Investment Valuation Analysis with Artificial Neural Networks
Author(s) -
Hüseyin İnce,
Kadir SAYIM,
Salih Zeki İMAMOĞLU,
Nihat Kasap
Publication year - 2017
Publication title -
doğuş üniversitesi dergisi
Language(s) - English
Resource type - Journals
eISSN - 1308-6979
pISSN - 1302-6739
DOI - 10.31671/dogus.2018.33
Subject(s) - artificial neural network , valuation (finance) , economics , investment analysis , computer science , artificial intelligence , econometrics , business , financial economics , finance , portfolio
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.
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