The term sentiment or momentum piece of our portfolio strategy is the entire to the entire process. The quant looks to sell and go into cash before the correction gains momentum and likewise, tries to signal a buy trade once the upward momentum is confirmed.

All of our portfolios are actively managed using term sentiment or a momentum trading algorithm. Further, this algorithm initiate buys and sells signals; this takes human emotion out of the portfolio management and allows for the process to be repeatable. This also seems to add significant alpha, particularly during market corrections.

Before we look into moving price data we establish a stock holding profile. This data which includes: minimum days held, maximum days held, trade profile mean, and trade profile standard deviation then projects max held days. Trading volume is also evaluated similarly as we look at past levels and trends to establish benchmarks. 

Due to our emphasis on being risk averse the one anomaly that occurs is that the number of “losing” trades normally outnumber the number of “winning” trades. Where we have found our success is the fact that a “winning” trade has had considerably higher returns that of a losing trade. Think of a teeter-totter seesaw with risk on one side and return on the other; most models have these two factors balanced. What we do is move the fulcrum point toward the returns side; although it takes greater factors to produce a trade each trade then causes higher returns over less than half the transactions. Most of our portfolios reside in the top left quadrant (higher return / less risk) on the typical Risk Reward benchmark scatter graph.