1. Type of data set define data variable
A. gen date1 = tm(1994m1) + _n1
B. Format %tm date1
C. Tsset date1
2. Convert data to returns
*Generate log returns:
Gen r_ttm = log(TataMotors)  log(l.TataM
MSFA 736: Quiz #1
(Three Questions in 20 minutes!)
Name: _
RISK AND RETURN IN INDIA
You are given the following information on monthly returns between December 1998 to
December 2003 for an Indian comp
Multiple Regression Analysis
y = 0 + 1x1 + 2x2 + . . . kxk + u
5. Dummy Variables
Economics 20  Prof.
1
Dummy Variables
A dummy variable is a variable that takes
on the value 1 or 0
Examples: male (=
MSFA 736
CLASS 4
Qualitative Variables in Multiple Regression
To this point we have looked only at independent variables that take on many values, either
discretely or continuously, i.e. quantitative
Specification Errors.
We do not know the true model that generates the observations.
Important therefore to ask about consequences of wrongly specifying the
model for the properties of our coefficie
Effects of Specification Errors.
Comparing the theoretical effects of the two types of specification error
we see a tradeoff:
1. INCLUDING IRRELEVANT variables does NOT affect unbiasedness or
consist
MSFA 736
CLASS 5
SERIAL CORRELATION
INTRODUCTION
We allow for errors whose structure violates the assumption of serial independence
used in the simple OLS method.
E ut ut s 0 s 0
Current error term ma
MSFA 736
CLASS 4
Dummy Variables: Shifts in both the Intercept and the Slope Terms
finally it is also possible to extend the dummy variable approach to shifts in
both the intercept and the slope term
SPECIAL PROBLEMS IN CROSSSECTION AND TIME SERIES DATA
HETEROSKEDASTICITY
MISSPECIFICATION: A College GPA regression example.
1.5
1.0
0.5
0.0
0.5
1.0
1.5
2.0
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C OLGPA
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Mass marketexpendablegoodspurchased byconsumers for their daily or frequent consumpton.
Not expected to have auseful lifeof more than 3 years.
Acaris adurable good. The gasolinethat powers it is a non
V
Financial Tales
The Birth of Junk Bonds
While junk bonds have existed in some form or another for a long time, there is one particular
name that is synonymous with the birth of junk bonds; Michael M
IBEW LOCAL 90 PENSION FUND v. DEUTSCHE BANK AG, Dist. Co. Page 1 of 20
IBEW LOCAL 90 PENSION FUND, on behalf of itself and all others similarly situated, Plaintiffs,
v.
DEUTSCHE BANK AG, et al., Defen
University of San Francisco
School of Management
MSFA 712
Spring 2016
Prof. Ludwig Chincarini
Problem Set #2
1. You are given the following information regarding prices for a sample of stocks.
Stock
A
Riding the Yield Curve:
A Variety of Strategies
DAVID S. BIERI AND LUDWIG B. CHINCARINI
DAVID S. BIERI
is adviser to the general
manager at the Bank for
International Settlements
in Basel, Switzerland
Financial Markets
Lecture 2
Ludwig B. Chincarini
University of San Francisco
1
Outline
I.
II.
III.
IV.
V.
The Crisis of Crowding Chapter 10
Complete IPS
How do you Invest in Oil?
Security Market Indic
MSFA 736 Assignment #4
Dummy Variables and Wages
Analyzing the Determinants of Wages1
Data sets used by researchers in the study of wage determinants are typically very large,
often involving over 10,
FINANCIAL ECONOMETRICS
ECON 736
ASSIGNMENT #3
PROF. JOHN M. VEITCH
ASSIGNMENT DUE IN CLASS 4.
You can answer this Assignment in a group of 35 students.
Your group should treat your answers to each qu
MSFA 736
WEEK 3
Joint Tests of Significance for Several Coefficients
It is often the case in a multiple regression model that we want to test the joint significance of
a subset of the independent vari
MSFA 736
WEEK 3
The Multiple Linear Regression Model.
until now we have considered only relationships between two economic variables. Clearly
most economic theories involve the relationship of several
Principios de Econometra
Revisi
on Estadstica Matem
atica
Ivan Gachet
Universidad San Francisco de Quito
Enero 2017
1 / 21
Outline
Outline
Poblaci
on, Parametros y
Muestras Aleatorias
Parametros, esti
Principios de Econometra
Modelo de Regresi
on M
ultiple I
Ivan Gachet
Universidad San Francisco de Quito
1 / 27
Outline
Outline
Motivaci
on
Estimaci
on
Interpretaci
on
Bondad de Ajuste
Insesgadez del
MSFA
Financial Econometrics
Review Statistics
Measures of Location  Returns
Measures of Dispersion  Risk
Relative Measures Risk vs. Return
Linear Regression
Statistical Concepts
Population is define
MSFA 736
Class 1
INTUITIVE LINKS BETWEEN PROBABILITY AND STATISTICS (FROM THE COIN FLIP EXAMPLE)
for a discrete random variable we could calculate the relative frequencies that we
observe particular v
MSFA 736: Advanced Tests
Test of Difference in Unknown Means
Note that the question asks whether the Index return is greater than the Nasdaq return. Since
this is phrased as an inequality, you have to
Metrics
Week 1
What is econometrics?
in more practical terms, econometrics is used by economists to
estimate economic relationships from economic data
test hypotheses about economic behavior from econ
ECONOMETRICS  MSFA 736
ASSIGNMENT #1
PROF. JOHN M. VEITCH
AN ASSIGNMENT WHERE YOU BEGIN TO UNDERSTAND SOME
OF THE PAINFUL LESSONS ON RISK AND RETURN.
You can answer this Assignment in a group of 35
MSFA 736
WEEK 2
Outline for Week 2:
INTUITION BEHIND REGRESSION LINE
1. SIMPLE REGRESSION MODEL
Yt = + X t + ut
for t = 1,2,T
correlation and maybe causation
unknown parameters estimated from sample

The Simple Regression Model
y = 0 + 1x + u
Economics 20  Prof. Anderson
1
Some Terminology
In the simple linear regression model,
where y = 0 + 1x + u,
We typically refer to y as the
Dependent Variab