23rd July 2012: Barton Biggs

Money manager Barton Biggs died last week. Biggs worked at EF Hutton, Morgan Stanley, and helped to found several hedge funds. He personified the old Wall Street tradition of research analysts and institutional money managers who were ‘big picture’ thinkers — the forerunners of today’s scenario planners and strategic foresight analysts. Biggs’ memoir Hedgehogging was an enjoyable, insightful entry into the world of hedge funds. I learned from Biggs how hedge fund managers read Barron’s, The Economist, and other publications.

Worth Reading

The moment we found a Bosavi woolly rat (with thanks to Leon Wild).

The New Yorker‘s Sasha Frere-Jones on Trent Reznor and Nine Inch Nails’ final tour.

My 2008 presentation on Reznor and Radiohead’s strategies during ‘label shopping’ negotiations.

What Reznor possibly wished he had produced and why it leaked to BitTorrent.

Sears Holdings chairman Edward Lampert responds to Barron’s.

TNR‘s Peter Boone and Simon Johnson on the next financial crisis.

Johnny Rotten revives Public Image Ltd.

Richard Metzger’s new site Dangerous Minds.

We Are All Traders Now?

Mark Pesce pointed me to Bernard Lunn’s article which contends netizens now live in a real-time Web. Lunn suggests that journalists and traders are two models for information filtering in this environment, and that potential applications include real-time markets for digital goods, supply chain management and location-based service delivery.

Lunn’s analogy to journalists and traders has interested me for over a decade. In the mid-1990s I read the Australian theorist McKenzie Wark muse about CNN and how coverage of real-time events can reflexively affect the journalists who cover them. As the one-time editor for an Internet news site I wrote an undergraduate essay to reflect on its editorial process for decisions. I then looked at the case studies on analytic misperception during crisis diplomacy, intelligence, and policymaker decisions under uncertainty. For the past year, I’ve read and re-read work in behavioural finance, information markets and the sociology of traders: how the financial media outlets create noise which serious traders do not pay attention to (here and here), what traders actually do (here, here, and perhaps here on the novice-to-journeyman transition), and the information strategies of hedge fund mavens such as George Soros, Victor Niederhoffer, David Einhorn, Paul Tudor Jones II and Barton Biggs. This body of research is not so much about financial trading systems, as it is about the individual routines and strategies which journalists and traders have developed to cope with a real-time world. (Of course, technology can trump judgment, such as Wall Street’s current debate about high-frequency trade systems which leaves many traders’ expertise and strategies redundant.)

Lunn raises an interesting analogy: How are journalists and financial traders the potential models for living in a real-time world? He raises some useful knowledge gaps: “. . . we also need to master the ability to deal with a lot of real-time
information in a mode of relaxed concentration. In other words, we need
to study how great traders work.” The sources cited above indicate how some ‘great traders work’, at least in terms of what they explicitly espouse as their routines. To this body of work, we can add research on human factors and decision environments such as critical infrastructure, disaster and emergency management, and high-stress jobs such as air traffic control.

Making the wrong decisions in a crisis or real-time environment can cost lives.

It would be helpful if Lunn and others who use this analogy are informed about what good journalists and financial traders actually do. As it stands Lunn mixes his analogy with inferences and marketing copy that really do not convey the expertise he is trying to model. For instance, the traders above do not generally rely on Bloomberg or Reuters, which as information sources are more relevant to event-based arbitrage or technical analysts. (They might subscribe to Barron’s or the Wall Street Journal, as although the information in these outlets is public knowledge, there is still an attention-decision premia compared to other outlets.) Some traders don’t ‘turn off’ when they leave the trading room (now actually an electronic communication network), which leaves their spouses and families to question why anyone would want to live in a 24-7 real-time world. Investigative journalists do not generally write their scoops on Twitter. ‘Traditional’ journalists invest significant human capital in sources and confidential relationships which also do not show up on Facebook or Twitter. These are ‘tacit’ knowledge and routines which a Web 2.0 platform or another technology solution will not be the silver bullet for, anytime soon.

You might feel that I’m missing Lunn’s point, and that’s fine. In a way, I’m using his article to raise some more general concerns about sell-side analysts who have a  ‘long’ position on Web 2.0. But if you want to truly understand and model expertise such as that of journalists and financial traders, then a few strategies may prove helpful. Step out of the headspace of advocacy and predetermined solutions — particularly if your analogy relies on a knowledge domain or field of expertise which is not your own. Be more like an anthropologist than a Web 2.0 evangelist or consultant: Understand (verstehen) and have empathy for the people and their expertise on its own terms, not what you may want to portray it as. Otherwise, you may miss the routines and practices which you are trying to model. And, rather than commentary informed by experiential insight, you may end up promoting some myths and hype cycles of your own.

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.