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We study multistep Bayesian betting strategies in coin-tossing games in the framework of game-theoretic probability of Shafer and Vovk (2001). We show that by a countable mixture of these strategies, a gambler or an investor can exploit…

Trading and Market Microstructure · Quantitative Finance 2010-08-23 Kei Takeuchi , Masayuki Kumon , Akimichi Takemura

We give a unified treatment of the convergence of random series and the rate of convergence of strong law of large numbers in the framework of game-theoretic probability of Shafer and Vovk (2001). We consider games with the quadratic hedge…

Probability · Mathematics 2011-11-23 Kenshi Miyabe , Akimichi Takemura

We study capital process behavior in the fair-coin game and biased-coin games in the framework of the game-theoretic probability of Shafer and Vovk (2001). We show that if Skeptic uses a Bayesian strategy with a beta prior, the capital…

Statistics Theory · Mathematics 2008-12-02 Masayuki Kumon , Akimichi Takemura , Kei Takeuchi

We study the behavior of the capital process of a continuous Bayesian mixture of fixed proportion betting strategies in the one-sided unbounded forecasting game in game-theoretic probability. We establish the relation between the rate of…

Probability · Mathematics 2018-05-08 Ryosuke Sato , Kenshi Miyabe , Akimichi Takemura

We introduce a new formulation of asset trading games in continuous time in the framework of the game-theoretic probability established by Shafer and Vovk (Probability and Finance: It's Only a Game! (2001) Wiley). In our formulation, the…

Trading and Market Microstructure · Quantitative Finance 2010-01-13 Kei Takeuchi , Masayuki Kumon , Akimichi Takemura

In this paper we propose an investing strategy based on neural network models combined with ideas from game-theoretic probability of Shafer and Vovk. Our proposed strategy uses parameter values of a neural network with the best performance…

Computational Finance · Quantitative Finance 2011-06-10 Ryo Adachi , Akimichi Takemura

In the framework of the game-theoretic probability of Shafer and Vovk (2001) it is of basic importance to construct an explicit strategy weakly forcing the strong law of large numbers (SLLN) in the bounded forecasting game. We present a…

Probability · Mathematics 2009-01-27 Masayuki Kumon , Akimichi Takemura

We propose a betting strategy based on Bayesian logistic regression modeling for the probability forecasting game in the framework of game-theoretic probability by Shafer and Vovk (2001). We prove some results concerning the strong law of…

Probability · Mathematics 2013-02-13 Masayuki Kumon , Jing Li , Akimichi Takemura , Kei Takeuchi

Game-theoretic upper expectations are joint (global) probability models that mathematically describe the behaviour of uncertain processes in terms of supermartingales; capital processes corresponding to available betting strategies.…

Probability · Mathematics 2021-07-14 Natan T'Joens , Jasper De Bock , Gert de Cooman

Conditional Value at Risk (CVaR) is widely used to account for the preferences of a risk-averse agent in the extreme loss scenarios. To study the effectiveness of randomization in interdiction games with an interdictor that is both risk and…

Computer Science and Game Theory · Computer Science 2020-03-19 Utsav Sadana , Erick Delage

Using the game-theoretic framework for probability, Vovk and Shafer. have shown that it is always possible, using randomization, to make sequential probability forecasts that pass any countable set of well-behaved statistical tests. This…

Machine Learning · Computer Science 2008-10-21 Vladimir V. V'yugin

We derive some results on contrarian and one-sided strategies by Skeptic for the fair-coin game in the framework of the game-theoretic probability of Shafer and Vovk \cite{sv}. In particular, concerning the rate of convergence of the strong…

Probability · Mathematics 2008-12-10 Yasunori Horikoshi , Akimichi Takemura

Recent advancements in algorithms for sequential decision-making under imperfect information have shown remarkable success in large games such as limit- and no-limit poker. These algorithms traditionally formalize the games using the…

Computer Science and Game Theory · Computer Science 2023-12-07 Vojtěch Kovařík , David Milec , Michal Šustr , Dominik Seitz , Viliam Lisý

We construct a diffusion approximation of a repeated game in which agents make bets on outcomes of i.i.d. random vectors and their strategies are close to an asymptotically optimal strategy. This model can be interpreted as trading in an…

Mathematical Finance · Quantitative Finance 2021-08-30 Mikhail Zhitlukhin

This paper studies a sequential decision problem where payoff distributions are known and where the riskiness of payoffs matters. Equivalently, it studies sequential choice from a repeated set of independent lotteries. The decision-maker is…

Theoretical Economics · Economics 2024-01-02 Zengjing Chen , Larry G. Epstein , Guodong Zhang

We consider a variant of sequential testing by betting where, at each time step, the statistician is presented with multiple data sources (arms) and obtains data by choosing one of the arms. We consider the composite global null hypothesis…

Methodology · Statistics 2026-03-19 Ricardo J. Sandoval , Ian Waudby-Smith , Michael I. Jordan

We consider discrete-time uncertain processes with finite state space and study the properties of game-theoretic upper expectations developed by Shafer and Vovk. We start by proving some basic properties, e.g. monotonicity, law of iterated…

Probability · Mathematics 2019-04-02 Natan T'Joens , Jasper De Bock , Gert de Cooman

We consider a dynamical approach to sequential games. By restricting the convertibility relation over strategy profiles, we obtain a semi-potential (in the sense of Kukushkin), and we show that in finite games the corresponding restriction…

Computer Science and Game Theory · Computer Science 2016-09-15 Stéphane Le Roux , Arno Pauly

This paper considers the problem of constructing a confidence sequence, which is a sequence of confidence intervals that hold uniformly over time, for estimating the mean of bounded real-valued random processes. This paper revisits the…

Probability · Mathematics 2024-08-27 J. Jon Ryu , Alankrita Bhatt

In this paper, we settle the sampling complexity of solving discounted two-player turn-based zero-sum stochastic games up to polylogarithmic factors. Given a stochastic game with discount factor $\gamma\in(0,1)$ we provide an algorithm that…

Machine Learning · Computer Science 2019-08-30 Aaron Sidford , Mengdi Wang , Lin F. Yang , Yinyu Ye
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