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Tribute to Mac McQuown, GCFP Board Member

Oct 25 Papers

Papers on Financial Policy by Sloan Colleagues

MIT Golub Center for Finance and Policy

Public Policy

Andrew Lo on TEDxCambridge – Can Financial Engineering Cure Cancer?

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We are making breakthroughs almost weekly in our understanding of cancer and other deadly diseases, both in how to treat and – in some cases – how to cure them. So why is funding for early stage biomedical research and development declining just when we need it most? One answer is that the financial risk of drug development has increased, and investors don’t like risk. What if we could reduce the risk and increase the reward through financial engineering? By applying tools like portfolio theory, securitization, and derivative securities to construct “megafunds” that invest in many biomedical projects, we can tap into the power of global financial markets to raise billions of dollars. If structured properly, investors can earn attractive returns with tolerable levels of risk, and many more patients can get the drugs they desperately need. Finance doesn’t have to be a zero-sum game; we can do well by doing good if we have sufficient scale.

Please click here to watch the video.

Andrew W. Lo is the Charles E. and Susan T. Harris Professor at the MIT Sloan School of Management, the director of MIT’s Laboratory for Financial Engineering, a principal investigator at MIT’s Computer Science and Artificial Intelligence Lab, and an affiliated faculty member of the MIT Department of Electrical Engineering and Computer Science.

Andrew is the author of five books and over 100 research articles. His early work showed that stock market prices do not follow random walks, as many economic theories imply, but contain predictable components that can be identified and exploited to manage risk and improved expected returns. Since then, his research has spanned many other areas, including: the econometrics of hedge funds; mathematical and statistical models of systemic risk in the financial system; evolutionary models of human behavior; and, most recently, applying financial engineering to fund biomedical innovation more efficiently.