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We consider two-player stochastic games played on a finite graph for infinitely many rounds. Stochastic games generalize both Markov decision processes (MDP) by adding an adversary player, and two-player deterministic games by adding…

Computer Science and Game Theory · Computer Science 2022-02-28 Laurent Doyen

The present paper provides a study of high-dimensional statistical arbitrage that combines factor models with the tools from stochastic control, obtaining closed-form optimal strategies which are both interpretable and computationally…

Mathematical Finance · Quantitative Finance 2021-06-25 Jorge Guijarro-Ordonez

Many problems in quantum information theory can be formulated as optimizations over the sequential outcomes of dynamical systems subject to unpredictable external influences. Such problems include many-body entanglement detection through…

Quantum Physics · Physics 2024-06-07 Mirjam Weilenmann , Costantino Budroni , Miguel Navascues

This paper investigates the investment problem of constructing an optimal no-short sequential portfolio strategy in a market with a latent dependence structure between asset prices and partly unobservable side information, which is often…

Mathematical Finance · Quantitative Finance 2025-01-22 Duy Khanh Lam

The paper investigates the long-time behavior of zero-sum linear-quadratic stochastic differential games, aiming to demonstrate that, under appropriate conditions, both the saddle strategy and the optimal state process exhibit the…

Optimization and Control · Mathematics 2024-06-05 Jingrui Sun , Jiongmin Yong

Kolmogorovs axiomatic framework is the best-known approach to describing probabilities and, due to its use of the Lebesgue integral, leads to remarkably strong continuity properties. However, it relies on the specification of a probability…

Probability · Mathematics 2018-06-11 Natan T'Joens , Gert de Cooman , Jasper De Bock

A confidence sequence (CS) is a sequence of confidence sets that contains a target parameter of an underlying stochastic process at any time step with high probability. This paper proposes a new approach to constructing CSs for means of…

Methodology · Statistics 2024-08-22 J. Jon Ryu , Gregory W. Wornell

We study sequential prediction of real-valued, arbitrary and unknown sequences under the squared error loss as well as the best parametric predictor out of a large, continuous class of predictors. Inspired by recent results from…

Machine Learning · Computer Science 2014-01-24 N. Denizcan Vanli , Suleyman S. Kozat

We study synchronous values of games, especially synchronous games. It is known that a synchronous game has a perfect strategy if and only if it has a perfect synchronous strategy. However, we give examples of synchronous games, in…

We consider games of chance played by someone with external capital that cannot be applied to the game and determine how this affects risk-adjusted optimal betting. Specifically, we focus on Kelly optimization as a metric, optimizing the…

Portfolio Management · Quantitative Finance 2020-12-29 Stanislav Shalunov , Alexei Kitaev , Yakov Shalunov , Arseniy Akopyan

This paper investigates the application of game-theoretic principles combined with advanced Kalman filtering techniques to enhance maritime target tracking systems. Specifically, the paper presents a two-player, imperfect information,…

Computer Science and Game Theory · Computer Science 2024-10-18 Daniel Leal , Ngoc Hung Nguyen , Alex Skvortsov , Sanjeev Arulampalam , Mahendra Piraveenan

A sequential quadratic programming method is designed for solving general smooth nonlinear stochastic optimization problems subject to expectation equality constraints. We consider the setting where the objective and constraint function…

Optimization and Control · Mathematics 2026-03-17 Haoming Shen , Yang Zeng , Baoyu Zhou

For a sequence of binary bets, the Kelly criterion provides a closed-form solution that maximizes the expected growth rate of wealth. In contrast, when multiple bets are placed simultaneously (e.g., in portfolio allocation or prediction…

Mathematical Finance · Quantitative Finance 2026-04-30 Ruslan Tepelyan , Daniel Lam

In games with a large number of players where players may have overlapping objectives, the analysis of stable outcomes typically depends on player types. A special case is when a large part of the player population consists of imitation…

Computer Science and Game Theory · Computer Science 2010-06-18 Soumya Paul , R. Ramanujam

This paper explores a predictive game in which a Forecaster announces odds based on a time-homogeneous Markov kernel, establishing a game-theoretic law of large numbers for the relative frequencies of occurrences of all finite strings. A…

Information Theory · Computer Science 2025-02-05 Takara Nomura , Akio Fujiwara

We consider strong law of large numbers (SLLN) in the framework of game-theoretic probability of Shafer and Vovk (2001). We prove several versions of SLLN for the case that Reality's moves are unbounded. Our game-theoretic versions of SLLN…

Probability · Mathematics 2007-08-27 Masayuki Kumon , Akimichi Takemura , Kei Takeuchi

We present a robust framework with computational algorithms to support decision makers in sequential games. Our framework includes methods to solve games with complete information, assess the robustness of such solutions and, finally,…

Computation · Statistics 2024-02-22 Tahir Ekin , Roi Naveiro , Alberto Torres-Barrán , David Ríos-Insua

While the Kelly portfolio has many desirable properties, including optimal long-term growth rate, the resulting investment strategy is rather aggressive. In this paper, we suggest a unified approach to the risk assessment of the Kelly…

Risk Management · Quantitative Finance 2025-03-25 Levon Hakobyan , Sergey Lototsky

We derive formulas for the performance of capital assets in continuous time from an efficient market hypothesis, with no stochastic assumptions and no assumptions about the beliefs or preferences of investors. Our efficient market…

Pricing of Securities · Quantitative Finance 2018-02-06 Vladimir Vovk , Glenn Shafer

In this paper, we consider the problem of optimization and learning for constrained and multi-objective Markov decision processes, for both discounted rewards and expected average rewards. We formulate the problems as zero-sum games where…

Optimization and Control · Mathematics 2021-03-05 Ather Gattami , Qinbo Bai , Vaneet Agarwal