1,720,958 research outputs found
Finite sample results of Range-based integrated volatility estimation
No full textIn this paper we consider the finite-sample properties of Realized Range estimators of integrated volatility and we compare them to those of the Realized Volatility estimators when a sample
of high-frequency data is observed. Simulated data are obtained from different generating mechanisms for the instantaneous volatility process, e.g. Ornstein-Uhlenbeck, long memory and
jump processes. We analyze the impact that missing observations have on the Realized Range measures and we propose a simple correction in order to reduce the bias. We also evaluate the robustness of the different approaches considered when high-frequency prices are affected by bid-ask bounce and price discreteness. Simulation results confirm that realized range corrected for irregular sampling has lower bias while not increasing the estimator variance. The simulations also show how the degree of persistence in the estimated Integrated Variance series crucially depends on the sampling frequency adopted in the estimation and thus on the precision of the estimators. A brief empirical application with high-frequency IBM data is also included
Model and distribution uncertainty in multivariate GARCH estimation: a Monte Carlo analysis
Full text linkMultivariate GARCH models are in principle able to accommodate the features
of the dynamic conditional correlations processes, although with the drawback, when
the number of financial returns series considered increases, that the parameterizations
entail too many parameters.In general, the interaction between model parametrization
of the second conditional moment and the conditional density of asset returns
adopted in the estimation determines the fitting of such models to the observed dynamics
of the data. This paper aims to evaluate the interactions between conditional
second moment specifications and probability distributions adopted in the likelihood
computation, in forecasting volatilities and covolatilities. We measure the relative
performances of alternative conditional second moment and probability distributions
specifications by means of Monte Carlo simulations, using both statistical and financial
forecasting loss functions
Model and distribution uncertainty in multivariate GARCH estimation: A Monte Carlo analysis
No full textMultivariate GARCH models are in principle able to accommodate the features of the dynamic conditional covariances; nonetheless the interaction between model parametrization of the second conditional moment and the conditional density of asset
returns adopted in the estimation determines the fitting of such models to the observed dynamics of the data. Alternative MGARCH specifications and probability distributions are
compared on the basis of forecasting performances by means of Monte Carlo simulations, using both statistical and financial forecasting loss functions
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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