Segregation and integration: a study of the behaviors of investors with extended value functions.
Grüss-type bounds for the covariance of transformed random variables.
Grüss-type bounds for covariances and the notion of quadrant dependence in expectation
We show that Grüss-type probabilistic inequalities for covariances can be considerably sharpened when the underlying random variables are quadrant dependent in expectation (QDE). The herein established covariance bounds not only sharpen the classical Grüss inequality but also improve upon recently derived Grüss-type bounds under the assumption of quadrant dependency (QD), which is stronger than QDE. We illustrate our general results with examples based on specially devised bivariate distributions...
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