How to Identify Financial Statement Fraud: Key Signs and Methods

Spotting financial statement fraud is crucial. Learn key signs and detection methods to protect your investments from risky ...

Top 5 Prediction Market Platforms To Keep An Eye On in 2026

The Edge: Polymarket offers the deepest order books in the industry. With the anticipated launch of the POLY token in 2026, ...

Forecasting the world in 2026

FT writers’ predictions for the new year, from the likelihood of higher Trump tariffs to the future of interest rates and the ...
World Business Council for Sustainable Development

Financial quantification: applying return and cash-flow methods

To compete for capital, sustainability must be framed in the same quantitative language as any other business investment: return, risk and cash flow. This article bridges strategic intent and ...
Scientific Research Publishing

Sezer, O.B., Gudelek, M.U. and Ozbayoglu, A.M. (2020) Financial Time Series Forecasting with Deep Learning: A Systematic Literature Review: 2005-2019. Applied Soft Computing ...

ABSTRACT: Stock markets are notoriously complex and volatile, which makes accurate price prediction a necessity for investor decision-making, risk mitigation, and profitability. This study develops ...
techtimes

Forecasting the Future: How AI Is Reshaping Financial Predictions

The innovation at the heart of this research lies in combining Long Short-Term Memory (LSTM) networks and Recurrent Neural Networks (RNNs) to tackle financial time series data. These architectures ...
IEEE

Long Short-Term Financial Time Series Forecasting Based on Residual Multiscale TCN Sparse Expert Network and Informer

Abstract: Due to the inherent high volatility and complexity of financial markets, traditional time series forecasting models face numerous challenges in handling both short- and long-term predictions ...
Frontiers

CMDMamba: dual-layer Mamba architecture with dual convolutional feed-forward networks for efficient financial time series forecasting

Introduction: Transformer models have demonstrated remarkable performance in financial time series forecasting. However, they suffer from inefficiencies in computational efficiency, high operational ...