Mathematical Finance (English)

   Thursday, March 21, 2024   

Starting a new Lecture Notes Series on Mathematical Finance

Youtube Lecture Playlist Credits 

Channel Name: NPTEL IIT Guwahati

So Let Us Start to This Journey of Learning 

Mathematical Finance By Lecture Notes together!

Lecture 1: Mathematical Finance

Lecture 2: Lec 01: Introduction to Financial Markets and Bonds

Lecture 3: Lec 02: Introduction to Stocks, Futures & Forwards and Swaps

Lecture 4: Lec 03: Introduction to Options

Lecture 5: Lec 04: Interest Rates and Present Value

Lecture 6: Lec 05: Present & Future Values, Annuities, Amortization and Bond Yield

Lecture 7: Lec 06: Price Yield Curve and Term Structure of Interest Rates

Lecture 8: Lec 07: Markowitz Theory, Return & Risk and Two Asset Portfolio

Lecture 9: Lec 08: Minimum Variance Portfolio and Feasible Set

Lecture 10: Lec 09:Multi Asset Portfolio, Min.Variance Portfolio, Efficient Frontier & Min.Variance Line

Lecture 11: Lec 10: Minimum Variance Line Continued, Market Portfolio

Lecture 12: Lec 11: Capital Market Line, Capital Asset Pricing Model

Lecture 13: Lec 12: Performance Analysis

Lecture 14: Lec 13: No Arbitrage Principle and Pricing of Forward Contracts

Lecture 15: Lec 14: Futures, Options and Put Call Parity

Lecture 16: Lec 15: Bounds on Options

Lecture 17: Lec 16: Derivative Pricing in a Single Period Binomial Model

Lecture 18: Lec 17: Derivative Pricing in Multiperiod Binomial Model

Lecture 19: Lec 18 Derivative Pricing in Binomial Model and Path Dependent Options

Lecture 20: Lec 19: Discrete Probability Spaces

Lecture 21: Lec 20: Filtrations and Conditional Expectations

Lecture 22: Lec 21: Properties of Conditional Expectations

Lecture 23: Lec 22: Examples of Conditional Expectations, Martingales

Lecture 24: Lec 23: Risk-Neutral Pricing of European Derivatives in Binomial Model

Lecture 25: Lec 24: Actual and Risk-Neutral Probabilities, Markov Process, American Options

Lecture 26: Lec 25: General Probability Spaces, Expectations, Change of Measure

Lecture 27: Lec 26: Filtrations, Independence, Conditional Expectations

Lecture 28: Lec 27: Brownian Motion and its Properties

Lecture 29: Lec 28: Itô Integral and its Properties

Lecture 30: Lec 29: Itô Formula, Itô Processes

Lecture 31: Lec 30: Multivariable Stochastic Calculus, Stochastic Differential Equations

Lecture 32: Lec 31: Black-Scholes-Merton (BSM) Model, BSM Equation, BSM Formula

Lecture 33: Lec 32: Greeks, Put-Call Parity, Change of Measure

Lecture 34: Lec 33: Girsanov Theorem, Risk-Neutral Pricing of Derivatives, BSM Formula

Lecture 35: Lec 34: MRT and Hedging, Multidimensional Girsanov and MRT

Lecture 36: Lec 35: Multidimensional BSM Model, Fundamental Theorems of Asset Pricing

Lecture 37: Lec 36: BSM Model with Dividend-Paying Stocks