921 resultados para inter-bank interest rate


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Includes bibliography

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This paper attempts to explain why the Brazilian inter-bank interest rate is so high compared with rates practiced by other emerging economies. The interplay between the markets for bank reserves and government securities feeds into the inter-bank rate the risk premium of the Brazilian public debt.

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This paper attempts to explain why the Brazilian inter-bank interest rate is so high compared with rates practiced by other emerging economies. The interplay between the markets for bank reserves and government securities feeds into the inter-bank rate the risk premium of the Brazilian public debt.

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Die Vielfalt von möglichen wirtschaftlichen Konsequenzen von Banksolvenzproblemen trägt auch dazu bei, dass wissenschaftliche Fragen über die Eigenkapitalregulierung im Bankensektor schon seit einigen Jahren ziemlich intensiv diskutiert werden. Die Effekte von Eigenkapitalregulierung können sich auf zahlreiche Weise zeigen, zum Beispiel ist ein Effekt auf das Kreditzinsniveau auch nicht auszuschließen. Um diesen potenziellen Zusammenhang, an den die frühere Literatur noch nicht fokussierte, klarer analysieren zu können, wird in der vorliegenden Studie ein theoretisches Modell präsentiert, in der eine Verbindung zwischen einem optimalen Bankkreditzinsniveau und der Eigenkapitalregulierung existiert. Die Optimalität von Kreditzinsniveaus wird aus zwei Aspekten betrachtet: als Optimalitätskriterien werden Gewinnmaximierung und Maximierung von Solvenzwahrscheinlichkeit verglichen. Aufgrund der Ergebnisse kann darauf geschlossen werden, dass diese zwei optimale Kreditzinsniveaus nicht identisch sind und unterschiedlich von Eigenkapitalregulierung beeinflusst werden. Nach theoretischen Ergebnissen ist es möglich, dass im Falle einer Erhöhung des Eigenkapitals bei gleichbleibenden Bankeinlagen das gewinnmaximierende Optimum sich nicht ändert, während das zu der Maximierung der Solvenzwahrscheinlichkeit gehörende Optimum sich verringert.

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Interest rate risk is one of the major financial risks faced by banks due to the very nature of the banking business. The most common approach in the literature has been to estimate the impact of interest rate risk on banks using a simple linear regression model. However, the relationship between interest rate changes and bank stock returns does not need to be exclusively linear. This article provides a comprehensive analysis of the interest rate exposure of the Spanish banking industry employing both parametric and non parametric estimation methods. Its main contribution is to use, for the first time in the context of banks’ interest rate risk, a nonparametric regression technique that avoids the assumption of a specific functional form. One the one hand, it is found that the Spanish banking sector exhibits a remarkable degree of interest rate exposure, although the impact of interest rate changes on bank stock returns has significantly declined following the introduction of the euro. Further, a pattern of positive exposure emerges during the post-euro period. On the other hand, the results corresponding to the nonparametric model support the expansion of the conventional linear model in an attempt to gain a greater insight into the actual degree of exposure.

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The purpose of this work is to verify the stability of the relationship between real activity and interest rate spread. The test is based on Chen (1988) and Osorio and Galea (2006). The analysis is applied to Chile and the United States, from 1980 to 1999. In general, in both cases the relationship was statistically significant in early 80s, but a break point is found in both countries during that decades, suggesting that the relationship depends on the monetary rule follow by the Central Bank.

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This paper studies monetary policy transmission using several statistical tools -- We find that the relationships between the policy interest rate and the financial system’s interest rates are positive and statistically significant, and transmission is complete eight months after policy shocks occur -- The speed of transmission varies according to the type of interest rates -- Transmission is faster for interest rates on loans provided to households, and is particularly rapid and complete for rates on preferential commercial loans -- Transmission is slower for credit card and mortgage rates, due to regulatory issues (interest rate ceilings)

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This article makes a connection between Lucas` (1978) asset pricing model and the macroeconomic dynamics for some selected countries. Both the relative risk aversion and the impatience for postponing consumption by synthesizing the investor behaviour can help to understand some key macroeconomic issues across countries, such as the savings decision and the real interest rate. I find that the government consumption makes worse the so-called `equity premium-interest rate puzzle`. The first root of the quadratic function for explaining the real interest rate can produce this puzzle, but not the second root. Thus, Mehra and Prescott (1985) identified only one possible solution.

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This paper investigates the robustness of a range of short–term interest rate models. We examine the robustness of these models over different data sets, time periods, sampling frequencies, and estimation techniques. We examine a range of popular one–factor models that allow the conditional mean (drift) and conditional variance (diffusion) to be functions of the current short rate. We find that parameter estimates are highly sensitive to all of these factors in the eight countries that we examine. Since parameter estimates are not robust, these models should be used with caution in practice.

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Financial literature and financial industry use often zero coupon yield curves as input for testing hypotheses, pricing assets or managing risk. They assume this provided data as accurate. We analyse implications of the methodology and of the sample selection criteria used to estimate the zero coupon bond yield term structure on the resulting volatility of spot rates with different maturities. We obtain the volatility term structure using historical volatilities and Egarch volatilities. As input for these volatilities we consider our own spot rates estimation from GovPX bond data and three popular interest rates data sets: from the Federal Reserve Board, from the US Department of the Treasury (H15), and from Bloomberg. We find strong evidence that the resulting zero coupon bond yield volatility estimates as well as the correlation coefficients among spot and forward rates depend significantly on the data set. We observe relevant differences in economic terms when volatilities are used to price derivatives.