中国金融周期与横向关联:时空双维度相结合视角

宏观审慎政策关注各金融子市场在时间维度上的金融周期和空间维度上的横向关联。本文结合时间维度与空间维度视角,使用股票市场、货币市场、房地产市场以及信贷市场的数据,测算2001—2019年中国金融周期和横向关联的波动特征、作用关系与频域叠加机理。研究结果表明:时间维度金融周期与空间维度横向关联的波动趋势具有一致性。我国金融周期长度约为10.33年,横向关联波动周期的长度约为10.58年。从作用关系上看,首先,我国房地产周期达到波峰后,会对股票市场和信贷市场产生较强的溢出效应。随后,股市周期达到波峰后,会向房地产市场和信贷市场产生较强的溢出效应。最后,我国信贷市场接受股票市场和房地产市场溢出后,信贷周期会逐渐达到波峰。从频域叠加机理的角度看,我国金融子市场间横向关联的波动主要由中低频波段驱动,中低频波段横向关联的持续期在2个月以上。     

Real Estate Markets and Macroprudential Policy in Europe

Boom‐bust cycles in real estate markets have been major factors in systemic financial crises and therefore need to be at the forefront of macroprudential policy. The geographically differentiated nature of real estate market fluctuations implies that these policies need to be granular across regions and countries. Before the financial crisis that started in 2007 property markets were overvalued in a range of European countries, but much like in other constituencies active policies addressing this were an exception. An increasing number of studies suggest that borrower‐based regulatory policies, such as reductions in loan‐to‐value or debt‐to‐income limits, can be effective in leaning against real estate booms. But many of the new macroprudential policy authorities in Europe do not have clear powers to determine them. Moreover, the cross‐border spillovers they may give rise to suggest the establishment of a well‐defined macroprudential coordination mechanism for the single European market.     

Volatility spillovers and the effect of news announcements

We examine the effect of US and European news announcements on the spillover of volatility across US and European stock markets. Using synchronously observed international implied volatility indices at a daily frequency, we find significant spillovers of implied volatility between US and European markets as well as within European markets. We observe a stark contrast in the effect of scheduled versus unscheduled news releases. Scheduled (unscheduled) news releases resolve (create) information uncertainty, leading to a decrease (increase) in implied volatility. Nevertheless, news announcements do not fully explain the volatility spillovers, although they do affect the magnitude of volatility spillovers. Our results are robust to extreme market events such as the recent financial crisis and provide evidence of volatility contagion across markets.     

How strong are the linkages between real estate and other sectors in China?

International experience points to the critical role of stable property markets in maintaining financial stability. This paper investigates the real and financial linkages between real estate sector and other sectors. The real linkage based on input–output analysis shows that the linkages have strengthened. The financial linkages in terms of credit risk spillovers across sectors are studied by using DAG method and SVAR. We find that that credit risk in the real estate sector has large-scale spillover effects onto other sectors. Consequently, shocks to the property market could have much larger impact on the Chinese economy than suggested by headline figures.     

Extreme risk spillover network: application to financial institutions

Using the CAViaR tool to estimate the value-at-risk (VaR) and the Granger causality risk test to quantify extreme risk spillovers, we propose an extreme risk spillover network for analysing the interconnectedness across financial institutions. We construct extreme risk spillover networks at 1% and 5% risk levels (which we denote 1% and 5% VaR networks) based on the daily returns of 84 publicly listed financial institutions from four sectors—banks, diversified financials, insurance and real estate—during the period 2006–2015. We find that extreme risk spillover networks have a time-lag effect. Both the static and dynamic networks show that on average the real estate and bank sectors are net senders of extreme risk spillovers and the insurance and diversified financials sectors are net recipients, which coheres with the evidence from the recent global financial crisis. The networks during the 2008–2009 financial crisis and the European sovereign debt crisis exhibited distinctive topological features that differed from those in tranquil periods. Our approach supplies new information on the interconnectedness across financial agents that will prove valuable not only to investors and hedge fund managers, but also to regulators and policy-makers.     

中国房地产企业间系统性风险溢出效应分析——基于尾部风险网络模型

本文以2007—2021年沪深A股上市房企为样本,首先基于SIM单指数分位数回归技术提出测量系统性风险的新指标SIM-CoVaR,并结合前沿的TENET网络模型,构造跨房地产企业风险动态传染的尾部风险网络,然后采用块模型探究房地产市场系统性风险溢出的聚类性、触发机制及传播路径,最后考察网络整体结构和宏观经济变量对房地产市场系统性风险溢出的影响。研究表明:(1)我国房地产企业间存在明显的系统性风险联动性和溢出效应,在市场动荡时期房地产部门是金融风险溢出的放大器;(2)评估系统重要性节点企业时,除考虑企业规模等内部属性,还应考虑房企间关联结构,利用系统性风险指数可有效捕捉网络中系统重要性节点;(3)跨房企的系统性风险溢出具有显著的聚类特征,尾部风险网络可被划分为4个不同的功能模块,各模块的成员及其角色呈现明显的时变特性,监管部门可据此从供给端“因企施策”;(4)网络聚集性、网络效率和网络匹配性的降低能显著降低房地产市场的系统性风险溢出效应。本文从企业微观层面探讨房地产市场风险的形成机制,为促进房地产业健康发展和防范化解宏观层面的系统性金融风险提供参考。     

Dynamic spillovers across oil,gold and stock markets in the presence of major public health emergencies

Extreme events have a systemic impact on global financial markets, leading to significant cross-market spillovers in the oil, gold, and stock markets and raising widespread concerns about market linkages and risk contagion. In this paper, with a focus on both return and volatility, a frontier spillover network analysis is used to examine the strength and scale characteristics of spillovers in the oil, gold and stock markets under major public health emergency shocks. In addition, the paper adopts a marginal spillover and network analysis to evaluate linkage relationships, risk sources and transmission paths in the oil, gold, and stock markets during such events. The results show that the return and volatility spillover effects generated across the oil, gold, and stock markets are significant, with return spillovers being more stable and volatility spillovers being highly sensitive to emergencies. Meanwhile, the COVID-19 pandemic has displayed the strongest return and volatility spillovers. The high intensity of the shocks during the COVID-19 period has changed the usual characteristics of the market, with the gold market becoming the risk receiver and the oil market becoming risk sources.     

State transformation of information spillover in asset markets and effective dynamic hedging strategies

This paper aims to develop a strategy to effectively and dynamically hedge risk by considering regime transitions of spillover effects between assets. We take six assets (stocks, bonds, real estate, currency exchange, crude oil, and gold) that are commonly used to construct investment portfolios as examples and analyze asset price data between September 2002 and January 2022. In doing so, we aim to examine the information spillover of different asset prices in both bear and bull market environments to determine whether state transformation affects dynamic hedging effectiveness. Using Markov-Switching Factor-Augmented Vector Autoregression (MS-FAVAR), we construct a regimen-switching model using variables from finance and economic conditions as endogenous variables to define the state transformations of the information spillover. Empirical results reveal that the MS-FAVAR model highlights changes in information spillover during a financial crisis/economic recession. Using dynamic-weighted hedging portfolios constructed with different indicators, we find that hedging effectiveness and volatility vary depending on the state of information spillover between different asset markets and that bear markets significantly impacted hedging effectiveness. Results also show that the panic sentiment (the fear index) explains the probability of a bear market. It is suggested that the state transformation of information spillovers should be monitored periodically, and hedging portfolios should be dynamically adjusted (bear or bull market) with shifting fear sentiment.     

波动溢出网络视角的金融风险传染研究

当前各类经济风险交叉关联,金融系统的风险溢出效应备受关注,为刻画我国金融系统性风险传染的路径特征,本文从波动溢出网络的视角分析金融系统内部的风险传染机制。首先使用广义动态因子模型对收益波动的共同波动率成分和特质性波动率成分进行区分。然后,根据货币市场、资本市场、大宗商品交易市场、外汇市场、房地产市场和黄金市场之间的特质性波动溢出效应,利用基于TVP-VAR模型的方差分解溢出指数分析金融系统波动溢出的动态联动性和风险传递机制。在分析方向性波动溢出效应的基础上,采用方差分解网络方法构建起信息溢出复杂网络,从网络视角分析金融系统内部的风险传染特征。实证研究发现,房地产市场和外汇市场的净溢出效应绝对值相较于其他市场更大,其受其他市场风险冲击的影响强于对外风险溢出效应,而股票市场的单向对外风险溢出效应强度最大。在波动溢出的基础上,进一步考虑股市波动率指数与其他市场波动率指数进行投资组合的资产配置权重,计算了波动率指数投资组合的最优组合权重和对冲策略。研究结论有助于更好地理解我国金融系统的风险传染机制,对监管机构加强宏观审慎监管、投资者规避投资风险具有重要意义。     

Spillovers among sovereign CDS,stock and commodity markets: A correlation network perspective

In the wake of the globalization of financial markets, studying spillovers among different asset markets, especially spillovers that include sovereign CDS markets, is of vital importance. This paper attempts to build a spillover network to investigate the complex interactions within the system of sovereign CDS, stock and commodity markets by adopting the spillover index based on forecast error variance (FEV) decomposition. The results reveal that emerging countries have larger average spillovers than developed countries with regard to sovereign CDS-to-stock returns spillovers, while the developed countries contribute more average spillovers than the emerging countries in the opposite direction. Moreover, the sovereign CDS market and the commodity market still demonstrate a relatively important role during certain periods although stock markets always occupy the dominant position during every phase. Our findings provide new insights into spillovers among the major global asset markets using a network perspective, which is valuable for regulation of financial markets, asset allocation and portfolio risk management.     

The behaviour of asset return and volatility spillovers in Turkey: A tale of two crises

This paper examines return and volatility spillovers between the Turkish stock market with international stock, exchange rate and commodity markets. Our aim is not only to examine spillover behaviour with a large emerging market but also to examine cross—asset spillovers and how they vary across two periods of financial market crisis; the dotcom crash and the liquidity-induced financial crisis. This is to be compared with existing work that typically focuses on industrialised countries or single asset markets only. Using the spillover index methodology we uncover an interesting distinction between these two periods of markets stress. Over the dotcom period spillovers are largely between the same asset class, notably two exchange rate series and two international stock markets series. However, in the period including the financial crisis, spillovers both increase and cross asset types and suggest a much greater degree of market interdependence. Understanding this changing nature in spillovers is key for investors, regulators and academics involved in theoretical model development.     

The contribution of (shadow) banks and real estate to systemic risk in China

We empirically evaluate how accounting and financial variables affect the level of systemic risk in traditional and shadow banks, and in real estate finance services in China over the period 2006–2019. We also conduct some stability analysis by evaluating the impact of crisis sub-periods. We find that systemic risk increases in the Size of large financial institutions, particularly shadow entities, while it is insensitive to the Size of real estate finance services. Real estate finance services are instead particularly sensitive to Maturity Mismatch and Leverage. Finally, systemic risk differs across state and non state owned banks.     

Explaining Monetary Spillovers: The Matrix Reloaded

This paper relies on a high-frequency identification approach to provide new insights into monetary policy spillovers by major central banks. Our long and broad sample (1999–2019, from four major economies to 47 advanced and emerging market economies) allows us to accurately identify the properties of spillovers and to shed light on different transmission channels. We find that spillovers by the Fed to foreign interest rates are economically large, but more surprisingly, document an intensification of spillovers by the European Central Bank over time. Spillovers are more significant to bond yields in advanced economies than they are to those in emerging markets. Differentiating across key spillover channels, we find strongest support for a financial links channel, but weaker evidence for the macroeconomic links channel and foreign exchange regime channel.     

Spillover effects of banking systemic risk on firms in China: A financial cycle analysis

This paper investigates the spillover effects of banking sector risk on firms in China and explores the risk transmission channels from the perspective of financial cycle. We use the banking risk-taking and systemic risk as the proxies of financial booms and busts. Our study yields four main findings. First, the banking risk-taking reduces firm risk in financial booms. Higher financing costs and constraints, larger firm size and financing scale, and state ownership inhibit the spillover effects. Second, the banking systemic risk increases firm risk during financial busts. Higher financing costs and constraints, larger firm size and financing scale, and state ownership facilitate the spillover effects. Third, the magnitudes of banking risk spillovers vary across industries, and this effect is more pronounced in the manufacturing industry. Fourth, bank risk-taking affects firm risk differently through various channels in different leading periods. When leading 1 to 3quarters, banking risk-taking reduces firm risk, and channel variables inhibit the spillover effects. However, when leading 4 to 8 quarters, the rising bank risk-taking eventually increases firm risk, and channel variables amplify its spillover effects. Our study offers important policy implications for risk assessment and mitigation in the Chinese loan market.     

Dynamic and frequency-domain spillover among economic policy uncertainty,stock and housing markets in China

This study examines the dynamic characteristics of information spillover effect among economic policy uncertainty (EPU), stock and housing markets in China's first-, second- and third-tier cities. To measure return and volatility spillovers over time and across frequencies simultaneously, the researchers utilize the time-frequency connectedness network approach developed by Baruník and Křehlík (2018). The empirical findings suggest that return and volatility spillovers are stronger in the longer period (more than 3 months) than in the shorter period (1 to 3 months). In the short term, second and third-tier cities are net transmitters of information spillovers, while in the long term, first-tier cities, EPU, and stock markets are the net information transmitters. Furthermore, the long-term information from the EPU and stock market affect most of the real estate markets for different tier cities. Additionally, market segmentation reveals the city-specific characteristics of China's real estate market, especially the close connections between first-tier cities and the stock market. These results have important empirical implications for real estate policymakers and investors when they make related short or long-term decisions.     

极端风险事件下股票市场与公司债券市场的尾部风险溢出研究——基于MVMQ-CAViaR模型

构建MVMQ-CAViaR模型,结合金融市场内部极端风险事件和外部极端风险事件,考量股票市场与公司债券市场的尾部风险溢出问题。结果表明,在金融市场内部极端风险事件下,股灾期间仅存在股票市场对公司债券市场单向的尾部风险溢出。公司债券违约潮期间,股票市场与公司债券市场之间存在双向不对称的尾部风险溢出,且公司债券市场对股票市...     

Risk spillovers from China's and the US stock markets during high-volatility periods: Evidence from East Asianstock markets

This paper studies cross-country risk spillovers through C-vine copula quantile regression. We find Both China's and the US markets can result in large risk spillovers to East Asian markets. Furthermore, their significant conditional spillovers indicate they can emit risk through an intermediary market. However, their distinctive dependency structures with East Asian markets reflect their differences in spillovers to the markets in magnitude. The risk spillovers from US are stronger than China in magnitude. Moreover, the risk spillover from China's stock market during its high-volatility period is weaker than the whole period, which is contrary to the US market. It may imply Chinese financial influences gradually increase with Chinese financial liberalization and regional integration. Our results have implications for macroprudential regulators adopt the effective supervision and regulation to deal with the cross-border risk spillovers, and for international investors in risk hedging, derivative valuation and investment.     

Does linkage fuel the fire? The transmission of financial stress across the markets

This paper develops an indicator of financial stress transmission, called Financial Stress Spillover Index (FSSI), to monitor the condition of financial system and to identify periods of excessive spillover that may lead to financial instability. Specifically, using the “spillover index” approach of Diebold and Yilmaz (2012), we modify and extend the financial stress indices proposed by Oet et al. (2011) to track both total and directional stress spillovers across the U.S. equity, debt, banking, and foreign exchange markets. Unlike other previous studies, the important linkages among these four major financial sectors in an interconnected world are directly taken into account by considering the average and time-varying connectedness of each individual market. The evidence suggests that there are important stress episodes and fluctuations across markets; the total cross-market stress spillovers were rather limited until the onsets of financial crises. As the crises intensified, so too did the financial stress spillovers; with significant stress carrying over from debt and equity markets to the others. In addition, our results indicate that FSSI has a significant predictive power for the economic activity and provides useful information for dating financial crisis.     

The extreme risk connectedness of the new financial system: European evidence

The paper empirically analyses the tail risk connectedness between FinTech and the banking sector in the European context over 2015–2022. For this purpose, we use the Tail-Event driven NETworks (TENET) risk model, i.e., we can capture the behaviour of extreme (negative and positive) risk spillover within the financial system. The results highlight how most tail risk spillovers are from banks to FinTech firms. Also, the findings suggest that the spillovers of cross-sector tail risk are more significant in downside (bearish) risk conditions than in upside (bullish) one. We find evidence of an asymmetric effect of extreme risk spillover to the real economy. Finally, we evaluate the monetary policy’s impact on extreme risk. Our findings highlight the importance of closer monitoring risk spillover between FinTech institutions and the European banking system to maintain financial stability.     

Research on China's financial systemic risk contagion under jump and heavy-tailed risk

To accurately measure the dynamic characteristics of systemic risk contagion under the impact of extreme financial events, we construct a research framework that analyzes the contagion dynamics of systemic risk under extreme risk impact from the perspectives of both time and space. Based on the macro-jump CCA method, this paper extracts the heterogeneous volatility sequence of financial industries considering the thick tail of the distribution of financial assets returns. Then, the dynamic variation of systemic risk in the financial sectors is characterized from the time dimension. The volatility spillover network method is used to examine the spillover contagion of systemic risk among financial system sectors from the spatial dimension. Empirical studies have found that when considering the risk contagion level, the capital market service sector plays a risk‑leading role, followed by the currency service sector and the insurance sector. The measurement indicators that consider the jump risk and the tail risk have good early warning effects on extreme financial events. Seen from the spatial direction of risk spillover, the real estate sector exhibits the most obvious risk spillover effect on other sectors and can be regarded as the source of systemic risk, which suggests differentiated regulation.