This study shows how price limit rules, intended to stabilize markets, inadvertently distort price dynamics by fostering strategic speculation. Through a dynamic rational expectations model, we demonstrate that price limits induce post limit-up price jumps by impeding full information incorporation, enabling speculators to artificially push prices to upper bounds and exploit uninformed traders. The model predicts two distinct patterns: (1) stocks closing at price limits exhibit positive overnight returns followed by long-term reversals, and (2) stocks retreating from upper bounds suffer sharp reversals with partial recovery. Empirical analysis confirms these predictions. A natural experiment from China’s 2020 GEM reform —- which widened the price limit -— further provides causal evidence that relaxed limits mitigate speculative distortions.

This paper models the effect of corporate information preference on stock return volatility based on optimization problems of information decisions for firms and investors. Our model hypothesizes a positive correlation between corporate information preference and volatility. Utilizing the ideal institutional background of the Chinese stock market, we empirically confirm that corporate information preference has a positive impact on volatility, particularly for firms facing more severe financial distress, limited investor attention, and fewer analyst coverage. Our study provides a new perspective for analyzing the interaction between information supply and asset price dynamics.

By testing properties implied by one-dimensional diffusion option pricing models, we find that call (put) prices in the Chinese 50ETF option market move in opposite (same) direction with the underlying between 13.39% and 27.89% (between 12.45% and 33.98%) of the time for 5-minute and 1-day sampling intervals respectively. Given fundamental different investor structures in U.S. and China option markets, we also observe some important unique features in the 50ETF option price dynamics. More importantly, we demonstrate that these striking violations reduce substantially in 2016 compared with those in 2015, indicating that Chinese stock option market becomes more efficient.

In this article, we consider a regulated market and explore the default events. By using a so-called reflected Ornstein-Uhlenbeck process with two-sided barriers to formulate the price dynamics, we derive the expression on the conditional default probability. In the cases of single observation and multiple observations, the conditional default probabilities are explicitly expressed in terms of the inverse Laplace transforms. Finally, we present a numerical simulation associated with the conditional default probability.