Besides responding to emails on my BlackBerry, I’ve been spending a few hours each night before I go to bed reading/watching/listening to media outside of my interests in technology. (Usually, this habit lasts about an hour or two before I completely pass out and have to shut down the small screen of the BlackBerry Curve). However, this past weekend, I couldn’t put it down. I stumbled across an epic, eye-opening perspective into the quantifiable world of risk management – or as New York Times writer, Joe Nocera, termed it in the Sunday Magazine – risk (mis)managament on Wall Street. Nocera asks a simple, but complicated question where his answer is woven into an 8,000 word post-mortem analysis of something entirely artificial: the notion of risk.
“The great housing-fueled market bubble couldn’t burst,” Nocera writes, “could it?” Well, could it?
It would be impractical to point a finger at something or someone as the root cause of the crisis. (Truth be told, there’s more than one answer in the complex deterioration of the economy. Merely listing possible reasons or linking to a detailed visualization on this blog wouldn’t do anyone justice). Rather, I found the insight that investment banks and hedge funds once developed to measure risk through a calculation called Value at Risk (VaR), applicable to the chang(ed) media landscape in 2009. Let’s look into it what happened on Wall Street through the lens of VaR and apply it to the environment inside the bright-lit computer screen or mobile phone display your reading right now.
Issue 1: The belief that the best decisions are based on numbers.
In the early 1990s, a group of mathematicians (”quants” as they’re called in financial circles) at JPMorgan went to work on a collection of financial models that dealt with measuring the boundaries of risk through financial portfolios in short duration. According to Nocera:
VaR isn’t one model but rather a group of related models that share a mathematical framework. In its most common form, it measures the boundaries of risk in a portfolio over short durations, assuming a “normal” market. For instance, if you have $50 million of weekly VaR, that means that over the course of the next week, there is a 99 percent chance that your portfolio won’t lose more than $50 million. That portfolio could consist of equities, bonds, derivatives or all of the above; one reason VaR became so popular is that it is the only commonly used risk measure that can be applied to just about any asset class. And it takes into account a head-spinning variety of variables, including diversification, leverage and volatility, that make up the kind of market risk that traders and firms face every day.
Another reason VaR is so appealing is that it can measure both individual risks — the amount of risk contained in a single trader’s portfolio, for instance — and firmwide risk, which it does by combining the VaRs of a given firm’s trading desks and coming up with a net number. Top executives usually know their firm’s daily VaR within minutes of the market’s close.
With the exponential rise in derivative use by the late 1990s, the Securities and Exchange Commission determined that “firms had to include a quantitative disclosure of market risks in their financial statements for the convenience of investors, and VaR became the main tool for doing so.” As Nocera explains, banks and financial institutions were using VaR to determine how much money could come in and out of the exchanges on a daily basis. Nocera continues:
Given the calamity that has since occurred, there has been a great deal of talk, even in quant circles, that this widespread institutional reliance on VaR was a terrible mistake. At the very least, the risks that VaR measured did not include the biggest risk of all: the possibility of a financial meltdown. “Risk modeling didn’t help as much as it should have,” says Aaron Brown, a former risk manager at Morgan Stanley who now works at AQR, a big quant-oriented hedge fund. A risk consultant named Marc Groz says, “VaR is a very limited tool.” David Einhorn, who founded Greenlight Capital, a prominent hedge fund, wrote not long ago that VaR was “relatively useless as a risk-management tool and potentially catastrophic when its use creates a false sense of security among senior managers and watchdogs. This is like an air bag that works all the time, except when you have a car accident.” Nassim Nicholas Taleb, the best-selling author of “The Black Swan,” has crusaded against VaR for more than a decade. He calls it, flatly, “a fraud.”
Deregulation. Greed. Too much leverage. All of these were possible explanations that caused the financial crisis. But what about the possible reality of “a false sense of security” guiding the judgement of the most senior managers at the financial institutions who had last and ultimate say? If we take the promise of VaR as a model of prediciting holes in something entirely artificial, such as risk, and then use this model to guide our definitive actions, what are we really placing heavier reasoning weight into? I’d argue the individual or the most senior manager. The belief that the best decisions are based on numbers is not complete; the best decisions are not only based on numbers but also based on contextual measurement.
So, Dave, what does this have to do with online marketing and communications, you ask? The kernel of a business does not entirely rest on a profit and loss statement, rather quite the contrary; today’s leading businesses utilize their most valuable assets – their people, their customers and their brand ambassadors. They use the power of community, and not computer systems like financial institutions did, to generate better decisions. As I mentioned in a post on my personal blog in early December,
We can’t succeed in a down economy by banking on either advertising over PR or PR over advertising. It’s a marriage of both, as IBM’s Beyond Advertising study found. But something I didn’t see and truly believe is the power of grassroots organized ambassadorship. The giants of the past business game always operated on a two-dimensional, symmetrical scale around tall and flat organizational design schemes; today, the agile businesses are running in a three dimensional and asymmetrical scale – in many ways, a very controlled core set of values that spreads through their potentially interested or passionate consumers to deliver the desired message.
Issue 2: For Nassim Taleb, VaR was a bad, bad thing.
According to Nassim Taleb, author of “The Black Swan,” risk modeling is not applicable in those instances where a “black swan” appears – something completely improbable but occurs before our eyes, as in the 2008 Financial Crisis. VaR is suitable for financial projections based on “normal” (relatively calculated) variables. As Nocera writes:
Taleb says that Wall Street risk models, no matter how mathematically sophisticated, are bogus; indeed, he is the leader of the camp that believes that risk models have done far more harm than good. And the essential reason for this is that the greatest risks are never the ones you can see and measure, but the ones you can’t see and therefore can never measure. The ones that seem so far outside the boundary of normal probability that you can’t imagine they could happen in your lifetime — even though, of course, they do happen, more often than you care to realize. Devastating hurricanes happen. Earthquakes happen. And once in a great while, huge financial catastrophes happen. Catastrophes that risk models somehow always manage to miss.
The financial crisis, Taleb argues, was a system that was bound to blow up due to the way VaR was created: inside a financial institution vacuum. Normal and relatively calculated instances do not, and will never apply to a black swan. However, what happened next in the history of risk modeling is something akin to a black swan of itself.
The growth of VaR throughout Wall Street as the de facto and most popular risk modelling approach occurred because JPMorgan essentially open-sourced proprietary knowledge, an idea that has gained significant traction in the software and web applications industry. Although Taleb characterized the financial industry as a set of systems, with clearly defined checks and balances as orchestrated by the top managers, JPMorgan did the unthinkable by breaking all of these rules and providing VaR methodologies free-of-charge to the financial community in 1993.
I couldn’t help but start to wonder: What really happened to VaR and it’s role in the 2008 Financial Crisis? Why didn’t crowd-sourcing and community action shape the future for VaR so it could have (or could have come as close as possible) to a black swan just like it has in the desktop software space?
I know I don’t have an answer.
Media, as has been written about before here, has evolved from a one-way mass medium to that of an interactive and multi-directional communications stream. 2008 was a year of great success for micro-communication such as Twitter as well as highly-personalized news such as Facebook and Socialmedian. But what about 2009? Can we learn from VaR, black swans and using numbers to make better decisions? I sure hope so.
Can we use our collective and contextual wisdom to predict as well as apply economic success in 2009? Without a doubt, but we need to start now.
