Financial cycle − A critical analysis of the methodology for its identification

While the legitimacy of the concept of the financial cycle (as distinct from the business cycle) in research and economic policy after the experience of the global financial crisis raises no concerns, the methodology for its application has become a subject of discussion. The purpose of this article is to indicate which research methods dominate in identifying a financial cycle and which methodological traps accompany them. The low level of critical perspective on the methods used to identify cycles often results in conclusions that have no economic justification and may result in erroneous decisions in economic policy and central bank practice. The case study carried out in the article confirms that the key elements in identifying a financial cycle are part of a long-term series covering at least two lengths of the financial cycle. In addition, because the results may be sensitive to the type of filter used, it is important not to rely on a single variable but rather to build indexes that take into account a number of them (including those obtained using filtration methods).

Measuring Sovereign Credit Risk of the EU countries

European countries have increased significantly their public debt since the Global Financial Crisis. The increasing trend and the high concentration of public debt in portfolios of financial institutions can lead to a financial turmoil we witnessed during the European Sovereign Debt Crisis. Financial stability authorities therefore look for models to measure the sovereign credit risk and develop“what-if”scenarios to assess a potential repercussion of a financial institution rescue or of an economic contraction on sovereign credit risk. The presented article introduces adjustments to the sovereign contingent claims analysis that is based on the Merton´s Credit Risk Model and the Black-Scholes option pricing techniques. The article proposes adjustments by introducing a new view on a stylised liability side of a central government balance sheet, seniority of its items, and a new proxy for risk measure of junior claims. We show reliable results using derived risk sensitivities for 20 EU countries with decent forward looking ability and propose potential stress-testing framework with an application for the Czech Republic.

The Evaluation of Block Chain Technology within the Scope of Ripple and Banking Activities

Technological developments have always led to changes in all aspects of our lives. Crypto currency is one of those changes. As a result of those changes, thousands of currencies such as bitcoin, ripple, litecoin and ethereum have evolved and have found a use in business. The present study focuses upon Ripple and tries to explain its effects on banks and business theoretically. It has been stated that the money transfer performed through Ripple is faster and more economical when compared to present systems. Additionally, it has been realised that the present SWIFT system has been influenced by that speed and economy, and therefore taken considerable technologic steps with an effort to improve its system.

Output Losses from Currency Crises and the Role of Central Bank

Generally, one of the important issues related to currency crises is the output losses caused by these phenomena. In this study, determinants of output losses and particularly the role of the central bank will be evaluated during currency crises. Moreover, the paper tries to investigate the roles of macroeconomic variables and also monetary, fiscal and exchange rate policies on the output losses during currency crises. In this regard, an econometric model with panel data has been used for emerging market countries during 1980-2016. The results show that currency crises accruing have a positive and significant effect on output losses. While the successful defence of central bank has had the negative effects on the output losses, but it is positive for the unsuccessful defence and the non-intervention or immediate depreciation. However, the role of the macroeconomic condition is important where total foreign reserves can be considered as a buffer against the output losses, while inflation and deviation of the real exchange rate from its trend have had positive effects on the output losses. Finally, the output losses can be reduced by an active monetary, fiscal and exchange rate policies.

How Does International Financial Integration Really Affect Post-Transition Countries' Growth? Empirical evidence from the CEE-10 countries

This paper seeks to empirically explore how an international financial integration influences a country’s GDP growth. The long run relationship is tested by PMG estimator for the sample of ten EU countries from Central, Eastern and Southeastern Europe (CEE-10 countries) between 1995 and 2017. Prior to the conducting of dynamic panel analysis based on PMG estimators, several panel unit root tests were conducted, as well as panel co integration tests. The findings offer mixed impact financial integration on growth. Among the measures of financial integration, growth of the CEE-10 countries is mostly driven in the long run by FDI inflows as well as remittances and financial openness. On the contrary, the study suggests a reversal relationship between growth and financial integration measured by Gross Foreign Assets and Liabilities in percentages of GDP. It might be explained with a fact that CEE-10 countries have not yet reached a certain level of financial development in order to benefit from financial integration. The study concludes that international financial integration does not per se enhance economic growth and country’s growth in the CEE-10 countries can be reached at a higher level of financial integration, further increase their financial openness and financial development.

Great Power, Great Responsibility: Addressing the Underestimated Issue of Central Bank’s Social Responsibility

This paper deals with the neglected issue of central banks’ social responsibility. Since central banks exert the “structural power” on economies as well as on societies, their power should be regulated and controlled by society through a reliable framework of social responsibility. To that aim, this article sheds light on the ‘why’ and the ‘how’ of central bank’s social responsibility: I suggest reforms in order to increase central banks’ social legitimacy, while being consistent with the mapping out of a new framework of social responsibility.

Nominal, Structural and Real Convergence of the EU Candidate Countries’ Economies

Despite the significant academic interest in the economic cohesion, the various aspects of convergence and the ways they can be measured still remain theoretically unclear. These are issues of extreme political significance, especially for countries aspiring for EU and euro area membership. The goal of this paper is to consolidate a variety of theoretical views on the convergence and its measurement and use it as the basis to assess the progress and the current state of economic convergence to the EU of the four candidate countries. The interrelation between the three forms of convergence in the different phases of the economic cycle is studied and the slobs in the ways the convergence is measured are outlined. The study reveals large differences between the candidate countries in achieving convergence with the EU. Their experiences do not confirm the positive relationship between nominal and real convergence. The structural convergence considered as convergence of sectoral structure has but little impact on the real convergence.

The impact of a political shock on foreign exchange markets in a small and open economy: A dynamic modelling approach

This paper aims to analyse the dynamics of foreign exchange markets in a country facing political uncertainty that prompt capital outflow from the country1. The economic environment under investigation is characterized by dual foreign exchange markets: a formal or official market for foreign exchange with insufficient and volatile foreign exchange flows, and a strong and thriving informal market, with a higher exchange rate2. The findings in the paper indicate a necessary condition for stabilization of the exchange rate system and that is that the return on investment should exceed the depreciation rate of domestic currency in the formal foreign exchange market. This condition implies that the return on investment should at least compensate investors for the opportunity cost of holding domestic money in their private portfolio wealth. Our findings also indicate that stability of the foreign exchange rates is more difficult to achieve under insufficient official reserves as the recovery process from a shock becomes more costly in terms of time period needed for the adjustment process to complete. The dynamic path of the foreign exchange premium shows that under massive capital outflow caused by economic sanctions, the informal market exchange rate overshoots the equilibrium stationary exchange rate, and the size of such overshooting depends on the size of available foreign exchange reserves held by the central bank.

Prospects of Artificial Intelligence and Machine Learning Application in Banking Risk Management

Artificial intelligence and machine learning have increasing influence on the financial sector, but also on economy as a whole. The impact of artificial intelligence and machine learning on banking risk management has become particularly interesting after the global financial crisis. The research focus is on artificial intelligence and machine learning potential for further banking risk management improvement. The paper seeks to explore the possibility for successful implementation yet taking into account challenges and problems which might occur as well as potential solutions. Artificial intelligence and machine learning have potential to support the mitigation measures for the contemporary global economic and financial challenges, including those caused by the COVID-19 crisis. The main focus in this paper is on credit risk management, but also on analysing artificial intelligence and machine learning application in other risk management areas. It is concluded that a measured and well-prepared further application of artificial intelligence, machine learning, deep learning and big data analytics can have further positive impact, especially on the following risk management areas: credit, market, liquidity, operational risk, and other related areas.

Non-Performing Loan Determinants and Impact of COVID-19: Case of Bosnia and Herzegovina

The aim of this paper is to investigate the determinants of the movement of non-performing loans in the banking sector of Bosnia and Herzegovina, as well as the impact of the COVID-19 pandemic on them. For this purpose, secondary data from the banking sector of BiH were used, over which a multi-regression analysis was performed. The variables non-performing loans, GDP, loan loss provision, and dummy variable COVID-19 were used in the analysis. The results of the analysis showed a significant influence of all three mentioned variables. The existence of a significant positive link between non-performing loans and the state of the country's economy has been proven. In addition to the above, it has been proven that the variable COVID-19 has a delayed effect on NPLs, due to the current application of the moratorium on loans.