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Julien Idier

23 December 2008
WORKING PAPER SERIES - No. 987
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Abstract
In this paper the probability of informed trading (PIN) model developed by Easley and O'Hara (1992) is applied to analyze the role and impact of heterogeneities in euro overnight unsecured market. The empirical assessment of the functioning of this market is based on the PIN which measures the ability of traders to interpret signals on the expected evolution of the overnight rate. Results show that between 2000 and 2004 a heterogeneous learning process of market mechanisms within participants could be observed, whereas such asymmetries have been sharply decreasing since 2005. This is reviewed against some significant events that occurred in the euro money market, such as the reform of the Eurosystem's operational framework in March 2004 and the recent financial market turmoil, which has represented a break in the steady decline of asymmetries as evidence suggest.
JEL Code
G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
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ECB workshop on the analysis of the money market
13 May 2013
WORKING PAPER SERIES - No. 1546
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Abstract
We explore the practical relevance from a supervisor's perspective of a popular market-based indicator of the exposure of a financial institution to systemic risk, the marginal expected shortfall (MES). The MES of an institution can be defined as its expected equity loss when the market itself is in its left tail. We estimate the dynamic MES recently proposed by Brownlees and Engle (2011) for a panel of 65 large US banks over the last decade and a half. Running panel regressions of the MES on bank characteristics, we first find that the MES can be roughly rationalized in terms of standard balance sheet indicators of bank financial soundness and systemic importance. We then ask whether the cross section of the MES can help to identify ex ante, i.e. before a crisis unfolds, which institutions are the more likely to suffer the most severe losses ex post, i.e. once it has unfolded. Unfortunately, using the recent crisis as a natural experiment, we find that standard balance-sheet metrics like the tier one solvency ratio are better able than the MES to predict equity losses conditionally to a true crisis.
JEL Code
C5 : Mathematical and Quantitative Methods→Econometric Modeling
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G2 : Financial Economics→Financial Institutions and Services
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Macroprudential Research Network
28 February 2014
WORKING PAPER SERIES - No. 1642
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Abstract
Policy impact studies often suffer from endogeneity problems. Consider the case of the ECB Securities Markets Programme: If Eurosystem interventions were triggered by sudden and strong price deteriorations, looking at daily price changes may bias downwards the correlation between yields and the amounts of bonds purchased. Simple regression of daily changes in yields on quantities often give insignificant or even positive coefficients and therefore suggest that SMP interventions have been ineffective, or worse counterproductive. We use high frequency data on purchases of the ECB Securities Markets Programme and sovereign bond quotes to address the endogeneity issues. We propose an econometric model that considers, simultaneously, first and second conditional moments of market price returns at daily and intradaily frequency. We find that SMP interventions succeeded in reducing yields and volatility of government bond segments of the countries under the programme. Finally, the new econometric model is broadly applicable to market intervention studies.
JEL Code
E52 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Monetary Policy
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
C58 : Mathematical and Quantitative Methods→Econometric Modeling→Financial Econometrics