Download Mathematics for statistical applications 1) Some matrix algebra 2

Preparatory course a.y. 2013 – 2014
Cod. 20356 Statistics
CLEFIN-FINANCE-MAFINRISK
Instructors: Francesco Corielli – Carlo Ambrogio Favero
Course taught in English
Course Objectives
An introduction to the basic concepts of statistics and probability required for the 20191 and
20192 courses in the CLEFIN degree.
Course Content Summary
Mathematics for statistical applications
1) Some matrix algebra
2) Interplay between matrix algebra and statistics. Expected values, Covariance matrices and related
properties.
3) Introduction to the linear model in matrix notation
4) Taylor formula and local approximations: the case of returns
Review of Key Statistical Concepts
1) Definition of random variables and its applications
2) Useful distributional results
3) Introduction to inference
4) Point estimation
5) Confidence intervals
6) Tests of hypothesis
7) Application of inference to simple finance
variances, and covariances.
problems:
estimation
of
means,
Some distribution theory
1) The use of the Gaussian in hypothesis testing and confidence intervals
2) The multidimensional Gaussian distribution
Matlab
1) Data Description with MATLAB (importing the data, transforming the data, descriptive statistics
and graphical analysis)
2) Descriptive analysis of Stock Market and Bond Market Returns with MATLAB
3) Static Asset Allocation with MATLAB (Tobin-Markowitz, dealing with estimation uncertainty:
resampled efficient frontier and Black-Litterman)
Textbooks
G. CASELLA, R.L. BERGER, Statistical inference, Duxbury Press, 2001
W.H. GREENE, Econometric Analysis, 5^ ed., Prentice Hall, 2003