Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Whether the online social media, like Twitter or its variant ibo, can be a convincing proxy to predict the stock market has been debated for years, especially for China. Hover, as the traditional theory in behavioral finance states, the individual emotions can influence decision-making of investors, so it is reasonable to further explore this controversial topic from the perspective of online emotions, which is richly carried by massive tets in social media. Surprisingly, through thorough study on over 10 million stock-relevant tets from ibo, both correlation analysis and causality test show that five attributes of the stock market in China can be competently predicted by various online emotions, like disgust, joy, sadness and fear. Specifically, the presented model significantly outperforms the baseline solutions on predicting five attributes of the stock market under the $K$-means discretization.  also employ this model in the scenario of realistic online application and its performance is further testified.
['Zhenkun Zhou', 'Jichang Zhao', 'Ke Xu']
I am writing a research paper on a idea Can Online Emotions Predict the Stock Market in China
[{"from": "human", "value": "I am writing a research paper on a idea Can Online Emotions Predict the Stock Market in China"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Whether the online social media, like Twitter or its variant ibo, can be a convincing proxy to predict the stock market has been debated for years, especially for China. Hover, as the traditional theory in behavioral finance states, the individual emotions can influence decision-making of investors, so it is reasonable to further explore this controversial topic from the perspective of online emotions, which is richly carried by massive tets in social media. Surprisingly, through thorough study on over 10 million stock-relevant tets from ibo, both correlation analysis and causality test show that five attributes of the stock market in China can be competently predicted by various online emotions, like disgust, joy, sadness and fear. Specifically, the presented model significantly outperforms the baseline solutions on predicting five attributes of the stock market under the $K$-means discretization.  also employ this model in the scenario of realistic online application and its performance is further testified."}]