Financial Data
Analysis (FIN822)
Administrative Issues and Course Overview
TIP
If you do not understand
something,
ask me!
The instructor
 My name is Donglin Li.
 Email: donglinli2006@yahoo.com
 Office hours: M 15:00-17:00(DTC580), Tu 12:00-14:00,
BUS315
http://online.sfsu.edu/~donglin/courses.html
 I will put lecture slides, in-class-work, and project assignments on my web.
 Research interest:
Corporate finance: Agency cost, overinvestment
Accounting: Financial Statement Analysis, Market
Anomalies
Credit Risk Analysis
2
My expectation in this course
I want everyone to be able to
understand fundamental financial statements
carry out basic valuation analysis and credit
analysis
master a set of statistical tools that will help
you identify the relation between some
accounting variables/ratios and stock returns.
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This course has not been
offered for the past 4 years
Please do not expect too high from this
course.
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Reference Books:
you may use any statistics/econometrics
textbook that you are familiar with. The
textbook should cover regression analysis.
or,
 “Introductory Econometrics with Applications” By
Ramanathan, 5e, South-Western.
 “Analysis of Financial Data”, By Gary Koop, John Wiley
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Prerequisite
FIN 819 with a grade of B- or better; FIN
825 and 828 recommended.
This course is about numbers, so you
should have a good knowledge of
financial accounting and statistics.
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Add, drop and withdrawal policy
The business school has the policy for
add, drop and withdrawal
In the first four weeks, you have to get
enrolled in the class, if you want.
Students can withdraw at most once.
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Projects
You will be given 3 projects.
You need to have access to a PC.
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In-Class-Work
There will be 4 in-class work assignments.
The schedule of these in-class projects will
not be announced in advance, so just
come to the lectures.
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Three quizzes and final exam
The quizzes are closed-book and closed
notes. There are no make-ups.
The tests are based on material covered in
lectures, in-class-work, homework, and
projects.
The in-class-work will be relevant for
the quizzes; The quizzes will be relevant
for the final!
10
Class performance
Any attempt to seek undue favor from the
instructor will negatively affect your class
performance.
The instructor cannot assign extra work to
any individual to improve her/his grade.
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Grading
Class performance
Quiz of lowest score
The other two quizzes
Final exam
Projects
Total
5 points
10
40
35
30
120points
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Curve grade
A range Top 30%
B range
Top 80%
The instructor reserves the right to make
minor adjustment if necessary.
The cure might be shifted upward if the
whole class is doing well on average.
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Academic integrity
The instructor has zero tolerance for
cheating or looking at each other during
the exams.
In the exams, please sit as far as possible
from each other.
In doing the in-class-work, feel free to
discuss with your classmates.
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Communicate with the
instructor
Teaching Style: Lectures, problem solving and
computer projects. Please pay attention to what
is covered in class.
I appreciate any constructive suggestions (in
person or through email) that would improve
the course.
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Course organization
This course is broken-down into two parts:
1: Techniques.
2: Applications of these techniques on data
analysis (often analyzing a lot of firm’s
financials at the same time.)
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You also need to understand
financial statements well
Financial analysts use financial statements
to rate and value companies.
External investors read financial
statements to select stocks and decide
when to buy or sell.
Bankers use them in deciding whether to
extend loans and determine loan terms.
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Financial statements may be cooked;
we will introduce some models that
unravel earnings management.
Earnings manipulation
GAAP
Earnings management
Real earnings management
No earnings management
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Equity Valuation Analysis
Discounted cashflow models
Residual income model
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Credit Analysis
Z-scores
 Z=1.2 Net Working Capital/Total assets+1.4 Retained
Earnings/Total assets+3.3 EBIT/Total assets +0.6
Market Value of Equity/Book Value of Liability+1.0
Sales/Total assets
Credit rating methods by S&P and
Moody’s
Logit/Probit models
My own model
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Why is Data Analysis useful?
Because you do not believe in semi-strong
form of market efficiency.
Because you can identify variables/ratios
that might be relied upon to predict future
stock returns.
Earn huge bucks! (in theory)
Another eye-catching item on your
resume.
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In Data Analysis,
We will focus on regression techniques.
Example, is there a significant relation
between firm investment and future stock
returns?
We will discuss several market anomalies.
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One-year-ahead hedge returns based on capital
investment levels. ©Donglin Li 2004
1 year ahead hedge returns between lowest and highest deciles of investment (d_PPE) firms
 Go long the lowest investment
stocks.
0.35
 Go short the highest investment
stocks.
0.3
0.25
 12 month size adjusted buy and
hold hedge returns after May each
year.
Hedge Portfolio Return
0.2
0.15
 Positive in 36 out of 39 years,
average 12.6%
0.1
0.05
0
1962 1964 1966 1968 1970 1972 1974 1976 1978 1980 1982 1984 1986 1988 1990 1992 1994 1996 1998 2000
-0.05
-0.1
 Pattern is consistent with
market mispricing and
inconsistent with semistrong efficiency.
Year
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