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Robert F. Engle

1 August 2001
WORKING PAPER SERIES - No. 75
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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
1 January 2003
WORKING PAPER SERIES - No. 204
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Abstract
This paper investigates the presence of asymmetric conditional second moments in international equity and bond returns. The analysis is carried out through an asymmetric version of the Dynamic Conditional Correlation model of Engle (2002). Widespread evidence is found that national equity index return series show strong asymmetries in conditional volatility, while little evidence is seen that bond index returns exhibit this behaviour. However, both bonds and equities exhibit asymmetry in conditional correlation. Worldwide linkages in the dynamics of volatility and correlation are examined. It is also found that beginning in January 1999, with the introduction of the Euro, there is significant evidence of a structural break in correlation, although not in volatility. The introduction of a fixed exchange rate regime leads to near perfect correlation among bond returns within EMU countries. However, equity return correlation both within and outside the EMU also increases after January 1999.
JEL Code
F3 : International Economics→International Finance
G1 : Financial Economics→General Financial Markets
C5 : Mathematical and Quantitative Methods→Econometric Modeling
10 March 2017
WORKING PAPER SERIES - No. 37
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Abstract
We introduce SRISK to measure the systemic risk contribution of a financial firm. SRISK measures the capital shortfall of a firm conditional on a severe market decline, and is a function of its size, leverage and risk. We use the measure to study top US financial institutions in the recent financial crisis. SRISK delivers useful rankings of systemic institutions at various stages of the crisis and identifies Fannie Mae, Freddie Mac, Morgan Stanley, Bear Stearns and Lehman Brothers as top contributors as early as 2005-Q1. Moreover, aggregate SRISK provides early warning signals of distress in indicators of real activity.
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
C23 : Mathematical and Quantitative Methods→Single Equation Models, Single Variables→Panel Data Models, Spatio-temporal Models
C53 : Mathematical and Quantitative Methods→Econometric Modeling→Forecasting and Prediction Methods, Simulation Methods
G01 : Financial Economics→General→Financial Crises
G20 : Financial Economics→Financial Institutions and Services→General
2 June 2021
WORKING PAPER SERIES - No. 2565
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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