EFTA00370775.pdf

From: Lesley Groff To: Michael Fowler Subject: Re: ATorus Daily Portfolio Report - 4/22 & 4/23 Date: Thu, 24 Apr 2014 12:46:38 +0000 Thx you too Sent from my iPhone On Apr 24, 2014, at 8:43 AM, Michael Fowler I> wrote: Lesley, Please see attached the Daily Portfolio Reports for 4/22 & 4/23. Have a good day. - Daily Commentary - One of our pet peeves is people detecting patterns where there may be none. Reading the following article about Allergen takeover volume spike (Flurry of Allergan Trading Preceded Offer) is a case in point. And this is not say the article or the analysis (especially specific to this one circumstance) is inaccurate. There is just not enough informative statistics disclosed to tell. The article references "the volume ofstock trading during the 10-day period before an announcement was 86% higher than it's average over the previous year...10 days before bullish activist bought stocks disclosed in regulatorypings, the stocks nose on average more than 3.2% more than the overall market based on an analysis of 975 announcements of leading activist investors since 2007." (1) Are the volumes measured in dollar volume traded instead of number of shares? Dollar volume measured as a percentage of either EV or market cap provides more relevant and relative context. (2) Also within the sample size, does that include periods of high and low realized volatility? In periods of high volatility turnover increases markedly. (3) Related to the "average 3.2% more" what was the standard deviation? What was the percentile distribution? What was the on average recent daily movement of these securities. Was the 3.2% unconditional or just noise given realized volatility at that moment? For instance in 2008, when S&P realized volatility was over 3% was the excess movement proportional to the overall market volatility if there are occurrences during this period? We always try to ask ourselves these types questions when we allocate risk, analyze our results, and and then to manage expectations for investors for when our results are either "noise" or are significant. "Humans are very good at detecting patterns, but rather poor at detecting randomness." - Joseph Jay Williams, UC Berkley (I've attached the paper to this email if you have any interest in reading Why are Bad at Detecting Randomness? Because it is HaM.) A few points Best Regards, Michael J. Fowler EFTA00370775  Sent From My Mobile Device The information contained in this electronic mail message is confidential information intended only for the use of the individual or entity named above, and may be privileged. If the reader of this message is not the intended recipient, you are hereby notified that any dissemination, distribution, or copying of this message is strictly prohibited. If you have recieved this communication in error, please immediately notify us by telephone, and delete the original message. <PeopleRandomnessHard.pdf> <ATorus BacktestNAV_042214.pdf> <ATorus BacktestNAV_042314.pdf> EFTA00370776