References of "Terraza, Virginie 50003187"
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See detailFunds Rating: the predictive power
Terraza, Virginie UL; Toque, Carole UL

in Euro-Mediterranean Economics and Finance Review (2009), 4(4),

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See detailValue at Risk, Outliers and Chaotic Dynamics
Kyrtsou, catherine; Terraza, Virginie UL

in COSTANTINO, M.; LARRAN, M. (Eds.) Computational Finance and its Applications III (2008)

Financial returns series typically exhibit excess kurtosis and volatility clustering. GARCH models are often applied to describe these two stylised facts. Nevertheless, applications of these processes to ... [more ▼]

Financial returns series typically exhibit excess kurtosis and volatility clustering. GARCH models are often applied to describe these two stylised facts. Nevertheless, applications of these processes to stock returns have shown that they cannot capture all excess kurtosis, high Jarque-Bera and inherent non-linearity. The aim of this work is to suggest a new non-linear framework for the calculation of the Value-at-Risk. As it has been demonstrated in Kyrtsou and Terraza V. (2004) the use of a mixed non-linear model in the estimation of VaR can improve the obtained results. In this paper we apply the traditional VaR-GARCH and the VaR-Mackey-Glass-GARCH models both to the initial and the filtered Nikkei returns series without outliers. [less ▲]

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See detailThe shapley decomposition for risk portfolios
Mussard, Stéphane; Terraza, Virginie UL

in Applied Economics Letters (2008), 15(9), 713-715

The aim of this paper is to propose the Shapley Value to decompose financial risk portfolios. Decomposing the sample covariance risk measure, gives us relative measures, which can be, classified ... [more ▼]

The aim of this paper is to propose the Shapley Value to decompose financial risk portfolios. Decomposing the sample covariance risk measure, gives us relative measures, which can be, classified securities of a portfolio according to a risk scale [less ▲]

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See detailExchange rates and macroeconomic dynamics
Terraza, Virginie UL; Karadeloglou, Pavlos

Book published by Palgrave (2008)

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See detailNew trading risk indexes: application of the shapley value in finance
Terraza, Virginie UL; Mussard, Stéphane

in Economics Bulletin (2007), 3(25), 1-7

The aim of this paper is to offer new risk indicators that enable one to classify securities of a portfolio according to their risk degrees. These indexes are issued from a new method of the covariance ... [more ▼]

The aim of this paper is to offer new risk indicators that enable one to classify securities of a portfolio according to their risk degrees. These indexes are issued from a new method of the covariance decomposition based on the Shapley Value. The risk indicators are computed via the well-known Gini coefficient, which is viewed as a new risk measure and compared with the traditional measures related with the modern theory of portfolio. These indicators yield suitable information, which could be used by private or institutional investors to trade strategies on market portfolio. [less ▲]

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See detailTiming inconsistencies in the calculation of Funds of funds Net Asset Value
Terraza, Virginie UL; Neuberg, Luc; Louargant, Christine

in Fundexpert (2006)

The purpose of this paper is to analyze the impact upon tracking errors of timing inconsistencies in the calculation of Funds of Funds (FoF) Net Asset Value (NAV). When the NAV of a FoF is calculated, the ... [more ▼]

The purpose of this paper is to analyze the impact upon tracking errors of timing inconsistencies in the calculation of Funds of Funds (FoF) Net Asset Value (NAV). When the NAV of a FoF is calculated, the NAVs of underlying funds are not always available at the same market date. This can be due to the time of publication of the underlying funds NAVs and also due to the fact that the funds relate to different markets with different closing times. The NAV of the FoF are therefore calculated using diverse market days. Benchmarks of FoF are usually composed of indices. The level of these benchmarks are calculated using underlying prices at the same market day. If we compare the return series of a FoF with the return series of its benchmark, a problem occurs due to the timing inconsistencies in the calculation. We examine how these timing inconsistencies produce noise in the NAV of FoF and therefore noise in the tracking error. We construct Funds of Funds and calculate NAVs of these FoF using underlying NAVs at different dates. We then compare series of tracking errors to analyze the impact of the timing inconsistencies and formalize a relation including a systematic error term generated by these timing inconsistencies. [less ▲]

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See detailSeasonal asymmetric persistence in volatility: an extension of GARCH models
Terraza, Virginie UL

in Wessex Institute of Technology (Ed.) Computational Finance and its Applications (2004)

In this paper, we study non-linear dynamics in the CAC 40 stock index. Our empirical results, suggest combining seasonality, persistence and asymmetric effects to model the conditional volatility. We ... [more ▼]

In this paper, we study non-linear dynamics in the CAC 40 stock index. Our empirical results, suggest combining seasonality, persistence and asymmetric effects to model the conditional volatility. We observe that seasonality can have an asymmetric impact on the volatility. In particular, we show that negative shocks observed on Mondays have a greater impact on the volatility than the other days. Then we construct a seasonal asymmetric GARCH model. It consists to add seasonal terms in the variance equation of a GJR-GARCH (1,1) model. [less ▲]

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