A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Paper proves game-theoretic and measure-theoretic expectations match for a specific financial scenario.
The paper explains the equity premium without probabilistic assumptions.
In this expository paper we illustrate the generality of game theoretic probability protocols of Shafer and Vovk (2001) in finite-horizon discrete games. By restricting ourselves to finite-horizon discrete games, we can explicitly describe how discrete distributions with finite support and the discrete pricing formulas…
The paper derives upper hedging prices for multivariate contingent claims using game-theoretic probability and submodularity.
We consider the game-theoretic scenario of testing the performance of Forecaster by Sceptic who gambles against the forecasts. Sceptic's current capital is interpreted as the amount of evidence he has found against Forecaster. Reporting the maximum of Sceptic's capital so far exaggerates the evidence. We characterize t…
This paper establishes a non-stochastic analogue of the celebrated result by Dubins and Schwarz about reduction of continuous martingales to Brownian motion via time change. We consider an idealized financial security with continuous price path, without making any stochastic assumptions. It is shown that typical price …
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 large numbers in the probability forecasting game with side information based on …
We give an overview of two approaches to probability theory where lower and upper probabilities, rather than probabilities, are used: Walley's behavioural theory of imprecise probabilities, and Shafer and Vovk's game-theoretic account of probability. We show that the two theories are more closely related than would be …
This work shows how evaluation metrics can be seen as fair gambles.
We give an exposition and numerical studies of upper hedging prices in multinomial models from the viewpoint of linear programming and the game-theoretic probability of Shafer and Vovk. We also show that, as the number of rounds goes to infinity, the upper hedging price of a European option converges to the solution of…
The paper explores game-theoretic alignment of LLMs with human preferences, finding limitations and conditions.
A new definition of events of game-theoretic probability zero in continuous time is proposed and used to prove results suggesting that trading in financial markets results in the emergence of properties usually associated with randomness. This paper concentrates on "qualitative" results, stated in terms of order (or or…
New algorithms compute Nash-equilibria in games with payoff distributions.
Motivated by the recent applications of game-theoretical learning techniques to the design of distributed control systems, we study a class of control problems that can be formulated as potential games with continuous action sets, and we propose an actor-critic reinforcement learning algorithm that provably converges t…
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 until the previous round (trading day) for deciding the investment in the curren…
Bayesian probability theory is one of the most successful frameworks to model reasoning under uncertainty. Its defining property is the interpretation of probabilities as degrees of belief in propositions about the state of the world relative to an inquiring subject. This essay examines the notion of subjectivity by dr…
Game-theoretic models predict asset prices in financial markets.
Paper compares fairness measures and feature importance measures using SHAP.
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 arbitrary patterns of deviations of nature's moves from independent Bernoulli trial…
Paper introduces metrics for evaluating multi-agent policies using best response dynamics.
Game-theoretic model captures investor interactions for stock price forecasting.
Novel segmentation method for energy game-theoretic frameworks using graphical lasso.
Proposes a game-theoretic framework to motivate energy-efficient behavior in smart buildings.
A game-theoretic framework identifies influential hyperparameters for neural networks.
Optimization models predict cryptocurrency market equilibria under government seizure risk.
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 law of large numbers (SLLN), we prove that Skeptic can force that the convergen…
In this article we consider a game theoretic approach to the Risk-Sensitive Benchmarked Asset Management problem (RSBAM) of Davis and Lleo \cite{DL}. In particular, we consider a stochastic differential game between two players, namely, the investor who has a power utility while the second player represents the market …
A game-theoretic approach for unsupervised domain adaptation.
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 market moves continuously, but an investor trades in discrete times, which can dep…
Paper proposes a game-theoretic approach to generate unlearnable examples.
GT-DDP optimizer trains residual networks using game theory.
Proposes a game-theoretic approach for class-dependent rationalization.
Paper applies NFSP to Mini-RTS, a small RTS game.
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 process is lucidly expressed in terms of the past average of Reality's moves. From t…
Modeling social conventions from real-time interactions and sensorimotor control.
Game-theoretic analysis of mining gaps in blockchain systems.
New method for evaluating LLMs reduces bias in open-ended evaluations.
DeepRole learns to play hidden role games like Avalon.
The paper improves dropout's utility by reducing interactions in deep neural networks.
This paper studies two important signal processing aspects of equilibrium behavior in non-cooperative games arising in social networks, namely, reinforcement learning and detection of equilibrium play. The first part of the paper presents a reinforcement learning (adaptive filtering) algorithm that facilitates learning…
Develops game theory framework for UAS integration into NAS.
The paper solves investment problems with uncertain factors using game theory.
Study shows market volatility arises from riskless opportunities not being available.
We solve a continuous-time game-theoretic problem for Kihlstrom-Mirman preferences.
The paper analyzes how mutable blockchain protocols affect miner behavior and strategic stability.
End-to-end model predicts multiagent trajectories using game theory and neural nets.
Paper analyzes adversarial attacks and defenses using game theory.
For a monotonically advancing front, the arrival time is the time when the front reaches a given point. We show that it is twice differentiable everywhere with uniformly bounded second derivative. It is smooth away from the critical points where the equation is degenerate. We also show that the critical set has finite …