Shunming Zhang

We study a risk-neutral firm's endogenous disclosure commitment before a fixed-precision signal is realized. A representative investor faces variance ambiguity, and the firm anticipates how disclosure changes the investor's worst-case valuation. Disclosure lowers the date-0 averages of the posterior mean and variance. The lower mean depresses the expected price, whereas the lower variance raises it. Two cases arise: costless disclosure is optimal at every degree of ambiguity, or a unique ambiguity threshold exists, with disclosure below it and nondisclosure above it. Thus, variance ambiguity can generate corporate opacity even when disclosure is costless.

This paper develops a behavioral-structural model of credit risk that integrates investor salience bias into a dynamic rollover-risk framework. Investors’ overweighting of the salient default state relative to the survival state depresses the price of newly issued bonds, increases firms’ rollover losses, and endogenously induces earlier default. The model nests a Leland-type benchmark without rollover-related illiquidity as well as a rational illiquidity benchmark, allowing us to distinguish the effects of salience from those of rollover frictions. Quantitatively, salience raises credit spreads through two channels. It lowers debt prices directly for a given default boundary and indirectly increases spreads by inducing firms to adopt a higher endogenous default threshold. The model also implies that credit spreads become more sensitive to deteriorating refinancing conditions when debt is priced by salience-distorted investors, with the main quantitative effect operating through the default component rather than through a large increase in the illiquidity premium itself. In addition, the impact of salience is stronger for firms with shorter debt maturity, which are more exposed to repeated refinancing. The model further implies a safety premium erosion mechanism: when downside risk becomes more salient, high-grade bonds can undergo pronounced relative repricing. We calibrate the model to China’s corporate bond market and obtain substantial heterogeneity across rating segments. The estimated salience parameter is higher for AAA bonds than for Non-AAA bonds, suggesting that the behavioral component of credit pricing is weaker in the high-grade segment and more pronounced in the lower-rated segment.

Firms can leverage Fintech to optimize capital allocation. This paper examines the impact of China's 2016 Fintech regulatory policy on firms' financialization, along with its influencing mechanisms and economic consequences. The results show that Fintech regulation significantly reduces financial assets investment of listed companies in China through the mitigated precautionary and speculative incentives, leading to the economic consequences of declining real assets investment, reducing short-term profits, and eventually decreasing market value of listed companies. Therefore, this paper not only contributes to existing literature on Fintech and firms' financialization, but also offers valuable policy insights for optimization of Fintech regulation framework.

This paper studies how probability distortion affects the sensitivity of asset prices to order flow. We develop a simple asset-pricing model in which optimistic investors overweight favorable outcomes when evaluating risky assets. This distortion generates a flat segment in their demand, implying that equilibrium prices can become locally insensitive to liquidity shocks. As a result, the model produces price inertia: over a range of order imbalances, prices do not respond to order flow. The width of this inelastic region increases with investor optimism and the fraction of optimistic traders. When investors update their beliefs dynamically in response to realized outcomes, the model endogenously generates regimes of low and high volatility. The analysis provides a behavioral explanation for price inertia, sudden market adjustments, and volatility clustering.

We examine how increasing market concentration, driven by dominant institutional investors, affects investor behavior and price dynamics. We develop a two-period non-competitive model in which large investors with market power trade strategically against small pricetakers. Large investors’ market power induces trading persistence, as they adjust their portfolios only partially due to price impact. Greater concentration amplifies this persistence. Under symmetric information, market concentration monotonically increases price reversals and volatility. Under asymmetric information, its effect is hump-shaped: moderate concentration enhances efficiency by improving price informativeness, reducing price reversals and volatility, while excessive dominance reverses these gains, reducing efficiency and stability.

We develops a behavioral-structural model of credit risk that integrates investor salience bias into a dynamic rollover risk framework. We show that investors' overweighting of salient default states underprices newly issued bonds, increasing rollover losses and endogenously motivating early default. This mechanism generates realistic spreads and captures the non-linear "crisis multiplier" effect during liquidity shocks. We uncover "safety premium erosion", where high-quality bonds are more sensitive to salience distortions. Calibrating the model to China reveals a stark dichotomy: AAA bonds are priced near-rationally due to implicit government guarantees suppressing default salience, whereas Non-AAA bonds bear the full brunt of behavioral overreaction. This highlights the critical interaction between behavioral bias and institutional support in pricing credit risk.