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

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.

An Empirical Analysis of the Impact of Fund Manager's Personal Characteristics on Fund Performance

A great deal of research found that fund performance is related to a series of personal characteristics of fund managers,but how these personal characteristics affect fund performance is still unknown.China is the most important emerging country and the second largest economy in the world.The development of China's capital market is different from that of most developed countries.Therefore,empirical evidence on the performance of funds in developed countries often cannot be extended to the Chinese market.In addition,there is evidence that many successful fund managers in developed countries may not achieve good performance in China.Therefore,it is particularly meaningful to examine the determinants of fund performance in the Chinese market.This paper establishes a three-level framework model to study this connection.Considering return and risk,the two basic factors that affect fund performance,this paper chooses nine proxy variables:Sharpe ratio,Jensen index,Treynor index,abnormal return(α),total risk(β),non-systemic risk,standard deviation of return,stock choosing ability and time picking ability as the criteria to measure the comprehensive performance.This paper investigates China's open-end funds to fill the gap in literature on the relationship between fund managers'personal characteristics and fund performance in emerging capital markets.The results of this paper found that age,gender,fund manager years,number of funds under management,master's or doctor’s degree,MBA degree,business background and fund managers have better stock choosing ability,higher abnormal return and better overall performance has a significant positive relationship.The results of further decomposition indicate that the abnormal return is the main influencing factor of the fund's comprehensive performance;the abnormal return is also affected by the fund manager's ability of stock choosing and time picking.In addition,stock choosing ability is the main factor affecting abnormal return.Therefore,the education background of the fund manager’s personal characteristics will affect the abnormal return and ultimately affect the comprehensive performance of the fund.This paper also finds that gender and majors affect fund managers'risk control behavior.The research results in this paper have great practical significance.Firstly,it introduces a framework that can explain how the individual characteristics of fund managers affect the performance mechanism of funds.Secondly,the findings in China's stock market supplement the empirical evidence in the mature markets of developed countries.Since China is already the largest emerging economy in the world,the results of this study are of great significance not only to Chinese researchers,but also to international scholars who want to study China's capital market.Thirdly,the empirical study is of great practical significance to test the ability of fund managers to divide abnormal earnings into stock choosing ability and time picking ability.

‘Smart’copycat mutual funds:on the performance of partial imitation strategies

Using a novel measure of stock-level trade imitation,we uncover‘smart’copycats:fund managers that use their own information when beneficial,and otherwise imitate other managers’better trades.Contrary to previous research,we find that these partial imitation strategies lead to outperformance.Our‘Copycat Score’combines the propensity to imitate and to lead trades.Funds at the high and low ends of the score outperform all others.The Copycat Score is persistent in time,related to other measures of skill,and a good predictor of fund performance.We conclude that smart copycatting is another skill of successful fund managers.

PERFORMANCE EVALUATION OF CHINESE NEW FUNDS

The performance of Chinese investment funds was empirically analyzed using the following models, i.e. Jensen model, Treynor Mazuy (T M) model amd Merton Henriksson model. The results show that T M model is fitted to Chinese investment funds best among these three. But none of them can perfectly interpret the new funds’ performance. So, the idea suggested by Jagannathan, Korajczyk (J K) to extend the test was adopted in this paper, and the results show that J K model augmented from the M H can explain the source of excess return of fund Anxin.

The market performance of foreign funded passenger car makers in China

1.Japan-based makers have presented most increasingly models and brands German-based car makers continued dominating the market until 2003 and the market shares of two