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 4,062 resources
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In this paper I argue that corporate finance theory, empirical research, practical applications, and policy recommendations are deeply rooted in an underlying theory of the firm. I also argue that although the existing theories have delivered very important and useful insights, they seem to be quite ineffective in helping us cope with the new type of firms that is emerging. I outline the characteristics that a new theory of the firm should satisfy and how such a theory could change the way we do corporate finance, both theoretically and empirically.
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Implied risk aversion estimates reported in the literature are strongly U-shaped. This article explores different potential explanations for these “smile” patterns: (i) preference aggregation, both with and without stochastic volatility and jumps in returns, (ii) misestimation of investors’ beliefs caused by stochastic volatility, jumps, or a Peso problem, and (iii) heterogeneous beliefs. The results reveal that preference aggregation and misestimation of investors’ beliefs caused by stochastic volatility and jumps are unlikely to be the explanation for the smile. Although a Peso problem can account for the smile, the required probability of a market crash is unrealistically large. Heterogeneous beliefs cause sizable distortions in implied risk aversion, but the degree of heterogeneity required to explain the smile is implausibly large.
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In this paper, we analyze the usefulness of technical analysis, specifically the widely employed moving average trading rule from an asset allocation perspective. We show that, when stock returns are predictable, technical analysis adds value to commonly used allocation rules that invest fixed proportions of wealth in stocks. When uncertainty exists about predictability, which is likely in practice, the fixed allocation rules combined with technical analysis can outperform the prior-dependent optimal learning rule when the prior is not too informative. Moreover, the technical trading rules are robust to model specification, and they tend to substantially outperform the model-based optimal trading strategies when the model governing the stock price is uncertain.
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Evaluating default correlations or the probabilities of default by more than one firm is an important task in credit analysis, derivatives pricing, and risk management. However, default correlations cannot be measured directly, multiple-default modeling is technically difficult, and most existing credit models cannot be applied to analyze multiple defaults. This article develops a first-passage-time model, providing an analytical formula for calculating default correlations that is easily implemented and conveniently used for a variety of financial applications. The model also provides a theoretical justification for several empirical regularities in the credit risk literature.
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A principal can observe both the output and input of an agent who works at a job involving multiple tasks. We provide a simple theory that explains why it may be optimal for the principal to use only an output-based incentive contract, even though the principal can monitor the agent's actions perfectly in all but one task and knows exactly which action is optimal for each task. (JEL D82, D86, M54)
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Zhang, X. F. (2006). Information Uncertainty and Stock Returns. The Journal of Finance, 61, 105–137.
There is substantial evidence of short‐term stock price continuation, which the prior literature often attributes to investor behavioral biases such as underreaction to new information. This paper investigates the role of information uncertainty in price continuation anomalies and cross‐sectional variations in stock returns. If short‐term price continuation is due to investor behavioral biases, we should observe greater price drift when there is greater information uncertainty. As a result, greater information uncertainty should produce relatively higher expected returns following good news and relatively lower expected returns following bad news. My evidence supports this hypothesis.
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The value anomaly arises naturally in the neoclassical framework with rational expectations. Costly reversibility and countercyclical price of risk cause assets in place to be harder to reduce, and hence are riskier than growth options especially in bad times when the price of risk is high. By linking risk and expected returns to economic primitives, such as tastes and technology, my model generates many empirical regularities in the cross‐section of returns; it also yields an array of new refutable hypotheses providing fresh directions for future empirical research.
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Journals
- American Economic Review (1,932)
- Journal of Finance (783)
- Journal of Financial Economics (773)
- Review of Financial Studies (574)
Topic
- Bond (133)
- Mergers and Acquisitions (63)
- CEO (58)
- Director (31)
- Capital Structure (22)
Resource type
- Journal Article (4,062)