Microblogs and social networks have become a valuable resource for mining sentiments in various fields. The sentiments posted on the web have reportedly influenced the trading and investment decisions and activities taking place in the stock exchanges. In this study, we have investigated explored the effects of microblogs on Chinese Stock Market. We have particularly focused on whether measurem...

This paper communicates the overall behaviour of the stock exchange. Basically, stock exchange is marketing for companies/group(s) assets to sell their shares and in-return generates revenues to invest and grow their company/business. The attitude of giant investors keeps on changing their move to destabilise the market so that the trivial investors cannot become stable/grow and compel to sell ...

In this paper, we examine the effect of explosive behaviors in Bitcoin market on top 10 largest stock markets developed and emerging countries. The daily dataset, including Dow Jones Industrial Index (DJIA), Nasdaq (NSQ), Shanghai Composite (SSE), Nikkei 225 (N225), Hang Seng (HSI), Shenzhen (SZSE), Euronext Amsterdam (AEX), London Stock Exchange (LSE), Toronto (TSX), Bombay (BSE), spans July 2...

We examine the antecedents and consequences in developing countries of creating a national stock exchange, a core technology of financial globalization. We study local conditions and global institutional pressures in the rapid spread of exchanges since the 1980s and examine how conditions at the point of adoption affected exchanges’ subsequent vibrancy. Little prior research connects the proces...

This paper analyzes the impact of network externalities and market quality on trading costs and activity. The price impacts of trades of stocks cross-listed on two international stock exchanges are found to be significantly lower on one of the exchanges. Foreign exchange conversion costs, and differences in tick size and the network externalities associated with how the upstairs markets on the ...

<p><span>Stock market data is considered to be one of the chaotic in nature. Analyzing stock and predicting has been area interest among researchers for a long time. In this paper, we have stepped forward used deep learning algorithm with classification predict behavior market. LSTM an optimization formulate hyperparameters. To further improve accuracy prediction first given reduce ...

Stock price prediction is considered a strategic and challenging issue in the stock markets. Considering complexity of market data fluctuations, improvement effective approaches for crucial essential task. Therefore, this study, new model based on “Adaptive Neuro-Fuzzy Inference System (ANFIS), Particle Swarm Optimization (PSO) Genetic Algorithm (GA)” employed to predict accurately. ANFIS has b...

In this paper, the forecasting problem of share prices at New York Stock Exchange (NYSE) was considered and investigated. For its solution alternative methods computational intelligence were suggested investigated: LSTM networks, GRU, simple recurrent neural networks (RNN) Group Method Data Handling (GMDH). The experimental investigations intelligent for CISCO carried out efficiency estimated c...