New residential housing construction bounced back in July. Although the consensus forecast was looking for a handsome rebound, the actual results were substantially better than expected. Housing starts revived to a 1.093 million annualized rate last month, which is well above the revised 945,000 pace for June. Newly issued building permits also posted a strong improvement in July. The bottom line: the worst fears for the housing sector have crumbled in the wake of today’s release from the US Census Bureau.
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Making informed choices about active managers has never been anyone’s idea of a picnic, but ongoing developments in R packages eases the burden. Consider the essential work of factor analysis, which is a statistical technique for identifying the sources of risk and return in a portfolio through an objective prism. If nothing else, performing this task is the antidote to marketing hype that permeates the world of investment management. The gold standard for analyzing equity portfolios is regressing the returns against the Fama-French data set (FF), which is updated regularly at Professor Ken French’s web site. In the old days, the chore of downloading FF data, copying it into Excel, and running the analysis was quite tedious and time consuming, as this 2001 how-to article by Bill Bernstein reminds. If you had a deft hand in spreadsheet analysis, maybe you could slice and dice a fund’s history in ten minutes. Fast forward 13 years and you’ll find that factor analysis has become a snap. Using the R code I’ve written below, we can download the necessary data and run the analysis in less than ten seconds for each fund.
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