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FINANCIAL MARKET COURSES

Options - Beyond Black-Scholes

The Black-Scholes approach to option pricing, while a massive advance on what little had been seen before, contains serious shortcomings. For example, the market assumptions are somewhat unrealistic, and the pricing formulas can only value a limited number of instruments.

 

This course examines alternative numerical methods which allow option practitioners to value a wider range of instruments, and can also incorporate different price evolution assumptions.

  • OBJECTIVES

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

    Describe how the binomial pricing model generates an option price through discrete changes in a future asset price, and how this procedure can be used to calculate American option prices

    Explain how numerical procedures have evolved beyond the binomial pricing model

    Describe how Monte Carlo simulations can be used to calculate values for options which are outside the scope of simple Black-Scholes or lattice models

  • COURSE OUTLINE

    Topic 1:  Binomial Option Pricing

    The Black-Scholes Model

    Shortcomings of the Black-Scholes Model

    Intermediate Asset Levels

    The Binomial Option Pricing Model

    Up & Down States

    Extending the Tree

    Recombining Trees & Bushy Trees

    Risk- Neutral Probabilities

    Simple Option Valuation

    Simple Option Valuation – Multiple Steps

    American Options

    More Steps Equals More Accuracy

    Relationship with Black- Scholes

    Control Variety Technique

    Equal Probability Tree

    Dividends

    Topic 2: Extensions to Basic Numerical Methods

    Trinomial Trees

    Barrier Options

    Adaptive Mesh

    Implied Trees

    Differing Models – Same Procedure

    Finite Differnce Method

    Scope of Simple Procedures

    Topic 3: Monte Carlo Simulation

    Monte Carlo Simulation

    Improving Monte Carlo Simulation

    Monte Carlo Simulation and American Options

  • PREREQUISITE KNOWLEDGE

  • ESTIMATED COMPLETED TIME

    90 Minutes

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