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This study mainly focuses on the impact of various financing channels on corporate innovations. For this purpose, three kinds of external financing sources and two kinds of internal financing sources are considered. The study covers 18 Turkis h companies traded in Istanbul Stock Exchange with the highest R&D expenditures of the year 2019. The analyzes are carried out using dynamic panel data analysis. The estimation results show that loans have a negative and statistically significant effect on R&D expenditures. Moreover, according to the findings, there is no statistically significant effect of internal financing on R&D expenditures. The results of the study provide valuable information on how companies finance innovation processes.

Markowitz's Mean-Variance portfolio is a breakthrough in finance because it leads the use of mathematics in financial applications. Moreover, with the model one period portfolio decisions can easily be taken and this is also important feature of the model. On the other side, the studies in the literature show that the performance of the mean-variance portfolios are very poor due to the estimation errors. Therefore, to overcome this problem several new theories and methods/approaches are proposed. The bayesian portfolio methodology is one of them. In this study we aim to compare three bayesian approaches, i.e. Jorion (1985, 1986), Kan and Zhou (2007) and Tu and Zhou (2011), with the Markowitz's mean-variance model. In addition, as being a base model the equally weighted portfolio is also compared with those models. For this purpose, in the study the daily return series of 30 assets traded in ISE30 during the period of 2010-2017 are considered and the performance of the portfolios of different dimensions which are constructed with the help of the simulations generated from the real return data are compared. As a general overview, it is concluded that Kan and Zhou's bayesian approach performed best among others.