The U.S. stock market enters the new millennium with five consecutive years of exceptional gains. The S&P 500 index has gained more than 18 percent each of these five years and its value has tripled since 1995. Whether these hefty gains will continue is an important question for many people. Investors obviously care because stock price movements directly affect their wealth. More generally, lar...

The purpose of this research is to predict stock returns and the purpose of the least squares regression and neural network approach is used. The potential financial ratios based on the historical cost and financial ratios based on Adjusted Cost predict stock returns are investigated. Independent variables and the dependent variable in this study and financial ratios and stock returns is for th...

This paper uses the smooth transition regression (STR) model to study the nonlinear relation between the consumer price index (CPI) and the composite index of Shanghai Stock Market in China from 1999 to 2011. The results show that there exists one way Granger causality relation from CPI to stock market in China; the internal relation between the CPI and stock market’s composite index appears as...

The prediction of a stock market direction may serve as an early recommendation system for short-term investors and as an early financial distress warning system for long-term shareholders. Many stock prediction studies focus on using macroeconomic indicators, such as CPI and GDP, to train the prediction model. However, daily data of the macroeconomic indicators are almost impossible to obtain....

We investigate the fluctuation behaviors of financial stock markets by Zipf analysis. In the present paper, the empirical research is made to describe ensembles and specifics of stock price returns for global stock indices, and the corresponding Zipf distributions are given. First we study the fluctuation behavior of global stock markets by m, k -Zipf method. Then we consider a dynamic stock pr...

This study aims to determine the effect of interest rates, inflation, exchange rates and money supply on composite stock price index Indonesia Stock Exchange from 2018 2021. type research is a quantitative with descriptive approach using multiple regression analysis methods. The results showed that rate had significant positive index. has negative Meanwhile, inflation no suggestion in this inve...

The application of deep learning approaches to finance has received a great deal of attention from both investors and researchers. This study presents a novel deep learning framework where wavelet transforms (WT), stacked autoencoders (SAEs) and long-short term memory (LSTM) are combined for stock price forecasting. The SAEs for hierarchically extracted deep features is introduced into stock pr...

In this study, a modeling method to analyze multidimensional time series based on complex networks is proposed. The rate of return sequence of the closing price and the trading volume fluctuation sequence of the Shanghai Composite Index, the Shenzhen Component Index, the S & P 500 index, and the Dow Jones Industrial Average are analyzed. The two-dimensional time series is transformed into a com...