Founded on an observation from forty years inside major investment banks: most investment mistakes start with not fully understanding the risk you already own.
Most portfolios carry risk their owners cannot see. Correlated holdings, hidden factor crowding, and concentration that only surfaces during a drawdown.
Without analytics that show you what is actually driving your portfolio, weighting decisions are guesswork. And guesswork compounds into underperformance.
Our analytics decompose any portfolio into factor exposures and risk attribution, so you see what you actually own before making any changes. Then the Arch Cortex Engine rebuilds the portfolio around the risk profile you want, optimizing for your specific goals while minimizing uncompensated exposure.
How the engine worksCapital markets veterans and applied intelligence engineers. The engine came out of that work.

Yang spent over a decade in macro solutions, structuring and sales roles at Morgan Stanley, Citi, Deutsche Bank, and Crédit Agricole CIB. Yang has worked with banks, insurers, and asset managers globally on solutions across asset classes for asset liability, yield enhancement, capital, and tactical opportunities. These structured solutions combined advanced machine learning and derivative replication with practitioner knowledge of financial markets to achieve client outcomes.

Jacob spent over two decades at Citi and its predecessor Salomon Brothers in trading, structuring, and quantitative research and analytics. Jacob has deep expertise working with institutional and private bank clients in multi-asset derivative solutions, cash products, and structured notes, with extensive machine learning, neural network, financial engineering, and analytics knowledge from roles in research, modeling, and quantitative analysis.
PhD Mathematics, University of Minnesota · former Assistant Professor of Mathematics, Penn State
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