Tax avoidance news, investor behavior, and stock market performance
Finance Research Letters, ISSN: 1544-6123, Vol: 67, Page: 105834
2024
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
This study investigates the relationship between tax avoidance news, investor behavior, and stock market performance in the Chinese financial context. Leveraging a comprehensive dataset spanning 2020–2023, we employ regression analyses and robustness tests to examine the impact of tax avoidance news on stock market performance. This quantitative empirical study addresses a significant gap in our understanding of the financial implications of tax avoidance news in China, highlighting its substantial influence on investor decisions and market dynamics. Key findings indicate that tax avoidance news leads to increased stock price volatility, moderated by investor trading behavior. This research contributes to the literature on taxation and financial markets by offering practical insights for policymakers, investors, and corporate entities. By understanding these dynamics, stakeholders can better navigate the complexities of financial markets and enhance corporate transparency and governance. The findings underscore the importance of effective communication and ethical practices in mitigating adverse market reactions, potentially influencing regulatory reforms and investment strategies.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S154461232400864X; http://dx.doi.org/10.1016/j.frl.2024.105834; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85198578975&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S154461232400864X; https://dx.doi.org/10.1016/j.frl.2024.105834
Elsevier BV
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