The development of composite sentiment index in Indonesia based on the internet-available data

• Main Authors: A. Rizkiana, H. Sari, P. Hardjomidjojo, B. Prihartono
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2019-01-01
• Series: Cogent Economics & Finance
• Subjects: google search; investor sentiment; news sentiment; principal component analysis; social media
• Online Access: http://dx.doi.org/10.1080/23322039.2019.1669399

The development of internet technology raises new sentiment measures used to predict stock market return. This raises a new problem because we must choose carefully which sentiment measures to be used to predict stock market return because various correlations and limitations of these different data sources, different sentiment measures, and its general prediction applicability to different domains are unclear. Since there are no perfect and/or uncontroversial proxies for investor sentiment, we will develop a composite sentiment index based on those different sentiment measures using principal component analysis. The investor sentiment measures we use are investor sentiment measured in social media, google search volume, and news media sentiment. We find that each investor sentiment proxies are positively related to sentiment index. We also find that investor sentiment in news media has one-day lag compared to investor sentiment in social media and investor attention in google trend. Lastly, we confirm that investor sentiment cannot be used to predict stock return.