Harin, Alexander (2020): Macroscopic analogs of quantum-mechanical phenomena and auto-transformations of functions.
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Abstract
The two main goals of the present article are: 1) To prove an existence theorem for forbidden zones for the expectations of real-valued random variables. 2) To define transformations (named here as auto-transformations) of the probability density functions (PDFs) of random variables into similar PDFs having smaller sizes of their domains and to outline their basic features. Such transformations can be used also for functions beyond the scope of the probability theory. The goals are caused by the well-known problems of behavioral sciences, e.g., by the underweighting of high and the overweighting of low probabilities, risk aversion, the Allais paradox, etc.
Item Type: | MPRA Paper |
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Original Title: | Macroscopic analogs of quantum-mechanical phenomena and auto-transformations of functions |
Language: | English |
Keywords: | Expectations; Boundaries; Forbidden zones; Domains; Utility; |
Subjects: | C - Mathematical and Quantitative Methods > C0 - General > C02 - Mathematical Methods C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General > C18 - Methodological Issues: General D - Microeconomics > D8 - Information, Knowledge, and Uncertainty D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D81 - Criteria for Decision-Making under Risk and Uncertainty D - Microeconomics > D8 - Information, Knowledge, and Uncertainty > D84 - Expectations ; Speculations |
Item ID: | 104188 |
Depositing User: | Alexander Harin |
Date Deposited: | 16 Nov 2020 16:26 |
Last Modified: | 16 Nov 2020 16:26 |
References: | [1] Arnold, L., H. Crauel, and V. Wihstutz (1983). Stabilization of linear systems by noise, SIAM J. Control Optim. 21(1), 451–461. [2] Cacoullos, T. (1982). On Upper and Lower Bounds for the Variance of a Function of a Random Variable. Ann. Probab. 10(3), 799–809. [3] Chernoff, H. (1981). The identification of an element of a large population in the presence of noise. Ann. Probab. 9(1), 533–536. [4] Prekopa, A. (1990). The discrete moment problem and linear programming, Discrete Appl. Math. 27(3), 235{254. [5] Thaler, R. (2016). Behavioral Economics: Past, Present, and Future. Am. Econ. Rev. 106(7), 1577–1600. [6] Schoemaker, P., and J. Hershey (1992). Utility measurement: Signal, noise, and bias. Organ. Behav. Hum. Dec. 52(1), 397–424. [7] Aczél, J., and D. R. Luce (2007). A behavioral condition for Prelec’s weighting function on the positive line without assuming W(1)=1. J. Math. Psychol. 51, 126–129. [8] Bhatia, R. and C. Davis (2000). A better bound on the variance, Am. Math. Mon. 107, 353–357. [9] Harin, A. (2018). Forbidden zones for the expectation. New mathematical results for behavioral and social sciences. MPRA Paper, No 86650. [10] Harin, A. (2012) Data dispersion in economics (II) – Inevitability and consequences of restrictions. Rev. Econ. Fin. 2(4), 24-36. [11] Harin, A. (2020). Behavioral sciences and auto-transformations of functions, MPRA No 99286. |
URI: | https://mpra.ub.uni-muenchen.de/id/eprint/104188 |