A new investor sentiment indicator (ISI) based on artificial intelligence: A powerful return predictor in China

Ruan, Qingsong; Wang, Zilin; Zhou, Yaping; Lv, Dayong

doi:10.1016/j.econmod.2019.09.009

Cited by 30 publications

(17 citation statements)

References 72 publications

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“…Previous studies argue that investor sentiment deviates from rational expectations (Barberis et al, 1998;Ruan et al, 2020). According to Chue et al (2019), investor sentiment represents a misestimate of asset values by stockholders.…”

Section: Literature Reviewmentioning

confidence: 99%

Rational catering of irrational emotions: Investor sentiment and executive tone

Jing

Yang

2022

Front. Psychol.

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In China, investors generally make decisions depending on the intonation of executive announcements. A total of 20,328 observations are sampled from the Chinese equity market between 2005 and 2019. We perform principal component analysis to produce monthly sentiment indices and calculate the weighted average of the value over the fiscal year to measure the degree of investor sentiment. The results of the empirical analysis reveal that: (1) there is a significant positive correlation between market-level investor sentiment and executive tone, (2) stock price and trading-volume pressures on executives, and firm-level investor expectation and gambling tendency positively moderate the relationship between investor sentiment and executive tone, (3) executive optimism does not mediate the association between investor sentiment and executive tone, and (4) manipulated and real intonations are non-homogeneous tactics adopted by rational managers to cater to changes in investor sentiment. These findings indicate that executives' intonations are both an extension of firms' current and past performances and managers' decision-making based on sentiments and behaviors of irrational investors, which are consistent with the Catering Theory. In addition, rational executives tend to adopt various intonation tactics to respond to investor sentiment to avoid declines in stock prices and trading volumes.

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Section: Literature Reviewmentioning

confidence: 99%

Rational catering of irrational emotions: Investor sentiment and executive tone

Jing

Yang

2022

Front. Psychol.

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“…Investors are not entirely rational and are more likely to be affected by psychological factors when making decisions. For example, Ruan, Wang, Zhou, and Lv (2020) have constructed an investor‐sentiment indicator using deep ML to forecast the stock market returns assuming that investor sentiments can heavily affect the asset prices. This technique outperforms other widely recognized predictors and can work well at cross‐sectional comparisons across industries.…”

Section: The Tasks Of Ai In Finance and Financial Marketsmentioning

confidence: 99%

Artificial intelligence techniques in finance and financial markets: A survey of the literature

2021

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Both academic and nonacademic literature is evolving following the oscillating development of artificial intelligence (AI) and computing power's evolution in their application to finance and financial markets. The limits to economic growth encountered after the financial crisis and, successively, the recent pandemic bursts have posed new challenges to AI-related technologies. The surveyed publications have given hope in harvesting improved efficiency, new data, information, advisory and management services, risk mitigation, and some unanswered questions regarding negative impacts on sustainable growth and increasing economic welfare.

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“…Subfigures B and C are word clouds of both supportive and oppositive comments This platform applies words segmentations and automatic matching of sentiment values, in terms of the distribution of word sentiment values. Each word has a sentiment value v i , multiplied by the word frequency p i , and added up as entire sentiment ( n i 1 p i × v i ) to obtain overall sentiment tendency [63]. In Fig.…”

Section: Data Acquisition Of Online Public Opinionsmentioning

confidence: 99%

Big data-drive agent-based modeling of online polarized opinions

Lü

Zhang

2021

Complex Intell. Syst.

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Under the mobile internet and big data era, more and more people are discussing and interacting online with each other. The forming process and evolutionary dynamics of public opinions online have been heavily investigated. Using agent-based modeling, we expand the Ising model to explore how individuals behave and the evolutionary mechanism of the life cycles. The big data platform of Douban.com is selected as the data source, and the online case “NeiYuanWaiFang” is applied as the real target, for our modeling and simulations to match. We run 10,000 simulations to find possible optimal solutions, and we run 10,000 times again to check the robustness and adaptability. The optimal solution simulations can reflect the whole life cycle process. In terms of different levels and indicators, the fitting or matching degrees achieve the highest levels. At the micro-level, the distributions of individual behaviors under real case and simulations are similar to each other, and they all follow normal distributions; at the middle-level, both discrete and continuous distributions of supportive and oppositive online comments are matched between real case and simulations; at the macro-level, the life cycle process (outbreak, rising, peak, and vanish) and durations can be well matched. Therefore, our model has properly seized the core mechanism of individual behaviors, and precisely simulated the evolutionary dynamics of online cases in reality.

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A new investor sentiment indicator (ISI) based on artificial intelligence: A powerful return predictor in China

Cited by 30 publications

References 72 publications

Rational catering of irrational emotions: Investor sentiment and executive tone

Rational catering of irrational emotions: Investor sentiment and executive tone

Artificial intelligence techniques in finance and financial markets: A survey of the literature

Big data-drive agent-based modeling of online polarized opinions

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