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We study a dynamic mean-variance portfolio optimization problem under the reinforcement learning framework, where an entropy regularizer is introduced to induce exploration. Due to the time-inconsistency involved in a mean-variance criterion, we aim to learn an equilibrium strategy. Under an...
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-- Principle VI: Superposition -- Principle VII: Game Theory -- Chapter 4: The Secret History of Wall Street: 1654-1982 -- Pascal … -- Chapter 5: When Harry Met Kelly -- Kelly -- Harry -- Commodity Futures -- If Harry Knew Kelly -- Investment Growth Theory … Money: The Future -- Farmers and Millers -- Money, New and Improved -- A General Theory of Money -- Value and Money …
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This paper studies the mean-variance portfolio selection under the assumption that the market state is modulated by a hidden Markov chain which is unobservable to investors. We employ a game-theoretic formulation to address the time-inconsistency arising in mean-variance analysis for portfolio...
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We study a multi-player stochastic differential game, where agents interact through their joint price impact on an asset that they trade to exploit a common trading signal. In this context, we prove that a closed-loop Nash equilibrium exists if the price impact parameter is small enough....
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We adapt a deterministic game theoretic framework in discrete time to super-hedge pricing contingent claims (CCs). The key aspect of this framework is that the worst-case scenario dictates the super-hedging price which protects counter-parties in financial contracts from insolvencies. A general...
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of population games as studied in evolutionary game theory. Consequently, evolutionary dynamics that have been designed …
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This paper characterizes the optimal risk-taking strategies of mutual fund managers competing in multi-period winner-take-all tournaments. With competition among mutual funds, every fund begins by taking maximum risk. In the final period, all funds continue to take maximum risk except possibly...
Persistent link: https://www.econbiz.de/10012940253