Prediction of mutual fund net asset value using low complexity feedback neural network

2016 ◽  
Author(s):  
C.M. Anish ◽  
Babita Majhi
Keyword(s):  
Neural Network ◽  
Mutual Fund ◽  
Low Complexity ◽  
Asset Value ◽  
Net Asset Value ◽  
Feedback Neural Network

A Mutual Fund Investment Method Using Fruit Fly Optimization Algorithm and Neural Network

2014 ◽  
Vol 571-572 ◽  
pp. 318-325 ◽  
Author(s):  
Tsu Hua Huang ◽  
Yung Ho Leu
Keyword(s):  
Neural Network ◽  
Mutual Funds ◽  
Optimization Algorithm ◽  
Mutual Fund ◽  
Fruit Fly ◽  
Fruit Fly Optimization Algorithm ◽  
Fruit Fly Optimization ◽  
Asset Value ◽  
Net Asset Value ◽  
Fund Portfolio

This paper presents a method to construct a profitable portfolio of mutual funds for investors. This method comprises two stages. In the first stage, the DEA, Sharpe and Treynor indices of mutual funds and the monthly rates of return (ROR) of mutual funds are used to select a mutual fund portfolio. In the second stage, the linear regression model, the Fruit Fly Optimization Algorithm (FOA) and the General Regression Neural Network (GRNN) are used to construct a prediction model for the net asset values of each of the constituent mutual funds of the portfolio. The trade decision of a selected mutual fund is then made based on the rise or fall of its net asset value. The empirical results showed that, compared to other combinations, the combination of using Sharpe index for portfolio selection and the GRNN optimized with FOA for net asset value prediction offered the best accumulated return rate for the mutual fund portfolio investment.

A neural network approach to mutual fund net asset value forecasting

Omega ◽  
1996 ◽  
Vol 24 (2) ◽  
pp. 205-215 ◽  
Author(s):  
W.-C. Chiang ◽  
T.L. Urban ◽  
G.W. Baldridge
Keyword(s):  
Neural Network ◽  
Mutual Fund ◽  
Network Approach ◽  
Neural Network Approach ◽  
Asset Value ◽  
Net Asset Value

Pengaruh Inflasi, BI-7 Day Reverse Repo Rate, Kurs, Jumlah Uang Beredar dan Indeks Harga Saham Gabungan terhadap Nilai Aktiva Bersih Reksa Dana Saham

Owner ◽  
2021 ◽  
Vol 5 (2) ◽  
pp. 358-367
Author(s):  
Jhon Lismart Benget. P.
Keyword(s):  
Exchange Rate ◽  
Mutual Funds ◽  
Money Supply ◽  
Mutual Fund ◽  
Stock Price ◽  
Price Index ◽  
Asset Value ◽  
Net Asset Value ◽  
Repo Rate ◽  
Stock Price Index

The purpose of this study is to examine the effect of inflation, BI-7 day reverses repo rate, exchange rate, the money supply, and composite stock price index on the net asset value of stock mutual funds. The population of this study is the stock mutual fund which was listed on the financial services authority in 2017-2020. The results of this study indicate that simultaneously inflation, BI-7 day reverse repo rate, exchange rate, the money supply, and composite stock price index affect the net asset value of the stock mutual fund. Partially, this study show BI-7 day reverse repo rate has a positive and significant effect on the net asset value of a stock mutual fund. The exchange rate has a positive and significant effect on the net asset value of stock mutual funds. The composite stock price index has a positive and significant effect on the net asset value of stock mutual funds. The money supply has a negative and significant effect on the net asset value of a stock mutual fund while inflation has no significant effect on the net asset value of a stock mutual fund.

scholarly journals A Factorial Analysis of Information Ratio and Its Causal Effect on Yearly Return of Net Asset Value – A Study of Indian Equity Diversified Mutual Fund Schemes

2018 ◽  
Vol 7 (4.36) ◽  
pp. 707 ◽  
Author(s):  
Suman Chakraborty ◽  
Satish Kumar ◽  
Lumen Shawn Lobo
Keyword(s):  
Interest Rates ◽  
Mutual Fund ◽  
Causal Effect ◽  
Secondary Data ◽  
Information Ratio ◽  
Wide Range ◽  
Asset Value ◽  
Net Asset Value ◽  
Equity Funds ◽  
Sector Funds

Evaluation of performance of mutual fund schemes has gained a wide range of attention from both investors and academicians. The study aims at assessing the returns from equity mutual fund schemes in India by applying risk adjusted performance evaluation techniques. The study is based on secondary data collected for ten years for selected open ended equity diversified mutual funds. A comparative assessment of performance of public sector sponsored equity funds and non-government sponsored  sector funds bring forth with an interesting inference. The present study also constitutes a modest attempt to assess the information ratio and its causal effect on the average yearly return of Net Asset Value (NAV). Based on the previous research findings, this paper puts an honest effort to identify twelve independent variables which affects significantly the performance of NAV. The evaluation relies on the Sharpe, Trenor and Jensen’s technique, which have been applied in conjunction with parametric and non-parametric statistical tools using. The result shows significant relationship exists between the NAV return and fund’s risk, information ratio, macro-economic variables such as inflation, interest rates, market index performance, foreign flow of funds and foreign exchange on the basis of regression analysis. 

Indonesian Mutual Funds Classification Using Clustering Method

2015 ◽  
Vol 21 (4) ◽  
pp. 826-829
Author(s):  
Ir. Dewi Tamara ◽  
Shintia Revina
Keyword(s):  
Mutual Funds ◽  
Mutual Fund ◽  
Money Market ◽  
Fixed Income ◽  
Clustering Method ◽  
New Classification ◽  
Asset Value ◽  
Net Asset Value ◽  
Alternative Investment

Mutual funds have existed since 1990 as an alternative investment in Indonesia. The objective of this research is to examine the existing classification of mutual funds database. The data of mutual funds is taken from Bloomberg through Portal Reksadana 2013 which covered 690 mutual funds. The existing classification consists of mutual funds fixed income (reksadana pendapatan tetap), equity (reksadana saham), money market (reksadana pasar uang) and structured (reksadana campuran). The existing financial attributes consists of the net asset value, percentage annualized return the last 6 months, 1 year, 3 years, 5 years and year-to-date. This paper uses K-means clustering to propose new classification of Indonesian mutual funds. The result reveals that mutual funds in equity and fixed income belong to its group. However, mutual funds money market is belong to mutual fund fixed income and mutual funds structures are identified to mutual funds equity. Furthermore, we find that in average 43% of Indonesian mutual funds are misclassified in accordance with their attributes. Finally, it is suggested to re-group the mutual funds into smaller classification, which has lower rates of misclassified mutual funds and possibility to achieve better performances in terms of its percentage annualized return.

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