Investment valuation analysis with artificial neural networks

Warning The system is temporarily closed to updates for reporting purpose.

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)

[img]PDF - Registered users only - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader

Official URL: http://journal.dogus.edu.tr/index.php/duj/article/view/1102


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
ID Code:34358
Deposited By:Nihat Kasap
Deposited On:15 Aug 2018 10:59
Last Modified:15 Aug 2018 10:59

Repository Staff Only: item control page