This manuscript proposes a new approach for unveiling existing linkages within the international oil market across multiple driving factors beyond production. A multi-layer, multi-country network is extracted through a novel Bayesian graphical vector autoregressive model, which allows for a more...

In this paper we expand the literature of risk neutral density estimation across maturities from implied volatility curves, usually estimated and interpolated through cubic smoothing splines. The risk neutral densities are computed through the second derivative as in Panigirtzoglou and...

We build on Fackler and King (1990) and propose a general calibration model for implied risk neutral densities. Our model allows for the joint calibration of a set of densities at different maturities and dates. The model is a Bayesian dynamic beta Markov random field which allows for possible...

We define a dynamic and self-adjusting mixture of Gaussian Graphical Models to cluster financial returns, and provide a new method for extraction of nonparametric estimates of dynamic alphas (excess return) and betas (to a choice set of explanatory factors) in a multivariate setting. This...

In this paper, we study the supply-demand drivers of the price of oil over the last two decades. We address the problem of endogeneity using a novel SVAR approach, which allows us to incorporate technological restrictions that occur at the micro level in the production of crude oil to solve the...

Risk neutral measures are defined such that the basic random assets in a portfolio are martingales. Hence, when the market model is complete, to value any instrument having the basic assets as underlying is, in principle, an easy task. For the determination of the risk neutral measure, it is...

Portfolio insurance strategies that control benchmark-underperformance risk require estimating the maximum multiplier of the risk budget, which determines the allocation to the performance-seeking asset (PSA) at each point in time. We explore the implications of taking into account the expected...