Adaptively truncated maximum likelihood regression with asymmetric errors

Marazzi, Alfio; Yohai, Vı́ctor J.

doi:10.1016/j.jspi.2003.06.011

Cited by 52 publications

(55 citation statements)

References 9 publications

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“…Two recent papers focus on robust estimation (Marazzi and Barbati, 2003 and Marazzi and Yohai, 2004) and develop robust estimates for locationscale models on the log-scale which can be used for typical data on health care expenditures. Their work is based on a truncated maximum likelihood regression where the errors are allowed to have asymmetric distribution (e.g.…”

Section: Introductionmentioning

confidence: 99%

A robust approach for skewed and heavy-tailed outcomes in the analysis of health care expenditures

Cantoni

Ronchetti

2006

Journal of Health Economics

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Section: Introductionmentioning

confidence: 99%

A robust approach for skewed and heavy-tailed outcomes in the analysis of health care expenditures

Cantoni

Ronchetti

2006

Journal of Health Economics

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“…As an alternative to the OLS and ML estimators, Boudt, Croux, and Laurent (2011b) propose using the Truncated Maximum Likelihood (TML) estimator introduced by Marazzi and Yohai (2004). This estimator gives a zero weight to outliers, as defined by the value of the ML loss function evaluated at the corresponding residual computed under the robust non-parametric estimatorf WSD in (4.6).…”

Section: Parametric Estimation Of Periodicitymentioning

confidence: 99%

“…Observations for which ρ ML (u WSD t,i ) is large, have a low likelihood and are therefore likely to be outliers (Marazzi and Yohai, 2004). Denote q an extreme upper quantile of the distribution of u t,i .…”

Section: Parametric Estimation Of Periodicitymentioning

confidence: 99%

Econometric Modeling of Exchange Rate Volatility and Jumps

2012

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This chapter reviews the rapid advances in foreign exchange volatility modeling made in the last three decades. Academic researchers have sought to fit the three major characteristics of foreign exchange volatility: intraday periodicity, autocorrelation and discontinuities in prices. Early research modeled the autocorrelation in daily and weekly squared foreign exchange returns with ARCH/GARCH models. Increased computing power and availability of high-frequency data allowed later researchers to improve volatility and jumps estimates. Researchers also found it useful to incorporate information about periodic volatility patterns and macroeconomic announcements in their calculations. This article details these volatility and jump estimation methods, compares those methods empirically and provides some suggestions for further research.

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“…SenGupta and Ugwuowo (2006) showed that many circular distributions are also asymmetrically distributed. Regression models using asymmetric error distributions appear in Bianco et al (2005) and Marazzi and Yohai (2002). Bianco et al (2005) introduces a regression model that is a natural extension of the method of moment estimates for ordinary regression and discusses their asymptotic properties.…”

Section: Introductionmentioning

confidence: 99%