References of "Heuchenne, Cédric"
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See detailA robust statistical approach to select adequate error distributions for financial returns
Hambuckers, julien ULg; Heuchenne, Cédric ULg

in Journal of Applied Statistics (in press)

In this article, we propose a robust statistical approach to select an appropriate error distribution, in a classical multiplicative heteroscedastic model. In a first step, unlike to the traditional ... [more ▼]

In this article, we propose a robust statistical approach to select an appropriate error distribution, 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 set of distributions as well as to focus on their behavior in the tails, giving us the capacity to map the strengths and weaknesses of the candidate distributions. A bootstrap procedure is provided to compute the rejection regions in this semiparametric context. Finally, we illustrate our methodology throughout a small simulation study and an application on three time series of daily returns (UBS stock returns, BOVESPA returns and EUR/USD exchange rates) [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

in Journal of Forecasting (in press)

In this paper, we provide a novel way to estimate the out-of-sample predictive ability of a trading rule. Usually, this ability is estimated using a sample splitting scheme, true out-of-sample data being ... [more ▼]

In this paper, we provide a novel way to estimate the out-of-sample predictive ability of a trading rule. Usually, this ability is estimated using a sample splitting scheme, true out-of-sample data being rarely available. We argue that this method makes a poor use of the available data and creates data mining possibilities. Instead, we introduce an alternative .632 bootstrap approach. This method enables to build in- sample and out-of-sample bootstrap datasets that do not overlap but exhibit the same time dependencies. We show in a simulation study that this technique drastically reduces the mean squared error of the estimated predictive ability. We illustrate our methodology on IBM, MSFT and DJIA stock prices, where we compare 11 trading rules speci cations. For the considered datasets, 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 np- Control Charts with the Guaranteed In-Control Performance
Faraz, Alireza ULg; Heuchenne, Cédric ULg

E-print/Working paper (2016)

In this paper, we evaluate the in-control performance of np-control charts with estimated parameters. We then apply the bootstrap method to adjust the control charts’ limits to guarantee the desired in ... [more ▼]

In this paper, we evaluate the in-control performance of np-control charts with estimated parameters. We then apply the bootstrap method to adjust the control charts’ limits to guarantee the desired in-control average run length (ARL0) value in monitoring stage. The adjusted limits ensure that ARL0 would take a value greater than the desired value (say, B) with a certain specified probability, that is Pr⁡(ARL_0>B)=1-ρ. We finally provide users with tables which with practitioners do not need to do bootstrapping Phase I data set to obtain the control limit thresholds. [less ▲]

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

in European Journal of Industrial Engineering (2016)

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 detailAn Exact Method for Designing Shewhart X ̅ and S2 Control Charts to Guarantee the In-Control Performance
Faraz, Alireza ULg; Heuchenne, Cédric ULg

in Journal of Quality Technology (2016)

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 detailModeling operational losses: a conditional Generalized Pareto regression based on a single-index assumption
Hambuckers, julien ULg; Heuchenne, Cédric ULg; Lopez, Olivier

Scientific conference (2016, March 09)

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 one are too rough to correctly fit to the data. We propose an iterative algorithm in order to perform their practical implementation. Our results are supported by some simulations. To illustrate the proposed approach, the method is applied to a novel database of operational losses from the bank UniCredit [less ▲]

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See detailModeling operational losses: a conditional Generalized Pareto regression based on a single-index assumption
Hambuckers, julien ULg; Heuchenne, Cédric ULg; Lopez, Olivier

Scientific conference (2016, February 24)

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 one are too rough to correctly fit to the data. We propose an iterative algorithm in order to perform their practical implementation. Our results are supported by some simulations. To illustrate the proposed approach, the method is applied to a novel database of operational losses from the bank UniCredit [less ▲]

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See detailA Statistically adaptive sampling policy to the Hotelling's T2 Control Chart: Markov Chain Approach
Seif, A.; Faraz, Alireza ULg; Heuchenne, Cédric ULg et al

in Communications in Statistics : Theory & Methods (2016)

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See detailConditional portfolio allocation: Does aggregate market liquidity matter?
Bazgour, Tarik ULg; Heuchenne, Cédric ULg; Sougné, Danielle ULg

in Journal of Empirical Finance (2016), 35

This paper investigates how aggregate liquidity influences optimal portfolio allocations across various US characteristic portfolios. We consider short-term allocation problems, with single and multiple ... [more ▼]

This paper investigates how aggregate liquidity influences optimal portfolio allocations across various US characteristic portfolios. We consider short-term allocation problems, with single and multiple risky assets, and use the nonparametric approach of Brandt (1999) to directly express optimal portfolio weights as functions of aggregate liquidity shocks. We find, first, that the effect of aggregate liquidity is positive and decreasing with the investment horizon. Second, at daily and weekly horizons, this effect is weaker on allocations in large stocks and gets stronger as we move toward small stocks, regardless of the other stock characteristics, suggesting that liquidity is the main concern of very short-term investors. Third, conditional allocations in risky assets decrease and exhibit shifts toward more liquid assets as aggregate liquidity worsens. Overall, conditioning on aggregate liquidity yields empirical results that are consistent with the so-called flight-to-safety and flight-to-liquidity episodes. Finally, we propose a simple tactical investment strategy and show how aggregate liquidity information can be exploited to enhance the out-of-sample performance of long-term strategies. [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 (2016)

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 detailNonparametric control charts: economic statistical design
Marcos Alvarez, Alejandro ULg; Heuchenne, Cédric ULg; Faraz, Alireza ULg

E-print/Working paper (2016)

This paper studies economic statistical designs (ESD) for nonparametric control charts based on the sign and Wilcoxon tests. The main advantage of the procedures is that, except for the tested location ... [more ▼]

This paper studies economic statistical designs (ESD) for nonparametric control charts based on the sign and Wilcoxon tests. The main advantage of the procedures is that, except for the tested location parameter, they do not use either any parametric distribution for the quality characteristic or any information about the possible involved parameters, neither in the in-control nor in the out-of-control state. This is made possible by minimizing a cost function specified independently of these quantities. Unlike the ESD for the $\overline{x}$ chart, the resulting charts designs are robust to changes of the distributions of the observations (in control or out of control), provide reliable statistical guarantees when the $\overline{x}$ chart ESD does not and stay competitive even when the strong assumptions of the $\overline{x}$ chart ESD are fully satisfied. These new techniques can therefore be applied to a definitely wider class of problems and their designs may stay constant over time without losing performance. [less ▲]

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See detailModeling the dependence between extreme operational losses and economic factors: a conditional semi-parametric Generalized Pareto approach
Hambuckers, julien ULg; Heuchenne, Cédric ULg; Lopez, Olivier

Conference (2015, December)

In this paper, we model the severity distribution of operational losses data, condi- tional on some covariates. Indeed, previous studies [Chernobai et al., 2011, Cope et al., 2012, Chavez-Demoulin et al ... [more ▼]

In this paper, we model the severity distribution of operational losses data, condi- tional on some covariates. Indeed, previous studies [Chernobai et al., 2011, Cope et al., 2012, Chavez-Demoulin et al., 2014a] suggest that this distribution might be in uenced by macroeconomic and rm-speci c factors. We introduce a conditional Generalized Pareto model, where the shape parameter is an unknown function of a linear combina- tion of the covariates. More precisely, we rely on a single-index assumption to perform a dimension reduction that enables to use univariate nonparametric techniques. Hence, we su er neither from too strong parametric assumption nor from the curse of dimen- sionality. Then, we develop an iterative approach to estimate this model, based on the maximisation of a semiparametric likelihood function. Finally, we apply this method- ology on a novel database provided by the bank UniCredit. We use rm-speci c factors to estimate the conditional shape parameter of the severity distribution. Our analysis suggests that the leverage ratio of the company, the proportion of the revenue coming from fees as well as the risk category have an important impact on the tail thickness of this distribution and thus on the probability of su ering from large operational losses. [less ▲]

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See detailShewhart Control Charts with Guaranteed In-Control Performance
Faraz, Alireza ULg; Heuchenne, Cédric ULg; Woodall, W.H.

Conference (2015, July 08)

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 ▲]

Detailed reference viewed: 41 (2 ULg)
See detailMonitoring supply chains with multivariate control charts: an economic-statistical design approach
Heuchenne, Cédric ULg; Faraz, Alireza ULg; Saniga, Erwin

Scientific conference (2015, June 02)

Detailed reference viewed: 23 (1 ULg)
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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 detailEstimation of the error distribution in a semiparametric transformation model.
Heuchenne, Cédric ULg; Samb, Rawane; Van Keilegom, Ingrid

in Electronic Journal of Statistics (2015), 9

Detailed reference viewed: 13 (3 ULg)
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See detailEstimating the error distribution function of a heteroskedastic nonparametric regression of cure model data
Chown, Justin; Heuchenne, Cédric ULg; Van Keilegom, Ingrid

Conference (2015)

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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 (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 ▲]

Detailed reference viewed: 68 (2 ULg)