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Lead-lag relationship between investor sentiment in social media9 investor attention in google, and stock return
Rizkiana A.a, Hasrini S.a, Hardjomidjojo P.a, Prihartono B.a, Sunaryo I.a, Prasetyo I.R.a
a Teknik Dan Manajemen Industri, Institut Teknologi Bandung, Bandung, Indonesia
[vc_row][vc_column][vc_row_inner][vc_column_inner][vc_separator css=”.vc_custom_1624529070653{padding-top: 30px !important;padding-bottom: 30px !important;}”][/vc_column_inner][/vc_row_inner][vc_row_inner layout=”boxed”][vc_column_inner width=”3/4″ css=”.vc_custom_1624695412187{border-right-width: 1px !important;border-right-color: #dddddd !important;border-right-style: solid !important;border-radius: 1px !important;}”][vc_empty_space][megatron_heading title=”Abstract” size=”size-sm” text_align=”text-left”][vc_column_text]© 2018 IEEE.Investor sentiment has a significant role in driving stock prices. Although many previous studies show that investor sentiment in social media can be used to predict stock price movements, there are two things that still need further investigation. The first one is related to the attention of investors that affect the ability to predict the movement of stocks price and its interaction with investor sentiment. The second one is related to the effect of the lead-lag relationship between investor sentiment, investor attention, and stock return. Therefore, the purpose of this research is to understand the effect of the lead-lag relationship between the three variables as well as the interaction between investor sentiment and investor attention in predicting the movement of stock prices. The steps taken to answer the research problem are to measure investor sentiment based on comments in social media Stockbit, measure investor attention based on search volume obtained from Google Trend, and then test the effect of lead-lag relationship and interaction between variable using Granger causality analysis and vector autoregression. Test results show that investor sentiment in Indonesia is a reaction from stock returns, not the cause, so it cannot be used to predict stock price movement. Also, investor attention measured by search volume in Google Trend cannot be used to predict stock price movement either. There are four reasons on why investor sentiment has no significant effect on stock return, which is the speed of information diffusion on the stock price, data source used, size of stock capitalization tested, and selection of investor sentiment measurement method. Furthermore, there are two reasons on why investor attention has no significant effect on stock return, which is related to stock capitalization size tested and google search volume that does not reflect investor attention. The insignificant effects of investor sentiment variable and investor attention to stock returns cause the interaction between the two not significant.[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Author keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Auto regression,Google,Investor attention,Lead-lag,Sentiment investors,Social media,Stocks[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Indexed keywords” size=”size-sm” text_align=”text-left”][vc_column_text]Google,Investor attention,Lead-lag,Sentiment investor,Social media,Stocks,Vector auto regression[/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”Funding details” size=”size-sm” text_align=”text-left”][vc_column_text][/vc_column_text][vc_empty_space][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][vc_empty_space][megatron_heading title=”DOI” size=”size-sm” text_align=”text-left”][vc_column_text]https://doi.org/10.1109/ICDIM.2018.8847094[/vc_column_text][/vc_column_inner][vc_column_inner width=”1/4″][vc_column_text]Widget Plumx[/vc_column_text][/vc_column_inner][/vc_row_inner][/vc_column][/vc_row][vc_row][vc_column][vc_separator css=”.vc_custom_1624528584150{padding-top: 25px !important;padding-bottom: 25px !important;}”][/vc_column][/vc_row]