Only 9 days left till school starts!!! Enrol now, free education.... https://www.coursera.org/course/compfinance Introduction to Computational Finance and Financial Econometrics 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. 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 Eulerâs theorem, asset contributions to volatility, beta as a measure of portfolio risk The Single Index Model Estimation using simple linear regression
Hi Slacker, Probably over my head, but what the heck. Took the Machine Learning course (Stanford) the first time it was offered (last October). A great experience. Very well done. There's really no downside to this type of thing.
Thanks for the link. I'm signed up, I wonder how much of the texts I need to read before the course. I hope I can follow the lectures well enough. I'm signed up for this one: https://www.coursera.org/course/compinvesting1 Computational Investing, Part I but it's always TBA, they don't have a start date.