Students
Tuition Fee
Not Available
Start Date
Not Available
Medium of studying
Not Available
Duration
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Details
Program Details
Degree
Bachelors
Major
Mathematics | Statistics
Area of study
Mathematics and Statistics
Course Language
English
About Program

Program Overview


Program Overview

The Math 86: Mathematical Finance I program is designed to provide students with a thorough understanding of discrete-time analogs of questions arising in finance from a mathematical viewpoint.


Course Description

In their simplest form, derivatives can be thought of as insurance policies that protect their holders from financial uncertainties. The course will consider the discrete-time analogs of these and other questions arising in finance, developing important mathematical ideas found in discrete probability and showing how these concepts can be used to construct a discrete-time model in which to explore questions appearing in finance.


Topics Covered

  • Reading & Writing Proofs
    • Finite Probability Spaces: sample space, sigma-algebras, random variables, expectation, (discrete-time) stochastic processes, filtrations, conditional expectation, martingales & Markov processes
  • Change of Measure and the (Discrete) Radon-Nikodym Derivative
  • The Binomial Asset Pricing Model
  • No-Arbitrage Pricing and the Risk-Neutral/Equivalent-Martingale Measure
  • Stopping Times and American Derivatives
  • Random Walks: the Discrete-Time Version of Brownian Motion
  • Stochastic Interest Rates & Fixed Income Derivatives

Prerequisites

  1. Math 60 or Math 20 and 40
  2. Math 23
  3. COSC 1

Textbook

Stochastic Calculus for Finance I: the Binomial Asset Pricing Model, Steven E. Shreve (Carnegie Mellon University), 2004


Tentative Syllabus

| Chapters |Brief Description
---|---|---
Week 1 & 2 |1 | No Arbitrage Pricing and the binomial asset pricing model; risk-neutral measure Week 2 & 3 |2 | Discrete probability: finite probability spaces, random variables, conditional expectation, filtrations, martingales & Markov processes Week 3 & 4 |2 | Discrete probability: finite probability spaces, random variables, conditional expectation, filtrations, martingales & Markov processes Week 4 & 5 |3 | Change of Measure & the Radon-Nikodym Derivative Week 5 & 6 |4 | American Derivatives: stopping times, path independent & dependent options Week 6 & 7 |5 | Random Walks Week 7 & 8 |6 | Fixed Income Securities Week 8 & 9 |1-6 | Review (of Math 86) & Preview (of Math 96)


Deliverables & Grading Guide

  • Midterm Exam: Date, Time and Location TBD (Closed Book)
  • Cumulative Final Exam: Friday, Nov. 21, 3-6 PM, Location TBD by Registrar, (Closed Book)
  • Weekly Homework: Assignments should be written neatly and presented using complete sentences. Collaboration is encouraged, but final write-ups must reflect individual understanding. Acknowledgment of consulted individuals is required. No late homework will be accepted.
  • Term Project: 15%
  • Homework: 15%
  • Midterm Exam: 30%
  • Cumulative Final Exam: 40%

Students with Disabilities

If you have a disability and require disability-related accommodations, please speak with the instructor or Ward Newmeyer, Director of Student Accessibility Services, as soon as possible to find a remedy.


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