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Cryptocurrency prices have high volatility compared to traditional financial time series. This is the reason why it is hard to predict prices properly using standard models. The aim of this work is to apply the hidden Markov chain model to predict cryptocurrency price direction and to determine regime switching impact to cryptocurrency prices. Various political actions and economic regimes affect cryptocurrency prices. Logarithmic returns used for 2-, 3- ,4- ,5-state hidden Markov model application. It was found that 3-state model is the best to find hidden regimes in cryptocurrency price changes. This model divided cryptocurrency returns according to their volatility into low, medium, and extreme volatility regimes. For the price direction forecast the hidden Markov model was constructed by discretizing the cryptocurrency prices returns into 5 intervals. Based on them, a sequence of observations was formed for 3-year data. The assumption was made that there are two hidden states which represents increasing and decreasing prices. Baum-Welch algorithm was used for learning the model. Then predicted price directions for 3 months data and calculated the accuracy of the model, which was compared with machine learning methods (random forest algorithm, artificial neural network method, and naive Bayesian classifier). In average the prediction made by the hidden Markov model is more accurate than other methods when daily observations are considered.

Cryptocurrency prices have high volatility compared to traditional financial time series. This is the reason why it is hard to predict prices properly using standard models. The aim of this work is to apply the hidden Markov chain model to predict cryptocurrency price direction and to determine regime switching impact to cryptocurrency prices. Various political actions and economic regimes affect cryptocurrency prices. Logarithmic returns used for 2-, 3- ,4- ,5-state hidden Markov model application. It was found that 3-state model is the best to find hidden regimes in cryptocurrency price changes. This model divided cryptocurrency returns according to their volatility into low, medium, and extreme volatility regimes. For the price direction forecast the hidden Markov model was constructed by discretizing the cryptocurrency prices returns into 5 intervals. Based on them, a sequence of observations was formed for 3-year data. The assumption was made that there are two hidden states which represents increasing and decreasing prices. Baum-Welch algorithm was used for learning the model. Then predicted price directions for 3 months data and calculated the accuracy of the model, which was compared with machine learning methods (random forest algorithm, artificial neural network method, and naive Bayesian classifier). In average the prediction made by the hidden Markov model is more accurate than other methods when daily observations are considered.

Cryptocurrency prices have high volatility compared to traditional financial time series. This is the reason why it is hard to predict prices properly using standard models. The aim of this work is to apply the hidden Markov chain model to predict cryptocurrency price direction and to determine regime switching impact to cryptocurrency prices. Various political actions and economic regimes affect cryptocurrency prices. Logarithmic returns used for 2-, 3- ,4- ,5-state hidden Markov model application. It was found that 3-state model is the best to find hidden regimes in cryptocurrency price changes. This model divided cryptocurrency returns according to their volatility into low, medium, and extreme volatility regimes. For the price direction forecast the hidden Markov model was constructed by discretizing the cryptocurrency prices returns into 5 intervals. Based on them, a sequence of observations was formed for 3-year data. The assumption was made that there are two hidden states which represents increasing and decreasing prices. Baum-Welch algorithm was used for learning the model. Then predicted price directions for 3 months data and calculated the accuracy of the model, which was compared with machine learning methods (random forest algorithm, artificial neural network method, and naive Bayesian classifier). In average the prediction made by the hidden Markov model is more accurate than other methods when daily observations are considered.

Cryptocurrency prices have high volatility compared to traditional financial time series. This is the reason why it is hard to predict prices properly using standard models. The aim of this work is to apply the hidden Markov chain model to predict cryptocurrency price direction and to determine regime switching impact to cryptocurrency prices. Various political actions and economic regimes affect cryptocurrency prices. Logarithmic returns used for 2-, 3- ,4- ,5-state hidden Markov model application. It was found that 3-state model is the best to find hidden regimes in cryptocurrency price changes. This model divided cryptocurrency returns according to their volatility into low, medium, and extreme volatility regimes. For the price direction forecast the hidden Markov model was constructed by discretizing the cryptocurrency prices returns into 5 intervals. Based on them, a sequence of observations was formed for 3-year data. The assumption was made that there are two hidden states which represents increasing and decreasing prices. Baum-Welch algorithm was used for learning the model. Then predicted price directions for 3 months data and calculated the accuracy of the model, which was compared with machine learning methods (random forest algorithm, artificial neural network method, and naive Bayesian classifier). In average the prediction made by the hidden Markov model is more accurate than other methods when daily observations are considered.

The a rticle d iscusses conceptualisation of populism, Lithuania's party system a nd electoral dynamics and their relation to the sustainability of populist parties. Special attention is given to Party Order and Justice, a former populist and protest party, and its leadership, namely to the issues related to scope and competencies of a leader's intra-partisan power, leadership selection rules and history, development of leaders' political careers and their electoral activity. Th e L ithuanian party system now exhibits moderate fragmentation without centrifugal tendencies. Voter volatility is still relatively high, yet the share of new parties has dropped to zero. Th e protest and populist parties in Lithuania went into the margins of political establishment. Popularity of the Order and Justice party has long been connected to the formerly impeached president Rolandas Paksas. His long-term leadership in the face of plummeting electoral support and an emphasis on his political martyrdom resulted in poor electoral performances, ensuing internal squabbles and his departure. Party Order and Justice's internal regulations, however, remained favourable to strong leadership.

The a rticle d iscusses conceptualisation of populism, Lithuania's party system a nd electoral dynamics and their relation to the sustainability of populist parties. Special attention is given to Party Order and Justice, a former populist and protest party, and its leadership, namely to the issues related to scope and competencies of a leader's intra-partisan power, leadership selection rules and history, development of leaders' political careers and their electoral activity. Th e L ithuanian party system now exhibits moderate fragmentation without centrifugal tendencies. Voter volatility is still relatively high, yet the share of new parties has dropped to zero. Th e protest and populist parties in Lithuania went into the margins of political establishment. Popularity of the Order and Justice party has long been connected to the formerly impeached president Rolandas Paksas. His long-term leadership in the face of plummeting electoral support and an emphasis on his political martyrdom resulted in poor electoral performances, ensuing internal squabbles and his departure. Party Order and Justice's internal regulations, however, remained favourable to strong leadership.

The a rticle d iscusses conceptualisation of populism, Lithuania's party system a nd electoral dynamics and their relation to the sustainability of populist parties. Special attention is given to Party Order and Justice, a former populist and protest party, and its leadership, namely to the issues related to scope and competencies of a leader's intra-partisan power, leadership selection rules and history, development of leaders' political careers and their electoral activity. Th e L ithuanian party system now exhibits moderate fragmentation without centrifugal tendencies. Voter volatility is still relatively high, yet the share of new parties has dropped to zero. Th e protest and populist parties in Lithuania went into the margins of political establishment. Popularity of the Order and Justice party has long been connected to the formerly impeached president Rolandas Paksas. His long-term leadership in the face of plummeting electoral support and an emphasis on his political martyrdom resulted in poor electoral performances, ensuing internal squabbles and his departure. Party Order and Justice's internal regulations, however, remained favourable to strong leadership.

The a rticle d iscusses conceptualisation of populism, Lithuania's party system a nd electoral dynamics and their relation to the sustainability of populist parties. Special attention is given to Party Order and Justice, a former populist and protest party, and its leadership, namely to the issues related to scope and competencies of a leader's intra-partisan power, leadership selection rules and history, development of leaders' political careers and their electoral activity. Th e L ithuanian party system now exhibits moderate fragmentation without centrifugal tendencies. Voter volatility is still relatively high, yet the share of new parties has dropped to zero. Th e protest and populist parties in Lithuania went into the margins of political establishment. Popularity of the Order and Justice party has long been connected to the formerly impeached president Rolandas Paksas. His long-term leadership in the face of plummeting electoral support and an emphasis on his political martyrdom resulted in poor electoral performances, ensuing internal squabbles and his departure. Party Order and Justice's internal regulations, however, remained favourable to strong leadership.

The a rticle d iscusses conceptualisation of populism, Lithuania's party system a nd electoral dynamics and their relation to the sustainability of populist parties. Special attention is given to Party Order and Justice, a former populist and protest party, and its leadership, namely to the issues related to scope and competencies of a leader's intra-partisan power, leadership selection rules and history, development of leaders' political careers and their electoral activity. Th e L ithuanian party system now exhibits moderate fragmentation without centrifugal tendencies. Voter volatility is still relatively high, yet the share of new parties has dropped to zero. Th e protest and populist parties in Lithuania went into the margins of political establishment. Popularity of the Order and Justice party has long been connected to the formerly impeached president Rolandas Paksas. His long-term leadership in the face of plummeting electoral support and an emphasis on his political martyrdom resulted in poor electoral performances, ensuing internal squabbles and his departure. Party Order and Justice's internal regulations, however, remained favourable to strong leadership.

In the 2000's excessive credit and asset price growth led to a global economic boom that was later followed by the biggest financial crisis since the Great Depression. The prelude and nature of the Global Financial Crisis revealed that banking sector can amplify economic cycles, and that banking regulation had been too micro-oriented. In response to this, a new type of policy emerged, which aims to mitigate systemic risk and increase the resilience of the financial industry and real economy. Macroprudential policy is in place in Lithuania for more than a decade, yet it is not well understood, as there are only a few academic studies on the topic. The aim of this dissertation is to assess the impact of macroprudential policy on the economy of Lithuania by building general equilibrium models. The developed models in the dissertation reveal that the tightening of policy measures may slightly increase interest rates and decrease lending, however, the impact on the general economy is quite small. Although the tightening of policy measures that are aimed to reduce indebtedness may decrease the speed of economic convergence in the long run, macroprudential policy should also reduce the volatility of Lithuania's economy.

Minority government in Lithuania is established for the fist time in the independent Lithuanian history. The research was cared out on the basis of the minority government formation, stability and efficiency variables. In this work were analysed factors, which influence formation, stability and efficiency of minority government in Lithuania. First chapter ("government formation, stability and efficiency concept") dealt with the theoretical notions about government forms, minority government formation factors, ideas about stability and efficiency. In the second chapter ("minority government formation process in Lithuania: factors influence") were analysed positive parliamentarism, parliamentary fragmentation, presidential powers and polarisation of party system. Third chapter ("minority government termination and stability") explored variables that are crucial for this government stability. First of all, in this chapter the termination of the 14 th Lithuanian government was analysed and then was made research of stability. This research was made with three main variables – party system fragmentation, polarisation (out - parties included), prime ministers forces to influence government stability and voters volatility with the variable of out - party strategy. Fourth chapter ("analysis of minority government efficiency") address factors that have influence to efficiency. Such factors are – productivity of minority government, party coherence and discipline, coalition coherence and discipline, budgetary and taxation policy.

Minority government in Lithuania is established for the fist time in the independent Lithuanian history. The research was cared out on the basis of the minority government formation, stability and efficiency variables. In this work were analysed factors, which influence formation, stability and efficiency of minority government in Lithuania. First chapter ("government formation, stability and efficiency concept") dealt with the theoretical notions about government forms, minority government formation factors, ideas about stability and efficiency. In the second chapter ("minority government formation process in Lithuania: factors influence") were analysed positive parliamentarism, parliamentary fragmentation, presidential powers and polarisation of party system. Third chapter ("minority government termination and stability") explored variables that are crucial for this government stability. First of all, in this chapter the termination of the 14 th Lithuanian government was analysed and then was made research of stability. This research was made with three main variables – party system fragmentation, polarisation (out - parties included), prime ministers forces to influence government stability and voters volatility with the variable of out - party strategy. Fourth chapter ("analysis of minority government efficiency") address factors that have influence to efficiency. Such factors are – productivity of minority government, party coherence and discipline, coalition coherence and discipline, budgetary and taxation policy.

In 2008, a global financial crisis happened. It led to strong currency price volatility. Because of that, discussions on the need for an alternative, institution-independent currency occurred. Due to this reason the first decentralized cryptocurrency Bitcoin was created. The new and not yet explored concept of cryptocurrency changed the previously strictly defined role of money. Currently, with the growth of the cryptocurrency market, the most important regional institutions (e.g. FED, EBA) provide regulatory guidelines of a recommendatory nature. The regulations of these institutions remain significant, reflecting the dominant approach to digital money. Because of this reason, the aim of the study is to identify the factors that determine the difficulties in the legalization process of cryptocurrencies and to investigate the features of the European Union's cryptocurrency regulatory policy. Methods used: analysis of scientific literature and legal documents, systematization, comparison, interpretation and generalization of information. The results of the study show that the European Union has taken active regulatory action with the growing importance of cryptocurrencies in the world. To date, a document regulating the definition of cryptocurrencies has not yet been adopted at Union level, but the adoption of the cryptocurrency regulation proposal presented in 2020 would mean greater clarity and security for cryptocurrency issuers, intermediaries and users.

In 2008, a global financial crisis happened. It led to strong currency price volatility. Because of that, discussions on the need for an alternative, institution-independent currency occurred. Due to this reason the first decentralized cryptocurrency Bitcoin was created. The new and not yet explored concept of cryptocurrency changed the previously strictly defined role of money. Currently, with the growth of the cryptocurrency market, the most important regional institutions (e.g. FED, EBA) provide regulatory guidelines of a recommendatory nature. The regulations of these institutions remain significant, reflecting the dominant approach to digital money. Because of this reason, the aim of the study is to identify the factors that determine the difficulties in the legalization process of cryptocurrencies and to investigate the features of the European Union's cryptocurrency regulatory policy. Methods used: analysis of scientific literature and legal documents, systematization, comparison, interpretation and generalization of information. The results of the study show that the European Union has taken active regulatory action with the growing importance of cryptocurrencies in the world. To date, a document regulating the definition of cryptocurrencies has not yet been adopted at Union level, but the adoption of the cryptocurrency regulation proposal presented in 2020 would mean greater clarity and security for cryptocurrency issuers, intermediaries and users.

In 2008, a global financial crisis happened. It led to strong currency price volatility. Because of that, discussions on the need for an alternative, institution-independent currency occurred. Due to this reason the first decentralized cryptocurrency Bitcoin was created. The new and not yet explored concept of cryptocurrency changed the previously strictly defined role of money. Currently, with the growth of the cryptocurrency market, the most important regional institutions (e.g. FED, EBA) provide regulatory guidelines of a recommendatory nature. The regulations of these institutions remain significant, reflecting the dominant approach to digital money. Because of this reason, the aim of the study is to identify the factors that determine the difficulties in the legalization process of cryptocurrencies and to investigate the features of the European Union's cryptocurrency regulatory policy. Methods used: analysis of scientific literature and legal documents, systematization, comparison, interpretation and generalization of information. The results of the study show that the European Union has taken active regulatory action with the growing importance of cryptocurrencies in the world. To date, a document regulating the definition of cryptocurrencies has not yet been adopted at Union level, but the adoption of the cryptocurrency regulation proposal presented in 2020 would mean greater clarity and security for cryptocurrency issuers, intermediaries and users.