Financial Data Analysis (FIN822)

TIP If you do not understand

something,

ask me!

Administrative Issues and Course Overview

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The instructor

My name is Donglin Li. Email: donglinli2006@yahoo.com Office hours: M 15:00-17:00(DTC580), Tu 12:00-

14:00, BUS315http://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, overinvestmentAccounting: Financial Statement Analysis, Market

AnomaliesCredit Risk Analysis

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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!

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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 5

pointsQuiz of lowest score 10 The other two quizzes 40

Final exam 35Projects 30 Total

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

Earnings management

Real earnings management

No earnings management

GAAP

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Equity Valuation Analysis

Discounted cashflow modelsResidual 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 modelsMy 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

Go long the lowest

investment stocks.

Go short the highest investment stocks.

12 month size adjusted buy and hold hedge returns after May each year.

Positive in 36 out of 39 years, average 12.6%

Pattern is consistent with market mispricing and inconsistent with semi-strong efficiency.

1 year ahead hedge returns between lowest and highest deciles of investment (d_PPE) firms

-0.1

-0.05

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

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