Commodity Risk Factors and Intertemporal Asset Pricing

2014 ◽  
Author(s):  
Joelle Miffre ◽  
Ana-Maria Fuertes ◽  
Adriin Fernnndez-PPrez
Keyword(s):  
Risk Factors ◽  
Asset Pricing ◽  
Intertemporal Asset Pricing

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.

scholarly journals Industry Risk Factors and Stock Returns of Malaysian Oil and Gas Industry: A New Look with Mean Semi-Variance Asset Pricing Framework

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1732
Author(s):  
Mohammad Enamul Hoque ◽  
Soo-Wah Low
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Exchange Rate ◽  
Asset Pricing ◽  
Stock Returns ◽  
Oil And Gas ◽  
Negative Relationship ◽  
Downside Risk ◽  
Total Risk ◽  
Pricing Framework

This study employs a mean semi-variance asset pricing framework to examine the influence of risk factors on stock returns of oil and gas companies. This study also examines how downside risk is priced in stock performance. The time-series estimations expose that market, size, momentum, oil, gas, and exchange rate have significant impacts on oil and gas stock returns, but effects are heterogeneous depending on an individual stock. The two-stage cross-section estimations provide new insights about investors’ risk-return trade-off when facing downside risks. The results show that downside risk exposures to market, momentum, oil, and exchange rate factors are negatively priced in the Malaysian oil and gas stocks. This implies that investors are penalized for their downside exposure to these risk factors, and such inference is consistent with the risk preference explanation of prospect theory. Liquefied natural gas (LNG) is the only risk factor found to be positively priced in the returns of oil and gas stocks. Additionally, we find a negative relationship between LNG factor and total risk. This suggests that as the risk exposure to LNG increases, the total risk decreases, implying that the LNG risk factor is an idiosyncratic risk and not a systematic risk factor. Such interpretation is consistent with the correlation result, which shows no association between LNG and the market risk factor.

The diverging role of the systematic risk factors: evidence from real estate stock markets

2015 ◽  
Vol 33 (1) ◽  
pp. 81-106 ◽  
Author(s):  
Stephan Lang ◽  
Alexander Scholz
Keyword(s):  
Risk Factors ◽  
Time Series ◽  
Asset Pricing ◽  
Real Estate ◽  
Systematic Risk ◽  
Content Type ◽  
Risk Return ◽  
Systematic Risk Factors ◽  
Relationship Of

Purpose – The risk-return relationship of real estate equities is of particular interest for investors, practitioners and researchers. The purpose of this paper is to examine, in an asset pricing framework, whether the systematic risk factors play a significantly different role in explaining the returns of listed real estate companies, compared to general equities. Design/methodology/approach – Running the difference test of the Fama-French three-factor and the liquidity-augmented asset pricing model, the authors analyze the effect of the systematic risk factors related to market, size, BE/ME and liquidity in a time-series setting over the period July 1992 to June 2012. By applying the propensity score matching (PSM) algorithm, the authors bypass the “curse of dimensionality” of traditional matching techniques and identify a comparable control sample of general equities, in terms of the relevant firm characteristics of size, BE/ME and liquidity. Findings – The empirical results indicate that European real estate equity returns load significantly differently on the size, value and liquidity factor, while the influence of the market factor seems to be equivalent. In addition, the authors find an economically and statistically significant underperformance of European real estate equities, after accounting for the diverging role of systematic risk factors. Running the conditional time-series regression, the authors further reveal that these findings are predominately caused by the divergent risk-return behavior of real estate equities in economic downturns. Practical implications – Due to the diverging role of the systematic risk factors in pricing real estate equities, the authors provide evidence of potential diversification benefits for investors and portfolio managers. Originality/value – This is the first real estate asset pricing study to dissect the unique risk-return relationship of real estate equities by employing propensity score matching.

Money and the C-CAPM

2009 ◽  
Vol 44 (2) ◽  
pp. 337-368 ◽  
Author(s):  
Ronald J. Balvers ◽  
Dayong Huang
Keyword(s):  
Asset Pricing ◽  
Explanatory Power ◽  
Capital Asset Pricing ◽  
Money Growth ◽  
Liquidity Shocks ◽  
A Value ◽  
Asset Pricing Models ◽  
Monetary Economy ◽  
Growth Firms ◽  
Intertemporal Asset Pricing

AbstractWe consider asset pricing in a monetary economy where liquid assets are held to lower transaction costs. The ensuing model extends the capital asset pricing model (CAPM) and the consumption CAPM by deriving real money growth as an additional factor determining returns. Empirically, the two model versions compare favorably to other theoretical asset pricing models along several dimensions, supporting the traditional intertemporal asset pricing perspective. A value premium arises because value firms are sensitive to liquidity shocks but growth firms are not. Although no alternative factor drives out the money growth factor, the conditioning CAY factors of Lettau and Ludvigson (2001b) add explanatory power.

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