AI applications in Quantitative Finance

Overview

Many financial applications are looking to incorporate machine learning techniques including risk classification, economic analysis, credit scoring, time series forecasting, estimating default probabilities, data mining and document generation. However, implementing and comparing machine learning techniques to choose the best method can be challenging.  Furthermore, it can be costly and time-consuming process to develop and maintain AI models. MATLAB minimizes these challenges by providing you with built-in functions and tools.

In this webinar, we will introduce how to build AI models with MATLAB through various machine learning, and deep learning examples in MATLAB. We will demonstrate MATLAB features that simplify the procedures so that the financial institutions can reduce costs, increase efficiency, and provide better outcomes for customers.

Highlights

• Use ChatGPT to generate financial documentation through the web application
• Compare Monte Carlo Methods with Neutral Networks on barrier option pricing
• Build Deep learning LSTM models for sequence/time series data

About the Presenter

Dr. Yuchen Dong is a Senior Application Engineer at MathWorks focusing on customers in the Financial Services industry. His focus areas are financial instruments, portfolio optimization, and risk management. Before joining the MathWorks, Yuchen worked as a derivative valuation analyst. He holds a Ph.D. in mathematical sciences at Worcester Polytechnic Institute.