Roughly 20 years ago, there was a paradigm shift in the investment world. A segment of investors, who over time became known as activists, started taking a more aggressive, hands on approach toward the corporations they invested in, looking to influence a company’s direction by exerting their control through ownership.
Shareholder activism continues to be a growing trend, which is why, in 2014, Q4 set out to create a unique and proprietary approach to identifying activist activity in real-time. Q4’s AA uses sophisticated models and historical analysis to create a baseline, or assumptive “normalcy”, for each stock. Through machine learning, algorithms closely monitor equity and options order flow, including liquidity analysis, volume velocity, and trade pattern recognition, to identify when current trading activity veers from pre-set norms.
When these norms are broken in such a way as to match the historical “footprints” left by activist investors, the alarm score begins to spike. These spikes are an indication that an activist investor could be building a significant position in the security. Q4’s AA is a differentiated model for detecting real-time activist movements, helping institution investors track and predict activist investor movements in the open market.