scholarly journals Empirical Asset Pricing and Statistical Power in the Presence of Weak Risk Factors

2007 ◽  
Author(s):  
A. Craig Burnside
Keyword(s):  
Risk Factors ◽  
Asset Pricing ◽  
Statistical Power ◽  
Empirical 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.

Abstract P311: Effect of Non-Invasive Imaging on Cardiovascular Risk Factors and Downstream Testing: A Meta-Analysis of Randomized Controlled Trials

Circulation ◽  
2012 ◽  
Vol 125 (suppl_10) ◽  
Author(s):  
Seamus P Whelton ◽  
Khurram Nasir ◽  
Michael J Blaha ◽  
Daniel S Berman ◽  
Roger S Blumenthal
Keyword(s):  
Risk Factors ◽  
Risk Factor ◽  
Statistical Power ◽  
Controlled Trial ◽  
Meta Analysis ◽  
Cardiovascular Imaging ◽  
Significant Trend ◽  
Inclusion Criteria ◽  
Non Invasive ◽  
Randomized Controlled

Introduction: Non-invasive cardiovascular imaging has been proposed as a method to improve risk stratification and motivate improved patient and physician risk factor modification. Despite increasing use of these technologies there remains limited evidence documenting its effect on downstream testing and improvement in risk factor control. Hypothesis: Addition of the EISNER study to a prior meta-analysis will improve statistical power to demonstrate the downstream consequences of non-invasive cardiovascular imaging. Methods: A comprehensive literature search of the MEDLINE database (1966 through July 2011) was conducted. Major inclusion criteria required: 1) randomized controlled trial design, 2) participants with no known history of coronary heart disease or stroke, and 3) comparison of a group provided with results of a non-invasive imaging scan versus those without results. A total of eight trials with 4,084 participants met the inclusion criteria for this analysis. We analyzed the data using a random effects model to allow for heterogeneity. Results: Among imaging groups there was a significant increase in prescribing for statins (RR, 1.15; 95% CI, 1.01–1.32) and a non-significant trend for increased prescription of aspirin (RR, 1.15; 95% CI, 0.97–1.35), ACE/ARB (RR, 1.12; 95% CI, 0.96–1.31), and insulin (RR, 1.54; 95% CI, 0.75–3.18). There was a non-significant trend towards increased smoking cessation (RR, 1.35; 95% CI, 0.88–2.08). For downstream outcomes there was a non-significant increase in coronary angiography (RR, 1.20; 95% CI, 0.92–1.57), but not for revascularization (RR, 0.92; 95% CI, 0.55–1.53). There was no significant effect of imaging on the change in traditional risk factors. Limitations: There remains a limited number of trials in this important area. Therefore, trials included in this analysis use a variety of different imaging modalities and we were not able to pool the results based on appropriate clinical action (intensification at high risk and reduction at low risk). Conclusions: Non-invasive cardiovascular imaging leads to increased statin use, but associations with other downstream treatments and change in risk factors are not statistically significant. Our results highlight the limited amount of data for describing the downstream consequences after CAC testing.

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