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Fabio Fornari

31 January 2008
WORKING PAPER SERIES - No. 859
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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
24 November 2009
WORKING PAPER SERIES - No. 1108
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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
14 October 2010
WORKING PAPER SERIES - No. 1255
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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
15 August 2011
WORKING PAPER SERIES - No. 1366
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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
6 March 2013
WORKING PAPER SERIES - No. 1522
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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
17 June 2020
ECONOMIC BULLETIN - BOX
Economic Bulletin Issue 4, 2020
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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