A quadratic discrete time probabilistic model, for optimal portfolio selection in (re-)insurance is studied. For positive values of underwriting levels, the expected value of the accumulated result is optimized, under constraints on its variance and on annual ROE's. Existence of a unique...

We propose a novel portfolio selection approach that manages to ease some of the problems that characterise standard expected utility maximisation. The optimal portfolio is no longer defined as the extremum of a suitably chosen utility function: the latter, instead, is reinterpreted as the...

What is the optimum quantity of money in a society? This paper answers this question both from the perspective of a utility maximizing model with real balances in the utility function, and employing an inventory theoretic model which focuses attention on the costs of transacting in different...

This paper decomposes the overall market beta of common stocks into four parts reflecting uncertainty related to the long-run dynamics of stock- specific and market-wide cash flows and discount rates. We employ a discrete time version of Merton�s Intertemporal CAPM to test whether these four...

This paper identifies the Multifractal Models of Asset Return (MMARs) from the eight nodal term structure series of US Treasury rates as well as the Fed Funds rate and, after proper synthesis, simulates those MMARs. We show that there is an inverse persistence term structure in the sense that...

Ideal economics? A “non-ideal” economics approach has been proposed, which considers the possibility of arrangement infringements. It gives promises for both solving fundamental problems of economic theory and creation of new directions and fields of research. The approach application in...

The definition of arrangement infringement has been given. Several characteristics of hurricanes as large-scale events and objectives for the first stages of insurance data analysis have been sketched out. Scale hypotheses, insurance and investment problems have been formulated.