Optimal trading strategy for an investor: the case of partial information
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TLDR
In this article, the drift process and the driving Brownian motion appearing in the stochastic differential equation for the security prices are not assumed to be observable for investors in the market.About:
This article is published in Stochastic Processes and their Applications.The article was published on 1998-08-01 and is currently open access. It has received 256 citations till now. The article focuses on the topics: Trading strategy & Expected utility hypothesis.read more
Citations
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The Role of Learning in Dynamic Portfolio Decisions
TL;DR: In this article, the authors analyzed the effect of uncertainty about the mean return on the risky asset on the portfolio decisions of an investor who has a long investment horizon and showed that the possibility of future learning induces the investor to take a larger or smaller position in a risky asset than she would if there were no learning, the direction of the effect depending on whether the investor is more or less risk tolerant than the logarithmic investor whose portfolio decisions are unaffected by the possibility.
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Optimizing the terminal wealth under partial information: The drift process as a continuous time Markov chain
Jörn Sass,Ulrich G. Haussmann +1 more
TL;DR: A multi-stock market model where prices satisfy a stochastic differential equation with instantaneous rates of return modeled as a continuous time Markov chain with finitely many states is considered.
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The relaxed investor and parameter uncertainty
TL;DR: An investor faced with the classical Merton problem of optimal investment in a log-Brownian asset and a fixed-interest bond, but constrained only to change portfolio choices at times which are a multiple of h is considered.
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A mean-field stochastic maximum principle via Malliavin calculus
TL;DR: In this article, the authors considered a mean-field type stochastic control problem where the dynamics is governed by a controlled Ito-Levy process and the information available to the controller is possibly less.
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Portfolio optimization with unobservable Markov-modulated drift process
Ulrich Rieder,Nicole Bäuerle +1 more
TL;DR: In this article, the authors study portfolio optimization problems in which the drift rate of the stock is Markov modulated and the driving factors cannot be observed by the investor, and prove a number of interesting properties of the optimal portfolio strategy.
References
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Brownian Motion and Stochastic Calculus
TL;DR: In this paper, the authors present a characterization of continuous local martingales with respect to Brownian motion in terms of Markov properties, including the strong Markov property, and a generalized version of the Ito rule.
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TL;DR: In this article, the authors propose a method for general stochastic integration and local times, which they call Stochastic Differential Equations (SDEs), and expand the expansion of Filtrations.
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TL;DR: In this paper, the optimal linear non-stationary filtering, interpolation and extrapolation of Partially Observable Random Processes with a Countable Number of States (POMOS) was studied.
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An intertemporal general equilibrium model of asset prices
TL;DR: In this paper, a continuous time general equilibrium model of a simple but complete economy is developed to examine the behavior of asset prices and their stochastic properties are determined endogenously, and the model is fully consistent with rational expectations and maximizing behavior on the part of all agents.