1 / 26

Hedge with an Edge An Introduction to the Mathematics of Finance

Hedge with an Edge An Introduction to the Mathematics of Finance . Monte Carlo Methods. Riaz Ahmed & Adnan Khan Lahore Uviersity of Management Sciences . Topics. Simulating Bernoulli Random Variable Generating Random Variables Inverse Transform Method Box Muller Method

leann
Télécharger la présentation

Hedge with an Edge An Introduction to the Mathematics of Finance

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Hedge with an EdgeAn Introduction to the Mathematics of Finance Monte Carlo Methods Riaz Ahmed & Adnan Khan Lahore Uviersity of Management Sciences

  2. Topics • Simulating Bernoulli Random Variable • Generating Random Variables • Inverse Transform Method • Box Muller Method • Rejection Method • Simulate a 1-D random Walk • Calculate the mean • Calculate the Variance • Simulating Brownian Motion • Geometric Brownian Motion • Arithmetic Brownian Motion • Variance Reduction Techniques

  3. Simulating a Binomially Distributed Random Variable • Note sum of Bernoulli trials is a binomial • Let Xi be a Bernoulli trial with probability ‘p’ of success • is binomial ‘n’, ‘p’

  4. Some Properties • Distribution of successes in trials • Expected Value • Variance

  5. Simulation of Binomial • Generating Bernoulli • Binomial as the sum of Bernoulli • Monte Carlo Simulation • Numerical vs. Exact Mean and Variance

  6. Simulation of Binomial

  7. Continuous Random Variables • Inverse Transform Method • Suppose a random variable has cdf ‘F(x)’ • Then Y=F-1(U) also had the same cdf • Generating the exponential • Generate the exponential, compare with exact cdf • Generate a r.v. with cdf

  8. Simulating the Exponential

  9. Simulating Normal using Inverse Transform • Cannot get a closed form in terms of elementary functions • Excel has built in command normsinv() • Use normsinv(rand())

  10. Simulation of Normal

  11. Rejection Method • Simulate & • To Simulate look @ •  If accept, else reject • To Simulate N(0,1) let • If set

  12. Box Muller Method • Recall the cdf for the standard normal is • We saw one way was to invert this • Another technique is to generate • Then and where

  13. Simulation

  14. Weiner Process • W(t) CT-CS process is a Weiner Process if W(t) depends continuously on t and the following hold a) • are independent

  15. Simulating Brownian Motion • Initialize at 0 as W(0)=0 • Simulate Weiner Increments according to • The Weiner Process then follows

  16. Simulation

  17. Simulation

  18. Stock Price Model • Modeled by Geometric Brownian Motion • Note • To simulate use the ‘Euler Scheme’

  19. Simulating GBM

  20. Simulating GBM

  21. Mean Reverting Process • Arithmetic Brownian Motion is mean reverting • Interest rate models • The numerical scheme is

  22. Simulating ABM

  23. Simulating ABM

  24. Option Pricing using Monte Carlo • Generate several risk-neutral random walks for the asset starting at the asset price today and going on till expiry. • For each path generated calculate the payoff. • Calculate average the average of all the payoffs • Take the present value of this average to get the option value today.

  25. Pricing of European Call

  26. Challenge Problem Simulate using Monte Carlo techniques the price of a European call option where the underlying with volatility 0.5 interest rate 3% exercise price 100 and currently underlying at 90

More Related