Generalized exponential moving average (EMA) model with particle filtering and anomaly detection

作者：

Highlights：

• We propose a new exponential moving average (EMA) model in a state space framework.

• We develop 3 anomaly detectors with a particle filter used for investment decision.

• We implement investment analysis with our method by using global asset price data.

• Our scheme outperforms practically well-known strategies including standard EMAs.

摘要

•We propose a new exponential moving average (EMA) model in a state space framework.•We develop 3 anomaly detectors with a particle filter used for investment decision.•We implement investment analysis with our method by using global asset price data.•Our scheme outperforms practically well-known strategies including standard EMAs.

论文关键词：Particle filtering,Anomaly detection,Exponential moving averages,Stochastic volatility,State space models,Global financial assets

论文评审过程：Received 15 September 2016, Revised 19 November 2016, Accepted 23 December 2016, Available online 28 December 2016, Version of Record 6 January 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2016.12.034