Our Collection of the Leading Voices in Autonomous Learning Investment Strategies (ALIS)
Board to help MOV37 find, develop and nurture the new wave of young talent revolutionizing investment management.
New York, March 8, 2018 – MOV37, the research and investment platform for Autonomous Learning Investment Strategies (ALIS), has assembled an Advisory Board to help find, develop and nurture the young talent that will revolutionize investment management.
“The Advisory Board’s primary role is to push us outside our intellectual comfort zones,” says Adil Abdulali, Chief Science Officer and President at MOV37.
The Board will partner with MOV37 in exploring how technology is fundamentally changing investment management and identifying and supporting the young ALIS managers at the forefront of that disruption. MOV37 gains access to people and concepts that are unparalleled in the fields of artificial intelligence, data science, alternative data, blockchain and ALIS through the new Board:
Raphael Douady earned his math PhD in Hamiltonian systems in Paris and holds the Robert Frey Endowed Chair for Quantitative Finance at Stony Brook, New York. He has won a gold medal in the International Mathematical Olympiad where top students compete from over 100 countries. Raphael is a non-linear thinker. He collaborated with Nassim Taleb to develop the mathematical foundations of “anti-fragility”, a key theory that extends our understanding of disorder in the world. Raphael also founded Riskdata and DataCore, companies built around his non-linear theory of risk using polymodels.
Hugo Liu is Chief Scientist at Artsy, the leading online marketplace for contemporary art. He joined Artsy through its acquisition of ArtAdvisor, a data science startup Hugo cofounded, which developed a breakthrough technology for valuing contemporary art and forecasting the art market based on cultural machine learning. Previously, he was Chief Scientist of taste prediction startup Hunch, and Principal Scientist of algorithmic merchandising at Ebay. His academic research includes computational sociology, sentiment analysis, and commonsense reasoning. Hugo received a BS in Electrical Engineering, a M.Eng in Artificial Intelligence, and a PhD in Media Arts and Science from the MIT Media Lab.
Rob Reitzen is the Founder of Random Order Inc., an innovative software design and development company that specializes in highly scalable machine learning methodologies and is based in Los Angeles, CA. Rob studied probability and game theory at UCLA, ultimately pursuing a career as a professional blackjack player in the 1980s. He began to leverage his knowledge in artificial intelligence and machine learning to develop new innovative data-driven blackjack techniques to exploit inefficiencies, achieving “Alpha” through the prediction of “nonrandom shuffles”. In the early 1990s, Rob co-founded Core Partners and Core Capital Management, a “think tank”, where he further developed his AI and machine learning technologies and equipped Core’s players with his advanced strategies, going on to win millions. Rob holds multiple patents for his poker strategies and gaming systems; in 2004, he licensed his poker technology to Momentum Investment Services, which went on to win over $34 million from 2004 to 2006.
Nate Sauder is a co-founder of Syntropy Farms which uses AI and proprietary neural network augmented devices to improve the efficiency of indoor farms. He was the Chief Scientist at Enlitic, a medical deep learning company which utilized unique algorithms to bring together medical images, text and other data sources to assist radiologists in making diagnoses. Nate previously studied Mathematics, Computer Science and Physics at the University of Chicago, the University of Oxford, the University of British Columbia and the University of Toronto.
Zubin Siganporia founded QED Analytics, a consultancy specializing in mathematical modelling and data science. His work has spanned a wide variety of industries, including cryptography, financial algorithms, genetics, and the design of strategy and training systems for world-leading sports teams and Olympic squads. Zubin’s work in finance has involved acting as an expert witness in a high-profile legal case between hedge funds, leading the risk analysis for major banking deals, and investigating computer-based trading for HM Treasury and the Government Office for Science. Alongside his work at QED, Zubin is a Fellow in industrial and applied mathematics at Oxford University, and a lecturer and tutor in pure mathematics. He is the only Oxford mathematician to have won the overall teaching prize across all areas of Mathematical, Physical, Life and Engineering Sciences.
“We are very excited to be partnering with this newly created board of preeminent thought leaders, who will enable us to be at the forefront of new technologies and developments in the fields of machine learning, artificial intelligence, data analysis and ALIS,” says Michael Oliver Weinberg, Chief Investment Officer of MOV37.
The MOV37 team has found that millennials are leading the creation of today’s new technologies and investing methods. These “kids” grew up gaming and hacking; using python for math calculations rather than a calculator. They don’t necessarily view Wall Street as an intermediary, and in fact, some want to disintermediate it. Along with figuring out the AI and data for investing, this generation is fully immersed in figuring out the blockchain.
Jeffrey Tarrant, Chairman and Founder of MOV37, has focused on identifying and incubating cutting edge strategies and talent over his three decade investment career. He was one of the backers of Polychain Capital, one of the first and most successful blockchain/cryptocurrency funds. Jeffrey also helped fund the Digital Currency Initiative out of MIT’s Media Lab that brought Bitcoin into the mainstream by directly supporting the core coders involved.
About MOV37: MOV37, LLC is a research and investment platform for Autonomous Learning Investment Strategies (ALIS). ALIS are the new wave of emerging managers using machine learning, new data and cheap computing power to run innovative investment strategies at lower costs versus traditional quantitative or fundamental managers. MOV37’s principals and advisors use their deep connections and backgrounds in finance, technology and academia to identify the best minds in autonomous learning, data analysis and blockchain, and the firm builds institutional-grade fund structures to help selected ALIS managers access investor capital. More information is at mov37.com.
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