Contents

# Tutorial Series

## Introduction to Financial Python

This tutorial series introduces basic Python applied to financial concepts. If you have great investment ideas but don't know how to write them, or if you think you need to learn some basic skills in quantitative finance, then this is a good starting point. The series is broken into four parts: python, math and statistics, basic financial concepts related to investment and financial time series analysis.

We not only introduce the concepts but also show you how to apply the introduced techniques step by step using Python code snippets. We use real financial datasets as examples and after each chapter we design a QuantConnect algorithm applying what we learned.

### What Will I learn ?

Python
Statistics
Linear Algebra
Modern Portfolio Theory
Multi-factor Models

1

## Python: Data Types and Data Structures

First glimpse of Python.
2

## Python: Logical Operations and Loop

The essential of programming.
3

## Python: Functions and Object-Oriented Programming

The Python magic.
4

## NumPy and Basic Pandas

The power scientific calculation package for Python.
5

## Pandas: Resampling and DataFrame

The magical Data manipulation tool for Python.
6

## Rate of Return, Mean and Variance

The basic mathematical concepts for quantitative finance.
7

## Random Variable and Distributions

Point estimation vs interval estimation
8

9

## Simple Linear Regression

Find the relationship between two random variables.
10

## Multiple Linear Regression and residual analysis

Explain a random variable using the power of multi-variables.
11

## Linear Algebra

Mathematic tool for large scale calculation
12

## Modern Portfolio Theory

Don't put all the eggs in one basket.
13

Beta and Alpha.