Corporate Quantitative Risk Management Training Course

1. Introduction to the training and what to expect

1. Goals and objectives of the training
2. Structure and approach
3. Expected outcomes for participants

2. How are business decisions made?

1. Decision-making processes in business
2. Role of data and analytics
3. Impact of risk on decision making

3. What is risk and why should risk be considered?

1. Definition and types of risk
2. Importance of risk management
3. Consequences of poor risk management

4. Overview of risk analysis software applications

1. Common risk analysis tools
2. Features and functionalities
3. Selecting the right tool for your needs

1. Overview of risk simulator software

1. Introduction to Monte Carlo simulation
2. Key features of risk simulator
3. Software setup and user interface

2. Profiling, assumptions, forecasts, and running simulations

1. Creating risk profiles
2. Setting assumptions and parameters
3. Generating and analyzing forecasts

3. Interpreting the forecast statistics

1. Understanding output data
2. Statistical interpretation techniques
3. Making informed decisions based on forecasts

4. Simulation run preferences and seed values

1. Configuring simulation settings
2. Importance of seed values in simulation
3. Optimizing simulation runs

5. Running reports, saving, and extracting simulation data

1. Generating reports and documentation
2. Saving and exporting data
3. Best practices for data management

1. Correlating and truncating distributions

1. Methods for correlating variables
2. Truncating distributions for realistic modeling
3. Practical applications and case studies

2. Alternate parameters

1. Exploring different parameter sets
2. Sensitivity analysis
3. Scenario planning with alternate parameters

3. Multidimensional simulations

1. Concept and implementation
2. Handling complexity in simulations
3. Case examples

4. Distributional fitting

1. Techniques for fitting distributions to data
2. Goodness of fit tests
3. Application in risk analysis

5. Due diligence and pitfalls in simulation

1. Ensuring accuracy and reliability
2. Common pitfalls and how to avoid them
3. Conducting thorough due diligence

1. Static tornado and spider charts

1. Creating and interpreting tornado charts
2. Utilizing spider charts for sensitivity analysis
3. Practical applications in risk management

2. Dynamic sensitivity analysis and scenario analysis

1. Techniques for dynamic analysis
2. Building and analyzing scenarios
3. Strategic decision-making based on analysis

3. Hypothesis test on different distributions

1. Conducting hypothesis testing
2. Comparing different statistical distributions
3. Applications in risk analysis

4. Nonparametric bootstrap simulation

1. Fundamentals of bootstrap techniques
2. Implementing nonparametric simulation
3. Case studies and examples

1. Introduction to optimization

1. Basics of optimization in risk management
2. Optimization algorithms and methods
3. Setting goals and constraints

2. Continuous optimization

1. Techniques for continuous variables
2. Solving continuous optimization problems
3. Real-world applications

3. Integer optimization

1. Understanding integer optimization
2. Solving problems with discrete variables
3. Practical use cases

1. Overview of forecasting techniques and data types

1. Types of forecasting methods
2. Data considerations and preparation
3. Selecting appropriate forecasting techniques

2. Nonlinear extrapolation

1. Principles of nonlinear forecasting
2. Techniques and models for extrapolation
3. Case studies

3. Multivariate linear and nonlinear regression analysis

1. Basics of multivariate regression
2. Linear vs. nonlinear models
3. Applications in risk forecasting

4. Stochastic processes

1. Understanding stochastic models
2. Implementing stochastic processes in forecasting
3. Practical examples

5. Advanced forecasting techniques

1. ARIMA, GARCH, J-Curve, S-Curves, Markov chains
2. Data diagnostics and statistical properties
3. Basic econometrics and model selection

1. Real options: what, where, who, when, how, and why?

1. Conceptual framework of real options
2. Different types and applications
3. Strategic importance in business decision-making

2. Sample applied business cases

1. Case studies illustrating real options
2. Practical insights and lessons learned
3. Application in various business contexts

3. Overview of different options valuation techniques

1. Techniques for valuing real options
2. Comparing and contrasting methods
3. Selecting the right approach

4. Risk-neutral probability technique

1. Theory and application of risk-neutral valuation
2. Practical examples and case studies
3. Implications for risk management

5. Solving a basic European and American call option

1. Basics of call options
2. Solving European and American options
3. Practical use cases

6. Using Excel to solve a basic European and American call option

1. Excel techniques for option valuation
2. Step-by-step guide and best practices
3. Hands-on exercises and applications

7. Abandonment, expansion, contraction, and chooser options

1. Types of real options in business
2. Analyzing and valuing different options
3. Strategic implications and applications

1. Overview of the different SLS modules and volatility estimates

1. Introduction to SLS modules
2. Estimating and applying volatility
3. Practical use and case studies

2. Volatility estimates

1. Techniques for estimating volatility
2. Importance in option valuation
3. Real-world applications

3. Options with changing inputs and customized exotic options

1. Handling dynamic inputs in option models
2. Designing and valuing exotic options
3. Case studies and practical examples

4. MSLS: multiple sequential compound options

1. Understanding and applying MSLS
2. Structuring complex option deals
3. Practical business applications

5. MNLS: Solving mean-reverting, jump-diffusion, and dual-asset rainbow options

1. Advanced models in real options
2. Implementing trinomial, quadranomial, and pentanomial lattices
3. Case studies and business implications

6. Framing real options - structuring the problem

1. Approaches to framing real options problems
2. Structuring and analyzing real option scenarios
3. Strategic decision-making using real options analysis