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David Hsieh

This course teaches you how to calculate the return of a portfolio of securities as well as quantify the market risk of that portfolio, an important skill for financial market analysts in banks, hedge funds, insurance companies, and other financial services and investment firms. Using the R programming language with Microsoft Open R and RStudio, you will use the two main tools for calculating the market risk of stock portfolios: Value-at-Risk (VaR) and Expected Shortfall (ES). You will need a beginner-level understanding of R programming to complete the assignments of this course.

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What's inside

Syllabus

Introduction to R, Data Retrieval, and Return Calculation
This module goes over the versions of R (R Studio and Microsoft Open R), the data source (FRED at the Federal Reserve Bank of St. Louis), and the calculation of returns.
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Risk Management under Normal Distributions
This module covers how to calculate value-at-risk (VaR) and expected shortfall (ES) when returns are normally distributed.
Risk Management under Non-normal Distributions
This module covers how to test for normality of returns, and how to calculate value-at-risk (VaR) and expected shortfall (ES) when returns are not normally distributed.
Risk Management under Volatility Clustering
This module covers how to test for the presence of volatility clustering, and how to calculate value-at-risk (VaR) and expected shortfall (ES) when returns exhibit volatility clustering.

Good to know

Know what's good
, what to watch for
, and possible dealbreakers
Covers the return of a portfolio of securities and measures its market risk
Taught by David Hsieh
Helps financial market analysts and firms quantify market risk
Uses Microsoft Open R and RStudio for the two key ways to calculate market risk
Requires at least a beginner's understanding of R programming

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Reviews summary

Engaging r-based financial risk management course

According to students, this course is largely positive and engaging, offering a solid introduction to financial risk management using R. Learners say that the course is well-structured and the instructor provides clear explanations. While some students found the difficulty level appropriate, others felt that it was too advanced for beginners or those without a strong background in statistics or finance. Overall, learners who enjoyed the course highlighted the practical and hands-on approach, with the use of R to apply concepts to real-world examples.
Well-organized and engaging
"This course has been very well planned and structured. I enjoyed taking it."
"Really great course! Just loved how clearly professor explained everything :)"
"It's been an amazing journey in the field of financial risk management. It provided me with additional knowledge to improve my technical skills in the field of financial risk management."
Moderate to challenging
"Challenging, but worthwhile -- would recommend approaching over weeks, and not rushing through."
"It`s a difficult curse. You learn a lot about R programming and statistics."
"The course is great and useful. But there are a few minor problems that are needed to fix: [...] The materials covered in the course are a bit simple for financing-majored students, the scope of the course is also a bit narrow, all the course is about the VaR and ES."
Knowledgeable and engaging
"The concepts are beautifully explained. This course requires basic understanding of Risk management and R coding. Thank you for such a good learning experience. Best of Luck"
"Excellent course, it deals adequately with each concept of risk management, in a concrete and simple way."
"Really great course! Just loved how clearly professor explained everything :)"
Hands-on practice and clear explanations
"I learnt a lot of concepts and how to implement those concept in R. Highly recommended if you are into technical risk management for financial portfolio."
"This was a very insightful course. As someone who has an extensive coding background and use of R programming, the assignments helped enhanced my understanding of new material to me: VaR, Es, GARCH, etc."
"It is an excellent option to learn and review the basic concepts to analyze financial data."
Practical and relevant to real-world scenarios
"Very practical and straight to the point."
"I work in the investment department of a commercial bank. This course was very useful for me."
"One of the best courses on Financial Risk Management on R starting right from the basics and going in-depth to cover the areas of Risk management transitioning smoothly for a new comer to understand the field."

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 Financial Risk Management with R with these activities:
Review basic statistics and probability
Review basic statistics and probability concepts to strengthen your foundation for this course.
Browse courses on Statistics
Show steps
  • Review notes or textbooks on descriptive statistics.
  • Practice solving probability problems.
  • Take a refresher course or watch online tutorials on statistics and probability.
Follow tutorials on R programming for financial analysis
Enhance your R programming skills for financial analysis by following step-by-step tutorials.
Browse courses on R Programming
Show steps
  • Find online resources or tutorials on R programming for finance.
  • Follow the instructions to install the necessary packages.
  • Work through the examples provided in the tutorials.
Attend networking events for financial professionals
Attend networking events to connect with professionals in the financial industry and explore career opportunities.
Browse courses on Networking
Show steps
  • Identify and RSVP to networking events relevant to your interests.
  • Prepare an elevator pitch and practice your networking skills.
  • Attend the event, introduce yourself to others, and actively engage in conversations.
Five other activities
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Show all eight activities
Practice calculating returns and risk metrics
Reinforce your understanding of calculating returns and risk metrics by practicing with real-world data.
Browse courses on Portfolio Management
Show steps
  • Download historical stock data from a reputable source.
  • Calculate the daily returns using the provided formulas.
  • Calculate value-at-risk (VaR) and expected shortfall (ES) using the methods taught in the course.
Attend a workshop on financial risk management
Attend a workshop to learn from experts and gain practical insights into financial risk management.
Browse courses on Risk Management
Show steps
  • Identify and register for relevant workshops in your area or online.
  • Attend the workshop and actively participate in discussions.
  • Network with other participants and industry professionals.
Create a visualization of portfolio risk-return characteristics
Visualize the risk-return characteristics of a portfolio to gain deeper insights and improve your decision-making.
Browse courses on Data Visualization
Show steps
  • Gather data on portfolio returns and risk metrics.
  • Choose an appropriate data visualization tool, such as Python's Matplotlib or Seaborn.
  • Create visualizations that depict the portfolio's historical performance, risk levels, and return distributions.
Contribute to open-source projects in financial modeling
Deepen your understanding of financial modeling practices by contributing to open-source projects.
Browse courses on Open Source
Show steps
  • Identify open-source projects in financial modeling on platforms like GitHub.
  • Explore the project's documentation and codebase.
  • Identify areas where you can contribute, such as improving existing features or adding new functionality.
Develop a financial risk management plan for a real-world portfolio
Apply your knowledge to develop a comprehensive financial risk management plan for a real-world portfolio.
Browse courses on Risk Management
Show steps
  • Research and select a real-world portfolio to analyze.
  • Gather data on the portfolio's assets, risk exposures, and return objectives.
  • Develop a risk management plan that includes strategies for mitigating risks and optimizing returns.

Career center

Learners who complete Financial Risk Management with R will develop knowledge and skills that may be useful to these careers:
Quantitative Risk Analyst
Quantitative Risk Analysts apply statistical methods to assess and manage financial risks. They use their knowledge of mathematics, statistics, and computer programming to develop models that can predict the likelihood and severity of different types of financial risks. Courses like Financial Risk Management with R can provide Quantitative Risk Analysts with the skills they need to develop these models.
Risk Manager
Risk Managers identify, assess, and mitigate financial risks. They work with senior management to develop risk management strategies and policies. Courses like Financial Risk Management with R can provide Risk Managers with the skills they need to understand and quantify financial risks. This can help them to make more informed decisions about how to allocate capital.
Financial Analyst
Financial Analysts provide investment advice to individuals and institutions. They use their knowledge of financial markets and economics to assess the risks and rewards of different investments. Courses like Financial Risk Management with R can provide Financial Analysts with the skills they need to understand and quantify financial risks. This can help them to make more informed investment decisions.
Actuary
Actuaries use mathematics and statistics to assess financial risks. They work with insurance companies, pension funds, and other financial institutions to develop products and services that help to protect against financial risks. Courses like Financial Risk Management with R can provide Actuaries with the skills they need to understand and quantify financial risks.
Data Scientist
Data Scientists use data to solve business problems. They work with large datasets to identify patterns and trends that can be used to make better decisions. Courses like Financial Risk Management with R can provide Data Scientists with the skills they need to manage financial data.
Software Engineer
Software Engineers design, develop, and maintain software applications. They work with businesses to understand their needs and develop software solutions that meet those needs. Courses like Financial Risk Management with R can provide Software Engineers with the skills they need to develop software applications for the financial industry.
Quantitative Trader
Quantitative Traders use mathematical models to trade financial instruments. They work with large datasets to identify trading opportunities. Courses like Financial Risk Management with R can provide Quantitative Traders with the skills they need to develop and implement trading models.
Hedge Fund Manager
Hedge Fund Managers manage investment funds that invest in a variety of financial instruments. They use their knowledge of financial markets and economics to make investment decisions. Courses like Financial Risk Management with R can provide Hedge Fund Managers with the skills they need to understand and quantify financial risks. This can help them to make more informed investment decisions.
Portfolio Manager
Portfolio Managers manage investment portfolios for individuals and institutions. They use their knowledge of financial markets and economics to make investment decisions. Courses like Financial Risk Management with R can provide Portfolio Managers with the skills they need to understand and quantify financial risks.
Financial Planner
Financial Planners help individuals and families plan for their financial future. They provide advice on investments, retirement planning, and other financial matters. Courses like Financial Risk Management with R can provide Financial Planners with the skills they need to understand and quantify financial risks.
Insurance Agent
Insurance Agents sell insurance policies to individuals and businesses. They help clients identify their insurance needs and find the best policies to meet those needs. Courses like Financial Risk Management with R can provide Insurance Agents with the skills they need to understand and quantify financial risks.
Banker
Bankers provide financial services to individuals and businesses. They help clients with a variety of financial needs, such as borrowing money, saving money, and managing investments. Courses like Financial Risk Management with R can provide Bankers with the skills they need to understand and quantify financial risks
Accountant
Accountants prepare and maintain financial records for individuals and businesses. They also provide advice on tax and financial planning. Courses like Financial Risk Management with R may be useful for Accountants who want to specialize in financial risk management.
Economist
Economists study the production, distribution, and consumption of goods and services. They use their knowledge of economics to analyze economic data and make predictions about the future. Courses like Financial Risk Management with R may be useful for Economists who want to specialize in financial risk management.
Statistician
Statisticians collect, analyze, and interpret data. They use their knowledge of statistics to solve problems in a variety of fields, including finance, healthcare, and marketing. Courses like Financial Risk Management with R may be useful for Statisticians who want to specialize in financial risk management.

Reading list

We've selected six 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 Financial Risk Management with R.
This handbook provides a comprehensive overview of financial risk management, including chapters on VaR and ES.
This textbook provides a comprehensive overview of risk management in financial institutions, including coverage of VaR and ES.
Provides a comprehensive overview of risk management in finance, including chapters on VaR and ES.
Provides a comprehensive overview of market risk analysis, including chapters on VaR and ES.
Provides a comprehensive overview of extreme value theory, which is used in the calculation of VaR and ES.

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