Beyond Models: A New Approach to Pricing Exotic Derivatives

A novel framework reconciles the benefits of model-independent pricing with the practical demands of implementation for complex financial instruments.

A novel framework reconciles the benefits of model-independent pricing with the practical demands of implementation for complex financial instruments.

This in-depth review charts the progression of reranking techniques, from early algorithmic approaches to the transformative impact of deep learning and large language models.

This review examines how leveraging graph-based approaches can improve the discovery of relevant research papers and enhance academic assistance tools.

A new study reveals that artificial intelligence systems used in news gathering and dissemination can inadvertently perpetuate outdated racial biases embedded within the historical data they are trained on.

Researchers have developed an AI-powered multi-agent system capable of forecasting Federal Funds target rates by analyzing a wide range of economic data.

New research reveals how the complexity of trading activity can foreshadow the size of price swings, even without indicating which way they’ll go.

A new framework leverages the power of machine learning and fast Fourier transforms to deliver significantly faster and more accurate option pricing compared to traditional methods.

A new framework combines the power of artificial intelligence with analyst insights to predict stock returns and offer economic transparency.

A new hybrid approach combining classical machine learning with quantum-enhanced features significantly improves the accuracy of S&P 500 directional prediction.

New research reveals that even cutting-edge artificial intelligence can be defeated by the inherent limitations of ultra-fast market dynamics.