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Good vs. Bad Volatility in Major Cryptocurrencies: The Dichotomy and Drivers of Connectedness
Šíla, Jan; Kočenda, Evžen; Kukačka, Jiří; Krištoufek, Ladislav
2023 - anglický
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.
Klíčová slova:
Volatility; Dynamic connectedness; Asymmetric effects; Cryptocurrency
Dokument je dostupný na externích webových stránkách.
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 - anglický
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.
Klíčová slova:
Financial Inclusion; Financial Inclusion Index; Sub-Saharan Africa
Dokument je dostupný na externích webových stránkách.
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 ...
On a stepladder model walking (with and without a decorator)
Polach, P.; Prokýšek, R.; Papáček, Štěpán
2023 - anglický
This work is related to our previous studies on underactuated biped robot models and has been motivated by the need to implement the previously developed sensor and control algorithms for the real-time movement of the laboratory walking robot, designed and built at the Department of Control Theory of the Institute of Information Theory and Automation of the Czech Academy of Sciences [1, 6, 7]. Underactuated biped robots with an upper body form a subclass of legged robots, see, e.g., [4] for a review on the control of underactuated mechanical systems and [2] for a study of an asymptotically stable walking for biped robots. It is obvious that in general, the walking control of underactuated walking robots is a more challenging problem than walking control of fully actuated walking robots. As follows, we examine the well-known mechanical system of the stepladder model with and without a decorator, whose role is substituted by an external inertial force according to the D’Alembert principle. It is well known, that stepladder walking is possible due to the periodic movement (pendulating) of an operator – decorator1 The rigorous dynamical analysis of stable cyclic walking of a class of stepladder models is presented in the next section.
Klíčová slova:
Underactuated biped robot models; Control algorithms; Legged robots
Dokument je dostupný na externích webových stránkách.
On a stepladder model walking (with and without a decorator)
This work is related to our previous studies on underactuated biped robot models and has been motivated by the need to implement the previously developed sensor and control algorithms for the ...
Average Reward Optimality in Semi-Markov Decision Processes with Costly Interventions
Sladký, Karel
2023 - anglický
In this note we consider semi-Markov reward decision processes evolving on finite state spaces. We focus attention on average reward models, i.e. we establish explicit formulas for the growth rate of the total expected reward. In contrast to the standard models we assume that the decision maker can also change the running process by some (costly) intervention. Recall that the result for optimality criteria for the classical Markov decision chains in discrete and continuous time setting turn out to be a very specific case of the considered model. The aim is to formulate optimality conditions for semi-Markov models with interventions and present algorithmical procedures for finding optimal solutions.
Klíčová slova:
controlled semi-Markov reward processes; long-run optimality; intervention of the decision maker
Dokument je dostupný na externích webových stránkách.
Average Reward Optimality in Semi-Markov Decision Processes with Costly Interventions
In this note we consider semi-Markov reward decision processes evolving on finite state spaces. We focus attention on average reward models, i.e. we establish explicit formulas for the growth rate of ...
Modeling the spread of loanwords in South-East Asia using sailing navigation software and Bayesian networks
Kratochvíl, F.; Kratochvíl, Václav; Saad, G.; Vomlel, Jiří
2022 - anglický
A loanword is a word permanently adopted from one language and incorporated into another language without translation. In this paper, we study loanwords in the South-East Asia Archipelago, home to a large number of languages. Our paper is inspired by the works of Hoffmann et al. (2021) Bayesian methods are applied to probabilistic modeling of family trees representing the history of language families and by Haynie et al. (2014) modeling the diffusion of a special class of loanwords, so-called Wanderw ̈orter in languages of Australia, North America, and South America. We assume that in the South-East Asia Archipelago Wanderwörter spread along specific maritime trade routes whose geographical characteristics can help unravel the history of Wanderwörter diffusion in the area. For millennia trade was conducted using sailing ships which were constrained by the monsoon system and in certain areas also by strong sea currents. Therefore rather than the geographical distances, the travel times of sailing ships should be considered as a major factor determining the intensity of contact among cultures. We use sailing navigation software to estimate travel times between different ports and show that the estimated travel times correspond well to the travel times of a Chinese map of the sea trade routes from the early seventeenth century. We model the spread of loanwords using a probabilistic graphical model - a Bayesian network. We design a novel heuristic Bayesian network structure learning algorithm that learns the structure as a union of spanning trees for graphs of all loanwords in the training dataset. We compare this algorithm with BIC optimal Bayesian networks by measuring how well these models predict the true presence/absence of a loanword. Interestingly, Bayesian networks learned by our heuristic spanning tree-based algorithm provide better results than the BIC optimal Bayesian networks.
Klíčová slova:
loanwords; Bayesian methods; probabilistic graphical model
Dokument je dostupný na externích webových stránkách.
Modeling the spread of loanwords in South-East Asia using sailing navigation software and Bayesian networks
A loanword is a word permanently adopted from one language and incorporated into another language without translation. In this paper, we study loanwords in the South-East Asia Archipelago, home to a ...
A Bootstrap Comparison of Robust Regression Estimators
Kalina, Jan; Janáček, Patrik
2022 - anglický
The ordinary least squares estimator in linear regression is well known to be highly vulnerable to the presence of outliers in the data and available robust statistical estimators represent more preferable alternatives.
Klíčová slova:
linear regression; robust estimation; nonparametric bootstrap; bootstrap hypothesis testing
Dokument je dostupný na externích webových stránkách.
A Bootstrap Comparison of Robust Regression Estimators
The ordinary least squares estimator in linear regression is well known to be highly vulnerable to the presence of outliers in the data and available robust statistical estimators represent more ...
Diffusion Kalman filtering under unknown process and measurement noise covariance matrices
Vlk, T.; Dedecius, Kamil
2022 - anglický
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.
Klíčová slova:
Collaborative estimation; State estimation; Variational Bayesian methods
Dokument je dostupný na externích webových stránkách.
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 ...
Two Composition Operators for Belief Functions Revisited
Jiroušek, Radim; Kratochvíl, Václav; Shenoy, P. P.
2022 - anglický
In probability theory, compositional models are as powerful as Bayesian networks. However, the relation between belief-function graphical models and the corresponding compositional models is much more complicated due to several reasons. One of them is that there are two composition operators for belief functions. This paper deals with their main properties and presents sufficient conditions under which they yield the same results.
Klíčová slova:
probability theory; Bayesian networks; belief functions
Dokument je dostupný na externích webových stránkách.
Two Composition Operators for Belief Functions Revisited
In probability theory, compositional models are as powerful as Bayesian networks. However, the relation between belief-function graphical models and the corresponding compositional models is much more ...
Modeling COVID Pandemics: Strengths and Weaknesses of Epidemic Models
Šmíd, Martin
2022 - anglický
We generally discuss modeling the present COVID pandemics. We argue that useful models have to be simple in the first case, yet their uncertainty has to be handled properly. In order to study circumstances of the upcoming wave of infection,\nwe construct a simple stochastic model and present predictions it gives. We conclude that the autumn wave is most likely unavoidable and suggest concentrating to mitigation.
Klíčová slova:
COVID; Epidemic Models; stochastic model
Dokument je dostupný na externích webových stránkách.
Modeling COVID Pandemics: Strengths and Weaknesses of Epidemic Models
We generally discuss modeling the present COVID pandemics. We argue that useful models have to be simple in the first case, yet their uncertainty has to be handled properly. In order to study ...
Analysis of Impact of Covariates Entering Stochastic Optimization Problem
Volf, Petr
2022 - anglický
In the contribution we study consequences of imperfect information to precision of stochastic optimization solution. In particular, it is assumed that the characteristics of optimization problem are influenced by a set of covariates. This dependence is described via a regression model. Hence, the uncertainty is then caused by statistical estimation of regression parameters. The contribution will analyze several regression model cases, together with their application. Precision of results will be explored, both theoretically as well as with the aid of simulations.
Klíčová slova:
stochastic optimization; regression model; statistical estimation
Dokument je dostupný na externích webových stránkách.
Analysis of Impact of Covariates Entering Stochastic Optimization Problem
In the contribution we study consequences of imperfect information to precision of stochastic optimization solution. In particular, it is assumed that the characteristics of optimization problem are ...
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