Model selection in univariate time series forecasting using discriminant analysis

When a large number of time series are to be forecast on a regular basis, as in large scale inventory management or production control, the appropriate choice of a forecast model is important as it has the potential for large cost savings through improved accuracy. A possible solution to this problem is to select one best forecast model for all the series in the dataset. Alternatively one may develop a rule that will select the best model for each series. Fildes (1989) calls the former an aggregate selection rule and the latter an individual selection rule. In this paper we develop an individual selection rule using discriminant analysis and compare its performance to aggregate selection for the quarterly series of the M-Competition data. A number of forecast accuracy measures are used for the evaluation and confidence intervals for them are constructed using bootstrapping. The results indicate that the individual selection rule based on discriminant scores is more accurate, and sometimes significantly so, than any aggregate selection method.     

Board structure,mergers, and shareholder wealth: A study of the mutual fund industry

We study mutual fund mergers between 1999 and 2001 to understand the role and effectiveness of fund boards. Some fund mergers—typically across-family mergers—benefit target shareholders but are costly to target fund directors. Such mergers are more likely when funds underperform and their boards have a larger percentage of independent trustees, suggesting that more-independent boards tolerate less underperformance before initiating across-family mergers. This effect is most pronounced when all of the fund's directors are independent, not the 75% level of independence required by the SEC. Higher-paid target fund boards are less likely to approve across-family mergers that cause substantial reductions in their compensation.     

Portfolio manager ownership and fund performance

This paper documents the range of portfolio manager ownership in the funds they manage and examines whether higher ownership is associated with improved future performance. Almost half of all managers have ownership stakes in their funds, though the absolute investment is modest. Future risk-adjusted performance is positively related to managerial ownership, with performance improving by about 3 basis points for each basis point of managerial ownership. These findings persist after controlling for various measures of fund board effectiveness. Fund manager ownership is higher in funds with better past performance, lower front-end loads, smaller size, longer managerial tenure, and funds affiliated with smaller families. It is also higher in funds with higher board member compensation and in equity funds relative to bond funds. Future performance is positively related to the component of ownership that can be predicted by other variables, as well as the unpredictable component. Our findings support the notion that managerial ownership has desirable incentive alignment attributes for mutual fund investors and indicate that the disclosure of this information is useful in making portfolio allocation decisions.     

Building Better Theory by Bridging the Quantitative–Qualitative Divide*

abstract Qualitative methods for data collection and analysis are not mystical, but they are powerful, particularly when used to build new or refine existing theories. This article provides an introduction to qualitative methods and an overview of tactics for ensuring rigor in qualitative research useful for the novice researcher, as well as more experienced researchers interested in expanding their methodological repertoire or seeking guidance on how to evaluate qualitative research. We focus our discussion on the qualitative analytical technique of grounded theory building, and suggest that organizational research has much to gain by coupling of use of qualitative and quantitative research methods.     

Comparison of test vs. control treatments using distance optimality criterion

We consider the problem of comparison of one test treatment (τ₀) with a set of v control treatments (τ₁, τ₂, …, τ_v) using distance optimality [DS-optimality] criterion introduced by Sinha (1970) in some treatment-connected design settings. It turns out that the nature of DS-optimal designs is quite similar to that for the usual A−, D− and E− optimality criteria. However, the optimality problem is quite complicated in most situations. First we deal with the CRD model and derive DS-optimal allocations for a given set of treatments. The results are almost identical to the A-optimal allocations for such problems. Then we consider a block design set-up and examine the nature of DS-optimal designs. In the process, we introduce the method of weighted coverage probability and maximize the resulting expression to obtain an optimal design. Received: December 1999     

Researching the Drivers of Socially Responsible Purchasing: A Cross-National Study of Supplier Diversity Initiatives

What drives organisations to engage in socially responsible purchasing initiatives? To investigate this important question, this article uses a case-study approach to examine the context within which supplier diversity programmes have emerged in both the U.S. and U.K. The analysis identifies legislative and policy developments, economic imperatives, stakeholder pressures and ethical influences as forces shaping organisational responses. It reveals important contextual differences between U.K. and U.S. experience and offers an empirical and theoretical explanation of corporate behaviour.     

Channels of interaction and past collaborative experience as imperatives in academia–industry collaboration

The present study deals with the engagement of academics with the industry using different channels for the transfer of knowledge and technology. The study provides empirical evidence substantiating the effect of the frequency of use of the different channels of interaction in explaining the relationship between past collaborative experience of the academic and the outcomes of academia–industry collaboration. The results indicate that past collaborative experience develops strong insights into industrial problems, opens up avenues for research projects, leads to industrial funding and builds research networks. The prospects of commercialisation of research of the academic are also rooted in past collaborative experience. The results also reveal that the frequency of use of the traditional and bi-directional channels partially mediate the relationship between the collaborative experience and the outcomes of collaboration, validating that higher collaborative experience leads to increased frequency of use of channels that results in improved outcomes of academia–industry collaboration.     

The Impact of Single Stock Futures on Market Efficiency and Volatility: A Dynamic CAPM Approach

The concerns regarding regulations of futures markets and their destabilizing ability are unresolved in both developed and developing markets. Following stringent regulations of single stock futures (SSFs) for resumption episode after financial crises, this study addresses this concern and investigates the destabilizing impact of SSFs on the underlying stocks in an emerging economy using data of companies listed in the Karachi Stock Exchange between 1999 and 2008. Specifically, the study explores whether SSFs have caused a simultaneous increase in the volatility and operational efficiency of their underlying spot market counterparts. The results reported in the study show that the introduction of SSFs has no significant impact on market efficiency and volatility of SSFs underlying stocks and non-SSFs stocks. The results affirm that SSFs have, at least, no destabilizing impact on the underlying stocks.