This study aims to investigate the effect of interest rates, inflation, rupiah exchange rate, money supply, and exports on composite stock price index (CSPI) in Indonesia. The data used is secondary obtained from Indonesian Statistics Agency (BPS) Central Bank Indonesia for period January 2014 May 2021. applies a multiple linear regression model. findings this indicate that have positive sign s...

In this paper, we showed a method to forecast the daily stock price using neural networks and the result of the Neural Network forecast is compared with the Statistical forecasting result. Stock price prediction is one of the emerging field in neural network forecasting area. This paper also presents the Neural Networks ability to forecast the daily Stock Market Prices. Stock market prediction ...

This study examines the dynamic relationships between stock market performance and the interest rates in Sri Lanka during June 2004 to April 2011. We use all share price index in the Colombo stock exchange as a measure of stock market performance indicator and Sri Lanka interbank offer rate as a measure of interest rate. We employ some conventional time series econometric techniques namely Unit...

In current Chinese Security Market, stock or main index running orbit is a complicated phenomenon. In this paper, proposed a method to forecast Shanghai composite index using time series volume, turnover rate, close price, high price, low price, and open price as parameters. In order to simulate Shanghai composite index’s running orbit we improve a new partial differential equations simulation ...

Artificial Neural Network (ANN) has preeminent learning ability, but often exhibit inconsistent and unpredictable performance for noisy data. In addition, it may not be possible to train ANN or the training task cannot be effectively carried out without data reduction when the amount of data is so large. In this paper, we have used a Neuro-genetic model to predict the index value for Stock Pric...

this paper investigates the asymmetry in volatility of returns for the iranian stock market using the daily closing values of the tehran exchange price index (tepix) covering the period from march 25, 2001 to july 25, 2012, with a total of 2743 observations. to this end, two sets of tests have been employed: the first set is based on the residuals derived from a symmetric garch (1,1) model. the...

This paper performs specification analysis on the term structure of variance swap rates on the S&P 500 index and studies the optimal investment decision on the variance swaps and the stock index. The analysis identifies 2 stochastic variance risk factors, which govern the short and long end of the variance swap term structure variation, respectively. The highly negative estimate for the market ...

By means of computer simulation technique, this paper builds an artificial stock market model consisting of decision making agents. Through the fundamental and technical analysis in the aspects of investors, trading cost, transaction volume, risk-free interest, tick size and price-limit system, the model is used to indicate the volatility and liquidity. The results show that the stock index tim...

This paper is mainly talking about several volatility models and its ability to predict and capture the distinctive characteristics of conditional variance about the empirical financial data. In my paper, I choose basic GARCH model and two important models of the GARCH family which are E-GARCH model and GJR-GARCH model to estimate. At the same time, in order to acquire the forecasting performan...