Ni na voljo v slovenščini.
Fabio Fornari
- 15 November 2022
- WORKING PAPER SERIES - No. 2749Details
- Abstract
- We test whether a simple measure of corporate insolvency based on equity return volatility -and denoted as Distance to Insolvency (DI) - delivers better prediction of corporate defaults than the widely-used Expected Default Frequency (EDF) measure computed by Moody’s. We look at the predictive power that current DIs and EDFs have for future defaults, both at a firm-level and at an aggregate level. At the granular level, both DIs and EDFs anticipate corporate defaults, but the DI contains information over and above the EDF, especially at longer forecasting horizons. At an aggregate level the DI shows superior forecasting power compared to the EDF, for horizons between 3 and 12 months. We illustrate the predictive power of the DI measure for the aggregate default rate by examining how corporate defaults would have evolved during the period marked by the spreading of the COVID-19 pandemic if DIs had not increased (so making future defaults less likely) also owing to the Eurosystem’s Public Emergency Purchase Program (PEPP).
- JEL Code
- C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C58 : Mathematical and Quantitative Methods→Econometric Modeling→Financial Econometrics
G33 : Financial Economics→Corporate Finance and Governance→Bankruptcy, Liquidation
- 10 October 2022
- WORKING PAPER SERIES - No. 2740Details
- Abstract
- Relying on a perspective borrowed from monetary policy announcements and introducing an econometric twist in the traditional event study analysis, we document the existence of an "event risk transfer", namely a significant credit risk transmission from the sovereign to the corporate sector after a sovereign rating downgrade. We find that after the delivery of the downgrade, corporate CDS spreads rise by 36% per annum and there is a widespread contagion across countries, in particular among those which were most exposed to the sovereign debt crisis. This effect exists on top of the standard relation between sovereign and corporate credit risk.
- JEL Code
- C21 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Cross-Sectional Models, Spatial Models, Treatment Effect Models, Quantile Regressions
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
- 21 September 2021
- OCCASIONAL PAPER SERIES - No. 271Details
- Abstract
- This paper analyses the implications of climate change for the conduct of monetary policy in the euro area. It first investigates macroeconomic and financial risks stemming from climate change and from policies aimed at climate mitigation and adaptation, as well as the regulatory and fiscal effects of reducing carbon emissions. In this context, it assesses the need to adapt macroeconomic models and the Eurosystem/ECB staff economic projections underlying the monetary policy decisions. It further considers the implications of climate change for the conduct of monetary policy, in particular the implications for the transmission of monetary policy, the natural rate of interest and the correct identification of shocks. Model simulations using the ECB’s New Area-Wide Model (NAWM) illustrate how the interactions of climate change, financial and fiscal fragilities could significantly restrict the ability of monetary policy to respond to standard business cycle fluctuations. The paper concludes with an analysis of a set of potential monetary policy measures to address climate risks, insofar as they are in line with the ECB’s mandate.
- 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
Q54 : Agricultural and Natural Resource Economics, Environmental and Ecological Economics→Environmental Economics→Climate, Natural Disasters, Global Warming
- 17 June 2020
- ECONOMIC BULLETIN - BOXEconomic Bulletin Issue 4, 2020Details
- Abstract
- The spread of the coronavirus (COVID-19) pandemic across the globe has led to significant declines in major equity indices and a spike in volatility to values above those recorded in the aftermath of the default of Lehman Brothers in September 2008. In line with the sharp rise in current risks, investors also raised their expectations of future risks, as shown by a widening of the risk-neutral density of future euro area equity returns. The increase in perceived risks accompanied a noticeable rise in investors’ risk aversion to negative tail events. More recently, and following the announcement of significant monetary and fiscal policy stimulus, the estimated tail risk aversion has been declining, while expected risks remain elevated.
- JEL Code
- G10 : Financial Economics→General Financial Markets→General
G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G13 : Financial Economics→General Financial Markets→Contingent Pricing, Futures Pricing
- 6 March 2013
- WORKING PAPER SERIES - No. 1522Details
- Abstract
- In this paper we attempt to evaluate the quantitative impact of financial shocks on key indicators of real activity and financial conditions. We focus on financial shocks as they have received wide attention in the recent literature and in the policy debate after the global financial crisis. We estimate a panel VAR for 21 advanced economies based on quarterly data between 1985 and 2011, where financial shocks are identified through sign restrictions. Overall, we find robust evidence that financial shocks can be separately identified from other shock types and that they exert a significant influence on key macroeconomic variables such as GDP and (particularly) investment, but it is unclear whether these shocks are demand or supply shocks from the standpoint of their macroeconomic impact. The financial development and the financial structure of a given country are found not to matter much for the intensity of the propagation of financial shocks. Moreover, we generally find that these shocks play a role not only in crisis times, but also in normal conditions. Finally, we discuss the implications of our findings for monetary policy.
- JEL Code
- 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
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G20 : Financial Economics→Financial Institutions and Services→General - Network
- Macroprudential Research Network
- 15 August 2011
- WORKING PAPER SERIES - No. 1366Details
- Abstract
- We provide evidence that changes in the equity price and volatility of individual firms (measures that approximate the definition of 'granular shock' given in Gabaix, 2010) are key to improve the predictability of aggregate business cycle fluctuations in a number of countries. Specifically, adding the return and the volatility of firm-level equity prices to aggregate financial information leads to a significant improvement in forecasting business cycle developments in four economic areas, at various horizons. Importantly, not only domestic firms but also foreign firms improve business cycle predictability for a given economic area. This is not immediately visible when one takes an unconditional standpoint (i.e. an average across the sample). However, conditioning on the business cycle position of the domestic economy, the relative importance of the two sets of firms - foreign and domestic - exhibits noticeable swings across time. Analogously, the sectoral classification of the firms that in a given month retain the highest predictive power for future IP changes also varies significantly over time as a function of the business cycle position of the domestic economy. Limited to the United States, predictive ability is found to be related to selected balance sheet items, suggesting that structural features differentiate the firms that can anticipate aggregate fluctuations from those that do not help to this aim. Beyond the purely forecasting application, this finding may enhance our understanding of the underlying origins of aggregate fluctuations. We also propose to use the cross sectional stock market information to macro-prudential aims through an economic Value at Risk.
- JEL Code
- C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
C58 : Mathematical and Quantitative Methods→Econometric Modeling→Financial Econometrics
F37 : International Economics→International Finance→International Finance Forecasting and Simulation: Models and Applications
G15 : Financial Economics→General Financial Markets→International Financial Markets
- 14 October 2010
- WORKING PAPER SERIES - No. 1255Details
- Abstract
- We forecast recession probabilities for the United States, Germany and Japan. The predictions are based on the widely-used probit approach, but the dynamics of regressors are endogenized using a VAR. The combined model is called a
- JEL Code
- C25 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Discrete Regression and Qualitative Choice Models, Discrete Regressors, Proportions
C32 : Mathematical and Quantitative Methods→Multiple or Simultaneous Equation Models, Multiple Variables→Time-Series Models, Dynamic Quantile Regressions, Dynamic Treatment Effect Models, Diffusion Processes
E32 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Business Fluctuations, Cycles
E37 : Macroeconomics and Monetary Economics→Prices, Business Fluctuations, and Cycles→Forecasting and Simulation: Models and Applications - Network
- Macroprudential Research Network
- 24 November 2009
- WORKING PAPER SERIES - No. 1108Details
- Abstract
- Previous research has shown that the US business cycle leads the European cycle by a few quarters, and can therefore help predicting euro area GDP. We investigate whether financial variables provide additional predictive power. We use a VAR model of the US and the euro area GDPs and extend it to take into account common global shocks and information provided by selected combinations of financial variables. In-sample analysis shows that shocks to financial variables influence real activity with a peak around 4 to 6 quarters after the shock. Out-of-sample Root-Mean- Squared Forecast Error (RMFE) shows that adding financial variables yields smaller errors in fore-casting US economic activity, especially at a five- quarter horizon, but the gain is overall tiny in economic terms. This link is even less prominent in the euro area, where financial indicators do not improve short and medium term GDP forecasts even when their timely availability, relative to a given GDP release, is exploited. The same conclusion is reached with a dataset of quarterly industrial production indices, although financial variables marginally improve fore- casts of monthly industrial production. We argue that the findings that financial variables have no predictive power for future activity in the euro area relate to the unconditional nature of the RMFE metric. When forecasting ability is assessed as if in real time (i.e. conditionally on the information available at the time when forecasts are made), we find that models using financial variables would have been preferred in many episodes, and in particular between 1999 and 2002. Results from the historical decomposition of a VAR model indeed suggest that in that period shocks were predominantly of financial nature.
- JEL Code
- F30 : International Economics→International Finance→General
F42 : International Economics→Macroeconomic Aspects of International Trade and Finance→International Policy Coordination and Transmission
F47 : International Economics→Macroeconomic Aspects of International Trade and Finance→Forecasting and Simulation: Models and Applications
- 31 January 2008
- WORKING PAPER SERIES - No. 859Details
- Abstract
- Volatilities implied from interest rate swaptions are used to assess the size and the sign of the compensation for volatility risk, for dollar, euro and pound rates at a daily frequency, between October 1998 and August 2006. The measurement of the volatility risk premium rests on a simple model according to which variance forecasts are generated under the objective probability measure. Results show that especially between September 2001 and mid-2003 dollar implieds were embodying a large - negative - compensation for volatility risk, a component which was smaller in absolute terms - but not relative to the level of the respective implied volatilities - for the other two currencies. While the negative compensation for volatility risk is in line with previous studies focusing on other asset classes, we also document that it exhibits a term structure, more evident for dollar and euro rates than for pound rates. The volatility risk premium is strongly changing through time but much less than implied volatilities. Estimates of risk aversion based on the physical skewness and kurtosis of interest rate changes suggest that (minus) the volatility risk premium can almost directly be read as risk aversion, as its proportionality with such risk aversion measure is about 0.8. Also, compensation for volatility risk is positively related to expected volatility, although the relation is not completely linear. Daily compensation for volatility risk is influenced, as expected, by the level of the short term rate and its volatility as well as by a small but robust number of macroeconomic surprises. The latter induce more sizeable changes on compensation for volatility risk of dollar rates than of euro or pound rates.
- JEL Code
- G12 : Financial Economics→General Financial Markets→Asset Pricing, Trading Volume, Bond Interest Rates
G13 : Financial Economics→General Financial Markets→Contingent Pricing, Futures Pricing
G14 : Financial Economics→General Financial Markets→Information and Market Efficiency, Event Studies, Insider Trading