References of "Heuchenne, Cédric"
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See detailA Simple Method for Designing Shewhart X ̅ and S2 Control Charts to Guarantee the In-Control Performance
Faraz, Alireza ULg; Heuchenne, Cédric ULg; Woodall, Bill

E-print/Working paper (in press)

The in-control performance of the Shewhart X ̅ and S2 control charts with estimated in-control parameters has been evaluated by a number of authors. Results indicate an unrealistically large amount of ... [more ▼]

The in-control performance of the Shewhart X ̅ and S2 control charts with estimated in-control parameters has been evaluated by a number of authors. Results indicate an unrealistically large amount of Phase I data is needed to have the desired in-control average run length (ARL) value in Phase II. To overcome this problem, it has been recommended that the control limits be adjusted based on a bootstrap method to guarantee that the in-control ARL is at least a specified value with a certain specified probability. In our paper we present simple formulas for the required control limits so that practitioners do not have to use the bootstrap method. An assumption of normality is required. The advantage of our proposed method is in its simplicity; there is no bootstrapping and the control chart constants do not depend on the Phase I sample data. [less ▲]

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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 ULg; Heuchenne, Cédric ULg; 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 ULg; Heuchenne, Cédric ULg; 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 detailA semiparametric model for Generalized Pareto regression based on a dimension reduction assumption
Hambuckers, julien ULg; Heuchenne, Cédric ULg; 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 ▲]

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See detailIdentifying the best technical trading rule: a .632 bootstrap approach.
Hambuckers, julien ULg; Heuchenne, Cédric ULg

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 detailThe Robust Economic Statistical Design of the Hotelling’s T^2 Chart
Faraz, Alireza ULg; Chalaki, Kamyar; Saniga, Erwin et al

in Communications in Statistics : Theory & Methods (2014)

Economic statistical designs aim at minimizing the cost of process monitoring when a specific scenario or a set of estimated process and cost parameters is given. However, in practical situations the ... [more ▼]

Economic statistical designs aim at minimizing the cost of process monitoring when a specific scenario or a set of estimated process and cost parameters is given. However, in practical situations the process may be affected by more than one scenario which may lead to severe cost penalties for upsetting the true scenario. This paper presents the robust economic statistical design (RESD) of the T^2 chart to reduce the monetary losses when there are multiple distinct scenarios. The genetic algorithm optimization method is employed here to minimize the total expected monitoring cost across all distinct scenarios. Through two numerical examples the proposed method is illustrated. Simulation studies indicate that the robust economic statistical designs should be encouraged in practice. [less ▲]

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

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 ULg; Heuchenne, Cédric ULg; Seif, Asghar

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

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

in Quality and Reliability Engineering International (2014)

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

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 detailStatistically Bundled Shewhart Control Charts for Monitoring Delivery Chains Systems
Foster, Earnest; Faraz, Alireza ULg; Heuchenne, Cédric ULg

E-print/Working paper (2014)

Continuous monitoring of Delivery Time variables by means of control charts in a delivery chain is a very recent application of Statistical Process Control (SPC) to the service sector. The aim of the ... [more ▼]

Continuous monitoring of Delivery Time variables by means of control charts in a delivery chain is a very recent application of Statistical Process Control (SPC) to the service sector. The aim of the proposed method is to provide supply chain decision makers with an easy to be managed tool monitoring the current functioning state of the delivery chain. The implementation of SPC control charts makes it possible to limit over-corrections to false alarm conditions and to maintain at an acceptable level the safety stock, with a consequent reduction of the overall management costs of the delivery chain. An illustrative example shows the proposed control chart implementation in a real delivery chain. [less ▲]

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See detailDouble Objective Economic Statistical Design of the VPT2 Control Chart: Wald’s identity approach
Faraz, Alireza ULg; Heuchenne, Cédric ULg; 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 ▲]

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

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

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See detailEstimation of the error distribution in nonparametric regression with cross-sectional data
Heuchenne, Cédric ULg; Laurent, Géraldine ULg

E-print/Working paper (2014)

In this article, we study the nonparametric regression model Y=m(X)+varepsilon where m(x)=E[Y|X=x] and sigma²(x)=Var[varepsilon|X=x] are unknown smooth functions, and the error varepsilon has zero mean ... [more ▼]

In this article, we study the nonparametric regression model Y=m(X)+varepsilon where m(x)=E[Y|X=x] and sigma²(x)=Var[varepsilon|X=x] are unknown smooth functions, and the error varepsilon has zero mean and finite variance conditionally on X=x. The problem consists in estimating the cumulative distribution function of the error in a nonparametric way when the couple (X,Y) is obtained by cross-sectional sampling while the positive response Y can be right-censored. We propose a new estimator for the error distribution function based on the estimators of m(.) and sigma²(.) described in Heuchenne and Laurent 2014. A bootstrap procedure is developed to solve the critical problem of the smoothing parameter choice. We assess the performance of the proposed estimator through simulations. Finally, a data set based on the mortality of diabetics is analyzed. (Heuchenne Cédric and Laurent Géraldine, Nonparametric regression with cross-sectional data: an alternative to conditional product-limit estimators, 2014) [less ▲]

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See detailParametric conditional variance estimation in location-scale models with censored data
Heuchenne, Cédric ULg; Laurent, Géraldine ULg

E-print/Working paper (2014)

Suppose the random vector (X,Y) satisfies the regression model Y=m(X)+sigma(X)*varepsilon, where m(.)=E(Y|.), sigma²(.)=Var(Y|.) belongs to some parametric class {sigma _theta(.): theta in Theta} and ... [more ▼]

Suppose the random vector (X,Y) satisfies the regression model Y=m(X)+sigma(X)*varepsilon, where m(.)=E(Y|.), sigma²(.)=Var(Y|.) belongs to some parametric class {sigma _theta(.): theta in Theta} and varepsilon is independent of X. The response Y is subject to random right censoring and the covariate X is completely observed. A new estimation procedure is proposed for sigma_theta(.) when m(.) is unknown. It is based on nonlinear least squares estimation extended to conditional variance in the censored case. The consistency and asymptotic normality of the proposed estimator are established. The estimator is studied via simulations and an important application is devoted to fatigue life data analysis. [less ▲]

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See detailNonparametric regression with cross-sectional data: an alternative to conditional product-limit estimators
Heuchenne, Cédric ULg; Laurent, Géraldine ULg

E-print/Working paper (2014)

Suppose the random vector (X,Y) satisfies the nonparametric regression model Y=m(X)+varepsilon, where m(x)=E[Y|X=x] and sigma²(x)=Var[varepsilon|X=x] are unknown smooth functions and the error varepsilon ... [more ▼]

Suppose the random vector (X,Y) satisfies the nonparametric regression model Y=m(X)+varepsilon, where m(x)=E[Y|X=x] and sigma²(x)=Var[varepsilon|X=x] are unknown smooth functions and the error varepsilon has zero mean and finite variance conditionally on X=x. The pair (X,Y) is obtained by cross-sectional sampling involving left-truncated and right-censored responses. The considered model is completely nonparametric but the conditional truncation distribution is assumed to be known. The novelty of this work is twofold: first, it extends the results on cross-sectional data to the conditional case and second, it generalizes the length bias results in the conditional case to right censoring and to any truncation distribution. New estimators for m(.) and sigma²(.) are constructed and relevant tools are used to quickly provide the main asymptotic properties for this kind of estimators. Extensive simulations are carried out and show that the new estimators outperform classical nonparametric estimators for left-truncated and right-censored data (when the truncation model is known). Finally, a data set on the mortality of diabetics is analyzed. [less ▲]

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