Simone Manganelli
Research
- Division
-
Financial Research
- Current Position
-
Head of Division
- Fields of interest
-
Mathematical and Quantitative Methods,Financial Economics,Microeconomics
- Education
- 1996-2000
PhD in Economics, University of California, San Diego, United States of America
- 1995-1999
Italian Doctorate, University of Siena, Italy
- 1988-1994
BA in Economics, Bocconi University, Milan, Italy
- Professional experience
- 2013-
Head of Division - Financial Research Division, Directorate General Research, European Central Bank
- 2012-2013
Adviser - Financial Research Division, Directorate General Research, European Central Bank
- 2010-2012
Principal Economist - Monetary Policy Stance Division, Directorate General Economics, European Central Bank
- 2009-2010
Principal Economist - Market Operations Analysis Division, Directorate General Market Operations, European Central Bank
- 2006-2009
Principal Economist - Financial Research Division, Directorate General Economics, European Central Bank
- 2004-2006
Senior Economist - Financial Research Division, Directorate General Economics, European Central Bank
- 2000-2004
Economist - Financial Research Division, Directorate General Economics, European Central Bank
- Awards
- 1998
Econometric analysis fellowship, University of California, San Diego, United States of America
- 1994
Gold medal for excellence in undergraduate studies, Bocconi University, Milan, Italy
- Teaching experience
- 1997-2000
Teaching Assistant - University of California, San Diego, United States
- 1994-1995
Teaching Assistant - Bocconi University, Milan, Italy
- 16 February 2023
- WORKING PAPER SERIES - No. 2786Details
- Abstract
- Bayesian decisions are observationally identical to decisions with judgment. Decisions with judgment test whether a judgmental decision is optimal and, in case of rejection, move to the closest boundary of the confidence interval, for a given confidence level. The resulting decisions condition on sample realizations, which are used to construct the confidence interval itself. Bayesian decisions condition on sample realizations twice, with the tested hypothesis and with the choice of the confidence level. The second conditioning reveals that Bayesian decision makers have an ex ante confidence level equal to one, which is equivalent to assuming an uncertainty neutral behavior. Robust Bayesian decisions are characterized by an ex ante confidence level strictly lower than one and are therefore uncertainty averse.
- JEL Code
- C1 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C12 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Hypothesis Testing: General
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
- 22 September 2021
- RESEARCH BULLETIN - No. 87.1Details
- Abstract
- When considering the use of macroprudential instruments to manage financial imbalances, macroprudential policymakers face an intertemporal trade-off between facilitating short-term expected growth and containing medium-term downside risks to the economy. To assist policymakers in assessing this trade-off, in this article we propose a risk management framework which extends the well-known notion of growth-at-risk to consider the entire predictive real GDP growth distribution, with a view to quantifying the macroprudential policy stance. A novel empirical model fitted to euro area data allows us to study direct and indirect interactions between financial vulnerabilities, financial stress and real GDP growth, incorporating non-linear amplification effects among all variables. Our framework can support policymakers by facilitating model-based macro-financial stress tests and model-based assessments of when to adjust macroprudential instruments.
- JEL Code
- G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models - Network
- Research Task Force (RTF)
- 2 June 2021
- WORKING PAPER SERIES - No. 2565Details
- Abstract
- Macro-prudential authorities need to assess medium-term downside risks to the real economy, caused by severe financial shocks. Before activating policy measures, they also need to consider their short-term negative impact. This gives rise to a risk management problem, an inter-temporal trade-off between expected growth and downside risk. Predictive distributions are estimated with structural quantile vector autoregressive models that relate economic growth to measures of financial stress and the financial cycle. An empirical study with euro area and U.S. data shows how to construct indicators of macro-prudential policy stance and to assess when interventions may be beneficial.
- JEL Code
- G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models - Network
- Research Task Force (RTF)
- 20 May 2021
- WORKING PAPER SERIES - No. 2556Details
- Abstract
- Macroprudential policymakers assess medium-term downside risks to the real economy arising from financial imbalances and implement policies aimed at managing those risks. In doing so, they face an inherent intertemporal trade-off between the expected growth and downside risks. This paper reviews the literature on Growth-at-Risk, embeds it in the wider literature on macroprudential policy, and proposes an empirical risk management framework that combines insights from the two literatures, by forecasting the entire real GDP growth distribution with a structural quantile vector autoregressive model. It accounts for direct and indirect interactions between financial vulnerabilities, financial stress and real GDP growth and allows for potential non-linear amplification effects. The framework provides policymakers with a macro-financial stress test to monitor downside risks to the economy and a macroprudential stance metric to quantify when interventions may be beneficial.
- JEL Code
- G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
C33 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Panel Data Models, Spatio-temporal Models - Network
- Discussion papers
- 25 January 2021
- WORKING PAPER SERIES - No. 2512Details
- Abstract
- A decision maker tests whether the gradient of the loss function evaluated at a judgmental decision is zero. If the test does not reject, the action is the judgmental decision. If the test rejects, the action sets the gradient equal to the boundary of the rejection region. This statistical decision rule is admissible and conditions on the sample realization. The confidence level reflects the decision maker’s aversion to statistical uncertainty. The decision rule is applied to a problem of asset allocation.
- JEL Code
- C1 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C12 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Hypothesis Testing: General
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
D81 : Microeconomics→Information, Knowledge, and Uncertainty→Criteria for Decision-Making under Risk and Uncertainty
- 7 October 2020
- WORKING PAPER SERIES - No. 2478Details
- Abstract
- Throughout the covid‐19 emergency, health authorities have presented contagion data divided by administrative regions with no reference to the type of landscape, environment or development model. This study has been conducted to understand whether there is a correlation between the number of infections and the different rural landscapes of the country. Italy’s rural landscape can be classified in four types, according to the intensity of energy inputs used in the agricultural process, socioeconomic and environmental features. Type A includes areas of periurban agriculture surrounding the metropolitan cities, type B areas of intensive agriculture with high concentration of agroindustry, type C hilly areas with highly diversified agriculture and valuable landscape, and type D high hills and mountains with forests and protected areas. Areas A and B are located in the plains, covering 21% of the territory and accounting for 57% of the population. They produce most of the added value, consume high levels of energy and represent the main source of pollution. Areas C and D cover 79% of the territory and 43% of the population. We find that provinces with 10% more type C and D areas exhibit on average 10% fewer cases of contagion. The result is statistically significant, after controlling for demographic, economic and environmental characteristics of the provinces. The pollution produced in more energy‐intensive landscape has triggered an intense debate of how to ensure the economic competitiveness of Italian agriculture, without compromising environmental integrity or public health. Our findings speak to this debate, by suggesting that planning for more rural territory with lower energy inputs may come with the added benefit of new development opportunities and decreasing the exposure of the population to covid‐19. . Cost benefit‐analyses should take into account that policies aimed at repopulating more rural areas may reduce the economic impact of covid‐19 and of potential future pandemics.
- JEL Code
- Q1 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Agriculture
Q15 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Agriculture→Land Ownership and Tenure, Land Reform, Land Use, Irrigation, Agriculture and Environment
O13 : Economic Development, Technological Change, and Growth→Economic Development→Agriculture, Natural Resources, Energy, Environment, Other Primary Products
- 25 September 2020
- WORKING PAPER SERIES - No. 2470Details
- Abstract
- We study the macroeconomic consequences of financial shocks and increase in economic risk using a quantile vector autoregression. Financial shocks have a negative, but asymmetric impact on the real economy: they substantially increase growth at risk, but have limited impact on upside potential. The impact of financial shocks is explained away after controlling for economic risk (measured by the interquantile range). The effects are economically relevant. Bad economic environment, characterized by negative real and financial shocks, has a highly skewed impact on business cycle fluctuations, leading to a peak reduction of monthly industrial production by more than 2%. In comparison, positive real and financial shocks in a good economic environment have limited effect on upside potential of the economy.
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
- 12 May 2020
- WORKING PAPER SERIES - No. 2404Details
- Abstract
- Two approaches are considered to incorporate judgment in DSGE models. First, Bayesian estimation indirectly imposes judgment via priors on model parameters, which are then mapped into a judgmental interest rate decision. Standard priors are shown to be associated with highly unrealistic judgmental decisions. Second, judgmental interest rate decisions are directly provided by the decision maker, and incorporated into a formal statistical decision rule using frequentist procedures. When the observed interest rates are interpreted as judgmental decisions, they are found to be consistent with DSGE models for long stretches of time, but excessively tight in the 1980s and late 1990s and excessively loose in the late 1970s and early 2000s.
- JEL Code
- E50 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→General
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
E47 : Macroeconomics and Monetary Economics→Money and Interest Rates→Forecasting and Simulation: Models and Applications
C12 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Hypothesis Testing: General
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
- 18 November 2019
- WORKING PAPER SERIES - No. 2330Details
- Abstract
- A quantile vector autoregressive (VAR) model, unlike standard VAR, models the interaction among the endogenous variables at any quantile. Forecasts of multivariate quantiles are obtained by factorizing the joint distribution in a recursive structure. VAR identification strategies that impose restrictions on the joint distribution can be readily extended to quantile VAR. The model is estimated using real and financial variables for the euro area. The dynamic properties of the system change across quantiles. This is relevant for stress testing exercises, whose goal is to forecast the tail behavior of the economy when hit by large financial and real shocks.
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
E17 : Macroeconomics and Monetary Economics→General Aggregative Models→Forecasting and Simulation: Models and Applications
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy - Network
- Research Task Force (RTF)
- 26 October 2018
- WORKING PAPER SERIES - No. 2188Details
- Abstract
- A statistical decision rule incorporating judgment does not perform worse than a judgmental decision with a given probability. Under model misspecification, this probability is unknown. The best model is the least misspecified, as it is the one whose probability of underperforming the judgmental decision is closest to the chosen probability. It is identified by the statistical decision rule incorporating judgment with lowest in sample loss. Averaging decision rules according to their asymptotic performance results in decisions which are weakly better than the best decision rule. The model selection criterion is applied to a vector autoregression model for euro area inflation.
- JEL Code
- C1 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C12 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Hypothesis Testing: General
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
- 6 December 2017
- WORKING PAPER SERIES - No. 2116Details
- Abstract
- This paper studies the impact of major ECB monetary policy announcements on the portfolio allocation of euro area fund investors, using daily data between 2012 and mid-2016, a period that includes a variety of unconventional measures. We distinguish between active portfolio reallocation, driven by redemptions or injections of investors, and passive portfolio rebalancing, triggered by valuation effects related to changes in asset prices and exchange rates. We find that, for this class of fund investors, policy announcements work mainly through valuation effects (the signalling channel), rather than via active reallocation (the portfolio rebalancing channel). Notably, since the autumn of 2014, monetary policy shocks triggered large asset price and exchange rate effects and prompted a passive shift of euro area investors into riskier assets, in particular European and Emerging Market equity funds and out of bond funds.
- JEL Code
- G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
G15 : Financial Economics→General Financial Markets→International Financial Markets
- 26 August 2016
- WORKING PAPER SERIES - No. 1947Details
- Abstract
- Non sample information is hidden in frequentist statistics in the choice of the hypothesis to be tested and of the confidence level. Explicit treatment of these elements provides the connection between Bayesian and frequentist statistics. A frequentist decision maker starts from a judgmental decision and moves to the closest boundary of the confidence interval of the first order conditions, for a given loss function. This statistical decision rule does not perform worse than the judgmental decision with a probability equal to the confidence level. For any given prior, there is a mapping from the sample realization to the confidence level which makes Bayesian and frequentist decision rules equivalent. Frequentist decision rules can be interpreted as decisions under ambiguity.
- JEL Code
- C1 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General
C11 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Bayesian Analysis: General
C12 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Hypothesis Testing: General
C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
D81 : Microeconomics→Information, Knowledge, and Uncertainty→Criteria for Decision-Making under Risk and Uncertainty
- 19 February 2016
- WORKING PAPER SERIES - No. 1886Details
- Abstract
- This paper investigates the impact of ample liquidity provision by the European Central Bank on the functioning of the overnight unsecured interbank market from 2008 to 2014. We use novel data on interbank transactions derived from TARGET2, the main euro area payment system. To identify exogenous shocks to central bank liquidity, we exploit the timing of ECB liquidity operations and use a simple structural vector auto-regression framework. We argue that the ECB acted as a de-facto lender-of-last-resort to the euro area banking system and identify two main effects of central bank liquidity provision on interbank markets. First, central bank liquidity replaces the demand for liquidity in the interbank market, especially during the financial crisis (2008-2010). Second, it increases the supply of liquidity in the interbank market in stressed countries (Greece, Italy and Spain) during the sovereign debt crisis (2011-2013).
- JEL Code
- E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
G01 : Financial Economics→General→Financial Crises
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
- 18 June 2015
- WORKING PAPER SERIES - No. 1814Details
- Abstract
- This paper proposes methods for estimation and inference in multivariate, multi-quantile models. The theory can simultaneously accommodate models with multiple random variables, multiple confidence levels, and multiple lags of the associated quantiles. The proposed framework can be conveniently thought of as a vector autoregressive (VAR) extension to quantile models. We estimate a simple version of the model using market equity returns data to analyse spillovers in the values at risk (VaR) between a market index and financial institutions. We construct impulse-response functions for the quantiles of a sample of 230 financial institutions around the world and study how financial institution-specific and system-wide shocks are absorbed by the system. We show how the long-run risk of the largest and most leveraged financial institutions is very sensitive to market wide shocks in situations of financial distress, suggesting that our methodology can prove a valuable addition to the traditional toolkit of policy makers and supervisors.
- JEL Code
- C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
- 19 December 2014
- WORKING PAPER SERIES - No. 1755Details
- Abstract
- This paper examines the degree of fragmentation in the Euro overnight unsecured money market during the period June 2008
- JEL Code
- G1 : Financial Economics→General Financial Markets
E5 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit - Network
- Macroprudential Research Network
- 28 February 2014
- WORKING PAPER SERIES - No. 1642Details
- 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
- 4 November 2011
- WORKING PAPER SERIES - No. 1394Details
- Abstract
- We exploit the 2007-2009 financial crisis to analyze how risk relates to bank business models. Institutions with higher risk exposure had less capital, larger size, greater reliance on short-term market funding, and aggressive credit growth. Business models related to significantly reduced bank risk were characterized by a strong deposit base and greater income diversification. The effect of business models is non-linear: it has a different impact on riskier banks. Finally, it is difficult to establish in real time whether greater stock market capitalization involves real value creation or the accumulation of latent risk.
- JEL Code
- G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
G15 : Financial Economics→General Financial Markets→International Financial Markets
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G32 : Financial Economics→Corporate Finance and Governance→Financing Policy, Financial Risk and Risk Management, Capital and Ownership Structure, Value of Firms, Goodwill - Network
- Macroprudential Research Network
- 14 January 2011
- OCCASIONAL PAPER SERIES - No. 122Details
- Abstract
- This paper provides an assessment of the impact of the covered bond purchase programme (hereafter referred to as the CBPP) relative to its policy objectives. The analysis presented on the impact of the CBPP on both the primary and secondary bond markets indicates that the Programme has been an effective policy instrument. It has contributed to: (i) a decline in money market term rates, (ii) an easing of funding conditions for credit institutions and enterprises, (iii) encouraging credit institutions to maintain and expand their lending to clients, and (iv) improving market liquidity in important segments of the private debt securities market. The paper also provides an overview of the investment strategy of the the Eurosystem with regard to the CBPP portfolio.
- JEL Code
- E22 : Macroeconomics and Monetary Economics→Consumption, Saving, Production, Investment, Labor Markets, and Informal Economy→Capital, Investment, Capacity
L63 : Industrial Organization→Industry Studies: Manufacturing→Microelectronics, Computers, Communications Equipment
L86 : Industrial Organization→Industry Studies: Services→Information and Internet Services, Computer Software
O3 : Economic Development, Technological Change, and Growth→Technological Change, Research and Development, Intellectual Property Rights
O47 : Economic Development, Technological Change, and Growth→Economic Growth and Aggregate Productivity→Measurement of Economic Growth, Aggregate Productivity, Cross-Country Output Convergence
- 21 October 2010
- WORKING PAPER SERIES - No. 1259Details
- Abstract
- We study how financial market efficiency affects a measure of diversification of output across industrial sectors borrowed from the portfolio allocation literature. Using data on sector-level value added for a wide cross section of countries and for various levels of disaggregation, we construct a benchmark measure of diversification as the set of allocations of aggregate output across industrial sectors which minimize the economy’s long-term volatility for a given level of long-term growth. We find that financial markets increase substantially the speed with which the observed sectoral allocation of output converges towards the optimally diversified benchmark. Convergence to the optimal shares of aggregate output is relatively faster for sectors that have a higher "natural" long-term risk-adjusted growth and which exhibit higher information frictions. Our results are robust to using various proxies for financial development, to accounting for the endogeneity of finance, and to controlling for investor’s protection, contract enforcement, and barriers to entry. Crucially, the observed patterns disappear when we employ "naive" measures of diversification based on the equal spreading of output across sectors.
- JEL Code
- E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
O16 : Economic Development, Technological Change, and Growth→Economic Development→Financial Markets, Saving and Capital Investment, Corporate Finance and Governance
- 12 November 2008
- WORKING PAPER SERIES - No. 957Details
- Abstract
- Engle and Manganelli (2004) propose CAViaR, a class of models suitable for estimating conditional quantiles in dynamic settings. Engle and Manganelli apply their approach to the estimation of Value at Risk, but this is only one of many possible applications. Here we extend CAViaR models to permit joint modeling of multiple quantiles, Multi-Quantile (MQ) CAViaR. We apply our new methods to estimate measures of conditional skewness and kurtosis defined in terms of conditional quantiles, analogous to the unconditional quantile-based measures of skewness and kurtosis studied by Kim and White (2004). We investigate the performance of our methods by simulation, and we apply MQ-CAViaR to study conditional skewness and kurtosis of S&P 500 daily returns.
- JEL Code
- C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
- 23 June 2008
- WORKING PAPER SERIES - No. 906Details
- Abstract
- This paper investigates whether comovements between euro area equity returns at national and industry level have changed after the introduction of the euro. By adopting a regression quantile-based methodology, we find that after 1999 the degree of comovements among euro area national equity markets has augmented. By explicitly controlling for the impact of global factors, we show that this result cannot be explained away by recent world-wide trends. A more refined analysis based on an industry breakdown suggests that the increase in national index comovements is mainly driven by financial, industrials and consumer services sectors.
- JEL Code
- F36 : International Economics→International Finance→Financial Aspects of Economic Integration
G15 : Financial Economics→General Financial Markets→International Financial Markets
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
- 13 March 2008
- OCCASIONAL PAPER SERIES - No. 81Details
- Abstract
- The study considers three broad categories of financial integration measures: (i) price-based, which capture discrepancies in asset prices across different national markets; (ii) news-based, which analyse the impact that common factors have on the return process of an asset; (iii) quantity-based, which aim at quantifying the effects of frictions on the demand for and supply of securities. This paper finds that financial markets in the new EU Member States (plus Cyprus, Malta and Slovenia) are significantly less integrated than those of the euro area. Nevertheless, there is strong evidence that the process of integration is well under way and has accelerated since accession to the EU.
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
F30 : International Economics→International Finance→General
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
- 24 April 2007
- WORKING PAPER SERIES - No. 745Details
- Abstract
- This paper studies the determinants of interest rate spreads of euro area 10 year government bonds against the benchmark, the German bund, after the introduction of the euro. In particular, it pays attention to the question whether market discipline is advanced or obstructed by financial integration and by fiscal rules like the Stability and Growth Pact. We first argue that financial integration - by improving market efficiency - is instrumental for markets to exert their disciplinary role. Next, we discuss the relationships between market discipline and fiscal rules, arguing that these in principle may reinforce each other. Finally, we provide strong empirical evidence that spreads depend on the ratings of the underlying bond and to a large extent are driven by the level of short-term interest rates.
- JEL Code
- G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G18 : Financial Economics→General Financial Markets→Government Policy and Regulation
C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
- 2 February 2007
- WORKING PAPER SERIES - No. 723Details
- Abstract
- This paper shows how the problem of mean-downside risk portfolio allocation can be cast in terms of penalized least squares (PLS). The penalty is given by a power function of the returns below a certain threshold. We derive the asymptotic properties of the PLS estimator, allowing for possible nonlinearities and misspecification of the model. We illustrate the usefulness of this new class of estimators with two empirical applications. First, we estimate an autoregressive model, in the spirit of the GARCH literature. Second, we suggest a simple strategy to derive the optimal portfolio weights associated to a mean-downside risk model.
- JEL Code
- C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
- 27 October 2006
- WORKING PAPER SERIES - No. 683Details
- Abstract
- This study assesses the degree of financial integration for a selected number of new EU member states between themselves and with the euro zone. Within the framework of a factor model for market returns, we measure integration as the amount of variance explained by the common factor relative to the local components. We show that this measure of integration coincides with return correlation. Correlations are proxied by comovements, estimated via a regression quantile-based methodology. We find that the largest new member states, the Czech Republic, Hungary and Poland, exhibit strong comovements both between themselves and with the euro area. As for smaller countries, only Estonia and to a less extent Cyprus show increased integration both with the euro zone and the block of large economies. In the bond markets, we document an increase in integration only for the Czech Republic versus Germany and Poland.
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
F30 : International Economics→International Finance→General
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
- 23 March 2006
- WORKING PAPER SERIES - No. 598Details
- Abstract
- We assess whether the euro had an impact first on the degree of integration of European financial markets, and, second, on the euro area term structure. We propose two methodologies to measure integration: one relies on time-varying GARCH correlations, and the other one on a regression quantile-based codependency measure. We document an overall increase in co movements in both equity and bond euro area markets, suggesting that integration has progressed since the introduction of the euro. However, while the correlations in bond markets reaches almost one for all euro area countries, co-movements in equity markets are much lower and the increase is limited to large euro area economies only. In the second part of the paper, we focus on the asset pricing implications of the euro. Specifically, we use a dynamic no arbitrage term structure model to examine the risk - return trade-off in the term structure of interest rates before and after the introduction of the euro. The analysis shows that while the average level of term premia seems little changed following the euro introduction, the variability of premia has been reduced as a result of smaller macro shocks during the euro period. Moreover, the macro factors that were found to be important in explaining the dynamics of premia before the introduction of the euro continue to play a key role in this respect also thereafter.
- JEL Code
- F36 : International Economics→International Finance→Financial Aspects of Economic Integration
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
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
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes - Network
- Proceedings of June 2005 workshop on what effects is EMU having on the euro area and its member countries?
- 31 January 2006
- WORKING PAPER SERIES - No. 584Details
- Abstract
- This paper argues that forecast estimators should minimise the loss function in a statistical, rather than deterministic, way. We introduce two new elements into the classical econometric analysis: a subjective guess on the variable to be forecasted and a probability reflecting the confidence associated to it. We then propose a new forecast estimator based on a test of whether the first derivatives of the loss function evaluated at the subjective guess are statistically different from zero. We show that the classical estimator is a special case of this new estimator, and that in general the two estimators are asymptotically equivalent. We illustrate the implications of this new theory with a simple simulation, an application to GDP forecast and an example of mean-variance portfolio selection.
- JEL Code
- C13 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Estimation: General
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
G11 : Financial Economics→General Financial Markets→Portfolio Choice, Investment Decisions
- 21 July 2005
- WORKING PAPER SERIES - No. 501Details
- Abstract
- This paper develops a rigorous econometric framework to investigate the structure of codependence between random variables and to test whether it changes over time. Our approach is based on the computation - over both a test and a benchmark period - of the conditional probability that a random variable yt is lower than a given quantile, when the other random variable xt is also lower than its corresponding quantile, for any set of prespecified quantiles. Time-varying conditional quantiles are modeled via regression quantiles. The conditional probability is estimated through a simple OLS regression. We illustrate the methodology by investigating the impact of the crises of the 1990s on the major Latin American equity markets returns. Our results document significant increases in equity return co-movements during crises consistent with the presence of financial contagion.
- JEL Code
- C14 : Mathematical and Quantitative Methods→Econometric and Statistical Methods and Methodology: General→Semiparametric and Nonparametric Methods: General
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
G15 : Financial Economics→General Financial Markets→International Financial Markets
- 1 May 2003
- WORKING PAPER SERIES - No. 230Details
- Abstract
- Four years after the introduction of the euro, this paper provides an overview of the current structure and integration of the euro area financial systems and related policy initiatives. We first compare the euro area financial structure with that of the United States and Japan. Using new and comprehensive financial account data, we also describe how the euro area financial structure evolved since 1995. We document the progress towards integration of the major euro area financial segments, namely money markets, bond markets, equity markets and banking. Finally, we discuss recent policy initiatives aimed at further improving European financial integration
- JEL Code
- G00 : Financial Economics→General→General
F36 : International Economics→International Finance→Financial Aspects of Economic Integration
- 1 April 2003
- WORKING PAPER SERIES - No. 226Details
- Abstract
- In deciding the monetary policy stance, central bankers need to evaluate carefully the risks the current economic situation poses to price stability. We propose to regard the central banker as a risk manager who aims to contain inflation within pre-specified bounds. We develop formal tools of risk management that may be used to quantify and forecast the risks of failing to attain that objective. We illustrate the use of these risk measures in practice. First, we show how to construct genuine real time forecasts of year-on-year risks that may be used in policy-making. We demonstrate the usefulness of these risk forecasts in understanding the Fed's decision to tighten monetary policy in 1984, 1988, and 1994. Second, we forecast the risks of worldwide deflation for horizons of up to two years. Although recently fears of worldwide deflation have increased, we find that, as of September 2002, with the exception of Japan there is no evidence of substantial deflation risks. We also put the estimates of deflation risk for the United States, Germany and Japan into historical perspective. We find that only for Japan there is evidence of deflation risks that are unusually high by historical standards.
- JEL Code
- E31 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Price Level, Inflation, Deflation
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications
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
C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
- 1 November 2002
- WORKING PAPER SERIES - No. 194Details
- Abstract
- The extension of GARCH models to the multivariate setting has been fraught with difficulties. In this paper, we suggest to work with univariate portfolio GARCH models. We show how the multivariate dimension of the portfolio allocation problem may be recovered from the univariate approach. The main tool we use is the "variance sensitivity analysis", which measures the change in the portfolio variance as a consequence of an infinitesimal change in the portfolio allocation. We derive the sensitivity of the univariate portfolio GARCH variance to the portfolio weights, by analytically computing the derivatives of the estimated GARCH variance with respect to these weights. We suggest a new and simple method to estimate full variance-covariance matrices of portfolio assets. An application to real data portfolios shows how to implement our methodology and compares its performance against that of selected popular alternatives.
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
G15 : Financial Economics→General Financial Markets→International Financial Markets
- 1 February 2002
- WORKING PAPER SERIES - No. 125Details
- Abstract
- This paper develops a new econometric framework to model duration, volume and volatility simultaneously. We obtain an econometric reduced form that incorporates causal and feedback effects among these variables. We construct impulse-response functions that show how the system reacts to a perturbation of its long-run equilibrium. The methodology is applied to two groups of stocks from NYSE, classified according to their trade intensity. We document how the two groups of stocks are characterised by different dynamics: 1) volume is more persistent for frequently traded stocks than for the infrequently traded ones; 2) the well-known positive relationship between volume and price variability holds only for the frequently traded stocks at the ultra high frequency level; 3) the trade arrival process can be considered exogenous only for the not frequently traded stocks; 4) the more frequently traded the stock, the faster the market returns to its full information equilibrium after a perturbation
- JEL Code
- C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading
- 1 August 2001
- WORKING PAPER SERIES - No. 75Details
- Abstract
- The main objective of this paper is to survey and evaluate the performance of the most popular univariate VaR methodologies, paying particular attention to their underlying assumptions and to their logical flaws. In the process, we show that the Historical Simulation method and its variants can be considered as special cases of the CAViaR framework developed by Engle and Manganelli (1999). We also provide two original methodological contributions. The first one introduces the extreme value theory into the CAViaR model. The second one concerns the estimation of the expected shortfall (the expected loss, given that the return exceeded the VaR) using a regression technique. The performance of the models surveyed in the paper is evaluated using a Monte Carlo simulation. We generate data using GARCH processes with different distributions and compare the estimated quantiles to the true ones. The results show that CAViaR models perform best with heavy-tailed DGP.
- JEL Code
- C22 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models &bull Diffusion Processes
G22 : Financial Economics→Financial Institutions and Services→Insurance, Insurance Companies, Actuarial Studies
- 2020
- Landscape and Urban Planning
- 2017
- Journal of Financial IntermediationBank risk during the financial crisis: do business models matter?
- 2017
- Journal of the European Economic AssociationA high frequency assessment of the ECB Securities Markets Programme
- 2017
- World Scientific BooksAchieving Financial Stability Challenges to Prudential Regulation
- 2016
- Journal of Financial IntermediationLending-of-last-resort is as lending-of-last-resort does: central bank liquidity provision and interbank market Functioning in the Euro Area
- 2015
- Journal of International EconomicsFinancial development, sectoral reallocation, and volatility: international evidence
- 2015
- Journal of EconometricsVAR for VaR: measuring tail dependence using multivariate regression quantiles
- 2014
- Journal of Business and Economic StatisticsDiscussion of 'Central bank macroeconomic forecasting during the global financial crisis: the European Central Bank and Federal Reserve Bank of New York experiences' by Alessi, L. Ghysels, E. Onorante, L. Peach, R. and Potter, S.
- 2014
- Economics LettersFragmentation in the euro overnight unsecured money market
- 2014
- Journal of Financial EconometricsMeasuring comovements by regression quantiles
- 2010
- Journal of Financial and Quantitative AnalysisThe impact of the euro on equity markets
- 2009
- Economic PolicyWhat drives spreads in the euro area government bond market?
- 2009
- Journal of Business and Economic StatisticsForecasting with judgment
- 2008
- Journal of Money, Credit, and BankingThe central banker as a risk manager: estimating the Federal Reserve's preferences under Greenspan
- 2008
- Volatility and time series econometrics: essays in honour of Robert F. EngleModeling autoregressive conditional skewness and kurtosis with multi-quantile CAViaR
- 2007
- Journal of Money, Credit, and BankingQuantifying the risk of deflation
- 2005
- Journal of Financial MarketsDuration, volume and volatility impact of trades
- 2004
- Journal of Business and Economic StatisticsCAViaR: conditional autoregressive value at risk by regression quantiles
- 2004
- Journal of Financial EconometricsAsset allocation by variance sensitivity analysis
- 2004
- European Central Bank, Frankfurt am MainRisk management for central bank foreign reserves
- 2004
- Risk measures for the 21st centuryA comparison of value at risk models in finance
- 2003
- Oxford Review of Economic PolicyEMU and the European financial system: structure, integration and policy initiatives