Monday 1st October 2012 – 12:30 to 13:30
Speaker(s): John Guerard (Director of Quantitative Research, McKinley Capital, USA)
Stock selection models often use momentum and analysts’ expectations data. We found continued support for composite modeling using these sources of data for United States, international, and global equities during the 1998-2009 time period. We found additional evidence to support the use of APT multi-factor models for portfolio construction and risk control. Investing with expectations data and momentum variables is a good investment strategy over the long-run. We find additional evidence to support the use of multi-factor models for portfolio construction and risk control. The anomalies literature can be applied in real-world portfolio construction. We find support for the use of tracking error at risk estimation procedures. One cannot achieve perfection in portfolio creation and modeling; however, the McKinley Capital Management Quantitative Research processes have passed the Markowitz and Xu (1994) Data Mining Corrections test as reported in Guerard, Chettiappan, and Xu (2010) and Guerard, Xu, and Gultekin (2012).