1,721,038 research outputs found
Multivariate Wavelet-based shape preserving estimation for dependent observations
No full textWe introduce a new approach to shape-preserving estimation of cumulative distribution functions and probability density functions using the wavelet methodology for multivariate dependent data. Our estimators preserve shape constraints such as monotonicity, positivity and integration to one, and allow for low spatial regularity of the underlying functions. We discuss conditional quantile estimation for financial time series data as an application. Our methodology can be implemented with B-splines. We show by means of Monte Carlo simulations that it performs well in finite samples and for a data-driven choice of the resolution level
The dark side of global integration: Increasing tail dependence
No full textWe measure stock market coexceedances using the methodology of Cappiello, Gerard and Manganelli (2005, ECB Working Paper 501). This method enables us to measure comovement at each point of the return distribution. First, we construct annual coexceedance probabilities for both lower and upper tail return quantiles using daily data from 1974–2006. Next, we explain these probabilities in a panel gravity model framework. Results show that macroeconomic variables asymmetrically impact stock market comovement across the return distribution. Financial liberalization significantly increases left tail comovement, whereas trade integration significantly increases comovement across all quantiles. Decreasing exchange rate volatility results in increasing lower tail comovement. The introduction of the euro increases comovement across the entire return distribution, thereby significantly reducing the benefits of portfolio diversification within the euro area
Early exercise decision in American options with dividends, stochastic volatility and jumps
No full textUsing a fast numerical technique, we investigate a large database of investors’ suboptimal nonexercise of short-maturity American call options on dividend-paying stocks listed on the Dow Jones. The correct modeling of the discrete dividend is essential for a correct calculation of the early exercise boundary, as confirmed by theoretical insights. Pricing with stochastic volatility and jumps instead of the Black–Scholes–Merton benchmark cuts the amount lost by investors through suboptimal exercise by one-quarter. The remaining three-quarters are largely unexplained by transaction fees and may be interpreted as an opportunity cost for the investors to monitor optimal exercise
A nonparametric ACD model
Full text linkWe propose a fully nonparametric approach to the analysis of the Autocorrelated Conditional Duration (ACD) process applied to durations between financial events. We use a recursive algorithm to estimate the nonparametric specification. In a Monte Carlo experiment, we analyse its forecasting performance and compare it with a correctly and a mis-specified parametric estimator. On a real dataset, the nonparametric estimator seems to mildly overperform in terms of predictive power. The nonparametric analysis can also provide guidance on the choice between alternative parametric specifications. In particular, once intraday seasonality is directly modelled in the conditional duration function, the nonparametric approach provides insights into the time-varying nature of the dynamics in the model that the standard procedures of deseasonalization may lead one to overlook
Inference in conditional moment restriction models when there is selection due to stratification
Full text linkWe show how to use a smoothed empirical likelihood approach to conduct efficient semiparametric inference in models characterized as conditional moment equalities when data are collected by variable probability sampling. Results from a simulation experiment suggest that the smoothed empirical likelihood based estimator can estimate the model parameters very well in small to moderately sized stratified samples
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
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