29 publications classées par:
type de publication
: Revue avec comité de lecture
Articles Abaunza F. Chavez-Demoulin V. Hameri A.-P. Niemi T. (in press). Do Flow Principles of Operations Management Apply to Computing Centers?. Production Planning & Control.
Chavez-Demoulin V. Embrechts P. Hofert M. (in press). An extreme value approach for modeling Operational Risk losses depending on covariates. Journal of Risk and Insurance.
Vatter T. & Chavez-Demoulin V. (2015). Generalized Additive Models for Conditional Dependence Structures. Journal of Multivariate Analysis, 141, 147-167.
Chavez-Demoulin V., Embrechts P. & Sardy S. (2014). Extreme-quantile tracking for financial time series. Journal of Econometrics, 181(1), 44-52. [doi] [url] [abstract]
Time series of financial asset values exhibit well-known statistical features such as heavy tails and volatility clustering. We propose a nonparametric extension of the classical Peaks-Over-Threshold method from extreme value theory to fit the time varying volatility in situations where the stationarity assumption may be violated by erratic changes of regime, say. As a result, we provide a method for estimating conditional risk measures applicable to both stationary and nonstationary series. A backtesting study for the UBS share price over the subprime crisis exemplifies our approach.
de Treville S. Bicer I. Chavez-Demoulin V. Hagspiel V. Schurhoff N. Tasserit C. & Wager S. (2014). Valuing lead time. Journal of Operations Management, 32(6), 337-346.
Appelqvista P., Chavez-Demoulin V., Hameri A.-P., Heikkiläc J. & Wautersa V. (2013). Turnaround across diverse global supply chains using shared metrics and change methodology: The Case of Amer Sports Corporation. International Journal of Operations and Production Management, 33(5), 622-647. [doi] [url] [abstract]
Purpose - The purpose of this paper is to document the outcome of a global three-year long supply chain improvement initiative at a multi-national producer of branded sporting goods that is transforming from a holding structure to an integrated company. The case company is comprised of seven internationally well-known sport brands, which form a diverse set of independent sub-cases, on which the same supply chain metrics and change project approach was applied to improve supply chain performance.¦Design/methodology/approach - By using in-depth case study and statistical analysis the paper analyzes across the brands how supply chain complexity (SKU count), supply chain type (make or buy) and seasonality affect completeness and punctuality of deliveries, and inventory as the change project progresses.¦Findings - Results show that reduction in supply chain complexity improves delivery performance, but has no impact on inventory. Supply chain type has no impact on service level, but brands with in-house production are better in improving inventory than those with outsourced production. Non-seasonal business units improve service faster than seasonal ones, yet there is no impact on inventory.¦Research limitations/implications - The longitudinal data used for the analysis is biased with the general business trend, yet the rich data from different cases and three-years of data collection enables generalizations to a certain level.¦Practical implications - The in-depth case study serves as an example for other companies on how to initiate a supply chain improvement project across business units with tangible results.¦Originality/value - The seven sub-cases with their different characteristics on which the same improvement initiative was applied sets a unique ground for longitudinal analysis to study supply chain complexity, type and seasonality.
Chavez-Demoulin V. & Davison A. C. (2012). Modelling time series extremes. REVSTAT - Statistical Journal, 10(1), 109-133. [url] [abstract]
The need to model rare events of univariate time series has led to many recent advances in theory and methods. In this paper, we review telegraphically the literature on extremes of dependent time series and list some remaining challenges.
Chavez-Demoulin V. & McGill J. A. (2012). High-frequency financial data modeling using Hawkes processes. Journal of Banking and Finance, 36(12), 3415-3426. [doi] [url] [abstract]
Intraday Value-at-Risk (VaR) is one of the risk measures used by market participants involved in high-frequency trading. High-frequency log-returns feature important kurtosis (fat tails) and volatility clustering (extreme log-returns appear in clusters) that VaR models should take into account. We propose a marked point process model for the excesses of the time series over a high threshold that combines Hawkes processes for the exceedances with a generalized Pareto distribution model for the marks (exceedance sizes). The conditional approach features intraday clustering of extremes and is used to calculate instantaneous conditional VaR. The models are backtested on real data and compared to a competitor approach that proposes a nonparametric extension of the classical peaks-over-threshold method. Maximum likelihood estimation is computationally intensive; we use a differential evolution genetic algorithm to find adequate starting values for the optimization process.
Chavez-Demoulin V., Davison A. C. & Frossard L. (2011). Discussion of the paper: Threshold modelling of spatially dependent non-stationary extremes with application to hurricane-induced wave heights. Environmetrics, 22(7), 810-816. [doi] [url]
Chavez-Demoulin V. & Embrechts P. (2011). Operational risk. Encyclopedia of Quantitative Finance. [doi] [url] [abstract]
Under the capital requirements of the Basel II regime, banks have to provide estimates of their operational risk on a yearly basis and, for larger international banks, use a Value-at- Risk estimate at the confidence level of 99.9%. The so-called loss distribution approach (LDA) allows for broad methodological flexibility for the estimation of this risk capital. In this article, we discuss some of the underlying statistical issues.
Chavez-Demoulin V. & Embrechts P. (2010). Revisiting the edge, ten years on. Communications in Statistics - Theory and Methods, 39(8-9), 1674-1688. [doi] [url] [abstract]
When these lines are written, it is January 21, 2008, a further "Black Monday" on the international markets. Stock indices have fallen between 5 and 10%. Which statistical tools help in describing such events and may help in understanding the consequences? In this article we update our knowledge on the modeling of extremal events, in particular with a view toward applications to finance, insurance, and risk management.
Chavez-Demoulin V. & Embrechts P. (2010). Copulas in insurance. Encyclopedia of Quantitative Finance, 379-382. [doi] [url] [abstract]
The modeling of dependence has increasingly become one of the key issues in insurance. We highlight the use as well as the misuse of the concept of copula in this context. The main themes are the use of copula methodology in quantitative risk management and actuarial ruin theory.
Chavez-Demoulin V., Embrechts P. & Neslehova J. (2006). Infinite mean models and the LDA for operational risk. Journal of Operational Risk, 1(1), 3-25.
Chavez-Demoulin V., Embrechts P. & Neslehova J. (2006). Quantitative models for operational risk: extremes, dependence and aggregation. Journal of Banking and Finance, 30(10), 2635-2658. [doi] [url] [abstract]
Due to the new regulatory guidelines known as Basel II for banking and Solvency 2 for insurance, the financial industry is looking for qualitative approaches to and quantitative models for operational risk. Whereas a full quantitative approach may never be achieved, in this paper we present some techniques from probability and statistics which no doubt will prove useful in any quantitative modelling environment. The techniques discussed are advanced peaks over threshold modelling, the construction of dependent loss processes and the establishment of bounds for risk measures under partial information, and can be applied to other areas of quantitative risk management.
Chavez-Demoulin V. & Davison A. C. (2005). Generalized additive modelling of sample extremes. Journal of the Royal Statistical Society; Series C (Applied Statistics), 54(1), 207-222. [doi] [url] [abstract]
We describe smooth non-stationary generalized additive modelling for sample extremes, in which spline smoothers are incorporated into models for exceedances over high thresholds. Fitting is by maximum penalized likelihood estimation, with uncertainty assessed by using differences of deviances and bootstrap simulation. The approach is illustrated by using data on extreme winter temperatures in the Swiss Alps, analysis of which shows strong influence of the north Atlantic oscillation. Benefits of the new approach are flexible and appropriate modelling of extremes, more realistic assessment of estimation uncertainty and the accommodation of complex dependence patterns.
Chavez-Demoulin V., Davison A. C. & McNeil A. J. (2005). Estimating value-at-risk: a point process approach. Quantitative Finance, 5(2), 227-234. [doi] [url] [abstract]
We consider the modelling of extreme returns in financial time series, and introduce a marked point process model for the exceedances of a high threshold. This model has a self-exciting, Hawkes-process structure in which recent events affect the current intensity of threshold exceedances more than distant ones. Estimates of value-at-risk are derived for real datasets and the success of the estimation method is evaluated in backtests.
Chavez-Demoulin V. & Embrechts P. (2004). Smooth extremal models in finance and insurance. Journal of Risk and Insurance, 71(2), 183-199. [doi] [url] [abstract]
This article describes smooth nonstationary generalized additive modeling for sample extremes, in which spline smoothers are incorporated into models for exceedances over high thresholds. We summarize the smoothing methodology as a new tool for practical extreme value exploration in finance and insurance.
Chavez-Demoulin V., Embrechts P. & Roehrl A. (2002). A statistical analysis of the share price of the SAIR group (1996-2001) from a risk manager's point of view. Derivatives Use Trading and Regulation, 8(2), 105-122. [abstract]
Over recent years, extreme value theory (EVT). has been used in order to analyse statistically financial data showing clear non~normal behaviour Several examples in the areas of market, credit and operational risk have been discussed. This paper loo oks at the particular case of Swissair and quantifies, using EVT, the extremal behaviour of the returns. For this, the paper goes beyond traditional EVT and introduces new methodology such as smoothing and more advanced maximum likelihood techniques.
Chavez-Demoulin V. (1999). Bayesian inference for small-sample capture-recapture data. Biometrics, 55(3), 727-731. [doi] [abstract]
We consider data on the survival of a population of Cephalorhynchus hectori, Hector's dolphins, in a marine area of New Zealand. To estimate survival probabilities of animal populations, a multiple capture-recapture sampling scheme can be used. In this paper, we propose a practical methodology to derive approximations to posterior distributions based on Laplace methods. We show how to calculate Bayes estimates and credible intervals in this setting.
Compte-rendu Chavez-Demoulin V., Das B. & Embrechts P. (2010). Probabilistic Analysis of flooding at Murgenthal for Kernkraft-Goesgen Daeniken (KKG). RiskLab internal report.
Vulgarisation Chavez-Demoulin V. (2004). Was ist Extremwerttheorie ?. Risknews.
Chavez-Demoulin V. & Roehrl A. (2004). EVT can save your neck (?). Bulletin of Swiss Statistical Society.
Chavez-Demoulin V., Roehrl A. S. A., Roehrl R. A. & Schmiedl S. W. (2002). Datamining mit R. Linux-Enterprise, 2.
Chavez-Demoulin V., Weinberg A., Berezka V., Roehrl A. & Schmiedl S. W. (2002). Risk reduction : Transparent real-time enterprise. Banks and Technologies, 9.
Parties de livre
Chapitre Chavez-Demoulin V. & Embrechts P. (2011). An EVT primer for credit risk. In Lipton, A. & Rennie, A. (Ed.), The Oxford Handbook of Credit Derivatives (pp. 500-532). Oxford University Press.
Sardy S., Bilat C., Tseng P. & Chavez-Demoulin V. (2002). A comparison between L1 Markov random field-based and wavelet-based estimators. In Dodge Y. (Ed.), Statistical Data Analysis Based on the L1-Norm and Related Methods (pp. 395-404). Birkhäuser Verlag.
Actes de conférence (partie) Chavez-Demoulin V., Jarvis S., Perera R., Roehrl A., Schmiedl S. & M.P. Sondergaard (2003). Extreme Datamining. In Schader M., Gaul W. & Vichi M. (Eds.), Proceedings of the 26th Annual Conference of the Gesellschaft für Klassifikation e.V., University of Mannheim, July 2002, Between Data Science and Applied Data Analysis (pp. 387-394). Springer.
Rapports Chavez-Demoulin V. & Davison A. C. (2010). Statistics of hydrological extreme values : Exploratory analysis, modelling and recommendations. Bundesamt für Umwelt.
Thèses Chavez-Demoulin V., Davison A. C. (Dir.) (1999). Two Problems in Environmental Statistics : Capture-Recapture Analysis and Smooth Extremal models. EPFL.