Lessons from the meltdown – the limits of modeling

I am amused to watch the debate over who was right and who was wrong in the meltdown. Of course the naysayers get their day, as if they were right all along. It is kind of like if you were to drive from San Francisco to New York and your travelling companion is convinced that you have to go south. You get on Interstate 80 and drive east. But shortly after you pass through Winnemucca in Nevada the highway swings south to Battle Mountain and for the better part of an hour you have to put up with “see I told you it was south”.

One of these annoying passengers is Nassim Nicholas Taleb who was profiled in an article by Joe Nocera in the New York Times today. Taleb makes that case that all our modeling, most importantly Value at Risk (VaR) is a fraud. He makes the point that he has made a killing on the market down turn because he saw past this fraud and truly understood the market.

Like anyone who bet the markets would collapse, I have no doubt Taleb did well in the downturn. But his strategy is like a broken clock that is right twice a day. He even reinforces this point by pointing out that he has only made money three times in the last 25 years: Black Monday in ’87, the dot com crash in 2000, and in this recent market collapse.

Arguing who is right on a given day misses the point. There are very important lessons to be learned, not the least of which is that all models are limited and therefore in many circumstances they’re wrong.

I love this debate because it highlights the most crucial difference between mathematicians and engineers. I have a degree in Control Systems Engineering. Engineers are practical, we call it applied mathematics. Mathematicians and, their less academic colleague’s, economists, like to deal in concepts and principals. It is obvious to an engineer that any model, like VaR, is limited in its practical application.

First models work in narrow bands. Any financial model is an approximation of a very complex system. It is intuitively obvious that a simplifying model that ignores a good deal of the complexity will only work for a limited range of motion. Mathematically there is good reason for this: the behavior being modeled – price movements of complex derivative financial instruments – is nonlinear. But to create math to describe it you need to create a linear approximation.

It is easy to mathematically calculate the range for which any particular linear approximation is valid. Go beyond this range and the model tells you nothing valid. Think of a spring; you pull on it and it pulls back. But if you pull too hard that spring deforms and no longer pulls back. We call this saturation, and once you pass saturation the equation that once gave you the force of the pull very accurately is now completely worthless.

Second, models assume a continuous market. In engineering systems this is continuous feedback that stays in phase. In the markets this means that when you create a model of financial instruments which don’t all mature at the same time, you can create a hedge by executing the right trades at the right times for various instruments in a continuous market. If you have a discontinuity in pricing everything in the model goes haywire. If the market experiences a sudden jump or fall, or if you can’t execute a trade as it moves through a given price point, your model is invalid.

Third, models are only as good as the data you feed them. Here engineers agree with mathematicians – garbage in, garbage out. In the case of the mortgage backed securities and credit default swaps, historical data was used that was not valid for the underlying subprime mortgages contained in the instruments. And, the models proved invalid – garbage out.

Taleb does make one very interesting assertion that if true could be used to better understand the market. He contends that his “fat tail”, the dramatic market crashes that happen infrequently, out weigh the potential positive results you get cumulatively all the other times in the market. He is articulating a model that might prove true and can be used to modify VaR. That is if VaR is meant to be the potential assets at risk on any day 99% of the time. Taleb is saying the other 1% ruins your return.

So VaR normally looks like:

VaR = (.99 X ‘expected asset loss’)

Taleb’s VaR is:

T:VaR = (.99 X ‘expected asset loss’) + (.01 X ‘exceptional asset loss’)

He is basically saying that T:VaR is much bigger than VaR and thus overwhelms any potential profit in the market.

Maybe he is right. But I think it is worth testing the limits of his model. Historically the market goes up over time as value is created in the economy. I find it intuitively difficult to accept his assertion that crashes will always overwhelm any market gains. I think he is fundamentally misunderstanding the limits of his own model.

Been on this ride before

It is always the same and it is totally different. It is when you feel that you have seen it before that you know you’re getting old. In 2000, we couldn’t get our road show done. In 1987, I watched from the trading room as our book lost $100,000 a minute. Each time it signaled an end of the cycle: the start of a prolonged down market.

I love looking at the 100 year charts of the economy. We cycle through growth and decline – expansion and recession – bull markets and bear markets. When you throw a ball straight up in the air its acceleration is constant but it is most dramatic when it stops going up and starts coming down. In each economic cycle I hear the rules have changed, everything is different this time. And each time economic growth surges and wanes.

Each time everything is different and everything stays the same. From cycle to cycle the key engines of growth change. One cycle it is steal, the next it is white goods, the next it is consumer products, the next aerospace, and the next technology. I was told today to buy GM because it has always been part of the foundation of our economic growth. I think they said the same thing about Bethlehem Steel.

In the last cycle the emphasis went from page views to revenue per user. The time before that, it went from revenue enhancement to cost savings. Each time it is the same: in expansion, value is in growing a business; and in contraction, value is in making the business more efficient.

What is happening economically is breathtaking and unprecedented. It is time to add circuit breakers, reforms, oversight. It is also the same as it has always been. In a down market: cash is king, value is in cost savings, and a good business is still a good business.

Taking my own advice

When should you start a company? This is the quintessential entrepreneurial question. A running debate rages: when do you have a feature rather than a company? When is a company being started because it should be rather than when it merely can be? What does it take to make a company successful? This debate heats up appropriately when exits are plentiful and lots things get funded that shouldn’t.

When potential entrepreneurs ask me when they should start a company? I tell them you should start a company when you can’t do anything else. When you have an idea that has such a grip on you, you can’t sleep at night. When you know it would be far worse not to pursue a venture than to fail miserably trying. If you have any intelligence at all, it is the only way you can do such an irrational thing as start a company.

It is called risk capital for a reason. Over half of all funded ventures fail: by most accounts fewer than 30% succeed in any meaningful way. The exercise of venture investment only becomes rational when 20% of the ventures in aggregate can provide ridiculous returns (better and 10 to 1). With diversity and persistence this looks somewhat rational and perhaps even highly lucrative when managed across multiple funds with portfolios of companies.

But take a specific venture, there is no rational for it being a good idea. In my experience companies succeed when they are meant to succeed; when all the stars align. It is like the old advertising adage: “we know half our advertising is a useless waste of money; we just don’t know which half.”

Don’t get me wrong, you need to do all the right things to succeed: identify a market; develop a compelling value proposition; get the right people; manage your cash well; keep maniacally focused, etc. etc. But all that’s not enough. You also have to have uncanny instinct (or maybe just dumb luck). When a prospective venture posses you, dominates your thoughts, doesn’t let you sleep, and jolts you from aha moment to aha moment yielding seeming clairvoyance, then you know it is time to start a company. New Stealth Co has that grip on me. I am going to build a wildly successful company and it will change the world.

Brush aside the ashes and kneel before Zod no longer

The tectonic plates of the Web are moving again. Some people say the Web 2.0 bubble is going to burst reminiscent of the 2000 Internet bubble. Many of the dynamics are the same: the money being thrown at sites that are little more than ideas will dry up; early exits at silly valuations will diminish; trendy sites that are cool but deliver little value will fade away. User aggregation as a business model will again fall from grace and Web 2.0 as a category will disappear.

What will emerge is a new generation of sites and applications that incorporate the characteristics of Web 2.0 – social networking, data tagging, rich media content, mashable functional components, and immersive user interfaces. The sites that survive and emerge as the new guard of Web properties will have a monetization model that drives real and growing earnings.

Like all generational transitions some past participants will die out, and some past leaders will fade to the background. I predict that Yahoo and Microsoft will have little presence in the next round of Web apps. Yahoo was the early leader in Web applications and to this day is far and away the market share leader. You could make the argument (as Tim O’Rielly does ) that Microsoft is purchasing Yahoo to consolidate a dominant position in Web apps. Statistically this is true but a closer look at Microsoft yields a different story.

Microsoft has been working through a 6 month re-org that has consolidated the Online Service Group and the Windows Business Group under Bill Veghte. This puts the Web assets into the group responsible for SMB, and SME software products. This group lives and dies by software license sales to business customers and will find it difficult to advance an ad or subscription recurring revenue model. Worse it is consolidated under Senior Software Architect Ray Ozzie who has always had an enterprise software view of the world.

Yahoo itself took its eye off Web Apps some years ago when their lead architect Zod Nazem shifted his focus to project Panama, an advertising targeting engine. For the last several years search and advertising has consumed Yahoos focus and resources. The death nil for Yahoo apps came when Zod left last June. Yahoo still has market share but is demonstrating no leadership.

Microsoft is aligning around two pillars: 1) software and 2) search advertising. When acquired, Yahoo will be folded into pillar (2) - the search advertising group - headed by Senior Vice Presient and former aQuantive CEO Brian McAndrews. Microsoft and Google have both done the calculus and determined that their growth lies in capturing the increasing flood of online advertising money.

They will continue to be players in Web apps but it will be far from their focus. This leaves the field wide open for the next generation of SaaS and Web applications. Once again the applications of the new Web will emerge out of the ashes of too many failed companies (and millions of Venture dollars) that chased the latest trend – this time Web 2.0. And hopefully, this time the Phoenix will sport labels other than Microsoft, Yahoo and Google.