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Elizaveta Krylova

3 June 2016
WORKING PAPER SERIES - No. 1912
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Abstract
This paper computes time-varying indicators of the relative importance of different credit spread determinants, including rating, sector and country attribution as well as the coupon rate, maturity and liquidity on the basis of the comprehensive dataset of individual bonds. Additionally, it decomposes variances of rating-specific (country- and sector-specific) spread indices into the impacts of explanatory variables. Both cross-sectional and time series analyses confirm that the rating effect was the major driver of corporate bond spreads during the pre-crisis period, while the recent financial crisis was characterised by increased cross-country and cross-sector heterogeneity. The sector effects in corporate spreads together with the rating effects for high-rated and low-rated bonds are found to be more closely linked to default rates and stock indices, whereas the common effect also to be linked to business cycle conditions. The dataset also allows documenting a break-up in the existence of country ceilings for corporate bond ratings during the crisis.
JEL Code
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
C21 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Cross-Sectional Models, Spatial Models, Treatment Effect Models, Quantile Regressions
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
3 June 2016
WORKING PAPER SERIES - No. 1911
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Abstract
This paper analyses leading indicator properties of a broad set of credit spreads, compiled on the basis of information from both corporate bonds and bank loans for forecasting of real activity, unemployment, inflation and lending volumes in the euro area and in five major European economies. It also introduces a set of indicators for excess bond premia, adjusting corporate bond spreads for credit risk of the issuer and the term, coupon and liquidity premia. I find that the majority of macroeconomic indicators can be better predicted by the excess bond premia compared to non-adjusted indices; the rating-adjustment and time-varying parameter estimates seem to be particularly important. Although the predictive power of lending spreads is inferior to the predictive power of the excess bond premia, the forecasting performance of models which use the information from both lending and corporate bond spreads is always superior to models using only information from one source of external funding.
JEL Code
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
C21 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Cross-Sectional Models, Spatial Models, Treatment Effect Models, Quantile Regressions
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
Annexes
3 June 2016
ANNEX
17 September 2014
OCCASIONAL PAPER SERIES - No. 155
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Abstract
This paper analyses the cross-country heterogeneity in retail bank lending rates in the euro area and presents newly developed pass-through models that account for the riskiness of borrowers, the balance sheet constraints of lenders and sovereign debt tensions affecting interest rate-setting behaviour. Country evidence for the four largest euro area countries shows that downward adjustments in policy rates and market reference rates have translated into a concomitant reduction in bank lending rates. In the case of Spain and Italy, however, sovereign bond market tensions and a deteriorating macroeconomic environment have put upward pressure on composite lending rates to non-financial corporations and households. At the same time, model simulations suggest that higher lending rates have propagated to the broader economy by depressing economic activity and inflation. As a response to increasing financial fragmentation, the ECB has introduced several standard and non-standard monetary policy measures. These measures have gone a long way towards alleviating financial market tensions in the euro area. However, in order to ensure the adequate transmission of monetary policy to financing conditions, it is essential that the fragmentation of euro area credit markets is reduced further and the resilience of banks strengthened where needed. Simulation analysis confirms that receding financial fragmentation could help to boost economic activity in the euro area in the medium term.
JEL Code
E43 : Macroeconomics and Monetary Economics→Money and Interest Rates→Interest Rates: Determination, Term Structure, and Effects
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
C52 : Mathematical and Quantitative Methods→Econometric Modeling→Model Evaluation, Validation, and Selection
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
28 September 2005
WORKING PAPER SERIES - No. 530
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Abstract
This paper examines the cross-dynamics of volatility term structures implied by foreign exchange options. The data used in the empirical analysis consist of daily observations of implied volatilities for OTC options on the euro, Japanese yen, British pound, Swiss franc, and Canadian dollar, quoted against the U.S. dollar. The empirical findings demonstrate that two common factors can explain a vast proportion of the variation in volatility term structures across currencies. Furthermore, the results indicate that the euro is the dominant currency, as the implied volatility term structure of the euro is found to affect all the other volatility term structures, while the term structure of the euro appears to be virtually unaffected by the other currencies. Finally, our results reveal a rather deviant relation between the volatility term structures of the euro and Swiss franc by providing evidence of significant nonlinearities in the relationship between these two currencies.
JEL Code
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
F33 : International Economics→International Finance→International Monetary Arrangements and Institutions
F40 : International Economics→Macroeconomic Aspects of International Trade and Finance→General
5 May 2004
OCCASIONAL PAPER SERIES - No. 14
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Abstract
In this paper, we present a set of specific measures to quantify the state and evolution of financial integration in the euro area. Five key markets are considered, namely the money, corporate bond, government bond, credit and equity markets. Building upon the law of one price, we developed two types of indicators that can be broadly categorised as price-based and news-based measures. We complemented these measures by a number of quantity-based indicators, mainly related to the evolution of the home bias. Results indicate that the unsecured money market is fully integrated, while integration is reasonably high in the government and corporate bond market, as well as in the equity markets. The credit market is among the least integrated, especially in the short-term segment.
JEL Code
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
G15 : Financial Economics→General Financial Markets→International Financial Markets
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation