Scalable Functions Used for Empirical Forecasting

Peter Stallinga *

Faculty of Science and Technology, Center for Electronics Optoelectronics and Telecommunications, University of the Algarve, Portugal

*Author to whom correspondence should be addressed.


Empirical forecasting is the science of using past data to predict the future, without physical modeling. For these, probability functions are used, normally bell-shaped Gaussian or Gaussian- like. Taleb in his book the Black Swan introduces for this purpose the concept of scalable functions. Here it is shown that the only scalable functions are power-law functions and they can be treated as one and the same. Moreover, the analytical problems of these functions are discussed. Scalable functions are inadequate for empirical forecasting.

Keywords: Empirical forecasting functions, extreme events, outliers, scalability

How to Cite

Stallinga, P. (2016). Scalable Functions Used for Empirical Forecasting. Journal of Advances in Mathematics and Computer Science, 18(2), 1–6.


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