Jonathan Levi is an entrepreneur and scientist who combines financial markets/industry experience with a very hands-on, practical technical background.
Focused on computational finance for over a decade, Jonathan combines a broad set of skills and experience in the financial services sector as a quantitative strategist (strat/quant/dev), working at a few of the world’s strongest trading desks. In addition to working on Credit Ratings at Standard and Poor’s in London, he was the head of Credit Analytics at Barclays Capital during the 2008 credit crisis, was a core-strategist on the desk at Goldman Sachs during the Flash Crash (of May 2010) and spent a few years of working at the Fund Derivatives desk (derivatives on hedge/mutual funds, replicated portfolios, ETFs).
His academic background in Computer Science, Applied (Computational) Mathematics, and Probability & Statistics is combined with applied cryptographic work with the Israeli Defense Forces and with Cisco Systems, where he worked on FIPS 140-2 certification of cryptographic C/C++ code. While working on his own initiative in this space, he talks and consults regularly with crypto-finance oriented start-ups.
Since 2013, Jonathan has given a series of talks about decentralization, hedging and liquidity. Levi frequently highlight issues from his popular recent presentations, “Small Errors in Big Data: White Noise or White Lies”, “Practical Machine Learning: Theory, Practice, and the Challenges in Making These Two Meet”, and “Theoretical Financial Mathematics Meets Real Data.” His presentations focus on the related challenges that should be considered and addressed in the context of financial quantitative analysis, operating in illiquid markets and decentralized trading environments. While no single model can capture 100% of the complex attributes of live securities markets, analyzing financial market data empirically is key for decision making and risk management. Understanding the intrinsic characteristics of financial markets is even more important in automated trading well beyond the needs of mandatory regulatory requirements.