Financial forecast in business and an application proposal

Financial forecast is a subject that investors and researchers have been working on for many years. It is known that in the 1960s, statistical methods were primarily used in financial failure predictions. However, the developing business environment and the globalizing market have led to the emergence of many different variables. This situation has led to the complexity of forecasting models. Technological developments have enabled financial forecast to be made by computer programs. In this way, it has been possible to analyze with more variables and to avoid mistakes. This study focuses on the use of machine learning techniques in financial forecast. In this study, five companies from different sectors whose shares are traded in Borsa Istanbul were randomly selected and the financial statements of these companies between 2009 and 2020 were obtained from the Public Disclosure Platform website. Current assets, fixed assets, equity, net sales and net profit items of the companies between 2010 and 2020 are forecasted using the random forest technique. As a result of the research, it has been determined that the random forest technique can be used effectively in financial forecast.