Advanced Portfolio Construction and Analysis with Python from Coursera

The practice of investment management has been transformed in recent years by computational methods. Instead of merely explaining the science, we help you build on that foundation in a practical manner, with an emphasis on the hands-on implementation of those ideas in the Python programming language. In this course, we cover the estimation, of risk and return parameters for meaningful portfolio decisions, and also introduce a variety of state-of-the-art portfolio construction techniques that have proven popular in investment management and portfolio construction due to their enhanced robustness.

As we cover the theory and math in lecture videos, we'll also implement the concepts in Python, and you'll be able to code along with us so that you have a deep and practical understanding of how those methods work. By the time you are done, not only will you have a foundational understanding of modern computational methods in investment management, you'll have practical mastery in the implementation of those methods. If you follow along and implement all the lab exercises, you will complete the course with a powerful toolkit that you will be able to use to perform your own analysis and build your own implementations and perhaps even use your newly acquired knowledge to improve on current methods.

What's inside

Syllabus

Style & Factors

Robust estimates for the covariance matrix

Robust estimates for expected returns

Portfolio Optimization in Practice

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Taught by Claudia Carrone who is recognized for their work in factor models and asset pricing

Develops advanced portfolio techniques used to achieve more robust outcomes

Teaches specialized Python skills related to investment management

Offers hands-on labs to solidify theory and math behind investment management

The emphasis on practical implementation of concepts is valuable for learners who wish to apply these methods in their own work

Assumes learners already have a foundational understanding of investment management

Reviews summary

Quality python-based portfolio design

According to students, this course largely positive reviews for its combination of theory and practical application of portfolio construction techniques. It's engaging assignments and well-structured course content make it a valuable learning experience. The course is especially praised for its excellent instructors, high-quality Python code, and up-to-date material.

Python code is well-written and efficient.

"The course is great, its combine the teoritcal approach with an application in python."

"And compare the backtest result from the portfolio constructed within the different scenario."

"I guess it would be valuable both in career progression, or for personal portfolio construction."

Explanations are clear and engaging.

"Super clear explanations, combining intuitions with rigorous definitions for the pros and cons of each investment strategy."

"The theory is clear, and the lab sessions introduce you to well-designed Python code, thus the perfect combo for pragmatic learners :)"

Lab sessions are practical and informative.

"Really good one just like the first MOOC, however, the lab sessions are a bit more hands off, which is okay if you payed enough attention on the first course."

"The lab sessions covering coding in Python to translate theories in to practice are very informative and useful."

Course is well-organized and well-paced.

"This course is something special, it exceeds all expectations."

"The syllabus is very practical and actual, all methods taught in this course are modern and sophisticated."

Instructors are knowledgeable and experienced.

"Dr.Martellini explains state of the art techniques in a very interesting and comprehensible manner."

"I really loved this course."

"Lionel and Vijay are extremely personable and have a way of presenting difficult material in an easygoing and straightforward manner"

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 Advanced Portfolio Construction and Analysis with Python with these activities:

Review descriptive statistics

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Refresh your knowledge of descriptive statistics to strengthen your foundation for understanding investment management concepts.

Browse courses on Descriptive Statistics

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Review key concepts: mean, median, mode, range, and standard deviation
Solve practice problems on calculating these statistics from sample data

Organize and review course materials regularly

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Stay organized and enhance your learning by regularly reviewing and consolidating course materials.

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Create a system for organizing notes, assignments, and resources
Set aside time each week or month to review and consolidate your materials
Summarize key concepts and create your own study guides

Practice portfolio optimization using Excel or Python

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Reinforce your understanding of portfolio optimization techniques by practicing with real-world data.

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Download historical stock data from a financial database
Calculate portfolio returns and risks using Excel or Python
Plot the efficient frontier and identify optimal portfolios

Five other activities

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Tutor or mentor a beginner in investment management

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Deepen your understanding of investment management by explaining concepts to others and answering their questions.

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Volunteer as a tutor or mentor at a local college or community center
Prepare lesson plans and materials to explain investment management concepts
Provide guidance and support to mentees

Create a Python script to automate data analysis and visualization

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Enhance your technical skills by automating data analysis and visualization tasks using Python.

Browse courses on Python Programming

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Learn the basics of Python data manipulation and visualization libraries
Develop a Python script to import, clean, and analyze investment data
Create interactive visualizations to present your findings

Participate in an investment simulation competition

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Test your skills in a simulated investment environment and compete against other participants to improve your decision-making abilities.

Browse courses on Portfolio Management

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Join an online or in-person investment simulation competition
Develop and implement a trading strategy
Monitor and adjust your strategy based on market conditions
Evaluate your performance and learn from your experience

Contribute to an open-source project in computational finance

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Gain hands-on experience in computational finance and contribute to the open-source community.

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Identify an open-source project in computational finance that aligns with your interests
熟悉项目代码和文档
Develop and submit a pull request with your contributions

Design and implement an investment strategy based on course concepts

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Apply your knowledge to develop a practical investment strategy that meets specific investment goals.

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Define investment objectives and risk tolerance
Research and select appropriate investment vehicles
Create a written investment plan outlining your strategy

Career center

Learners who complete Advanced Portfolio Construction and Analysis with Python will develop knowledge and skills that may be useful to these careers:

Portfolio Manager

Portfolio Managers are responsible for making decisions about how to invest funds, and this course can give you a foundation in implementing those decisions. The course will teach you how to estimate risk and return so you can make better choices and build a more successful investment portfolio.

See salaries and explore the career path for Portfolio Manager

Quantitative Analyst

Quantitative Analysts use analytical tools and statistical techniques to develop models that estimate risk and returns. This course teaches you the same skills, and you can use your training to build more effective investment models. This course's focus on the Python programming language means you'll be able to implement advanced methods in your own work. Since the course concentrates on practical application, you should be able to be more productive as a Quantitative Analyst as you'll quickly be able to make use of the methods you learn.

See salaries and explore the career path for Quantitative Analyst

Financial Analyst

Financial Analysts must understand how to evaluate stocks, and this course will help you understand this in more depth. Learn how to calculate risk and return and implement those ideas through coding. You'll also learn about different portfolio construction techniques to help you excel in your role.

See salaries and explore the career path for Financial Analyst

Investment Strategist

Investment Strategists develop and implement investment strategies for clients. This course will help you develop the skills you need to be successful in this role. Learn how to estimate risk and return, and how to use Python to implement your own investment strategies. This course provides a useful foundation for anyone looking to build a career in investment strategy.

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Risk Manager

Risk Managers help to identify and mitigate financial risks. This course will teach you how to estimate risk and will provide you with hands-on experience implementing those methods. The course is especially useful because it teaches you how to use Python to code your own risk management tools.

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Quantitative Researcher

Quantitative Researchers develop and implement quantitative models for investment purposes. This course can help you develop the skills you need to be successful in this role. Learn how to estimate risk and return, and how to use Python to implement your own quantitative models. This course is especially useful for Quantitative Researchers who want to work in the financial industry.

See salaries and explore the career path for Quantitative Researcher

Data Scientist

Data Scientists use data to solve business problems. This course can help you develop the skills you need to be successful in this role. You'll learn how to use Python to clean and analyze data, and how to build models to predict future outcomes. This course is especially useful for Data Scientists who want to work in the financial industry.

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Machine Learning Engineer

Machine Learning Engineers build and deploy machine learning models. This course can help you develop the skills you need to be successful in this role. You'll learn how to use Python to clean and analyze data, and how to build models to predict future outcomes. This course is especially useful for Machine Learning Engineers who want to work in the financial industry.

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Software Engineer

Software Engineers design, develop, and maintain software systems. This course can help you develop the skills you need to be successful in this role. You'll learn how to use Python to write code that is efficient, reliable, and secure. This course may help you get started on a career as a Software Engineer, and the focus on financial applications will make you a more competitive candidate for roles within the financial industry.

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Business Analyst

Business Analysts identify and solve business problems. This course can help you develop the skills you need to be successful in this role. You'll learn how to use data to analyze business problems and develop solutions. This course is especially useful for Business Analysts who want to work in the financial industry.

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Data Analyst

Data Analysts collect, clean, and analyze data. This course can help you develop the skills you need to be successful in this role. You'll learn how to use Python to clean and analyze data, and how to visualize data to communicate your findings. This course is especially useful for Data Analysts who want to work in the financial industry.

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Financial Planner

Financial Planners help individuals and families plan for their financial future. This course can help you develop the skills you need to be successful in this role. You'll learn how to estimate risk and return, and how to develop investment plans that meet your clients' needs. This course is especially useful for Financial Planners who want to work with high-net-worth individuals.

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Actuary

Actuaries use mathematics and statistics to assess risk and uncertainty. This course can help you develop the skills you need to be successful in this role. You'll learn how to estimate risk and return, and how to develop models to predict future outcomes. This course is especially useful for Actuaries who want to work in the insurance industry.

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Economist

Economists study the economy and how it works. This course can help you develop the skills you need to be successful in this role. You'll learn how to estimate risk and return, and how to develop models to predict future outcomes. This course is especially useful for Economists who want to work in the financial industry.

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Statistician

Statisticians collect, analyze, and interpret data. This course can help you develop the skills you need to be successful in this role. You'll learn how to use Python to clean and analyze data, and how to visualize data to communicate your findings. This course is especially useful for Statisticians who want to work in the financial industry.

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