| Software Engineering Project: Web-based Stock Forecasters |
Think of yourself as “...one of those gold prospectors with a tin pan, searching for gold in a river, and the river [is] the stream of information and gossip blogs.”
Your job is “to listen to all these rumors and find this one gold nugget of information.” — William R. Barzee
“The Man Who Was ‘Octopussy’,” By Paul M. Barrett
Book, Section 1.5.5 Web-based Stock Forecasters
Two groups worked on this project, each with a somewhat different take at it.
Developed in the Spring 2014 semester by Peter Zhang, Vincent Chen, Robert Adrion, Syedur Rahman, Robin Karmakar, Mohammed Latif, and Manoj Velagaleti
Project report #3 (final), group
#3, Spring 2014
[PDF document; size: approx 12 MBytes]
Project files, group
#3, Spring 2014, in case you want to
install the full software locally on your computer.
[ZIP file; size: approx 67 MBytes]
Developed in the Spring 2014 semester by Krisha Paula Olanday, Vinay Panjabi, Vinay Shivakumar, Neha Desai, Jonathan Haas, and Sivaramharesh Siva
Project report #3 (final), group
#9, Spring 2014
[PDF document; size: approx 2.8 MBytes]
Project files, group
#9, Spring 2014, in case you want to
install the full software locally on your computer.
[ZIP file; size: approx 7 MBytes]
Developed in the Spring 2013 semester by Asim Alvi, Frank Bohn, Giovanni DeGrande, Andrew Demoleas, Eric Lee, and Sangit Patel
Project report #3 (final), group
#11, Spring 2013
[PDF document; size: approx 1.5 MBytes]
Project files, group
#11, Spring 2013, in case you want to
install the full software locally on your computer.
[ZIP file; size: approx 12 MBytes]
Software projects developed in the Spring 2008 semester of Software Engineering of Web Applications:
Stock Market Prediction, from Wikipedia, the free encyclopedia.
Yahoo! Finance: Basic Technical Analysis, e.g., Bank of America, ticker symbol BAC
Google Prediction API
Google’s Prediction API is a new service that lets developers make their applications “intelligent.” The service can be applied for many things, from tell you what language a certain string is, to having it monitor transactions for things that may be fraudulent. It is basically a big “black box” that you can send historic data into, and then ask it questions about the future.
② Esignal
③ CQG
⑥ Stock-Forecasting.com:
Using Neural Network to Predict Stock’s Trend
SF
software demo
Check for the links along the top line: Company Finder | Profit
Calculator | Forecasting | Portfolio | Testing
E.g., Company
Finder (MTS) is completely automatic software that simulates trade
with an initial investment of $1000 for every company from S&P 500
list and follows the daily update 10 days predictions trend.
Investopedia: Investment learning site
Risk Glossary: Investment learning site
Trade2Win.com: Why
Trade? by Robert Newgrosh - June 30, 2005
A discussion of the reasons why people get into trading, and the
impact those reasons can have on their performance.
Stocks:
Love That Volatility!
For day traders, explains a
former practitioner, all movement is good movement.
BusinessWeek Slide Show: Tips for Winning at Day Trading
Hedge fund description at Wikipedia
Managed futures funds use computer models to find trends in currencies, stocks, bonds, and other markets. Once the managers spot a trend, they try to capitalize on it by buying and selling futures contracts and other derivatives.
TIME: Stock
Technicians’ Verdict: The Market Rally Will Continue
Stock technicians, who use mathematical formulas as
well as charts and historical data to figure out where share prices
are headed, believe the market’s rally that started in early
March 2009, and has pushed stocks up 36% in less than two months, is
here to stay. They say stocks will rise another 10%, before the market
stalls...
A collection of relevant links available here.
Apache Axis engine for
developing and deploying Web services.
(The current
version of Axis is written in Java, but a C++ implementation of the
client side of Axis is being developed.)
Perhaps the best way to start is with Axis User’s
Guide
An introductory description of the Delphi
method
An in-depth review of the Delphi
method:
M. Turoff and
S. R. Hiltz: "Computer Based Delphi Processes", in M. Adler and
E. Ziglio (Editors), Gazing Into the Oracle: The Delphi Method and
Its Application to Social Policy and Public Health, London, UK:
Kingsley Publishers, 1995.
Computer
model says UNC will win tournament
-People are using computer models to try to pick NCAA basketball
winners
-A successful model from Georgia Tech picks UNC to win this year
-Georgia Tech professor Joel Sokol’s statistical model predicted last
year’s winner
-As more data is available online, the practice appears to be more
popular
-Kenneth Massey’s Web site, http://www.masseyratings.com/, lets users
compare the analyses
-One professor says it’s more fun to watch for fun than fill out
bracket
See also Georgia Tech Professors Predict Final Four Match Ups
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Last modified: Mon Feb 25 13:13:51 EST 2008 Maintained by: Ivan Marsic