The financial industry relies on trade secrecy to protect its business processes and methods, which can obscure critical financial risk exposures from regulators and the public. Using results from cryptography, we develop computationally tractable protocols for sharing and aggregating such risk exposures that protect the privacy of all parties involved, without the need for trusted third parties. Financial institutions can share aggregate statistics such as Herfindahl indexes, variances, and correlations without revealing proprietary data. Potential applications include: privacy-preserving real-time indexes of bank capital and leverage ratios; monitoring delegated portfolio investments; financial audits; and public indexes of proprietary trading strategies.

Fear and Greed in Financial Markets: A Clinical Study of Day-Traders by Andrew W. Lo, Dmitry V. Repin and Brett N. Steenbarger. Published in volume 95, issue 2, pages 352-359 of American Economic Review, May 2005

Traditional financing sources such as private and public equity may not be ideal for investment projects with low probabilities of success, long time horizons, and large capital requirements. Nevertheless, such projects, if not too highly correlated, may yield attractive risk-adjusted returns when combined into a single portfolio. Such “megafund” portfolios may be too large to finance through private or public equity alone. But with sufficient diversification and risk analytics, debt financing via securitization may be feasible. Credit enhancements (i.e., derivatives and government guarantees) can also improve megafund economics. We present an analytical framework and illustrative empirical examples involving cancer research.