In the study we investigate the effectiveness of the National Bank of Poland in counteracting the negative results of the financial crisis in the Polish interbank market. The situation was exceptional in a sense, that during the period of the financial crisis the Polish interbank market experienced liquidity surplus, and the main problem of the central bank was to regain confidence among commercial banks and stimulate interbank transactions. We concentrate on the spread between the rate of overnight interbank loans and the reference rate and based upon its dynamics we assess the monetary policy of the Polish central bank. Using econometric techniques we study how the central bank influenced the spread, when its control over it weakened and when was it strengthened. The study is supported by the results of the survey directed to the headquarters of commercial banks. We conclude that the ability of the central bank to control overnight rate wasThe views in this paper should be regarded as those of the author, and do not necessarily reflect those of the National Bank of Poland. temporarily lost during the first phases of the financial crisis, but gradually regained after implementation of the confidence pact.The aim of the research was to assess the ability of the Polish central bank to control the rate of overnight loans in the Polish interbank market and conduct its monetary policy during the confidence crisis, as well as facing the liquidity surplus. The Polish interbank market is special in a sense that liquidity surplus has been present there even since 1994 (National Bank of Poland 2009). However, together with the outbreak of the financial crisis, the confidence in the Polish interbank market declined drastically. Commercial banks preferred to accumulate liquidity surplus and performed almost no interbank transactions of maturity longer than 7 days. Banks preferred to keep their surplus on their current accounts with the central bank or in the form of deposit facility, and they significantly limited participation in the 7-day open market operations conducted by the National Bank of Poland (NBP) (National Bank of Poland 2009). The latter resulted in the so called underbidding (i.e. the situation during the tenders for the NBP bills, when the banks' total bid is lower than the supply offered by the central bank). As a consequence, the effectiveness of the central bank in stabilization of the market rates, what is one of the main goals of the monetary policy, diminished significantly.Our goal was to assess the effectiveness of the monetary policy of the Polish central bank, using econometric methods, as well as with respect to the results of the survey, sent to the head-quarters of the Polish commercial banks. The problem of assessing the effectiveness of the stabilization policy of central banks using econometric methods is also rather new in literature. Panigirtzoglou et al. (2000) studied the effectiveness of controlling the interbank rates through the key interest rates of the central banks of Grea...
Streszczenie: Spread pomiędzy stopą procentową LIBOR a stałą stopą kontraktu OIS o tym samym czasie zapadalności jest miernikiem kondycji sektora bankowego. W cyklicznych raportach o stabilności systemu finansowego w analogiczny sposób wykorzystuje się spread pomiędzy stopą WIBOR 3M a kontraktem OIS. Parametryczne modele z przełączaniem typu Markowa umożliwiły dokonanie identyfikacji reżimów, z których jeden można utożsamiać z dobrą kondycją sektora bankowego, a drugi z kondycją osłabioną z racji kryzysu hipotecznego oraz kryzysu zadłużeniowego w państwach Europy Południowej. Dzięki temu można zidentyfikować momenty, w których skutki kryzysu stały się odczuwalne w polskim sektorze bankowym. Modele z przełączaniem typu Markowa pozwolą także na dokładny opis zmienności warunkowej spreadu, którą można interpretować jako miarę niepewności co do przyszłego ukształtowania się sytuacji w sektorze bankowym w Polsce.
Subprime crisis which started in the USA in 2007 was the cause of the most significant economic disturbances since the Great Depression in 1930s. Soon it transmitted to other countries, including those in which banks were not engaged in the subprime mortgage market. The crisis hit various sectors of national economies and led to changing of the trends on the stock markets, which are connected to American capital market. In the following article we researched the influence of the American market on the other markets in the context of the financial crisis. Our analysis is based on the results obtained from the multivariate parametric models. Seeing that the data space is high-dimensional, we used GO-GARCH models introduced by van der Weide (2005) and Boswijk and van der Weide (2006).
Due to the traditional operational model of cooperative banks which is mostly based on financial intermediation, the range of a local bank’s social influence in a given environment is highly dependent on the money transfer balance, that is using local money to satisfy local needs. A typical obstacle to this activity could be observed in Poland, in positive money transfers in those banks understood as the excess of deposits from customers over loans given to them. The purpose of the following paper is to examine this phenomenon in Polish cooperative banks in comparison to credit cooperatives in Europe together with its explanation on the basis of the selected group of cooperative banks in Poland. According to the sector data in the years 2004-2015 Polish cooperative banks are net lenders for the remaining entities of the financial sector. On the European market, on the other hand, groups of cooperative banks aim to balance money transfers. It is the activity of the biggest sector players that mostly influences the information concerning credit cooperatives, which is why more thorough research into the group of over 90 Polish cooperative banks was conducted in the years 2009-2016. In the examined group deposits exceed loans and the phenomenon continues to grow and it has been observed in over three quarters of the institutions in question since 2011.
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