of the best practice criteria as in past studies. We conduct our tests using a sample of New Zealand listed companies that, relative to firms in other capital markets, are smaller and have more concentrated ownership. This setting differs from prior research because we expect the costs of voluntarily achieving best practice to be reasonably high. The results show that demand factors are not significantly related to the presence of an audit committee that conforms with best practice membership guidelines. However, supply factors (i.e. those firms with larger and more independent boards) are more likely to form audit committees that meet best practice. These results suggest that compliance costs will be greater for firms with smaller and less independent boards of directors if they are required to comply with best practice requirements.     

Implementing statistical criteria to select return forecasting models: what do we learn?

Statisticl model selection criteria provide an informed choiceof the model with best external (i.e., out-of-sample) validity.Therefore they guard against overfitting ('data snooping').We implement several model selection criteria in order to verifyrecent evidence of predictability in excess stock returns andto determine which variables are valuable predictors. We confirmthe presence of in-sample predictability in an internationalstock market dataset, but discover that even the best predictionmodels have no out-of-sample forecasting power. The failureto detect out-of-sample predictability is not due to lack ofpower.     

Systemic risk measures: The simpler the better?

This paper estimates and compares two groups of high-frequency market-based systemic risk measures using European and US interbank rates, stock prices and credit derivatives data from 2004 to 2009. Measures belonging to the macro group gauge the overall tension in the financial sector and micro group measures rely on individual institution information to extract joint distress. We rank the measures using three criteria: (i) Granger causality tests, (ii) Gonzalo and Granger metric, and (iii) correlation with an index of systemic events and policy actions. We find that the best systemic measure in the macro group is the first principal component of a portfolio of Credit Default Swap (CDS) spreads whereas the best measure in the micro group is the multivariate densities computed from CDS spreads. These results suggest that the measures based on CDSs outperform measures based on interbank rates or stock market prices.     

Models of the yield curve and the curvature of the implied forward rate function

We examine several alternative models of the UK gilt yield curve using daily data for the period 12 July 1996-10 February 2010. We select the best models according to two criteria: low out of sample errors in pricing bonds and low curvature of the implied forward rate curve function. We suggest additions to some of the models that significantly improve their performance. Some of the new models out perform those typically used by the central banks. In particular this paper suggests that the model used by the Canadian Central Bank which both outperforms other models and is particularly easy to estimate, is well suited to the UK gilt market.     

Buyer seller relationships in the UK insurance market: Is this the key competitive advantage?

In services marketing much of the recent literature recommends the use of relationship marketing frameworks rather than the extended marketing mix which adds people, process and physical evidence to the traditional four Ps of product, price, promotion and place. In the UK permanent health insurance sector some suppliers sell through intermediaries, making this an ideal environment for testing the value of relationship marketing. Using the Industrial Marketing and Purchasing (IMP) group framework, interviews were conducted with 100 intermediaries. Respondents were asked to rate their top two suppliers against five relationship marketing variables: commercial skills, technical skills, commitment, adaptability and conflict management.The data showed the top supplier was rated more highly than the second supplier in three of the criteria:— commercial skills— technical skills— adaptability.Two of the criteria, commercial skills and technical skills, showed significant differences. The results of this research provide support for the importance of relationship marketing within this sector of the insurance market. For suppliers in the insurance industry, developing competencies in adaptability and conflict management may be the best method both to differentiate the firm and to develop competitive advantage.     

Un enfoque multicriterio para el diseño de una red para el transporte de embarques internacionales

One of the important challenges for manufacturers and distributors of autoparts is the coordination of multiple sourcing areas where their international suppliers are located. The objective of this research is the design of a service transportation network that takes into account the time shipments are held at customs and transshipment terminals, as well as the possible delays due to the use of different transportation modes. To assure the best performance of the whole transportation network, a bi-criteria optimization model was formulated, the two criteria considered were cost and time. The solution to the model was the structure of the transportation network to be used by a manufacturer of auto parts located in the Toluca industrial zone; this firm imports auto parts produced by suppliers located in the United States (E.E.U.U.) and commercializes them among multiple automakers. The structure of the optimization problem was analyzed to obtain a convenient separable arrangement and then the problem was solved by using Lagrangian relaxation. A set of possible efficient solutions for the structure of the transportation network was generated by using the weighting method and the ε-constraint method; the resulting solutions represent the set of best alternatives from which the logistics managers may choose the service network that best attends the needs and logistics performance goals of the firm.     

Triple-entry Bookkeeping: A Critique

This paper reviews Ijiri's proposals for triple-entry bookkeeping systems. The first part summarises the essential elements of Ijiri's proposals. Ijiri examines two different versions of triple-entry bookkeeping—temporal and differential; however, Ijiri himself concludes that temporal triple-entry bookkeeping is unsatisfactory and so this paper concentrates almost exclusively on differential triple-entry bookkeeping. Ijiri's theoretical approach is then examined, with the conclusion that it is methodologically unsound. There are two problems here. Ijiri does not define the objectives of his proposed system ex ante, and his integrity criterion is an arbitrary and imperfect one. Differential triple-entry bookkeeping is then analysed in detail and it is concluded that it may be imperfect in terms of Ijiri's own logical criteria. Potential usefulness is also examined, and it is concluded that this is at best problematic.     

Robust and Efficient Estimation of the Tail Index of a Single-Parameter Pareto Distribution

Abstract

Estimation of the tail index parameter of a single-parameter Pareto model has wide application in actuarial and other sciences. Here we examine various estimators from the standpoint of two competing criteria: efficiency and robustness against upper outliers. With the maximum likelihood estimator (MLE) being efficient but nonrobust, we desire alternative estimators that retain a relatively high degree of efficiency while also being adequately robust. A new generalized median type estimator is introduced and compared with the MLE and several well-established estimators associated with the methods of moments, trimming, least squares, quantiles, and percentile matching. The method of moments and least squares estimators are found to be relatively deficient with respect to both criteria and should become disfavored, while the trimmed mean and generalized median estimators tend to dominate the other competitors. The generalized median type performs best overall. These findings provide a basis for revision and updating of prevailing viewpoints. Other topics discussed are applications to robust estimation of upper quantiles, tail probabilities, and actuarial quantities, such as stop-loss and excess-of-loss reinsurance premiums that arise concerning solvency of portfolios. Robust parametric methods are compared with empirical nonparametric methods, which are typically nonrobust.     

Inconsistency in Welfare Inferences from Distance Variables in Hedonic Regressions

In hedonic analysis, a common approach for eliciting information regarding the welfare significance of some landmark or (dis)amenity is to control for its distance from each observation. Unfortunately, the effects of distances to amenities on housing prices are generally not consistent indicators of the true price impact of that amenity. Instead these variables serve as proxies for the relative position of every observation in space. Whenever a household considers more than two landmarks in a housing purchase, distance variable parameter estimates are simply the best linear fitted weights for that multiple criteria location decision. Simulations illustrate extreme sensitivity in parameter estimates to the researcher’s choice of landmarks. One strategy models the location of each observation directly instead of its distances to amenities. Using the quadratic controls of longitude and latitude controls for location effects on price to assure unbiased estimates of non-distance variable regressors.     

Analysis of the complexity of writing used in accounting textbooks over the past 100 years

The Accounting Education Change Commission (AECC) and the large international accounting firms have all emphasized that accountants must be able to work with unstructured problems to be successful in today's business environment. Measures of this ability are essential if accounting educators are to assist students in improving their abilities to work with unstructured problems. However, there appears to be no measure that has been widely accepted as being the ‘best’ measure. This study considers whether two linguistic performance measures might be usable by accounting educators for this purpose. We use data obtained from a student assessment centre to consider two measures of linguistic performance, idea density and grammatical complexity. We incorporate five criteria in deciding whether these measures could be usable: (1) whether the measures are related to students' performance when solving unstructured problems; (2) whether the measures distinguish between the ability to work with unstructured compared to structured problems; (3) ease of obtaining necessary information from students; (4) ease of scoring, and (5) robustness of the findings after considering other variables that may have an effect. Our results indicate that subjects' linguistic performance as measured by idea density meets these five criteria. However, grammatical complexity is not related to performance for either type of problem. These results were found even after controlling for the effects of other variables such as grade point average (GPA), experience, and personality variables. Because the measures can be obtained from virtually any written work produced by students, the information to be scored is relatively easy to obtain. Scoring is also relatively straightforward.     

An appraisal framework for evaluating financing approaches for public infrastructure

Innovative financing solutions for public infrastructure megaprojects require new approaches to assess the various financing portfolios being proposed. This paper discusses a range of international financing models and presents a new multi- criteria appraisal framework for assessing alternative ways of raising capital. The proposed framework combines elements of a multi-criteria analysis and cost benefit analysis, and incorporates both monetary and intangible impact measures to facilitate the selection of a financing approach that is in society’s best interest.     

CREDIT SCORING,STATISTICAL TECHNIQUES AND EVALUATION CRITERIA: A REVIEW OF THE LITERATURE

Credit scoring has been regarded as a core appraisal tool of different institutions during the last few decades and has been widely investigated in different areas, such as finance and accounting. Different scoring techniques are being used in areas of classification and prediction, where statistical techniques have conventionally been used. Both sophisticated and traditional techniques, as well as performance evaluation criteria, are investigated in the literature. The principal aim of this paper, in general, is to carry out a comprehensive review of 214 articles/books/theses that involve credit scoring applications in various areas but in particular primarily in finance and banking. This paper also aims to investigate how credit scoring has developed in importance and to identify the key determinants in the construction of a scoring model, by means of a widespread review of different statistical techniques and performance evaluation criteria. Our review of literature revealed that there is no overall best statistical technique used in building scoring models and the best technique for all circumstances does not yet exist. Also, the applications of the scoring methodologies have been widely extended to include different areas, and this subsequently can help decision makers, particularly in banking, to predict their clients' behaviour. Finally, this paper also suggests a number of directions for future research. Copyright © 2011 John Wiley & Sons, Ltd.     

Downside risk and portfolio diversification in the euro-zone equity markets with special consideration of the crisis period

This study examines the Value-at-Risk for ten euro-zone equity markets individually and also divided into two groups: PIIGS (Portugal, Italy, Ireland, Greece and Spain) and the Core (Austria, Finland, France, Germany and the Netherlands), employing four VaR estimation and evaluation methods considered over the full period and the pre- and post-global crisis subperiods 1 and 2. The backtesting results are also evaluated according to the Basel capital requirements. The results demonstrate that the CEVT methods meet all the statistical criteria the best for most individual equity indices over the full period, but these results over the two subperiods for those two methods are mixed, compared to those the DPOT methods. Moreover, the two optimal group portfolios of the PIIGS and the Core as well as the grand portfolio that combines the ten indices do not show much diversification benefits. The PIIGS portfolio selects Spain's IBEX only, while that of the Core opts for Austria's ATX only in the full period and subperiod 1. However, Germany's DAX overwhelmingly dominates both the Core and the Grand portfolios in subperiod 2.     

Influences of family ownership on dividend policy under mandatory dividend rules

The LIBOR manipulation scandal of 2008 spurred extensive policy debates regarding the importance of market-based reference rates. The alternative reference rates committee (ARRC) eventually identified the secured overnight financing rate (SOFR) to be a suitable replacement to LIBOR. In this study, we question the underlying process behind the choice of SOFR as a replacement for LIBOR. Both academic literature and regulatory bodies fail to identify a consistent definition and criteria of a good reference rate. We fill in this gap in the literature by providing an empirically testable ‘checklist’ to evaluate any potential money market rate to gauge its suitability as a reference rate. We also carry out an empirical evaluation of various money market rates against our criteria and identify the 1-month AA non-financial commercial paper rate as the best available replacement for LIBOR.

     

A comparison of models of long-term inflationary expectations

This paper compares several models of long-term inflationary expectations, including time series models, models drawn from interest rate relationships, and a structural model developed from a portfolio balance framework. Their within-sample performance over 1961–1974 and out-of-sample performance over periods covering 1975–1982 are compared. Evaluation criteria include accuracy of forecasts and ability to capture changes in the trend of long-term inflation.The structural model is judged best. Its forecasts are generally the most accurate and it performs well in periods of rising and falling inflation, an attribute not present in other models.     

On the Efficiency of Bankruptcy Law: Empirical Evidence in Spain

The current economic crisis is showing one of the main problems that many companies in financial distress have to face, namely, the impact of bankruptcy law in relation to companies and firms. This paper aims to analyze the bankruptcy law ex‐ante efficiency when companies are in financial distress. To test it out, two research questions are submitted: (i) Is solvency, the criterion used in the Spanish law, the best one to assess the relative significance of the main indicators, which determine bankrupt firms? (ii) Is the Spanish bankruptcy law efficient according to solvency or are there better criteria? To answer them, a logistic regression model is conducted. The sample embraces 1,387 firms in Spain, the data being obtained from 12 Commercial Justice Courts complemented with financial information. The main conclusion is that the solvency criterion is adequate to classify bankrupt companies although currently Spanish Bankruptcy law is not as efficient as it could be. Additionally, the relevant companies' indicators, which explain the financial distress procedure, are presented. Copyright © 2013 INSOL International and John Wiley & Sons, Ltd     

Truncation and acceleration of the Tian tree for the pricing of American put options

We present a new method for truncating binomial trees based on using a tolerance to control truncation errors and apply it to the Tian tree together with acceleration techniques of smoothing and Richardson extrapolation. For both the current (based on standard deviations) and the new (based on tolerance) truncation methods, we test different truncation criteria, levels and replacement values to obtain the best combination for each required level of accuracy. We also provide numerical results demonstrating that the new method can be 50% faster than previously presented methods when pricing American put options in the Black–Scholes model.     

Estimating the Correlation Structure of International Share Prices

Recently, the case for international portfolio diversification has been convincingly argued in the framework of mean-variance portfolio analysis by a number of researchers. However, virtually no empirical documentation exists concerning the best method for estimating the correlation structure of international share prices. In this paper, 12 models for estimating the international correlation matrix are presented and empirically tested relative to full historical extrapolation. The major evaluation criteria are the mean squared error and stochastic dominance based on the frequency distribution of the squared forecast errors. The results indicate that the National Mean Model strictly dominates all the others in terms of forecasting accuracy.     

Forecasting Stock Index Futures Price Volatility: Linear vs. Nonlinear Models

The study examines the relative ability of various models to forecast daily stock index futures volatility. The forecasting models that are employed range from naïve models to the relatively complex ARCH-class models. It is found that among linear models of stock index futures volatility, the autoregressive model ranks first using the RMSE and MAPE criteria. We also examine three nonlinear models. These models are GARCH-M, EGARCH, and ESTAR. We find that nonlinear GARCH models dominate linear models utilizing the RMSE and the MAPE error statistics and EGARCH appears to be the best model for forecasting stock index futures price volatility.     

Momentum strategies based on reward–risk stock selection criteria

In this paper, we analyze momentum strategies that are based on reward–risk stock selection criteria in contrast to ordinary momentum strategies based on a cumulative return criterion. Reward–risk stock selection criteria include the standard Sharpe ratio with variance as a risk measure, and alternative reward–risk ratios with the expected shortfall as a risk measure. We investigate momentum strategies using 517 stocks in the S&P 500 universe in the period 1996–2003. Although the cumulative return criterion provides the highest average monthly momentum profits of 1.3% compared to the monthly profit of 0.86% for the best alternative criterion, the alternative ratios provide better risk-adjusted returns measured on an independent risk-adjusted performance measure. We also provide evidence on unique distributional properties of extreme momentum portfolios analyzed within the framework of general non-normal stable Paretian distributions. Specifically, for every stock selection criterion, loser portfolios have the lowest tail index and tail index of winner portfolios is lower than that of middle deciles. The lower tail index is associated with a lower mean strategy. The lowest tail index is obtained for the cumulative return strategy. Given our data-set, these findings indicate that the cumulative return strategy obtains higher profits with the acceptance of higher tail risk, while strategies based on reward–risk criteria obtain better risk-adjusted performance with the acceptance of the lower tail risk.