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Does the Spillover Index Respond Significantly to Systemic Shocks? A Bootstrap-Based Probabilistic Analysis
Greenwood-Nimmo, M.; Kočenda, Evžen; Nguyen, V. H.
2021 - English
The spillover index developed by Diebold and Yilmaz (Economic Journal, 2009, vol. 119, pp. 158-171) is widely used to measure connectedness in economic and financial networks. Abrupt increases in the spillover index are typically thought to result from systemic events, but evidence of the statistical significance of this relationship is largely absent from the literature. We develop a new bootstrap-based technique to evaluate the probability that the value of the spillover index changes over an arbitrary time period following an exogenously defined event. We apply our framework to the original dataset studied by Diebold and Yilmaz and obtain qualified support for the notion that the spillover index increases in a timely and statistically significant manner in the wake of systemic shocks.
Keywords:
Spillover index; systemic events; bootstrap-after-bootstrap procedure
Fulltext is available at external website.
Does the Spillover Index Respond Significantly to Systemic Shocks? A Bootstrap-Based Probabilistic Analysis
The spillover index developed by Diebold and Yilmaz (Economic Journal, 2009, vol. 119, pp. 158-171) is widely used to measure connectedness in economic and financial networks. Abrupt increases in the ...
Distributed Sequential Zero-Inflated Poisson Regression
Žemlička, R.; Dedecius, Kamil
2021 - English
The zero-inflated Poisson regression model is a generalized linear model (GLM) for non-negative count variables with an excessive number of zeros. This letter proposes its low-cost distributed sequential inference from streaming data in networks with information diffusion. The model is viewed as a probabilistic mixture of a Poisson and a zero-located Dirac component, whose probabilities are estimated using a quasi-Bayesian procedure. The regression coefficients are inferred by means of a weighted Bayesian update. The network nodes share their posterior distributions using the diffusion protocol.\n
Keywords:
Poisson regression; zero inflation; GLM
Fulltext is available at external website.
Distributed Sequential Zero-Inflated Poisson Regression
The zero-inflated Poisson regression model is a generalized linear model (GLM) for non-negative count variables with an excessive number of zeros. This letter proposes its low-cost distributed ...
Media Treatment of Monetary Policy Surprises and Their Impact on Firms’ and Consumers’ Expectations
Pinter, J.; Kočenda, Evžen
2021 - English
We empirically investigate whether monetary policy announcements affect firms’ and consumers’ expectations by taking into account media treatments of monetary policy announcements. To identify exogenous changes in monetary policy stances, we use the standard financial monetary policy surprise measures in the euro area. We then analyze how a general newspaper and a financial newspaper (Le Monde and The Financial Times) report on announcements. We find that 87 % of monetary policy surprises are either not associated with the general newspaper reporting a change in the monetary policy stance to their readers or have a sign that is inconsistent with the media report of the announcement. When we use the raw monetary policy surprises variable as an independent variable in the link between monetary policy announcements and firms’/consumers’ expectations, we mostly do not find, in line with several previous studies, any statistically significant association. When we take only monetary policy surprises that are consistent with the general newspaper report, in almost all cases we find that monetary policy surprises on the immediate monetary policy stance do affect expectations. Surprises related to future policy inclination and information shocks usually do not appear to matter. The results appear to be in line with rational inattention theories and highlight the need for caution in the use of monetary policy surprise measures for macroeconomic investigations.
Keywords:
firm expectations; consumer expectations; monetary policy surprises; European Central Bank; information effect
Fulltext is available at external website.
Media Treatment of Monetary Policy Surprises and Their Impact on Firms’ and Consumers’ Expectations
We empirically investigate whether monetary policy announcements affect firms’ and consumers’ expectations by taking into account media treatments of monetary policy announcements. To identify ...
City simulation software for modeling, planning, and strategic assessment of territorial city units
Svítek, M.; Přibyl, O.; Vorel, J.; Garlík, B.; Resler, Jaroslav; Kozhevnikov, S.; Krč, Pavel; Geletič, Jan; Daniel, Milan; Dostál, R.; Janča, T.; Myška, V.; Aralkina, O.; Pereira, A. M.
2021 - English
SVÍTEK, M., PŘIBYL, O., VOREL, J., GARLÍK, B., RESLER, J., KOZHEVNIKOV, S., KRČ, P., GELETIČ, J., DANIEL, M., DOSTÁL, R., JANČA, T., MYŠKA, V., ARALKINA, O., PEREIRA, A. M. City simulation software for modeling, planning, and strategic assessment of territorial city units. 1.1. Prague: CTU & ICS CAS, 2021. Technical Report. ABSTRACT: The Smart Resilience City concept is a new vision of a city as a digital platform and eco-system of smart services where agents of people, things, documents, robots, and other entities can directly negotiate with each other on resource demand principals providing the best possible solution. It creates the smart environment making possible self-organization in sustainable or, when needed, resilient way of individuals, groups and the whole system objectives.
Keywords:
Smart city; City simulation; Energy resource-demand modelling; Environmental modelling; Synthetic population; Transport modelling
Available on request at various institutes of the ASCR
City simulation software for modeling, planning, and strategic assessment of territorial city units
SVÍTEK, M., PŘIBYL, O., VOREL, J., GARLÍK, B., RESLER, J., KOZHEVNIKOV, S., KRČ, P., GELETIČ, J., DANIEL, M., DOSTÁL, R., JANČA, T., MYŠKA, V., ARALKINA, O., PEREIRA, A. M. City simulation software ...
Score matching filters for Gaussian Markov random fields with a linear model of the precision matrix
Turčičová, Marie; Mandel, J.; Eben, Kryštof
2021 - English
We present an ensemble filter that provides a rigorous covariance regularization when the underlying random field is Gaussian Markov. We use a linear model for the precision matrix (inverse of covariance) and estimate its parameters together with the analysis mean by the Score Matching method. This procedure provides an explicit expression for parameter estimators. The resulting analysis step formula is the same as in the traditional ensemble Kalman filter.
Keywords:
Score matching; ensemble filter; Gaussian Markov random field; covariance modelling
Available at various institutes of the ASCR
Score matching filters for Gaussian Markov random fields with a linear model of the precision matrix
We present an ensemble filter that provides a rigorous covariance regularization when the underlying random field is Gaussian Markov. We use a linear model for the precision matrix (inverse of ...
Assessment of Independent EEG Components Obtained by Different Methods for BCI Based on Motor Imagery
Húsek, Dušan; Frolov, A. A.; Kerechanin, J. V.; Bobrov, P.D.
2021 - English
Eight methods of decomposition of a multichannel EEG signal are compared in terms of their ability to identify the most physiologically significant components. The criterion for the meaningfulness of a method is its ability to reduce mutual information between components; to create components that can be attributed to the activity of dipoles located in the cerebral cortex; find components that are provided by other methods and for this case; and at the same time, these components should most contribute to the accuracy of the BCI based on imaginary movement. Independent component analysis methods AMICA, RUNICA and FASTICA outperform others in the first three criteria and are second only to the Common Spatial Patterns method in the fourth criterion. The components created by all methods for 386 experimental sessions of 27 subjects were combined into more than 100 clusters containing more than 10 elements. Additionally, the components of the 12 largest clusters were analyzed. They have proven to be of great importance in controlling BCI, their origins can be modeled using dipoles in the brain, and they have been detected by several degradation methods. Five of the 12 selected components have been identified and described in our previous articles. Even if the physiological and functional origins of the rest of identified components’ are to be the subject of further research, we have shown that their physiological nature is at least highly probable.\n
Keywords:
brain–computer interface; motor imagery; blind source separation; independent component analysis; common spatial patterns; cluster analysis; EEG pattern extraction; EEG analysis; ICA; CSP; BCI; motor imagery
Available at various institutes of the ASCR
Assessment of Independent EEG Components Obtained by Different Methods for BCI Based on Motor Imagery
Eight methods of decomposition of a multichannel EEG signal are compared in terms of their ability to identify the most physiologically significant components. The criterion for the meaningfulness of ...
GPR survey of the reinforcement above the long horizontal window case study: Ice ring stadium restaurant Fuchs on Štvanice Island
Válek, Jan; Kozlovcev, Petr; Eisler, Marek; Dušek, Ondřej
2021 - English
The aim of the survey was to assess the use of Ground Penetration Radar for the reinforcement position detection on the Ice ring restaurant – an early concrete building on Štvanice Island in Prague from 1932. For this case study a potentially critical section of a façade above the app. 16 m long horizontal window was selected. GPR from IDS company equipped with 2 GHz high frequency antenna was used.
Keywords:
Fuchs restaurant; GPR; reinforced concrete
Available at various institutes of the ASCR
GPR survey of the reinforcement above the long horizontal window case study: Ice ring stadium restaurant Fuchs on Štvanice Island
The aim of the survey was to assess the use of Ground Penetration Radar for the reinforcement position detection on the Ice ring restaurant – an early concrete building on Štvanice Island in Prague ...
Transferring Improved Local Kernel Design in Multi-Source Bayesian Transfer Learning, with an application in Air Pollution Monitoring in India
Nugent, Sh.; Quinn, Anthony
2021 - English
Existing frameworks for multi-task learning [1],[2] often rely on completely modelled relationships between tasks, which may not be available. Recent work [3], [4] has been undertaken on approaches to fully probabilistic methods for transfer learning between two Gaussian Process (GP) tasks. There, the target algorithm accepts source knowledge in the form of a probabilistic prior from a source algorithm, without requiring the target to model their interaction with the source. These strategies have offered robust improvements on current state of the art algorithms, such as the Intrinsic Coregionalization Model. The Bayesian Transfer Learning algorithm proposed in [4], was found to provide robust, positive\ntransfer. This algorithm was then extended to accommodate knowledge transfer from multiple source modellers [5]. Improved predictive performance was observed from increases in the number of sources. This report reviews the multi-source transfer findings in [5] and applies it to a real world problem of pollution modelling in India, using public-domain data.
Keywords:
fully probabilistic methods; Bayesian Transfer Learning algorithm; Gaussian Process; Intrinsic Coregionalization Model; pollution modelling
Fulltext is available at external website.
Transferring Improved Local Kernel Design in Multi-Source Bayesian Transfer Learning, with an application in Air Pollution Monitoring in India
Existing frameworks for multi-task learning [1],[2] often rely on completely modelled relationships between tasks, which may not be available. Recent work [3], [4] has been undertaken on approaches to ...
Nearly All Reals Can Be Sorted with Linear Time Complexity
Jiřina, Marcel
2021 - English
We propose a variant of the counting sort modified for sorting reals in a linear time. It is assumed that the sorting key and pointers to the items being sorted are moved and individual items remain at the same place in the memory (in place sorting). In this case, the space complexity of the new variant of the algorithm is the same as the complexity of the quicksort. We also quantify the practical limits for possible sorting reals in a linear time. This possibility is assured under additional assumptions on the distribution of the sorting key, mainly the independence and identity of the distribution. Here we give a more general criteria easily applicable in practice. We also show that the algorithm is applicable for data that do not fulfill criteria for linear time complexity but even that the computation is faster than the system quicksort. A new, faster version of the algorithm is attached.
Keywords:
sorting; algorithm; real sorting key; time complexity; linear complexity
Available in digital repository of the ASCR
Nearly All Reals Can Be Sorted with Linear Time Complexity
We propose a variant of the counting sort modified for sorting reals in a linear time. It is assumed that the sorting key and pointers to the items being sorted are moved and individual items remain ...
Measurements on KR-D-4 Cascade
Šimurda, David; Radnic, Tomáš
2021 - English
This report contains results and evaluation of aerodynamic measurements conducted on a subsonic compressor blade cascade.
Keywords:
compressor blade cascade; experiment; subsonic flow; transonic flow; AVDR
Available at various institutes of the ASCR
Measurements on KR-D-4 Cascade
This report contains results and evaluation of aerodynamic measurements conducted on a subsonic compressor blade cascade.
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