Course Summary
Learn how to assess and manage financial risk in this course offered by the Wharton School of the University of Pennsylvania. Gain a thorough understanding of risk modeling techniques and their applications in finance.Key Learning Points
- Explore the fundamentals of risk modeling
- Learn how to apply risk modeling to investment management
- Discover techniques for managing risks in financial institutions
Job Positions & Salaries of people who have taken this course might have
- USA: $77,000
- India: ₹1,179,000
- Spain: €34,000
- USA: $77,000
- India: ₹1,179,000
- Spain: €34,000
- USA: $107,000
- India: ₹2,694,000
- Spain: €64,000
- USA: $77,000
- India: ₹1,179,000
- Spain: €34,000
- USA: $107,000
- India: ₹2,694,000
- Spain: €64,000
- USA: $115,000
- India: ₹3,121,000
- Spain: €74,000
Related Topics for further study
Learning Outcomes
- Master the techniques of risk modeling and its applications in finance
- Develop a thorough understanding of investment management and risk management in financial institutions
- Gain practical skills in data analysis and quantitative finance
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of statistics and probability theory
- Familiarity with financial markets and instruments
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Introduction to Financial Modeling
- Financial Engineering and Risk Management Part I
- Quantitative Finance and Risk Management
Notable People in This Field
- Nassim Nicholas Taleb
- Harry Markowitz
Related Books
Description
Useful quantitative models help you to make informed decisions both in situations in which the factors affecting your decision are clear, as well as in situations in which some important factors are not clear at all. In this course, you can learn how to create quantitative models to reflect complex realities, and how to include in your model elements of risk and uncertainty. You’ll also learn the methods for creating predictive models for identifying optimal choices; and how those choices change in response to changes in the model’s assumptions. You’ll also learn the basics of the measurement and management of risk. By the end of this course, you’ll be able to build your own models with your own data, so that you can begin making data-informed decisions. You’ll also be prepared for the next course in the Specialization.
Outline
- Week 1: Modeling Decisions in Low Uncertainty Settings
- Course Introduction
- 1.1 How To Build an Optimization Model: Hudson Readers Ad Campaign
- 1.2 Optimizing with Solver, and Alternative Data Inputs
- 1.3 Adding Risk: Managing Investments at Epsilon Delta Capital
- PDFs of Slides for Week 1
- Excel Files for Week 1
- Week 1: Modeling in Low Uncertainty Quiz
- Week 2: Risk and Reward: Modeling High Uncertainty Settings
- 2.1 High Uncertainty Settings, Probability Distributions, Uncertainty and Risk
- 2.2 Common Scenarios for Multiple Random Variables, Risk Reduction, and Calculating and Interpreting Correlation Values
- 2.3 Using Scenarios for Optimizing Under High Uncertainty, Sensitivity Analysis and Efficient Frontier
- PDFs of Lecture Slides for Week 2
- Excel Files for Week 2
- Week 2: Modeling in High Uncertainty Quiz
- Week 3: Choosing Distributions that Fit Your Data
- 3.1 Data and Visualization: Graphical Representation
- 3.2, pt 1: Choosing Among Distributions: Discrete Distributions
- 3.2, pt 2: Choosing Among Distributions: Continuous Distributions
- 3.3 Hypothesis Testing and Goodness of Fit
- PDFs of Lecture Slides for Week 3
- Excel Files for Week 3
- Week 3: Choosing Fitting Distributions Quiz
- Week 4: Balancing Risk and Reward Using Simulation
- 4.1: Modeling Uncertainty: From Scenarios to Continuous Distributions
- 4.2 Connecting Random Inputs and Random Outputs in a Simulation
- 4.3 Analyzing and Interpreting Simulation Output: Evaluating Alternatives Using Simulation Results
- Course Conclusion
- PDFs of Lecture Slides
- Excel files for Week 4
- Week 4: Using Simulations Quiz
Summary of User Reviews
Discover the Wharton Risk Management and Decision Processes Center's models for anticipating and quantifying risk, and learn how to apply them to real-world situations. Students praise the course for its practical approach to risk modeling.Key Aspect Users Liked About This Course
Practical approach to risk modelingPros from User Reviews
- Real-world examples and case studies
- Hands-on exercises and quizzes
- Instruction by Wharton faculty
Cons from User Reviews
- Some technical jargon may be difficult to understand for beginners
- Course may be too basic for advanced risk management professionals
- Limited interaction with instructors and peers
Sergei Savin
4.6 Raiting
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