“…In particular, the increase in TECP led to the rise of the NASDAQ 100 index.…”
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“…However, our new design, which can display all results using Heatmap Visualization, shows that the NASDAQ100 index outperforms the DJ30 index and that weekly data outperforms daily data when measured by annualized return. …”
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“…We rely on the twitter data from NASDAQ 100 firms to generate themes regarding the issues faced by the firms and the strategies they are adopting using text analytics tools. …”
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“…The experimental findings obtained using the DOW30 and NASDAQ100 reveal that the accuracy of the GA and ANN hybrid model for the DOW30 and NASDAQ100 is greater than that of the single ANN (BPANN) technique, both in the short and long term.…”
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“…This result is stronger for Russell2000 stocks and Nasdaq100 stocks than for S&P500 stocks. Moreover, consistent with the theoretical framework, the price adjustment for bad news was found to be quicker than for good news. …”
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“…The M_Omega and R_Omega models produce a higher return than that of the S&P 500 index or NASDAQ 100 index, considering the intraday trading cost. …”
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“…This research also provides evidence that social risk impact negatively the simple excess return for both the S & P500 and nasdaq100 stocks indicating that social issues must be mitigated in order to maximize a firm value. …”
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“…This research tests for the existence of nonlinear patterns and chaotic nature in four major stock market indices: namely Dow Jones Industrial Average, Ibex 35, Nasdaq-100 and Nikkei 225. To this end, a comprehensive framework has been adopted encompassing a wide range of techniques and the most suitable methods for the analysis of noisy time series. …”
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“…To such a scope, we consider 15-minutes prices and returns of the set of the NASDAQ-100 components before and after the Cambridge Analytica case. …”
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“…We studied daily data from 13 stocks from the Dow-Jones and NASDAQ100 indices, over a period of 4 trading years. …”
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“…We study the real-time relationship between chatter on Twitter and the stock trading volume of 96 firms listed on the Nasdaq 100, during 193 days of trading in the period from May 21, 2012 to September 18, 2013. …”
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“…The methodology is applied to examine the dynamics and structure of the Nasdaq-100 stock market during the pandemic period 2019/12–2021/12 considering both asset returns and volume trading to model the behaviour of different assets that are part of the index, applying an algorithm that offers better performance than others applied in the clustering literature. …”
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“…Here we show that daily trading volumes of stocks traded in NASDAQ-100 are correlated with daily volumes of queries related to the same stocks. …”
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“…We illustrate this method with two case studies: (i) a case study of 100 assets of the U.S. stock market’s NASDAQ-100 index and (ii) a case study of 50 assets of the Indian stock market’s NIFTY-50 index. …”
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