arXiv:2510.16066v4 Announce Type: replace-cross
Abstract: Despite accounting for 96.1% of all businesses in Malaysia, access to financing remains one of the most persistent challenges faced by Micro, Small, and Medium Enterprises (MSMEs). Newly establ…
arXiv:2603.05917v2 Announce Type: replace
Abstract: Stock market prediction presents considerable challenges for investors, financial institutions, and policymakers operating in complex market environments characterized by noise, non-stationarity, and…
arXiv:2604.02549v1 Announce Type: cross
Abstract: In this work we evaluate the performance of three classes of methods for detecting financial anomalies: topological data analysis (TDA), principal component analyis (PCA), and Neural Network-based appr…
arXiv:2603.19136v2 Announce Type: replace
Abstract: Stock markets exhibit regime-dependent behavior where prediction models optimized for stable conditions often fail during volatile periods. Existing approaches typically treat all market states unifo…
arXiv:2603.10202v2 Announce Type: replace-cross
Abstract: Generating synthetic financial time series that preserve the statistical properties of real market data is essential for stress testing, risk model validation, and scenario design. Existing app…
arXiv:2603.28198v1 Announce Type: new
Abstract: Static regret to a single expert is often the wrong target for strictly online prediction under non-stationarity, where the best expert may switch repeatedly over time. We study Policy-Controlled General…
arXiv:2603.28257v1 Announce Type: cross
Abstract: KAN-PCA is an autoencoder that uses a KAN as encoder and a linear map as decoder. It generalizes classical PCA by replacing linear projections with learned B-spline functions on each edge. The motivati…
arXiv:2506.09851v2 Announce Type: replace-cross
Abstract: The prediction of foreign exchange rates, such as the US Dollar (USD) to Bangladeshi Taka (BDT), plays a pivotal role in global financial markets, influencing trade, investments, and economic s…