asset pricing tests
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2021 ◽  
Author(s):  
Sirio Aramonte ◽  
Mohammad R. Jahan-Parvar ◽  
Samuel Rosen ◽  
John W. Schindler

We propose a method to extract the risk-neutral distribution of firm-specific stock returns using both options and credit default swaps (CDS). Options and CDS provide information about the central part and the left tail of the distribution, respectively. Taken together, but not in isolation, options and CDS span the intermediate part of the distribution, which is driven by exposure to the risk of large, but not extreme, returns. Through a series of asset-pricing tests, we show that this intermediate-return risk carries a premium, particularly at times of heightened market stress. This paper was accepted by David Simchi-Levi, finance.


2021 ◽  
Author(s):  
Tim Alexander Kroencke ◽  
Julian Thimme

2021 ◽  
pp. 295-347
Author(s):  
Yuliya Plyakha ◽  
Raman Uppal ◽  
Grigory Vilkov

2020 ◽  
Vol 20 (110) ◽  
Author(s):  
Tobias Adrian ◽  
Peichu Xie

The USD asset share of non-U.S. banks captures the demand for dollars by these investors. An instrumental variable strategy identifies a causal link from the USD asset share to the USD exchange rate. Cross-sectional asset pricing tests show that the USD asset share is a highly significant pricing factor for carry trade strategies. The USD asset share forecasts the dollar with economically large magnitude, high statistical significance, and large explanatory power, both in sample and out of sample, pointing towards time varying risk premia. It takes 2-5 years for exchange rate risk premia to normalize in response to demand shocks.


2020 ◽  
Author(s):  
Nora Laurinaityte ◽  
Christoph Meinerding ◽  
Christian Schlag ◽  
Julian Thimme

2019 ◽  
Vol 95 (5) ◽  
pp. 321-350 ◽  
Author(s):  
Maria Ogneva ◽  
Joseph D. Piotroski ◽  
Anastasia A. Zakolyukina

ABSTRACT In this paper, we use accounting fundamentals to measure systematic risk of distress. Our main testable prediction—that this risk increases with the probability of recessionary failure, P(R|F)—is based on a stylized model that guides our empirical analyses. We first apply the lasso method to select accounting fundamentals that can be combined into P(R|F) estimates. We then use the obtained estimates in asset-pricing tests. This approach successfully extracts systematic risk information from accounting data—we document a significant positive premium associated with P(R|F) estimates. The premium covaries with the news about the business cycle and aggregate failure rates. Additional tests underscore the importance of the “structure” imposed through recessionary-failure-probability estimation. The “agnostic” return predictor that relies only on past correlations between the same fundamental variables and returns exhibits markedly different properties. JEL Classifications: G12; G32; G33; M41.


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