We study positional portfolio management strategies in which the manager maximizes an expected utility function written on the cross-sectional rank (position) of the portfolio return. The objective function reflects the manager's goal to be well-ranked among competitors. To implement positional...

The recursive prediction and filtering formulas of the Kalman filter are difficult to implement in nonlinear state space models since they require the updating of a function. The aim of this paper is to consider the situation of a large number n of individual measurements, called...

This paper studies the problem of disentangling risk correlation and contagion in a set of individual binary processes. The two admissible values correspond to bad and good risk states of an individual. The risk correlation is captured by introducing a dynamic frailty, whereas the contagion...

We consider a homogeneous class of assets, whose returns are driven by an unobservable factor representing systematic risk. We derive approximated pricing formulas for the future factor values and their proxies, when the size n of the class is large. Up to order 1/n, these closed-form...

Supported by empirical examples, this paper provides a theoretical analysis on the impacts of using a suboptimal information set for the estimation of the empirical pricing kernel and, more in general, for the validity of the fundamental theorems of asset pricing. While inferring the...

The article presents a Bayesian nonparametric approach to model the Pricing Kernel (PK), defined as the present value of the ratio between the risk neutral density, q, and a modified physical density, p*. The risk neutral density is estimated from option data and the modified physical density is...