[Live Webinar] MATLAB for Finance

Outline

From the beginning, let participants learn about what's MATLAB and be familiar with MATLAB environment.

Next session, brief an overview of how to use MATLAB in the Finance environment e.g. Financial data access, Finance toolboxes. Then we will do a Classification trading stock signal example by using Machine Learning/ Deep Learning Technique.

Final session, We will bring the model from earlier session to deploy a web application.

This webinar for Everyone at Chulalongkorn University

Agenda

21 August 2020 at 18:00 - 19:00

#1st Topic: Overview of MATLAB Computational Finance Suite

- Access various databases and data feeds

- Use machine learning or an econometrics model to forecast financial data

- Price Financial instruments, such as equity derivatives, interest rate derivatives, or hybrid derivatives

- Perform credit scorecard modelling using interactive application

- Simulate credit portfolios based on probability of default or credit migration matrix Validate value-at-risk model

28 August 2020 at 18:00 - 20:00

#2nd Topic: Classifying Trading Signals using Machine Learning and Deep Learning

- Data pre-processing, factor creation, and data partitioning

- Rule-based trading

- Classifying trading signals using Classification Learner App

- Classifying trading signals using LSTM (deep Learning Algorithm)

#3rd Topic: Application Deployment Solution
- Deploy your finance models
- Wide range of deployment option for your MATLAB algorithm
- Create standalone desktop application
- Production requirement to create web application with MATLAB as backend engine

Prerequisites

Undergraduate-level mathematics and experience with basic computer operations.
MATLAB installation Guideline, please access this Link

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