There has been increasing attention all over the world on corporate governance issues after experiencing some financial crises and corporation scandals. It is assumed that the investors search for emerging economies to diversify their investment portfolios and maximize their returns is considering corporate governance applications. Investors are also concerned about governance factors to minimize their risks. In this study, we examine the impact of corporate governance variables on firms" financial performance in Turkey. The relationship between ownership structures, board structures and financial performances are tested. Influence of corporate governance variables, board size, share of independent board members, foreign investors, leverage ratio on firms" financial performance "return on assets" are utilized on firms traded in Turkey"s stock exchange BIST 100. This research concludes that corporate governance variables influence firms" performances. Shares of independent board members and leverage have negative influences while foreign ownership has a positive influence on firms" financial performances.

Traffic accidents, which continue to increase from year to year in Turkey and in the world, have become a huge problem that can result in serious traumas, injuries, and deaths, as well as their material and moral consequences. Many studies have been carried out in the world and in Turkey to reduce the number of traffic accidents, but these studies have not been very effective in reducing accidents. In this study, 3105 fatal or injured traffic accidents between 2010–2017 in Sarıyer district of Istanbul, Turkey’s largest city in terms of population, were discussed. We analyzed the statistical information on the subject in detail within the framework of geographic information systems. It has been tried to determine the sections where traffic accidents are concentrated in this region with studies based on spatial methods. Thematic accident map was created according to the accident types. In this context, the advantages and disadvantages of these methods were compared using Point Density, Kernel Density, Getis Ord Gi*, and Anselin Local Moran’s I (LISA) Spatial Autocorrelation. In addition, in order to observe the change in accidents, thematic accident and Kernel Density maps were created separately according to accident occurrence types in the beginning and last year. From this point of view, the changes that occurred in the accidents were interpreted. The current study determined that the most accidents were on some streets and these streets divided into regions in a plan. The cases were examined with statistical analyses according to accident types and using the Kernel Density method. In addition, it has been observed that Kernel Density method gives better visual results than other spatial methods. In this study, spatial analysis and statistical analysis methods were used to evaluate traffic accidents more realistically. The day of the week effect and month of the year effect on traffic accidents was investigated for the first time. In addition, it is proposed to bring a new approach to the prevention of traffic accidents by using hotspot, accident type, and day of the week effect.

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This study was conducted to investigate the market anomalies in the Borsa Istanbul Index (BIST). The scope of this study is to examine the Monday effects in BIST that are stock index of Turkey with an data set that contains daily stock prices between 02.01.2010 and 22.10.2014. The stock returns of the 289 companies were calculated according to the daily historical stock prices of companies. These returns were classified based on the sectors, and statistically analysed if the days of the week had any effects on Monday when the daily stock returns of Monday were fixed constant. The findings showed that the stock returns on Monday were affected by the other days. These effects were mostly negative, and varied according to the stocks and sectors. Thursday and Friday had the highest effect, whereas Tuesday had the least effect on the stocks. The results show that the stock market in Turkey has market anomaly, and BIST is not an efficient market.

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The aim of this study was to analyse the win, draw, and loss outcomes of soccer matches with situational variables and performance indicators. Data from group stage matches spanning the ten years between the 2010/2011 and 2019/2020 seasons in the European Champions League, were used. One-way analysis of variance (ANOVA) and Tukey HSD (honestly significant difference) tests indicated performance indicators which affected the outcome of matches. K-mean clustering, with statistically significant variables, categorized the quality of the opposition into three clusters: weak, balanced, and strong. Multidimensional scaling (MDS) and decision tree analysis were applied to each of these clusters, highlighting that performance indicators of the teams differed according to the quality of their opponent. Furthermore, according to the decision tree analysis, certain performance indicators, including scoring first and shots on target, increased the chances of winning regardless of the quality of the opposition. Finally, particular performance indicators increased the chance of winning, while others decreased this, in accordance with the quality of the opposition. These findings can help coaches develop different strategies, before or during the match, based on the quality of opponents, situational variables, and performance indicators.

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Standard survival techniques such as proportional hazards model are suffering from the unobserved heterogeneity. Frailty models provide an alternative way in order to account for heterogeneity caused by unobservable risk factors. Although vast studies have been done on estimation procedures, Evolutionary Algorithms (EAs) haven't received much attention in frailty studies. In this paper, we investigate the estimation performance of maximum likelihood estimation (MLE) via Particle Swarm Optimization (PSO) in modelling multivariate survival data with shared gamma frailty. Simulation studies and real data application are performed in order to assess the performance of MLE via PSO, quasi-Newton and conjugate gradient method.