High-frequency trading (HFT) has significantly transformed modern financial markets, influencing liquidity, volatility, and price efficiency. This paper presents a mathematical modeling approach to analyze the impact of HFT on market liquidity using queueing theory and game-theoretic frameworks. We examine both the liquidity-enhancing and destabilizing effects of HFT, emphasizing its role in spread reduction, order book depth, and volatility fluctuations. Empirical evidence suggests that while HFT improves liquidity in stable conditions, it may withdraw liquidity during market stress, amplifying volatility. Additionally, we explore regulatory challenges and policy interventions, such as financial transaction taxes, speed bumps, and market maker obligations, to mitigate systemic risks while preserving market efficiency. Future research should focus on AI-driven HFT, cross-asset liquidity dynamics, and HFT’s role in emerging markets. The findings contribute to the ongoing debates on whether HFT stabilizes or destabilizes financial markets, providing insights for academics, regulators, and market participants.

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In recent years, as Corporate Social Responsibility (CSR) reports have evolved from marginal texts to strategic tools, investors have gradually recognized the limitations of traditional financial indicators. This study focuses on how accounting information in CSR reports penetrates the superficial layer of "responsibility narratives" and actually influences investment decisions. Through literature analysis, case studies, and theoretical reasoning, it answers two core questions: Which accounting data truly trigger investors' nerves? How do these data convey the sustainable development potential of enterprises? The study finds that accounting indicators, such as environmental governance costs and employee welfare expenditures, constitute the anchor points of "responsibility credibility", and the quality of their disclosure directly affects the risk pricing in the capital market. It suggests that enterprises adopt "industry-customized" disclosure strategies, while investors need to establish a "financial-responsibility" dual-dimension analysis framework. The study reveals a new path for the capitalization of non-financial information, providing a new perspective for value assessment in the era of responsibility.

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A notable feature of the Chinese economy over the past decade has been the continuous decline in nominal interest rates. As of May 2025, the one-year loan prime rate (LPR) had gradually declined from 5.3% to 3.1% (data from the People's Bank of China (PBoC). Although conventional wisdom suggests that a low interest rate environment can stimulate economic activity, many studies in recent years have shown that a persistently low interest rate environment can exacerbate capital misallocation in the credit market, leading to economic contraction. This paper studies the impact of the current low interest rate environment on the credit market under China's economic system by constructing an Agent-Based Model. The study found that a sustained low interest rate environment will exacerbate the capital mismatch between state-owned enterprises and private enterprises in the credit market, which in turn will lead to a decline in the average return on investment. Structural reforms can eliminate the adverse effects of this phenomenon, but there are still difficulties in practice.

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This study outlines some integrated approaches for pairs trading and portfolio analysis, focusing on the performance in generating consistent returns under varying market conditions over one year. The relationships between returns and some relevant factors are also explored. Steps for pairs trading involve selecting securities with strong historical associations or return correlations, normalizing their price series, calculating related price statistics, and employing a strategy based on Z-score to identify trading opportunities. Regression analysis of performance metrics across thousands of pairs highlights the significant relationship between the standard deviation of spread and profitability, whereas the return correlation is insignificant. The chosen portfolio exhibits low volatility, a high Sharpe ratio, and minimal drawdowns. Incorporating trading costs reveals a break-even point where the overall profit is zero. This confirms the strategy's robustness and real-world feasibility. In this paper, our result is against the weak form of the market efficiency theory, showing that strategies based on past information can generate consistent returns.

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