Harry Long is the inventor of Hedged Contango Capture and Hedged Convexity Capture and is the Managing Partner of Zomma, an innovative algo creator which specializes in predicting moves in the Brent/WTI spread.
Mr. Long is a globally recognized expert on the research and development of quantitative investment strategies. The Zomma IP portfolio of strategy indices is sought after by asset management firms, investment banks, hedge funds, principal trading organizations, index providers, ETP sponsors, and private equity firms to help them develop and deploy active manager-crushing quantitative investment strategies.
Zomma helps global institutions create long term value by replacing emotional decision making with cutting-edge technology based upon objective evidence.
Mr. Long is a graduate of Rice University with a B.A. in Economics.
Evidence-based methods are the cutting edge. Algorithms which use evidence based methods create the potential for out-sized advantages for investors who embrace them.
Financial markets have undergone a tremendous shift in the past decade. Large herds of investors quickly herd in and out of popular indices at the click of a button.
These movements create large statistical footprints and exhibit classic herding behavior. However, separating signal from noise is difficult without cutting edge technology.
The major question for today's investor is: are we long or in cash?
The Zomma Directional Algorithm seeks to answer that question
The Inefficiency of Fundamental Information in Financial Markets
Valuable fundamental information is imperfectly distributed.Therefore, prices move before all competitors in the market have the complete fundamental picture. These price moves leave large statistical footprints.
The fundamental reasons for many major price moves are only widely known days or weeks later. In addition, the reaction to important economic events is contained in the herding behavior of market participants, not in the economic data itself.
Predicting financial market moves using mathematics is one of the world’s most difficult technological challenges.
We have created an algorithmic solution to this problem using price data, with a novel approach. The results have been significant.
Zomma Algorithms utilize evidence-based methods to identify robust risk reward signals by separating signal from noise.
Our technology was developed in a live, walk forward environment. This allowed for modeling that was not vulnerable to over-fitting of historical data.
The algorithm is run on a web-based charting system. We chose this approach to offer maximum up time and avoid dependency on additional local hardware. The result is minimal incremental cost and maximum stability.
Our Technology Has Been Embraced By Large Institutional Clients In the Oil Markets
Zomma's current and former clients include a global physical oil trading firm, and one of the top three global investment banks for energy trading.
Use Of Hypothetical Results
Hypothetical performance results have many inherent limitations, some of which are described below. No representation is being made that any account will or is likely to achieve profits or losses similar to those shown; in fact, there are frequently sharp differences between hypothetical performance results and the actual results subsequently achieved by any particular trading program. One of the limitations of hypothetical performance results is that they are generally prepared with the benefit of hindsight. In addition, hypothetical trading does not involve financial risk, and no hypothetical trading record can completely account for the impact of financial risk of actual trading. For example, the ability to withstand losses or to adhere to a particular trading program in spite of trading losses are material points, which can also adversely affect actual trading results. There are numerous other factors related to the markets in general or to the implementation of any specific trading program, which cannot be fully accounted for in the preparation of hypothetical performance results and all which can adversely affect trading results.