A second, more likely explanation, is that they did not consider it their job to warn the public. If that is the cause of their failure, we believe that it involves a misunderstanding of the role of the economist, and involves an ethical breakdown. In our view, economists, as with all scientists, have an ethical responsibility to communicate the limitations of their models and the potential misuses of their research. Currently, there is no ethical code for professional economic scientists. There should be one.
I certainly agree with that, but for such warnings about the models to be heard in the capitalist world we are living in, they must be broadcasted quite loudly, and even enforced by some sort of regulations. Some people just don't want to hear certain truths, especially when these ones are liable to jeopardize their multi-millions bonuses. Let's keep in mind that most financial researchers are funded by these people (directly or indirectly), and that they therefore are cordially invited to present results that are pleasing to their benevolence.
If speculators pay for the financial researches done in academia, is it such a big surprise to find that these researches tend to show the harmlessness of speculation?
While the overall article is interesting, I'd like to comment a bit on the following:
Of course, considerable progress has been made by moving to more refined models with, e.g., ‘fat-tailed’ Levy processes as their driving factors. However, while such models better capture the intrinsic volatility of markets, their improved performance, taken at face value, might again contribute to enhancing the control illusion of the naïve user.
The user who thinks that Levy processes may somehow enhance his control, is not naïve, he is ignorant of what a Levy process is all about. Levy process is exactly telling us that we have less control about what's going on, and particularly, it invalidates the dynamic hedging strategy inspired by Black, Merton and Scholes work. Furthermore, this invalidation is not a matter of opinion, it is a matter of mathematical correctness, as Haug and Taleb have shown in the previously cited article (Haug and Taleb, November 2007), a Levy distribution entails such a weakening of the Central Limit Theorem that the hypothesis(finite variance) making possible dynamic hedging becomes false.
And last but not least, it would be unfair not to mention the existence of the Truncated Levy Process(TLF) that seemingly resolved the "inconvenience" of the Levy Process with regard to the infinite variance, and therefore bring it back to the scope of validity of the Central Limit Theorem, making Dynamic Hedging again possible. It is indeed what Andrew Matacz in this article aims at achieving.
While I don't question the value of the mathematical parts in the article, I wonder about their applicability from an investment point of view, and there's indeed a profound ethical problem at play here, and it is rooted in the belief of the possibility of a riskless strategy (which is at the core of Dynamic Hedging). There can't be such a strategy, because if there was one, its implementation would invalidate it (the statistical model of a market is always historical, the market can perfectly shift from one model to another, it is not causally determined to stay within the limits of one precise model).
A riskless strategy is potentially the equivalent of the perpetual motion machine in mechanics, to use it may well lead to its destruction (and also create a speculative bubble in the process).
On the other hand, the study of TLF is interesting and should be pursued, but it is necessary to separate this study from the sole motivation of creating an investing edge in the market (again the problem of deontology and financing creeps back). In this sense, the approach of Cont, Potters and Bouchaud in this article from May 1997, displaying as its primary concern the fitting with existing data, appears more promising.
: The Financial Crisis and the Systemic Failure of Academic Economics
: Financial Modeling and Option Theory with the Truncated Levy Process
: Scaling in stockmarket data: Stable laws and beyond