Stock market manipulation: A comparative analysis of East Asian emerging and developed financial markets

Abstract

The study investigates the firm's specific characteristics of manipulated firms in East Asian emerging and developed markets using hand-collected 244 manipulated cases between 2001 and 2017. The empirical analysis is conducted using panel logistic regression to identify which stocks are more likely to be manipulated. Result shows that large and highly liquid firms were more likely to be manipulated in both emerging and developed markets. Additionally, marginal effect shows that firms with high free float and market capitalization had a higher probability of being manipulated in these markets. On the contrary, profitable firms were less likely to be manipulated in both developed and emerging markets. Limited studies have been conducted to empirically identify the characteristics of the manipulated stocks across the developed and emerging markets. The regulator can use these results to identify possible and expected manipulation and to design enforcement rules, accordingly. Further, investors can take into consideration these characteristics of manipulated stocks while designing their portfolio in order to reduce the portfolio risk.

Market abuse under different close price determination mechanisms: A European case

“…One strand is based on prosecuted case studies, another on econometric modeling of data with investor details. Regarding prosecuted cases stock market manipulation has taken place in the stock markets of Canada (Comerton-Forde & Putnicnš, 2011, Hong-Kong (Gerace et al, 2014), Taiwan (Huang & Cheng, 2015), Turkey (Öugüt et al, 2009), the US (Aggarwal & Wu, 2006;Comerton-Forde & Putnicnš, 2011 as well as in the East Asian regions (Shah et al, 2019). The evidence suggest that manipulators obtain wealth at the expense of others and market efficiency is negatively impacted.…”

“…Liquidity, returns, bid-ask spreads, volatility and trading activity are worse off due to manipulation. Moreover, the negative effects of manipulation spread to stocks irrespective of their liquidity and/or market capitalization; hence necessitating appropriate course of action (Aggarwal & Wu, 2006;Shah et al, 2019). Empirical studies using data with investor details are limited due to the data availability, see for example Felixson and Pelli (1999), Khwaja and Mian (2005), Lee et al, (2013) and references therein.…”

Stock Price Manipulation Detection Using Deep Unsupervised Learning: The Case of Thailand

“…Palshikar and Bahulkar [15] also proved that temporal price and volume patterns repeated themselves while a stock was manipulated. In the context of sizes of companies, both small and large size companies in developed and emerging financial markets were equally likely to be manipulated [14], [16], [17], [18], [19]. Two common types of investors also involve stock manipulation.…”

Assessing four decades of global research studies on stock market manipulations: a sceintometric analysis

“…Few researchers in the literature shed light on “market abuses” at stock exchanges (Aussenegg et al , 2018) and elaborate on these fraudulent activities as “market manipulation”. Öǧüt et al (2009), Vlad (2014), Maxim and Ashif (2017), Shah et al (2019) The traditional manipulation is defined in numerous research papers, review articles, case studies, laws, etc., as “pump and dump” schemes (Huang and Cheng, 2015; Neupane et al , 2017; Riyanto and Arifin, 2018; Lee et al , 2019) and “insider trading” (Benabou and Laroque, 1992; John and Narayanan, 1997; Austin, 2016; Kan, 2018; Brochet, 2019). For no less than a decade, market manipulation, stock market abuses have been associated with “social media” or “internet” in various research studies.…”