Behavioral premium principles
Sign Up to like & getrecommendations! Published in 2019 at "Decisions in Economics and Finance"
DOI: 10.1007/s10203-019-00246-x
Abstract: We define a premium principle under the continuous cumulative prospect theory which extends the equivalent utility principle. In prospect theory, risk attitude and loss aversion are shaped via a value function, whereas a transformation of… read more here.
Keywords: prospect theory; probability weighting; function; behavioral premium ... See more keywords
Probability weighting for losses and for gains among smallholder farmers in Uganda
Sign Up to like & getrecommendations! Published in 2020 at "Theory and Decision"
DOI: 10.1007/s11238-020-09796-8
Abstract: Probability weighting is a marked feature of decision-making under risk. For poor people in rural areas of developing countries, how probabilities are evaluated matters for livelihoods decisions, especially the probabilities associated with losses. Previous studies… read more here.
Keywords: losses gains; probability; among smallholder; probability weighting ... See more keywords
Efficient inverse probability weighting method for quantile regression with nonignorable missing data
Sign Up to like & getrecommendations! Published in 2017 at "Statistics"
DOI: 10.1080/02331888.2016.1268615
Abstract: ABSTRACT Quantitle regression (QR) is a popular approach to estimate functional relations between variables for all portions of a probability distribution. Parameter estimation in QR with missing data is one of the most challenging issues… read more here.
Keywords: inverse probability; probability; regression; probability weighting ... See more keywords
Probability weighting and default risk: a possible explanation for distressed stock puzzles
Sign Up to like & getrecommendations! Published in 2020 at "Quantitative Finance"
DOI: 10.1080/14697688.2019.1698057
Abstract: This paper suggests incorporating investor probability weighting and the default risk of individual firms into a consumption-based asset pricing model. The extended model provides a unified explanation for several anomalous patterns observed in financial markets.… read more here.
Keywords: weighting default; default risk; probability; probability weighting ... See more keywords
Does Probability Weighting Drive Lottery Preferences?
Sign Up to like & getrecommendations! Published in 2019 at "Journal of Behavioral Finance"
DOI: 10.1080/15427560.2019.1672167
Abstract: Abstract We propose a test of the theory of skewness preferences. The probability weighting feature that is the basis of their theory relies on investors overweighting the probability of extreme, positive returns. The resulting investor… read more here.
Keywords: probability; week high; preferences probability; probability weighting ... See more keywords
A Simulation Study Comparing the Performance of Time-Varying Inverse Probability Weighting and g-Computation in Survival Analysis.
Sign Up to like & getrecommendations! Published in 2022 at "American journal of epidemiology"
DOI: 10.1093/aje/kwac162
Abstract: Inverse probability weighting (IPW) and g-computation are commonly used in time-varying analyses. To inform decisions on which to use, we compared these methods using a plasmode simulation, based on the Effects of Aspirin in Gestation… read more here.
Keywords: computation; time; inverse probability; time varying ... See more keywords
Inverse probability weighting to estimate exposure effects on the burden of recurrent outcomes in the presence of competing events.
Sign Up to like & getrecommendations! Published in 2023 at "American journal of epidemiology"
DOI: 10.1093/aje/kwad031
Abstract: Recurrent events - outcomes that an individual can experience repeatedly over the course of follow-up - are common in epidemiologic and health services research. Studies involving recurrent events often focus on time to first occurrence… read more here.
Keywords: probability weighting; inverse probability; mean cumulative; cumulative count ... See more keywords
Household Portfolio Underdiversification and Probability Weighting: Evidence from the Field
Sign Up to like & getrecommendations! Published in 2020 at "Review of Financial Studies"
DOI: 10.1093/rfs/hhaa131
Abstract: We test whether probability weighting affects household portfolio choice in a representative survey. On average, people display inverse-S-shaped probability weighting, overweighting low probability events. As theory predicts, probability weighting is positively associated with portfolio underdiversification… read more here.
Keywords: household portfolio; portfolio underdiversification; probability; probability weighting ... See more keywords
Exploring the Subtleties of Inverse Probability Weighting and Marginal Structural Models.
Sign Up to like & getrecommendations! Published in 2018 at "Epidemiology"
DOI: 10.1097/ede.0000000000000813
Abstract: Since being introduced to epidemiology in 2000, marginal structural models have become a commonly used method for causal inference in a wide range of epidemiologic settings. In this brief report, we aim to explore three… read more here.
Keywords: inverse probability; structural models; marginal structural; epidemiology ... See more keywords
On the Relation Between G-formula and Inverse Probability Weighting Estimators for Generalizing Trial Results.
Sign Up to like & getrecommendations! Published in 2019 at "Epidemiology"
DOI: 10.1097/ede.0000000000001097
Abstract: When generalizing inferences from a randomized trial to a target population, two classes of estimators are used: g-formula estimators that depend on modeling the conditional outcome mean among trial participants and inverse probability (IP) weighting… read more here.
Keywords: probability weighting; weighting estimators; inverse probability; probability ... See more keywords
Meta-Probability Weighting for Improving Reliability of DNNs to Label Noise
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2023.3237033
Abstract: Training noise-robust deep neural networks (DNNs) in label noise scenario is a crucial task. In this paper, we first demonstrates that the DNNs learning with label noise exhibits over-fitting issue on noisy labels because of… read more here.
Keywords: noise; label noise; dnns label; meta probability ... See more keywords