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Journals / Doğuş Üniversitesi Dergisi / 2017 / Cilt: 18 Sayı: 2

Investment Valuation Analysis with Artificial Neural Networks

Yapay Sinir Ağları ile Yatırım Değerlemesi Analizi

Hüseyin İnce(Gebze Teknik Üniversitesi, İktisat Bölümü)
Kadir Sayım(Gebze Teknik Üniversitesi, Sosyal Bilimler Enstitüsü)
Salih Zeki İmamoğlu(Gebze Teknik Üniversitesi, Strateji Bilimi)
Nihat Kasap(Sabancı Üniversitesi, Yönetim Bilimleri Fakültesi)
Pages
85–96
Publication Date
2017-07-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Finally, the results are benchmarked with conventional practices.

📌 3 Key Takeaways

🎯
Objective & Hypothesis: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.
📊
Key Findings & Data: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.
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Conclusion & Impact:Finally, the results are benchmarked with conventional practices.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Yapay sinir ağları · Yatırım değerlemesi · Tahmin etme

Abstract

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.

Özet

Bu çalışmada geleneksel yatırım değerleme metotlarından olan indirgenmiş nakit akım ve net bugünkü değer modeli ile yapay sinir ağları modelinin tahmin etme özelliğinin birleştirilmesi analiz edilmiştir. Değerleme modellerinin temel bileşenlerinden olan satış gelirleri, maliyetler, yatırım harcamaları ve bunların yıllar içerisindeki büyüme oranları sektörel dinamikler ve makroekonomik faktörlerle yakından ilişkilidir. Bununla birlikte, enflasyon oranı ve döviz kurları bu bileşenlerin değişim oranlarını etkilemektedir. Dolayısıyla enflasyon oranını ve döviz kurlarını tahmin etmek değerlemenin sonucu açısından kritik bir önem taşımaktadır. Bu çalışmada Türkiye enflasyonu ve USD/TRY döviz kuru yapay sinir ağları modeli ile tahmin edilmiş ve bu değişkenler indirgenmiş nakit akım modeli içerisine yerleştirilmiştir. Bu modelin sonuçları geleneksel yöntemler ile karşılaştırılmıştır

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Cite This Article

İnce, H., Sayım, K., İmamoğlu, S. Z., Kasap, N. (2017). Investment Valuation Analysis with Artificial Neural Networks. Doğuş Üniversitesi Dergisi, Cilt: 18 Sayı: 2, 85–96. https://ajindex.com/articles/1172282

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