Latest Articles for Finance

TimeAutoDiff offers new solutions for creating realistic synthetic time series data.

A new method enhances covariance estimation in Gaussian processes with adaptive thresholding.

A look into SPIMs and their potential in optimization problems.

Learn how to refine trading strategies while managing transaction costs in real markets.

This article presents a method to certify feasibility in semidefinite programming.

Learn how transfer learning aids in classifying dynamic data effectively.

Alchemist automates data labeling, improving efficiency and reducing costs.

Cora helps researchers achieve precise analysis and reliable insights in critical fields.

A deep dive into random walks and their significance in complex systems.

Innovative methods for simulating complex diffusion processes show great potential across multiple fields.

Learn how advanced methods improve investment strategies for better returns.

A new method enhances financial simulations using detailed Limit Order Book data.

This article discusses how long-term memory affects rare event timing.

A new approach to enhance decision-making transparency in machine learning models.

New method improves efficiency in distributed minimax optimization problems.

Examining risks and their connections in finance helps improve risk management.

An overview of integrodifferential operators and their role in various fields.

A new method improves covariance matrix estimation without strict assumptions.

Learn how stochastic control methods help in uncertain decision-making.

This study analyzes a specialized mathematical operator across different scales.

A new model enhances predictions in finance, weather, and economics.

Examining DRL algorithms and their impact on trading strategies in finance.

Introducing a new method to optimize investment portfolios for real-world applications.

A new method improves accuracy in predicting state transitions using Markov chains.

A look at how trading volume trends inform financial strategies.

This study examines private equity's impact on predicting public stock performance.

Exploring particle systems that simulate jumps and their stability in various fields.

A look at the arc-search interior-point algorithm and its applications.

Examining how partial resets affect growth and stability in complex systems.

A deep look into basket options and their innovative pricing strategies.

This research explores innovative methods for managing uncertainty in control systems.

A new model tackles biases and improves stock price predictions using diverse data.

Research unveils methods to tackle sparse quadratic optimization challenges effectively.

New method enhances the analysis of jump-diffusion processes through neural networks.

Introducing a new method for statistical modeling on quantum processors.

Analyzing how the 2020 election affected financial markets in real-time.

A model-based approach to effective stock selection.

A look into how CER systems analyze data patterns in real-time.

A look into precision-focused estimation methods in critical fields.

New method ESQA uses large language models for event sequence analysis.