Forecasting stock market volatility and information content of implied volatility index

This study investigates the incremental information content of implied volatility index relative to the GARCH family models in forecasting volatility of the three Asia-Pacific stock markets, namely India, Australia and Hong Kong. To examine the in-sample information content, the conditional variance equations of GARCH family models are augmented by incorporating implied volatility index as an explanatory variable. The return-based realized variance and the range-based realized variance constructed from 5-min data are used as proxy for latent volatility. To assess the out-of-sample forecast performance, we generate one-day-ahead rolling forecasts and employ the Mincer–Zarnowitz regression and encompassing regression. We find that the inclusion of implied volatility index in the conditional variance equation of GARCH family model reduces volatility persistence and improves model fitness. The significant and positive coefficient of implied volatility index in the augmented GARCH family models suggests that it contains relevant information in describing the volatility process. The study finds that volatility index is a biased forecast but possesses relevant information in explaining future realized volatility. The results of encompassing regression suggest that implied volatility index contains additional information relevant for forecasting stock market volatility beyond the information contained in the GARCH family model forecasts.     

Frequent acquirers and management compensation

We find positive contemporaneous, short-, and long-run effects of an increase in the acquisition rate on management compensation. A positive bidirectional causality exists between acquisition frequency and management compensation. A higher firm value is likely to associate with higher acquisition frequency. Acquisition rate has a positive impact on the market share. Acquirers with lower market share are more likely to become frequent acquirers. A causal order follows from lower market share to higher acquisition frequency to higher firm value to higher management compensation. The impact of acquisition frequency on management compensation is higher for value-enhancing acquirers relative to value-destroying acquirers.     

Knowledge Management in Supply Chains: The Role of Explicit and Tacit Knowledge

We theorize, building on the knowledge‐based view and the theoretical distinction between explicit and tacit knowledge, that knowledge management capability across the supply chain manifests itself in explicit and tacit knowledge, which in turn effectuates supply chain performance. The model is tested with survey data from 195 small‐ and medium‐sized enterprises reporting on their primary supply chain. The results indicate that the supply chain's knowledge management capability manifests itself in both explicit and tacit knowledge, with the latter being influenced more strongly. Moreover, it was found that while both explicit and tacit knowledge influence supply chain performance, the latter exerts a significantly greater impact than the former. Exploratory post hoc analyses add robustness to these findings and investigate mechanisms inherent to the transformation of tacit into explicit knowledge. Overall, this research contributes to academic theory development in logistics and supply chain management by the dichotomization of knowledge types and the demonstration of their differential magnitude of effects, and to managerial practice by providing important guidance for logistics managers structuring their knowledge management efforts across supply chains.     

Accommodating spatial correlation across choice alternatives in discrete choice models: an application to modeling residential location choice behavior

This paper presents a modeling methodology capable of accounting for spatial correlation across choice alternatives in discrete choice modeling applications. Many location choice (e.g., residential location, workplace location, destination location) modeling contexts involve choice sets where alternatives are spatially correlated with one another due to unobserved factors. In the presence of such spatial correlation, traditional discrete choice modeling methods that are often based on the assumption of independence among choice alternatives are not appropriate. In this paper, a Generalized Spatially Correlated Logit (GSCL) model that allows one to represent the degree of spatial correlation as a function of a multi-dimensional vector of attributes characterizing each pair of location choice alternatives is formulated and presented. The formulation of the GSCL model allows one to accommodate alternative correlation mechanisms rather than pre-imposing restrictive correlation assumptions on the location choice alternatives. The model is applied to the analysis of residential location choice behavior using a sample of households drawn from the 2000 San Francisco Bay Area Travel Survey (BATS) data set. Model estimation results obtained from the GSCL are compared against those obtained using the standard multinomial logit (MNL) model and the spatially correlated logit (SCL) model where only correlations across neighboring (or adjacent) alternatives are accommodated. Model findings suggest that there is significant spatial correlation across alternatives that do not share a common boundary, and that the GSCL offers the ability to more accurately capture spatial location choice behavior.     

The Effect of Probability Distribution Functions of Economic Life on Retirement Alternatives

Economic analysis, supported by computer hardware and software, can easily overwhelm a decision maker with data. However, this data can be organized in a readily understandable way using well-designed graphs. Some simple guidelines suggest substantial improvements over available examples from papers and textbooks. Although these graphs and sensitivity analyses are useful in many quantitative problems, the long-range focus of engineering economy and its concomitant uncertainty dramatically increase their value.     

The pricing of accruals for profit and loss firms

This paper investigates whether the accrual anomaly reported in prior studies exists across both profit and loss firms. We posit that the extent of accrual mispricing is less severe for loss firms than for profit firms because earnings for loss firms are less value relevant and, therefore, less subject to accrual mispricing. As expected, we find that the accrual overpricing anomaly is restricted to profit-making firms and, thus, is dampened by the inclusion of loss firms in the sample. Furthermore, we report that accrual overpricing for profit firms but not for loss firms is primarily attributable to the overpricing of positive accruals of profit firms compared with those of loss firms. Finally, we find that the phenomenon of accrual overpricing for profit but not for loss firms may persist into the new regulatory environment following the passage of the Sarbanes–Oxley Act of 2002.     

Investigating the different approaches to importance–performance analysis

Importance–performance analysis (IPA) is an analytic technique that generates a two-dimensional importance–performance grid, where the values of importance and performance across attributes are plotted against each other. This technique is used to assist service and other firms in prioritizing areas for service improvement when resources are limited. This study contributes to service theory by first performing a comprehensive literature review of four different and commonly used approaches to IPA. Survey data from the ports sector are then used to elucidate the value and the distinctiveness of these four different approaches, and it is also shown how the underlying theoretical assumptions led to somewhat varying, and contradictory interpretations. Subsequently, novel guidelines for integrating results from these four different approaches are proposed. The study advances service theory by detailing the integration of the different approaches to make sense of the importance and performance of diverse service attributes. The integrative approach developed in this paper also provides practitioners with clearer guidance for the application of IPA.