Abstract

http://ssrn.com/abstract=940729
 
 

References (114)



 
 

Citations (4)



 


 



Using Adaboost for Equity Investment Scorecards


Germán G. Creamer


Stevens Institute of Technology - Wesley J. Howe School of Technology Management

Yoav Freund


University of California, San Diego

2005

Howe School Research Paper
NIPS Workshop Machine Learning in Finance, 2005, Whistler, British Columbia, Canada

Abstract:     
The objective of this paper is to demonstrate how the boosting approach can be used to define a data-driven board balanced scorecard (BSC) with applications to S&P 500 companies. Using Adaboost, we can generate alternating decision trees (ADTs) that explain the relationship between corporate governance variables, and firm performance.

We also propose an algorithm to build a representative ADT based on cross-validation experiments. The representative ADT selects the most important indicators for the board BSC. As a final result, we propose a partially automated strategic planning system combining Adaboost with the board BSC for board-level or investment decisions.

Number of Pages in PDF File: 25

Keywords: Boosting, machine learning, corporate governance, balanced scorecard, planning, performance management

JEL Classification: C49, C63, G38

working papers series





Download This Paper

Date posted: October 28, 2006 ; Last revised: January 26, 2014

Suggested Citation

Creamer, Germán G. and Freund, Yoav, Using Adaboost for Equity Investment Scorecards (2005). Howe School Research Paper; NIPS Workshop Machine Learning in Finance, 2005, Whistler, British Columbia, Canada. Available at SSRN: http://ssrn.com/abstract=940729 or http://dx.doi.org/10.2139/ssrn.940729

Contact Information

German G. Creamer (Contact Author)
Stevens Institute of Technology - Wesley J. Howe School of Technology Management ( email )
1 Castle Point on Hudson
Hoboken, NJ 07030
United States
2012168986 (Phone)
HOME PAGE: http://www.creamer-co.com

Yoav Freund
University of California, San Diego ( email )
9500 Gilman Drive
Mail Code 0502
La Jolla, CA 92093-0502
United States
Feedback to SSRN


Paper statistics
Abstract Views: 2,373
Downloads: 701
Download Rank: 19,534
References:  114
Citations:  4

© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.  FAQ   Terms of Use   Privacy Policy   Copyright   Contact Us
This page was processed by apollo3 in 0.391 seconds