Syllabus
ISQS 7342: Advanced Topics in Business Intelligence  Financial
Market Analytics
Fall 2012
Class Meeting: TR, 2:003:20p, BA 271
Instructor: Zhangxi Lin
Office: BA E311, Tel: (806) 8341926, Email:
zhangxi.lin@ttu.edu

Financial
Market Analytics:
Definition: The applications of
information technology and statistical methods to covert financial market data
into knowledge for decision making, where the financial market is the one for
buying and selling of the monetary goods, such as stock, commodities, and their
derivatives, or different kinds of financial services, such as credit risk
management, loan services, etc.
Course
Description:
This course is designed
for those who intend to further improve their skills in applying analytical
methods and techniques in financial market analysis. The course is to address
topics in three aspects with the focus on analytical problem solving:
1.
Solving
financial engineering problems with the Monte Carlo method
2.
Security
market analytics
3.
Financial
problem solving in the advanced BI approach
Students will
master the skills of modeling with SAS Enterprise Guide 4.x, and advanced
applications of Excel. Cases in financial market analytics, such as Monte Carlo
simulation, financial market forecasting, portfolio optimization, and capital
asset pricing modeling will be covered.
Topics:
1.
Monte
Carlo simulation for financial engineering
2.
Pairs
trading analytics
3.
Financial
time series analysis
4.
Analytical
results visualization and reporting
Software
tools:
Base SAS
SAS Enterprise Guide 4.x
Microsoft Excel
Prerequisite: A mediumlevel
statistics course, basic skills of analytical tools (e.g. Excel), and basic
concepts of financial markets.
Learning Outcomes:
A student who
successfully completes this course should be able to:
1.
Solve
basic financial engineering problems with Monte Carlo simulation methods
2.
Implement
statistical arbitrage projects
3.
Financial
time series analysis
4.
Visualize
and present the analytical results.
Assessment of Learning Outcomes:
1.
All
the relevant theories for financial market analytics will be assessed by exams.
2.
All
the skills in financial market analytics will be assessed by inclass exercises,
homework, and the term project.
3.
The
comprehensive ability to carry out a financial market analytics will be
assessed by the term project including both report and presentation.
Required textbooks:
·
Financial Modeling – Uses Excel, by Simon Benninga, Publisher: The MIT Press; third edition (January
8, 2008), ISBN10: 0262026287, ISBN13: 9780262026284
·
SAS
Course Notes (eversions are available to registered students)
o
Querying
and Reporting Using SAS® Enterprise Guide®
o
SAS Enterprise Guide: ANOVA,
Regression, and Logistic Regression Course Notes, ISBN: 9781612901770
Optional Textbooks:
·
SAS for Monte Carlo Studies: A Guide
for Quantitative Researchers, ISBN: 9781590471418,
2002
·
Statistical Arbitrage:
Algorithmic Trading Insights and Techniques (Wiley Finance) by
Andrew Pole (Hardcover  Oct 5, 2007)
·
Pairs Trading:
Quantitative Methods and Analysis (Wiley Finance) by
Ganapathy Vidyamurthy,
ISBN10: 0471460672, ISBN13: 9780471460671, 2004
References:
·
Textbooks
1.
Monte Carlo Methods
in Financial Engineering (Stochastic Modelling and
Applied Probability)
by Paul Glasserman (Paperback  Nov 19, 2010)
2.
Principles of
Finance with Excel, Second Edition, Simon Benninga,
ISBN13: 9780199755479, ISBN10: 0199755477, Hardback, 816 pages, Sep 2010, 816
pages
3.
Simulation and
Monte Carlo: With applications in finance and MCMC, J. S. Dagpunar, ISBN: 9780470854952, 348 pages, Wiley, March
2007
·
SAS Materials
1.
SAS for Forecasting Time Series,
Second Edition, ISBN:
9781590471821
2.
Using SAS in
Financial Research, Ekkehart
Boehmer, John Broussard, and Juha Pekka
Kallunki, ISBN: 9781590470398, SAS Press,
February 2002
3.
Forecasting Examples
for Business and Economics Using SAS, ISBN: 9781555447632
4.
Stock Market Analysis
Using the SAS System: Portfolio Selection and Evaluation, ISBN: 9781555446239, 1994
Tentative course schedule
Week 
Lectures 
Assignments 
Exams 
1 
Introduction 


27 
Monte Carlo
simulation in finance 1)
Generating Random Numbers and Random variables 2)
Monte Carlo Simulations 3)
Estimating Default Risk and ValueatRisk 4)
Modeling Time Series Processes 5)
Portfolio optimization 6)
Financial engineering cases 
5 exercises 
3 quizzes 
813 
Portfolio analytics 1)
CAPM model 2)
Time series 3)
Pairs selection 4)
Risk management 5)
Testing for tradability 6)
Algorithmic trading cases 7)
Advanced topics 
5 exercises 
3 quizzes 
14 
Review

Presentations
and discussions 
1 quiz 
15 

Term
project 
Final
exam 
Grading
Policy:
The total is 320 points.