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Ryan Ahmed
In this project, we will use Python to perform stocks analysis such as calculating stock beta and expected returns using the Capital Asset Pricing Model (CAPM). CAPM is one of the most important models in Finance and it describes the relationship between the expected return and risk of securities. We will analyze the performance of several companies such as Facebook, Netflix, Twitter and AT&T over the past 7 years. This project is crucial for investors who want to properly manage their portfolios, calculate expected returns, risks, visualize datasets, find useful patterns, and gain valuable insights. This project could be practically used for analyzing company stocks, indices or currencies and performance of portfolio.
Read more
In this project, we will use Python to perform stocks analysis such as calculating stock beta and expected returns using the Capital Asset Pricing Model (CAPM). CAPM is one of the most important models in Finance and it describes the relationship between the expected return and risk of securities. We will analyze the performance of several companies such as Facebook, Netflix, Twitter and AT&T over the past 7 years. This project is crucial for investors who want to properly manage their portfolios, calculate expected returns, risks, visualize datasets, find useful patterns, and gain valuable insights. This project could be practically used for analyzing company stocks, indices or currencies and performance of portfolio.
Read more
In this project, we will use Python to perform stocks analysis such as calculating stock beta and expected returns using the Capital Asset Pricing Model (CAPM). CAPM is one of the most important models in Finance and it describes the relationship between the expected return and risk of securities. We will analyze the performance of several companies such as Facebook, Netflix, Twitter and AT&T over the past 7 years. This project is crucial for investors who want to properly manage their portfolios, calculate expected returns, risks, visualize datasets, find useful patterns, and gain valuable insights. This project could be practically used for analyzing company stocks, indices or currencies and performance of portfolio.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/l8mbdz/python
What's inside
Syllabus
Portfolio Assets Allocation and Statistical Data Analysis
In this project, we will use Python to perform stocks analysis such as calculating stock beta and expected returns using the Capital Asset Pricing Model (CAPM). CAPM is one of the most important models in Finance and it describes the relationship between the expected return and risk of securities. We will analyze the performance of several companies such as Facebook, Netflix, Twitter and AT&T over the past 7 years. This project is crucial for investors who want to properly manage their portfolios, calculate expected returns, risks, visualize datasets, find useful patterns, and gain valuable insights. This project could be practically used for analyzing company stocks, indices or currencies and performance of portfolio.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers statistical data analysis, which is standard in the finance industry
Teaches portfolio asset allocation, which helps investors manage their portfolios effectively
Uses Python for stocks analysis, which is a valuable skill for finance professionals
Focuses on the Capital Asset Pricing Model (CAPM), which is fundamental in finance for understanding the relationship between expected return and risk
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Save Python for Finance: Beta and Capital Asset Pricing Model to your list so you can find it easily later:
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Reviews summary
Well-received finance course
Learners say this Python course on finance is well-received. The course is engaging and provides helpful lessons on financial modeling.
Course is engaging
"Smart course"
"Excellent and engaging"
Teaches financial modeling
"Excellent... Teaches you how to actually use python for finance"
"Muy bueno como iniciación para modelación financiera"
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 Finance: Beta and Capital Asset Pricing Model with these
activities:
Follow a tutorial on using Python for stock analysis
Show steps
This activity will help you learn how to use Python for stock analysis by providing you with a step-by-step tutorial.
Browse courses on
Python
Show steps
-
Find a tutorial on using Python for stock analysis
-
Follow the tutorial and complete the exercises
Role play as a portfolio manager
Show steps
This activity will help you develop your skills in managing a portfolio, making financial decisions, and understanding the relationship between expected return and risk.
Browse courses on
Portfolio Management
Show steps
-
Establish investment goals, risk tolerance, and time horizon
-
Research and select stocks for your portfolio
-
Calculate expected returns and risks for your portfolio
-
Monitor and adjust your portfolio as needed
Analyze historical stock data
Show steps
This activity will help you improve your skills in analyzing historical stock data and identifying trends and patterns.
Browse courses on
Stock Analysis
Show steps
-
Gather historical stock data for a particular company
-
Clean and preprocess the data
-
Perform exploratory data analysis to identify trends and patterns
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend a local investing meetup
Show steps
This activity will help you connect with other investors and learn about different investment strategies.
Browse courses on
Investing
Show steps
-
Find a local investing meetup
-
Attend the meetup and introduce yourself to people
Write a blog post about stock analysis
Show steps
This activity will help you solidify your understanding of stock analysis and financial modeling by requiring you to write a blog post about these topics.
Browse courses on
Stock Analysis
Show steps
-
Choose a topic related to stock analysis
-
Research the topic and gather relevant data
-
Write a blog post that explains the topic clearly and concisely
Attend a workshop on portfolio management
Show steps
This activity will help you learn about the different aspects of portfolio management.
Browse courses on
Portfolio Management
Show steps
-
Find a workshop on portfolio management
-
Attend the workshop and take notes
Create a cheat sheet of key concepts
Show steps
This activity will help you consolidate your knowledge of stock analysis and financial modeling by creating a cheat sheet of key concepts.
Browse courses on
Stock Analysis
Show steps
-
Identify the key concepts from the course
-
Create a cheat sheet that summarizes the key concepts
Follow a tutorial on using Python for stock analysis
Show steps
This activity will help you learn how to use Python for stock analysis by providing you with a step-by-step tutorial.
Browse courses on
Python
Show steps
Show steps
Show steps
- Find a tutorial on using Python for stock analysis
- Follow the tutorial and complete the exercises
Role play as a portfolio manager
Show steps
This activity will help you develop your skills in managing a portfolio, making financial decisions, and understanding the relationship between expected return and risk.
Browse courses on
Portfolio Management
Show steps
Show steps
Show steps
- Establish investment goals, risk tolerance, and time horizon
- Research and select stocks for your portfolio
- Calculate expected returns and risks for your portfolio
- Monitor and adjust your portfolio as needed
Analyze historical stock data
Show steps
This activity will help you improve your skills in analyzing historical stock data and identifying trends and patterns.
Browse courses on
Stock Analysis
Show steps
Show steps
Show steps
- Gather historical stock data for a particular company
- Clean and preprocess the data
- Perform exploratory data analysis to identify trends and patterns
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend a local investing meetup
Show steps
This activity will help you connect with other investors and learn about different investment strategies.
Browse courses on
Investing
Show steps
Show steps
Show steps
- Find a local investing meetup
- Attend the meetup and introduce yourself to people
Write a blog post about stock analysis
Show steps
This activity will help you solidify your understanding of stock analysis and financial modeling by requiring you to write a blog post about these topics.
Browse courses on
Stock Analysis
Show steps
Show steps
Show steps
- Choose a topic related to stock analysis
- Research the topic and gather relevant data
- Write a blog post that explains the topic clearly and concisely
Attend a workshop on portfolio management
Show steps
This activity will help you learn about the different aspects of portfolio management.
Browse courses on
Portfolio Management
Show steps
Show steps
Show steps
- Find a workshop on portfolio management
- Attend the workshop and take notes
Create a cheat sheet of key concepts
Show steps
This activity will help you consolidate your knowledge of stock analysis and financial modeling by creating a cheat sheet of key concepts.
Browse courses on
Stock Analysis
Show steps
Show steps
Show steps
- Identify the key concepts from the course
- Create a cheat sheet that summarizes the key concepts
Career center
Learners who complete Python for Finance: Beta and Capital Asset Pricing Model will develop knowledge and skills
that may be useful to these careers:
Financial Analyst
Financial Analyst
Python is used by Financial Analysts to perform financial modeling, data analysis, and risk management. This course will enable you to use Python to calculate stock beta and expected returns using the Capital Asset Pricing Model (CAPM). Financial Analysts often rely on CAPM to assess the risk and return of investment opportunities.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use Python to develop and implement mathematical models for financial analysis and trading. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Quantitative Analysts who need to analyze large amounts of data to make informed investment decisions.
Portfolio Manager
Portfolio Manager
Portfolio Managers use Python to manage investment portfolios, including stocks, bonds, and other financial instruments. This course will provide you with the skills to use Python to calculate expected returns and risks, and to create visualizations that can help you make informed investment decisions.
Risk Manager
Risk Manager
Risk Managers use Python to identify, assess, and manage financial risks. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Risk Managers who need to analyze large amounts of data to identify and mitigate risks.
Investment Banker
Investment Banker
Investment Bankers use Python to value companies, analyze financial statements, and create financial models. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Investment Bankers who need to analyze large amounts of data to make informed investment decisions.
Financial Consultant
Financial Consultant
Financial Consultants use Python to provide financial advice to individuals and businesses. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Financial Consultants who need to analyze large amounts of data to provide informed financial advice.
Data Scientist
Data Scientist
Data Scientists use Python to analyze large amounts of data, including financial data. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Data Scientists who need to analyze large amounts of data to identify trends and make predictions.
Auditor
Auditor
Auditors use Python to perform financial audits and to ensure that companies are complying with financial regulations. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Auditors who need to analyze large amounts of data to identify financial fraud and other irregularities.
Actuary
Actuary
Actuaries use Python to assess financial risks and to develop insurance products. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Actuaries who need to analyze large amounts of data to assess risks and develop insurance products.
Financial Planner
Financial Planner
Financial Planners use Python to help clients plan for their financial future. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Financial Planners who need to analyze large amounts of data to create personalized financial plans.
Market Analyst
Market Analyst
Market Analysts use Python to analyze financial markets and to make investment recommendations. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Market Analysts who need to analyze large amounts of data to identify investment opportunities.
Credit Analyst
Credit Analyst
Credit Analysts use Python to assess the creditworthiness of borrowers and to make lending decisions. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Credit Analysts who need to analyze large amounts of data to assess risks and make lending decisions.
Insurance Analyst
Insurance Analyst
Insurance Analysts use Python to analyze the financial risks of insurance companies and to develop insurance products. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Insurance Analysts who need to analyze large amounts of data to assess risks and develop insurance products.
Compliance Officer
Compliance Officer
Compliance Officers use Python to ensure that companies are complying with financial regulations. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Compliance Officers who need to analyze large amounts of data to identify financial fraud and other irregularities.
Stockbroker
Stockbroker
Stockbrokers use Python to analyze financial markets and to make investment recommendations to clients. This course will help you build skills in using Python to perform statistical data analysis, visualize datasets, and find useful patterns. These skills are essential for Stockbrokers who need to analyze large amounts of data to identify investment opportunities.
For more career information including salaries, visit:
OpenCourser.com/course/l8mbdz/python
Reading list
We've selected ten books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Python for Finance: Beta and Capital Asset Pricing Model.
Provides a comprehensive overview of quantitative equity investing techniques and strategies commonly used by investment professionals to make investment decisions, for example, stock selection and portfolio construction.
Classic in the field of investing and provides a valuable foundation for understanding the principles of value investing, a strategy that involves buying stocks that are trading at a discount to their intrinsic value.
Is another classic in the field of investing and provides a comprehensive guide to security analysis, covering topics such as financial statement analysis, valuation techniques, and risk assessment.
Save
Provides a clear and concise overview of the principles of index investing, a strategy that involves investing in a broad market index, such as the S&P 500, rather than trying to pick individual stocks.
Provides a comprehensive overview of the principles and practices of portfolio management, including topics such as investment objectives, asset allocation, and performance measurement.
Provides a theoretical framework for understanding the value of investments and how to make investment decisions.
Provides a practical guide to using machine learning techniques in asset management, covering topics such as data preprocessing, model selection, and performance evaluation.
Provides a detailed explanation of the Black-Scholes option pricing model, a mathematical model for pricing options.
Provides a comprehensive overview of the markets for options, futures, and other derivatives.
Provides a comprehensive overview of the principles and practices of risk management in financial institutions.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/l8mbdz/python
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Effort
2 hours
Level
Introductory
Via
Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Language
English
Good to know
Covers statistical data analysis, which is standard in the finance industry
Teaches portfolio asset allocation, which helps investors manage their portfolios effectively
Uses Python for stocks analysis, which is a valuable skill for finance professionals
Focuses on the Capital Asset Pricing Model (CAPM), which is fundamental in finance for understanding the relationship between expected return and risk
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