Performance Evaluation of Fund Portfolios Constucted by Artificial Neural Network

• Main Authors: Zu-Chung Wang, 王子銓
• Other Authors: Chin-Sheng Haung
• Format: Others
• Language: zh-TW
• Published: 2008
• Online Access: http://ndltd.ncl.edu.tw/handle/10645166925458239651

碩士 === 雲林科技大學 === 財務金融系碩士班 === 96 === Nowdays it is not easy for fund investors to make investment decisions when cofronting wide varieties of fund catalogs.However, as pointed out by plenty of empirical researches in finance that artificial neural networks can have competent capacity in constructing investment portfolios when comparing to more traditional portfolio construction.This article mainly adopts more flexible artificial neural networks to construct fund of funds in Taiwan mutual fund market. The fund of funds construction of this study consists of a two- step procedure. The first step takes Arnott (2004) fundamental index to select the components of the funnd.Then the historical returns of funds using AR 4 form are fed into the feedforward three layers artifical neural network to forecaste the returns of componet funds.Specifically, AR 4 integrated with neural newtowrks is trained in thirty-six months retruns data to forecaste the thirty-seven monthly return of the underlying fund.The procedure is moving forward in one-month window through thirty-six months (three years) forecasting period. The empirical results drawn from this study are as follows. (1).Four types of funds of funds constructed in this study are superior to TAIEX and Taiwan 50 Index. (2)The size of the four funds of funds in this study does not significantly affect the relevant returns. (3) However, the size of the four funds of funds does exhibit inverse relation assicaited with their volatility. (4)In short, the neural networks construction funds of this study in general can not render any excess returns after risk-adjusting.