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Group Description
The Quantitative Investing Group brings together professionals seeking to incorporate cutting edge quantitative investment techniques and alternative data sets in their investing and risk processes. Members include (but are not limited to) discretionary and systematic portfolio managers, risk managers, traders and fundamental analysts, data strategists, quantitative researchers, and others. The topic covered range from quantitative alpha generation, big data as well as alternative datasets, quantamental signals i.e. the intersection of fundamental analysis and quantitative decision making, mathematical and statistical aspects of modern quantitative analysis, use of programming languages or quant tools, Natural Language Processing, machine learning for investing and risk management, theory and implementation of AI in finance and more.
Guest Speaker
Marshall Alphonso, Senior Global Lead Engineer, MathWorks
Marshall Alphonso specializes in quantitative finance and is currently the global lead engineer for the top five banks. He has over 10+ years’ experience training clients at over 250 companies, including top hedge funds, banks and other financial institutions around the world. As advisor to the CRO of McKinsey & Co. Investment Office, Marshall was responsible for the design and implementation of the fund liquidity framework, stress testing framework and a multitude of quantitative risk and investment tools, enabling evaluation of exposures for risk and attribution. Prior experience included use of artificial intelligence and advanced statistical signal processing in communication and geostationary satellite systems. He holds a B.S. in electrical engineering and mathematics from Purdue University and an M.S. in electrical engineering from George Mason University. Additional significant experiences include work with the European Space Agency to present at the UN on high inclination comets, NIH-sponsored research in proteomics at Harvard University and KISR-sponsored data science research at MIT.