Mathematical Modeling in Finance with Stochastic Processes

(Ben Green) #1



  • 1 Background Ideas

  • 1.1 Brief History of Mathematical Finance

  • 1.2 Options and Derivatives

  • 1.3 Speculation and Hedging

  • 1.4 Arbitrage

  • 1.5 Mathematical Modeling

  • 1.6 Randomness

  • 1.7 Stochastic Processes

  • tions (CDOs) 1.8 A Binomial Model of Mortgage Collateralized Debt Obliga-

  • 2 Binomial Option Pricing Models

  • 2.1 Single Period Binomial Models

  • 2.2 Multiperiod Binomial Tree Models

  • 3 First Step Analysis for Stochastic Processes

  • 3.1 A Coin Tossing Experiment

  • 3.2 Ruin Probabilities

  • 3.3 Duration of the Gambler’s Ruin

  • 3.4 A Stochastic Process Model of Cash Management

  • 4 Limit Theorems for Stochastic Processes

  • 4.1 Laws of Large Numbers

  • 4.2 Moment Generating Functions

  • 4.3 The Central Limit Theorem

  • 4.4 The Absolute Excess of Heads over Tails



  • 5 Brownian Motion 4 CONTENTS

  • 5.1 Intuitive Introduction to Diffusions

  • 5.2 The Definition of Brownian Motion and the Wiener Process

  • 5.3 Approximation of Brownian Motion by Coin-Flipping Sums

  • 5.4 Transformations of the Wiener Process

  • 5.5 Hitting Times and Ruin Probabilities

  • 5.6 Path Properties of Brownian Motion

  • 5.7 Quadratic Variation of the Wiener Process

  • 6 Stochastic Calculus

  • 6.1 Stochastic Differential Equations and the Euler-Maruyama Method

  • 6.2 Itˆo’s Formula

  • 6.3 Properties of Geometric Brownian Motion

  • 7 The Black-Scholes Model

  • 7.1 Derivation of the Black-Scholes Equation

  • 7.2 Solution of the Black-Scholes Equation

  • 7.3 Put-Call Parity

  • 7.4 Derivation of the Black-Scholes Equation

  • 7.5 Implied Volatility

  • 7.6 Sensitivity, Hedging and the “Greeks”

  • 7.7 Limitations of the Black-Scholes Model

  • 1.1 This isnotthe market for options! List of Figures

  • 1.2 Intrinsic value of a call option

  • 1.3 A diagram of the cash flow in the gold arbitrage

  • 1.4 The cycle of modeling

  • 1.5 Initial conditions for a coin flip, from Keller

  • 1.6 Persi Diaconis’ mechanical coin flipper

  • 1.7 The family tree of some stochastic processes

  • 0 to 100 and the base mortgage default probability 0.01 to 0.15 1.8 Default probabilities as a function of both the tranche number

  • 2.1 The single period binomial model.

  • 2.2 A binomial tree

  • 2.3 Pricing a European call

  • 2.4 Pricing a European put

  • 3.1 Welcome to my casino!

  • 3.2 Welcome to my casino!

  • 3.3 Several typical cycles in a model of the reserve requirement.

  • 4.1 Block diagram of transform methods.

  • distribution. 4.2 Approximation of the binomial distribution with the normal

  • 4.3 The half-integer correction

  • 4.4 Probability ofsexcess heads in 500 tosses

  • 5.1 Graph of the Dow-Jones Industrial Average from August,

  • increments with the same mean and variance (brown line). to August 2009 (blue line) and a random walk with normal



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