The Evolution of Trend Following

The rebirth of Quant Hedgefunds?


When it comes to the stock market, trend following involves researching the past movement of a security’s price in order to determine where the price may be headed. This strategy is particularly popular with quant focused funds in which an algorithm within a trading model is trained to trigger position entries or exits based off of pre-determined market moving patterns. The allure of trend following has seemingly diminished as of recent due to poor results. In an article recently published in the economist discussing the reemergence of trend following strategies, the editor keyed in on the fact that the models should not take all of the heat for sub-par returns. One must attach the majority of that blame to recent governmental policies and other unprecedented macro-economic events. Although it may not be able to predict legislative strategies, can unstructured and market sentiment detecting data stemming from social media form the missing piece for the quant model puzzle?

According to Hedge Fund Research, trend following funds have seen total returns drop from a peak of around 18% in 2008, to a paltry -3% in 2013. During this 5 year time period we have seen:

  • A near-complete market shutdown
  • Three (or four depending on who you ask) rounds of quantitative easing
  • The simultaneous buying and selling of long and short-term bonds respectively
  • Most recently, Fed tapering

Needless to say this amount of government intervention upended every single quant fund algorithm that had led to above average returns in the preceding years. The task at hand now involves trend following strategists figuring out a way to protect themselves from erratic macro events. There is no way to predict what the government will do and what the market reaction will be, but adding some touch of a human element to help the machine may help.

Trend following models have long been focused on strictly analyzing the technical aspect of a stock’s movement. This approach ignores many external factors that may additionally effect the price movement. Teetering on the edge of both the quantitative and qualitative realms, there is now enough data gathered from social media that can be paired along side any pre-existing market data to give new insights and possibly expose trends that have never seen the light of day. Some of these data points include but are not limited to:

Funds have definitely taken notice, but have still not figured out how to properly integrate this new information. The answer may lie in taking a synergistic approach between existing and new data sets instead of focusing wholly one on or the other (e.g. DCM Capital Failure).