Goldman Sachs’ Foresight Culture

Recently I posed two questions about Foresight in Organisations: What are are the intervention points?  After five or six years, who are the teachable case studies for successful implementation of the foresight function?

I’ve only read the Los Angeles Times and New York Times reviews but Charles D. Ellis’s The Partnership: The Making of Goldman Sachs (Penguin Press HC, New York, 2008) has some answers to both questions.

Ellis suggests Goldman Sachs has three intervention points to cultivate a foresight function: (1) a human resources function staffed by A+ people who recruit “A+++ people” usually in computational finance, financial engineering and statistical arbitrage; (2) an organisational culture tolerant of the “longer-term view” that is linked to the “[operational] details” necessary for strategic execution; and (3) a creative tension between past excellence and new frontiers.  Intriguingly, the “longer-term view” or “forward view” in Foresight parlance, emerges from people in a supportive culture who are faced with challenge at the boundary of the firm and the external competitive environment.

Two other biographies partially validate Ellis’s insights.

Perry Mehrling’s biography Fischer Black and the Revolutionary Idea of Finance (New York: John Wiley & Sons, 2005) and his working paper ‘Understanding Fischer Black‘ describe why Goldman Sachs recruited the economist Black: to tap his academic knowledge to design new financial instruments, and use his influence as coauthor of the Black-Scholes equation in finance to impress clients.

Emanuel Derman describes his Goldman Sachs collaboration with Black in My Life As A Quant: Reflections on Physics and Finance (New York: John Wiley & Sons, 2004) and how the firm benefited from the influx of PhD graduates in the 1980s.  Derman was bored at AT&T Bell Labs which had a reactive culture of research management.  He transitioned into Goldman Sachs’ fixed income division in 1985 and then moved to equities in 1990 where he thrived for the next decade in a culture that appreciated how conceptual expertise can underpin a firm’s competitive advantage in new growth markets.

The contrast was so different that I pointed Derman’s experience out in a private submission to Australia’s National Innovation System Review (aka Cutler Innovation Review) in comments about the institutional design and research management culture of Cooperative Research Centre consortia.  Maybe given the subprime fallout CRCs can also learn something from Goldman Sachs and Berkshire Hathaway‘s Warren Buffett who has now taken a $US5 billion equity stake in Sachs’ foresight culture.

Errors In Quantitative Models & Forecasting

Could the roots of the 2007 subprime crisis in collateralised debt obligations (CDOs) and residential mortgage-backed securities (RMBS) lie in financial analysts who all used similar assumptions and forecasts in their quantitative models?

Barron’s Bill Alpert argues so
, pointing to a shift of investment styles after the 2000 dotcom crash from sector-specific, momentum and growth stocks to value investing.  Investment managers who prefer the value approach then constructed their portfolios with ‘stocks that were cheap relative to their book value.’  In other words, the value investors exploited several factors — the gaps in asset valuation, asymmetries in public and private information sources, price discovery mechanisms and market participants — which contributed to mispriced stocks compared to their true value.

However, the value investing strategy had a blindspot: many of the stocks selected for investment portfolios also had a high exposure to credit and default risk.  The 2007 subprime crisis exposed this blindspot, which adversely affected value investors whose portfolios had stocks with a high degree of positive covariance.

Alpert quotes hedge fund manager Rick Bookstaber who believes that financial engineers have accelerated crises and systemic risks via the complex dynamics of new futures contracts, exotic options and swaps.  These new financial instruments create interlocking markets (capital, commodities, debt, equity, treasuries) which have the second-order effects of larger yield curve spreads and trading volatility.  Alpert and Bookstaber’s views echo Susan Strange‘s warnings a decade ago of ‘casino capitalism’  and ‘mad money’ as unconstrained forces in the international political economy.

Quantitative models also failed to foresee the 2007 subprime crisis due to excessive leverage, difficulties to achieve ‘alpha’ or above-market returns in market volatility, and the separation of risk management from the modelling process and testing.  Other commentators have raised the first two errors, which have led to changes in portfolio construction and market monitoring.  Nassim Nicholas Taleb has built a second career on the third error, with his Black Swan conjecture of high-impact events, randomness and uncertainty (see Taleb’s Long Now Foundation lecture The Future Has Always Been Crazier Than We Thought).

Alpert hints that these three errors may lead to several outcomes: (1) a new ‘arms race’ between investment managers to find the new ‘factors’ in order to construct resilient investment portfolios; (2) the integration of Taleb’s second-order creative thinking and risk management in the construction of financial models, in new companies and markets such as George Friedman’s risk boutique Stratfor; and (3) a new ‘best of breed’ manager who can make investment decisions in a global and macroeconomic environment of correlated and integrated financial markets.