This course is part one of a twopart introductory survey of graduatelevel academic asset pricing. We will focus on building the intuition and deep understanding of how the theory works, how to use it, and how to connect it to empirical facts. This first part builds the basic theoretical and empirical tools around some classic facts. The second part delves more deeply into applications and empirical evaluation.
Are you curious about quantitative academic finance? Have you considered graduate study in finance? Are you working in an investment bank, moneymanagement firm or hedge fund and you want to understand models better? Would you like to know what buzzwords like beta, risk premium, riskneutral 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 timeseries in continuous and discrete time. We'll look at some basic facts. Then we’ll start with the underlying consumptionbased 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 meanvariance 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 ConsumptionBased Model.
 Week 3:
 Classic issues in Finance
 Equilibrium, Contingent Claims, RiskNeutral Probabilities.

Week 4: StateSpace Representation, Risk Sharing, Aggregation, Existence of a Discount Factor.

Week 5: MeanVariance Frontier, Beta Representations, Conditioning Information.

Week 6: Factor Pricing Models  CAPM, ICAPM and APT.

Week 7: Econometrics of Asset Pricing and GMM.
 Final Exam
Part 2 is a separate course, which may be taken separately from Part 1. Here is the syllabus to whet your appetite:

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
Recommended Background
This course uses concepts from finance, undergraduate applied mathematics, advanced undergraduate / beginning graduate level economics, and timeseries econometrics. Students should be able to use single and multivariable calculus, simple differential equations, matrix algebra, and basic statistics. They should be able to program simple simulations in a matrix programming language like Matlab, Octave, R, Python, Julia, etc. Students should have some background in economics, including utility functions and maximization, and have worked with basic timeseries econometrics, such as AR(1) models.
Suggested Readings
The
Preface and
Chapter 1 of
Asset Pricing (
Princeton University Press) give a good feel for the class, the range of topics, and the mathematical level. The first two weeks of the class will be based on Chapter 1. We recommend purchasing the textbook to supplement your study in this class.
Course Format
• Reading assignments for each week, deriving the theory in detail and also giving intuition and applications. • Short lecture videos, emphaszing intuition and interpretation of the results rather than algebraic drudgery. The videos will incorporate integrated quiz questions. • Quizzes and weekly problem sets. • Forum discussions and regular Google hangouts. • A final exam.
FAQ
 Will I need to purchase anything to succeed in this course?
We recommend purchasing the textbook Asset Pricing, but you can complete the class without it. It is possible to rent the ebook version of Asset Pricing for about $20. Some of the readings will require a free myJSTOR account (see jstor.org for more information).  What resources will I need for this class?
Time, a computer with a good internet connection, some programming language, and curiosity.  Do I need to be a finance professional to benefit from this class?
No. The course is directed at doing and understanding academic research. It's useful if you want to do research in asset pricing, either in academia or industry, that recognizes a balance between risk and return.  Do I need a background in finance?
You should know what a stock and bond are, but an extensive knowledge of finance is not necessary. Those who bring previous experience will enjoy seeing familiar concepts united and brought to a deeper level. Please see the section on Recommended Background above for information on the mathematical and economic prerequisites of the class.