Usage of Multiple Perceptron Neural Networks in Determination of the Financial Plan

Financial planning within a company represents one of the basic activities of a company as well as a very demanding activity of the financial manager. Based on the main principles of economy and data from the previous periods (especially main financial statements – balance sheet, profit and loss, cash-flow statement) the future development of the given company is predicted. Different mathematical and statistical models and methods including statistical, causal and intuitive methods are used to carry this out. Some models, such as artificial neural networks, represent a very efficient method for prediction. The article identifies company revenues as the initial indicator in setting a company´s financial plan. Multilayer perceptron neural networks are very often used for their prediction. Information on Hornbach Company´s Profit and Loss Statement from the period of 1999 to 2015 is used as input data. A total of 1000 artificial neural networks is generated, out of which 5 most appropriate are maintained. Sensitivity analysis is also carried out. The contribution finally states that in practice, the suggested neural structures are useful for compiling a company financial plan which is always derived from the amount of sales.