This course introduces learners to Monte Carlo simulation as a powerful tool for modeling uncertainty and forecasting financial outcomes. It explores probability distributions, scenario generation, valuation techniques, and risk analysis applied to investments and corporate finance. Students learn to build simulations using practical examples that reveal the range of possible market behaviors. Designed for analysts and data-driven professionals, the course enhances decision-making by incorporating randomness and statistical rigor into financial modeling.
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Skills & learning objectives
There are 8 modules in this class
- What is Financial Modeling?Unlock this class to watch9m 26s
- Setting Up the Financial ModelUnlock this class to watch5m 58s
- Links Between the Financial StatementsUnlock this class to watch1m 59s
- Overview of Risk ModelingUnlock this class to watch8m 3s
- Excel Functions for Financial ModelingUnlock this class to watch2m 57s
- Challenges and ConsiderationsUnlock this class to watch1m 9s
- Introduction to Monte Carlo Simulation in Financial ModelingUnlock this class to watch7m 12s
- Probability distributions and their characteristicsUnlock this class to watch7m 28s
- Random number generation and sampling techniquesUnlock this class to watch4m 13s
- Basics of Monte Carlo SimulationUnlock this class to watch2m 41s
- Algorithms used in Monte Carlo simulationsUnlock this class to watch59s
- Monte Carlo in Python — BasicsUnlock this class to watch2m 46s
- How Does a Monte Carlo Simulation Work?Unlock this class to watch1m 26s
- Applications of Monte Carlo SimulationsUnlock this class to watch1m 32s
- Pros and Cons of Monte Carlo SimulationsUnlock this class to watch1m 19s
- What is Model Risk and Why is it Important?Unlock this class to watch3m
- Introduction to Credit Risk ModelingUnlock this class to watch2m 42s
- Credit and UncertaintyUnlock this class to watch1m 11s
- Elements of Credit Risk ModelingUnlock this class to watch2m 27s
- Capital Adequacy RatioUnlock this class to watch4m 16s
- Credit Risk Assessment ApproachesUnlock this class to watch2m 39s
- The Black-Scholes ModelUnlock this class to watch4m 5s
- The KMV ModelUnlock this class to watch2m 8s
- The Credit Metrics ModelUnlock this class to watch4m 4s
- The CreditRisk+ ModelUnlock this class to watch1m 55s
- Risk-Adjusted Return on Capital (RAROC)Unlock this class to watch56s
- Credit Risk Models and AlgorithmsUnlock this class to watch58s
- Understanding Project Risk AnalysisUnlock this class to watch7m 9s
- Stress Testing and Scenario Analysis in Credit Risk ValidationUnlock this class to watch5m 21s
- Building Scenarios in ExcelUnlock this class to watch2m 42s
- Sensitivity Analysis Using Data TablesUnlock this class to watch3m 21s
- Advanced Topics in Financial ModelingUnlock this class to watch5m 15s
- Best Practices and Model ReviewUnlock this class to watch2m 25s
- Model Auditing and Review ProcessUnlock this class to watch3m 39s
- Step-by-Step Model BuildingUnlock this class to watch4m 12s
- Industry-Specific Modeling ChallengesUnlock this class to watch2m 31s
- Examples of Monte Carlo Strategy SimulationUnlock this class to watch2m 5s
- ClosingUnlock this class to watch1m 16s
This class is part of the following certifications
Certified Portfolio & Fund Manager (CPFM)
63 ClassesUnlimited interactive exercises
Unlock Certificate
Certificate in AI-Powered Financial Analysis (CAFA)
56 ClassesUnlimited interactive exercises
Unlock Certificate
ClassFAQs
The course aims to teach learners how to build, implement, and analyze financial models using Monte Carlo simulation to assess uncertainty, risk, and scenario outcomes across trading, credit, and project finance contexts.
The course is designed for finance professionals, analysts, and risk practitioners seeking to strengthen their modeling skills and apply probabilistic methods to financial decision-making.
The module covers probability distributions, random sampling techniques, and Excel-based simulation methods used to model uncertainty in financial projections.
The course explores credit-risk frameworks such as CAMEL, KMV, and CreditRisk+, teaches probability-of-default calculations, and demonstrates how Monte Carlo simulation is applied to credit-risk assessment.
Learners will develop the ability to build stress tests, create scenario-based models, and use Excel data tables to integrate Monte Carlo simulations for robust sensitivity analysis.
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