Latest Articles for Finance

A novel framework enhances learning of stochastic processes in various fields.

This paper explores methods to compare multisets across various fields.

Discover how Exponentiated Gradient Algorithms optimize investment strategies in real-time.

Analyzing trader clusters reveals patterns to enhance investment predictions.

A deep look into path-dependent volatility and its impact on options pricing.

Discover how the truncation method enhances numerical differentiation across various fields.

A clear overview of limit order books and their significance in trading.

A new approach to classifying tabular data using ICL-transformers shows promising results.

New model enhances the study of changing relationships over time.

A new method enhances solutions for high-dimensional optimal control problems in finance and engineering.

Examining the relationship between quantum algorithms and signal processing for better efficiency.

This paper analyzes market makers' interactions using game theory for insights into pricing strategies.

Revolutionizing the way we solve optimization challenges in multiple fields.

Revolutionizing finance through extended weak convergence and advanced modeling techniques.

Discover the role of Cluster GARCH in understanding asset relationships.

Explore the significance of random matrices in various fields and their eigenvalue behavior.

This paper explores how AI and machine learning can improve market trend predictions.

Learn how robust minmax control tackles uncertainty in various fields.

New methods for identifying significant changes in data variance over time.

A method to learn low-dimensional dynamics from noisy high-dimensional observations.

A study comparing HAR model and machine learning in stock volatility forecasting.

This article presents a new method for pricing options using deep learning techniques.

A new method improves predictions of asset relationships for better investment strategies.

Explore how recent experiences shape decision-making in reinforcement learning.

A novel method improves the accuracy and efficiency of implied volatility estimates.

A new method for deriving interpolation constraints enhances optimization performance analysis.

A look into how specific operators function with boundary conditions in various applications.

Analyzing how fee structures affect automated market makers and arbitrage in decentralized finance.

Learn how Bayesian inference enhances neural networks and decision-making.

A study on maximizing returns through alpha and phi-portfolios.

New methods for preparing quantum states improve efficiency and reduce resource needs.

Strategies for optimizing asset allocation while considering data uncertainty.

Learn how probabilistic programming helps analyze uncertainty in data.

A novel approach to measure dependencies in extreme data sets across various fields.

Learn how compromise decisions enhance reliability in stochastic programming.

Exploring the need for clear explanations in Graph Neural Networks.

This article presents a fresh perspective on analyzing Markov chains through distribution transformers.

A new pricing formula for VIX options using the Heston-Hawkes model enhances volatility trading strategies.

Quantum computing offers new solutions for complex optimization challenges.

New approach enhances decision-making by providing reliable input changes.