We consider an agent who has to repeatedly make choices in an uncertain and changing environment, who has full information of the past, who discounts future payoffs, but who has no prior. We provide a learning algorithm that performs almost as well as the best of a given finite number of experts...

We study the interaction between insurance and capital markets within single but general framework.We show that capital markets greatly enhance the risk sharing capacity of insurance markets and the scope of risks that are insurable because efficiency does not depend on the number of agents at...

This paper extends previous resuls on optimal insurance trading in the presence of a stock market that allows continuous asset trading and substantial personal heterogeneity, and applies those results in a context of asymmetric information with references to the role of genetic testing in...

This paper surveys asset allocation methods that extend the traditional approach. An important feature of the the traditional approach is that measures the risk and return tradeoff in terms of mean and variance of final wealth. However, there are also other important features that are not always...

This paper looks at the dynamic management of risk in an economy with discrete time consumption and endowments and continuous trading. I study how agents in such an economy deal with all the risk in the economy and attain their Pareto optimal allocations by trading in a few natural securities:...

This paper extends existing insurance results on the type of insurance contracts needed for insurance market efficiency to a dynamic setting. It introduces continuosly open markets that allow for more efficient asset allocation. It also eliminates the role of preferences and endowments in the...

This paper introduces a mixture model based on the beta distribution, without preestablished means and variances, to analyze a large set of Beauty-Contest data obtained from diverse groups of experiments (Bosch-Domenech et al. 2002). This model gives a better t of the experimental data, and more...

Minimax lower bounds for concept learning state, for example, that for each sample size $n$ and learning rule $g_n$, there exists a distribution of the observation $X$ and a concept $C$ to be learnt such that the expected error of $g_n$ is at least a constant times $V/n$, where $V$ is the VC...

The classical binary classification problem is investigated when it is known in advance that the posterior probability function (or regression function) belongs to some class of functions. We introduce and analyze a method which effectively exploits this knowledge. The method is based on...

We model the different ways in which precedents and contract standardization shape the development of markets and the law. In a setup where more resourceful parties can distort contract enforcement to their advantage, we find that the introduction of a standard contract reduces enforcement...