As China's bond market expands rapidly, the complexity of financial guarantee networks and their implications for credit risk have become critical issues in both academic research and financial practice. Utilizing micro-level data from China's credit bond market spanning 2014 to 2024, this study constructs a multi-layer network incorporating bonds, guarantors, and issuing firms to empirically examine the impact of guarantor network centrality on bond credit spreads. The results reveal a significant U-shaped relationship: moderate centrality reduces spreads by bolstering market confidence, whereas excessive centrality increases them due to heightened systemic risk. Mechanism analyses identify systemic risk and information asymmetry as key mediating channels through which centrality affects credit risk premiums. Heterogeneity tests indicate that this U-shaped pattern is more pronounced among state-owned guarantors, real estate firms, and high-risk clusters within the network. Furthermore, both cross-layer connectivity within the multi-layer structure and regional financial development levels significantly moderate the centrality-spread relationship. These findings offer a structural perspective on credit risk pricing in emerging markets and provide valuable policy insights for credit rating system design, guarantee regulation, and systemic risk prevention. International investors could also leverage these findings to better assess systemic risk in interconnected financial markets across emerging economies.

Straddle Option is a financial trading tool that explores volatility premiums in high-volatility markets without predicting price direction. Although deep reinforcement learning has emerged as a powerful approach to trading automation in financial markets, existing work mostly focused on predicting price trends and making trading decisions by combining multidimensional datasets like blogs and videos, which led to high computational costs and unstable performance in high-volatility markets. To tackle this challenge, we develop automated straddle option trading based on reinforcement learning and attention mechanisms to handle unpredictability in high-volatility markets. Firstly, we leverage the attention mechanisms in Transformer DDQN through both self-attention with time series data and channel attention with multi-cycle information. Secondly, a novel reward function considering excess earnings is designed to focus on long-term profits and neglect short-term losses over a stop line. Thirdly, we identify the resistance levels to provide reference information when great uncertainty in price movements occurs with intensified battle between the buyers and sellers. Through extensive experiments on the Chinese stock, Brent crude oil, and Bitcoin markets, our attention-based Transformer-DDQN model exhibits the lowest maximum drawdown across all markets, and outperforms other models by 92.5% in terms of the average return excluding the crude oil market due to relatively low fluctuation.

As companies and investors globalize, we are increasingly faced with estimation questions about the risk associated with this globalization. When investors invest in China Mobile, Infosys or Vale, they may be rewarded with higher returns, but they are also exposed to additional risk. When Siemens and Apple push for growth in Asia and Latin America, they clearly are exposed to the political and economic turmoil that often characterize these markets. In practical terms, how, if at all, should we adjust for this additional risk? We will begin the paper with an overview of overall country risk, its sources and measures. We will continue with a discussion of sovereign default risk and examine sovereign ratings and credit default swaps (CDS) as measures of that risk. We will extend that discussion to look at country risk from the perspective of equity investors, by looking at equity risk premiums for different countries and consequences for valuation. In the fourth section, we argue that a company’s exposure to country risk should not be determined by where it is incorporated and traded. By that measure, neither Coca Cola nor Nestle are exposed to country risk. Exposure to country risk should come from a company’s operations, making country risk a critical component of the valuation of almost every large multinational corporation. In the final section, we will also look at how to move across currencies in valuation and capital budgeting, and how to avoid mismatching errors.

February 9, 2025 marks the 10th anniversary of the establishment of China's ETF options market. To celebrate this anniversary, China will open the ETF options market to qualified foreign investors on October 9, 2025. This is both an opportunity and a challenge. This is the first time in a decade that China has decided to open its ETF options market. The challenge is that foreign investors will face competition from China's 1.08 million options investors. This article will discuss the basic rules and requirements for options trading in China. In addition, we will introduce the application of Confusion Quotient sentiment index in options trading, and analyze how options contract premiums fluctuated significantly after the Fed cut interest rates by 50 basis points on September 18, 2024. Within a month, the Fed's interest rate cut triggered a sharp rise in call options contracts in China's options market, with a maximum profit of 3507.32%, and put option contracts suffered huge losses, with a maximum loss of 99.91%. Our findings prove that China's ETF options market is highly volatile, presenting both opportunities and challenges for foreign investors. Options trading is a double-edged sword, and you need to be cautious when entering the market.

This paper investigates the gambling preference of Chinese investors in the convertible bond (CB) market through a natural experiment—the 2018 amendment of Article 142 of the Company Law. Utilizing CB issuance data from 2016 to 2023, we employ a cohort difference-in-difference approach and find a 4% to 7% increase in IPO premiums for high-repurchase-expectation CBs across various measures. This significant increase indicates that the legal revision reshapes investors’ expectation and adjusts their valuation of CBs. Furthermore, the event-study analysis reveals the escalating impact of legal revision, driven by the herding behavior of gambling investors.

This study explores the anchoring effect of previous bid premiums on acquirers’ bidding behavior in serial acquisitions. We demonstrate that, after controlling for deal characteristics, learning, and unobserved factors, the current bid premium is positively correlated with the acquirer’s previous bid premium. The strength of this anchoring effect diminishes with longer time intervals between acquisitions and increases with the industry similarity of targets. Notably, it remains unaffected by the acquirer’s state ownership or acquisition frequency. Additionally, the anchoring effect is less pronounced during periods of high economic uncertainty and can reverse following a change in the acquirer’s CEO. Our findings suggest that serial acquisitions are interrelated events, challenging the notion that each bid is an isolated occurrence. This research provides insights into the underperformance of serial acquirers compared to single acquirers and the declining trend in announcement returns across successive deals.

We examine the risk-return trade-off in market anomalies within the A-share market, showing that even decaying anomalies may proxy for latent risk factors. To balance forecast bias and variance, we integrate the 1/N and mean-variance frameworks, minimizing out-of-sample forecast error. Treating anomalies as tradable assets, we construct optimized long-short portfolios with strong performance: an average annualized Sharpe ratio of 1.56 and a certainty-equivalent return of 29.4% for a meanvariance investor. These premiums persist post-publication and are largely driven by liquidity risk exposures. Our results remain robust to market frictions, including shortsale constraints and transaction costs. We conclude that even decaying market anomalies may reflect priced risk premia rather than mere mispricing. This research provides practical guidance for academics and investors in return predictability and asset allocation, especially in the unique context of the Chinese A-share market.

We examine the risk-return trade-off in market anomalies within the A-share market, showing that even decaying anomalies may proxy for latent risk factors. To balance forecast bias and variance, we integrate the 1/N and mean-variance frameworks, minimizing out-of-sample forecast error. Treating anomalies as tradable assets, we construct optimized long-short portfolios with strong performance: an average annualized Sharpe ratio of 1.56 and a certainty-equivalent return of 29.4% for a mean-variance investor. These premiums persist post-publication and are largely driven by liquidity risk exposures. Our results remain robust to market frictions, including short-sale constraints and transaction costs. We conclude that even decaying market anomalies may reflect priced risk premia rather than mere mispricing. This research provides practical guidance for academics and investors in return predictability and asset allocation, especially in the unique context of the Chinese A-share market.

Culture and experience associate A with superior quality. In the marketing of dual-class IPOs, issuers are mindful of this preference. For years after IPO issuance, inferior voting rights shares labeled Class A enjoy higher market valuations and smaller voting premiums than do Class B shares.

The study introduces 'earnings purity,' a concept based on the 'gold content' of target earnings, to evaluate its impact on merger and acquisition (M&A) premiums. Our findings reveal that targets with higher earnings purity command increased valuations and premiums. Further analysis of the information effects uncovers a U-shaped relationship between earnings purity and negotiation duration, suggesting that elevated premiums might not always be justified. The heterogeneity test indicates that the effect of a target firm's earnings purity on M&A premiums is more pronounced in cross-border and inter-industry M&As. However, it is less influential in cases with larger target firms and better external conditions. These results highlight the dual aspects of M&As, presenting them as both advantageous and potentially hazardous.