End-to-end large portfolio optimization for variance minimization with neural networks through covariance cleaning
December 2026
We develop a rotation-invariant neural network that provides the global minimum-variance portfolio by jointly learning how to lag-transform historical returns and marginal volatilities and how to regularise...
A meta reinforcement learning approach to goals-based wealth management
December 2026
Applying concepts related to zero-shot meta-learning and pre-training of foundation models, we develop a meta reinforcement learning approach (denoted MetaRL) that is pre-trained on thousands of goals-based...
Characterization of S&P 500 companies by sector using artificial intelligence: Statistical evidence and machine learning application
December 2026
This article explores the extent to which established sector classifications continue to provide meaningful insights into the financial underpinnings of firms. Utilizing a contemporary cross-sectional...
A Conformable Heston option pricing model
December 2026
In the aftermath of the proposal of the Black-Scholes-Merton model in 1973, a considerable number of research groups issued substantial criticisms of the model. An initial observation revealed a discontinuity...
Explainable ensemble machine learning for financial transaction fraud detection: Insights from XGBoost and deep neural networks
December 2026
The rapid digitalization of financial services has enhanced transaction speed and accessibility but also amplified exposure to fraud activities that undermine institutional integrity and consumer trust....
Reinforcement learning for automated market making in cryptocurrency perpetual futures: Integrating funding rate dynamics with historical BTCUSDT evidence
December 2026
The emergence of cryptocurrency perpetual futures has created unique opportunities for automated market making, yet existing approaches often ignore the funding rate mechanism that transfers payments...
Memory, persistence, and the price process in interest rate futures contracts: A statistical investigation at the mesoscale using kernel two-sample testing
December 2026
We test whether long memory in interest rate futures reflects intrinsic dynamics or calendar-time artifact. Using tick-level data from 11 futures contracts, we compare multifractal scaling properties...
Semantic drift in long-form financial disclosures in Portuguese
December 2026
Financial disclosures contain critical information that is not always immediately reflected in market prices. Tracking semantic change in these communications can surface narrative shifts, but it is...
RMSE-triggered rebalancing for deep learning-guided portfolio optimization
December 2026
This paper addresses the gap between improved forecasting accuracy from machine learning and deep learning models and their limited translation into realized portfolio performance under transaction-cost...
Incorporating news sentiment into FIGARCH models for asset returns and volatility
December 2026
This paper introduces a novel sentiment-driven framework for modeling asset return volatility and for comparing FIGARCH-based specifications by integrating machine learning and time-series econometric...
Scalable and interpretable fraud detection in FinTech: Evidence from a hybrid TabNet–Graph neural network framework
December 2026
This study proposes a fraud detection framework for FinTech that integrates tabular deep learning with relational graph reasoning. We address a key limitation of state-of-the-art tabular fraud models:...
Sample Reconstruction and Prediction of Stock Time Series Based on Trend Structure Extraction
Available online 7 August 2026
Financial time series are characterized by strong noise, frequent fluctuations, and dense local trend switching, making raw-sequence prediction difficult. This paper investigates stock time-series prediction...
Deep Learning and the International Capital Asset Pricing Model
Available online 3 August 2026
We revisit the international conditional Capital Asset Pricing Model (ICCAPM) using a Long Short-Term Memory (LSTM) model to estimate high-dimensional, time-varying covariances with fewer parametric...
International Financial Markets Through 150 Years: Evaluating Stylized Facts
Available online 25 June 2026
In the theory of financial markets, a stylized fact is a qualitative summary of a pattern in financial market data that is observed across multiple assets, asset classes and time horizons. In this article,...
Optimal rebalancing strategies reduce market variability
December 2025
The increasing fraction of passive funds influences stock market variability since passive investors behave differently than active investors. We demonstrate via simulations how portfolios that rebalance...
Symbolic Modeling for financial asset pricing
December 2025
Symbolic Regression is a machine learning technique that discovers an unknown function from its samples. Compared to conventional regression techniques (e.g., linear regression, polynomial regression,...
Unsupervised generation of tradable topic indices through textual analysis
December 2025
Stock returns are moved by many risk factors. Thematic stock indices try to represent these factors, but are limited by the fact that risk factors are not directly observable. This paper introduces...
Financial inclusion, technologies, and worldwide economic development: A spatial Durbin model approach
December 2025
Using panel data from 144 countries, this study constructed an inclusive financial evaluation index and depicted the inclusive finance development worldwide under digital empowerment through classification....
Finding a needle in a haystack: A machine learning framework for anomaly detection in payment systems
December 2025
We propose a flexible machine learning (ML) framework for real-time transaction monitoring in high-value payment systems (HVPS), which are central to a country’s financial infrastructure and integral...
Using Bell violations as an indicator for financial market crisis
December 2025
The failure to identify and measure financial risk carries significant social and economic consequences. This paper introduces a novel framework for analyzing financial stress and crises, based on the...
Catastrophic-risk-aware reinforcement learning with extreme-value-theory-based policy gradients☆
December 2025
This paper tackles the problem of mitigating catastrophic risk (which is risk with very low frequency but very high severity) in the context of a sequential decision making process. This problem is...
Integrating credit and debit data for enhanced insights into borrowing behavior and predictive modeling of credit card delinquency
December 2025
This research delves into the predictive modeling of credit card delinquency by harnessing both credit and debit data, offering a nuanced perspective on consumer financial behavior. The study introduces...
Paper discussion at the third annual conference on capital market research in the era of AI
December 2025
Dumb money? Social network attention herding, sentiment, and markets
December 2025
Wallstreetbets (WSB) is the perfect echo chamber to study retail investor behaviour and markets. We introduce a direct measure of individual stock attention and the concept of forum-wide attention herding....
Enhancing bookkeeper decision support through graph representation learning for bank reconciliation
December 2025
The emergence of cloud-based bookkeeping platforms has made it possible to streamline decision-making in tedious accounting tasks, such as bank reconciliation. Bank reconciliation involves tracing the...
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