We are Forward Thinkers.
Our thesis is simple. Let's dive in.
Family Offices // Foundations // Pensions // Endowments // Fund of Funds // Public Institutions // RIA's
overview
We believe computers
are critical to finding sustainable edge
in the ever evolving
financial markets.
Investors are inundated with data and opinions on a daily basis, making it hard to know when to take action. DropShot's core technology uses Machine Learning to search through mountains of data, finding signals that stand the test of time. We strive to take the guess work out of portfolio rebalancing and leave our clients with highly favorable outcomes. Our totally systematic approach is multi-faceted, relying on both diversified alpha and dynamic market exposure.
The Theory
Hypothesis
Active, automated strategies based on machine intelligence can achieve market outperformance over time, especially relative to passive or human discretionary trading methods.
Context
Of public equity assets in the US, worth $31 Trillion, only 2.4% of the trading is accounted for by quantitatively focused funds. (Economist, Oct 2019) This stands in contrast to many reports that algorithmic trading dominates the markets. In truth, many orders are executed electronically, and thus get classified as ‘algo trading’ but this is not the same as using quantitative methods to trade systematically.
Evidence
Our past success has made us believe even more in our systematic approach. We are really trying not to have any trace of human complacency in our process, letting science drive the decision making. Past performance does not guarantee future success after all, but hard work doesn’t hurt.
Conclusion
Ultimately, our past trading performance is the litmus test for this idea. We have always operated systematically, using machine learning algorithms. Therefore, our nearly 5-yr track record is the perfect way to test the hypothesis.