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Quantitative Finance

Investment Management, Risk Management, Algorithmic Trading, Econometric Modeling, Pricing and Insurance

Posts 1 - 10 of 45

CRISK: A Market‑Based Framework for Quantifying Climate Risk in Banking

Effective risk management increasingly requires understanding how climate‑related factors can influence market valuations and balance‑sheet resilience. CRISK provides a transparent, market‑based… 더 읽어보기 >>

Systemic Risk Modeling with MATLAB: Tools and Techniques for Central Banks

Systemic risk modeling is essential for central banks as financial systems grow more interconnected and vulnerable to sudden shocks. From market implied indicators to climate stress testing and… 더 읽어보기 >>

Refining Macroeconomic Forecasting with MATLAB Techniques

Nonlinear confidence bands help you quantify forecast uncertainty in DSGE models, but they can be slow to compute. At the MathWorks Finance Conference, Kadir Tanyeri (International Monetary Fund)… 더 읽어보기 >>

Upgrading MATLAB: What You Gain and How to Get There

Every MATLAB release opens the door to new capabilities, better performance, and tighter integration with the platforms your team already uses. With two major releases a year and over 800… 더 읽어보기 >>

Central Bank of The Bahamas Uses MATLAB and Dynare to Model Climate and Tourism Shocks

“It [MATLAB] was used in Dynare in order to promote the accuracy and the ease of generating this model.”— Allan Wright, Manager, Central Bank of the Bahamas

Watch the Full… 더 읽어보기 >>

Credit and Market Risk Management: From Risk Modeling to Regulatory Compliance

In this technical session, Valerio Sperandeo, Senior Application Engineer, demonstrated how MATLAB can support financial institutions in building robust, transparent, and scalable risk models aligned… 더 읽어보기 >>

Speeding Up Dynare Models: Practical Paths to Performance Gains 2

Dynamic Stochastic General Equilibrium (DSGE) models are essential tools for policy analysis and forecasting, but estimation runs often exceed 24 hours—particularly for large-scale models or Bayesian… 더 읽어보기 >>

Pricing Special Purpose Vehicles with Physics‑Informed Neural Networks at Nasdaq Private Market

Summary
Nasdaq Private Market (NPM) used MATLAB® to prototype and scale physics‑informed neural networks (PINNs) that price Special Purpose Vehicles (SPVs) with embedded carried interest and… 더 읽어보기 >>

Highlights from MathWorks Finance Conference 2025

The 2025 MathWorks Finance Conference brought together quants, economists, financial modelers and researchers to explore how MATLAB is shaping the future of finance. Across two days, speakers shared… 더 읽어보기 >>

Build a RAG Pipeline in MATLAB: From Document Ingestion to LLM-Driven Insights

The following post is from Yuchen Dong, Senior Finance Application Engineer at MathWorks.
The example featured in the blog can be found on GitHub here.
Retrieval-Augmented Generation (RAG) has… 더 읽어보기 >>

Posts 1 - 10 of 45

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