scholarly journals On the predictive power of CAPE or Shiller’s PE ratio: the case of the Greek stock market

Author(s):  
Dimitrios Kenourgios ◽  
Spyros Papathanasiou ◽  
Anastasia Christina Bampili
2017 ◽  
Vol 21 (5) ◽  
Author(s):  
Terence Tai-Leung Chong ◽  
Ka-Ho Poon

AbstractSavin et al. [Savin, G., P. Weller, and J. Zvingelis. 2007. “The Predictive Power of “Head-and-Shoulders” Price Patterns in the US Stock Market.”


2017 ◽  
Vol 10 (3) ◽  
pp. 431
Author(s):  
Rafael Igrejas ◽  
Raphael Braga Da Silva ◽  
Marcelo Cabus Klotzle ◽  
Antonio Carlos Figueiredo Pinto ◽  
Paulo Vitor Jordão da Gama Silva

The estimation of cross-section returns for defining investment strategies based on financial multiples has been proven to be relevant following Fama and French’s (1992) research. One of the challenges for such studies is to identify the main variables that are suitable for explaining the returns in a particular context because the variables that are widely used in developed markets behave differently in emerging countries. In this study, we analyze the predictive power of the EV/EBITDA multiple in the context of the Brazilian stock market. The results show that the analyzed multiple has a strong relationship with the future returns of companies listed on the BM&F BOVESPA index between 2005 and 2013. For the period under review, the investment strategy of purchasing stocks when EV/EBITDA was low and selling stocks when EV/EBITDA was high showed abnormal returns of 15.94% per year, even after controlling for risk factors.


2020 ◽  
Vol 37 (2) ◽  
pp. 323-346
Author(s):  
Mohammed M. Elgammal ◽  
Fatma Ehab Ahmed ◽  
David G. McMillan

Purpose The purpose of this paper is to consider the economic information content within several popular stock market factors and to the extent to which their movements are both explained by economic variables and can explain future output growth. Design/methodology/approach Using US stock portfolios from 1964 to 2019, the authors undertake three related exercises: whether a set of common factors contain independent predictive ability for stock returns, what economic and market variables explain movements in the factors and whether stock market factors have predictive power for future output growth. Findings The results show that several of the considered factors do not contain independent information for stock returns. Further, most of these factors are neither explained by economic conditions nor they provide any predictive power for future output growth. Thus, they appear to contain very little economic content. However, the results suggest that the impact of these factors is more prominent with higher macroeconomic risk (contractionary regime). Research limitations/implications The stock market factors are more likely to reflect existing market conditions and exhibit a weaker relation with economic conditions and do not act as a window on future behavior. Practical implications Fama and French three-factor model still have better explanations for stock returns and economic information more than any other models. Originality/value This paper contributes to the literature by examining whether a selection of factors provides unique information when modelling stock returns data. It also investigates what variables can predict movements in the stock market factors. Third, it examines whether the factors exhibit a link with subsequent economic output. This should establish whether the stock market factors contain useful information for stock returns and the macroeconomy or whether the significance of the factor is a result of chance. The results in this paper should advance our understanding of asset price movement and the links between the macroeconomy and financial markets and, thus, be of interest to academics, investors and policy-makers.


2003 ◽  
Vol 33 (02) ◽  
pp. 399-417 ◽  
Author(s):  
Jens Perch Nielsen ◽  
Stefan Sperlich

While the traditional R 2 value is useful to evaluate the quality of a fit, it does not work when it comes to evaluating the predictive power of estimated financial models in finite samples. In this paper we introduce a validated value useful for prediction. Based on data from the Danish stock market, using this measure we find that the dividend-price ratio has predictive power. The best horizon for prediction seems to be four years. On a one year horizon, we find that while inflation and interest rate do not add to the predictive power of the dividend-price ratio then last years excess stock return does.


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