Performance of soccer on the stock market: Evidence from Turkey

This paper assesses the effect of soccer success on stock market returns for three major Turkish teams (Beşiktaş, Fenerbahçe and Galatasaray) after certain characteristics of the stock market are controlled for. The empirical evidence presented here suggests that Beşiktaş's win against foreign rivals in the Winner's Cup increases stock market returns. The same effect is not present for the other two big teams (Fenerbahçe and Galatasaray). The day of the week effect on the stock market and the relationship between risk and return are also presented.     

Practical Advice on How to Impute Continuous Data When the Ultimate Interest Centers on Dichotomized Outcomes Through Pre-Specified Thresholds

Multiple imputation under the multivariate normality assumption has often been regarded as a viable model-based approach in dealing with incomplete continuous data in the last two decades. A situation where the measurements are taken on a continuous scale with an ultimate interest in dichotomized versions through discipline-specific thresholds is not uncommon in applied research, especially in medical and social sciences. In practice, researchers generally tend to impute missing values for continuous outcomes under a Gaussian imputation model, and then dichotomize them via commonly-accepted cut-off points. An alternative strategy is creating multiply imputed data sets after dichotomization under a log-linear imputation model that uses a saturated multinomial structure. In this work, the performances of the two imputation methods were examined on a fairly wide range of simulated incomplete data sets that exhibit varying distributional characteristics such as skewness and multimodality. Behavior of efficiency and accuracy measures was explored to determine the extent to which the procedures work properly. The conclusion drawn is that dichotomization before carrying out a log-linear imputation should be the preferred approach except for a few special cases. I recommend that researchers use the atypical second strategy whenever the interest centers on binary quantities that are obtained through underlying continuous measurements. A possible explanation is that erratic/idiosyncratic aspects that are not accommodated by a Gaussian model are probably transformed into better-behaving discrete trends in this particular missing-data setting. This premise outweighs the assertion that continuous variables inherently carry more information, leading to a counter-intuitive, but potentially useful result for practitioners.     

BinNor: An R Package for Concurrent Generation of Binary and Normal Data

This article describes the package BinNor, which is designed for generating multiple binary and normal variables simultaneously given marginal characteristics and association structure via combining well-established results from the random number generation literature, based on the methodology proposed by Demirtas and Doganay.     

Soccer, stock returns and fanaticism: Evidence from Turkey

This paper assesses the effect of three major soccer teams’ wins on the returns of the Istanbul Stock Exchange (ISE). We argue that the effect of soccer wins on ISE returns increases with the fanaticism of the teams’ supporters.     

A Robust Control Chart for Monitoring the Mean of an Autocorrelated Process

Residual control charts are frequently used for monitoring autocorrelated processes. In the design of a residual control chart, values of the true process parameters are often estimated from a reference sample of in-control observations by using least squares (LS) estimators. We propose a robust control chart for autocorrelated data by using Modified Maximum Likelihood (MML) estimators in constructing a residual control chart. Average run length (ARL) is simulated for the proposed chart when the underlying process is AR(1). The results show the superiority of the new chart under several situations. Moreover, the chart is robust to plausible deviations from assumed distribution of errors.     

MANUFACTURING QUALITY,RELIABILITY AND PREVENTIVE MAINTENANCE

We consider an important topic from the traditional quality literature-the impact of conformance quality of a manufactured product on the preventive maintenance costs to downstream users of this product. Folk wisdom supports the notion that higher conformance quality translates into lower maintenance costs (as well as other components of life-cycle costs) for these users. We examine this proposition in some detail on the basis of a failure-time model that relates conformance quality to reliability. We consider both repairable and nonrepairable items that are maintained by a block-replacement or a minimal-repair strategy. In addition to maintenance cycles and costs, we discuss the value of information to the user as to the actual production quality, and the value of inspection.     

Online routing and searching on graphs with blocked edges

Journal of Combinatorial Optimization - We study routing and searching decisions of a search-and-detection (SDT) team on a road network under online uncertainty setting. Given an undirected...