Download - 125.785 Research Methods in Finance
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125.785 Research Methods in Finance
Seminar One
Monday 17 July
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Honest politicians make the other 95% look bad
-- Mark Twain
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Overview
Administrative Issues– Timetable– Labs– Textbook– Assessment
Aims and Objectives Introduction
– Eviews
Readings: Chapters 1-3, Chapter 16 optional
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Administration
The general format will be for 1st half– A 2 hour seminar– A 2 hour lab in either CLQB4 or IIMS5/6– Finish approximately 7pm.
Textbook is Studenmund
Using Econometrics: A Practical Guide. 5th Ed.– 4th Edition can also be used.
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Assessment
1 Assignment Due September 1: 20% Quiz 1: 31 July (10%) Quiz 2: 14 August (10%) Quiz 3: To Be Advised (10%)
– Probably 28 August
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Web Support
Web CT should be available for students In the interim, the following website also will
have material: http://www.massey.ac.nz/~bjmoyle/mu/teach.html
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Computer Labs
Your user-name is your student ID Your password is your 4 digit pin number You will benefit from bringing
– A floppy disk OR– A USB drive (preferred)
We will use Eviews for this section of the course
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Learning Objectives
Develop your skills at estimating economic relationships.– This skill cannot be memorised from a textbook or
lectures– The textbook and seminars are to assist and
guide you.
Increase your familiarity with statistical software.
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Learning Outcome
To give you a sufficient background that you can:– Attempt a research project with some of the skills
you have learned; or– Can progress on to advanced techniques used in
financial econometrics without difficulty.
It is impossible to teach you all the tools you might use in the constraints of this paper.
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The Unreliability of Textbooks
This is an applied paper, not a theory paper.– Every data set you model, will have ‘different’
problems present.– It is impossible to memorise all the permutations of
problems that you will encounter.– Skilled researchers are those with good problem-
solving strategies, not recall of textbook stylised facts.– Most of this skill must be developed with practical
work.
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Introduction to Research
A research project involves three stages– Choosing a Topic– Analysis– Writing Report
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Choosing a Topic
Ideally choose something you are interested in for motivation
Make sure you can get enough data Make sure there is some substance to topic
– Not purely descriptive– Not tautological (so obvious to be uninteresting).
E.g. does an increase in the number of bidders raise prices?
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Analysis
Develop your theoretical model first– May involve reading literature
Specify the model– What causes what?
Hypothesise the effects you expect– This must be done before you run any models
Collect the data
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Analysis 2
Estimate the Equation– This should take the least amount of effort
Document the results– There must be enough information given, that
someone else could replicate your results.
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Report Writing
This is an important step– The purpose of research is often to generate
information for a decision-maker.– Hopefully, a manager or policy-maker could read
your report and learn something new.
A box of computer printouts, neither informs nor impresses.
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Report Writing 2
A report should not gloss over or ignore results that you did not expect.– It is a common mistake to not discuss results that
contradict your prior beliefs.
Keeping a research journal can assist– Record your hypotheses, regression results,
statistical tests etc.
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Practical Advice
Use common sense and economic theory– E.g. Real variables should not be matched with
nominal.
Ask the right questions– Sometimes regression problems are a
consequence of the wrong specification
Know the context– Understand the problem, not just the statistics
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Practical Advice 2
Inspect the Data– Graphs or summary statistics can reveal missing
variables, outliers or other anomalies. Keep it sensibly simple
– Complexity is not ‘good’ for its own sake– Consider Occam’s Razor.
Look long and hard at your results– Does it make sense? You have to explain this to
others.
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Practical Guide 3
Practice data-mining with care– Exhaustive experimentation to ‘get’ the ‘right’
results shows you’re biased…
Be prepared to compromise– Trying to find the perfect model will drive you
crazy. – Real data tends to throw up intractable problems.
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Practical Guide 4
Do not confuse statistical significance with meaningful magnitude.– Trivial variables may have very small effects, but
are highly significant.– It is tempting to use statistical significance as a
measure of a model’s performance. Report a sensitivity analysis
– Do results vary of you change the sample period etc?
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Basic Stats
We use statistical tools in this paper
– But it is not a course in statistics
We will estimate the value of many parameters
E.g.– A mean (average)– A regression coefficient
We signal our uncertainty about the parameter with a type of ‘spread’.
E.g.– Variance– Standard Deviation
These uncertainty measures form the basis of statistical tests.
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Recap
The main difference between statistics and other maths, is answers will have 2 dimensions
In normal algebra, variables combine to produce an explicit solution.
In statistics, we think in 2 dimensions– What we think the value of something is– How confident we are in that estimate
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Correlation
Quantifies the relationship between 2 variables.
-1 ≤ r ≤ 1 Correlations imply
– Relationships or associations
– General tendencies
Correlations do not prove causality
Correlations can be shown graphically
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Correlation between GDP and G
0
5000
10000
15000
20000
25000
0 10 20 30 40 50 60 70
CG
DP
CG
CGDP
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Regression
Suppose we wanted to– Forecast prices for an
asset.– Determine causes of
unemployment
A regression “models” finance or economic data
Regression Models can be used for several purposes.
– Forecasting– Testing hypotheses– Detecting influential
variables
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Simple OLS Model
We begin with the Ordinary Least Squares (OLS) regression model
This generates a ‘straight line’ between 2 variables.
The line ‘approximates’ the relationship between the two variables
The variables are– Dependent (Y)– Independent or
explanatory (X).
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Regression Example
Y is GDP per capita X is Govt spending We ‘explain’ Y in terms
of X We can estimate Y if
we know– Intercept of line-
constant– Slope of line
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Note on Regression
Researchers can (potentially) use many different regression techniques.
OLS is a convenient starting point.– But not all regression models use least-squares
methods.– If certain assumptions are met, OLS is the best
method to use.
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Intuition
OLS is based on Cartesian Geometry.– The line we estimate (with intercept and slope),
comes closer to all the observations than any other line.
– We minimise the (sum of) distance between the line and the observations (squared). This is an idea that draws on geometry.
– As a minimisation problem, it can be readily solved with differential calculus.
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Eviews
Eviews is a popular (and powerful) econometrics program.– It is the software most students use for their
graduate research reports
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Where menu to estimate equations is located
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Equation Estimation Menu
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Dependent Variable
Explanatory Variable
Constant
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Output
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Readings
Studenmund– Chapter 16 Statistical Principles– Chapter 1-3
WebCT– Guide to Eviews- Introduction