Investment valuation analysis with artificial neural networks

İnce, Hüseyin and Sayım, Kadir and İmamoğlu, Salih Zeki and Kasap, Nihat (2017) Investment valuation analysis with artificial neural networks. Doğuş University Journal (Doğuş Üniversitesi Dergisi), 18 (2). pp. 85-96. ISSN 1302-6739 (print) 1308-6979 (online)

[thumbnail of Kasap_2017_DogusUniv.pdf] PDF
Restricted to Registered users only

Download (551kB) | Request a copy


This paper shows that discounted cash flow and net present value, which are traditional investment valuation models, can be combined with artificial neural network model forecasting. The main inputs for the valuation models, such as revenue, costs, capital expenditure, and their growth rates, are heavily related to sector dynamics and macroeconomics. The growth rates of those inputs are related to inflation and exchange rates. Therefore, predicting inflation and exchange rates is a critical issue for the valuation output. In this paper, the Turkish economy’s inflation rate and the exchange rate of USD/TRY are forecast by artificial neural networks and implemented to the discounted cash flow model. Finally, the results are benchmarked with conventional practices.
Item Type: Article
Uncontrolled Keywords: Artificial neural networks, Investment valuation, Forecasting, Inflation rate forecast, Exchange rate forecast, Discounted cash flow
Divisions: Sabancı Business School
Sabancı Business School > Operations Management and Information Systems
Depositing User: Nihat Kasap
Date Deposited: 15 Aug 2018 10:59
Last Modified: 15 Aug 2018 10:59

Actions (login required)

View Item
View Item