Optimum consumption and portfolio rules in a continuous-time model☆
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TL;DR: In this paper, the authors considered the continuous-time consumption-portfolio problem for an individual whose income is generated by capital gains on investments in assets with prices assumed to satisfy the geometric Brownian motion hypothesis, which implies that asset prices are stationary and lognormally distributed.
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About: This article is published in Journal of Economic Theory. The article was published on 01 Dec 1971. and is currently open access. The article focuses on the topics: Geometric Brownian motion & Intertemporal portfolio choice.
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References
Lifetime Portfolio Selection under Uncertainty: The Continuous-Time Case
TL;DR: In this paper, the combined problem of optimal portfolio selection and consumption rules for an individual in a continuous-time model was examined, where his income is generated by returns on assets and these returns or instantaneous "growth rates" are stochastic.
5.7K
Stochastic Differential Equations
Ioannis Karatzas,Steven E. Shreve +1 more
- 01 Jan 1998
TL;DR: In this paper, the authors explore questions of existence and uniqueness for solutions to stochastic differential equations and offer a study of their properties, using diffusion processes as a model of a Markov process with continuous sample paths.
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Lifetime Portfolio Selection By Dynamic Stochastic Programming
TL;DR: In this paper, the optimal consumption-investment problem for an investor whose utility for consumption over time is a discounted sum of single-period utilities, with the latter being constant over time and exhibiting constant relative risk aversion (power-law functions or logarithmic functions), is discussed.
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Diffusion Processes and their Sample Paths
Kiyosi Itô,Henry P. McKean +1 more
- 05 Jan 1996
TL;DR: In this article, the authors consider the problem of approximating the Brownian motion by a random walk with respect to the de Moivre-laplace limit theorem and show that it is NP-hard.
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Stochastic Stability and Control
Harold J. Kushner
- 17 Jan 2012
TL;DR: In this article, a book on stochastic stability and control dealing with Liapunov function approach to study of Markov processes is presented, which is based on the work of this article.
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