scholarly journals Universal time preference

PLoS ONE ◽  
2021 ◽  
Vol 16 (2) ◽  
pp. e0245692
Author(s):  
Marc Oliver Rieger ◽  
Mei Wang ◽  
Thorsten Hens
Keyword(s):  
Time Preference ◽  
School Attendance ◽  
Common Factor ◽  
Large Degree ◽  
Gasoline Prices ◽  
Aggregation Method ◽  
Risk Premiums ◽  
Latent Construct ◽  
Equity Risk ◽  
Human Decision

Time preferences are central to human decision making; therefore, a thorough understanding of their international differences is highly relevant. Previous measurements, however, vary widely in their methodology, from questions answered on the Likert scale to lottery-type questions. We show that these different measurements correlate to a large degree and that they have a common factor that can predict a broad spectrum of variables: the countries’ credit ratings, gasoline prices (as a proxy for environmental protection), equity risk premiums, and average years of school attendance. The resulting data on this time preference factor for N = 117 countries and regions will be highly useful for further research. Our aggregation method is applicable to merge cross-cultural studies that measure the same latent construct with different methodologies.

Multifactor Models and Their Consistency with the APT

2020 ◽  
Author(s):  
Ilan Cooper ◽  
Liang Ma ◽  
Paulo Maio ◽  
Dennis Philip
Keyword(s):  
Large Scale ◽  
Common Factor ◽  
Empirical Asset Pricing ◽  
Arbitrage Pricing Theory ◽  
Risk Premiums ◽  
Multifactor Models ◽  
Equity Risk ◽  
Pricing Theory ◽  
The Common ◽  
Components Method

Abstract We examine the consistency of several prominent multifactor models from the empirical asset pricing literature with the arbitrage pricing theory (APT) framework. We follow the APT-related literature and estimate the common factor structure from a rich cross-section (associated with 42 major CAPM anomalies) by employing the asymptotic principal components method. Our benchmark model contains six statistical factors and clearly dominates, in both economic and statistical terms, most of the empirical multifactor models proposed in the literature by a good margin. These results represent a critical challenge to the current workhorse models in terms of explaining large-scale equity risk premiums.

scholarly journals Nuclear Hazard and Asset Prices: Implications of Nuclear Disasters in the Cross-Sectional Behavior of Stock Returns

2020 ◽  
Vol 12 (22) ◽  
pp. 9721
Author(s):  
Ana Belén Alonso-Conde ◽  
Javier Rojo-Suárez
Keyword(s):  
Stock Returns ◽  
Factor Model ◽  
Large Fraction ◽  
Factor Models ◽  
Cross Sectional ◽  
Risk Premiums ◽  
Conditional Capm ◽  
Equity Risk ◽  
The Cross ◽  
The Cost

Using stock return data for the Japanese equity market, for the period from July 1983 to June 2018, we analyze the effect of major nuclear disasters worldwide on Japanese discount rates. For that purpose, we compare the performance of the capital asset pricing model (CAPM) conditional on the event of nuclear disasters with that of the classic CAPM and the Fama–French three- and five-factor models. In order to control for nuclear disasters, we use an instrument that allows us to parameterize the linear stochastic discount factor of the conditional CAPM and transform the classic CAPM into a three-factor model. In this regard, the use of nuclear disasters as an explanatory variable for the cross-sectional behavior of stock returns is a novel contribution of this research. Our results suggest that nuclear disasters account for a large fraction of the variation of stock returns, allowing the CAPM to perform similarly to the Fama–French three- and five-factor models. Furthermore, our results show that, in general, nuclear disasters are positively related to the expected returns of a large number of assets under study. Our results have important implications for the task of estimating the cost of equity and constitute a step forward in understanding the relationship between equity risk premiums and nuclear disasters.

Dividend yields are equity risk premiums

1986 ◽  
Vol 12 (2) ◽  
pp. 81-83 ◽  
Author(s):  
Lewis D. Johnson
Keyword(s):  
Risk Premiums ◽  
Equity Risk
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