Forecasting stock market has been a difficult job for applied researchers owing to nature of facts which is very noisy and time varying. However, this hypothesis has been featured by several empirical experiential studies and a number of researchers have efficiently applied machine learning techniques to forecast stock market. This paper studied stock prediction for the use of investors. It is ...

Using an agent-based model we examine the dynamics of stock price fluctuations and their rates of return in an artificial financial market composed of fundamentalist and chartist agents with and without confidence. We find that chartist agents who are confident generate higher price and rate of return volatilities than those who are not. We also find that kurtosis and skewness are lower in our ...

While the relationship between stock market return and oil price is of great interest to researchers, previous studies do not investigate stock market return with petrochemical products market. In this paper, we analyzed the relationship between prices of main petrochemical products and stock returns of petrochemical companies in Tehran stock exchange. Using a panel data model and GLS estimatio...

In this research, role of accruals in elaboration of quality of earning of the companies accepted in Mumbai Stock Exchange has been studied and relationship between quality of earning through accruals and its constituents and abnormal stock return has been studied. The studied sample includes 35 companies in group A of Mumbai Stock Exchange in 2009-2013.Fordata analysisandhypothesistesting mult...

We have introduced an early warning system for volatility regimes regarding Tehran Stock Exchange using Markov Switching GARCH approach. We have examined whether Tehran Stock Market has calmed down or more specifically, whether the surge in volatility during 2007-2010 global financial crises still affects stock return volatility in Iran.  Doing so, we have used a regime switching GARCH model.  ...

This paper investigates the relationship between aggregate stock market trading volume and the serial correlation of daily stock returns. For both stock indexes and individual large stocks, the first-order daily return autocorrelation tends to decline with volume. The paper explains this phenomenon using a model in which risk-averse "market makers" accommodate buying or selling pressure from "l...

for assessment of portfolio performance, it's crucial to adjust the return by the risk which is taken. so it seems undeniable that for measuring the risk-adjusted return of portfolio, we need an appropriate and developed model for risk and asset pricing. fama & french 3 factor model could explain several return anomalies. recent studies show that capital productivity effects on stock retur...

Generally, high oil prices slow economic growth, cause inflationary pressures and creates global imbalances. In addition, oil price volatility increase uncertainty and restrain the much-needed investment in the capital market. Thus, this paper applies the Augmented Dickey Fuller and Johansen Co-integration Tests in which the effect of oil price volatility, crude oil price and stock price is ana...

Objective: In general, financial time series such as stock indexes have nonlinear, mutable and noisy behavior. Structural and statistical models and machine learning-based models are often unable to accurately predict series with such a behavior. Accordingly, the aim of the present study is to present a new hybrid model using the advantages of the GMDH method and Non-dominated Sorting Genetic A...

this study determined the value relevance of assets and liabilities after the adoption of ifrs among listed nigerian firms. ohlson model (1995) model of stock price regressions tested the relationship between assets and liabilities with the stock price, which has been widely adopted by accounting researchers. a sample of 126 firms listed in nigeria stock market is used for the study. data is co...