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arXiv research

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.

168,657 papers · 148 categories

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118235353470 · Jun 202019922001200920172026
48 results for Contraction Analysis

Predicts short-term futures contract direction using neural networks and order flow data.

problem Challenges in predicting short-term directional movement of futures contracts.
method Engineering features from technical analysis, order flow, and order-book data; training a Tabnet neural network.
result Achieved an accuracy of 0.601 in predicting directional change on the Silver Futures Contract.

Lyapunov's second theorem is an essential tool for stability analysis of differential equations. The paper provides an analog theorem for incremental stability analysis by lifting the Lyapunov function to the tangent bundle. The Lyapunov function endows the state-space with a Finsler structure. Incremental stability is…

2012-08-14abs ↗pdf ↗

Study develops a smart contract framework for efficient and fair resource allocation.

problem Lack of rigorous economic foundation in decentralized coordination and smart contract implementations.
method Mechanism design framework with provable convergence guarantees for decentralized price adjustment.
result Proves stability and robustness of the proposed mechanism under various perturbations.

Fair insurance contracts are designed to handle default risk using cooperative game theory.

problem Designing fair insurance contracts in the presence of default risk.
method Cooperative game theory to specify premiums and participation in benefit.
result Fair benefit participation emerges as a game outcome involving residual risks.

The main purpose of this paper is to formalize the modelling process, analysis and mathematical definition of corruption when entering into a contract between principal agent and producers. The formulation of the problem and the definition of concepts for the general case are considered. For definiteness, all calculati…

2018-04-06abs ↗pdf ↗

We analyze conditional optimization problems arising in discrete time Principal-Agent problems of delegated portfolio optimization with linear contracts. Applying tools from Conditional Analysis we show that some results known in the literature for very specific instances of the problem carry over to translation invari…

2014-12-15abs ↗pdf ↗

New bounds for SA with arbitrary norm contractions and Markovian noise.

problem Finite-time analysis of two-time-scale stochastic approximation with arbitrary norm contractions and Markovian noise.
method Use of generalized Moreau envelope for arbitrary norm contractions and solutions of Poisson equation for Markovian noise.
result Mean square error decays at rates of O(1/n2/3)O(1/n^{2/3}) and O(1/n)O(1/n) under different conditions.

The paper analyzes game theory in convertible contracts during liquidity events.

problem Optimizing payments in convertible contracts during liquidity events.
method Defined a general model for games, showed non-existence of pure strategy Nash equilibria, developed algorithms for computing equilibria.
result Optimum pure strategy Nash equilibria exist when all contracts are of the same type (SAFE).

The paper analyzes optimal investment strategies for life insurance contracts using mean-variance optimization.

problem Optimal portfolio choice for equity holders in life insurance contracts.
method Mean-variance optimization, explicit formulas, Hamilton-Jacobi-Bellman equations, numerical analysis.
result Equity holders increase investment in risky assets during economic downturns.

Proposes a regularization approach to model German power derivative market, identifying significant risk spillovers.

problem Large portfolio of German power derivative contracts, identifying significant risk spillovers.
method Combines high-dimensional variable selection with dynamic network analysis.
result Identifies significant risk contributors and interdependencies between contracts, especially spot contracts.

The paper uses neural networks to price complex life insurance contracts with multiple risk factors.

problem Pricing equity-linked life insurance contracts with various stochastic risk factors.
method Assuming hedging to reduce local variance, the price is expressed as a system of non-linear PDEs. Reformulated as a backward SDE with jumps, solved numerically using neural networks.
result Neural networks provide an efficient numerical solution for pricing these complex contracts.

Bayesian neural networks achieve optimal posterior contraction rates in Besov spaces with intrinsic dimensionality.

problem High-dimensional structured estimation problems with unknown smoothness levels.
method Sparse Bayesian neural networks with either sparse or continuous shrinkage priors.
result Optimal posterior contraction rates are achieved, adapting to the unknown smoothness level of the true function.

Convergence of the Kalman filter is best analyzed by studying the contraction of the Riccati map in the space of positive definite (covariance) matrices. In this paper, we explore how this contraction property relates to a more fundamental non-expansiveness property of filtering maps in the space of probability distrib…

2015-03-31abs ↗pdf ↗

New Q-learning method achieves optimal sample complexity for average-reward problems.

problem Challenges in achieving optimal sample complexity for average-reward Q-learning.
method Synchronous and asynchronous Q-learning with a new contraction principle.
result Optimal O~(ε2)\widetilde{O}(\varepsilon^{-2}) sample complexity guarantees.

We analyze reinforcement learning algorithms using a distributional approach.

problem Theoretical analysis of reinforcement learning algorithms for constant step-sizes.
method Distributional approach to theoretical analyses of reinforcement learning algorithms.
result TD(λλ) and QQ-Learning have contractive update rules in the space of distributions of functions, leading to exponentially fast convergence.

We introduce a two-agent problem which is inspired by price asymmetry arising from funding difference. When two parties have different funding rates, the two parties deduce different fair prices for derivative contracts even under the same pricing methodology and parameters. Thus, the two parties should enter the deriv…

2019-01-12abs ↗pdf ↗

Bayesian KANs achieve near-minimax posterior contraction rates in anisotropic Besov spaces.

problem Statistical foundation for Bayesian Kolmogorov-Arnold networks in anisotropic Besov spaces.
method Sparse Bayesian KANs with spike-and-slab priors, hyperprior on model size, and approximation complexity bounds.
result Posterior contraction rates depend on intrinsic anisotropic smoothness and effective dimension of the compositional structure.

The paper analyzes reinsurance strategies in peer-to-peer insurance schemes.

problem Strategic interaction between plan managers and reinsurers in P2P insurance.
method Develops two game-theoretic contract designs: Pareto and Bowley designs, deriving optimal contracts and analyzing their welfare effects.
result The Bowley design yields a unique optimal contract, while the Pareto design allows for multiple Pareto-optimal contracts.

Study optimizes smart contract adoption under high demand variability using Negative Binomial models.

problem Effective supply chain management under high demand variability.
method Combines dynamic Negative Binomial demand modeling with endogenous smart contract adoption optimization.
result The NB model outperforms other benchmarks in forecasting and optimizing smart contract adoption and order quantity.

A large collection of financial contracts offering guaranteed minimum benefits are often posed as control problems, in which at any point in the solution domain, a control is able to take any one of an uncountable number of values from the admissible set. Often, such contracts specify that the holder exert control at a…

2015-02-19abs ↗pdf ↗

This study examines lead-lag relationships in Chinese futures markets using high-frequency data.

problem Understanding high-frequency trading dynamics and information flow in futures markets.
method High-frequency tick-by-tick data analysis of lead-lag relationships between different maturity futures contracts.
result The near-month futures lead longer-dated contracts by one tick, with a negative feedback effect on the leading asset.

Unified framework for solving fixed-point equations in deterministic and stochastic settings.

problem Solving fixed-point equations for seminorm-contractive operators in both deterministic and stochastic contexts.
method Fixed-point theorem and stochastic approximation analysis.
result Unified finite-sample bounds for various reinforcement learning algorithms.

Bayesian analysis shows unlabeled data improve graph-based semi-supervised learning.

problem Improving semi-supervised learning with limited labeled data.
method Bayesian nonparametric approach using unlabeled data for graph-based learning.
result Posterior contracts optimally around the truth with sufficient unlabeled data.

The paper explores coalescent contractions in contractible spaces, providing criteria and examples.

problem Existence and absence of coalescent contractions in contractible spaces.
method Analysis of contractible finite simplicial complexes and criteria for coalescent contractions.
result Criteria for contractible finite simplicial complexes that ensure no coalescent contractions.

Study examines risk premium convergence rates in risk sharing contracts.

problem Analyzing risk premium convergence rates in risk sharing contracts.
method Examines the limiting behavior of risk premium associated with Pareto optimal risk sharing contracts under general law-invariant risk measures.
result Risk premium convergence rate is typically n1/2n^{1/2}, not nn.

With the inflation of the data, clustering analysis, as a branch of unsupervised learning, lacks unified understanding and application of its mathematical law. Based on the view of fixed point, this paper restates the model-based clustering and proposes a unified clustering framework. In order to find fixed points as c…

2020-02-19abs ↗pdf ↗

The paper analyzes distributed Bayesian inference and its Frequentist guarantees.

problem Analyzing large decentralized datasets with distributed Bayesian inference.
method Establishes Frequentist properties for distributed (non-)Bayesian inference.
result Distributed Bayesian inference retains parametric efficiency and enhances robustness.

In an online contract selection problem there is a seller which offers a set of contracts to sequentially arriving buyers whose types are drawn from an unknown distribution. If there exists a profitable contract for the buyer in the offered set, i.e., a contract with payoff higher than the payoff of not accepting any c…

2013-05-15abs ↗pdf ↗

Optimal execution strategy for merger & acquisition contracts with price impact.

problem Optimal execution and pricing of financial derivatives in M&A deals.
method Indifference utility arguments, considering linear and nonlinear contracts.
result Linear contracts are more expensive and vulnerable to manipulation.