After the hacker break-in at CRU, I speculated on what the possibilities might be should the consensus change. Today, as the world looks forward to the Copenhagen summit, the market consensus seems to be starting to shift as a result of the CRU incident. Avner Mandelman recently voiced his skepticism about climate change thesis and the issue of researchers either fudging data or denying others access to data:
Say that a pharmaceutical company's researchers were caught fudging their tests to make their drug look effective; then, when found out, conveniently lost the non-fudged data. If a doctor prescribed for your child the fraudsters' drug, would you let her take it? If you said yes, would we not be justified in saying you are acting irrationally?If you missed the controvery, the issue isn't about just how a researcher might have used some "trick" to fudge data so that it would agree his model, but the distressing lack of discipline in the scientific method. Judith Curry, an American climate scientist and no skeptic of the climate change thesis, was appalled [emphasis mine]:
What has been noticeably absent so far in the ClimateGate discussion is a public reaffirmation by climate researchers of our basic research values: the rigors of the scientific method (including reproducibility), research integrity and ethics, open minds, and critical thinking. Under no circumstances should we sacrifice any of these values; the CRU emails, however, appear to violate them...Meanwhile, the financial market consensus appears to be starting to shift. Donald Coxe, former Global Portfolio Strategist at BMO Capital Markets, also indicated his doubts about the global warming thesis. In reporting on Coxe, a reporter commented:
If climate science is to uphold core research values and be credible to public, we need to respond to any critique of data or methodology that emerges from analysis by other scientists. Ignoring skeptics coming from outside the field is inappropriate; Einstein did not start his research career at Princeton, but rather at a post office. I’m not implying that climate researchers need to keep defending against the same arguments over and over again. Scientists claim that they would never get any research done if they had to continuously respond to skeptics. The counter to that argument is to make all of your data, metadata, and code openly available. Doing this will minimize the time spent responding to skeptics; try it! If anyone identifies an actual error in your data or methodology, acknowledge it and fix the problem.
My purpose here is not to weigh in on Mr. Coxe's theory of climate change (which mostly has to do with sunspots) or those of the scientists who disagree with him. But he is worth listening to in this respect: The big money is always, always made by those willing to bet against a deeply held consensus. So if, five or 10 years from now, new evidence has thrown theories of global warming into doubt, enormous profits will be made by those putting their cash on that outcome now.
Quantitative finance = science
While I have my own personal opinions about climate change, I have learned to be flexible and open-minded about my beliefs as an investment and quantitative analyst.
Quantitative finance is much like science. We observe, we form our hypothesis, we test our hypothesis and we try to apply them. If the evidence changes, our models have to change too.
I have observed situations in the past where people have been dogmatic about models and investment processes despite evidence to the contrary. In the short term, these people may be successful in the short term. In the long term, the market will punish them for their views if they are wrong. Some of these models were built by analysts with incredible stature. Not only do some of these people have Ph.D.s from top universities, published in leading peer-reviewed journals, a few are even Nobel laureates.
In fact, why don’t we start a hedge fund with some Nobel laureates, we’ll call it Long Term Capital Management….
Here’s another idea. Let’s take some of these models of mortgages and apply them to how we package mortgage backed securities. We’ll slice up the mortgages into different tranches, from senior to junior and…
Oh, I remember how that turned out.
Good quantitative modelers observe, form hypotheses, test and apply them. So do good scientists.
We all need to thimk and watch out for errors in our data set and assumptions.