Showing 11 - 20 of 321
Persistent link: https://www.econbiz.de/10011518800
Persistent link: https://www.econbiz.de/10012604816
The results of an experiment extending Ellsberg's setup demonstrate that attitudes towards ambiguity and compound uncertainty are closely related. However, this association is much stronger when the second layer of uncertainty is subjective than when it is objective. Provided that the compound...
Persistent link: https://www.econbiz.de/10011457763
There is considerable literature on matrix-variate gamma distributions, also known as Wishart distributions, which are driven by a shape parameter with values in the (Gindikin) set {i/2, i = 1, . . . , k−1}∪((k−1)/2, ∞). We provide an extension of this class to the case where the shape...
Persistent link: https://www.econbiz.de/10013469607
Anscombe and Aumann (1963) offer a definition of subjective probability in terms of comparisons with objective probabilities. That definition - which has provided the basis for much of the succeeding work on subjective probability - presumes that the subjective probability of an event is...
Persistent link: https://www.econbiz.de/10013264885
I introduce dynamic option trading and non-linear views into the classical portfolio selection problem. The optimal dynamic option portfolio is characterized explicitly in terms of its expected sensitivities (Greeks) and the role of the mean-variance effi cient portfolio is played by the "Greek...
Persistent link: https://www.econbiz.de/10010337963
Persistent link: https://www.econbiz.de/10001609824
We introduce a model for portfolio selection with an extendable investment universe where the agent faces a trade-off between exploiting existing and exploring for new investment opportunities. An agent with mean-variance preferences starts with an existing investment universe consisting of a...
Persistent link: https://www.econbiz.de/10012271124
Persistent link: https://www.econbiz.de/10013259971
We introduce an ensemble learning method based on Gaussian Process Regression (GPR) for predicting conditional expected stock returns given stock-level and macro-economic information. Our ensemble learning approach significantly reduces the computational complexity inherent in GPR inference and...
Persistent link: https://www.econbiz.de/10014236083