Percorrer por autor "Santos, Paulo Araújo"
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- Downside risk and portfolio diversification in the euro-zone equity markets with special consideration of the crisis periodPublication . Liu, Tengdong; Hammoudeh, Shawkat; Santos, Paulo AraújoThis study examines the Value-at-Risk for ten euro-zone equity markets individually and also divided into two groups: PIIGS (Portugal, Italy, Ireland, Greece and Spain) and the Core (Austria, Finland, France, Germany and the Netherlands), employing four VaR estimation and evaluation methods considered over the full period and the pre- and post-global crisis subperiods 1 and 2. The backtesting results are also evaluated according to the Basel capital requirements. The results demonstrate that the CEVT methods meet all the statistical criteria the best for most individual equity indices over the full period, but these results over the two subperiods for those two methods are mixed, compared to those the DPOT methods. Moreover, the two optimal group portfolios of the PIIGS and the Core as well as the grand portfolio that combines the ten indices do not show much diversification benefits. The PIIGS portfolio selects Spain's IBEX only, while that of the Core opts for Austria's ATX only in the full period and subperiod 1. However, Germany's DAX overwhelmingly dominates both the Core and the Grand portfolios in subperiod 2.
- Downside risk, portfolio diversification and the financial crisis in the euro-zonePublication . Sarafrazi, Soodabeh; Hammoudeh, Shawkat; Santos, Paulo AraújoThis paper evaluates the value at risk for individual sovereign bond and national equity markets for 10 member countries in the euro-zone, using four estimation models and three accuracy criteria in addition to the daily capital requirements, for the full sample period and a subperiod that marks the beginning of the recent global financial crisis. The results show that the conditional extreme value theory model under both the normal and Student-t distributions satisfies the four accuracy criteria the best and gives the least capital charges for both periods, while the RiskMetrics gives the worst results. These euro-zone bond and equity markets are also classified into two groups: the PIIGS (Portugal, Italy, Ireland, Greece and Spain) and the Core (Germany, France, Austria, The Netherlands and Finland), and optimal portfolios are constructed for these two groups as well as for the ten euro area as a whole. Given the sample periods, the results show no strong diversification for any of the two groups or for the whole area in any of the bond and equity asset classes or both. The bond and equity portfolios are augmented with commodities and the best grand portfolio is the one that is diversified with the commodities gold, silver and oil, particularly for the subperiod.
- Estatística no Instituto Politécnico de SantarémPublication . Santos, Paulo Araújo; Lopes, Miguel; São João, RicardoO ensino da estatística nas licenciaturas do Instituto Politécnico de Santarém.
- GFC-robust risk management under the basel accord using extreme value methodologiesPublication . Santos, Paulo Araújo; Jiménez-Martín, Juan-Ángel; McAleer, Michael; Pérez Amaral, TeodosioIn McAleer et al. (2010b), a robust risk management strategy to the Global Financial Crisis (GFC) was proposed under the Basel II Accord by selecting a Value-at-Risk (VaR) forecast that combines the forecasts of different VaR models. The robust forecast was based on the median of the point VaR forecasts of a set of conditional volatility models. In this paper we provide further evidence on the suitability of the median as a GFC-robust strategy by using an additional set of new extreme value forecasting models and by extending the sample period for comparison. These extreme value models include DPOT and Conditional EVT. Such models might be expected to be useful in explaining financial data, especially in the presence of extreme shocks that arise during a GFC. Our empirical results confirm that the median remains GFC-robust even in the presence of these new extreme value models. This is illustrated by using the S&P500 index before, during and after the 2008-09 GFC. We investigate the performance of a variety of single and combined VaR forecasts in terms of daily capital requirements and violation penalties under the Basel II Accord, as well as other criteria, including several tests for independence of the violations. The strategy based on the median, or more generally, on combined forecasts of single models, is straightforward to incorporate into existing computer software packages that are used by banks and other financial institutions.
- High quantiles estimation with Quasi-PORT and DPOT:an application to value-at-risk for financial variablesPublication . Santos, Paulo Araújo; Alves, Isabel Fraga; Hammoudeh, ShawkatRecurrent “black swans” financial events are a major concern for both investors and regulators because of the extreme price changes they cause, despite their very low probability of occurrence. In this paper, we use unconditional and conditional methods, such as the recently proposed high quantile (HQ) extreme value theory (EVT) models of DPOT (Duration-based Peak Over Threshold) and quasi-PORT (peaks over random threshold), to estimate the Value-at-Risk with very small probability values for an adequately long and major financial time series to obtain a reasonable number of violations for backtesting. We also compare these models and other alternative strategies through an out-of-sample accuracy investigation to determine their relative performance within the HQ context. Policy implications relevant to estimation of risk for extreme events are also provided.
- Peaks over random threshold methodology for tail index and high quantile estimationPublication . Santos, Paulo Araújo; Alves, M. Isabel Fraga; Gomes, M. IvetteIn this paper we present a class of semi-parametric high quantile estimators which enjoy a desirable property in the presence of linear transformations of the data. Such a feature is in accordance with the empirical counterpart of the theoretical linearity of a quantile χp: χp(δX + λ) = δχp(X) + λ, for any real λ and positive δ. This class of estimators is based on the sample of excesses over a random threshold, originating what we denominate PORT (Peaks Over Random Threshold) methodology. We prove consistency and asymptotic normality of two high quantile estimators in this class, associated with the PORT-estimators for the tail index. The exact performance of the new tail index and quantile PORT-estimators is compared with the original semiparametric estimators, through a simulation study.
- PORT Hill and Moment Estimators for Heavy-Tailed ModelsPublication . Gomes, M. Ivette; Alves, M. Isabel Fraga; Santos, Paulo AraújoIn this article, we use the peaks over random threshold (PORT)-methodology, and consider Hill and moment PORT-classes of extreme value index estimators. These classes of estimators are invariant not only to changes in scale, like the classical Hill and moment estimators, but also to changes in location. They are based on the sample of excesses over a random threshold, the order statistic X[np]+1:n, 0 ≤ p < 1, being p a tuning parameter, which makes them highly flexible. Under convenient restrictions on the underlying model, these classes of estimators are consistent and asymptotically normal for adequate values of k, the number of top order statistics used in the semi-parametric estimation of the extreme value index γ. In practice, there may however appear a stability around a value distant from the target γ when the minimum is chosen for the random threshold, and attention is drawn for the danger of transforming the original data through the subtraction of the minimum. A new bias-corrected moment estimator is also introduced. The exact performance of the new extreme value index PORT-estimators is compared, through a large-scale Monte-Carlo simulation study, with the original Hill and moment estimators, the bias-corrected moment estimator, and one of the minimum-variance reduced-bias (MVRB) extreme value index estimators recently introduced in the literature. As an empirical example we estimate the tail index associated to a set of real data from the field of finance.
- Value-at-risk model based on extreme value theory:comparison with other models under the basel accordPublication . Santos, Paulo Araújo; Jiménez-Martin, Juan-Ángel; McAleer, Michael; Pérez Amaral, TeodosioSince the Basel II accord, forecasting Value-at-Risk become a daily task of banks and other Authorized Deposit-taking Institutions (ADIs). These forecasts are used to determine capital requirements and associated capital costs of ADIs. Methods based on Extreme Value Theory (EVT) showed better performance in terms of unconditional coverage and independence in many comparative studies. In this work we compare, in terms of daily capital requirements and violation penalties under the Basel II accord, the performance of a new model based on the EVT, with other models based on EVT, GARCH-type models and the Riskmetrics model. We emphasize that with the indexes under study and taking into account the Basel penalty zones, we achieve much better results with this new model than with the well known Riskmetrics model.