Over the past 30 years, the rise of the Chinese economy has elevated the significance of its financial markets. With more data becoming available and regulations improving efficiency, research on multifactor models explaining stock returns in this retail investor dominated ecosystem becomes feasible. However, the most prominent model, CH-3, employs an extreme filter by excluding the lowest 30% of stocks by market capitalization to reduce the impact of shell value through reverse merger IPOs 3 a practice dominant in the early 2000s. This thesis introduces an individual sentiment factor by running a horserace on social media-based proxies. To analyse the performance of the new four-factor CH-G model, it is tested against a replicated CH-3 model across three subsamples, with a focus on including and excluding microcaps. The CH-G better captures the characteristics of the Chinese stock market in the 2009 to 2023 period, with the sentiment factor proving significant across panels. The model demonstrates higher average adjusted R-squares and notable explanatory power, especially when including all individual stocks instead of excluding the smallest 30%. This supports the argument that excluding microcaps may no longer be appropriate in the evolving Chinese market.
Date of Award | 17 Oct 2024 |
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Original language | English |
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Awarding Institution | - Universidade Católica Portuguesa
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Supervisor | Mengdi Gu (Supervisor) |
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- Chinese stock returns
- Multifactor models
- CH-3
- Individual investor sentiment
- Mestrado em Finanças (mestrado internacional)
The role of individual investor sentiment as a factor in the Chinese stock market
Hirsch, M. (Student). 17 Oct 2024
Student thesis: Master's Thesis