From: Michael Fowler cj To: Subject: ATorus Daily Portfolio Report - 3/26, 3/27, & 3/28 Date: Tue, 01 Apr 2014 16:31:16 +0000 Attachments: ATours_BackTestNAV 032814.pdf; ATours_BackTestNAV_032614.pdf; ATours_BackTestNAV 032714.pdf Please see attached the the Daily Portfolio Reports for 3/26, 3/27, & 3/28. Hope you had a good holiday! Daily Commentary Over the past few days there has been considerable discussion on the topic of 'Big Data' analysis specifically related to Google Flu Trends in the media. Some like to use the example of Google's algorithm to predict flu trends (pure statistical approach) recent under performance versus the 'theory-based' CDC model as evidence of 'Big Data' limitations. Google Flu Trends Show the Limits of Big Data Big Data: Are We Making a Big Mistake? While many carry on this discussion as if these methodologies are mutually exclusive. Our approach is more similar to 'Big Data' analysis, but this is only a part of the story.We have done considerable research and analysis over the years to help us identify asymmetries in asset returns given an understanding of causation versus correlation. This allows us to optimize the portfolio construction. This analysis includes for example relationships between FCF Yield to market Capitalization (proprietary study we've collaborated with Credit Suisse HOTLT) and 4 Week Rate of Change of US Jobless Claims to 4 Week Rate of Change in SPX. In a quest to continually improve alpha capture we continue to expand the scope of our research looking at questions such as: When volatility materially increases should the opportunity set change? Would a bias toward mid-cap versus mega-cap securities generate higher volatility adjusted out performance? Is shorting securities (only when we get sell trade signals) that have relatively high FCF to equity the most optimal use of the capital? We believe a 'Big Data' like approach to trading discipline specific to timing of position entry, exit