References of "Heuchenne, Cédric"
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See detailWhat are the determinants of the operational losses severity distribution ? A multivariate analysis based on a semiparametric approach.
Hambuckers, julien ULiege; Heuchenne, Cédric ULiege; Lopez, Olivier

Poster (2015, June)

In this paper, we analyse a database of around 41,000 operational losses from the European bank UniCredit. We investigate three kinds of covariates: firm-specific, fi- nancial and macroeconomic covariates ... [more ▼]

In this paper, we analyse a database of around 41,000 operational losses from the European bank UniCredit. We investigate three kinds of covariates: firm-specific, fi- nancial and macroeconomic covariates and we study their relationship with the shape parameter of the severity distribution. To do so, we introduce a semiparametric approach to estimate the shape parameter of the severity distribution, conditionally to large sets of covariates. Relying on a single index assumption to perform a dimension reduction, this approach avoids the curse of dimensionality of pure multivariate nonparametric techniques as well as too restrictive parametric assumptions. We show that taking into account variables measuring the economic well being of the bank could cause the required Operational Value-at-Risk to vary drastically. Especially, high pre-tax ROE, efficiency ratio and stock price are associated with a low shape parameter of the severity distribution, whereas a high market volatility, leverage ratio and unemployment rate are associated with higher tail risks. Finally, we discuss the fact that the considered approach could be an interesting tool to improve the estimation of the parameters in a Loss Distribution Approach and to offer an interesting methodology to study capital requirements variations throughout scenario analyses. [less ▲]

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See detailGuaranteed Conditional Performance of the S2 Control Chart with Estimated Parameters
Faraz, Alireza ULiege; Heuchenne, Cédric ULiege; Woodall, William

in International Journal of Production Research (2015)

We evaluate the in-control performance of the S2 control chart with estimated parameters conditional on the Phase I sample. Simulation results indicate no realistic amount of Phase I data is enough to ... [more ▼]

We evaluate the in-control performance of the S2 control chart with estimated parameters conditional on the Phase I sample. Simulation results indicate no realistic amount of Phase I data is enough to have confidence that the in-control average run length (ARL) obtained will be near the desired value. To overcome this problem, we adjust the S2 chart controls limits such that the in-control ARL is guaranteed to be above a specified value with a certain specified probability. The required adjustment does not have too much of an effect on the out-of-control performance of the chart. [less ▲]

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See detailEstimation of the error distribution in a semiparametric transformation model.
Heuchenne, Cédric ULiege; Samb, Rawane; Van Keilegom, Ingrid

in Electronic Journal of Statistics (2015), 9

Detailed reference viewed: 12 (3 ULiège)
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See detailEstimating the error distribution function of a heteroskedastic nonparametric regression of cure model data
Chown, Justin; Heuchenne, Cédric ULiege; Van Keilegom, Ingrid

Conference (2015)

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See detailShewhart Control Charts for Monitoring Reliability with Weibull Lifetimes
Faraz, Alireza ULiege; Saniga, Erwin; Heuchenne, Cédric ULiege

in Quality and Reliability Engineering International (2015), 31

In this paper, we present Shewhart type Z ̅ and S2 control charts for monitoring individual or joint shifts in the scale and shape parameters of a Weibull distributed process. The advantage of this method ... [more ▼]

In this paper, we present Shewhart type Z ̅ and S2 control charts for monitoring individual or joint shifts in the scale and shape parameters of a Weibull distributed process. The advantage of this method is its ease of use and flexibility for the case where the process distribution is Weibull, although the method can be applied to any distribution. We illustrate the performance of our method through simulation and the application through the use of an actual data set. Our results indicate that Z ̅ and S2 control charts perform well in detecting shifts in the scale and shape parameters. We also provide a guide that would enable a user to interpret out-of-control signals. [less ▲]

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See detailEstimation of the error density in a semiparametric transformation model
Colling, Benjamin; Heuchenne, Cédric ULiege; Samb, Rawane et al

in Annals of the Institute of Statistical Mathematics (2015), 67

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See detailA semiparametric model for Generalized Pareto regression based on a dimension reduction assumption
Hambuckers, julien ULiege; Heuchenne, Cédric ULiege; Lopez, Olivier

E-print/Working paper (2015)

In this paper, we consider a regression model in which the tail of the conditional distribution of the response can be approximated by a Generalized Pareto distribution. Our model is based on a ... [more ▼]

In this paper, we consider a regression model in which the tail of the conditional distribution of the response can be approximated by a Generalized Pareto distribution. Our model is based on a semiparametric single-index assumption on the conditional tail index; while no further assumption on the conditional scale parameter is made. The underlying dimension reduction assumption allows the procedure to be of prime interest in the case where the dimension of the covariates is high, in which case the purely nonparametric techniques fail while the purely parametric ones are too rough to correctly fit to the data. We derive asymptotic normality of the estimators that we define, and propose an iterative algorithm in order to perform their practical implementation. Our results are supported by some simulations and a practical application on a public database of operational losses. [less ▲]

Detailed reference viewed: 60 (10 ULiège)
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See detailIdentifying the best technical trading rule: a .632 bootstrap approach.
Hambuckers, julien ULiege; Heuchenne, Cédric ULiege

Conference (2014, December 07)

In this paper, we estimate the out-of-sample predictive ability of a set of trading rules. Usually, this ability is estimated using a rolling-window sample-splitting scheme, true out-of-sample data being ... [more ▼]

In this paper, we estimate the out-of-sample predictive ability of a set of trading rules. Usually, this ability is estimated using a rolling-window sample-splitting scheme, true out-of-sample data being rarely available. We argue that this method makes a poor use of the available information and creates data mining possibilities. Instead, we introduce an alternative bootstrap approach, based on the .632 bootstrap principle. This method enables to build in-sample and out-of-sample bootstrap data sets that do not overlap and exhibit the same time dependencies. We illustrate our methodology on IBM and Microsoft daily stock prices, where we compare 11 trading rules specifications. For the data sets considered, two different filter rule specifications have the highest out-of-sample mean excess returns. However, all tested rules cannot beat a simple buy-and-hold strategy when trading at a daily frequency. [less ▲]

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See detailEstimating the out-of-sample predictive ability of trading rules: a robust bootstrap approach
Hambuckers, julien ULiege; Heuchenne, Cédric ULiege

E-print/Working paper (2014)

In this paper, we estimate the out-of-sample predictive ability of a set of trading rules. Usually, this ability is estimated using a rolling-window sample-splitting scheme, true out-of-sample data being ... [more ▼]

In this paper, we estimate the out-of-sample predictive ability of a set of trading rules. Usually, this ability is estimated using a rolling-window sample-splitting scheme, true out-of-sample data being rarely available. We argue that this method makes a poor use of the available information and creates data mining possibilities. Instead, we introduce an alternative bootstrap approach, based on the .632 bootstrap principle. This method enables to build in-sample and out-of-sample bootstrap data sets that do not overlap and exhibit the same time dependencies. We illustrate our methodology on IBM and Microsoft daily stock prices, where we compare 11 trading rules specifications. For the data sets considered, two different filter rule specifications have the highest out-of-sample mean excess returns. However, all tested rules cannot beat a simple buy-and-hold strategy when trading at a daily frequency. [less ▲]

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See detailThe application of the NSGA-II optimization method in designing control charts
Faraz, Alireza ULiege; Heuchenne, Cédric ULiege; Seif, Asghar

Conference (2014, June 04)

The problem of designing control chart is formulated as a multi-objective optimization problem with the adjusted average time to signal as the statistical objective and the expected cost per hour as the ... [more ▼]

The problem of designing control chart is formulated as a multi-objective optimization problem with the adjusted average time to signal as the statistical objective and the expected cost per hour as the economic objective. Then we try to find the Pareto-optimal designs in which the two objectives are minimized simultaneously by using the elitist non-dominated sorting genetic algorithm method. Through an illustrative example, the advantages of the proposed approach is shown by providing a list of viable optimal solutions and graphical representations, thereby bolding the advantage of flexibility and adaptability. [less ▲]

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See detailThe variable parameters T2 chart with run rules
Faraz, Alireza ULiege; Celano, Giovanni; Heuchenne, Cédric ULiege et al

in Statistical Papers (2014), 55(4), 933-950

The Hotelling’s T2 control chart with variable parameters (VP T2) has been shown to have better statistical performance than other adaptive control schemes in detecting small to moderate process mean ... [more ▼]

The Hotelling’s T2 control chart with variable parameters (VP T2) has been shown to have better statistical performance than other adaptive control schemes in detecting small to moderate process mean shifts. In this paper, we investigate the statistical performance of the VP T2 control chart coupled with run rules. We consider two well-known run rules schemes. Statistical performance is evaluated by using a Markov chain modeling the random shock mechanism of the monitored process. The in-control time interval of the process is assumed to follow an exponential distribution. A Genetic Algorithm has been designed to select the optimal chart design parameters. We provide an extensive numerical analysis indicating that the VP T2 control chart with run rules outperforms other charts for small sizes of the mean shift expressed through the Mahalanobis distance. [less ▲]

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See detailA new methodological approach for error distributions selection in Finance
Hambuckers, julien ULiege; Heuchenne, Cédric ULiege

E-print/Working paper (2014)

In this article, we propose a robust methodology to select the most appropriate error distribution candidate, in a classical multiplicative heteroscedastic model. In a first step, unlike to the ... [more ▼]

In this article, we propose a robust methodology to select the most appropriate error distribution candidate, in a classical multiplicative heteroscedastic model. In a first step, unlike to the traditional approach, we don't use any GARCH-type estimation of the conditional variance. Instead, we propose to use a recently developed nonparametric procedure (Mercurio and Spokoiny, 2004): the Local Adaptive Volatility Estimation (LAVE). The motivation for using this method is to avoid a possible model misspecification for the conditional variance. In a second step, we suggest a set of estimation and model selection procedures (Berk-Jones tests, kernel density-based selection, censored likelihood score, coverage probability) based on the so-obtained residuals. These methods enable to assess the global fit of a given distribution as well as to focus on its behavior in the tails. Finally, we illustrate our methodology on three time series (UBS stock returns, BOVESPA returns and EUR/USD exchange rates). [less ▲]

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See detailA new methodological approach for error distributions selection in Finance
Hambuckers, julien ULiege; Heuchenne, Cédric ULiege

Conference (2014, April)

In this article, we propose a robust methodology to select the most appropriate error distribution candidate, in a classical multiplicative heteroscedastic model. In a first step, unlike to the ... [more ▼]

In this article, we propose a robust methodology to select the most appropriate error distribution candidate, in a classical multiplicative heteroscedastic model. In a first step, unlike to the traditional approach, we don't use any GARCH-type estimation of the conditional variance. Instead, we propose to use a recently developed nonparametric procedure (Mercurio and Spokoiny, 2004): the Local Adaptive Volatility Estimation (LAVE). The motivation for using this method is to avoid a possible model misspecification for the conditional variance. In a second step, we suggest a set of estimation and model selection procedures (Berk-Jones tests, kernel density-based selection, censored likelihood score, coverage probability) based on the so-obtained residuals. These methods enable to assess the global fit of a given distribution as well as to focus on its behavior in the tails. Finally, we illustrate our methodology on three time series (UBS stock returns, BOVESPA returns and EUR/USD exchange rates). [less ▲]

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See detailLikelihood based inference for semi-competing risks
Heuchenne, Cédric ULiege; Laurent, Stéphane ULiege; Legrand, Catherine et al

in Communications in Statistics : Simulation and Computation (2014), 43(5), 1112-1132

Detailed reference viewed: 65 (8 ULiège)
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See detailCox proportional hazard cure models with time-varying covariates
Heuchenne, Cédric ULiege

Conference (2014)

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See detailDouble Objective Economic Statistical Design of the VPT2 Control Chart: Wald’s identity approach
Faraz, Alireza ULiege; Heuchenne, Cédric ULiege; Saniga, Erwin et al

in Journal of Statistical Computation & Simulation (2014), 84

Recent studies have shown that applying the control chart by using a variable parameters (VP) scheme yields more rapid detection of assignable causes than the classical method of taking fixed sample sizes ... [more ▼]

Recent studies have shown that applying the control chart by using a variable parameters (VP) scheme yields more rapid detection of assignable causes than the classical method of taking fixed sample sizes at fixed intervals of time. In this paper, the problem of economical statistical design of the VP T2 control chart is considered as a double-objective minimization problem with the statistical objective adjusted average time to signal and the economic objective expected cost per hour. Then we strive to find the Pareto-optimal designs in which the two objectives are met simultaneously by using a multi-objective Genetic Algorithm or GA. Through an illustrative example, we show that relatively large benefits accrue to the VP method relative to the classical policy; further another advantage of our approach is to provide a list of alternative solutions that can be explored graphically. This then ensures flexibility and adaptability, an important attribute of contemporary control chart design. [less ▲]

Detailed reference viewed: 78 (10 ULiège)