Expert Contributor: Dr. Yuchen Dong
Yuchen is a Senior Application Engineer at MathWorks focusing on customers in the financial services industry. His focus areas are financial instruments,… 더 읽어보기 >>
R2026a covers a lot of ground for economists—Bayesian state-space estimation, macro-scale forecasting, climate and physical risk mapping, symbolic dynamics, and AI-assisted model review, among… 더 읽어보기 >>
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 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 >>
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 >>
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 >>
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 >>
The following blog was written by Owen Lloyd , a Penn State graduate who recently join the MathWorks Engineering Development program.
The code used to develop this example can be found on GitHub… 더 읽어보기 >>
