Robustify Financial Time Series Forecasting with Bagging

Robustify Financial Time Series Forecasting with Bagging

In this paper we propose a revised version of (bagging) bootstrap aggregating as a forecast combination method for the out-of-sample forecasts in time series models. The revised version explicitly takes into account the dependence in time series data and can be used to justify the validity of baggin...

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Bibliographic Details
Main Authors: JIN, Sainan, SU, Liangjun, ULLAH, Aman
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2014
Subjects:
Bagging
Combined forecasts
Nonparametric Models
Predictability
Time Series
Econometrics
Online Access:https://ink.library.smu.edu.sg/soe_research/1428
https://ink.library.smu.edu.sg/context/soe_research/article/2427/viewcontent/RobustifyFinancialTimeSeriesForecastingBagging_2014.pdf
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Institution: Singapore Management University
Language: English

Internet

https://ink.library.smu.edu.sg/soe_research/1428
https://ink.library.smu.edu.sg/context/soe_research/article/2427/viewcontent/RobustifyFinancialTimeSeriesForecastingBagging_2014.pdf

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