Stark points and Hida-Rankin p-adic L-function

This article is devoted to the elliptic Stark conjecture formulated by Darmon, Lauder and Rotger [DLR], which proposes a formula for the transcendental part of a $p$-adic avatar of the leading term at $s=1$ of the Hasse-Weil-Artin $L$-series $L(E,\varrho_1\otimes \varrho_2,s)$ of an elliptic curve $E$ twisted by the tensor product $\varrho_1\otimes \varrho_2$ of two odd $2$-dimensional Artin representations, when the order of vanishing is two. The main ingredient of this formula is a $2\times 2$ $p$-adic regulator involving the $p$-adic formal group logarithm of suitable Stark points on $E$. This conjecture was proved in [DLR] in the setting where $\varrho_1$ and $\varrho_2$ are induced from characters of the same imaginary quadratic field $K$. In this note we prove a refinement of this result, that was discovered experimentally in Remark 3.4 of [DLR] in a few examples. Namely, we are able to determine the algebraic constant up to which the main theorem of [DLR] holds in a particular setting where the Hida-Rankin $p$-adic $L$-function associated to a pair of Hida families can be exploited to provide an alternative proof of the same result. This constant encodes local and global invariants of both $E$ and $K$

Temporal Aggregation and Ordinary Least Squares Estimation of Cointegrating Regressions

The paper derives the asymptotic distribution of the ordinary least squares estimator of cointegrating vectors with temporally aggregated time series. It is shown, that temporal aggregation reduces the bias and variance of the estimator for average sampling (temporal aggregation of flow series) and does not affect the limiting distribution for systematic sampling (temporal aggregation of stock series). A Monte Carlo experiment shows the consistency of the finite sample results with the asymptotic theory.

La adaptacion del plan nacional de evaluacion de la calidad de las universidades al contexto de una universidad con estructura matricial de centros y departamentos: el caso de la universidad politecnica de cataluña

Peer ReviewedPostprint (published version

Forecasting high-frequency electricity demand with a diffusion index model.

We propose a discussion index model (Stock and Watson, 2002) to fore-cast electricity demand for one hour to one week ahead. The model isparticularly useful as it captures complicated seasonal patterns in thedata. The forecast performance of the proposed method is illustratedwith a simulated real-time experiment for datafrom the Pennsylvania-New Jersey-Maryland Interchange.seasonality;diffusion index forecast;electricity load