1. Type of data set define data variable
A. gen date1 = tm(1994m1) + _n-1
B. Format %tm date1
C. Tsset date1
2. Convert data to returns
*Generate log returns:
Gen r_ttm = log(TataMotors) - log(l.TataMotors)
Gen r_ttm = log(Bombay) - log(I.Bombay)
List dat
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 (= 1 if are male, 0
otherwise), south (= 1 if in the sout
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 variables. It is clear that another type of variable, a
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 coefficients, predictions, and tests.
There are a wide variety
Effects of Specification Errors.
Comparing the theoretical effects of the two types of specification error
we see a trade-off:
1. INCLUDING IRRELEVANT variables does NOT affect unbiasedness or
consistency of the coefficient estimates or predictions, but i
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 may be influenced by the level of the error terms in the
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 of the regression model.
Y1
X1
0
u1
1
0
Y
X
SPECIAL PROBLEMS IN CROSS-SECTION 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
50
100
150
200
250
300
350
400
C OLGPA Residuals
1
STRUCTURAL BREAKS: The residuals from a CA
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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-durable good, or consumable good.
Company Descriptions
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 Milken. The son of an accountant,
he started reading com
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., Defendants.
No. 11 Civ. 4209 (KBF).
United States District C
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
B
C
Number of Shares t
1,000,000
10,000,000
30,000,000
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.
david.bieri@bis.org
LUDWIG B.
CHINCARINI
is an adjunc
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 10,000 observations, and it is simply not feasible to prov
FINANCIAL ECONOMETRICS
ECON 736
ASSIGNMENT #3
PROF. JOHN M. VEITCH
ASSIGNMENT DUE IN CLASS 4.
You can answer this Assignment in a group of 3-5 students.
Your group should treat your answers to each question as a brief report. I am looking for both
the cor
MSFA 736
3
WEEK
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 variables. This is not the same a series of t-tests on each
MSFA 736
4
WEEK
Multicollinearity
another possibly serious consequence of adding more variables to a regression model is that
it becomes more likely that some of the explanatory variables will be highly correlated
(linearly related). This is known as mult
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 variables. This is not the same a series of t-tests on each
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 exogenous variables in explaining
movements in an endo
MSFA
Financial Econometrics
Review Statistics
Measures of Location - Returns
Measures of Dispersion - Risk
Relative Measures Risk vs. Return
Linear Regression
Statistical Concepts
Population is defined as all members of a specified group.
Sample is a subs
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 values in our sample, call these fk for all k possible 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 test the complement as Null Hypothesis. If you
reject
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 economic data
forecast future economic behavior or variable
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 3-5 students. Your group should treat your
answers to each
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 company; Tata Motors (TTM) and the Overall Bombay
Stock Mar
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
- = marginal effect of X on Y (often has economic interp
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 Variable
We typically refer to x as the
Independent Variable
ECONOMETRICS - SIMPLE LINEAR REGRESSION BY HAND
The following chart shows the relationship between two variables (DCONS = Y-variable,
DINC = X-variable). Economic theory claims there is a linear (straight-line) relationship between
these two variables. Mo