Python for Financial Analysis and Algorithmic Trading from Udemy

What's inside

Learning objectives

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
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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
Show more
Show less

Syllabus

Let's go over the course!

Introduction to Course

Course Overview Lecture (DON'T SKIP THIS!)

Did you skip the last lecture? Please go back and view it!

Course FAQ

Let's get you set-up!

Note on yml File

Course Installation Guide

Quick Review of Python if you need it!

Welcome to the Python Crash Course

Introduction to Crash Course

Python Crash Course Part One

Python Crash Course Part Two

Python Crash Course Part Three

Python Crash Course Exercises

Python Crash Course Exercise Solutions

Let's learn about Numerical Python

Welcome to NumPy

Introduction to NumPy

NumPy Arrays

Numpy Operations

Numpy Indexing

NumPy Review Exercise

Numpy Exercise Solutions

Let's how to use Pandas!

Welcome to Pandas

Introduction to Pandas

Series

DataFrames

DataFrames Part Two

DataFrames Part Three

Missing Data

Group By with Pandas

Merging, Joining, and Concatenating DataFrames

Pandas Common Operations

Data Input and Output

General Pandas Review Exercises

General Pandas Exercise Solutions

Let's learn how to visualize our data!

Welcome to Visualization

Introduction to Visualization in Python

Matplotlib Basics - Part One

Matplotlib Basics - Part Two

Matplotlib Part Three

Matplotlib Exercise

Matplotlib Exercise Solutions

Pandas Visualization Overview

Pandas Time Series Visualization

Pandas Visualization Exercise Overview

Pandas Visualization Exercise Solutions

Learn how to use Pandas DataReader and Quandl

Introduction to Data Sources

Note on Pandas Datareader

Pandas DataReader

Quandl

Let's quickly learn about using Pandas for Time Series!

Welcome to Pandas for Time Series

Introduction to Time Series with Pandas

Datetime Index

Time Resampling

Time Shifts

Pandas Rolling and Expanding

Let's finish the first half of the course with a project!

Welcome to the Capstone Project!

Stock Market Analysis Project

Stock Market Analysis Project Solutions Part One

Python Stock Market Analysis Solutions - Part Two

Stock Market Analysis Project Solutions Part Three

Stock Market Analysis Project Solutions Part Four

Let's learn how to use Python for Time Series Data

Welcome to Time Series Analysis

Introduction to Time Series

Time Series Basics

Introduction to Statsmodels

ETS Theory

EWMA Theory

EWMA Code Along

ETS Code Along

ARIMA Theory

ACF and PACF

ARIMA with Statsmodels

Quick Note on Second Milk Difference!

ARIMA Code Part Two

ARIMA Code Part Three

ARIMA Code Part Four

Discussion on choosing PDQ

Learn some basics of finance!

Welcome to Finance Fundamentals

Introduction to Python Finance Fundamentals

Sharpe Ratio Slides

Portfolio Allocation Code Along Part One

Portfolio Allocation Code Along Part Two

Portfolio Optimization

Portfolio Optimization Code Along One

Portfolio Optimization Code Along Two

Portfolio Optimization Code Along Three

Key Financial Topics

Types of Funds

Order Books

Short Selling

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Suitable for Python learners who wish to pursue algorithmic trading within the finance industry

Taught by Jose Portilla, who holds extensive experience in finance and algorithmic trading

Involves working with various essential Python libraries like NumPy, Pandas, Matplotlib, and Statsmodels

Covers a wide range of topics including Python fundamentals, financial analysis techniques, time series analysis, and algorithmic trading

Offers comprehensive instruction on using Python's data analysis capabilities for financial applications

Provides hands-on exercises and projects to reinforce the concepts covered in the course

Reviews summary

Python for financial analysis and algorithmic trading

Learners say this course is largely positive, well received, and a great match for beginners or those who need a financial analysis and python coding refresher. According to students, this course is a beginner-friendly introduction to financial analysis, algorithmic trading, and essential Python libraries for finance. The first half of the course focuses on introductions to Python, data science, and financial analysis with many reviewers highlighting the content around Pandas and Numpy as some of the most valuable. Many reviewers also mention the Capstone project as a major highlight of the course. The second half of the course introduces algorithmic trading on the Quantopian platform. Reviews around this section are more mixed, with many students noting that this section has become outdated and that the platform is no longer available. Other reviewers note that the content in these sections is still valuable despite the platform changes. Overall, reviewers who came into this course with some background in Python and finance found this course to be a valuable learning experience. Several reviewers mentioned taking multiple courses from this instructor and recommend other courses on Python and data science he teaches on Udemy.

Several reviewers mentioned taking multiple courses from this instructor and recommend other courses on Python and data science he teaches on Udemy.

"Several reviewers mentioned taking multiple courses from this instructor and recommend other courses on Python and data science he teaches on Udemy."

Many reviewers also mention the Capstone project as a major highlight of the course.

"Many reviewers also mention the Capstone project as a major highlight of the course."

Other reviewers note that the content in these sections is still valuable despite the platform changes.

"Other reviewers note that the content in these sections is still valuable despite the platform changes."

Overall, reviewers who came into this course with some background in Python and finance found this course to be a valuable learning experience.

"Overall, reviewers who came into this course with some background in Python and finance found this course to be a valuable learning experience."

Many reviewers highlighted the content around Pandas and Numpy as some of the most valuable.

"Many reviewers highlighted the content around Pandas and Numpy as some of the most valuable."

learners say this course is largely positive, well received, and a great match for beginners or those who need a financial analysis and python coding refresher.

"This course is largely positive, well received, and a great match for beginners or those who need a financial analysis and python coding refresher."

"this course is a beginner-friendly introduction to financial analysis, algorithmic trading, and essential Python libraries for finance."

"The first half of the course focuses on introductions to Python, data science, and financial analysis"

Reviews around this section are more mixed, with many students noting that this section has become outdated and that the platform is no longer available.

"Reviews around this section are more mixed, with many students noting that this section has become outdated and that the platform is no longer available."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Python for Financial Analysis and Algorithmic Trading with these activities:

Review Fundamentals of Python

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This activity will allow you to recall and refresh your memory for the basic fundamentals of Python programming language, which this course will heavily rely on.

Browse courses on Python Basics

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Go over your notes or resources from previous Python courses or materials.
Re-watch introductory Python video tutorials
Install Python on your computer and run through some basic Python exercises.

Read 'Python for Data Analysis'

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This book provides a comprehensive guide to Python libraries essential for data analysis and manipulation, reinforcing your understanding of concepts covered in the course.

View Python for Data Analysis on Amazon

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Obtain a copy of the book.
Read through the chapters relevant to the course topics.
Work through the exercises and examples provided in the book.

Join a Python Study Group

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This activity will allow you to connect with other learners, share knowledge, and enhance your understanding through discussions and problem-solving.

Browse courses on Python

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Find or create a study group with fellow learners.
Meet regularly to discuss course topics, work on assignments together, and support each other's learning.
Take turns presenting concepts, leading discussions, and sharing resources.

Four other activities

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Show all seven activities

Complete NumPy and Pandas Tutorials

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This activity will help you strengthen your hands-on skills for using NumPy and Pandas, which are essential libraries for data analysis and manipulation.

Browse courses on NumPy

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Find online tutorials or courses on NumPy and Pandas.
Follow the tutorials and complete the practice exercises.
Refer to the official NumPy and Pandas documentation for further clarification or advanced techniques.

Solve Data Analysis Challenges

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By engaging in practice drills and solving data analysis challenges, you will enhance your ability to apply the concepts and techniques learned in this course to real-world scenarios.

Browse courses on Data Analysis

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Find online data analysis challenges or platforms.
Work through the challenges and try to solve them using NumPy, Pandas, and other techniques covered in the course.
Review your solutions and identify areas for improvement.

Develop a Python Project for Portfolio Optimization

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This activity will provide you with an opportunity to apply your knowledge and skills to a practical project, demonstrating your understanding of the concepts covered in the course.

Browse courses on Portfolio Optimization

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Gather data on financial assets and markets.
Design a Python program to implement portfolio optimization algorithms.
Test and refine your program.
Write a report summarizing your findings and insights.

Develop a Financial Analysis Dashboard

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This activity will allow you to apply your knowledge and skills to create a practical tool that visualizes and analyzes financial data, enhancing your understanding of financial concepts.

Browse courses on Financial Analysis

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Gather and prepare financial data.
Design and develop a Python program to create interactive visualizations.
Deploy the dashboard and share it with others.

Career center

Learners who complete Python for Financial Analysis and Algorithmic Trading will develop knowledge and skills that may be useful to these careers:

Quantitative Analyst

Quantitative Analysts (Quants) use mathematical and statistical models to analyze financial data and develop trading strategies. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Quant, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and statsmodels for data analysis and visualization. This course would also provide a solid foundation in time series analysis, econometrics, and portfolio optimization, which are all essential for success in this role.

See salaries and explore the career path for Quantitative Analyst

Hedge Fund Manager

Hedge Fund Managers manage investment funds that use advanced investment strategies. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Hedge Fund Manager, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and statsmodels for data analysis and visualization. This course would also provide a solid foundation in portfolio theory, risk management, and financial modeling, which are essential for success in this role.

See salaries and explore the career path for Hedge Fund Manager

Trader

Traders buy and sell financial instruments for their own account or on behalf of clients. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Trader, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and matplotlib for data analysis and visualization. This course would also provide a solid foundation in technical analysis and trading strategies, which are essential for success in this role.

See salaries and explore the career path for Trader

Private Equity Investor

Private Equity Investors invest in private companies. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Private Equity Investor, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and matplotlib for data analysis and visualization. This course would also provide a solid foundation in financial modeling, valuation, and due diligence, which are essential for success in this role.

See salaries and explore the career path for Private Equity Investor

Portfolio Manager

Portfolio Managers manage investment portfolios for individuals and institutions. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Portfolio Manager, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and statsmodels for data analysis and visualization. This course would also provide a solid foundation in portfolio theory and optimization, which are essential for success in this role.

See salaries and explore the career path for Portfolio Manager

Risk Manager

Risk Managers identify, assess, and manage risks. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Risk Manager, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and statsmodels for data analysis and visualization. This course would also provide a solid foundation in risk management and financial modeling, which are essential for success in this role.

See salaries and explore the career path for Risk Manager

Venture Capitalist

Venture Capitalists invest in early-stage companies. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Venture Capitalist, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and matplotlib for data analysis and visualization. This course would also provide a solid foundation in financial modeling, valuation, and due diligence, as well as an overview of the venture capital industry, which are essential for success in this role.

See salaries and explore the career path for Venture Capitalist

Data Scientist

Data Scientists use data to solve business problems. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Data Scientist, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and matplotlib for data analysis and visualization. This course would also provide a solid foundation in machine learning and statistical modeling, which are essential for success in this role.

See salaries and explore the career path for Data Scientist

Financial Analyst

Financial Analysts help organizations make informed financial decisions by analyzing financial data, identifying trends, and making recommendations. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Financial Analyst, as it will teach the basics of Python, as well as how to use NumPy and Pandas for data analysis and visualization. This course would also provide a solid foundation in time series analysis, which is essential for understanding and forecasting financial data.

See salaries and explore the career path for Financial Analyst

Financial Planner

Financial Planners help individuals and families plan for their financial future. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Financial Planner, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and matplotlib for data analysis and visualization. This course would also provide a solid foundation in financial planning and investment management, which are essential for success in this role.

See salaries and explore the career path for Financial Planner

Statistician

Statisticians collect, analyze, and interpret data. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Statistician, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and statsmodels for data analysis and visualization. This course would also provide a solid foundation in probability and statistics, which are essential for success in this role.

See salaries and explore the career path for Statistician

Economist

Economists study the economy and make predictions about its future performance. The Python for Financial Analysis and Algorithmic Trading course would be useful for an Economist, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and statsmodels for data analysis and visualization. This course would also provide a solid foundation in econometrics and forecasting, which are essential for success in this role.

See salaries and explore the career path for Economist

Actuary

Actuaries use mathematical and statistical models to assess risk and uncertainty. The Python for Financial Analysis and Algorithmic Trading course would be useful for an Actuary, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and statsmodels for data analysis and visualization. This course would also provide a solid foundation in probability and statistics, which are essential for success in this role.

See salaries and explore the career path for Actuary

Investment Banker

Investment Bankers help companies raise capital and advise on mergers and acquisitions. The Python for Financial Analysis and Algorithmic Trading course would be useful for an Investment Banker, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and matplotlib for data analysis and visualization. This course would also provide a solid foundation in financial modeling and valuation, which are essential for success in this role.

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Software Engineer

Software Engineers design, develop, and maintain software applications. The Python for Financial Analysis and Algorithmic Trading course would be useful for a Software Engineer, as it will teach the basics of Python, as well as how to use NumPy, Pandas, and matplotlib for data analysis and visualization. This course would also provide a solid foundation in object-oriented programming and software design, which are essential for success in this role.

See salaries and explore the career path for Software Engineer