Article explains why gambling is crucial for market efficiency.
problem Inefficiency of traditional market theories.
method Introduces gambling theory as a superior approach.
result Gambling theory can reveal profitable trading systems.
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48 results for “gambling theory”
Understanding Gambling Behavior and Risk Attitudes Using Cryptocurrency-based Casino Blockchain Dataphysics.soc-ph
Study analyzes gambling behavior and risk attitudes using blockchain data.
problem Lack of real-life gambling data for validating predictions and experimental findings.
method Collects and analyzes betting data from a decentralized application on the Ethereum Blockchain.
result Empirical examples of gambling systems and insights into risk preferences.
Optimal exit strategies of CPT gamblers in unfair gambles
problem Optimal exit strategies of gamblers with CPT preferences in games with strictly negative expected payoffs
method Formulating the problem as an optimal stopping problem on asymmetric random walks, applying geometric transformation, randomized strategies, and changing the decision variable
result The unfair problem in the infinite time horizon has finite values for a wide range of CPT parameter specifications
A new theory explains financial markets using gambling and human decision-making.
problem No theory satisfies both practitioners and theorists for explaining market anomalies and exceptional returns.
method Combines gambling theory, human decision-making, and strategic problem-solving.
result Proposes a new theory (S SAFM) to explain financial market behavior.
Develops a model for gambling decisions under time inconsistency.
problem Time inconsistency in gambling decisions due to probability weighting in CPT.
method Formulates the problem as a mathematical program, derives optimal precommitted rule.
result Gambler may enter the casino even with limited play, behavior varies based on gains/losses.
PsychFM predicts individual gambling choices using psychological and machine learning models.
problem Predicting individual gambling choices with high precision.
method PsychFM combines machine learning and psychological theories.
result PsychFM outperforms existing models like random forest and factorization machines.
This paper examines limitations of Kelly Criterion in gambling.
problem Limitations of the Kelly Criterion in gambling.
method Provided specific examples and described research directions.
result Quantified difficulties with Taylor-style approximations and wealth drawdowns.
ETHGamDet detects crypto gambling contracts and addresses.
problem Identifying crypto gambling contracts and addresses.
method Multi-modal retrieval methods, LightGBM model with memory components.
result ETHGamDet achieves high F1-scores in address and contract classification.
Gambles are random variables that model possible changes in monetary wealth. Classic decision theory transforms money into utility through a utility function and defines the value of a gamble as the expectation value of utility changes. Utility functions aim to capture individual psychological characteristics, but thei…
We study the capital growth in gambling with (and without) side information and memory effects. We derive several equalities for gambling, which are of similar form to the Jarzynski equality and its extension to systems with feedback controls. Those relations provide us with new measures to quantify the effects of info…
Elasticity theory of structuringq-fin.GN
Financial derivatives have often been criticized as casino-style betting instruments. It turns out that many naive ways of making them are indeed equivalent to gambling. Fortunately, this inadvertent effect can be understood and prevented. We present a theory of product design which achieves that.
Study compares financial and gambling markets, finding similarities and potential applications.
problem Lack of comprehensive study on gambling markets compared to financial markets.
method Comprehensive comparison of five aspects: platform, product, procedure, participant, and strategy.
result Well-established financial strategies can be applied to gambling markets, particularly in peer-to-peer betting exchanges.
We introduce and discuss a nonlinear kinetic equation of Boltzmann type which describes the evolution of wealth in a pure gambling process, where the entire sum of wealths of two agents is up for gambling, and randomly shared between the agents. For this equation the analytical form of the steady states is found for va…
This work shows how evaluation metrics can be seen as fair gambles.
problem The relationship and evaluation of machine learning forecasts.
method Using game-theoretic probability, the authors show evaluation metrics as fair gambles.
result Standard evaluation metrics are fair gambler outcomes, with calibration and regret metrics on two dimensions.
Foster and Hart proposed an operational measure of riskiness for discrete random variables. We show that their defining equation has no solution for many common continuous distributions including many uniform distributions, e.g. We show how to extend consistently the definition of riskiness to continuous random variabl…
Researchers analyze betting odds and free coupons to find exploitable gains.
problem Determining if customers can exploit free coupons for guaranteed gains.
method Using desirability theory and the Choquet integral, they evaluate odds and free coupons.
result Customers can exploit free coupons for guaranteed gains under certain conditions.
It is well-known that there are a number of relations between theoretical finance theory and information theory. Some of these relations are exact and some are approximate. In this paper we will explore some of these relations and determine under which conditions the relations are exact. It turns out that portfolio the…
Gamblers lose in long bets despite casino claims, study shows.
problem Gamblers losing in seemingly fair gambling scenarios.
method Theoretical and experimental analysis of two-armed Futurity slot machines.
result Casinos have a win rate greater than 50% in long bets, making them unfair.
A method for selective classification using gambling-inspired loss function.
problem Achieving high performance while covering all data points.
method Transformed classification to selective classification problem, using portfolio theory-inspired loss function.
result Our method identifies uncertainty and achieves strong results on datasets.
Gambling in contests with regretq-fin.PM
This paper discusses the gambling contest introduced in Seel & Strack (Gambling in contests, Discussion Paper Series of SFB/TR 15 Governance and the Efficiency of Economic Systems 375, Mar 2012.) and considers the impact of adding a penalty associated with failure to follow a winning strategy. The Seel & Strack model c…
One index satisfies the duality axiom if one agent, who is uniformly more risk-averse than another, accepts a gamble, the latter accepts any less risky gamble under the index. Aumann and Serrano (2008) show that only one index defined for so-called gambles satisfies the duality and positive homogeneity axioms. We call …
The Labouchere system increases winning chances but exposes players to significant losses.
problem Improving odds of winning in gambling systems with 1:1 payouts.
method Simulated millions of rounds of Labouchere gambling sequence to analyze outcomes.
result As the number of bets increases, the system's outcomes approach zero.
This paper optimizes sports betting strategies using neural networks and portfolio theory.
problem Optimizing betting strategies in sports gambling.
method Combining neural network models with portfolio optimization, integrating Von Neumann-Morgenstern Expected Utility Theory and the Kelly Criterion.
result Achieved 135.8% relative profit during the English Premier League season.
Risk-Constrained Kelly Gamblingq-fin.PM
We consider the classic Kelly gambling problem with general distribution of outcomes, and an additional risk constraint that limits the probability of a drawdown of wealth to a given undesirable level. We develop a bound on the drawdown probability; using this bound instead of the original risk constraint yields a conv…
New strategy for gambling with changing environments achieves sub-linear regret.
problem Optimizing rewards in a non-stationary -armed bandit problem.
method Proposes a novel strategy for environments that change behavior abruptly.
result Proves the proposed strategy attains sub-linear cumulative regret.
We introduce a near-linear complexity (geometric and meshless/algebraic) multigrid/multiresolution method for PDEs with rough () coefficients with rigorous a-priori accuracy and performance estimates. The method is discovered through a decision/game theory formulation of the problems of (1) identifying restri…
Risk aversion in economic transactionscond-mat.stat-mech
Most people are risk-averse (risk-seeking) when they expect to gain (lose). Based on a generalization of ``expected utility theory'' which takes this into account, we introduce an automaton mimicking the dynamics of economic operations. Each operator is characterized by a parameter q which gauges people's attitude unde…
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…
Paper analyzes U.S. broker call rate laws of motion and their implications.
problem Understanding the dynamics and pricing of margin loans in the U.S. market.
method Analysis of monthly observations, derivation of stochastic differential equations, application of arbitrage theory.
result Margin loan interest rate follows mean-reverting behavior, with total call loan volume constituting over 70% of leveraged portfolios.
Neilson's Weak vs. Strong Loss Aversion: A Characterization and a Generalized CPT-Utility Functionq-fin.MF
This paper analyzes risk perception and aversion in decision-making.
problem Understanding and quantifying risk perception and aversion in decision-making.
method Theoretical analysis and generalized CPT-utility function development.
result A generalized CPT-utility function that captures risk perception and aversion.
We present a universal algorithm for online trading in Stock Market which performs asymptotically at least as good as any stationary trading strategy that computes the investment at each step using a fixed function of the side information that belongs to a given RKHS (Reproducing Kernel Hilbert Space). Using a universa…
This paper formulates and studies a general continuous-time behavioral portfolio selection model under Kahneman and Tversky's (cumulative) prospect theory, featuring S-shaped utility (value) functions and probability distortions. Unlike the conventional expected utility maximization model, such a behavioral model could…
The normalized maximized likelihood (NML) provides the minimax regret solution in universal data compression, gambling, and prediction, and it plays an essential role in the minimum description length (MDL) method of statistical modeling and estimation. Here we show that the normalized maximum likelihood has a Bayes-li…
Myopic investors make suboptimal choices that benefit others, leading to market inefficiencies.
problem Myopic investors make suboptimal decisions that lag the market.
method Constrained optimisation and overlapping examples of different investor types.
result Myopic investors' suboptimal choices lead to market inefficiencies and profit opportunities for others.
New bounds derived using conditional -information for machine learning models.
problem Improving generalization bounds in machine learning.
method Introducing novel information-theoretic generalization bounds via conditional -information.
result Derives generalization bounds applicable to both bounded and unbounded loss functions.
The link between different psychophysiological measures during emotion episodes is not well understood. To analyse the functional relationship between electroencephalography (EEG) and facial electromyography (EMG), we apply historical function-on-function regression models to EEG and EMG data that were simultaneously r…
The Kelly betting theory can sometimes lead to overly conservative bets.
problem Kelly betting can be too conservative in some cases.
method The authors use empirical data and theoretical distribution to compare Kelly bets, identifying cases where theoretical bets are much smaller than empirical bets.
result Theoretical Kelly bets can lead to no betting at all when the distribution is unbounded.
Investing is a compression problem, maximizing growth by minimizing divergence.
problem Maximizing long-term wealth and minimizing risk of ruin in investing.
method Decomposes investing into three terms: money, entropy, and divergence. Uses Kelly Criterion and universal portfolio theory.
result Investing can be seen as a compression problem, with optimal strategies minimizing divergence.
Cricket betting is a multi-billion dollar market. Therefore, there is a strong incentive for models that can predict the outcomes of games and beat the odds provided by bookers. The aim of this study was to investigate to what degree it is possible to predict the outcome of cricket matches. The target competition was t…
An explicit solution for an optimal stopping/optimal control problem which models an asset saleq-fin.PM
In this article we study an optimal stopping/optimal control problem which models the decision facing a risk-averse agent over when to sell an asset. The market is incomplete so that the asset exposure cannot be hedged. In addition to the decision over when to sell, the agent has to choose a control strategy which corr…
Tontines were once a popular type of mortality-linked investment pool. They promised enormous rewards to the last survivors at the expense of those died early. And, while this design appealed to the gambling instinc}, it is a suboptimal way to generate retirement income. Indeed, actuarially-fair life annuities making c…
A two-stream reinforcement learning model improves decision-making across human and neuropsychiatric studies.
problem Improving reinforcement learning models to better simulate human decision-making and neuropsychiatric conditions.
method Proposes a two-stream reinforcement learning model that processes positive and negative rewards and incorporates reward-processing biases.
result The two-stream model outperforms standard Q-learning and SARSA methods on various tasks and datasets.
Exploiting oddsmaker biases improves NFL game outcome predictions.
problem Accurately predicting NFL game outcomes is challenging due to dynamic factors and biases.
method Used real-world gambling data to train and test predictive models leveraging oddsmaker biases.
result Methods exploiting oddsmaker biases perform best in predicting NFL game outcomes.
New tontine model with transaction costs for retirees.
problem Maximizing consumption and bequest utilities for retirees.
method Formulated as a stochastic and impulse control problem, characterized by viscosity solutions.
result V-shaped transaction region with two stages: smoothing and gambling.
Unified framework for human-like decision making in various sequential tasks.
problem Real-life decision-making involves diverse strategies leading to similar outcomes.
method Two-stream reward processing mechanism for flexible and unified models.
result Framework unified MAB, CB, and RL with comparable performance.
Be Water: An Evolutionary Proof for Trend-Followingphysics.soc-ph
Trend-following strategies outperform in a noisy financial market, mirroring ancient wisdom.
problem Navigating the complex, noisy financial market environment.
method Agent-based model with 10,000 agents representing different trading strategies.
result Trend-following strategies are structurally more robust than mean-reversion strategies.
Paper proposes new features to improve Bitcoin address classification.
problem Identifying criminal activities in Bitcoin transactions.
method New features based on transaction history summarized by block height.
result Improved performance of Bitcoin address classification significantly.
Optimal margin loan agreements for sophisticated gamblers and brokers.
problem Finding fair interest rates and loan sizes between gamblers and brokers.
method Derives formulas for optimal arrangements based on gamblers' risk preferences and market conditions.
result Gambler gains higher capital growth with lower interest rates, broker gains intermediary profit.