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.
New algorithm closes empirical gap in PFSGD performance.
Paper tightens PAC-Bayes bounds using coin-betting for better estimates.
New algorithms learn latent variable models without tuning, outperforming existing methods.
Deep learning methods achieve state-of-the-art performance in many application scenarios. Yet, these methods require a significant amount of hyperparameters tuning in order to achieve the best results. In particular, tuning the learning rates in the stochastic optimization process is still one of the main bottlenecks. …
New algorithms for sampling in constrained domains without learning rates.
What would you do if you were invited to play a game where you were given \$25 and allowed to place bets for 30 minutes on a coin that you were told was biased to come up heads 60% of the time? This is exactly what we did, gathering 61 young, quantitatively trained men and women to play this game. The results, in a nut…
New coin sampling method for Bayesian inference without learning rates.
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…
This paper explores using nonlinear control for robust logarithmic growth in coin flipping games.
A key challenge in online learning is that classical algorithms can be slow to adapt to changing environments. Recent studies have proposed "meta" algorithms that convert any online learning algorithm to one that is adaptive to changing environments, where the adaptivity is analyzed in a quantity called the strongly-ad…
This paper describes a new parameter-free online learning algorithm for changing environments. In comparing against algorithms with the same time complexity as ours, we obtain a strongly adaptive regret bound that is a factor of at least better, where is the time horizon. Empirical results show tha…
The Labouchere gambling system is hypothesized to increase the probability of winning a predetermined arbitrary profit in a gambling system such as a coin flip or a roulette game in which both payouts and odds are 1:1. However, use of the system increases the downside monetary risk in the event of a streak of multiple …
The Kelly Criterion is applied to prediction markets to analyze risk and return.
We study a coin-tossing model used by a ratings agency to justify the sale of constant proportion debt obligations (CPDOs), and prove that it was impossible for CPDOs to achieve in a finite lifetime the Cash-In event of doubling its capital. In the best-case scenario of a two-headed coin, we show that the goal of attai…
New algorithm reduces privacy loss in SGD without learning rate tuning.
Inefficient markets allow investors to consistently outperform the market. To demonstrate that inefficiencies exist in sports betting markets, we created a betting algorithm that generates above market returns for the NFL, NBA, NCAAF, NCAAB, and WNBA betting markets. To formulate our betting strategy, we collected and …
Law of iterated logarithm derived from betting strategy.
Kelly betting is a prescription for optimal resource allocation among a set of gambles which are typically repeated in an independent and identically distributed manner. In this setting, there is a large body of literature which includes arguments that the theory often leads to bets which are "too aggressive" with resp…
BBE simulates sports betting exchanges for data generation.
RIVCoin stabilizes cryptocurrency portfolios through a DAO and redistributes income.
BBE simulates betting exchanges to generate synthetic data for AI research.
Modeling horse race betting odds with Ornstein-Uhlenbeck process.
In the UK betting market, bookmakers often offer a free coupon to new customers. These free coupons allow the customer to place extra bets, at lower risk, in combination with the usual betting odds. We are interested in whether a customer can exploit these free coupons in order to make a sure gain, and if so, how the c…
New Bitcoin coin selection method improves cost savings.
We propose a novel "tree-averaging" model that utilizes the ensemble of classification and regression trees (CART). Each constituent tree is estimated with a subset of similar data. We treat this grouping of subsets as Bayesian ensemble trees (BET) and model them as an infinite mixture Dirichlet process. We show that B…
Bitcoin draws the highest degree of attention among cryptocurrencies, while coin mining is one of the most important fashion of profiting in the Bitcoin ecosystem. This paper constructs fresh coin circulation networks by tracking the fresh coin transfer routes with transaction referencing in Bitcoin blockchain. This pa…
This paper optimizes sports betting strategies using neural networks and portfolio theory.
Paper approximates Kelly betting for wealth growth.
New betting strategy reduces regret to ln(ln n) with protection against adversarial data.
Gamblers lose in long bets despite casino claims, study shows.
We introduce an evolutionary game with feedback between perception and reality, which we call the reality game. It is a game of chance in which the probabilities for different objective outcomes (e.g., heads or tails in a coin toss) depend on the amount wagered on those outcomes. By varying the `reality map', which rel…
We introduce a general framework for continuous-time betting markets, in which a bookmaker can dynamically control the prices of bets on outcomes of random events. In turn, the prices set by the bookmaker affect the rate or intensity of bets placed by gamblers. The bookmaker seeks a price process that maximizes his exp…
Testing-by-betting strategies almost surely go bankrupt under null hypotheses.
The betting CI outperforms classical methods in constructing confidence intervals for bounded means.
Enhanced ICM ensemble detects concept drift better with novel betting functions.
Extends Kelly Criterion to more complex betting scenarios.
Study proposes new methods to convert betting odds into accurate probabilities for sports forecasting.
Study reveals strong price correlations between major and alt-coins.
PEAK tests means of multiple data streams with sequential betting.
Sequential tests for two-sample and independence testing using betting strategies.
New bounds derived using conditional -information for machine learning models.
A quantum memory model for Kelly betting with amplified or attenuated outcomes.
The study shows how probability weighting can lead to betting in a risk-averse economy.
We consider the problem of unconstrained online convex optimization (OCO) with sub-exponential noise, a strictly more general problem than the standard OCO. In this setting, the learner receives a subgradient of the loss functions corrupted by sub-exponential noise and strives to achieve optimal regret guarantee, witho…
Investigates sports betting strategies using modern portfolio theory and Kelly criterion.
This work examines the effects of allowing borrowing in betting-based hypothesis testing.
We develop a model of how information flows into a market, and derive algorithms for automatically detecting and explaining relevant events. We analyze data from twenty-two "political stock markets" (i.e., betting markets on political outcomes) on the Iowa Electronic Market (IEM). We prove that, under certain efficienc…
Study compares financial and gambling markets, finding similarities and potential applications.