References of "Heuchenne, Cédric"
     in
Bookmark and Share    
Full Text
Peer Reviewed
See detailVariable selection in proportional hazards cure model with time-varying covariates, application to US bank failures
Beretta, Alessandro ULiege; Heuchenne, Cédric ULiege

in Journal of Applied Statistics (in press)

From a survival analysis perspective, bank failure data are often characterized by small default rates and heavy censoring. This empirical evidence can be explained by the existence of a subpopulation of ... [more ▼]

From a survival analysis perspective, bank failure data are often characterized by small default rates and heavy censoring. This empirical evidence can be explained by the existence of a subpopulation of banks likely immune from bankruptcy. In this regard, we use a mixture cure model to separate the factors with an influence on the susceptibility to default from the ones affecting the survival time of susceptible banks. In this paper, we extend a semi-parametric proportional hazards cure model to time-varying covariates and we propose a variable selection technique based on its penalized likelihood. By means of a simulation study, we show how this technique performs reasonably well. Finally, we illustrate an application to commercial bank failures in the United States over the period 2006-2016. [less ▲]

Detailed reference viewed: 71 (15 ULiège)
Peer Reviewed
See detailReal Time Data-Driven Approaches for Credit Card Fraud Detection
Tran, Phuong Hanh; Tran, Kim Phuc; Thu Huong, Truong et al

in ICEBA 2018 Proceedings of the 2018 International Conference on E-Business and Applications (2018)

Detailed reference viewed: 61 (5 ULiège)
Peer Reviewed
See detailA Variable Sampling Interval EWMA Distribution-Free Control Chart for Monitoring Services Quality
Tran, Phuong Hanh; Tran, Kim Phuc; Thu Huong, Truong et al

in ICEBA 2018 Proceedings of the 2018 International Conference on E-Business and Applications (2018)

Detailed reference viewed: 25 (4 ULiège)
Full Text
Peer Reviewed
See detailAn exact method for designing Shewhart and S2 control charts to guarantee in-control performance
Faraz, Alireza ULiege; Heuchenne, Cédric ULiege; Saniga, Erwin

in International Journal of Production Research (2018), 56

Detailed reference viewed: 34 (4 ULiège)
Full Text
See detailEstimation from cross-sectional data under a semiparametric truncation model
De uña Alvarez, Jacobo; Heuchenne, Cédric ULiege; Laurent, Géraldine

E-print/Working paper (2018)

Detailed reference viewed: 24 (3 ULiège)
Full Text
See detailNonparametric regression with cross-sectional data: an alternative to conditional product-limit estimators
Heuchenne, Cédric ULiege; Laurent, Géraldine

E-print/Working paper (2018)

Detailed reference viewed: 12 (4 ULiège)
Full Text
Peer Reviewed
See detailStatistically Bundled Shewhart Control Charts for Monitoring Delivery Chains Systems
Foster, Earnest; Faraz, Alireza ULiege; Heuchenne, Cédric ULiege

in European Journal of Industrial Engineering (2018)

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 ▲]

Detailed reference viewed: 156 (16 ULiège)
See detailVariable selection in proportional hazards cure model with time-varying covariates, application to US bank failures
Beretta, Alessandro ULiege; Heuchenne, Cédric ULiege

Conference (2017, December 16)

From a survival analysis perspective, bank failures data exhibit heavy censoring rates, but defaults are rare events. This empirical evidence can be explained by the existence of a subpopulation of banks ... [more ▼]

From a survival analysis perspective, bank failures data exhibit heavy censoring rates, but defaults are rare events. This empirical evidence can be explained by the existence of a subpopulation of banks likely immune from bankruptcy. In this regard, we use a mixture cure model to separate the factors with an influence on the susceptibility to default from the ones affecting the survival time of susceptible banks. We extend a semi-parametric proportional hazards cure model to time-varying covariates and we propose a variable selection technique based on its penalized likelihood. By means of a simulation study, we show how this technique performs reasonably well. Finally, we illustrate an application to commercial bank failures in the United States over the period 2006-2016. [less ▲]

Detailed reference viewed: 61 (16 ULiège)
See detailVariable selection in proportional hazards cure model with time-varying covariates, application to bank failures
Beretta, Alessandro ULiege; Heuchenne, Cédric ULiege

Conference (2017, June)

In the last three decades, as a consequence of failures and corporate actions, the number of commercial banks in the United States has shrunk by two thirds. Empirical evidence in the analysis of bank ... [more ▼]

In the last three decades, as a consequence of failures and corporate actions, the number of commercial banks in the United States has shrunk by two thirds. Empirical evidence in the analysis of bank failures suggests the existence of banks which are not susceptible to default. For this reason, we use a semi-parametric proportional hazards cure model with time-varying covariates to study their effects either on the probability that a bank is susceptible to default and on the survival time of failed institutions. We propose a penalized maximum likelihood method for the selection of the most significant variables, using a Smoothly Clipped Absolute Deviation (SCAD) penalty. A simulation study shows that this procedure performs reasonably well. We apply this methodology to a quite large sample of United States commercial banks insured by the Federal Deposit Insurance Corporation (FDIC) and with more than 50 million dollars of total assets during the last quarter of 2002. More in detail, we use bank-specific covariates observed on a quarterly basis until the end of 2015, that we use as proxies for capital adequacy, asset quality, earnings, management efficiency, liquidity, cost structure and size. [less ▲]

Detailed reference viewed: 70 (7 ULiège)
Full Text
Peer Reviewed
See detailParametric conditional variance estimation in location- scale models with censored data
Heuchenne, Cédric ULiege; Laurent, Géraldine

in Electronic Journal of Statistics (2017), 11

Detailed reference viewed: 15 (0 ULiège)
Full Text
Peer Reviewed
See detailThe np Chart with Guaranteed In-control Average Run Lengths
Faraz, Alireza ULiege; Heuchenne, Cédric ULiege; Saniga, Erwin

in Quality and Reliability Engineering International (2017), 33(5), 1057--1066

Detailed reference viewed: 34 (1 ULiège)
Full Text
Peer Reviewed
See detailA robust statistical approach to select adequate error distributions for financial returns
Hambuckers, julien ULiege; Heuchenne, Cédric ULiege

in Journal of Applied Statistics (2017), 44(1), 137-161

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 ▲]

Detailed reference viewed: 106 (16 ULiège)
Full Text
Peer Reviewed
See detailThe np- Control Charts with the Guaranteed In-Control Performance
Faraz, Alireza ULiege; Heuchenne, Cédric ULiege

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 ▲]

Detailed reference viewed: 109 (1 ULiège)
Full Text
Peer Reviewed
See detailEstimating the out-of-sample predictive ability of trading rules: a robust bootstrap approach
Hambuckers, julien ULiege; Heuchenne, Cédric ULiege

in Journal of Forecasting (2016), 35(4), 347-372

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 ▲]

Detailed reference viewed: 88 (21 ULiège)
See detailModeling operational losses: a conditional Generalized Pareto regression based on a single-index assumption
Hambuckers, julien ULiege; Heuchenne, Cédric ULiege; 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 ▲]

Detailed reference viewed: 22 (2 ULiège)
See detailModeling operational losses: a conditional Generalized Pareto regression based on a single-index assumption
Hambuckers, julien ULiege; Heuchenne, Cédric ULiege; 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 ▲]

Detailed reference viewed: 27 (5 ULiège)
Full Text
Peer Reviewed
See detailA Statistically adaptive sampling policy to the Hotelling's T2 Control Chart: Markov Chain Approach
Seif, A.; Faraz, Alireza ULiege; Heuchenne, Cédric ULiege et al

in Communications in Statistics: Theory and Methods (2016)

Detailed reference viewed: 56 (9 ULiège)
Full Text
Peer Reviewed
See detailThe Robust Economic Statistical Design of the Hotelling’s T^2 Chart
Faraz, Alireza ULiege; Chalaki, Kamyar; Saniga, Erwin et al

in Communications in Statistics: Theory and 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 ▲]

Detailed reference viewed: 75 (8 ULiège)