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VAR - Monte Carlo Simulation

As options and other financial derivatives became more complex, the use of Monte Carlo simulation methods to price them became more popular. Today, many financial institutions with large derivatives portfolios employ this technique. This course looks at how Monte Carlo simulations are applied to VAR calculations. Monte Carlo VAR is an important approach because it can be used for more difficult positions, such as those involving optionality, when other approaches such as variance-covariance are inappropriate.

  • OBJECTIVES

    On completion of this course, you will be able to:

    Outline the Monte Carlo simulation approach to calculating value at risk (VAR)

    Describe the benefits and problems that arise from using Monte Carlo simulations to calculate VAR

  • COURSE OUTLINE

    Topic 1: Calculating VAR Using Monte Carlo Simulations

    What is Monte Carlo VAR?

    Options & VAR

    Step 1: Generate Scenarios

    o Opportunity Cost of Capital

    o Stochastic Element

    o Probability Distribution

    o Formula for Generating Scenarios

    o Simulate the Price Path

    o Correlation

    o Cholesky Decomposition

    Step 2: Calculate the Value of the Portfolio

    o Partial Versus Full Valuation

    Step 3: Reorder the Results

    Topic 2: Appraisal of Monte Carlo VAR

    Benefits of Monte Carlo VAR

    o Non-linear Positions

    o Data Selection

    o Missing Data

    o Combining Histories

    o Parameter Estimation

    Drawbacks of Monte Carlo VAR

    o Cost and Speed of Computing Resources

    o Increasing the Accuracy

    o Problems Generating Random Numbers

    o Other Issues with Monte Carlo VAR

  • PREREQUISITE KNOWLEDGE

  • ESTIMATED COMPLETED TIME

    60 Minutes

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