Thursday, March 18, 2010

"Model-less" Modeling?

One of the themes that seems to be emerging in some circles of finance is the notion of "model-free" analysis and reasoning. Here is a comment that I recently posted in response to such thinking in a popular public forum:

To all, the case for modeling probabilities and inferential statistics is a bit harder to dismiss than some are presupposing in this forum. Now, I do concede that researchers have many challenges to deal with when validating data and models. Moreover, the theoretical relationships between dependent and independent variables (including proxy measures) are often misspecified and/or interpreted by researchers to the point where some research is outright misleading (especially in the social sciences). Nevertheless, inferential modeling of complex pheonomena cannot be simply dismissed as incredible via declaratory argument and assertions. There is a tremendous burden of proof that is assumed when one takes the path of falsifying probability theory and inferential statistics as a discipline. Thus, I fear that the notion of "model-less" reasoning is problematic as an approach to understanding what is happening in this place called "reality" around us. For the record, I am not as pessimistic about the validity and reliability of such methods as some may be here and in society. My advice to all is "be prepared" to defend your evidence if your goal is to falsify probability theory as a tool for understanding and evaluating the risks (and dangers) that seem to prevail in this universe. Thanks for the opportunity to comment...

1 comment:

jm said...

Model-less or model-free techniques are, in my view, going to give science the next big boost. Our conventional math has been tremendously successful in solving many problems, getting man to the moon, true, but it cannot discribe a leaf, a cell's nucleus, not to mention life. In effect, our math is not "natural", it is a bit too "artificial". Nature doesn't work by using differential equations or integrals or algebra. Nature dones't "know" the concepts of function or matrix and yet it DOES work. If we want to get to the next level we must acknowledge this fact and try to develop tools and methods that MIMICK Nature not methods that just passively discribe her. Our company develops such methods and is using them to develop new (and useful!) means of measuring complexity.

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