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.     

THE JOINT ARRIVAL AND DEPARTURE PROCESS FOR THE M/M/l QUEUE

We consider the M/M/1-queue and derive an explicit expression for the joint distribution of the number of arrivals and the number of departures in [0, t), given the number of customers initially present. The derivation is almost purely combinatorial, it avoids the use of generating functions, and immediately yields a simple probabilistic interpretation of the result.     

A critical appraisal of the reporting quality of published randomized controlled trials in the fall injuries

To evaluate the quality of reporting in published randomized controlled trials (RTCs) in the field of fall injuries. The 188 RTCs published between 2001 and 2011, indexed in EMBASE and Medline databases were extracted through searching by appropriate keywords and EMTree classification terms. The evaluation trustworthiness was assured through parallel evaluations of two experts in epidemiology and biostatistics. About 40%–75% of papers had problems in reporting random allocation method, allocation concealment, random allocation implementation, blinding and similarity among groups, intention to treat and balancing benefits and harms. Moreover, at least 10% of papers inappropriately/not reported the design, protocol violations, sample size justification, subgroup/adjusted analyses, presenting flow diagram, drop outs, recruitment time, baseline data, suitable effect size on outcome, ancillary analyses, limitations and generalizability. Considering the shortcomings found and due to the importance of the RCTs for fall injury prevention programmes, their reporting quality should be improved.     

Evolution of Smartn Players

To model the evolution of strategic intelligence, player types are drawn from a hierarchy of "smartness" analogous to the levels of iterated rationalizability. Nonrationalizable strategies die out, but when higher levels of smartness incur maintenance costs, being right is always as good as being smart. Moreover, if a manifest way to play emerges, then dumb players never die out, while smarter players with positive maintenance costs vanish. These results call to question the standard game-theoretic assumption of super-intelligent players. Journal of Economic Literature Classification Numbers: B40, C70, C72, C73.     

Sources of variation in firm profitability and growth

This article reports an analysis of the sources of variation in profitability and growth for manufacturing firms located in eleven European countries. A variance decomposition analysis determines the importance of the country, industry, corporate group and firm effects on profitability and growth. The analysis reveals evidence of differences between industries in the comparative advantage offered by different countries, reflecting a tendency for specialization and geographic concentration. However, as in several previous studies, the firm-level effects are the most important class of effect in explaining the variation in performance.     

Categorizing risks in seven large projects—Which risks do the projects focus on?

In a hierarchy of project objectives, strategic objectives will often be principally different from the operational ones. Operational objectives concern the project outputs/results, and strategic objectives concern the project goal and purpose. In this study, risks are categorized as risks to operational, long‐term, or short‐term strategic objectives, and, by studying a dataset of some 1,450 risk elements that make up the risk registers of seven large projects, we examine how operational and strategic risks are distributed in the projects. The study strongly indicates that risks to a project's strategic objectives rarely occur in the project's risk registers, though project success and failure stories indicate their importance.     

Empirical Bayes analysis of log-linear models for a generalized finite stationary Markov chain

This article presents the empirical Bayes method for estimation of the transition probabilities of a generalized finite stationary Markov chain whose ith state is a multi-way contingency table. We use a log-linear model to describe the relationship between factors in each state. The prior knowledge about the main effects and interactions will be described by a conjugate prior. Following the Bayesian paradigm, the Bayes and empirical Bayes estimators relative to various loss functions are obtained. These procedures are illustrated by a real example. Finally, asymptotic normality of the empirical Bayes estimators are established.