In the article a definition of propensity and methods of measurements of propensities (frequency & trigonometric) were presented. Possibility of application of the Bayesian methods in research of propensities was also recommended. 'A posteriori' distributions and estimators of propensity parameter were analytically found. The uniform distribution and beta distribution with specified parameters were assumed as 'a priori' distributions. Empirical example presents an analysis of propensity to risk calculated for chosen investment funds in the year 2003. The author estimated also 'a posteriori' distributions of the parameter utilised in order to measure the propensity to risk of discussed funds.
Financed by the National Centre for Research and Development under grant No. SP/I/1/77065/10 by the strategic scientific research and experimental development program:
SYNAT - “Interdisciplinary System for Interactive Scientific and Scientific-Technical Information”.