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Sequential smoothing for turning point detection with application to financial decisions

• Carlo Grillenzoni
• 2012

A fundamental problem in financial trading is the correct and timely identification of turning points in stock value series. This detection enables to perform profitable investment decisions, such as… (More)

Recursive Kernel Estimation of the Conditional Intensity of Nonstationary Point Processes

• Carlo Grillenzoni
• 2004

This paper develops adaptive nonparametric methods for analyzing seismic data. Kernel smoothing techniques are suitable for space-time point processes; however, they must be adapted to deal with the… (More)

Comparison of sequential monitoring methods for environmental time series with stochastic cycle

• Carlo Grillenzoni
• Environmental and Ecological Statistics
• 2013

The paper compares recursive methods for detecting change points in environmental time series. Timely identification of peaks and troughs is important for planning defense actions and preventing… (More)

Performance of adaptive estimators in slowly varying parameter models

• Carlo Grillenzoni
• Statistical Methods and Applications
• 2008

Design of Blurring Mean-Shift Algorithms for Data Classification

• Carlo Grillenzoni
• J. Classification
• 2016

Evaluation of on-line trading systems: Markov-switching vs time-varying parameter models

• Michele Fornaciari, Carlo Grillenzoni
• Decision Support Systems
• 2017

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