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The price discovery in finance markets has been the focus of many researches. On the basis of 1‐min high‐frequency returns, this paper sets out to examine the dynamics of price discovery between the China Securities Index 300 index and its derivative products: the futures, the index exchange‐traded fund (ETF), and the ETF options. Nonparametric nonlinear method thermal optimal path method is adopted in this study. The empirical evidence shows a clear difference in price discovery ability concerning the three products under investigation, and their rank (sorted by strength) can be presented as options, futures, and ETF. In addition, the leading phenomenon has been verified by the regression method. Furthermore, we find that out‐of‐the‐money options have the strongest price discovery ability among different moneyness option contracts. On this basis, we find that leverage is an important factor affecting the ability of price discovery.

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In this paper, we investigate whether the option features in convertible bonds lead to price discovery. On the basis of minute-level data from January 2019 to December 2021, we find that the convertible bond market contributes to the price discovery of the stock market by using the thermal optimal path method, and that the option features in convertible bonds are an important factor affecting the price discovery ability. Regression analysis shows that the effect of option features remains significant after controlling for a range of variables, such as the size of the convertible bond, the premium rate, information shock, and volatility. In addition, we further explore the impact of the difference in trading regimes between the convertible bond market and the equity market on price discovery.

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