Asset Pricing in Production Economies When Capital Inputs are Heterogeneous

2016 ◽  
Author(s):  
Nicole Branger ◽  
Nikolai Grrber ◽  
Malte Schumacher
Keyword(s):  
Asset Pricing ◽  
Production Economies

scholarly journals Asset pricing in production economies with extrapolative expectations

2015 ◽  
Vol 76 ◽  
pp. 87-106 ◽  
Author(s):  
David Hirshleifer ◽  
Jun Li ◽  
Jianfeng Yu
Keyword(s):  
Asset Pricing ◽  
Production Economies

Asset Pricing in Home Production Economies

2009 ◽  
Author(s):  
Ivan Jaccard
Keyword(s):  
Asset Pricing ◽  
Home Production ◽  
Production Economies

scholarly journals Asset pricing in production economies

1998 ◽  
Vol 41 (2) ◽  
pp. 257-275 ◽  
Author(s):  
Urban J. Jermann
Keyword(s):  
Asset Pricing ◽  
Production Economies

scholarly journals Asset Pricing in Production Economies with Extrapolative Expectations

2012 ◽  
Author(s):  
David A. Hirshleifer ◽  
Jianfeng Yu
Keyword(s):  
Asset Pricing ◽  
Production Economies

Asset Pricing in Production Economies with Learning About Rare Disasters

2020 ◽  
Author(s):  
Yingjie Niu ◽  
Yaoyao Wu ◽  
Jinqiang Yang ◽  
Zhentao Zou
Keyword(s):  
Asset Pricing ◽  
Production Economies ◽  
Rare Disasters

Asset Pricing for Dynamic Economies

2008 ◽  
Author(s):  
Sumru Altug ◽  
Pamela Labadie
Keyword(s):  
Asset Pricing ◽  
Dynamic Economies

Freedom Indices and Capital Asset Pricing Model: Some Malaysian Evidence

2020 ◽  
Vol 1 (1) ◽  
pp. 1-21
Author(s):  
Ying Tay Lee ◽  
Devinaga Rasiah ◽  
Ming Ming Lai
Keyword(s):  
Human Rights ◽  
Asset Pricing ◽  
Stock Returns ◽  
Firm Size ◽  
Explanatory Power ◽  
Least Square ◽  
Press Freedom ◽  
Capital Asset Pricing ◽  
Capital Asset ◽  
Cross Sectional

Human rights and fundamental freedoms such as economic, political, and press freedoms vary widely from country to country. It creates opportunity and risk in investment decisions. Thus, this study is carried out to examine if the explanatory power of the model for capital asset pricing could be improved when these human rights movement indices are included in the model. The sample for this study comprises of 495 stocks listed in Bursa Malaysia, covering the sampling period from 2003 to 2013. The model applied in this study employed the pooled ordinary least square regression estimation. In addition, the robustness of the model is tested by using firm size as a controlled variable. The findings show that market beta as well as the economic and press freedom indices could explain the cross-sectional stock returns of the Malaysian stock market. By controlling the firm size, it adds marginally to the explanation of the extended CAP model which incorporated economic, political, and press freedom indices.

Risk Factors of Collateralized Loan Obligations and Corporate Bonds

2020 ◽  
Vol 32 (6) ◽  
pp. 347-355
Author(s):  
Mark Wahrenburg ◽  
Andreas Barth ◽  
Mohammad Izadi ◽  
Anas Rahhal
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Asset Pricing ◽  
Systemic Risk ◽  
Corporate Bonds ◽  
Risk Exposure ◽  
Expected Returns ◽  
Yield Spreads ◽  
Pricing Factors ◽  
Return Difference

AbstractStructured products like collateralized loan obligations (CLOs) tend to offer significantly higher yield spreads than corporate bonds (CBs) with the same rating. At the same time, empirical evidence does not indicate that this higher yield is reduced by higher default losses of CLOs. The evidence thus suggests that CLOs offer higher expected returns compared to CB with similar credit risk. This study aims to analyze whether this return difference is captured by asset pricing factors. We show that market risk is the predominant risk factor for both CBs and CLOs. CLO investors, however, additionally demand a premium for their risk exposure towards systemic risk. This premium is inversely related to the rating class of the CLO.

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