Elena-Ivona Dumitrescu

University of Orleans

France

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Elena-Ivona Dumitrescu created these companion sites

Testing Interval Forecasts: A GMM-Based Approach
Abstract
This paper proposes a new evaluation framework of interval forecasts. Our model free test can be used to evaluate intervals forecasts and/or High Density Region, potentially discontinuous and/or asymmetric. Using simple J-statistic based on the moments defined by the orthonormal polynomials associated with the Binomial distribution, this new approach presents many advantages. First, its implementation is extremely easy. Second, it allows for a separate test for unconditional coverage, independence and conditional coverage hypothesis. Third, Monte-Carlo simulations show that for realistic sample sizes, our GMM test outperforms traditional LR test. These results are corroborated by an empirical application on SP500 and Nikkei stock market indexes. The empirical application for financial returns confirms that using a GMM test leads to major consequences for the ex-post evaluation of interval forecasts produced by linear versus non linear models.
Dumitrescu, E., C. Hurlin, "Testing Interval Forecasts: A GMM-Based Approach", Journal of Forecasting, -.
Authors: Dumitrescu
Hurlin
Madkour
Coders: Dumitrescu
Hurlin
Last update
Tue Jun 05 04:57:00 CEST 2012
Ranking
10
Runs
29
Visits
340
Currency Crises Early Warning Systems: why they should be Dynamic
Abstract
This paper introduces a new generation of Early Warning Systems (EWS) which takes into account the dynamics, i.e. the persistence in the binary crisis indicator. We elaborate on Kauppi and Saikonnen (2008), which allows to consider several dynamic specifications by re- lying on an exact maximum likelihood estimation method. Applied so as to predict currency crises for fifteen countries, this new EWS turns out to exhibit significantly better predic- tive abilities than the existing models both within and out of the sample, thus vindicating dynamic models in the quest for optimal EWS.
Candelon, B., E. Dumitrescu, and C. Hurlin, "Currency Crises Early Warning Systems: why they should be Dynamic", Maastricht University.
Authors: Candelon
Dumitrescu
Hurlin
Coders: Candelon
Dumitrescu
Hurlin
Last update
Mon Jun 04 05:52:00 CEST 2012
Ranking
45
Runs
64
Visits
112
Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests
Abstract
In this paper we propose a new tool for backtesting that examines the quality of Value-at-Risk (VaR) forecasts. To date, the most distinguished regression-based backtest, proposed by Engle and Manganelli (2004), relies on a linear model. However, in view of the dichotomic character of the series of violations, a non-linear model seems more appropriate. In this paper we thus propose a new tool for backtesting (denoted DB) based on a dynamic binary regression model. Our discrete-choice model, e.g. Probit, Logit, links the sequence of violations to a set of explanatory variables including the lagged VaR and thelagged violations in particular. It allows us to separately test the unconditional coverage, the independence and the conditional coverage hypotheses and it is easy to implement. Monte-Carlo experiments show that the DB test exhibits good small sample properties in realistic sample settings (5% coverage rate with estimation risk). An application on a portfolio composed of three assets included in the CAC40 market index is finally proposed.
Hurlin, C., and E. Dumitrescu, "Backtesting Value-at-Risk: From Dynamic Quantile to Dynamic Binary Tests", Finance, 33.
Authors: Hurlin
Pham
Coders: Hurlin
Dumitrescu
Last update
Thu Jul 05 03:07:00 CEST 2012
Ranking
20
Runs
46
Visits
168
How To Evaluate an Early Warning System? Towards a unified Statistical Framework for Assessing Financial Crises Forecasting Methods
Abstract
This paper proposes an original and unified toolbox to evaluate financial crisis Early Warning Systems (EWS). It presents four main advantages. First, it is a model-free method which can be used to asses the forecasts issued from different EWS (probit, logit, markov switching models, or combinations of models). Second, this toolbox can be applied to any type of crisis EWS (currency, banking, sovereign debt, etc.). Third, it does not only provide various criteria to evaluate the (absolute) validity of EWS forecasts but also proposes some tests to compare the relative performance of alternative EWS. Fourth, our toolbox can be used to evaluate both in-sample and out-of-sample forecasts. Applied to a logit model for twelve emerging countries we show that the yield spread is a key variable for predicting currency crises exclusively for South-Asian countries. Besides, the optimal cut-off correctly allows us to identify now on average more than 2/3 of the crisis and calm periods.
Candelon, B., E. Dumitrescu, and C. Hurlin, "How To Evaluate an Early Warning System? Towards a unified Statistical Framework for Assessing Financial Crises Forecasting Methods", IMF Economic Review, 60.
Authors: Candelon
Dumitrescu
Hurlin
Coders: Candelon
Dumitrescu
Hurlin
Last update
Mon Jul 23 05:34:00 CEST 2012
Ranking
34
Runs
24
Visits
269
Outliers and GARCH Models in Financial Data
Abstract
We propose to extend the additive outlier (AO) identification procedure developed by Franses and Ghijsels(Franses, P.H., Ghijsels, H., 1999. Additive outliers, GARCH and forecasting volatility. International Journal of Forecasting, 15, 1–9) to take into account the innovative outliers (IOs) in a GARCH model. We apply it to three daily stock market indexes and examine the effects of outliers on the diagnostics of normality.
Charles, A., and O. Darné, D. Banulescu, E. Dumitrescu, "Outliers and GARCH Models in Financial Data", Economics Letters, 86, 347-352.
Authors: Charles
Darné
Coders: Charles
Darné
Banulescu
Dumitrescu
Last update
Fri Jun 22 08:48:00 CEST 2012
Ranking
15
Runs
61
Visits
238
Testing for Granger Non-causality in Heterogeneous Panels
Abstract
This paper proposes a very simple test of Granger (1969) non-causality for hetero- geneous panel data models. Our test statistic is based on the individual Wald statistics of Granger non causality averaged across the cross-section units. First, this statistic is shown to converge sequentially to a standard normal distribution. Second, the semi- asymptotic distribution of the average statistic is characterized for a fixed T sample. A standardized statistic based on an approximation of the moments of Wald statistics is hence proposed. Third, Monte Carlo experiments show that our standardized panel statistics have very good small sample properties, even in the presence of cross-sectional dependence.
Dumitrescu, E., and C. Hurlin, "Testing for Granger Non-causality in Heterogeneous Panels", Economic Modelling, Forthcoming.
Authors: Dumitrescu
Hurlin
Coders: Dumitrescu
Hurlin
Last update
Wed Jul 12 04:35:00 CEST 2017
Ranking
40
Runs
451
Visits
502