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FINANCIAL MARKET COURSES

Options - Future Asset Prices & Volatility

Option pricing requires some estimation of possible future values of an asset; some model is required which shows where prices can move to, and with what probability. The influences can be many, but at least some part of the future price evolution is random. This randomness can be estimated by analyzing the past values of an asset. It is also incorporated into option models through a 'volatility' term. However, the historic estimation and the use of volatility as a pricing input are very different things. This course will provide you with an insight into future asset pricing and volatility.

  • OBJECTIVES

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

    Explain the basic components of drift and randomness, which are assumed to underlie the price evolution process

    Describe the idealized 'normal' distribution of returns (lognormal price distribution) and how this differs from reality

    Describe the idea of a probability distribution for the future price of an asset

    Calculate the historic volatility of an asset and explain the key differences between historic and implied volatility

  • COURSE OUTLINE

    Topic 1: Drift & Randomness

    Drift

    Drift – An Example

    The Random Component

    Returns not Prices

    Natural Logarithms of Price Relatives

    Topic 2: Normal & Lognormal Distributions

    An Assumption of Normality

    Introducing Volatility

    The Price Distribution

    The Markov Property

    The Square root of Time

    Volatility Conversions

    Brownian Motion

    Topic 3: Historical & Implied Volatility

    Types of Volatility

    Calculating Volatility

    Volatility Conversion Table

    Limitations of Historical Volatility

    Implied Volatility

    Skews and Smiles

    Topic 4: Future Path Prices

    Generalized Weiner Process

    Mean Expectation of Lognormal Prices

    A Recipe for a Price Evolution Path

    Other Price Evolutions

    The Random Walk

    Putting the Paths Together

    Confidence Intervals

    Fat Rails

  • PREREQUISITE KNOWLEDGE

  • ESTIMATED COMPLETED TIME

    75 Minutes

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