C
Carlos Velasco
Researcher at BI Norwegian Business School
Publications - 227
Citations - 7761
Carlos Velasco is an academic researcher from BI Norwegian Business School. The author has contributed to research in topics: Asymptotic distribution & Parametric statistics. The author has an hindex of 42, co-authored 220 publications receiving 6186 citations. Previous affiliations of Carlos Velasco include Complutense University of Madrid & Nanyang Technological University.
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Gaussian Semiparametric Estimation of Non-stationary Time Series
TL;DR: In this paper, the memory of non-stationary processes is estimated using a Gaussian semiparametric estimate of long-range dependence, which is consistent for d ∈ (−½, 1) and asymptotically normal for d∈ (− ½,¾) under a similar set of assumptions to those in Robinson's paper.
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Non-stationary log-periodogram regression
TL;DR: It is obtained that the log-periodogram semiparametric estimate of the memory parameter d for non-stationary time series is asymptotically normal for d and still consistent for d, and the estimates are invariant to the presence of certain deterministic trends, without any need of estimation.
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Digital sensory marketing: Integrating new technologies into multisensory online experience
TL;DR: This review is designed to help the interested reader better understand what sensory marketing in a digital context can offer, thus hopefully opening the way for further research and development in the area.
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Conducting perception research over the internet: a tutorial review.
TL;DR: An overview of the recent literature on the use of internet-based testing to address important questions in perception research is provided, andStrengths and weaknesses of the online approach, relative to others, are highlighted, and recommendations made for those researchers who might be thinking about conducting their own studies using this increasingly-popular approach to research in the psychological sciences.
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Long Memory in Stock-Market Trading Volume
Ignacio N. Lobato,Carlos Velasco +1 more
TL;DR: In this article, a multivariate two-step estimator of the memory parameters of a nonstationary vector process was proposed to analyze the long-memory properties of trading volume for the 30 stocks in the Dow Jones Industrial Average index.