A Fast Literature Search Engine based on top-quality journals, by Dr. Mingze Gao.
- Topic classification is ongoing.
- Please kindly let me know [mingze.gao@mq.edu.au] in case of any errors.
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22,315 resources
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We have developed Bayesian Markov chain Monte Carlo (MCMC) methods for inferences of continuous-time models with stochastic volatility and infinite-activity Lévy jumps using discretely sampled data. Simulation studies show that (i) our methods provide accurate joint identification of diffusion, stochastic volatility, and Lévy jumps, and (ii) the affine jump-diffusion (AJD) models fail to adequately approximate the behavior of infinite-activity jumps. In particular, the AJD models fail to capture the "infinitely many" small Lévy jumps, which are too big for Brownian motion to model and too small for compound Poisson process to capture. Empirical studies show that infinite-activity Lévy jumps are essential for modeling the S&P 500 index returns.
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Traditional real options models demonstrate the importance of the “option to wait” due to uncertainty over future shocks to project cash flows. However, there is often another important source of uncertainty: uncertainty over the permanence of past shocks. Adding Bayesian uncertainty over the permanence of past shocks augments the traditional option to wait with an additional “option to learn.” The implied investment behavior differs significantly from that in standard models. For example, investment may occur at a time of stable or decreasing cash flows, respond sluggishly to cash flow shocks, and depend on the timing of project cash flows.
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The acceleration of the U.S. productivity growth in the late 1990s suggests a significant advance in technological innovation, making the perceived probability of entering a “new economy” ever increasing. Based on macroeconomic data, we identify a Bayesian investor's belief evolution when facing a possible structural break in the economy. We show that such belief evolution plays a significant role in explaining both the stock market boom and crash during 1998 to 2001. We conclude that a rational investor's uncertainty about the future of the U.S. economy provides an alternative explanation for the late 1990s stock market “bubble.”
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We examine the reference-dependent risk preferences of Koszegi and Rabin (2007), focusing on their choice-acclimating personal equilibria. Although their model has only a trivial intersection (expected utility) with other reference-dependent models, it has very strong connections with models that rely on different psychological intuitions. We prove that the intersection of rank-dependent utility and quadratic utility, two well-known generalizations of expected utility, is exactly monotone linear gain-loss choice-acclimating personal equilibria. We use these relationships to identify parameters of the model, discuss loss and risk aversion, and demonstrate new applications.
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Journals
- American Economic Review (10,442)
- Journal of Finance (6,024)
- Journal of Financial Economics (3,464)
- Review of Financial Studies (2,385)
Topic
- Bond (773)
- CEO (263)
- Mergers and Acquisitions (243)
- Director (145)
- Capital Structure (111)
Resource type
- Journal Article (22,315)
Publication year
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Between 1900 and 1999
(11,325)
- Between 1940 and 1949 (67)
- Between 1950 and 1959 (544)
- Between 1960 and 1969 (1,002)
- Between 1970 and 1979 (3,347)
- Between 1980 and 1989 (3,182)
- Between 1990 and 1999 (3,183)
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Between 2000 and 2024
(10,990)
- Between 2000 and 2009 (4,062)
- Between 2010 and 2019 (5,189)
- Between 2020 and 2024 (1,739)