Search results for "Econometric"
showing 10 items of 3780 documents
A new look at the meeting clustering effect
2021
PurposeThe study aims to test the existence of a meeting clustering effect in the Spanish Stock Exchange (SSE).Design/methodology/approachThis paper studies the relationship between the clustering of annual general meetings and stock returns in the SSE. A multivariate analysis is carried out in order to analyse the relationship between monthly returns and the clustering of general meetings in the SSE.FindingsThe authors show that meeting clustering exists and that some months exhibit significant and positive additional returns related to the holding of ordinary or extraordinary general meetings.Research limitations/implicationsThe authors have explored some possible explanations for the mee…
On the interplay between multiscaling and stocks dependence
2019
We find a nonlinear dependence between an indicator of the degree of multiscaling of log-price time series of a stock and the average correlation of the stock with respect to the other stocks traded in the same market. This result is a robust stylized fact holding for different financial markets. We investigate this result conditional on the stocks' capitalization and on the kurtosis of stocks' log-returns in order to search for possible confounding effects. We show that a linear dependence with the logarithm of the capitalization and the logarithm of kurtosis does not explain the observed stylized fact, which we interpret as being originated from a deeper relationship.
Influence Functions and Efficiencies of k-Step Hettmansperger–Randles Estimators for Multivariate Location and Regression
2016
In Hettmansperger and Randles (Biometrika 89:851–860, 2002) spatial sign vectors were used to derive simultaneous estimators of multivariate location and shape. Oja (Multivariate nonparametric methods with R. Springer, New York, 2010) proposed a similar approach for the multivariate linear regression case. These estimators are highly robust and have under general assumptions a joint limiting multinormal distribution. The estimates are easy to compute using fixed-point algorithms. There are however no exact proofs for the convergence of these algorithms. The existence and uniqueness of the solutions also still remain unproven although we believe that they hold under general conditions. To ci…
Assessing directional interactions among multiple physiological time series: The role of instantaneous causality
2012
This paper deals with the assessment of frequency domain causality in multivariate (MV) time series with significant instantaneous interactions. After providing different causality definitions, we introduce an extended MV autoregressive modeling approach whereby each definition is described in the time domain in terms of the model coefficients, and is quantified in the frequency domain by means of novel measures of directional connectivity. These measures are illustrated in a theoretical example showing how they reduce to known indexes when instantaneous causality is trivial, while they describe peculiar aspects of directional interaction in the presence of instantaneous causality. The appl…
Decoupling factors on the energy–output linkage: The Spanish case
2007
The recent increase of energy intensity in Spain and the ratification of the Kyoto protocol call for the implementation of energy policies in Spain. In this paper, we investigate the relationship between Gross Domestic Product (GDP) and Energy Consumption (EC) by taking into account several decoupling factors that can affect this linkage. Specifically, we have considered the temporal aggregation of data and its seasonal adjustments, the multivariate methodology, the substitution between EC and other inputs and the technological changes. Empirical tests reveal a long-run relationship between EC and GDP that can only be established in a complete way with a multivariate cointegration analysis.…
Assessing Frequency Domain Causality in Cardiovascular Time Series with Instantaneous Interactions
2009
Summary Background: The partial directed coherence (PDC) is commonly used to assess in the frequency domain the existence of causal relations between two time series measured in conjunction with a set of other time series. Although the multivariate autoregressive (MVAR) model traditionally used for PDC computation accounts only for lagged effects, instantaneous effects cannot be neglected in the analysis of cardiovascular time series. Objectives: We propose the utilization of an extended MVAR model for PDC computation, in order to improve the evaluation of frequency domain causality in the presence of zero-lag correlations among multivariate time series. Methods: A procedure for the identif…
Data Banks and Multivariate Statistics in Physical Anthropology
1984
In recent decades, the fields of administration and economy, the press and - last but not least - the sciences have been characterized by an “explosion of knowledge”, and, as a consequence, by the problem of managing the rapidly increasing mass of information. It has been estimated that knowledge doubles each five years, and even that the interval of doubling seems to decrease. The main response to this challenge are computerized and structured data collections called data banks. “Data banks are systems of data collections which are organized according to logical and/or formal criteria; they should make it possible to reproduce the data of the total collection arranged according to differen…
Modelling systemic price cojumps with Hawkes factor models
2015
Instabilities in the price dynamics of a large number of financial assets are a clear sign of systemic events. By investigating a set of 20 high cap stocks traded at the Italian Stock Exchange, we find that there is a large number of high frequency cojumps. We show that the dynamics of these jumps is described neither by a multivariate Poisson nor by a multivariate Hawkes model. We introduce a Hawkes one factor model which is able to capture simultaneously the time clustering of jumps and the high synchronization of jumps across assets.
Visitor arrivals forecasts amid COVID-19: A perspective from the Africa team
2021
Abstract COVID-19 disrupted international tourism worldwide, subsequently presenting forecasters with a challenging conundrum. In this competition, we predict international arrivals for 20 destinations in two phases: (i) Ex post forecasts pre-COVID; (ii) Ex ante forecasts during and after the pandemic up to end 2021. Our results show that univariate combined with cross-sectional hierarchical forecasting techniques (THieF-ETS) outperform multivariate models pre-COVID. Scenarios were developed based on judgemental adjustment of the THieF-ETS baseline forecasts. Analysts provided a regional view on the most likely path to normal, based on country-specific regulations, macroeconomic conditions,…
Probabilistic Flood Hazard Mapping Using Bivariate Analysis Based on Copulas
2017
This study presents a methodology to extract probabilistic flood hazard maps in an area subject to flood risk, taking into account uncertainties in the definition of design hydrographs. Particularly, the authors present a new method to produce probabilistic inundation and flood hazard maps in which the hydrological input (i.e., synthetic flood design event) to a 2D hydraulic model has been obtained by using a bivariate statistical analysis (copulas) to generate flood peak discharges and volumes. This study also aims to quantify the contribution of boundary conditions’ uncertainty in order to evaluate the effect of this uncertainty source on probabilistic flood hazard mapping. Different comb…