# CFRM 502: Financial Data Science

> Reading Material:
>
> * *Statistics and Data Analysis for Financial Engineering with R*, D. Ruppert.
> * *Introduction to Time Series and Forecasting*, P, Brockwell.

This course covers the main statistical methods used for analyzing financial data. Our focus will be roughly evenly divided between the theory of these methods and their implementation using the R programming language. The topics covered will include linear regression, multiple linear regression, nonlinear regression, nonparametric regression, time series analysis, ARMA and ARIMA models, GARCH models, cointegration and VAR models.

1. Linear Regression
2. Multiple Linear Regression
3. Nonlinear Regression
4. Nonparametric Regression
5. Time Series Analysis
6. ARMA and ARIMA models
7. GARCH models
8. Cointegration
9. VaR Models


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://cfrm.franco.biz/program/second-quarter/cfrm-502-financial-data-science.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.