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The games of prediction with expert advice are considered in this paper. We present some modification of Kalai and Vempala algorithm of following the perturbed leader for the case of unrestrictedly large one-step gains. We show that in…

Machine Learning · Computer Science 2008-06-30 Vladimir V. V'yugin

This paper studies a two-person trading game in continuous time that generalizes Garivaltis (2018) to allow for stock prices that both jump and diffuse. Analogous to Bell and Cover (1988) in discrete time, the players start by choosing fair…

General Economics · Economics 2022-10-24 Alex Garivaltis

The rating of items based on pairwise comparisons has been a topic of statistical investigation for many decades. Numerous approaches have been proposed. One of the best known is the Bradley-Terry model. This paper seeks to assemble and…

Statistics Theory · Mathematics 2025-08-08 Ian Hamilton , Nick Tawn , David Firth

We investigate the use of Kelly's strategy in the construction of an optimal portfolio of assets. For lognormally distributed asset returns, we derive approximate analytical results for the optimal investment fractions in various settings.…

Portfolio Management · Quantitative Finance 2011-04-08 Paolo Laureti , Matus Medo , Yi-Cheng Zhang

In this work, Bernoulli's Law of Large Numbers, also known as the Golden theorem, has been extended to study the relations between empirical probability and empirical randomness of an otherwise random experiment. Using the example of a coin…

Data Analysis, Statistics and Probability · Physics 2025-06-04 Allen Lobo , Saravanan Arumugam

Our main goal is to study a class of processes whose increments are generated via a cellular automata rule. Given the increments of a simple biased random walk, a new sequence of (dependent) Bernoulli random variables is produced. It is…

Probability · Mathematics 2017-10-24 Andrea Collevecchio , Kais Hamza , Yunxuan Liu

Work in machine learning and statistics commonly focuses on building models that capture the vast majority of data, possibly ignoring a segment of the population as outliers. However, there does not often exist a good model on the whole…

Machine Learning · Computer Science 2019-07-11 Diego Calderon , Brendan Juba , Sirui Li , Zongyi Li , Lisa Ruan

This paper presents a wp-style calculus for obtaining expectations on the outcomes of (mutually) recursive probabilistic programs. We provide several proof rules to derive one-- and two--sided bounds for such expectations, and show the…

Logic in Computer Science · Computer Science 2016-03-10 Federico Olmedo , Benjamin Lucien Kaminski , Joost-Pieter Katoen , Christoph Matheja

This paper presents a novel approach for optimizing betting strategies in sports gambling by integrating Von Neumann-Morgenstern Expected Utility Theory, deep learning techniques, and advanced formulations of the Kelly Criterion. By…

Portfolio Management · Quantitative Finance 2023-07-27 Vélez Jiménez , Román Alberto , Lecuanda Ontiveros , José Manuel , Edgar Possani

Estimating the parameter of a Bernoulli process arises in many applications, including photon-efficient active imaging where each illumination period is regarded as a single Bernoulli trial. Motivated by acquisition efficiency when multiple…

Applications · Statistics 2026-03-12 Safa C. Medin , John Murray-Bruce , David Castañón , Vivek K Goyal

Quantum Decision Theory, advanced earlier by the authors, and illustrated for lotteries with gains, is generalized to the games containing lotteries with gains as well as losses. The mathematical structure of the approach is based on the…

Physics and Society · Physics 2018-02-20 V. I. Yukalov , D. Sornette

The Elo rating system is a highly successful ranking algorithm for games of skill where, by construction, one team wins and the other loses. A primary limitation of the original Elo algorithm is its inability to predict information beyond a…

Methodology · Statistics 2018-02-05 J. Scott Moreland , Matthew C. Superdock

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

The Lindy effect is a statistical tendency for things with longer pasts behind them to have longer futures ahead. It has been experimentally confirmed to apply to some categories, but not others, raising questions about when it is…

Physics and Society · Physics 2023-08-21 Toby Ord

We shall show in this paper that there are experiments which are Bernoulli trials with success probability p > 0.5, and which have the curious feature that it is possible to correctly predict the outcome with probability > p.

Other Statistics · Statistics 2018-01-09 James D. Stein

We study the problems of sequential nonparametric two-sample and independence testing. Sequential tests process data online and allow using observed data to decide whether to stop and reject the null hypothesis or to collect more data,…

Machine Learning · Statistics 2023-07-21 Aleksandr Podkopaev , Aaditya Ramdas

The notion of belief likelihood function of repeated trials is introduced, whenever the uncertainty for individual trials is encoded by a belief measure (a finite random set). This generalises the traditional likelihood function, and…

Statistics Theory · Mathematics 2018-08-21 Fabio Cuzzolin

We consider a random trial-based telegraph process, which describes a motion on the real line with two constant velocities along opposite directions. At each epoch of the underlying counting process the new velocity is determined by the…

Probability · Mathematics 2013-12-17 Irene Crimaldi , Antonio Di Crescenzo , Antonella Iuliano , Barbara Martinucci

Rigorous guarantees about the performance of predictive algorithms are necessary in order to ensure their responsible use. Previous work has largely focused on bounding the expected loss of a predictor, but this is not sufficient in many…

Machine Learning · Computer Science 2022-12-29 Jake C. Snell , Thomas P. Zollo , Zhun Deng , Toniann Pitassi , Richard Zemel

In many predictive decision-making scenarios, such as credit scoring and academic testing, a decision-maker must construct a model that accounts for agents' propensity to "game" the decision rule by changing their features so as to receive…

Machine Learning · Computer Science 2022-08-26 Yonadav Shavit , Benjamin Edelman , Brian Axelrod
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