6 | 2016 | Bartov et al. [35] | Can Twitter Help Predict Firm-Level Earnings and Stock Returns? | Accepted | Observed positive association between the aggregate opinion and the immediate abnormal stock price reaction to the quarterly earnings announcement |
7 | 2016 | Jin et al. [36] | Has Microblogging Changed Stock Market Behavior? Evidence from China | Accepted | Observed significant impact of microblogging to increase the relative trading volume as well as the decreases in the daily expected stock return |
8 | 2016 | Singh [7] | R&D Spillovers & Productivity Growth: Evidence from Indian Manufacturing | Accepted | Technology influences productivity |
9 | 2016 | Singh [6] | Do Technology Spillovers Accelerate Performance of Firms? | Accepted | R&D promote the adoption of new technologies such as big Data and Machine Learning |
10 | 2015 | Seth and Chaudhary [29] | Big Data in Finance | Accepted | Big Data in finance will evolve to influence the trading the pattern of the investors |
11 | 2015 | Attigeri et al. [12] | Stock Market Prediction: A Big Data Approach | Accepted | In the technical analysis and fundamental research scholar found that social media has influence on the stock prices |
12 | 2015 | Tian et al. [42] | Latency Critical Big Data Computing in Finance | Accepted | Big data and Analytics based computing could benefit today's banking and financial organizations to achieve more intelligent trading in the capital market |
13 | 2014 | Shorter et al. [43] | High-Frequency Trading: Background, Concerns, and Regulatory Developments | Accepted | High frequency trading will keep on posing the regulatory challenges with the development of technology |
14 | 2014 | Funk and Hirschman [27] | Derivatives and Deregulation: Financial Innovation and the Demise of Glass-Steagall | Accepted | Big Data implications on the HFT trading is highly tilted due to technology |
15 | 2014 | Nagata and Inui [37] | Does High-Speed Trading Enhance Market Efficiency? Empirical Analysis on “Arrowhead” of the Tokyo Stock Exchange | Accepted | High efficiency trading enhances marketing efficiency |
16 | 2014 | Moat et al. [38] | Using Big Data to Predict Collective Behavior in the Real World | Accepted | Observed the predictive effect of the Big Data analysis in the financial world |
17 | 2013 | Aldridge [14] | Market Microstructure and the Risks of High-Frequency Trading | Accepted | High frequency trading reduces the arbitrage due to gap in information |
18 | 2013 | Angel and McCabe [44] | Fairness in Financial Markets: The Case of High Frequency Trading | Accepted | Impact of High frequency trading was put into question as the fair practice in the capital market |
19 | 2013 | Aït-Sahalia and Saglam [45] | High Frequency Traders: Taking Advantage of Speed | Accepted | High Frequency traders could take the advantage of the speed to influence the capital market in their favour |
20 | 2013 | Alanyali et al. [46] | Quantifying the Relationship between Financial News and the Stock Market | Accepted | Observed that movements in financial markets and movements in financial news are intrinsically interlinked |
21 | 2012 | Snijders et al. [26] | Big Data: Big Gaps of Knowledge in the Field of Internet Science | Accepted | Observed that Big Data could bridge the gap in knowledge in the capital markets and reduce efficiency |