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Predictability of HK-REITs returns using artificial neural network

Predictability of HK-REITs returns using artificial neural network The purpose of this paper is to determine if artificial neural network (ANN) works better than linear regression in predicting Hong Kong real estate investment trusts’ (REITs) excess return.Design/methodology/approachBoth ANN and the regression were applied in this study to forecast the Hong Kong REITs’ (HK-REITs) return using the capital asset pricing model and Fama and French’s three-factor models. Each result was further split into annual time series as a measure to investigate the consistency of the performance across time.FindingsANN had produced a better forecasting results than the regression based on their trading performance. However, the forecasting performance varied across individual REITs and time periods.Practical implicationsANN should be considered for use when one were to attempt forecasting the HK-REITs excess returns. However, the trading performance should be always compared with buy and hold strategy prior to make any investment decisions.Originality/valueThis paper tested the predicting power of ANN on the HK-REITs and the consistency of its predicting power. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Property Investment & Finance Emerald Publishing

Predictability of HK-REITs returns using artificial neural network

Loo, Wei Kang
Journal of Property Investment & Finance , Volume 38 (4): 17 – Jun 16, 2020
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Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
1463-578X
DOI
10.1108/jpif-07-2019-0090
Publisher site
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Abstract

The purpose of this paper is to determine if artificial neural network (ANN) works better than linear regression in predicting Hong Kong real estate investment trusts’ (REITs) excess return.Design/methodology/approachBoth ANN and the regression were applied in this study to forecast the Hong Kong REITs’ (HK-REITs) return using the capital asset pricing model and Fama and French’s three-factor models. Each result was further split into annual time series as a measure to investigate the consistency of the performance across time.FindingsANN had produced a better forecasting results than the regression based on their trading performance. However, the forecasting performance varied across individual REITs and time periods.Practical implicationsANN should be considered for use when one were to attempt forecasting the HK-REITs excess returns. However, the trading performance should be always compared with buy and hold strategy prior to make any investment decisions.Originality/valueThis paper tested the predicting power of ANN on the HK-REITs and the consistency of its predicting power.

Journal

Journal of Property Investment & Finance – Emerald Publishing

Published: Jun 16, 2020

Keywords: Investment; Artificial neural network; Real estate investment trust; Hong Kong REITs; Real estate investment; Return forecasting

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