Combining time series analysis and multi criteria decision making techniques for forecasting financial performance of banks in Turkey

Forecasting plays a major role in financial planning and it is an essential analytical tool in banks‟ strategies. In recent years, researchers are developing new techniques for estimation. Financial performance evaluation of banks is a kind of multi-criteria decision making (MCDM) problem which has developed rapidly. It is very important for a firm to monitor a wide range of performance indicators in order to ensure that appropriate and timely decisions and plans can be made. Suitable performance measures can ensure that managers adopt a long-term perspective and allocate the company‟s resources to the most effective activities. The aim of this study is to evaluate the financial performance model of Turkish Banks during 2012-2015 using forecasting (based on 2002-2011 data) methods and multi criteria decision techniques. As forecasting analysis tools, classical time series methods such as moving averages, exponential smoothing, Brown's single parameter linear exponential smoothing, Brown‟s second-order exponential smoothing, Holt's two parameter linear exponential smoothing and decomposition methods applied to financial ratios data. After forecasting techniques Analytical Hierarchy Process (AHP) and Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) methodologies are used for the outranking of banks.
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Combining time series analysis and multi criteria decision making techniques for forecasting financial performance of banks in Turkey