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Some modifications of the limited-memory variable metric optimization methods
Vlček, Jan; Lukšan, Ladislav
2023 - English
Several modifications of the limited-memory variable metric (or quasi-Newton) line search methods for large scale unconstrained optimization are investigated. First the block version of the symmetric rank-one (SR1) update formula is derived in a similar way as for the block BFGS update in Vlˇcek and Lukˇsan (Numerical Algorithms 2019). The block SR1 formula is then modified to obtain an update which can reduce the required number of arithmetic operations per iteration. Since it usually violates the corresponding secant conditions, this update is combined with the shifting investigated in Vlˇcek and Lukˇsan (J. Comput. Appl. Math. 2006). Moreover, a new efficient way how to realize the limited-memory shifted BFGS method is proposed. For a class of methods based on the generalized shifted economy BFGS update, global convergence is established. A numerical comparison with the standard L-BFGS and BNS methods is given.
Keywords:
unconstrained minimization; variable metric methods; limited-memory methods; variationally derived methods; arithmetic operations reduction; global convergence
Available in a digital repository NRGL
Some modifications of the limited-memory variable metric optimization methods
Several modifications of the limited-memory variable metric (or quasi-Newton) line search methods for large scale unconstrained optimization are investigated. First the block version of the symmetric ...
GA 19-07635S: Outputs and Results
Rehák, Branislav
2023 - English
This manuscript aims to deliver a survey of results obtained during the solution of the project No. GA19-07635S of the Czech Science Foundation. The timespan dedicated to the work on this project was 1.3.2019 - 30.6.2022. The main area dealt with were\nnonlinear multi-agent systems and their synchronization, further, attention was paid to some auxiliary results in the area of nonlinear observers. This Report briefly introduces the Project, provides a summary of the results obtained and also sketches an outline how these results will be applied and extended in future.
Keywords:
multi-agent systems; nonlinear multi-agent systems; synchronization
Fulltext is available at external website.
GA 19-07635S: Outputs and Results
This manuscript aims to deliver a survey of results obtained during the solution of the project No. GA19-07635S of the Czech Science Foundation. The timespan dedicated to the work on this project was ...
Drivers of Private Equity Activity across Europe: An East-West Comparison
Kočenda, Evžen; Shivendra, R.
2023 - English
We investigate the key macroeconomic and institutional determinants of fundraising and investment activities and compare them across Europe, covering 13 Central and Eastern European (CEE) and 16 Western European (WE) countries. Five macroeconomic variables and nineteen institutional variables are selected. These variables are studied using panel data analysis with fixed effects and random effects models over an eleven-year observation period (2010–2020). Bayesian Model Averaging (BMA) is applied to select the key variables. Our results suggest that macroeconomic variables have no significant impact on fundraising and investment activity in either region. Investment activity is a significant driver of fundraising across Europe. Similarly, fundraising and divestment activity are significant drivers of investments across Europe. Institutional variables, however, affect fundraising and investment activity differently. While investment freedom has a significant effect on funds raised in the WE and CEE countries, government integrity and trade freedom are both significant determinants of investments in both European regions. In addition, the results demonstrate that, in contrast to the WE region, fundraising in the CEE region is not country specific. We investigate the key macroeconomic and institutional determinants of fundraising and investment activities and compare them across Europe, covering 13 Central and Eastern European (CEE) and 16 Western European (WE) countries. Five macroeconomic variables and nineteen institutional variables are selected. These variables are studied using panel data analysis with fixed effects and random effects models over an eleven-year observation period (2010–2020). Bayesian Model Averaging (BMA) is applied to select the key variables. Our results suggest that macroeconomic variables have no significant impact on fundraising and investment activity in either region. Investment activity is a significant driver of fundraising across Europe. Similarly, fundraising and divestment activity are significant drivers of investments across Europe. Institutional variables, however, affect fundraising and investment activity differently. While investment freedom has a significant effect on funds raised in the WE and CEE countries, government integrity and trade freedom are both significant determinants of investments in both European regions. In addition, the results demonstrate that, in contrast to the WE region, fundraising in the CEE region is not country specific.
Keywords:
Private equity; Fundraising; Investment
Fulltext is available at external website.
Drivers of Private Equity Activity across Europe: An East-West Comparison
We investigate the key macroeconomic and institutional determinants of fundraising and investment activities and compare them across Europe, covering 13 Central and Eastern European (CEE) and 16 ...
Good vs. Bad Volatility in Major Cryptocurrencies: The Dichotomy and Drivers of Connectedness
Šíla, Jan; Kočenda, Evžen; Kukačka, Jiří; Krištoufek, Ladislav
2023 - English
Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. We investigate the volatility connectedness dynamics of a representative set of eight major crypto assets. Methodologically, we decompose the measured volatility into positive and negative components and employ the time-varying parameters vector autoregression (TVP-VAR) framework to show distinct dynamics associated with market booms and downturns. The results suggest that crypto connectedness reflects important events and exhibits more variable and cyclical dynamics than those of traditional financial markets. Periods of extremely high or low connectedness are clearly linked to specific events in the crypto market and macroeconomic or monetary history. Furthermore, existing asymmetry from good and bad volatility indicates that information about market downturns spills over substantially faster than news about comparable market surges. Overall, the connectedness dynamics are predominantly driven by fundamental crypto factors, while the asymmetry measure also depends on macro factors such as the VIX index and the expected inflation.
Keywords:
Volatility; Dynamic connectedness; Asymmetric effects; Cryptocurrency
Fulltext is available at external website.
Good vs. Bad Volatility in Major Cryptocurrencies: The Dichotomy and Drivers of Connectedness
Cryptocurrencies exhibit unique statistical and dynamic properties compared to those of traditional financial assets, making the study of their volatility crucial for portfolio managers and traders. ...
Determinants of Financial Inclusion in Africa and OECD Countries
Kočenda, Evžen; Eshun, S. F.
2023 - English
Sub-Saharan Africa (SSA) has been identified as one of the least financially inclusive regions in the world with a huge disparity in comparison to highly financially inclusive regions. Using a dynamic panel data analysis, we explore the factors influencing financial inclusion in Sub-Saharan Africa (SSA) using countries belonging to the Organisation for Economic Co-operation and Development (OECD) as a benchmark. We employ the System Generalized Method of Moments (GMM) estimator and assess 31 SSA and 38 OECD countries from 2000-2021. We show that the differences in trade openness, banks' efficiency, income, and remittances are some macro-level factors that explain the variation in financial inclusion levels. We highlight the importance of quality literacy policies, trade improvement with restrictions on cross-border capital flows, and a more efficient financial system to promote financial inclusion.
Keywords:
Financial Inclusion; Financial Inclusion Index; Sub-Saharan Africa
Fulltext is available at external website.
Determinants of Financial Inclusion in Africa and OECD Countries
Sub-Saharan Africa (SSA) has been identified as one of the least financially inclusive regions in the world with a huge disparity in comparison to highly financially inclusive regions. Using a dynamic ...
Spatio-Spectral EEG Patterns in the Source-Reconstructed Space and Relation to Resting-State Networks: An EEG-fMRI Study
Jiříček, Stanislav; Koudelka, V.; Mantini, D.; Mareček, R.; Hlinka, Jaroslav
2022 - English
In this work, we present and evaluate a novel EEG-fMRI integration approach combining a spatio-spectral decomposition method and a reliable source localization technique. On the large 72 subjects resting- state hdEEG-fMRI data set we tested the stability of the proposed method in terms of both extracted spatio-spectral patterns(SSPs) as well as their correspondence to the BOLD signal. We also compared the proposed method with the spatio-spectral decomposition in the electrode space as well as well-known occipital alpha correlate in terms of the explained variance of BOLD signal. We showed that the proposed method is stable in terms of extracted patterns and where they correlate with the BOLD signal. Furthermore, we show that the proposed method explains a very similar level of the BOLD signal with the other methods and that the BOLD signal in areas of typical BOLD functional networks is explained significantly more than by a chance. Nevertheless, we didn’t observe a significant relation between our source-space SSPs and the BOLD ICs when spatio-temporally comparing them. Finally, we report several the most stable source space EEG-fMRI patterns together with their interpretation and comparison to the electrode space patterns.
Keywords:
EEG-fMRI Integration; EEG-informed fMRI; Spatio-spectral Decomposition; Electrical Source Imaging; Independent Component Analysis; Resting State Networks
Available in digital repository of the ASCR
Spatio-Spectral EEG Patterns in the Source-Reconstructed Space and Relation to Resting-State Networks: An EEG-fMRI Study
In this work, we present and evaluate a novel EEG-fMRI integration approach combining a spatio-spectral decomposition method and a reliable source localization technique. On the large 72 subjects ...
Diffusion Kalman filtering under unknown process and measurement noise covariance matrices
Vlk, T.; Dedecius, Kamil
2022 - English
The state-of-the-art algorithms for Kalman filtering in agent networks with information diffusion impose the requirement of well-defined state-space models. In particular, they assume that both the process and measurement noise covariance matrices are known and properly set. This is a relatively strong assumption in the signal processing domain. By design, the Kalman filters are rather sensitive to its violation, which may potentially lead to their divergence. In this paper, we propose a novel distributed filtering algorithm with increased robustness under unknown process and measurement noise covariance matrices. It is formulated as a Bayesian variational message passing procedure for simultaneous analytically tractable inference of states and measurement noise covariance matrices.
Keywords:
Collaborative estimation; State estimation; Variational Bayesian methods
Fulltext is available at external website.
Diffusion Kalman filtering under unknown process and measurement noise covariance matrices
The state-of-the-art algorithms for Kalman filtering in agent networks with information diffusion impose the requirement of well-defined state-space models. In particular, they assume that both the ...
Recursive mixture estimation with univariate multimodal Poisson variable
Uglickich, Evženie; Nagy, Ivan
2022 - English
Analysis of count variables described by the Poisson distribution is required in many application fields. Examples of the count variables observed per a time unit can be, e.g., number of customers, passengers, road accidents, Internet traffic packet arrivals, bankruptcies, virus attacks, etc. If the behavior of such a variable exhibits a multimodal character, the problem of clustering and classification of incoming count data arises. This issue can touch, for instance, detecting clusters of the different behavior of drivers in traffic flow analysis as well as cyclists or pedestrians. This work focuses on the model-based clustering of Poisson-distributed count data with the help of the recursive Bayesian estimation of the mixture of Poisson components. The aim of the work is to explain the methodology in details with an illustrative simple example, so that the work is limited to the univariate case and static pointer.
Keywords:
recursive mixture estimation; mixture of Poisson distributions; clustering and classification
Fulltext is available at external website.
Recursive mixture estimation with univariate multimodal Poisson variable
Analysis of count variables described by the Poisson distribution is required in many application fields. Examples of the count variables observed per a time unit can be, e.g., number of customers, ...
Macroeconomic Responses of Emerging Market Economies to Oil Price Shocks: Analysis by Region and Resource Profile
Togonidze, S.; Kočenda, Evžen
2022 - English
This study employs a vector autoregressive (VAR) model to analyse how oil price shocks affect macroeconomic fundamentals in emerging economies. Findings from existing literature remain inconclusive how macroeconomic variables fare towards shocks, especially in emerging economies. The objective of our study is to uncover if analysis by region (Latin America and the Caribbean, East Asia and the Pacific, Europe, and Central Asia) and resource intensity of economies (oil exporters, oil importers, minerals exporters, and less resource intensive). Our unique approach forms part of our contribution to the literature. We find that Latin America and the Caribbean are least affected by oil price shocks, while in East Asia and the Pacific the response of inflation and interest rate to oil price shocks is positive, and output growth is negative. Our analysis by resource endowment fails to show oil price shocks’ ability to explain huge variations in macroeconomic variables in oil importing economies. Further sensitivity analysis using US interest rates as an alternative source of external shocks to emerging economies establishes a significant response of interest rate responses to US interest rate in Europe and Central Asia, and in inflation in Latin America and the Caribbean. We also find that regardless of resource endowment, the response of output growth and capital to a positive US interest rate shock is negative and significant in EMs. Our results are persuasive that resource intensity and regional factors impact the responsiveness of emerging economies to oil price shocks, thus laying a basis for policy debate.\n
Keywords:
Emerging market economies; Oil shocks; GDP; Markov-switching; Exchange rate; Oil exporters; Metal exporters
Fulltext is available at external website.
Macroeconomic Responses of Emerging Market Economies to Oil Price Shocks: Analysis by Region and Resource Profile
This study employs a vector autoregressive (VAR) model to analyse how oil price shocks affect macroeconomic fundamentals in emerging economies. Findings from existing literature remain inconclusive ...
Yield Curve Dynamics and Fiscal Policy Shocks
Kučera, A.; Kočenda, Evžen; Maršál, Aleš
2022 - English
We show that government spending does play a role in shaping the yield curve which has important consequences for the cost of private and government financing. We combine government spending shock identification strategies from the fiscal macro literature with recent advancements in no-arbitrage affine term structure modeling, where we account for time-varying macroeconomic trends in inflation and the equilibrium real interest rate. We stress in our empirical macro-finance framework the importance of timing in the response of yields to government spending. We find that the yield curve responds positively but mildly to a surprise in government spending shocks where the rise in risk-neutral yields is compensated by a drop in nominal term premia. The news shock in expectations about future expenditures decreases yields across all maturities. Complementarily, we also analyze the effect of fiscal policy uncertainty where higher fiscal uncertainty lowers yields.
Keywords:
Government Expenditures; Fiscal policy; U.S. Treasury Yield Curve; Affine Term Structure Model
Fulltext is available at external website.
Yield Curve Dynamics and Fiscal Policy Shocks
We show that government spending does play a role in shaping the yield curve which has important consequences for the cost of private and government financing. We combine government spending shock ...
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