We study machine-learning forecasts and portfolio allocation for Chinese government bonds. Penalised linear regressions and gradient-boosted trees predict next-month total returns for eight maturity buckets. Their forecasts feed mean–variance, Black–Litterman, and risk-budgeting implementations with weight, duration, and trading-cost controls; convexity, tail-risk, and attribution constraints are analysed separately as theoretical extensions. From January 2019 through December 2025, the three optimised cash portfolios earn net excess-return Sharpe ratios of 1.94–2.26 and maximum drawdowns of 0.18–0.25%. Three long-only bond-selection variants attain Sharpe ratios of 1.39–1.70. A futures-hedged arbitrage variant attains 1.08 under an 80% hedge-P&L scaling and basis-cost assumption. A stylised 10-year futures overlay reduces rather than improves cash-portfolio Sharpe ratios.

The essay delves into the impact of environmental uncertainty on asymmetric mispricing utilizing the data from listed firms in China spanning from 2007 to 2023. Our analysis reveals that environmental uncertainty amplifies stock mispricing within capital markets, whether upward or downward. Diverging from prior research, we distinguish between upward and downward mispricing and reveal the black box of environmental uncertainty affecting stock mispricing from dual channels. Specifically, environmental uncertainty intensifies upward mispricing through heightened earnings management and exacerbates downward mispricing by boosting investor irrationality. Furthermore, we explore the heterogeneous impact of different media coverage. In the downward mispricing sample, negative media exacerbated the relationship between the two, while positive coverage played a mitigating role. In the upward mispricing sample, only negative reports have a significant impact, and mitigate the impact of uncertainty on mispricing. Our research on media heterogeneity once again proves that it is a double-edged sword. Our research indicates that improving the capacity to recognize different mispricing mechanisms in various market directions can greatly boost decision-making efficiency. Meanwhile, it is vital to strengthen professional ethics in media organizations and encourage more objective reporting. These efforts can jointly contribute to improve he efficiency of emerging capital markets.

This paper studies the economic impact of introducing a personal bankruptcy regime, using China’s recent pilot reforms as a natural experiment. We exploit the staggered rollout of personal bankruptcy frameworks across Chinese cities and construct a novel dataset of bankruptcy case filings, combined with survey-based measures of credit access and official firm registration records. Our difference-in-differences estimates show that the reforms significantly improve small business credit access - business loan take-up increases by 1.3 % (21% relative to pre-reform mean), with no offsetting rise in interest rates. Effects are concentrated among non-corporate firms, firms with less employees and female entrepreneurs. Moreover, the reform is also associated with a 9.7% increase in new firm registrations. To interpret these findings, we develop a simple but novel theoretical model in which personal bankruptcy reduces the downside risk of entrepreneurial failure while preserving creditor recoveries. These findings underscore how debtor protection policies, when designed to reduce enforcement costs without expanding exemption rights, can enhance credit supply and entrepreneurial activity.

The debate on whether legalization or prohibition is more effective in conserving species and curbing illicit black-market trade remains controversial, with insufficient evidence available. Here we investigate the effects of China’s ivory ban on elephant poaching. We find that the enaction of the total ivory ban corresponds with a sharp 50% decrease in poaching and a significant reduction of the number of seizure cases. Further, although China has taken restrictive measures in 2015 and signaled a total ivory ban in 2016, no occurrence of “last minute rush” in smuggling activity was found preceding the implementation of the ivory ban.

影响决策之变量有个人特征、社会影响及情境因素等等，其中个人特征部分又分为：个人资源、动机涉入、知识、态度、人格、价值观与生活型态(Engel 和 Black wall，1990)。而态度，是指人由经验而组织起来的对人、事、物以及周围世界所做的评价，既反映出个人对某些事情的感觉，也是一种相当持久且一致的行为倾向（荣泰生，1999）。而金钱意义除了表面上的购买能力外，还对不同人所代表的意涵也是有所不同的（Keller, C., & Siegrist, M.，2005）。故投资人对金钱的态度会影响投资者决策行为；而投资者不同的风险承担程度会对投资动机产生影响(陈丽梅，2010)。 　　因此，本研究将以(Farley,2000)之风险承担程量表包括风险规避、风险接受及风险偏好三个构面； Yamauchi and Templer(1982)的金态度量表包括权?/名望、保?/时间、诱惑以及焦虑四个构面；及江佳宇(2006)之投资决策量表包括投资信息、产品熟悉度、商业消息、投资者信心及投资意图五个构面对三个变量作为衡量之基础。以观察风险承担程和金钱态度对投资决策的影响程度；同时以金钱态度作为中介变项解释投资决策，以探讨潜在依变项金钱态度是否能增加风险承担对投资决策的解释力。 　　研究结果显示：在人口统计变量分析发现：性别对各变数皆无显著差异；而年龄、教育程度、月收入、投资经验对各变量皆有显著性差异；婚姻状况则只对风险承担形成显著差异；而投资时间之长短则不会显著影响风险承担程度，但显著影响其他变量。各变量以结构方程模式（structural equation model, SEM）作研究工具分析发现：(1)风险承担会影响投资决策部分成立。(2)金钱态度影响投资决策部分成立。(3)当金钱态度作为完全中介变量以增加风险承担对投资决策的解释力部分成立 ,即投资者金钱态度能作为风险承担对投资决策之中介作用。

This paper first studies the Chinese warrant market that has been developing since August 2005. Empirical evidence shows that the market prices of warrants are much higher systematically than the Black-Scholes prices with historical volatility. The prices of a warrant and its underlying asset do not support the monotonicity, perfect correlation and option redundancy properties. The cumulated delta-hedged gains for almost all expired warrants are negative. The negative gains are mainly driven by the volatility risk, and the trading values of the warrants for puts and the market risk for calls. The investors are trading some other risks in addition to the underlying risk.

This paper consists of two parts. In the first part, through the calculation of “binomial correlation measure”, we suggest that from the perspective of default correlation it would be better to use structural approach rather than reduced form approach for pricing derivatives with two counterparties and its CVA calculation unless default intensities follow jump-diffusion process in latter one. In the second part, we derive the pricing model for CDS with counterparty risk and its CVA calculation by Black-Cox first passage time model in structural approach. Different from most of the previous paper our recovery is based on the CDS with counterparty risk, so the pricing model is a boundary-value problem of fully-nonlinear PDE. To solve it, we introduce an approximation problem by penalty model in reduced form approach by assuming an incentive function. Also finite element method and iteration approach are used. The numerical results show the convergence of approximation problem, iteration problem and finite element method, a comparison between CVA with different recovery rules and also the impact of wrong-way risk and right-way risk on CVA.

China launched her warrant market in August 2005 in the split share structure reform of listed companies. As up to now, equity trading on margin and short-sale of any form are still prohibited in China. This warrant market enables investors to trade on information that otherwise might be prohibitively expensive to trade on. The Chinese warrant market created top trading volume and turnover with only a handful of different warrants traded. This paper first studies the Chinese warrant market. Empirical evidence shows that the market prices of warrants are much higher systematically than the Black-Scholes prices with historical volatility. Moreover, the paper documents ample evidence that the one-dimensional diffusion model does not apply well in the Chinese warrant market. The prices of a warrant and its underlying asset do not support the monotonicity, perfect correlation and option redundancy properties. The paper also studies the cumulated gains of a delta-hedged warrant portfolio. In the Chinese warrant market, the cumulated delta-hedged gains for almost all expired warrants are negative. The negative gains are mainly driven by the volatility risk, and the trading values of the warrants for puts and the market risk for calls. The investors are trading some other risks in addition to the underlying risk.

可转债的定价问题是学术界和实务界都关心的问题。本文在考虑行权策略的基础上，采用最小二乘蒙特卡罗模拟（LSMC）对沪深证券市场中交易的可转债进行定价分析。结果表明， 该方法确定的价格略低于市场价格， 模型价格与市场价格误差较小， 且不具有系统性。这与 Black-Scholes 等传统模型系统性高估可转债的价格形成了鲜明对比。另外，最小二乘蒙特卡罗模拟的稳定性要优于 Black-Scholes 模型，尤其是在转股价格调整的时候更是如此。可转债是否处于转股期对于可转债价格的敏感性以及定价误差有一定影响。我们认为，可转债市场价格偏高既与投资者的预期有关，也与市场缺乏套利机制有关。

This paper explores whether the pricing of the option-type derivative is affected by some of fundamental characteristics, such as size and liquidity of the derivative itself and the underlying asset, which are not involved in the standard pricing theory. Considering the unique status of warrants in China due to the relatively more flexible trading mechanism, I empirically examine the pricing of Chinese covered warrants to develop this study. Empirical results show that market prices of Chinese warrants are significantly higher than theoretical prices predicted by traditional pricing models such as Black-Scholes, Jump-Diffusion, and CEV model. For call warrants, about 25 percent of the market price can not be explained by pricing models, and this figure rises to over 60 percent for put warrants. Further regression tests show that both size and liquidity of warrants and underlying stocks significantly affect warrant pricing errors. The way in which the size and liquidity affect the pricing error depends on the type of warrants. In addition, it is evident that movements of put warrant prices in China do not follow movements of stock prices. To explain the above pricing puzzles,the concept of functional asset pricing is proposed. According to this concept, these pricing puzzles just reflect the existence of functional value of financial instruments that has long been neglected by traditional pricing models. In fact, Due to the high level of liquidity and popularity, the Chinese warrant may well function as a good tool for obtaining short-term profits. The pricing of Chinese warrants by the market may correctly re°ect the value of this function, and thus is rational in essence.