scholarly journals Multiple-output support vector regression with a firefly algorithm for interval-valued stock price index forecasting

2014 ◽  
Vol 55 ◽  
pp. 87-100 ◽  
Author(s):  
Tao Xiong ◽  
Yukun Bao ◽  
Zhongyi Hu
Keyword(s):  
Support Vector Regression ◽  
Stock Price ◽  
Firefly Algorithm ◽  
Price Index ◽  
Support Vector ◽  
Stock Price Index ◽  
Interval Valued

Forecasting of stock price index using support vector regression with multivariate empirical mode decomposition

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yanmei Huang ◽  
Changrui Deng ◽  
Xiaoyuan Zhang ◽  
Yukun Bao
Keyword(s):  
Support Vector Regression ◽  
Empirical Mode Decomposition ◽  
Stock Price ◽  
Price Index ◽  
Support Vector ◽  
Modeling Framework ◽  
Content Type ◽  
Multivariate Empirical Mode Decomposition ◽  
Mode Decomposition ◽  
Stock Price Index

Purpose Despite the widespread use of univariate empirical mode decomposition (EMD) in financial market forecasting, the application of multivariate empirical mode decomposition (MEMD) has not been fully investigated. The purpose of this study is to forecast the stock price index more accurately, relying on the capability of MEMD in modeling the dependency between relevant variables. Design/methodology/approach Quantitative and comprehensive assessments were carried out to compare the performance of some selected models. Data for the assessments were collected from three major stock exchanges, namely, the standard and poor 500 index from the USA, the Hang Seng index from Hong Kong and the Shanghai Stock Exchange composite index from China. MEMD-based support vector regression (SVR) was used as the modeling framework, where MEMD was first introduced to simultaneously decompose the relevant covariates, including the opening price, the highest price, the lowest price, the closing price and the trading volume of a stock price index. Then, SVR was used to set up forecasting models for each component decomposed and another SVR model was used to generate the final forecast based on the forecasts of each component. This paper named this the MEMD-SVR-SVR model. Findings The results show that the MEMD-based modeling framework outperforms other selected competing models. As per the models using MEMD, the MEMD-SVR-SVR model excels in terms of prediction accuracy across the various data sets. Originality/value This research extends the literature of EMD-based univariate models by considering the scenario of multiple variables for improving forecasting accuracy and simplifying computability, which contributes to the analytics pool for the financial analysis community.

Stock Price Index Prediction Based on Improved SVM

2011 ◽  
Vol 267 ◽  
pp. 468-471
Author(s):  
Jin Yan Shi ◽  
Xue Li ◽  
Yan Xi Li
Keyword(s):  
Kernel Function ◽  
Stock Price ◽  
Price Index ◽  
Kernel Functions ◽  
Classification Model ◽  
Support Vector ◽  
Theoretical Advantage ◽  
Stock Price Index ◽  
Hybrid Kernel Function ◽  
Hybrid Kernel

Accurate stock price predicting is a key problem to the financial field. Comparing with the traditional stock price predicting models such as GARCH models and neural networks, the theoretical advantage of applying support vector machine (SVM) to stock price predicting highly depends on solving the problem of kernel function construction and parameter optimization. For the effect of the kernel function in the SVM classification model, a hybrid kernel function is presented. In order to optimize and adjust the important parameters during the process of building the hybrid kernel function, an improved particle swarm optimization which has better global search ability is used. Experimental results about stock price index predicting show that this method has higher prediction accuracy compared with the traditional kernel functions.

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

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).

scholarly journals ANALISIS FAKTOR PENENTU INDEKS HARGA SAHAM GABUNGAN DI INDONESIA

2019 ◽  
Vol 1 (4) ◽  
pp. 37
Author(s):  
Yulizar Fikri ◽  
Ali Anis
Keyword(s):  
Economic Growth ◽  
Foreign Exchange ◽  
Stock Price ◽  
Price Index ◽  
Time Series Data ◽  
Secondary Data ◽  
Coefficient Of Determination ◽  
Series Data ◽  
Foreign Exchange Reserves ◽  
Stock Price Index

This study aims to determine the analysis of the determinants of the composite stock price index in Indonesia. The independent variables in this study are inflation as X1, foreign exchange reserves as X2, exchange rates as X3, and economic growth as X4, and the dependent variable of the composite stock price index as Y. The data used are secondary data in the formof time series data from 2010Q1 until 2019Q2, with data collection techniques, namely documentation from Bank Indonesia publications, the Central Statistics Agency, investing. comsite and library research. The research methods used are: (1) Multiple Linear Regression, (2) Classical Assumption Test (3) coefficient of determination. The results of this study indicate that:(1) inflation does not significantly influence the composite stock price index. (2) foreign exchange reserves have a significant positive effect on the composite stock price index. (3) the rupiah exchange rate has an influence on the composite stock price index and (4) economic growth hasno significant effect on the composite stock price index.

scholarly journals Analisis Pengaruh Nilai Tukar Rupiah, Inflasi Dan Indeks Dow Jones Terhadap Indeks Harga Saham Gabungan (IHSG) Di Bursa Efek Indonesia (BEI)

KINDAI ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. 542-562
Author(s):  
Delila Putri Syarina
Keyword(s):  
Exchange Rate ◽  
Exchange Rates ◽  
Stock Price ◽  
Quantitative Method ◽  
Price Index ◽  
Stock Exchange ◽  
Sampling Techniques ◽  
Jones Index ◽  
Stock Price Index

Abstract: This study aims to study both partially and simultaneously, large, Analysis, Analysis, Value, Exchange, Inflation, and the Dow Jones Index Against the Composite Stock Price Index (CSPI) on the Indonesia Stock Exchange (BEI) and the dominant dominant variable on the Price Index Joint Stock (CSPI)).The method used in this study is a quantitative method and with a population of 10 (ten) years, samples were taken with census sampling techniques of 10 (ten) years per year-end period, research instruments using classical data assumptions - data used using regression linear multiple.The results of this study indicate that (1) Rupiah Exchange Rates, Inflation and the Dow Jones Index influence simultaneously on the Composite Stock Price Index (CSPI) on the Indonesia Stock Exchange (2) the Dow Jones Index is partially related to the Composite Stock Price Index (CSPI) in The Indonesian Stock Exchange, while the Rupiah Exchange Rate and Inflation are not partially on the Composite Stock Price Index (CSPI) on the Indonesia Stock Exchange (3) The dominant dominant variable on the Composite Stock Price Index (CSPI) on the Indonesia Stock Exchange is the Dow Jones Index..Keywords  : Rupiah Exchange Rate, Inflation, Dow Jones Index and Composite Stock Price Index (CSPI)   Abstrak: Penelitian ini bertujuan untuk mengetahui baik secara parsial dan simultan seberapa besar Analisis Pengaruh Nilai Tukar Rupiah, Inflasi Dan Indeks Dow Jones Terhadap Indeks Harga Saham Gabungan (IHSG) Di Bursa Efek Indonesia (BEI) serta variabel yang berpengaruh dominan terhadap Indeks Harga Saham Gabungan (IHSG). Metode yang digunakan dalam penelitian ini adalah metode kuantitatif dan dengan populasi sebanyak 10 (sepuluh) tahun, diambil sampel dengan teknik sampling sensus sebanyak 10 (sepuluh) tahun per periode akhir tahun, instrument penelitian uji asumsi klasik data – data diuji dengan menggunakan regresi linear berganda. Hasil penelitian ini menunjukkan bahwa (1) Nilai Tukar Rupiah, Inflasi dan Indeks Dow Jones berpengaruh secara simultan terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia (2) Indeks Dow Jones berpengaruh secara parsial terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia, sedangkan Nilai Tukar Rupiah dan Inflasi tidak berpengaruh secara parsial terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia (3) Variabel yang berpengaruh dominan terhadap Indeks Harga Saham Gabungan (IHSG) di Bursa Efek Indonesia adalah Indeks Dow Jones. . Kata kunci :     Nilai Tukar Rupiah, Inflasi, Indeks Dow Jones dan Indeks Harga Saham Gabungan (IHSG).

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