Chief Risk Officer
D.E. Shaw & Co.
[24]
With $16 billion in hedge fund assets and a total $19 billion in investment capital, ranking No. 21 in Institutional Investor’s Hedge Fund 100, D.E. Shaw & Co. continues the quantitative-systems-based investing tradition set by founder David Shaw in 1988. The computer scientist left day-to-day management in 2002 to work on a computational approach to curing cancer. A couple of New York City blocks away from his lab, at D.E. Shaw’s new headquarters, chief risk officer Peter Bernard is focused on improvements in portfolio risk management and modeling. Bernard, 53, a former RiskMetrics Group CFO who joined the firm in 2006, says he is concerned that “the world is beginning to rely on a static library of stress tests — a potentially dangerous way to think about portfolio risk.” He is developing technology for crisis scenarios using a flexible set of variables rather than rigidly defined events. Bernard is also taking a new approach to portfolio optimization, using adverse scenario testing to balance liquidity needs and alpha capture. On the horizon: an initiative that will automate the filtering of data to indicate the difference between temporary volatility and the start of a crisis.
D.E. Shaw & Co.
[24]
With $16 billion in hedge fund assets and a total $19 billion in investment capital, ranking No. 21 in Institutional Investor’s Hedge Fund 100, D.E. Shaw & Co. continues the quantitative-systems-based investing tradition set by founder David Shaw in 1988. The computer scientist left day-to-day management in 2002 to work on a computational approach to curing cancer. A couple of New York City blocks away from his lab, at D.E. Shaw’s new headquarters, chief risk officer Peter Bernard is focused on improvements in portfolio risk management and modeling. Bernard, 53, a former RiskMetrics Group CFO who joined the firm in 2006, says he is concerned that “the world is beginning to rely on a static library of stress tests — a potentially dangerous way to think about portfolio risk.” He is developing technology for crisis scenarios using a flexible set of variables rather than rigidly defined events. Bernard is also taking a new approach to portfolio optimization, using adverse scenario testing to balance liquidity needs and alpha capture. On the horizon: an initiative that will automate the filtering of data to indicate the difference between temporary volatility and the start of a crisis.