QUANTITATIVE INVESTMENT ANALYSIS (2 SCU)
Learning Outcomes:
On successful completion of this course, students will be able to: explain the statistical concept and probability concepts; apply common probability distribution, the sampling and estimation; apply the hypothesis testing, linear regression, multiple linear regression and able to run the data using R-Studio; apply time-series analysis, multifactor models and able to run the data using R-Studio; explain machine learning, big data projects, and market risk.
Topics:
- Statistical Concepts: Organizing, Visualizing, and Describing Data;
- Probability Concepts;
- Common Probability Distributions;
- Sampling and Estimation;
- Hypothesis Testing;
- Introduction to Linear Regression;
- Multiple Regression;
- Multiple Linear Regression and classic assumption test using R-Studio;
- Time Series Analysis;
- Using Multifactor Models;
- Machine Learning;
- Big Data Projects;
- Measuring and Managing Market Risk.
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