|PROPRIETARY SERVICES |
EVENTS PERFORMANCE ANOMALIES
We have a number of specific databases that will track companies for the following events:
- Identification (Name and Ticker Change)
- Splits (since 1980)
- True Mergers
- Secondary Offerings
- Dividend Dynamics (Initials, Resumptions, Cuts, Omissions)
- Wall Effect
- Investor Behavior Effect
- Anticipated Surprise (are analysts too optimistic in EPS estimates?)
- Analyst Effect
- Volume Effect
- EQTP Improvement Effect
- SUPERMO Effect
We then use our own research and that of academic studies to provide performance predictions each quarter.
ZPR has many years of experience testing special company events and analyzing specific investment strategies. As a by-product of ZPR's years of testing specific investment strategies, we have produced the Event Analysis Database. Then ZPR diligently determined the validity of the data for investment decision-making.
Because of the synergy between the ZPR ICX 3000 Database and the databases that make up these special effects, we have the ability to analyze the excess return performance on a quarterly and monthly basis. We can also analyze the size adjusted excess return performance on quarterly performance. Furthermore, we are able to further break down these databases into smaller groups and even subgroups that are specific to certain characteristics of the companies. This allows us to see if performance significantly differs for any of these groups and/or subgroups as opposed to the entire database of companies. We determined whether the event for the company is an immediate intersection or lagged (delayed) intersection.
ZPR has many years of experience testing these special events and quantitative strategies. If you have an investment strategy or quantitative model that you would like tested (either for historical information or for current prediction use), ZPR can professionally and thoroughly complete the task. The event analysis database can be acquired separately or as part of the Integrated Effects Data Browser system.