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    China Real Estate Market Crisis: Can Things Get Worse?

    December 2023

    China Real Estate Market Crisis: Can Things Get Worse?

    Since the implementation of the “three red lines” policy in August 2020, coupled with strict COVID-19 measures, China’s real estate sector has grappled with significant financial hurdles, eroding consumer confidence. These hurdles are evident in the crises faced by major developers, including China Evergrande Group, Country Garden Holdings, and Sino-OceanGroup Holdings. Using Moody’s EDF-X Early Warning System (EWS) and economic scenario-conditioned forecasts, we examine the current and projected state of the Chinese and Hong Kong real estate and construction industry, while identifying potential winners and losers in the tumultuous landscape.

    Challenge

    In August 2023, the People’s Bank of China and the National Administration of Financial Regulation introduced a range of measures to revive the property industry. These measures included reducing the minimum down payments for home buyers and cutting mortgage rates. Despite these efforts, so far, the industry has shown few signs of recovery amid China’s unsteady economic revival and escalating geopolitical tensions.

    In a rapidly changing and uncertain landscape, how should portfolio managers plan for aggregate changes in credit warning signals and identify potential risky firms under different future scenarios? An early warning signal based on a current point-in-time one-year probability of default (PD) can efficiently flag exposures that are at risk when macroeconomic fundamentals are unchanged. However, accounting for changes in monetary and fiscal policies, pandemic-related mobility restrictions, oil prices, or geopolitical relations requires a more comprehensive examination of warning signals that are conditioned on a variety of economic scenarios.

    Insights

    Powered by Moody’s time-tested credit risk models and the most relevant and comprehensive data sources, the EDF-X EWS offers real-time, actionable early warning signals for over 450 million public and private companies, both rated and unrated, across over 200 countries and territories. Integrating Moody’s scenario-conditioned PDs with EDF-X EWS empowers institutions to monitor their portfolios in the existing economic climate, while also unveiling vulnerable entities, sectors, and geographical regions under various prospective economic conditions. For instance, institutions can examine how their exposures may change during a recession, or whether certain entities would outperform their peers should economic growth surpass expectations. Institutions can then take proactive measures with this contingent perspective. Hence, the EDF-X scenario-conditioned EWS is an invaluable tool for navigating a volatile and uncertain landscape such as the Chinese and Hong Kong real estate and construction industry.

    Our analysis suggests the following:

    1. The easing of housing restrictions could favor state-owned developers in high-tier cities, previously subject to stricter regulations.1 The EDF-X EWS identifies three notable developers who may benefit from the government’s economic measures.
    2. Despite significant centralized policy measures, a substantial portion of the industry is still expected to exhibit severe risk even in an optimistic economic scenario. This implies that complete industry-wide containment may not be achieved in the short term.
    3. The risk associated with most risky developers is expected to persist, and there are four large developers whose credit risk remains severe even in an upside scenario.

    Analysis

    In this article, we use the EDF-X scenario-conditioned EWS to look at industry-wide risk distribution changes in advance of emerging uncertainties. We examine the projected shifts in risk warning categories one year ahead of Q3 2023 for 717 publicly traded companies in China and Hong Kong under various hypothetical economic scenarios. To account for cross-sector effects, we consider companies in the real estate, real estate investment trust (REIT), construction, and construction materials sectors.

    The EDF-X EWS synthesizes two measures—PD relative to trigger2 and changes in PD-implied rating—into an actionable signal that identifies companies as “severe,” “high,” “medium,” or “low” credit risks. The EDF-X scenario-conditioned EWS utilizes the same framework. We compute the distance between scenario-conditioned PDs and triggers, and map scenario-conditioned PDs to implied ratings to calculate the 12-month PD-implied rating change. This approach allows us to obtain a comprehensive contingent view of a firm’s risk profile.

    We consider three different hypothetical economic scenarios in Q3 2024: one baseline (BL), one upside (S1), and one mild recession (S2).3 The BL scenario has additional monetary and fiscal stimulus to support recovery in real estate and construction, no COVID-19 mobility restrictions, a sustained Russia-China relationship, and a modest rise in crude oil prices until late 2023. The S1 scenario assumes reduced US-China tensions and faster COVID-19 recovery, coupled with targeted regulatory and fiscal stimulus to restore homebuyer confidence and prevent bankruptcies. In contrast, the S2 scenario is marked by growing concerns about geopolitical tensions between China and Taiwan, rising COVID-19 cases, supply chain disruptions leading to inflationary pressures, and more proactive monetary and fiscal policies enacted to prop up demand.

    To visualize industry-wide risks, we use the EDF-X EWS quadrant. Figure 1 presents the risk distribution as of Q3 2023 as well as the projected risk distribution under the three hypothetical economic scenarios. Each firm within the industry is represented by a circle, with the circle’s size commensurate with the firm’s total book value of assets in USD. A specific subset of firms, each identified by a unique number, is a focal point of our analysis. As of Q3 2023, we find that while 42% of firms are in the low-risk category, 39% of firms exhibit an elevated risk relative to peers (high or severe). This demonstrates that much of the industry remains vulnerable.

    To understand potential shifts in industry-wide risks, we apply the EDF-X EWS quadrant to scenario-conditioned PDs and triggers under selected economic scenarios. Under the BL scenario, the overall risk distribution moves from low risk to medium risk, while 30 fewer firms exhibit elevated risk relative to peers compared to Q3 2023. Under the pessimistic S2 scenario, the overall risk distribution concentrates even more toward medium risk as well as severe risk, with 39 more firms facing severe risk relative to Q3 2023. On the other hand, under the S1 scenario, 54% of the distribution leans towards low risk. Yet, a quarter of the sector is still projected to exhibit severe risk, indicating that even under optimistic conditions, the industry remains fragile.

    Our scenario analysis indicates that several state-owned developers, classified as medium risks in Q3 2023 and operating in top-tier cities, are poised to benefit from government support measures. These developers are also well-positioned to capitalize on potential surges in housing demand. Notable examples include China Overseas Land & Investment Ltd. (transitioning to low risk in S1), China Resources Land Ltd. (moving to low risk in BL and S1), and Poly Developments and Holdings Group Co., Ltd. (shifting to low risk across all three scenarios).

    On the other hand, Hong Kong-based Yuexiu Property Co., Ltd., which is at low risk as of Q3 2023, is expected to transition to a medium-risk profile under all three scenarios. This risk trajectory may be influenced, at least in part, by the performance of its subsidiary, Yuexiu REIT, which saw its risk profile escalate from medium to severe in Q3 2023. This shift followed a market cap decrease of over 30% in the first three quarters of 2023 and a debt-to-equity ratio that exceeded 123% in FY 2022. Yuexiu REIT is projected to maintain an elevated credit risk across all scenarios, including the optimistic S1.

    Meanwhile, most companies currently facing a heightened level of risk are expected to continue to exhibit elevated risk profiles. These include Sino-Ocean Group Holdings Ltd., Country Garden Holdings Co. Ltd., Central China Real Estate Ltd., and Sunac China Holdings Ltd. After experiencing significant losses in FY 2022 and accumulating considerable market leverage, these companies are at severe risk as of Q3 2023 and are projected to maintain this risk status under all three scenarios.

    Given the volatile nature of the current economic landscape, the EDF-X scenario-conditioned EWS serves as a critical tool for monitoring exposures, identifying potential risks, and taking preemptive action.

    Key Takeaways

    • The Chinese and Hong Kong real estate and construction industry’s recovery is being hindered by a confluence of factors. In this volatile and uncertain landscape, the EDF-X EWS provides a comprehensive view of a portfolio’s credit risk under current and prospective economic conditions, allowing institutions to identify potential risks and take preemptive action.
    • Despite expansionary government policies, recovery remains elusive. Fiscal and monetary stimulus is unlikely to translate to a broader resolution of the protracted crisis, considering a substantial portion of the industry is still projected to exhibit severe risk even in an optimistic scenario.
    • The centralized easing of restrictions could favor state-owned companies in high-tier cities. Policy changes may not be too impactful for firms that already exhibit significantly elevated risk, even in an upside scenario.
    Footnotes

    1 The degree of benefit would hinge on firm-specific elements, such as financial resilience as perceived by homebuyers and political considerations.

    2 The trigger threshold is a PD level computed according to a pre-specified peer percentile, adjusting for credit cycle and small sample effects.

    3 The forecasts were created in August 2023. BL, S1, and S2 are economic scenarios produced by Moody’s Economics and Consumer Credit Analytics (ECCA) team. BL, S1, and S2 scenarios are designed so that the probability that the economy will perform worse than in the scenario is 50%, 90%, and 25% respectively.

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