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This chapter examines the increased levels of cross-asset price comovement and its relationship with the recent rounds of “extraordinary intervention” from the US Federal Reserve. The results show that, even after controlling for the preceding financial crisis, asset return volatility, investor risk perceptions, and channels of monetary stimulus, historically unrelated financial asset returns experienced abnormal changes in their conditional correlations. The strength of these cross-asset correlations is directly linked to periods of Federal Reserve interventions yet disappear when the interventions were (in fact or were perceived to be) withdrawn. Despite being studied extensively in the academic literature, no traditional intervention channels can explain the changes in cross-comovement. It is proposed that the Fed’s extraordinary stimulus caused investors to use Fed announcements as a common, low-cost information source on which they used to make common portfolio-allocation decisions. The changes in comovement during the intervention period may have reduced investor welfare for those with longer-horizon allocation strategies, those not prepared for the eventual ending of the stimulus, and for underfunded liability-optimizing portfolio managers (e.g., state pension funds).

Understandings of house prices and their interrelationships have undoubtedly drawn a great amount of attention from various market participants. This study aims to investigate the monthly newly-built residential house price indices of seventy Chinese cities during a 10-year period spanning January 2011–December 2020 for understandings of issues related to their interdependence and synchronizations.

Analysis here is facilitated through network analysis together with topological and hierarchical characterizations of price comovements.

This study determines eight sectoral groups of cities whose house price indices are directly connected and the price synchronization within each group is higher than that at the national level, although each shows rather idiosyncratic patterns. Degrees of house price comovements are generally lower starting from 2018 at the national level and for the eight sectoral groups. Similarly, this study finds that the synchronization intensity associated with the house price index of each city generally switches to a lower level starting from early 2019.

Results here should be of use to policy design and analysis aiming at housing market evaluations and monitoring.

Local investors have the ability to impact the stock prices and returns of local firms. However, the impact of news made by a firm on local investors and neighboring companies is absent from the academic literature. The purpose of this paper is to fill that void and examine how a local investor clientele affects the stock market reactions of firms located within the same geographic proximity as a news-generating firm.

After accounting for firm, industry, and geographic characteristics, this study examines how a firm’s dividend initiation announcement (positive news) influences stock prices of seemingly unrelated firms within the same metropolitan statistical area (MSA).

Dividend-paying firms located in areas with a higher percentage of dividend clientele experience a positive comovement reaction when a seemingly unrelated firm within the same MSA announces a dividend initiation. The positive reactions are specifically for dividend-paying firms, while non-dividend payers exhibit no significant response. These results are robust to numerous regression methods and alternative explanations.

These findings are consistent with the positive-investor-attention hypothesis, suggesting positive spillover effects from news announcements for other local firms in the presence of individual investor clientele.

This is the first study to link how news generated by one firm can influence other geographically local firms, providing evidence on the impact of individual investor clientele on stock returns of local non-news firms.

The purpose of this paper to provide a discussion of the empirical evidence and contributing factors of the synchronization of house prices globally.

The author reviewed the main studies on house price synchronization and conducted an empirical analysis using OECD house price indices. A discussion of the contributing factors of synchronization, with a focus on the demand and supply dimensions is provided, and synchronization across both countries and cities is examined.

Housing markets globally have become more synchronized; this is particularly clear for cities. The sustained demand for places that are attractive for financial motives and for lifestyle and sometimes climate along with the fact that such places tend to be supply-constrained is likely to lead to more synchronization across markets.

The conclusions are important for investors seeking to diversify their housing holdings internationally. The discussion should also benefit policy-makers.

To date, very scarce evidence exists on the synchronization of house prices globally. By surveying the results contained in previous studies and providing a thorough discussion of the possible drivers of house price synchronization, this study contributes to a better understanding of this important topic.

This paper investigates the impact of financial stress on the dynamic connectedness and hedging for oil market and stock-bond markets of the Gulf Cooperation Council (GCC).

This study uses the wavelet coherence model to examine the interactions between financial stress, oil and GCC stock and bond markets. Second, the authors apply the time–frequency connectedness developed by Barunik and Krehlik (2018) so as to identify the direction and scale connectedness among these markets. Third, the authors examine the optimal weights, hedge ratio and hedging effectiveness for oil and financial markets based on constant conditional correlation (CCC), dynamic conditional correlation (DCC) and Baba-Engle-Kraft-Kroner (BEKK)-GARCH models.

The authors have found that the correlation between the oil and stock-bond markets tends to be stable in nonshock periods, but it evolves during oil and financial shocks at lower frequencies. Moreover, the authors find that the oil market and financial stress are the main transmitters of risks. The connectedness is mainly driven by the long term, demonstrating that the markets rapidly process the financial stress spillover effect, and the shock is transmitted over the long run. Optimal weights show different patterns for each negative and positive case of the financial stress index. In the negative (positive) financial stress case, investors should have more oil (stocks) than stocks (oil) in their portfolio in order to minimize risk.

This study has gone some way toward enhancing one’s understanding of the time–frequency connectedness between the financial stress, oil and GCC stock-bond markets. Second, it identifies the impact of financial stress into hedging strategies offering important insights for investors aiming at managing and reducing portfolio risk.

The purpose of this paper is to examine the short‐term stock market interactions between US and six major Asian markets – China, India, Hong Kong, Singapore, South Korea and Taiwan. These six economies along with Japan and Australia have the largest stock exchanges in the Asia‐Pacific region. The importance of the US market to the Asian economies is the prime motivation for a quantitative assessment of its role in this region. The objective of this study is to measure the dynamic stock market interdependence of US and Asian newly industrialized economies (NIEs) (Hong Kong, Singapore, South Korea and Taiwan) and emerging market economies (EMEs) (China and India) post Asian crisis of 1997 and also to capture the market interactions during the sub‐prime crisis.

The study has employed Granger causality tests and generalized forecast error variance decomposition (FEVD) analysis to analyze the fluctuations in and the extent of short‐term interdependence between the US and Asian economies. VAR model was estimated to run the simulations for FEVD analysis.

The empirical results from FEVD analysis revealed the dominance of US stock market on Asian markets; the USA being a large economy of the world, an important trading partner and major supplier of capital to Asian region. Stock markets of Asia are not immune to the shocks originating in the USA although the effects of shocks vary considerably across markets. Further, an important implication is that major crisis events can influence the relationship among stock markets.

This is one of the first papers in the Asian context examining the interdependence with the US markets. Hence, even though most of the Asian economies went through liberalization, the macroeconomic and financial circumstances were very different before, after and during the process. This motivated the examination of the interactions between US and other Asian markets.

This chapter seeks to analyze the development across the length and breadth of the Indian financial system in the post-reform period, based on the “flow of funds” accounts estimates by RBI. Besides, this chapter also analyzes the integration of the Indian capital market with the stock markets of the United States, the United Kingdom, Japan, China, Hong Kong, and Singapore using the movements in their stock prices during 1998–2015. Moreover, this chapter is intended for examining the potential implication financial integration, particularly the financial openness of India, on volatility spillover and financial contagion in as much as these two issues have emphatic significance in the determination of the relevant policy roadmap. Our findings broadly confirms the expectations by revealing significantly positive correlations in stock prices, in returns to investments in stock markets, and in mean returns and risk. The integration of the capital markets is also manifested in the cyclical fluctuations of the stock price indices, signifying the underlying sensitivity to random shocks.

This paper aims to examine how banks’ accounting disclosure policies affect information content in stock prices and stock crash risk.

This paper uses 1996-2013 as the sample period. The final sample includes 10,045 observations in 37 countries. This paper uses stock return synchronicity to measure information content in stock prices. This study uses the frequency difference between extremely negative and positive stock returns to measure stock crash risk. To measure the level of bank accounting disclosure, this research follows Nier and Baumann (2006) to construct an aggregate disclosure index based on inclusions and omissions of a series of items in a bank’s annual accounting reports.

This paper finds that banks’ stocks have lower stock return synchronicity and fewer extremely negative returns if banks have higher levels of financial statement disclosure. These results suggest that banks’ stocks have higher information content and lower crash risk if banks’ information environment is more transparent.

Overall, this paper provides new insight about how to increase banks’ transparency and the safety of the banking industry, which is beneficial to economic growth. To increase banks’ transparency and reduce the possibility of extremely negative stock returns, one way to regulate banks is to increase their accounting disclosure. In addition, the extant literature (Chen et al., 2006, Durnev et al., 2003, 2004; Wurgler, 2000) demonstrates that firms with lower stock return synchronicity have more transparent information environments and higher investment efficiency. Thus, this paper finds that higher levels of bank accounting disclosure are associated with lower stock return synchronicity, which further reduces banks’ opacity and increases banks’ investment efficiency. Finally, compared to business firms, stock crash risk has much direr consequences because one bank’s stock crash will affect overall financial stability. Thus, it is important for authorities to know the effects of accounting disclosure on bank stock crash risk.

The study's purpose is to investigate the price volatility of four dairy commodities (skim milk powder [SMP], whole milk powder [WMP], butter and cheddar cheese) in the three most significant regional markets (EU, Oceania and US) in the international dairy market.

The study uses a panel-Generalized Autoregressive Conditional Heteroskedastic (panel-GARCH) modeling technique and data from January 12, 2001, to April 28, 2017.

Conditional volatility was higher during subperiods 2007–2010 and 2014–2016 when conditional cross-correlations between prices had the lowest values. In some cases, they were negative (i.e. between the EU and the USA and between Oceania and the USA for both butter and cheese). Interdependence across the three dairy markets, especially for SMP and WMP markets and for the butter market between EU and Oceania is also strongly evidenced. Interdependence is responsible for the spillover of price shocks across the three regions.

The data set used should be extended to cover the COVID-19 pandemic period.

This is the first study to use panel-GARCH to examine international dairy prices and volatility linkages, where previous studies mainly used multivariate GARCH models. Panel-GARCH allows a high-dimensional data series (i.e. 12 dairy prices) and generates potential efficiency gains in estimating conditional variances and covariances by incorporating information about heterogeneity across markets and considering their interdependence.

The studies on international housing markets have not modeled frequency domain and focused only on the time domain. The purpose of the present research is to fill this gap by using the state-of-the-art econometric technique of wavelets to understand how differences in the horizon of analysis across time impact international housing markets’ relationship with some of the key macroeconomic variables. The purpose is to also analyze the direction of causation in the relationships.

The author uses the novel time–frequency analysis of international housing markets’ linkages to the macroeconomic drivers. Unlike conventional approaches that do not distinguish between time and frequency domain, the author uses wavelets to study house prices’ relationship with its drivers in the time–frequency space. The novelty of the approach also allows gaining insights into the debates that deal with the direction of causation between house price changes and macroeconomic variables.

Results show that the relationship between house prices and key macroeconomic indicators varies significantly across countries, time, frequencies and the direction of causation. House prices are most related to interest rates at the higher frequencies (short-run) and per capita income growth at the lower frequencies (long-run). The role of industrial production and income growth has switched over time at lower frequencies, particularly, in Finland, France, Sweden and Japan. The stock market’s nexus with the housing market is significant mainly at high to medium frequencies around the recent financial crisis.

The present research implies that in contrast to the existing approaches that are limited to the only time domain, the frequency considerations are equally, if not more, important.

Results show that interested researchers and analysts of international housing markets need to account for the both horizon and time under consideration. Because the factors that drive high-frequency movements in housing market are very different from low-frequency movements. Furthermore, these roles vary over time.

The insights from the present study suggest policymakers interested in bringing social change in the housing markets need to account for the time–frequency dynamics found in this study.

The paper is novel on at least two dimensions. First, to the best of the author’s knowledge, this study is the first to propose the use of a time–frequency approach in modeling international housing market dynamics. Second, unlike present studies, it is the first to uncover the direction of causation between house prices and economic variables for each frequency at every point of time.