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Python for Finance
Portfolio Statistical Data Analysis
Ryan Ahmed
Ryan Ahmed
In this project, we will use the power of python to perform portfolio allocation and statistically analyze the performance of portfolio using metrics such as cumulative return, average daily returns and Sharpe ratio. We will analyze the performance of...
Read more
In this project, we will use the power of python to perform portfolio allocation and statistically analyze the performance of portfolio using metrics such as cumulative return, average daily returns and Sharpe ratio. We will analyze the performance of...
Read more
In this project, we will use the power of python to perform portfolio allocation and statistically analyze the performance of portfolio using metrics such as cumulative return, average daily returns and Sharpe ratio. We will analyze the performance of following companies: Facebook, Netflix and Twitter over the past 7 years. This project is crucial for investors who want to properly manage their portfolios, visualize datasets, find useful patterns, and gain valuable insights such as stock daily returns and risks. 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/x7p27j/python
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Explores portfolio allocation, a core skill for investors
Provides valuable insights such as stock daily returns and risks
Uses Python for portfolio allocation, a standard in the finance industry
Teaches data analysis and visualization, skills useful for making informed investment decisions
Covers performance analysis over the past 7 years
Suitable for beginners looking to learn about portfolio management and data analysis
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Save Python for Finance: Portfolio Statistical Data Analysis to your list so you can find it easily later:
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Reviews summary
Practical python for finance professionals
This course is a practical guide to using Python for portfolio allocation and statistical analysis of portfolio performance. It is well-suited for beginners who are new to Python.
Easy to follow explanations and step-by-step instructions.
"Author is very clear in the explanations and everything is done step by step."
Suitable for beginners with little to no Python experience.
"Just what I needed as a practitioner who's relatively new to Python."
Focuses on practical applications for finance professionals.
"This project is crucial for investors who want to properly manage their portfolios, visualize datasets, find useful patterns, and gain valuable insights such as stock daily returns and risks."
May be too basic for experienced Python users.
"Very basic course where simple tasks has been performed."
Activities
Coming soon
We're preparing activities for
Python for Finance: Portfolio Statistical Data Analysis.
These are activities you can do either before, during, or after a course.
Career center
Learners who complete Python for Finance: Portfolio Statistical Data Analysis will develop knowledge and skills
that may be useful to these careers:
Portfolio Manager
Portfolio Manager
Portfolio Managers analyze investments and make decisions on how to allocate funds. They use this information to create a portfolio that meets the needs of their clients. This course will directly teach Portfolio Managers how to do their job because it is focused on portfolio allocation and statistical data analysis of portfolio performance.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data. They often use statistical techniques to find patterns and trends in data. This course will be useful to Data Analysts because it will teach them how to analyze financial data and use it to make better decisions.
Investment Analyst
Investment Analyst
Investment Analysts collect and analyze data to make recommendations on which investments to buy or sell. One of their primary tasks is to analyze financial data to identify trends and patterns. This course will be useful to Investment Analysts because it will teach them how to do data analysis and risk assessment.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts create mathematical models to analyze financial data. They are in charge of developing and implementing trading strategies. This course will be useful to Quantitative Analysts because one of their top responsibilities is to statistically analyze data and find anomalies and trends. Completing this course will help build a strong foundation for aspiring Quantitative Analysts on how to accomplish these tasks.
Statistician
Statistician
Statisticians collect and analyze data to draw conclusions about the world around us. Statisticians often work with financial data to help businesses make decisions. This course will be useful to Statisticians because it will introduce them to the principles of finance and portfolio management.
Economist
Economist
Economists study economic trends and make predictions about the future. Economists often work with large amounts of data and use statistical analysis to make their predictions. This course will be useful to Economists because it will help them develop the skills necessary to do this.
Financial Analyst
Financial Analyst
Financial Analysts and advisors develop and maintain plans for businesses. They often help individual clients manage their money. Having a strong foundation in portfolio allocation, statistical data analysis, and cumulative returns is crucial for success in this role. Therefore, taking this course may be helpful for those who want to become Financial Analysts.
Data Scientist
Data Scientist
Data Scientists collect, clean, analyze, and interpret data to find useful patterns and trends. This course will help build a foundation for those who aspire to become Data Scientists on how to do this. They can then apply these skills when analyzing financials and other data for their company.
Financial Planner
Financial Planner
Financial Planners help individuals and businesses manage their finances. The work involves analyzing a client's financial situation, goals, and risk tolerance. This course will be useful to Financial Planners because it will help them build a foundation in how to analyze and interpret financial data and use it to create a financial plan.
Actuary
Actuary
Actuaries assess and manage financial risks. Being able to analyze financial data is essential for Actuaries, as well as understanding portfolio allocation and statistical data analysis. This course may be helpful for Actuaries in that it will help them build a foundation in these areas.
Consultant
Consultant
Consultants provide professional services to help businesses improve their performance. Consultants often have to analyze financial data and understand portfolio allocation and statistical data analysis. This course may be helpful for aspiring Consultants by providing them with the necessary skills to do this.
Trader
Trader
Traders buy and sell stocks, bonds, and other financial instruments. This course may be helpful for Traders because it teaches how to analyze financial data to make decisions on which investments to buy or sell.
Auditor
Auditor
Auditors examine and verify financial records for accuracy and compliance. Auditors rely on financial data to ensure that it is presented accurately and fairly. This course will help build a good foundation for Auditors by teaching them how to analyze and interpret financial data.
Risk Manager
Risk Manager
Risk Managers identify and mitigate financial risks. This course may be helpful for Risk Managers because they are responsible for analyzing and evaluating financial risks, and this course will help teach them how to do this effectively using Python.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. Software Engineers often work with financial data and need to understand how to analyze it to develop software solutions. This course may be helpful for aspiring Software Engineers by providing them with the necessary skills to do this.
For more career information including salaries, visit:
OpenCourser.com/course/x7p27j/python
Reading list
We've selected 13 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: Portfolio Statistical Data Analysis.
Provides a comprehensive introduction to Python for data analysis, covering topics such as data manipulation, data visualization, and machine learning. It valuable resource for learners who want to gain a strong foundation in Python for data analysis.
Provides a practical introduction to machine learning using Python. It covers a wide range of topics, including supervised learning, unsupervised learning, and deep learning. It valuable resource for learners who want to gain a strong foundation in machine learning.
Provides a comprehensive introduction to machine learning using Python. It covers a wide range of topics, including supervised learning, unsupervised learning, and deep learning. It valuable resource for learners who want to gain a strong foundation in machine learning.
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Provides a comprehensive introduction to deep learning. It covers a wide range of topics, including convolutional neural networks, recurrent neural networks, and generative adversarial networks. It valuable resource for learners who want to gain a strong foundation in deep learning.
Provides a comprehensive introduction to data science for business. It covers topics such as data collection, data analysis, and data visualization. It valuable resource for learners who want to gain a strong foundation in data science for business.
Provides a comprehensive introduction to reinforcement learning. It covers a wide range of topics, including Markov decision processes, value functions, and policy iteration. It valuable resource for learners who want to gain a strong foundation in reinforcement learning.
Classic work on investing. It provides timeless principles for investing that have been used by successful investors for decades. It valuable resource for learners who want to gain a deep understanding of investing.
Provides a comprehensive introduction to Bayesian reasoning and machine learning. It covers a wide range of topics, including Bayesian inference, graphical models, and variational inference. It valuable resource for learners who want to gain a strong foundation in Bayesian reasoning and machine learning.
Is another classic work on investing. It provides a comprehensive framework for analyzing stocks and bonds. It valuable resource for learners who want to gain a deep understanding of security analysis.
Provides a comprehensive introduction to information theory, inference, and learning algorithms. It covers a wide range of topics, including entropy, mutual information, and Bayesian inference. It valuable resource for learners who want to gain a strong foundation in information theory, inference, and learning algorithms.
Provides a comprehensive introduction to convex optimization. It covers a wide range of topics, including linear programming, quadratic programming, and semidefinite programming. It valuable resource for learners who want to gain a strong foundation in convex optimization.
Provides a comprehensive introduction to quantitative equity investing. It covers topics such as factor models, portfolio optimization, and risk management. It valuable resource for learners who want to gain a strong foundation in quantitative equity investing.
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Concise guide to investing. It provides simple, practical advice that can help learners make better investment decisions. It valuable resource for learners who want to get started with investing.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/x7p27j/python
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Ryan Ahmed
Good to know
Explores portfolio allocation, a core skill for investors
Provides valuable insights such as stock daily returns and risks
Uses Python for portfolio allocation, a standard in the finance industry
Teaches data analysis and visualization, skills useful for making informed investment decisions
Covers performance analysis over the past 7 years
Suitable for beginners looking to learn about portfolio management and data analysis
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