Sentiment contagion analysis of interacting investors: Evidence from China’s stock forum

Shi, Yong; Tang, Ye-ran; Long, Wen

doi:10.1016/j.physa.2019.02.025

Cited by 30 publications

(10 citation statements)

References 34 publications

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“…As well as the stock market, the gold, bond, and foreign exchange markets are all financial markets with a large scale in China. If such emotional contagion exists in China, investors who excessively ignore the fundamentals will find it difficult to form the ideal of value investment [23]. Further, Chinese investor sentiment is more sensitive to different financial information, such as the wax and wane of other financial markets.…”

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confidence: 99%

Can Stock Investor Sentiment Be Contagious in China?

Cai

Ran

2020

Sustainability

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This paper explores the impact of investor sentiment on financial markets in China by taking the quantile causality test. We find that government bond markets, gold markets, and foreign exchange markets are affected by stock investor sentiment, except for in the corporate bond market. In extreme situations, such as excessively optimistic or pessimistic sentiment, these markets will become more vulnerable to suffering from drastic fluctuations. On the contrary, the market return in government bonds, corporate bonds, and foreign exchange also has an influence on stock investor sentiment. Moreover, these links show various asymmetry due to the heterogeneity of different financial markets. Our results are consistent with the noise trader model, which shows the impact of investor sentiment on market returns. Hence, the authorities can sustain the stabilization of financial markets by reducing information asymmetry, guiding the rational sentiment of investors, and increasing effective regulations.Especially in certain extreme pessimistic situations, sentiment in the stock market can lead to drastic fluctuations in other financial markets [15,16], and the authorities cannot maintain market stability and continuity of development. In turn, the performance of these markets is also a remarkable barometer that leads stock investor sentiment to change [17]. Through information in different market environments, external shocks, not only make asset price fluctuate, but also result in stock investors overreacting, and this affects their investment expectations [18]. This bidirectional transmission is regarded as an important factor for the linkage among major financial markets [19]. Hence, investor sentiment plays an important role in the formation of financial market effectiveness. If investor sentiment cannot be reasonably guided, it will be difficult to suppress irrational trading and speculative bubbles and improve market efficiency.Compared with stock markets in developed countries, individual investors account for a large proportion of Chinese stock investors, which makes the whole market more emotional [20]. With a lack of social responsibility and an awareness of sustaining market efficiency, the individual Chinese investor has an underdeveloped investment education and, thus, they often show irrational investment behavior [21]. Hence, market fluctuation frequently happens, and it is difficult for investor sentiment to be properly guided. Not only do investors make irrational trades in the stock market, but they are also more likely to carry their emotions to other markets [22]. If investor sentiment in the stock market spreads to other markets and causes unexpected fluctuations in China, the pricing and operating efficiency of many financial markets will be damaged. As well as the stock market, the gold, bond, and foreign exchange markets are all financial markets with a large scale in China. If such emotional contagion exists in China, investors who excessively ignore the fundamentals will find it difficult to form th...

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confidence: 99%

Can Stock Investor Sentiment Be Contagious in China?

Cai

Ran

2020

Sustainability

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“…However, a dataset combining multiple sources while covering the same period for financial textual sentiment is absent. Such a dataset comes with many potential applications which remain unexplored to this date, examples are the effect of sentiment contagion (Shi et al, 2019), leveraging contextual sentiments which is especially beneficial to enhance the detection of implicit sentiments, and development of improved market sentiment indices. All these research topics require sentiment information based on a broad audience, stemming from different data types and sources, annotated on a scale, covering a set of sentiment targets, and stemming from the same period.…”

Section: Introductionmentioning

confidence: 99%

A multi-source entity-level sentiment corpus for the financial domain: the FinLin corpus

Daudert

2021

Lang Resources & Evaluation

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We introduce FinLin, a novel corpus containing investor reports, company reports, news articles, and microblogs from StockTwits, targeting multiple entities stemming from the automobile industry and covering a 3-month period. FinLin was annotated with a sentiment score and a relevance score in the range [− 1.0, 1.0] and [0.0, 1.0], respectively. The annotations also include the text spans selected for the sentiment, thus, providing additional insight into the annotators’ reasoning. Overall, FinLin aims to complement the current knowledge by providing a novel and publicly available financial sentiment corpus and to foster research on the topic of financial sentiment analysis and potential applications in behavioural science.

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“…LSTM based model is an alternative popular method [11] used for modeling dependent data. LSTM and its variations are useful in areas such as Natural Language Processing [12,13], Financial Time series, or some application of speech processing. Many researchers [9,14,15] used an LSTM model to predict the stock price.…”

Section: Introductionmentioning

confidence: 99%

Construction of Confidence Interval for a Univariate Stock Price Signal Predicted Through Long Short Term Memory Network

Dey

Gouda

2020

Ann. Data. Sci.

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In this paper, we show an innovative way to construct bootstrap confidence interval of a signal estimated based on a univariate LSTM model. We take three different types of bootstrap methods for dependent set up. We prescribe some useful suggestions to select the optimal block length while performing the bootstrapping of the sample. We also propose a benchmark to compare the confidence interval measured through different bootstrap strategies. We illustrate the experimental results through some stock price data set.

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Sentiment contagion analysis of interacting investors: Evidence from China’s stock forum

Cited by 30 publications

References 34 publications

Can Stock Investor Sentiment Be Contagious in China?

Can Stock Investor Sentiment Be Contagious in China?

A multi-source entity-level sentiment corpus for the financial domain: the FinLin corpus

Construction of Confidence Interval for a Univariate Stock Price Signal Predicted Through Long Short Term Memory Network

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