Journals / Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi / 2000 / Cilt: 18 - Sayı: 2

PREDICTING STOCK RETURNS USING FUNDAMENTAL INFORMATION AND MULTIVARIATE STATISTICAL MODELLING: AN EMPIRICAL STUDY ON ISTANBUL STOCK EXCHANGE

Pages
433–450
Publication Date
2000-12-31
DOI
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AI Summary & Key Takeaways

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

We conclude that developing a more general model for prediction might solve the problem about unstable variables, but the general model has verv limited ability of ranking the stocks according to their perfonnance.

📌 3 Key Takeaways

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Objective & Hypothesis:This paper performs a financial analysis that combines a set of fundamental information into a summarv measure which predicts the return of stocks bv usin2 logit analysis, The findings suggest that the predictive power of financial ratios is verv high and more important than the fundamental information. but the variables (ratios) of logit models are not stable from one period to another.
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Key Findings & Data:Also it is found that there is a statistically significant correlation benveen the observed and predicted ranking.
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Conclusion & Impact:We conclude that developing a more general model for prediction might solve the problem about unstable variables, but the general model has verv limited ability of ranking the stocks according to their perfonnance.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Fnancial statement analysis · logit model · prediction of stock perfonnance

Özet

This paper performs a financial analysis that combines a set of fundamental information into a summarv measure which predicts the return of stocks bv usin2 logit analysis, The findings suggest that the predictive power of financial ratios is verv high and more important than the fundamental information. but the variables (ratios) of logit models are not stable from one period to another. Also it is found that there is a statistically significant correlation benveen the observed and predicted ranking. We conclude that developing a more general model for prediction might solve the problem about unstable variables, but the general model has verv limited ability of ranking the stocks according to their perfonnance.

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Cite This Article

AKTAŞ, R., KARAN, M. B. (2000). PREDICTING STOCK RETURNS USING FUNDAMENTAL INFORMATION AND MULTIVARIATE STATISTICAL MODELLING: AN EMPIRICAL STUDY ON ISTANBUL STOCK EXCHANGE. Hacettepe Üniversitesi İktisadi ve İdari Bilimler Fakültesi Dergisi, Cilt: 18 - Sayı: 2, 433–450. https://ajindex.com/articles/670529

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References (1)

  1. Ağaoğlu, E. A. (1989) Türkiye' de Banka İşletmelerinin Ekonomik Analizi ve Gelişme Eğilimleri. Unpublished Ph.D. Thesis. Ankara.