About the Course
Learn mathematical, programming and statistical tools used in the real world analysis and modeling of financial data. Apply these tools to model asset returns, measure risk, and construct optimized portfolios using the open source R programming language and Microsoft Excel. Learn how to build probability models for asset returns, to apply statistical techniques to evaluate if asset returns are normally distributed, to use Monte Carlo simulation and bootstrapping techniques to evaluate statistical models, and to use optimization methods to construct efficient portfolios.


Course Syllabus
Topics covered include:
Computing asset returns
Univariate random variables and distributions
Characteristics of distributions, the normal distribution, linear function of random variables, quantiles of a distribution, Value-at-Risk
Bivariate distributions
Covariance, correlation, autocorrelation, linear combinations of random variables
Time Series concepts
Covariance stationarity, autocorrelations, MA(1) and AR(1) models
Matrix algebra
Descriptive statistics
histograms, sample means, variances, covariances and autocorrelations
The constant expected return model
Monte Carlo simulation, standard errors of estimates, confidence intervals, bootstrapping standard errors and confidence intervals, hypothesis testing , Maximum likelihood estimation, review of unconstrained optimization methods
Introduction to portfolio theory
Portfolio theory with matrix algebra
Review of constrained optimization methods, Markowitz algorithm, Markowitz Algorithm using the solver and matrix algebra
Statistical Analysis of Efficient Portfolios
Risk budgeting
Euler’s theorem, asset contributions to volatility, beta as a measure of portfolio risk
The Single Index Model
Estimation using simple linear regression

Suggested Readings
(The first 4 texts are highly recommended)
Introduction to Computational Finance and Financial Econometrics, Eric Zivot and R. Douglas Martin. 
Manuscript under preparation
Statistics and Data Analysis for Financial Engineering by David Ruppert, Springer-Verlag.
Beginner's Guide to R by Alain Zuur, Elena Ieno and Erik Meesters, Springer-Verlag.
R Cookbook by Paul Teetor, O'Reilly.
Other books for further reference:
Introductory Statistics with R, Second Edition (Statistics and Computing, Paperback), by Peter Dalgaard, Springer-Verlag, New York.
Modern Portfolio Theory and Investment Analysis, by E.J. Elton et al., Wiley, New York.
Financial Modeling, by Simon Benninga. MIT Press.
Statistical Analysis of Financial data in S-PLUS, by Rene Carmona, Springer-Verlag, 2004.

Hogfather,
а вы заметили, что на coursera.org появились курсы на французском, итальянском, испанском и даже китайском. Это к вопросу о поддержке своей культуры, языка, своих журналов, рекламы своей системы образования, своих университетов и т.п. ;) в какой-то теме был такой спор, что надо мол своих поддерживать, свои журналы, свой язык. Вот один из вариантов рекламы. Даже китайцы уже подключились. Вот почему-то на русском от ведущих университетов России ничего нет. Видимо, не очень надо ;)

About the Course
We live in a complex world with diverse people, firms, and governments whose behaviors aggregate to produce novel, unexpected phenomena. We see political uprisings, market crashes, and a never ending array of social trends. How do we make sense of it? Models. Evidence shows that people who think with models consistently outperform those who don't. And, moreover people who think with lots of models outperform people who use only one. Why do models make us better thinkers? Models help us to better organize information - to make sense of that fire hose or hairball of data (choose your metaphor) available on the Internet. Models improve our abilities to make accurate forecasts. They help us make better decisions and adopt more effective strategies. They even can improve our ability to design institutions and procedures. In this class, I present a starter kit of models: I start with models of tipping points. I move on to cover models explain the wisdom of crowds, models that show why some countries are rich and some are poor, and models that help unpack the strategic decisions of firm and politicians. The models covered in this class provide a foundation for future social science classes, whether they be in economics, political science, business, or sociology. Mastering this material will give you a huge leg up in advanced courses. They also help you in life. Here's how the course will work. For each model, I present a short, easily digestible overview lecture. Then, I'll dig deeper. I'll go into the technical details of the model. Those technical lectures won't require calculus but be prepared for some algebra. For all the lectures, I'll offer some questions and we'll have quizzes and even a final exam. If you decide to do the deep dive, and take all the quizzes and the exam, you'll receive a certificate of completion. If you just decide to follow along for the introductory lectures to gain some exposure that's fine too. It's all free. And it's all here to help make you a better thinker!
Recommended Background
Students should be very comfortable with basic algebra. Calculus isn’t necessary but a conceptual understanding of how derivatives give the slope at a point proves useful.
Suggested Readings
The Difference: How the Power of Diversity Creates Better Groups, Firms, Schools, and Societies (New Edition), Scott E Page.
Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton Studies in Complexity), John Miller and Scott Page
An Introduction to Models in the Social Sciences, Jean Lave and James March
Course Format
The class will cover a variety of models. For each model, I will give an introductory lecture accessible to a general audience that last approximately ten minutes. I will follow this with advanced lectures that explain how model's details and how to use it, as well as possible extensions. Many of these more detailed lectures will include integrated questions so you can test your knowledge of the material. I will also offer quizzes separate from the video lectures. I anticipate covering two models per week and recording approximately one hour of video per model.
FAQ
Do I need to buy a textbook?
No. I'm working to get all necessary reading material to be available for free on the course web site.

Will I get a certificate after completing this class?
Yes. Students who successfully complete the class will receive a certificate signed by the instructor.

About the Instructor

Scott E. Page
University of Michigan

Categories:
Economics & Finance
Humanities

Мне очень нужен этот курс. Сотрудничаю с группой фин.математики из ЮАР, но мне ужасно тяжело с ними ... я не статистик :( и не экономист :( я больше по численным методам, но так уж сложилось, что я обсчитываю им всякие модели.. вернее, пытаюсь. Очень тяжело идет.