Monetary policy implications of housing shift-contagion across regional markets

This paper extends the shift-contagion concept to housing price returns in order to examine co-movements between pairs of regional housing markets in the US. It associates nonlinearities of housing prices with the monetary policy criteria at disaggregate levels. The framework with Markov-switching volatility in Gravelle et al. (Journal of International Economics 68:409–423, 2006) is utilized to investigate housing contagion phenomena which are defined as the switches in the structural transmission of common shocks across regional housing markets. The empirical results suggest that interactions between regional and nationwide housing markets switch across low-volatility and high-volatility regimes of common shocks for the Northeast and the West whose housing price returns are nonlinear. In addition, there is the significantly time-varying interdependence between the West and each of the other three regional housing markets. The estimated indicator of the monetary policy effectiveness implies that monetary policies can be effective in the Northeast and the West because they are more closely linked with other regional housing markets in volatile phases which are subject to housing crises. Noticeably, the broken interrelationships between regional housing markets and real economies in the 2001 recession imply high vulnerability to housing bubbles for regional markets, while short-term monetary policies can be effective in stabilizing the housing market turmoil around 2007.     

Wealth effect and investor sentiment

This paper investigated the relationship between the U.S. stock and housing markets as well as their influence on the wealth effect of consumption and found that the stock market sentiment index can explain changes in the wealth effect. The empirical results indicate that these two markets exert a wealth effect on consumption. The estimation results of the Markov-switching model indicate two states: a state in which the stock market influences its coexistence with the housing market and a state in which the housing and stock markets are unrelated. Public optimism regarding stock market investments affects the probability of transitioning between these states.     

Asymmetric dependence structures for regional stock markets: An unconditional quantile regression approach

Owing to the asymmetry of stock markets, this study investigates the dependence structures for six regional stock markets according to different market conditions by applying the unconditional quantile regression (UQR) approach. This approach can address the traditional conditional quantile regression (CQR) approach’s limitation that its distributions are defined conditional on specific covariates. Specifically, we not only examine the detailed linkages among these six regional stock markets, but also explore the effect of global economic factors on them, given the strengthening of both international investment and the globalization of financial markets. The results show these dependence structures are often an asymmetric U-shaped or inverted U-shaped structure, which indicates that the impacts of both other geographically and economically close stock markets and economic factors are more pronounced during bear and bull markets than during normal markets, especially so in bear markets. Moreover, the UQR approach provides stronger extreme-value relationships and more significant asymmetric effects than the traditional CQR approach.     

Risk dependence and cointegration between pharmaceutical stock markets: The case of China and the USA

This paper analyses risk-integration and the degree of dependence between the Values-at-Risk (VaRs) estimates for the two major pharmaceutical stock markets in the world: USA and China. To do this, we study the dependence and fractional cointegration properties among risks. Using daily returns for an eleven-year period, we estimated the VaRs obtained for pharmaceutical market portfolios in China (Shanghai) and the USA (NYSE) using the market model and considering both long and short trading positions. We conclude that the Shanghai pharmaceutical market is riskier than NYSE, although is predictable and losses in both markets exhibit tail dependence between VaR estimates. Particularly, there is lower tail VaR dependence for long position and upper tail dependence for short positions, both being small and fairly constant. On the other hand, we have not found fractional cointegration between risks, suggesting that China’s pharmaceutical sector is not integrated into the global pharmaceutical market.     

Dependent relationships between Chinese commodity markets and the international financial market: Evidence from quantile time-frequency analysis

In this article, the quantile time–frequency method is utilized to study the dependence of Chinese commodities on the international financial market. The impacts of risk management and diversification benefits of different portfolios are examined by calculating the reduction in downside risk. Moreover, we estimate and compare Sharpe Ratios (SRs) and Generalized Sharpe Ratios (GSRs) based on the frequencies of the investigated portfolios. Our empirical results reveal a strong asymmetric response from Chinese commodity markets. Specifically, we find that gold is a safe-haven asset, and due to negative correlations found at lower quantiles in medium and long term, an increase in the USD index damages bull commodity markets but boosts bear conditions under long-term investments, and negative (positive) tail correlations with interest rates (IRs) in bull (bear) markets are observed. It is proven that WTI can decrease short-run risks while USD and GOLD are more efficient in the diversification of downside risk. Adding international commodities may not improve the returns of Chinese commodities at given risk levels in the short and medium term through SRs and GSRs. In brief, investors should consider these dependence structures and modes of risk management in terms of time and frequency.     

An analysis of dependence between Central and Eastern European stock markets

We examine the dependence structure between four Central and Eastern European (CEE) stock markets (Czech Republic, Hungary, Poland and Romania) using static and dynamic copula functions with different forms of tail dependence. We find evidence of positive dependence between all CEE stock markets, although this dependence is stronger between the Hungarian, Czech and Polish markets than between these markets and the Romanian market. We also find evidence of symmetric tail dependence, although not for the Hungarian and Czech markets. The dependence is time-varying and intensified after the onset of the recent global financial crisis. These results confirm that CEE stock markets are gradually coupling, a fact that has risk management implications for policymakers and investors.     

Downside/upside price spillovers between precious metals: A vine copula approach

We studied downside and upside price spillovers between four precious metals (gold, silver, platinum and palladium), characterizing the multivariate dependence structure using a vine copula model and computing downside and upside value-at-risk and conditional value-at-risk. We found that the dependence structure differed across precious metals, all of which displayed different average and tail dependence features. Gold and silver prices were highly dependent except at the upper tail, whereas silver prices were integrated with those for platinum and palladium except at the upper tail. The gold market was very little integrated with the platinum and palladium markets. We document asymmetric downside and upside price spillover effects that differed in magnitude across precious metals; silver, in particular, had a greater downside and upside price impact on gold. Our results, indicating that precious metals do not behave as a single asset class, have implications for risk management, trading and hedging strategies for portfolios that include precious metals.     

Risk and return in the Tehran stock exchange

This paper analyzes market index returns in the Tehran stock exchange (TSE) within the context of three variants of the Capital Asset Pricing Model: the static international; the constant-parameter intertemporal; and a Markov-switching intertemporal CAPM, which allows for time-varying degree of integration with regional and international equity markets. We find that TSE returns are CAPM-efficient at monthly frequency with respect to several international market indices. Moreover, we find evidence in support of international integration of the TSE with respect to international markets. In addition, we conduct an extensive investigation for the direction of causality between TSE returns, international market index returns, and those in neighboring countries.     

Do house prices reflect fundamentals? Aggregate and panel data evidence

We investigate whether recently high and consequently rapidly decreasing U.S. house prices have been justified by fundamental factors such as personal income, population, house rent, stock market wealth, building costs, and mortgage rate. We first conduct the standard unit root and cointegration tests with aggregate data. Nationwide analysis potentially suffers from problems of the low power of stationarity tests and the ignorance of dependence among regional house markets. Therefore, we also employ panel data stationarity tests which are robust to cross-sectional dependence. Contrary to previous panel studies of the U.S. housing market, we consider several, not just one, fundamental factors. Our results confirm that panel data unit root tests have greater power as compared with univariate tests. However, the overall conclusions are the same for both methodologies. The house price does not align with the fundamentals in sub-samples prior to 1996 and from 1997 to 2006. It appears that the real estate prices take long swings from their fundamental value and it can take decades before they revert to it. The most recent correction (a collapsed bubble) occurred around 2006.     

Contagion effects and risk transmission channels in the housing,stock, interest rate and currency markets: An Empirical Study in China and the U.S.

This paper aims to investigate the crisis linkage and transmission channels within the housing, stock, interest rate and the currency markets in the U.S. and China in the past decade since the 2008 Subprime Mortgage Crisis. Two hybrid models, namely the SWARCH-EVT-Copula and the Bivariate SWARCH-EVT models, are proposed and applied in order to take into account (A) the high/low volatility regimes, (B) the interdependence structure inherited from the joint tail behaviours, as well as, (C) the risk spillover dynamics among financial sectors during market turmoils. We empirically show that the housing and stock markets share the strongest linkage and play central roles in the spreading of shocks. With a highly integrated system, the American financial sectors are under greater exposure to risk contagion and systemic risk during crises than the Chinese markets. Nevertheless, the exchange rate risk of Renminbi remains at an intensive level since its “crawl-like arrangement” and leads to increasing co-movements in the stock and interest rate markets since 2014.     

Diversificationas a Strategic Preemptive Weapon

This article examines the role that multimarket operations play in a firm's ability to preempt entry into new markets when presence in a market does not commit the firm to remain there. Success in one market affects a firm's incentives and, in turn, strategic power, to fight a rival fur survival in a related market. This is modeled as a way of attrition, and the risk-dominant equilibrium is derived. The model supports brand proliferation as a credible preemptive strategy for an established firm and also has implications regarding the strategic role of economies of scope and "deep pockets."     

Volatility linkages in the spot and futures market in Australia: a copula approach

To better characterize the dependence structure of the joint returns distribution, we propose to blend copula functions with Asymmetric GARCH (AGARCH) models, which are allowed for generalized error distribution. We model the copula’s marginals by the AGARCH processes that can differentiate between the impacts of positive and negative shocks on the returns volatility while taking the large kurtosis of the returns into account. An application of the procedure is elaborated on the All Ordinaries Index and its corresponding Share Price Index on future contracts in Australia. The findings reveal that the two spot and future markets show a strong right tail dependence but no left tail dependence. This provides a very useful knowledge for the risk management and hedging in futures markets.     

Negotiating Social Mix in Toronto's First Public Housing Redevelopment: Power,Space and Social Control in Don Mount Court

This article examines the experience of social interaction in Toronto's Don Mount Court community, the first socially mixed public‐housing redevelopment site in Canada. Similar to the American HOPE VI program, redevelopment involved the demolition and mixed‐income reconstruction of the community to include both public housing and new market condominiums with a neo‐traditional redesign. Based on participant observation, this article describes four struggles that emerged over the course of a series of mixed‐income community governance meetings intended to promote social inclusion. These struggles related to (1) unequal power relations in shaping local priorities; (2) the power to brand the community and define its aesthetic characteristics; (3) the power to define and use public space; and (4) power over modes of surveillance and exclusion. The findings challenge the myth that the ‘benevolent’ middle class will use their political influence and social capital to the benefit of their low‐income neighbors in mixed neighbourhoods. Instead, the research found that public‐housing tenants were often on the receiving end of antagonism. It is argued that policymakers intent on ameliorating problems related to residence in disadvantaged communities should focus on funding for social programs and transformative change, rather than on public‐housing demolition and state‐driven gentrification via mixed‐income redevelopment.     

Dependence structures between Chinese stock markets and the international financial market: Evidence from a wavelet-based quantile regression approach

In this study, we investigate the dependence structures between six Chinese stock markets and the international financial market including possible safe haven assets and global economic factors under different market conditions and investment horizons. The research is conducted by combining a quantile regression approach with a wavelet decomposition analysis. Although we find little or insignificant dependence under short investment horizons, we detect the strong asymmetric dependence of oil prices and the US dollar index on the six Chinese stock markets in the medium and long terms. Moreover, not only is crude oil not a safe haven, it may damage Chinese stock markets as it increases over the long term, even in bull markets. Meanwhile, appreciation of the US dollar (depreciation of RMB) damages (boosts) Chinese stock markets during bull (bear) market conditions under long investment horizons. Moreover, we find that VIX (volatility index)-related derivatives may serve as good risk management tools under any market condition, while gold is a safe haven asset only during crisis periods.     

List price and sales prices of residential properties during booms and busts

This paper investigates the relationship between the list and sale price of residential properties over the housing cycle. In down or normal markets the list price generally exceeds the sales price; however, when the housing market is strong, homes sell for more than their list price. This observation is not consistent with the assumptions made in the standard model of home sellers’ search behavior. We consider alternative models. In one, sellers set list prices based on their expectations of future changes in sales prices and the arrival rate of buyers; however, demand shocks occur. This model partially explains our data from the Belfast, U.K. housing market, but it fails to predict the list to sales price ratio during a sustained housing boom. We next describe a model where sellers’ endogenously select their search mechanism depending on the strength of the housing market. We find support for the conjecture that sellers switch to an auction-like model during housing booms. There also is evidence that during a downturn in the market, sellers’ list prices are sticky.     

沪深股市在牛市和熊市阶段的波动非对称效应实证分析

本文分别采用EGARCH-M、TGARCH-M模型对沪深股市在牛市和熊市阶段的非对称波动效应进行了分析,这两个模型得出了相同的结论,在牛市阶段利好消息引起股市更大的波动,在熊市阶段利空消息引起股市更大的波动,而且这两个模型同时也说明了我国股市风险和收益的正相关关系,并从我国股票市场交易者构成和交易机制两方面说明了波动非对称的原因。     

The transition of the global financial markets' connectedness during the COVID-19 pandemic

This study contributes to the literature on financial research under the presence of the COVID-19 pandemic. Fresh evidence emerges from using two novel approaches, namely network analysis and wavelet coherence, to examine the connectedness and comovement of financial markets consisting of stock, commodity, gold, real estate investment trust, US exchange, oil, and Cryptocurrency before and during the COVID-19 onset. Moreover, unlike the previous studies, we seek to fill a gap in the literature regarding the ex-post detection of COVID-19 crises and propose the Markov-switching autoregressive model to detect structural breaks in financial market returns. The first result shows that most financial markets entered the downtrend after January 30, 2020, coinciding with the date the World Health Organization (WHO) declared the COVID-19 pandemic as a Public Health Emergency of International Concern. Thus, it is reasonable to use this date as the break date due to COVID-19. The empirical result from network analysis indicates a similar connectedness, or the network structure, in other words, among global financial markets in both the pre-and during COVID-19 pandemic periods. Moreover, we find evidence of market differences as the MSCI stock market plays a central role while Cryptocurrency presents a weak role in the global financial markets. The findings from the wavelet coherence analysis are quite mixed and illustrate that the comovement of the financial markets varies over time across different frequencies. We also find the main and most significant period of coherence and comovement among financial markets to be between December 2019 and August 2020 at the low-frequency scale (>32 days) (middle and long terms). Among all market pairs, the oil and commodity market pair has the strongest comovement in both pre-and during the COVID-19 pandemic phases at all investment horizons.     

Firm size,economic risks,and the cross-section of international stock returns

Recent empirical evidence from developed markets indicates a negative relation between value premium and firm size. We find that the value premium in small stocks is consistently priced in the cross-section of international returns, whereas the value premium in big stocks is not. Based on US data, we show that the small-stock value premium is associated with business cycle news and reflects changes in macroeconomic, especially credit market related risks. Our results hold true for regional and global equity markets and remain valid after controlling for firm characteristics and prominent profitability and investment factors.     

A multivariate unobserved component analysis of US housing market

This study explores price dynamics and price relationships in the US housing market with a focus on four regions: Northeast, Midwest, South, and West. It applies a multivariate state-space model to identify the common trends and common cycles in US regional markets. The study finds that the principal source of secular price variability in the Northeast and West markets is due to two common stochastic trends, while a large share of transitional price variability in the Northeast, West and Midwest originates from three common stochastic cycles. The study estimates the relationships between the common unobserved components and economic variables and finds that unemployment, federal funds rate, corporate default risk, economic expansion, unanticipated inflation in the construction market are significant underlying economic phenomena that impact the evolution of the common movements in both the short run and the long run housing dynamics. Authorship is equally shared between the authors.     

中国城市住宅市场的结构差异性分析

市场价商品房、经济适用住房和廉租房构成了目前中国城市住宅市场的供应体系.依据中国30个主要城市的房地产开发统计数据,选择吸纳率作为评价住宅市场供需均衡状态的指标,利用固定影响变截距模型,重点研究了商品房和经济适用住房供给结构的城市差异性.研究发现,在城市住宅市场中,经济适用住房市场和商品房市场具有很强的相关性.作为具有政府资助性质的经济适用住房建设,存在典型的地域性特征,其政策的设定和实施会对整个住宅市场产生影响,地方政府应在利用比较全面的住宅市场指标体系进行综合分析基础上,制定适合本地的经济适用住房政策.