Evaluation of the robusticity of mutual fund performance in Ghana using Enhanced Resilient Backpropagation Neural Network (ERBPNN) and Fast Adaptive Neural Network Classifier (FANNC)

Yushen Kong,Xuhua Hu,Micheal Owusu-Akomeah,Henry Asante Antwi,Patrick Acheampong

doi:10.1186/s40854-019-0125-5

Yushen Kong, Xuhua Hu + Show 3 more

Open Access

https://doi.org/10.1186/s40854-019-0125-5

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Journal: Financial Innovation	Publication Date: Feb 21, 2019
Citations: 11	License type: open-access

Affiliation: Jiangsu University

Abstract

Mutual fund investment continues to play a very important role in the world financial markets especially in developing economies where the capital market is not very matured and tolerant of small scale investors. The total mutual fund asset globally as at the end of 2016 was in excess of $40.4 trillion. Despite its success there are uncertainties as to whether mutual funds in Ghana obtain optimal performance relative to their counterparts in United States, Luxembourg, Ireland, France, Australia, United Kingdom, Japan, China and Brazil. We contribute to the extant literature on mutual fund performance evaluation using a collection of more sophisticated econometric models. We selected six continuous historical years that is 2010–2011, 2012–2013 and 2014–2015 to construct a mutual fund performance evaluation model utilizing the fast adaptive neural network classifier (FANNC), and to compare our results with those from an enhanced resilient back propagation neural networks (ERBPNN) model. Our FANNC model outperformed the existing models in terms of processing time and error rate. This makes it ideal for financial application that involves large volume of data and routine updates.

Highlights

Mutual fund investment has played a very important role in the world financial markets especially in developing economies where the capital market is not very matured and tolerant of small scale investors (Song et al 2017)
Inputs Instances This study focuses on the fund manager’s momentum strategies and herding behavior as the input variables applied in fast adaptive neural network classifier (FANNC) and enhanced resilient back propagation neural networks (ERBPNN)
It can be seen that RMSE from FANNC is significantly lower than those from ERBPNN, indicating the significant difference by a factor of two or three

Summary

Introduction

Mutual fund investment has played a very important role in the world financial markets especially in developing economies where the capital market is not very matured and tolerant of small scale investors (Song et al 2017). According to the Investment Company Institute, the total mutual fund asset globally as at the end of 2016 was in excess of $40.4 trillion. In the United States, mutual funds play an important role in U.S household finances. At the end of 2016, 22% of household financial assets (2019) 5:10 were held in mutual funds. Luxembourg and Ireland are the primary jurisdictions for the registration of UCITS funds. These funds may be sold throughout the European Union and in other countries that have adopted mutual recognition regimes (El Ghoul and Karoui 2017)

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