Lucena means actionable investment insights from Big Data
Lucena Strategies demonstrate the power of QuantDesk®
Lucena leads the way in Predictive Analytics
Lucena Research Team
Lucena’s team represent a combination of academia, business experience, and software development expertise that provides a highly unique and complimentary skill set. Co-founded in 2014 by entrepreneur and technologist CEO Erez Katz and machine learning and artificial intelligence expert, Chief Science Officer Tucker Balch, Ph.D, Lucena Research partners with data providers and develops algorithms that can validate and enhance investment strategies through advanced analytics of big data.
Using Dynamic Models To Adjust To Changing Market Conditions One of the biggest fallacies of quantitative strategy development is the belief that a successful model will continue to outperform indefinitely. Many quant funds mistakenly fall in love with an investment strategy on which they have spent substantial R&D capital and countless hours developing. Understandably, when the strategy stops performing, it’s hard to throw all that hard work away and start from scratch. A way to prolong a strategy’s life is to design it with the notion of self-adjustment. These strategies are harder to develop but ultimately provide the unemotional self-adjustment context when they are deployed live.
Lucena Research and Nasdaq’s Analytics Hub are proud to introduce MELS: Multi-Expert Factors Long/short. MELS is an ensemble, or group, of factor models that have been trained using Machine Learning. Research shows that ensembles of classifiers perform better than a single model and more accurate and less susceptible to overfitting. MELS experts are single asset screen utilizing hundreds of factors.
Lucena Research’s Chief Scientist Tucker Balch, Ph.D. was tapped by the White House’s Office of Science and Technology Policy to advise the G7 on Artificial Intelligence policy. Balch will represent the U.S. at a G7 conference in Turin, Italy. He, and 4 other U.S. innovators will advise the G7 on A.I., Big Data, and the future of A.I at the work place. The goal of the panel is to recommend policy to address the multiple challenges innovation poses that cannot be faced only at national level.
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