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Explore the random behavior of assets in quantitative finance, covering topics such as normal distribution, covariance, correlation, volatility, simulation, and the Central Limit Theorem. Dive into practical examples and calculations to grasp key concepts effectively.
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Financial Engineering Zvi Wiener mswiener@mscc.huji.ac.il 02-588-3049 http://pluto.mscc.huji.ac.il/~mswiener/zvi.html
Random Behavior of Assets Following Paul Wilmott, Introduces Quantitative Finance Chapter 6 http://pluto.mscc.huji.ac.il/~mswiener/zvi.html
Returns FE-Wilmott-IntroQF Ch6
Returns See file 6.Random Behavior of Assets.XLS FE-Wilmott-IntroQF Ch6
Normal Distribution N(, ) FE-Wilmott-IntroQF Ch6
Normal Distribution N(, ) FE-Wilmott-IntroQF Ch6
Normal Distribution 1% quantile FE-Wilmott-IntroQF Ch6
Lognormal Distribution FE-Wilmott-IntroQF Ch6
Covariance • Shows how two random variables are connected • For example: • independent • move together • move in opposite directions • covariance(X,Y) = FE-Wilmott-IntroQF Ch6
Correlation • -1 1 • = 0 independent • = 1 perfectly positively correlated • = -1 perfectly negatively correlated FE-Wilmott-IntroQF Ch6
Properties FE-Wilmott-IntroQF Ch6
Time Aggregation Assuming normality FE-Wilmott-IntroQF Ch6
Time Aggregation • Assume that yearly parameters of CPI are: • mean = 5%, standard deviation (SD) = 2%. • Then daily mean and SD of CPI changes are: FE-Wilmott-IntroQF Ch6
Volatility FE-Wilmott-IntroQF Ch6
Simulation of a Random Walk See spreadsheet A general formula FE-Wilmott-IntroQF Ch6
Geometrical Brownian Motion Arithmetical Brownian Motion FE-Wilmott-IntroQF Ch6
Central Limit Theorem • The mean of n independent and identically distributed variables converges to a normal distribution as n increases. FE-Wilmott-IntroQF Ch6
Home Assignment • Read chapter 6 in Wilmott. • Follow Excel files coming with the book. FE-Wilmott-IntroQF Ch6