'Moment generating functions' presentation slideshows

Chapter 5 Expectations

Chapter 5 Expectations. ??? : ???. Content. Introduction Expectation of a Function of a Random Variable Expectation of Functions of Multiple Random Variables Important Properties of Expectation Conditional Expectations Moment Generating Functions Inequalities

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Lecture 12 Probability and Random Variables (II)

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Expectation

Expectation. Expected value:. Expectation of Sum of R.V. X and Y r.v. with joint pdf p(x,y) : Example: R = the return on the S&P500 each day (continuously compounded) Distributed according to h ( r ) What is the return over two days?. Expectation of Sum of R.V. In general,

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Moment Generating Functions

Moment Generating Functions. Moment Generating Functions (I). Moment Generating Functions (II). M(t) is called the moment-generating function for Y , and cam be used to derive any non-central moments of the random variable (assuming it exists in a neighborhood around t =0).

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