Predictive Modeling Using MATLAB

Seminar Overview

Predictive Modeling Using MATLAB

Predictive modeling techniques based on computational statistics are often used for financial analysis tasks such as time series analysis, forecasting, risk classification, estimating default probabilities, and data mining. However, implementing and comparing modeling techniques to choose the best approach can be challenging.

In this seminar, you will learn about econometric modeling and supervised learning techniques available in MATLAB, and how to perform data preprocessing and cleanup, select models and evaluate their performance, compare results, and apply the best techniques for your problem.

Highlights include:

  • Multivariate linear regression techniques in time series analysis
  • Automated predictor selection and cross validation
  • Residual analysis – diagnostics for autocorrelation and heteroscedasticity
  • Dynamic model construction using autoregressive, moving average, and distributed lag variables
  • Neural networks
  • Decision trees and ensemble learning