Why Are Warrant Markets Sustained in Taiwan but Not in China?

Abstract

This paper uses moment analysis, capital asset pricing model (CAPM) statistics, stochastic dominance (SD) test, and volume analysis to investigating why the market for Taiwan warrants can be sustained but not in China. Our moment analysis shows that buying in China warrants has a higher likelihood of losses. Our CAPM analysis shows that both the Sharpe ratio and Jensen index for warrants from the Chinese market are too negative. The Treynor index shows that Chinese warrants are highly volatile. Our SD analysis shows that risk averters prefer to invest in Chinese warrants compared to Taiwanese warrants, implying that the warrant issuers prefer to issue Taiwanese warrants than Chinese warrants. Using volume analysis, the Chinese warrant market is much more active, implying more speculative activities in China than in Taiwan. All the above could lead to China’s decision to close its warrant market. The findings in the paper are useful for academics, investors, and policy makers.

The Three Musketeers Relationships between Hong Kong, Shanghai and Shenzhen Before and After Shanghai–Hong Kong Stock Connect

“…It is suggested here that This paper studies sustainability of financial integration among Shenzhen, Shanghai, and Hong Kong stock markets. An extension of our paper could study sustainability of other aspects of financial markets, for example, sustainability in warrant markets [48], sustainability in REITs [49], sustainability in equity return dispersion and stock market volatility [50], sustainability in herding behaviour [51], sustainability in portfolio selection [52], and sustainability in credit risk [53]. This paper studies sustainability of financial integration among Shenzhen, Shanghai, and Hong Kong stock markets.…”

Sustainable Portfolio Optimization with Higher-Order Moments of Risk

“…Investors always look for a portfolio which provides maximum return at minimum risk [7]. Previous studies presented the notion of diversification that by dividing available capital into smaller parts and investing those small portions of the capital into various small investments can spread the risk against a single large risk in case of a single investment [15]. However, a rational for portfolio diversification is missing because they are unable to diversify the non-systematic risk (diversifiable risk) [19].…”

“…However, excess kurtosis indicates the high probability of extreme events either positive or negative called fat-tail risk or leptokurtic risk. The presence of skewness and kurtosis in financial returns indicate the necessary inclusion of these moments of risk to optimize the portfolio and its behavioral description [15,16]. Optimization based on mean-variance can lead to understated risk, which could result in an inefficient portfolio.…”

Optimal Solution Techniques in Decision Sciences: A Review

“…The SD theory can be used in many areas, including indifference curves (Wong, 2006(Wong, , 2007Ma and Wong, 2010;Broll, Egozcue, Wong, and Zitikis, 2010), two-moment decision model (Broll, Guo, Welzel, and Wong, 2015;Guo, Wagener, and Wong, 2018), moment rule (Chan, Chow, Guo, and Wong, 2018), economic growth (Chow, Vieito, and Wong, 2018), diversification Egozcue, Fuentes García, Wong, and Zitikis, 2011;Lozza, Wong, Fabozzi, and Egozcue, 2018). It can also be applied to many different assets, including stock (Fong, Lean, and Wong, 2008), fund Zumwalt, 2007, 2012;Wong, Phoon, Lean, 2008), futures (Lean, McAleer, Wong, 2010;Lean, Phoon, Wong, 2012;Qiao, Clark, Wong, 2012;Qiao, Wong, Fung, 2013;Lean, McAleer, Wong, 2015;Clark, Qiao, Wong, 2016), Warrant (Chan, de Peretti, Qiao, Wong, 2012;Wong, Lean, McAleer, Tsai, 2018), Option (Abid, Mroua, and 2009), wine (Bouri, Gupta, Wong, and Zhu, 2018), warrants (Chan, de Peretti, Qiao, and Wong, 2012), gold Zhu, 2015, 2018;Hoang, Zhu, El Khamlichi, and Wong, 2019) , property market (Qiao, Wong, 2015;Tsang, Wong, Horowitz, 2016).…”