Lecture 1 of 41Module 1: Introduction to Financial Markets and Instruments
Lecture 1: Introduction to Financial Markets and Bonds
Prof. N. Selvaraju and Prof. Siddhartha Pratim Chakrabarty · IIT Guwahati
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- Mathematical Finance, IIT Guwahati (at NPTEL)
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- CC BY-NC-SA, as NPTEL states it. Non-commercial use only.
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- NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
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All the lectures
- Lecture 1: Introduction to Financial Markets and Bonds
- Lecture 2: Introduction to Stocks, Futures & Forwards and Swaps
- Lecture 3: Introduction to Options
- Lecture 1: Interest Rates and Present Value
- Lecture 2: Present & Future Values, Annuities, Amortization and Bond Yield
- Lecture 3: Price Yield Curve and Term Structure of Interest Rates
- Lecture 7: Markowitz Theory, Return & Risk and Two Asset Portfolio
- Lecture 8: Minimum Variance Portfolio and Feasible Set
- Lecture 9: Multi Asset Portfolio, Minimum Variance Portfolio, Efficient Frontier and Minimum Variance Line
- Lecture 10: Minimum Variance Line (Continued), Market Portfolio
- Lecture 11: Capital Market Line, Capital Asset Pricing Model
- Lecture 12: Performance Analysis
- Lecture 13: No-Arbitrage Principle and Pricing of Forward Contracts
- Lecture 14: Futures, Options and Put-Call-Parity
- Lecture 15: Bounds on Options
- Lecture 16: Derivative Pricing in a Single Period Binomial Model
- Lecture 17: Derivative Pricing in Multiperiod Binomial Model
- Lecture 18: Derivative Pricing in Binomial Model and Path Dependent Options
- Lec 19: Discrete Probability Spaces
- Lec 20: Filtrations and Conditional Expectations
- Lec 21: Properties of Conditional Expectations
- Lecture 22: Examples of Conditional Expectations, Martingales
- Lecture 23: Risk-Neutral Pricing of European Derivatives in Binomial Model
- Lecture 24: Actual and Risk-Neutral Probabilities, Markov Process, American Options
- Lecture 25: General Probability Spaces, Expectations, Change of Measure
- Lecture 26: Filtrations, Independence, Conditional Expectations
- Lecture 27: Brownian Motion and its Properties
- Lecture 28: Itô Integral and its Properties
- Lecture 29: Itô Formula, Itô Processes
- Lecture 30: Multivariable Stochastic Calculus, Stochastic Differential Equations
- Lec 31: Black-Scholes-Merton (BSM) Model, BSM Equation, BSM Formula
- Lec 32: Greeks, Put-Call Parity, Change of Measure
- Lec 33: Girsanov Theorem, Risk-Neutral Pricing of Derivatives, BSM Formula
- Lec 34: MRT and Hedging, Multidimensional Girsanov and MRT
- Lec 35: Multidimensional BSM Model, Fundamental Theorems of Asset Pricing
- Lec 36: BSM Model with Dividend-Paying Stocks
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