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Probability Weighting Functions Implied in Options Prices
SSRN Electronic Journal, 2012The empirical pricing kernels estimated from index options are non-monotone (Rosenberg and Engle, 2002; Bakshi, Madan, and Panayotov, 2010) and the corresponding risk aversion functions can be negative (Ait-Sahalia and Lo, 2000; and Jackwerth, 2000).
Valery Polkovnichenko, Feng Zhao
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The Probability Weighting Function
Econometrica, 1998Summary: A probability weighting function \(w(p)\) is a prominent feature of several non-expected utility theories, including prospect theory and rank-dependent models. Empirical estimates indicate that \(w(p)\) is regressive (first \(w(p)>p\), then \(w(p)
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How Categorization Shapes the Probability Weighting Function
SSRN Electronic Journal, 2021The tendency to overweight low probability events and underweight high probability events stems from the categorical distinction between ``not happening,'' ``a chance,'' and ``happening.'' We demonstrate that there exist multiple intermediary categories within the probability space that produce additional inflection points. Across preregistered studies,
Dan Schley +3 more
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On the probability density function of the LMS adaptive filter weights
IEEE Transactions on Acoustics, Speech, and Signal Processing, 1989The joint probability density function of the weight vector in least-mean-square (LMS) adaptation is studied for Gaussian data models. An exact expression is derived for the characteristic function of the weight vector at time n+1, conditioned on the weight vector at time n.
Neil J. Bershad, Lian Zuo Qu
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Separating curvature and elevation: A parametric probability weighting function
Journal of Risk and Uncertainty, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
L'Haridon, Olivier +2 more
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Probability Weighting Functions* [PDF]
, 2010 In this paper we begin by stressing the empirical importance of non-linear weighting of probabilities, which expected utility theory (EU) is unable to accommodate. We then go on to outline three stylized facts on non-linear weighting that any alternative theory of risk must address.
Dhami, S., al-Nowaihi, Ali
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WEIGHTED DISTRIBUTIONS AND ESTIMATION OF RESOURCE SELECTION PROBABILITY FUNCTIONS
Ecology, 2006Understanding how organisms selectively use resources is essential for designing wildlife management strategies. The probability that an individual uses a given resource, as characterized by environmental factors, can be quantified in terms of the resource selection probability function (RSPF).
Subhash R, Lele, Jonah L, Keim
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Unusual Estimates of Probability Weighting Functions
2023Abstract The author presents new estimates of the probability weighting functions found in rank-dependent theories of choice under risk. These estimates are unusual in two senses. First, they are free of functional form assumptions about both utility and weighting functions, and they are entirely based on binary discrete choices and ...
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Weighted Simulation for Failure Probability Function Estimation
Vulnerability, Uncertainty, and Risk, 2014In the structural reliability-based design, the ‘failure probability function (FPF)’ is referred to the failure probability as a function of the distribution parameters of random variables. This problem generally requires repeated reliability analyses to estimate the failure probability for different distribution parameter values, which is a ...
Xiukai Yuan, Lin Zeng
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Prospect Theory:A Novel Probability Weighting Function Model
ICLEM 2014, 2014The investigation of probability weighting is one of the key components of the modern risky decision making theories. In this study, we propose an approach to build a novel probability weighting model with the use of the Lagrange interpolation method based on Prelec’s probability weighting function model.
Yanlai Li, Sheng Wu
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