Comparing the Effectiveness of One- and Two-step Conditional Logit Models for Predicting Outcomes in a Speculative Market

Sung, Ming-Chien and Johnnie Johnson
Additional contact information
Sung, Ming-Chien: Centre for Risk Research, School of Management, University of Southampton
Johnnie Johnson: Centre for Risk Research, School of Management, University of Southampton

Journal of Prediction Markets, 2007, vol. 1, issue 1, pages 43-59

Abstract: This paper compares two approaches to predicting outcomes in a speculative market, the horserace betting market. In particular, the nature of one- and two-step conditional logit procedures involving a process for exploding the choice set are outlined, their strengths and weaknesses are compared and their relative effectiveness is evaluated by predicting winning probabilities for horse races at a UK racetrack. The models incorporate variables which are widely recognised as having predictive power and which should therefore be effectively discounted in market odds. Despite this handicap, both approaches produce probability estimates which can be used to earn positive returns, but the two-step approach yields substantially higher profits.

Date: 2007

Downloads: (external link)
http://www.ingentaconnect.com/content/ubpl/jpm/2007/00000001/00000001/art00004 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: http://EconPapers.repec.org/RePEc:buc:jpredm:v:1:y:2007:i:1:p:43-59

Ordering information: This journal article can be ordered from
http://www.predictio ... ex_files/Page418.htm

Access Statistics for this article

Journal of Prediction Markets is edited by Nottingham Business School Leighton Vaughan Williams

More articles in Journal of Prediction Markets from University of Buckingham Press
Series data maintained by Victor Matheson, College of the Holy Cross ().