Using the unique regulatory setting from the Hong Kong stock market with both shortable and no-short stocks, we document that no-short stocks on average earn significantly higher average returns than shortable stocks. Furthermore, stocks that comove more with the portfolio of no-short stocks than with the portfolio of shortable stocks on average earn higher subsequent abnormal returns. Additions to and deletions from the shorting list only partially contribute to the no-short return premium. To interpret our findings, we provide a theoretical model showing that rational investors’ discounting for the mispricing risk of no-short stocks can lead to the no-short return premium.

This paper studies the transmission of monetary policy to the stock market through investors’ discount factors. To isolate this channel, we investigate the effect of US monetary policy surprises on the ratio of prices of the same stock listed simultaneously in Hong Kong and Mainland China, and thereby control for revisions in cash-flow expectations. We find this channel to be strong and asymmetric, with the effect driven by surprise monetary policy interest rate cuts. A 100 basis point surprise cut results in a 30 basis point increase in the ratio of stock prices over 5 days. These results suggest significant slow-moving reductions in stock market risk premia following accommodating monetary policy surprises.

A lack of sufficient information about potential borrowers is a major obstacle to access to financing from the traditional financial sector. In response to the need for better information to prevent fraud, to increase access to finance and to support balanced sustainable development, countries around the world have moved over the past several decades to develop credit information reporting requirements and systems to improve the coverage and quality of credit information. Until recently, such requirements mainly covered only banks. However, with the process of digital transformation in China and around the world, a range of new credit providers have emerged, in the context of financial technology (FinTech, TechFin and BigTech). Application of advanced data and analytics technologies provides major opportunities for both market participants – both traditional and otherwise – as well as for credit information agencies: by utilizing advanced technologies, participants and credit reporting agencies can collect massive amounts of information from various online and other activities (‘Big Data’), which contributes to the analysis of borrowing behavior and improves the accuracy of creditworthiness assessments, thereby enhancing availability of finance and supporting growth and development while also moderating prudential, behavioral and conduct related concerns at the heart of financial regulation. Reflecting international experience, China has over the past three decades developed a regulatory regime for credit information reporting and business. However, even in the context of traditional banking and credit, it has not come without problems. With the rapid growth and development of FinTech, TechFin and BigTech lenders, however, have come both real opportunities to leverage credit information and data but also real challenges around its regulation. For example, due to fragmented sources of borrower information and the involvement of many players of different types, there are difficulties in clarifying the business scope of credit reporting and also serious problems in relation to customer protection. Moreover, inadequate incentives for credit information and data sharing pose a challenge for regulators to promote competition and innovation in the credit market. Drawing upon the experiences of other jurisdictions, including the United States, United Kingdom, European Union, Singapore and Hong Kong, this paper argues that China should establish a sophisticated licensing regime and setout differentiated requirements for credit reporting agencies in line with the scope and nature of their business, thus addressing potential for regulatory arbitrage. Further, there is a need to formulate specific rules governing the provision of customer information to credit reporting agencies and the resolution of disputes arising from the accuracy and completeness of credit data. An effective information and data sharing scheme should be in place to help lenders make appropriate credit decisions and facilitate access to finance where necessary. The lessons from China’s experience in turn hold key lessons for other jurisdictions as they move from credit information to credit data regulation in their own financial systems.

We examine the interest rate pass-through in Hong Kong (HK) and Macao to see if the monetary policy transmission mechanism has been impaired since the Global Financial Crisis (GFC). Our results show that, in the post-GFC period, both the long-run and short-run interest rate pass-through from policy rates to prime rates have disappeared in Macao and weakened significantly in HK. The long-term relationship between deposit rates and policy rates no longer exists in either market while the short-term relationship has been reduced significantly. The results indicate that the effectiveness of the monetary policy in HK and Macao has been seriously undermined after the GFC and alternative monetary policy tools were needed.

Purpose – For Chinese companies that cross-list in Chinese A share and Hong Kong (H share) markets, the H share price has been consistently lower than the A share price by an average of 85% in recent years. This is puzzling because most institutional differences between the two markets have been eliminated since 2007. The purpose of this study is to explain the puzzle of the price difference of AþH companies. Design/methodology/approach – Using all A and H share Chinese firms in the period 2007–2013 and a simultaneous equations approach, this study identifies three new explanations for the recent price difference. Findings – First, utilizing a unique earning quality measure that is directly related to non-persistent components of fair value accounting under International Financial Reporting Standards (IFRS), this study finds that the lower the earnings quality, the lower the H share price relative to the A share price, and hence the greaterthe price difference. Second, the higherthe myopic investor ownership in A share firms, the largerthe A share price relative to the H share price. Third, the short-selling mechanism introduced to the A share market since 2010 helps reduce the price difference. Originality/value – First, this study identifies three new explanations for the puzzle of the AH price difference which remains substantial even afterthe institutional and accounting standards differences between the two markets were eliminated. Second, we examine the impact of the implementation of fair value accounting under IFRS in an emerging market on the pricing difference of cross-listed shares and reveal that it can induce an unintended negative consequence on the pricing difference of cross-listed shares. Third, this study contributes to the literature on short sales by providing its mitigating role in pricing differences across two different markets. Finally, this study makes improvements in research design, which utilizes a unique measure of earnings quality that is directly related to the implementation of IFRS and a simultaneous equations approach that minimizes endogeneity concern.

Mainland China traditionally maintained the one-share-one-vote (OSOV) principle. Since 2019, however, Chinese authorities have introduced rules supporting the dual-class equity structure (DCES) for “innovative enterprises.” Due to concerns about investor-protection issues, China’s DCES currently operates as a “stringent permit system,” and as of the end of June 2023, only eight corporations have achieved listings with DCES adopted. This article provides a broad and profound policy analysis of the Chinese DCES system, including empirical analyses on the eight existing DCES cases. Also, this article explores the legal and economic aspects of investor-protection issues with respect to the China’s DCES. Regarding DCES rules in the context of investor protection, this article examines “three sets of investor safeguard measures”: (1) “three numerically speciffed rules” (this article calls the three rules the “10% equity rule,” the “10-time voting-right rule,” and the “2/3 voting-right rule”); (2) “sunset provisions” (such as event-driven sunset and time-based sunset); and (3) “rules converting special-voting shares (shares with higher voting rights) into shares with one vote” (such as conversion in mergers and a conversion in an amendment of the charter). Due to the concerns about the prevailing practice of tunneling in China, this article argues in favor of the “DCES with enhanced investor protection.” To foment founders’ entrepreneurship and allow more corporations with the DCES, however, this article recommends that the Chinese authorities gradually relax the implementation of the current DCES system of de facto stringent permit system. The future relaxation of the stringent permit system will also be beneffcial for China because, as a result of the escalated tension with the U.S., China has already lost a substantial portion of its reliable DCES-IPO markets in the U.S. Also, DCES-IPO markets in Hong Kong is still inactive. Thus, the establishment of viable DCES-IPO markets will soon be necessary in Mainland China.

This paper investigates the effect on A–H premiums of the China Stock Connect, which allows the Mainland to invest in H-shares in Hong Kong (Southbound) and overseas to invest in A-shares in the Mainland (Northbound). It removes barriers to investor trading all crosslisted A- and H-shares but leads to them an enlarged premium. We develop the differential demand hypothesis of Stulz and Wasserfallen (1995) in China and identify the elasticities of Stock Connect relying on the demand asset pricing of Koijen and Yogo (2019). We ffnd that the average elasticity of Northbound (A-shares) is 0.18, and that of Southbound (H-shares) is 0.66, implying that A-H shares have different levels of substitute effect for investors on each side of Stock Connect, leading to the long-term premium. On a univariate basis, they explain 20% of the variation of the A-H premium and remain highly signiffcant when controlling other variables. We also estimate the cross-listed and time-varying elasticities of Stock Connect. They illustrate the strong positive spillover effect of A-H shares and check the robustness of our results.

The U.S. stock market has long been the most popular venue for both foreign companies and global investors. The recent cross-border regulation tensions between the U.S. and China, however, have exposed many U.S.-listed China Concepts Stocks (CCS) to substantial de-listing risks, forcing them to pursue dual listings on the Hong Kong Stock Exchange (HKEX). In this paper, we quantify the economic value of dual-listing, using the SEC’s adoption of the ffnal amendments implementing mandates of the Holding Foreign Companies Accountable Act (HFCAA) on December 2, 2021 as a natural experiment. We estimate that CCS with pre-shock dual-listing status on average have 14.88% higher returns, or USD 8 billion in market capitalization, than their peers listed only on the U.S. exchanges during a three-month period after the shock. Our ffndings survive a set of robustness checks, including parallel trends test, alternative treatment and control groups based on the qualiffed but not yet dual-listed CCS, and various sub-sample and placebo analyses. In addition to stock returns, dual-listed CCS are also less adversely affected in trading volume, volatility, and liquidity. Our ffndings highlight the large economic impact of the escalating political U.S.-China tensions on the global ffnancial markets.

China’s housing purchase restriction (HPR) policy imposes administrative restrictions on households’ home purchase eligibility to curb speculative demand. We quantify households’ willingness to pay (WTP) to re-acquire such eligibility. The empirical results based on the staggered DID specification suggest that when local governments implement the HPR policy, the transaction prices of judicial housing auctions legally exempted from HPR increase by 18.91%. This HPR-exempted qualification premium can be converted to an estimate of 22.48% of the transaction price as buyers’ WTP for home purchase eligibility. The heterogeneity analysis also suggests that the WTP significantly increases when speculative incentives are stronger in the housing market. If policymakers in mainland China consider replacing the HPR policy with an additional buyer transaction tax like that in Singapore and Hong Kong, China, the WTP estimates can serve as the benchmark in setting the tax rate.

Stock market prediction provides the decision-making ability to the different stockholders for their investments. Recently, stock technical indicators (STI) emerged as a vital analysis tool for predicting high-dimensional stock data in various studies. However, the prediction performance and error rate still face limitations due to the lack of correlational analysis between STI and stock movement. This paper proposes a correlational strategy to overcome these challenges by analyzing the correlation of STI with stock movement using neural networks with the feature vector. This strategy adopts the Pearson coefficient to analyze STI and close index of stock data from 8 Chinese companies in the Hong Kong stock market. The results reveal the price prediction of BiLSTM outperformed the GRU and LSTM in various datasets and prior studies.