Topics in Mathematics with Applications in Finance
Broad familiarity with linear algebra, statistics, stochastic processes and partial differential equations will be helpful (but not required). Prior knowledge of economics or finance is not required but may be helpful for some lectures.
Share
Course Description :
The purpose of the class is to expose undergraduate and graduate students to the mathematical concepts and techniques used in the financial industry. The course will consist of a set of mathematics lectures on topics in Linear Algebra, Probability, Statistics, Stochastic Processes and Numerical Methods. Mathematics lectures will be mixed with lectures illustrating the corresponding application in the financial industry.
MIT mathematicians will teach the mathematics part while industry professionals will give the lectures on applications in finance. We also plan to organize an optional field trip to visit Morgan Stanley offices in New York.
This lesson is Made for :
You will learn stuff about :
Requirements for this lesson :
CURRICULUM
-
Chapter #1 - Introduction, Financial Terms and Concepts
-
Chapter #2 - Linear Algebra
-
Chapter #3 - Probability Theory
-
Chapter #4 - Stochastic Processes
-
Chapter #5 - Regression Analysis
-
Chapter #6 - Value At Risk (VAR) Models
-
Chapter #7 - Time Series Analysis
-
Chapter #8 - Volatility Modeling
-
Chapter #9 - Regularized Pricing and Risk Models
-
Chapter #10 - Commodity Models
-
Chapter #11 - Portfolio Theory
-
Chapter #12 - Factor Modeling
-
Chapter #13 - Portfolio Management
-
Chapter #14 - Itou Calculus
-
Chapter #15 - Black-Scholes Formula, Risk-neutral Valuation
-
Chapter #16 - Option Price and Probability Duality
-
Chapter #17 - Quanto Credit Hedging
-
Chapter #18 - HJM Model for Interest Rates and Credit
-
Chapter #19 - Ross Recovery Theorem
-
Chapter #20 - Introduction to Counterparty Credit Risk
