Hybrid knowledge integration using the fuzzy genetic algorithm: prediction of the Korea stock price index

2004 ◽  
Vol 12 (1) ◽  
pp. 43-60 ◽  
Author(s):  
Myoung Jong Kim ◽  
Ingoo Han ◽  
Kun Chang Lee
Keyword(s):  
Genetic Algorithm ◽  
Stock Price ◽  
Knowledge Integration ◽  
Price Index ◽  
Fuzzy Genetic Algorithm ◽  
Hybrid Knowledge ◽  
Stock Price Index ◽  
Fuzzy Genetic

ANALISIS PENGARUH INFLASI, KURS DAN IHSG TERHADAP RETURN REKSA DANA SAHAM PT NIKKO SECURITIES INDONESIA PERIODE 2014-2017

2019 ◽  
Vol 2 (2) ◽  
pp. 103
Author(s):  
Muhammad Rois Rois ◽  
Manarotul Fatati Fatati ◽  
Winda Ihda Magfiroh
Keyword(s):  
Regression Analysis ◽  
Exchange Rate ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Stock Price ◽  
Price Index ◽  
Linear Regression Analysis ◽  
Multiple Linear Regression Analysis ◽  
Equity Fund ◽  
Stock Price Index

This study aims to determine the effect of Inflation, Exchange Rate and Composite Stock Price Index (IHSG) to Return of PT Nikko Securities Indonesia Stock Fund period 2014-2017. The study used secondary data obtained through documentation in the form of PT Nikko Securities Indonesia Monthly Net Asset (NAB) report. Data analysis is used with quantitative analysis, multiple linear regression analysis using eviews 9. Population and sample in this research are PT Nikko Securities Indonesia. The result of multiple linear regression analysis was the coefficient of determination (R2) showed the result of 0.123819 or 12%. This means that the Inflation, Exchange Rate and Composite Stock Price Index (IHSG) variables can influence the return of PT Nikko Securities Indonesia's equity fund of 12% and 88% is influenced by other variables. Based on the result of the research, the variables of inflation and exchange rate have a negative and significant effect toward the return of PT Nikko Securities Indonesia's equity fund. While the variable of Composite Stock Price Index (IHSG) has a negative but not significant effect toward Return of Equity Fund of PT Nikko Securities Indonesia

scholarly journals Aluminium foam production control by using a combined fuzzy-genetic algorithm model

Procedia CIRP ◽  
2020 ◽  
Vol 88 ◽  
pp. 503-508
Author(s):  
Gennaro Salvatore Ponticelli ◽  
Stefano Guarino ◽  
Oliviero Giannini ◽  
Flaviana Tagliaferri ◽  
Simone Venettacci ◽  
...  
Keyword(s):  
Genetic Algorithm ◽  
Production Control ◽  
Aluminium Foam ◽  
Fuzzy Genetic Algorithm ◽  
Fuzzy Genetic ◽  
Foam Production ◽  
Genetic Algorithm Model

Fuzzy-Genetic Algorithm for Pre-Processing Data at the RTU

2004 ◽  
Vol 19 (2) ◽  
pp. 718-723 ◽  
Author(s):  
P. Kumar ◽  
V.K. Chandna ◽  
M.S. Thomas
Keyword(s):  
Genetic Algorithm ◽  
Processing Data ◽  
Fuzzy Genetic Algorithm ◽  
Fuzzy Genetic

Fast Covariance Matching With Fuzzy Genetic Algorithm

2012 ◽  
Vol 8 (1) ◽  
pp. 148-157 ◽  
Author(s):  
Xuguang Zhang ◽  
Shuo Hu ◽  
Dan Chen ◽  
Xiaoli Li
Keyword(s):  
Genetic Algorithm ◽  
Covariance Matching ◽  
Fuzzy Genetic Algorithm ◽  
Fuzzy Genetic

MODELING THE INTERACTIONS OF STOCK PRICE AND EXCHANGE RATE IN MALAYSIA

2009 ◽  
Vol 54 (04) ◽  
pp. 605-619 ◽  
Author(s):  
MOHD TAHIR ISMAIL ◽  
ZAIDI BIN ISA
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Stock Prices ◽  
Stock Price ◽  
Price Index ◽  
Composite Index ◽  
Regime Shifts ◽  
Var Model ◽  
Vector Autoregressive ◽  
Stock Price Index

After the East Asian crisis in 1997, the issue of whether stock prices and exchange rates are related or not have received much attention. This is due to realization that during the crisis the countries affected saw turmoil in both their currencies and stock markets. This paper studies the non-linear interactions between stock price and exchange rate in Malaysia using a two regimes multivariate Markov switching vector autoregression (MS-VAR) model with regime shifts in both the mean and the variance. In the study, the Kuala Lumpur Composite Index (KLCI) and the exchange rates of Malaysia ringgit against four other countries namely the Singapore dollar, the Japanese yen, the British pound sterling and the Australian dollar between 1990 and 2005 are used. The empirical results show that all the series are not cointegrated but the MS-VAR model with two regimes manage to detect common regime shifts behavior in all the series. The estimated MS-VAR model reveals that as the stock price index falls the exchange rates depreciate and when the stock price index gains the exchange rates appreciate. In addition, the MS-VAR model fitted the data better than the linear vector autoregressive model (VAR).

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