In this paper, we present a software package for the data mining of Twitter microblogs for the purpose of using them for the stock market analysis. The package is written in R langauge using apropriate R packages. The model of tweets has been considered. We have also compared stock market charts with frequent sets of keywords in Twitter microblogs messages.

We analyze the relations between the stock market and a stock bulletin board system (BBS) in Japan. Previous studies in the USA found that the characteristics of messages posted on stock BBSs can predict market volatility and trading volume. We develop hypotheses based on the results of those analyses and apply statistical analysis to the data about companies mentioned in a large number of mess...

This paper provides new evidence on the dynamics of equity risk premia in euro area stock markets across country and industry portfolios. We develop and estimate a conditional intertemporal CAPM where returns on aggregate euro area, country and industry portfolios depend on the market risk as well as on the risk that the investment opportunity set changes over time. Prices of risks are time-var...

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...

This paper examines the effects of selected macroeconomic variables on the stock market index in Iran. Using quarterly data, we examine the relationships between the Tehran Stock Index (TSI) and five macroeconomic variables which consist of gross domestic product, nominal effective exchange rate, money supply, gold coin price and investment in housing sector from 1996:1 to 2008:1.Various e...

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...

Modern day stock markets have almost entirely became automated. Even though it means increased profits for the investors by algorithms acting upon the slightest price change in order of microseconds, it also has given birth to many ethical dilemmas in the sense that slightest mistake can cause people to lose all of their livelihoods. This paper reviews one such event that happened on May 06, 20...

This paper uses an empirical connection between real stock market indices of Germany and the USA for forecasting corresponding returns. We are starting from the random walk as the traditional forecasting model in stock market applications, extending it by co-integration. Since the cointegrating relation considers information about a systematic link between the stock market indices, containing a...

In this research we mainly focus on overcoming the drawbacks in FITI approach in predicting the stock market and propose a new approach called fragment based mining which gives some promising results as compared to FITI. FITI consists of all the transaction from the stock market some of which are not necessary and simply increases the overhead in processing the data, so we improve this by reduc...

Financial decisions are among the most significant life-changing decisions that individuals make. There is a strong correlation between financial decision making and human behavior. In this research the relationship between what people think and how stock market moves is investigated. The data from 2010 to 2015 of some of business, political and financial events which directly impact the local ...