Capital structure and its possible effects on the firms' financial and real decisions have been one of the most debated concepts in finance literature. This paper investigates the relation between firms' financial and real decisions, in terms of capital structure and firm performance. Such possible relation is analyzed for the manufacturing firms, which are traded in Borsa Istanbul during the period of [2003][2004][2005][2006][2007][2008][2009][2010][2011][2012][2013][2014][2015]. Return on equity and return on assets are used as measures of firm performance; and short-term debt to total assets, long-term debt to total assets and debt to equity is used as explanatory variables; the total assets are control variables.The findings of the study presented that for both short-term debt and long-term debt have a negative and statistically significant effect on both return

Especially for the last decade, the neural network models have been applied to solve financial problems like portfolio construction and stock market forecasting. Among the alternative neural network models, the multilayer perceptron models are expected to be effective and widely applied in financial forecasting. This study examines the forecasting power multilayer perceptron models for daily and sessional returns of ISE-100 index. The findings imply that the multilayer perceptron models presented promising performance in forecasting the ISE-100 index returns. However, further emphasis should be placed on different input variables and model architectures in order to improve the forecasting performances.

The main purpose of this study is to investigate the relationship between intellectual capital and financial performance of financial companies listed in Borsa Istanbul, using data of 44 listed companies over 2004-2015. Value Added Intellectual Coefficient (VAIC) method is used as a measure of intellectual capital (IC). An OLS regression is utilized to examine the impact of intellectual capital; Human capital efficiency (HCE), Structural capital efficiency (SCE), and Capital employed efficiency (CEE) on market performance, financial performance, and productivity performance. The findings show that HCE has a positive significant relation with ROA after the crisis and with ROE before and after the crisis. SCE show a positive significant relation with PE and ROE after the crisis and a negative significant association with MB after the crisis. Regarding to CEE, the results show that it has only a positive significant impact on MB after the crisis and a negative significant influence on ATO after the crisis. Generally, VAIC has a negative significant relationship with ATO before the crisis and has a positive association with ROA after the crisis, in addition to a positive significant influence of ROE before and after crisis.

While neglecting the importance of technological intensity, most of the prior studies documented the positive contribution of intellectual capital (IC) to corporate financial performance. This study aims at analyzing the relation between IC and corporate financial performance addressing the technological intensity in different sectors from 17 emerging countries. The impact of IC, which is measured by Value Added Intellectual Coefficient (VAIC) and its components; Capital Employed Efficiency (CEE), Human Capital Efficiency (HCE), and Structural Capital Efficiency (SCE), on corporate financial performance will be evaluated using panel data analysis for the period between 2009-2019. Accordingly, IC and its components are found to be significant drivers of financial performance being higher for sectors that are more technology intensive. Moreover, human and physical capital are the main components, which boost finance performance for all groups irrespective of technological intensity in the emerging market context.

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