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We investigate the computational issues related to the memory size in the estimation of quadratic covariation, taking into account the specifics of financial ultra-high-frequency data. In multivariate price processes, we consider both contamination by the market microstructure noise and the non-synchronicity of the observations. We formulate a multi-scale, flat-top realized kernel, non-flat-top realized kernel, pre-averaging and modulated realized covariance estimators in quadratic form and fix their bandwidth parameter at a constant value. This allows us to operate with limited memory and formulate this estimation as a streaming algorithm. We compare the performance of the estimators with fixed bandwidth parameter in a simulation study. We find that the estimators ensuring positive semidefiniteness require much higher bandwidth than the estimators without this constraint. [ABSTRACT FROM AUTHOR]

This paper proposes a new methodology for the assessment of quality and benchmarking of antiquarian bookshops. The methodology reflects current trends in this specific market, where, in particular, the most influential factor is the Internet, which changed the structure of this market from a locally oligopolistic structure closer to the perfect competition model. However, though the Internet allowed for the competition in prices, there are several further aspects determining the quality of a bookshop. In our AHP-based methodology, we combine both the traditional bookshop-specific criteria (such as opening hours) with those measuring the new features resulting from the public open-access database of all books in stock. We present a case study of antiquarian bookshops in Prague, Czech Republic. The case study illustrates not only the insight into the structure of this market, but also demonstrates that the methodology is useful in the management of bookshops, enabling a bookshop to determine its market position among competitors. The main findings support the hypothesis that quality web services are essential as the pricing policy, which distinguishes the market from its previous locally oligopolistic phase. We also confirm the results of the case study by a robustness analysis showing that the possible subjectivity of experts plays a minor role since we would need large changes in weights of criteria to alter the resulting ranking. [ABSTRACT FROM AUTHOR]

Arrivals in a queueing system are typically assumed to be independent and exponentially distributed. Our analysis of an online bookshop, however, shows that there is an autocorrelation structure. First, we adjust the inter-arrival times for diurnal and seasonal patterns. Second, we model adjusted inter-arrival times by the generalized autoregressive score (GAS) model based on the generalized gamma distribution in the spirit of the autoregressive conditional duration (ACD) models. Third, in a simulation study, we investigate the effects of the dynamic arrival model on the number of customers, the busy period, and the response time in queueing systems with single and multiple servers. We find that ignoring the autocorrelation structure leads to significantly underestimated performance measures and consequently suboptimal decisions. The proposed approach serves as a general methodology for the treatment of arrivals clustering in practice. [ABSTRACT FROM AUTHOR]

While working with data, we typically utilize four basic operations: Create, Read, Update, and Delete. These functions, used altogether with a persistent storage, are encapsulated into the acronym CRUD. Although the data functions are easy for machines, people have to use them through a user interface and its components. Even though some of these components are standardized (for example, HTML forms), their visual representation is highly customized among devices and technologies. Concerning users, subjective preferences are taken into account as well. As a result, the efficiency of working with data can be affected by choosing appropriate components and their attributes, such as colors. Choosing the right colors, we can work with data faster and more effectively, utilizing users' expectations, understanding, and perception. We developed a publicly accessible Software Ergonomics Testing Platform. Through running experiments worldwide, we found out that users have a prior expectation about colors used for CRUD operations. Results show that there is a strong consensus on the color preference for the delete operation with color red being voted by 64 % users worldwide. On the other hand, color preferences for update operation strongly differ among continents. The impact of temporary weather conditions to color preference seems to be negligible. [ABSTRACT FROM AUTHOR]