A Fast Literature Search Engine based on top-quality journals, by Dr. Mingze Gao.
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- Please kindly let me know [mingze.gao@mq.edu.au] in case of any errors.
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Results 462 resources
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We study the transmission channels from central banks’ quantitative easing programs via the banking sector when central banks start purchasing corporate bonds. We find evidence consistent with a “capital structure channel” of monetary policy. The announcement of central bank purchases reduces the bond yields of firms whose bonds are eligible for central bank purchases. These firms substitute bank term loans with bond debt, thereby relaxing banks’ lending constraints: banks with low tier-1 ratios and high nonperforming loans increase lending to private (and profitable) firms, which experience a growth in investment. The credit reallocation increases banks’ risk-taking in corporate credit.
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We present a dynamic model that links characteristic‐based return predictability to systematic factors that determine the evolution of firm fundamentals. In the model, an economy‐wide disruption process reallocates profits from existing businesses to new projects and thus generates a source of systematic risk for portfolios of firms sorted on value, profitability, and asset growth. If investors are overconfident about their ability to evaluate the disruption climate, these characteristic‐sorted portfolios exhibit persistent mispricing. The model generates predictions about the conditional predictability of characteristic‐sorted portfolio returns and illustrates how return persistence increases the likelihood of observing characteristic‐based anomalies.
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Recent studies show that the standard test portfolios do not contain sufficient information to discriminate between asset pricing models. To address this issue, we develop a large-scale approach that expands the cross-section to several thousand portfolios. Our novel approach is simple, widely applicable, and allows for formal evaluation/comparison tests. Its benefits are confirmed in empirical tests of CAPM- and characteristic-based models. While these models are all misspecified, we uncover striking performance differences between them. In particular, the human capital and conditional CAPMs largely outperform the CAPM, which suggests that labor income and time-varying recession risks are primary concerns for investors.
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This paper shows that a macro model with segmented financial markets can generate sizable movements in housing prices in response to changes in credit conditions. We establish theoretically that reductions in mortgage rates always have a positive effect on prices, whereas the relaxation of loan-to-value constraints has ambiguous effects. A quantitative version of the model under perfect foresight accounts for about one-half of the observed price increase in the United States in the 2000s. When we include shocks to expectations about housing finance conditions, the model's ability to match house values improves significantly. The framework reconciles the observed disconnect between house prices and rents since, in general equilibrium, financial shocks can decrease rents and increase prices.
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What makes an asset a "safe" asset? We study a model where two countries each issue sovereign bonds to satisfy investors' safe asset demands. The countries differ in the float of their bonds and the fundamental resources available to rollover debts. A sovereign's debt is safer if its fundamentals are strong relative to other possible safe assets, not merely strong on an absolute basis. If demand for safe assets is high, a large float enhances safety through a market depth benefit. If demand for safe assets is low, then large debt size is a negative as rollover risk looms large.
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This note corrects an error in the proof of Proposition 2 of “Risk Reduction in Large Portfolios: Why Imposing the Wrong Constraint Helps” that appeared in the Journal of Finance, August 2003.
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We propose a protocol for identifying genuine risk factors. A genuine risk factor must be related to the covariance matrix of returns, must be priced in the cross-section of returns, and should yield a reward-to-risk ratio that is reasonable enough to be consistent with risk pricing. A market factor, a profitability factor, and traded versions of macroeconomic factors pass our protocol, but many characteristic-based factors do not. Several of the underlying characteristics, however, do command premiums in the cross-section.
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Leading empiricists and theorists of cities have recently argued that the generation and exchange of ideas must play a more central role in the analysis of cities. This paper develops the first system of cities model with costly idea exchange as the agglomeration force. The model replicates a broad set of established facts about the cross section of cities. It provides the first spatial equilibrium theory of why skill premia are higher in larger cities and how variation in these premia emerges from symmetric fundamentals.
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What is the impact of higher technological volatility on asset prices and macroeconomic aggregates? I find the answer hinges on its sectoral origin. Volatility that originates from the consumption (investment) sector drops (raises) macroeconomic growth rates and stock prices. Moreover, consumption (investment) sector’s technological volatility has a positive (negative) market price of risk. I show that a quantitative two-sector DSGE model that features monopolistic power for firms and sticky prices, as well as early resolution of uncertainty, can explain the differential impact of sectoral volatilities on real and financial variables. In all, the sectoral decomposition of volatility can overturn the typical negative relation between aggregate volatility and economic activity.
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Modigliani and Miller show that the total market value of a firm is unaffected by a repackaging of asset return streams to equity and debt if pricing is arbitrage‐free. We investigate this invariance theorem in experimental asset markets, finding value‐invariance for assets of identical risks when returns are perfectly correlated. However, exploiting price discrepancies has risk when returns have the same expected value but are uncorrelated, in which case the law of one price is violated. Discrepancies shrink in consecutive markets, but persist even with experienced traders. In markets where overall trader acuity is high, assets trade closer to parity.
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Journals
- American Economic Review (127)
- Journal of Finance (76)
- Journal of Financial Economics (136)
- Review of Financial Studies (123)
Topic
- Bond (28)
- Director (5)
- CEO (5)
- Capital Structure (3)
- Mergers and Acquisitions (3)
Resource type
- Journal Article (462)