What will you in Modeling Risk and Realities Course
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Build optimization models for low-uncertainty scenarios using tools like Excel Solver.
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Incorporate risk into models through probability distributions and scenario analysis.
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Select appropriate probability distributions based on data characteristics.
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Utilize simulation techniques to evaluate decisions under uncertainty.
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Apply sensitivity analysis to understand the impact of variable changes on outcomes.
Program Overview
1. Modeling Decisions in Low Uncertainty Settings
⏱ Duration: ~1 hour
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Introduction to optimization models in deterministic environments.
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Building algebraic models and translating them into spreadsheet models.
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Utilizing Excel Solver to identify optimal decisions.
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Introducing basic risk elements into models.
2. Risk and Reward: Modeling High Uncertainty Settings
⏱ Duration: ~1 hour
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Understanding high-uncertainty scenarios and associated risks.
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Incorporating probability distributions and correlations into models.
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Conducting sensitivity analysis and exploring the efficient frontier.
3. Choosing Distributions that Fit Your Data
⏱ Duration: ~2 hours
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Visualizing data to identify suitable probability distributions.
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Differentiating between discrete and continuous distributions.
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Performing hypothesis testing to assess goodness of fit.
4. Balancing Risk and Reward Using Simulation
⏱ Duration: ~1 hour
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Implementing simulation techniques to model uncertainty.
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Analyzing simulation outputs to inform decision-making.
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Comparing alternative decisions based on simulation results.
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Job Outlook
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Enhances capabilities in roles requiring risk assessment and decision modeling.
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Applicable to careers in finance, operations, data analysis, and strategic planning.
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Provides foundational skills for positions involving quantitative analysis and forecasting.
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Related Reading
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What Is Risk Management? – Learn the key principles and strategies used to identify, assess, and mitigate risks in business and finance.
