Optimisation in Financial Engineering
University of Geneva - Department of Economics; Swiss Finance Institute
affiliation not provided to SSRN
February 9, 2010
Journal of Financial Transformation, Vol. 28, pp. 117-122, 2010
We discuss the precision with which financial models are handled, in particular optimisation models. We argue that precision is only required to a level that is justified by the overall accuracy of the model, and that this required precision should be specifically analysed, so to better appreciate the usefulness and limitations of a model. In financial optimisation, such analyses are often neglected; operators and researchers rather show an a priori preference for numerically-precise methods. We argue that given the (low) empirical accuracy of many financial models, such exact solutions are not needed; ‘good’ solutions suffice. Our discussion may appear trivial: everyone knows that financial markets are noisy, and that models are not perfect. Yet the question of the appropriate precision of models with regard to their empirical application is rarely discussed explicitly; specifically, it is rarely discussed in university courses on financial economics and financial engineering. Some may argue that the models’ errors are understood implicitly, or that in any case more precision does no harm. Yet there are costs. We seem to have a built-in incapacity to intuitively appreciate randomness and chance; all too easily then, precision is confused with actual accuracy, with potentially painful consequences.
Number of Pages in PDF File: 10
Keywords: Financial Optimisation, Financial Modelling, Heuristics, Model Evaluation
JEL Classification: C60, G11Accepted Paper Series
Date posted: February 3, 2010 ; Last revised: October 19, 2010
© 2014 Social Science Electronic Publishing, Inc. All Rights Reserved.
This page was processed by apollo6 in 0.422 seconds