Mô tả

Welcome to Python for Financial Analysis and Algorithmic Trading! Are you interested in how people use Python to conduct rigorous financial analysis and pursue algorithmic trading, then this is the right course for you!

This course will guide you through everything you need to know to use Python for Finance and Algorithmic Trading! We'll start off by learning the fundamentals of Python, and then proceed to learn about the various core libraries used in the Py-Finance Ecosystem, including jupyter, numpy, pandas, matplotlib, statsmodels, zipline, Quantopian, and much more!

 We'll cover the following topics used by financial professionals:

  • Python Fundamentals
  • NumPy for High Speed Numerical Processing
  • Pandas for Efficient Data Analysis
  • Matplotlib for Data Visualization
  • Using pandas-datareader and Quandl for data ingestion
  • Pandas Time Series Analysis Techniques
  • Stock Returns Analysis
  • Cumulative Daily Returns
  • Volatility and Securities Risk
  • EWMA (Exponentially Weighted Moving Average)
  • Statsmodels
  • ETS (Error-Trend-Seasonality)
  • ARIMA (Auto-regressive Integrated Moving Averages)
  • Auto Correlation Plots and Partial Auto Correlation Plots
  • Sharpe Ratio
  • Portfolio Allocation Optimization 
  • Efficient Frontier and Markowitz Optimization
  • Types of Funds
  • Order Books
  • Short Selling
  • Capital Asset Pricing Model
  • Stock Splits and Dividends
  • Efficient Market Hypothesis
  • Algorithmic Trading with Quantopian
  • Futures Trading

Bạn sẽ học được gì

Use NumPy to quickly work with Numerical Data

Use Pandas for Analyze and Visualize Data

Use Matplotlib to create custom plots

Learn how to use statsmodels for Time Series Analysis

Calculate Financial Statistics, such as Daily Returns, Cumulative Returns, Volatility, etc..

Use Exponentially Weighted Moving Averages

Use ARIMA models on Time Series Data

Calculate the Sharpe Ratio

Optimize Portfolio Allocations

Understand the Capital Asset Pricing Model

Learn about the Efficient Market Hypothesis

Conduct algorithmic Trading on Quantopian

Yêu cầu

  • Some knowledge of programming (preferably Python)
  • Ability to Download Anaconda (Python) to your computer
  • Basic Statistics and Linear Algebra will be helpful

Nội dung khoá học

14 sections

Course Introduction

4 lectures
Introduction to Course
02:12
Course Overview Lecture (DON'T SKIP THIS!)
03:32
Did you skip the last lecture? Please go back and view it!
00:25
Course FAQ
00:58

Course Materials and Set-up

2 lectures
Note on yml File
00:16
Course Installation Guide
08:48

Python Crash Course

7 lectures
Welcome to the Python Crash Course
00:19
Introduction to Crash Course
01:16
Python Crash Course Part One
19:00
Python Crash Course Part Two
13:37
Python Crash Course Part Three
15:02
Python Crash Course Exercises
04:13
Python Crash Course Exercise Solutions
09:06

NumPy

7 lectures
Welcome to NumPy
00:23
Introduction to NumPy
01:37
NumPy Arrays
15:47
Numpy Operations
04:19
Numpy Indexing
10:54
NumPy Review Exercise
04:10
Numpy Exercise Solutions
09:51

General Pandas Overview

13 lectures
Welcome to Pandas
00:22
Introduction to Pandas
02:39
Series
06:58
DataFrames
15:34
DataFrames Part Two
16:59
DataFrames Part Three
09:01
Missing Data
06:14
Group By with Pandas
06:37
Merging, Joining, and Concatenating DataFrames
09:10
Pandas Common Operations
12:12
Data Input and Output
13:50
General Pandas Review Exercises
03:06
General Pandas Exercise Solutions
12:53

Visualization with Matplotlib and Pandas

11 lectures
Welcome to Visualization
00:23
Introduction to Visualization in Python
01:48
Matplotlib Basics - Part One
18:45
Matplotlib Basics - Part Two
15:31
Matplotlib Part Three
11:43
Matplotlib Exercise
03:42
Matplotlib Exercise Solutions
10:08
Pandas Visualization Overview
12:07
Pandas Time Series Visualization
17:32
Pandas Visualization Exercise Overview
01:18
Pandas Visualization Exercise Solutions
08:51

Data Sources

4 lectures
Introduction to Data Sources
01:21
Note on Pandas Datareader
00:09
Pandas DataReader
04:37
Quandl
10:21

Pandas with Time Series Data

6 lectures
Welcome to Pandas for Time Series
00:13
Introduction to Time Series with Pandas
00:58
Datetime Index
09:38
Time Resampling
12:48
Time Shifts
05:58
Pandas Rolling and Expanding
17:52

Capstone Stock Market Analysis Project

6 lectures
Welcome to the Capstone Project!
00:30
Stock Market Analysis Project
06:38
Stock Market Analysis Project Solutions Part One
20:25
Python Stock Market Analysis Solutions - Part Two
09:36
Stock Market Analysis Project Solutions Part Three
16:52
Stock Market Analysis Project Solutions Part Four
08:23

Time Series Analysis

16 lectures
Welcome to Time Series Analysis
00:33
Introduction to Time Series
02:51
Time Series Basics
03:58
Introduction to Statsmodels
12:29
ETS Theory
04:16
EWMA Theory
02:49
EWMA Code Along
14:24
ETS Code Along
06:24
ARIMA Theory
09:33
ACF and PACF
06:20
ARIMA with Statsmodels
11:42
Quick Note on Second Milk Difference!
00:31
ARIMA Code Part Two
13:59
ARIMA Code Part Three
06:49
ARIMA Code Part Four
14:14
Discussion on choosing PDQ
00:08

Python Finance Fundamentals

17 lectures
Welcome to Finance Fundamentals
00:36
Introduction to Python Finance Fundamentals
00:49
Sharpe Ratio Slides
07:16
Portfolio Allocation Code Along Part One
15:31
Portfolio Allocation Code Along Part Two
06:44
Portfolio Optimization
05:14
Portfolio Optimization Code Along One
14:44
Portfolio Optimization Code Along Two
07:45
Portfolio Optimization Code Along Three
16:32
Key Financial Topics
01:06
Types of Funds
06:09
Order Books
14:35
Short Selling
02:35
CAPM - Capital Asset Pricing Model
05:18
CAPM Code Along
12:09
Stock Splits and Dividends
03:16
EMH
02:00

Basics of Algorithmic Trading with Quantopian and Zipline

13 lectures
Note on Quantopian and Zipline
00:31
Welcome to the Quantopian Section
00:24
Introduction to Quantopian
09:27
Quantopian Algorithms Basics Part One
16:17
Quantopian Algorithms Basics Part Two
17:17
First Trading Algorithm - Part One
16:47
First Trading Algorithm - Part Two
16:44
Trading Algorithm Exercise
04:50
Trading Algorithm Exercise Solutions Part One
12:36
Trading Algorithm Exercise Solutions Part Two
02:38
Quantopian Pipelines Factors
16:59
Quantopian Pipelines Filters
05:58
Quantopian Pipeline - Masking and Classifiers
09:17

Advanced Quantopian and Trading Algorithms

13 lectures
Welcome to Trading Algorithms
00:48
Pipeline Trading Algorithm Example - Code Along - Part One
13:34
Pipeline Trading Algorithm - Code Along - Part Two
10:27
Quick note
00:08
Pipeline Trading Algorithm Code along Part Three
19:28
Leverage
12:48
Hedging
14:17
Hedging- Part Two
14:54
Portfolio Analysis with PyFolio
15:20
Stock Sentiment Analysis Project
16:23
What are Futures?
09:02
Futures on Quantopian
18:19
Futures on Quantopian Part Two
20:34

BONUS SECTION: THANK YOU!

1 lectures
Bonus Lecture:
00:10

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