- Provider Coursera
- Cost Free Online Course (Audit)
- Session Finished
- Language English
- Certificate Certificate Available
- Effort 10-15 hours a week
- Duration 7 weeks long
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Overview
Class Central Tips
Are you curious about quantitative academic finance? Have you considered graduate study in finance? Are you working in an investment bank, money-management firm or hedge fund and you want to understand models better? Would you like to know what buzzwords like beta, risk premium, risk-neutral price, arbitrage, equity premium, and discount factor mean? This class is for you.
We will see how one basic idea, price equals expected discounted payoff, unites everything - models that describe stocks, bonds, options, real investments, discrete time, continuous time, asset pricing, portfolio theory, and so forth.
In this part I, we’ll quickly learn or review time-series in continuous and discrete time. We'll look at some basic facts. Then we’ll start with the underlying consumption-based model, and we’ll preview some classic issues in finance. That outlines the big ideas of the whole class. Then, we'll take a step back and study contingent claims and the theorems showing the existence of a discount factor (the m in p=E(mx)). We'll explore the mean-variance frontier and expected return vs. beta models and factor structures. We will study the classic linear models — CAPM, APT, ICAPM. We will learn how to use GMM to estimate and evaluate asset pricing models, as well as the classic regression tests. This paves the way for Part 2 which focuses on applications and empirical evaluation.
The math in real, academic, finance is not actually that hard. Understanding how to use the equations, and see what they really mean about the world... that's hard, and that's what I hope will be uniquely rewarding about this class.
We will see how one basic idea, price equals expected discounted payoff, unites everything - models that describe stocks, bonds, options, real investments, discrete time, continuous time, asset pricing, portfolio theory, and so forth.
In this part I, we’ll quickly learn or review time-series in continuous and discrete time. We'll look at some basic facts. Then we’ll start with the underlying consumption-based model, and we’ll preview some classic issues in finance. That outlines the big ideas of the whole class. Then, we'll take a step back and study contingent claims and the theorems showing the existence of a discount factor (the m in p=E(mx)). We'll explore the mean-variance frontier and expected return vs. beta models and factor structures. We will study the classic linear models — CAPM, APT, ICAPM. We will learn how to use GMM to estimate and evaluate asset pricing models, as well as the classic regression tests. This paves the way for Part 2 which focuses on applications and empirical evaluation.
The math in real, academic, finance is not actually that hard. Understanding how to use the equations, and see what they really mean about the world... that's hard, and that's what I hope will be uniquely rewarding about this class.
Syllabus
Part 1 syllabus:
- Week 1: Stochastic Calculus Introduction and Review. dz, dt and all that.
- Week 2: Introduction and Overview. Challenging Facts and Basic Consumption-Based Model.
- Week 3:
- Classic issues in Finance
- Equilibrium, Contingent Claims, Risk-Neutral Probabilities.
- Week 4: State-Space Representation, Risk Sharing, Aggregation, Existence of a Discount Factor.
- Week 5: Mean-Variance Frontier, Beta Representations, Conditioning Information.
- Week 6: Factor Pricing Models -- CAPM, ICAPM and APT.
- Week 7: Econometrics of Asset Pricing and GMM.
- Final Exam
- Spring break (1 week)
-
Week 1: Factor pricing models in action
- The Fama and French model
- Fund and performance evaluation.
- Week 2: Time series predictability, volatilty and bubbles.
- Week 3: Equity premium, macroeconomics and asset pricing.
- Week 4: Option Pricing.
- Week 5: Term structure models and facts.
- Week 6: Portfolio Theory.
- Final Exam
Taught by
and John Cochrane
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