Information Spillover Effects Research Articles

Spillover effects of multidimensional information in Fed statements on China's bond market

This paper shows significant information spillover effects of Fed statements on China's bond market. Regarding Fed monetary policy statements as external shocks, we extract both monetary policy information and narrative sentiment information from the statements, with the sentiment data measured using the text analysis method. Furthermore, it investigates spillover effects of the multidimensional Fed information on investors' trading behaviors in China's bond market, using the event study method. Our study emphasizes three key findings. First, both monetary policy and textual sentiment within Fed statements influence trading decisions of China's bond investors, generating international spillover effects. Importantly, the role of textual sentiments as an additional spillover channel of Fed statements has been overlooked in existing literature. Second, the US monetary policy information influences investors' expectations of China's short-term interest rates and their perceptions of risks associated with holding China's long-term bonds, while the Fed's negative and uncertain sentiments primarily impact investors' short-term rate expectations. Moreover, the spillover effects of Fed sentiments on China's yield curve cannot be blocked by China's managed floating exchange rate regime. Third, the heterogeneity test reveals that spillover effects of multidimensional information in Fed conventional monetary policy statements on China's bond market are stronger than those of Fed unconventional monetary policy statements. These findings suggest that Fed narrative sentiments should be incorporated into the research framework of international spillover effect of monetary policy, especially amidst the current period characterized by growing anticipation of federal funds rate cuts and enduring monetary policy uncertainty, providing valuable insights for trading decisions of China's bond market investors.

Alumni network, mutual fund herding and information spillover: Evidence from China

This paper studies the influence of alumni connections on mutual fund herding behavior. We find funds with alumni connections have significantly more overlap in holdings, purchases, and sales than funds without connections. Based on the perspective of information spillover effect, further research find alumni fund managers are more likely to conduct corporate site visit together, and shared stocks held by alumni funds have higher probability of positive earnings surprise. The performance of funds with alumni connections are more related and are more likely to suffer unsystematic shocks simultaneously. Our findings reveal the importance of alumni networks in assets management industry.

A Study on Co-movements and Information Spillover Effects Between the International Commodity Futures Markets and the South Korean Stock Markets: Comparison of the COVID-19 and 2008 Financial Crises

Purpose - This paper aims to compare and analyze the co-movements and information spillover effects between the international commodity futures markets and the South Korean stock markets during the COVID-19 and the 2008 financial crises.
 Design/methodology - The DCC-GARCH model is used in the co-movements analysis. In contrast, the BEKK-GARCH model is used to evaluate information spillover effects. The statistical data used is from January 1, 2005, to December 31, 2022. It comprises the Korea Composite Stock Price Index data and daily international commodity futures prices of natural gas, West Texas Intermediate crude oil, gold, silver, copper, nickel, soybean, and wheat.
 Findings - The results of the co-movement analysis were as follows: First, it was shown that the co- movements between the international commodity futures markets and the South Korean stock markets were temporarily strengthened when the COVID-19 and 2008 financial crises occurred. Second, the South Korean stock markets were shown to have high correlations with the copper, nickel, and crude oil futures markets. The results of the information spillover effects analysis are as follows: First, before the 2008 financial crisis, four commodity futures markets (natural gas, gold, copper, and wheat) were shown to be in two-way leading relationships with the South Korean stock markets. In contrast, seven commodity futures markets, except for the natural gas futures market, were shown to be in two-way leading relationships with the South Korean stock markets after the financial crisis. Second, before the COVID-19 crisis, most international commodity futures markets, excluding natural gas and crude oil future markets, were shown to have led the South Korean stock markets in one direction. Third, it was revealed that after the COVID-19 crisis, the connections between the South Korean stock markets and the international commodity futures markets, except for natural gas, crude oil, and gold, were completely severed.
 Originality/value - Useful information for portfolio strategy establishment can be provided to investors through the results of this study. In addition, it is judged that financial policy authorities can utilize the results as data for efficient regulation of the financial market and policy establishment.

Risk transmission of El Niño-induced climate change to regional Green Economy Index

Global warming and rare weather caused by climate change continue to affect ecosystems, human health, and economic systems, which pose serious climate risk challenges for humanity. To address and adapt to climate change risks and to facilitate the process of achieving carbon peaking and carbon-neutral targets, the financial industry has become more concerned about the information spillover effects of extreme climate events on green financial products. Therefore, this paper adopts the Southern Oscillation Index (SOI) to describe climate change and investigates the influence of the SOI on the volatility of the NASDAQ OMX Green Economy Index (OMX-GEI) under a variant of the Double Asymmetric GARCH-MIDAS (DA-GM-X) model. The results show that the SOI provides relevant information for OMX-GEI volatility forecasting and the DA-GM-X model yields outstanding forecasting performance in statistical and economic terms. This conclusion indicates that considering SOI and its asymmetry changes can significantly improve the prediction accuracy of econometric models. Also, several robustness tests confirm our findings. Overall, the findings of this paper suggest that to achieve the two-carbon goal and combat climate change, governments should pay more attention to policy formulation that combines environment, climate, health, energy, and economy, and actively promote green, low-carbon, and sustainable energy development globally.

Big tech credit score and default risk ——Evidence from loan-level data of a representative microfinance company in China

Using a unique loan-level dataset from a representative microfinance company in China, this paper investigates the information spillover effect of big tech credit scores on microloan risk management. We analyze a quasi-natural experiment where the microfinance company integrated big tech credit scores into its loan decision-making process. Our findings indicate that incorporating fintech information into risk assessments significantly lowers the default rate for new borrowers compared to existing ones. This effect is more pronounced for borrowers with insufficient collateral, higher loan demand, and medium risk levels, as well as for branches with higher historical default rates. Additionally, we observe a slight reduction in approved loan amounts for borrowers with medium risk levels, suggesting that big tech information contributes to more prudent loan decisions in microfinance.

Examining the Spillover Effects from Global Stock Markets to Indian Stock Market

Purpose: The study aims to examine the transmission of spillover effects from global stock markets to the Indian stock market. The chosen global markets are CAC-40, DJIA, FTSE 100, SMI, KOSPI, DAX, HANG SENG, and NIKKEI with respect to S&P BSE SENSEX.
 Design/Methodology/Approach: The study uses secondary data. The study period is from 1st January 2000 to 4th June 2021. The required data for the study has been collected from the Thomson Reuters database. Later the collected data has been tested for stationarity by running the ADF test. Since we found an arch effect in the collected time series data, we ran the GARCH model to investigate the spillover effect from developed stock markets to the Indian stock market by running all the three suggested models such as Normal Gaussian Distribution, Student t Distribution, and GED with fixed parameter. To capture the leverage effect, the researchers have run the EGARCH model to capture spillover asymmetry in the Indian stock market.
 Findings: The ARCH, GARCH, and EGARCH revealed that there was a significant information spillover effect from CAC-40, FTSE 100, SMI, KOSPI, HANG SENG, and NIKKEI on S&P BSE SENSEX. DJIA and DAX were not capable of spreading the spillover effect on BSE SENSEX. The EGARCH revealed that negative shocks in the foreign market created a significant spillover effect in the Indian stock market.
 Originality and Value: This study’s empirical analysis would help market participants in understanding the forecasted volatility of Sensex returns and can take this sign as an advantage to converting their holdings into returns. The market participants can also make a decision as to whether they can invest in the Indian stock market and diversify their portfolios.

Interrelation measurement based on the multi-layer limited penetrable horizontal visibility graph

Interrelation measurement is the basis of big data mining. This paper proposes an efficient method to measure the dynamic correlation and synchronicity relationship of multidimensional data using the microscopic topological structure of a multi-layer network. In order to measure the dynamic correlation between multidimensional data, multidimensional data are transformed into a time-varying multi-layer limited penetrable horizontal visibility graph network. On this basis, a time-varying correlation measurement index of multidimensional data based on the microscopic structure of the interlayer network connection is proposed. In addition, based on the degree distribution of each layer and information entropy theory, a time-varying information measurement index of multidimensional data is introduced. Further, to measure the synchronicity relationship between multidimensional data, time-delay parameters are defined, and a method to transform multidimensional data into a delay time-varying multi-layer limited penetrable horizontal visibility graph network is developed. A symmetrical and antisymmetrical combinations index is defined to measure the synchronicity relationship and to determine which system leads the others. Numerical simulation verifies the effectiveness of the proposed index and the proposed method's robustness to handle data disturbed by noise. Finally, an empirical analysis is conducted using the price data of the energy and carbon markets. The dynamic relationship between the crude oil future and gasoline future market is obtained. The dynamic information spillover effect between the carbon and energy markets is analyzed.

The Information Spillover among the Carbon Market, Energy Market, and Stock Market: A Case Study of China’s Pilot Carbon Markets

The carbon emission trading market is an important policy tool to promote the realization of China’s carbon peaking and carbon neutrality goals. Research on the relationship between the carbon market and other related ones supports policy formulation and risk aversion. Firstly, we construct the Carbon–Energy–Stock system to compare the information spillover between the three subsystems under a unified framework. Secondly, we adopt the connectedness network to identify the role and status of the carbon, energy, and stock markets. Thirdly, through the rolling window approach, we explore the dynamic evolution of the information spillover. The results show that (1) the information spillover effect between China’s pilot carbon markets, the energy market, and the stock market is relatively low; (2) in the Carbon–Energy–Stock system, China’s pilot carbon markets behave as the information transmitters, and the Guangdong pilot and Beijing pilot are core pilots. The coal market is the top information recipient, while the new energy industry is the top information transmitter; (3) the system connectivity shows the characteristics of increasing first and then decreasing. For investors and policymakers, looking at each market from a systems point of view will present a more accurate understanding of them and their interconnections.

A Study on Information Spillover Effects between the Korean, U. S. and Japanese Housing Markets

A Study on Information Spillover Effects between the Korean, U. S. and Japanese Housing Markets

Information spillover effects from media coverage to the crude oil, gold, and Bitcoin markets during the COVID-19 pandemic: Evidence from the time and frequency domains

Many scholars have explored the COVID-19 impact on the crude oil, gold, and Bitcoin markets, whereas most have ignored the media coverage influence. This paper focuses on examining information spillover from epidemic-related news to the crude oil, gold, and Bitcoin markets with the time-frequency analysis method. The empirical results reveal that both the return and volatility spillovers from epidemic-related news to the crude oil, gold, and Bitcoin markets are stronger in the short term (less than 1 week). In the long term, only the media sentiment index notably impacts crude oil, gold, and Bitcoin market returns. The volatility spillover from media coverage to crude oil mainly occurs in the short term. Regarding the gold and Bitcoin markets, the long-term volatility spillovers are significant. An obvious risk contagion path is found. Media hype is the main risk transmitter and transmits vast shocks to these three markets, especially the Bitcoin market, which subsequently transmits these shocks to the gold market. Risk accumulates systemically in the gold and Bitcoin markets. These findings have crucial empirical implications for policymakers and investors when formulating related short- or long-term decisions during the pandemic.

Spillover Effects of Analyst Coverage on IPO Firms

This study investigates the effect of analysts’ recommendations and earnings forecasts for newly listed firms in the same industry. IPO underpricing is significantly lower as the number of firms whose investment recommendations are upgraded increases, supporting the contagion effect hypothesis that a high affinity for the industry has a positive effect on the IPO offer price. However, as the number of listed firms with higher earnings forecasts increases, IPO underpricing is higher, which supports the competitive effect hypothesis that the profit growth of competitors negatively affects IPO firms’ competitiveness. The effects vary depending on the competitive positions of both listed firms and IPO firms within the industry. The results also show that in industries with high concentration (i.e. low competition) , analyst information on listed firms has a greater contagion effect, while the competition effect hypothesis that better earnings forecasts for rival firms negatively affect IPO firms’ competitive position is not supported. This study contributes to the literature by analyzing the information spillover effect of analyst coverage in the IPO market by showing that the effects vary depending on the firms’ competitive positions as well as industry competition.

Research on the Information Spillover Effect of Production Network：From the Perspective of Analysts

As China’s capital market reform enters the deep-water zone, strengthening the role of security analysts is an excellent way to alleviate the contradiction between the sharply increased market specialization level and the backward literacy of investors. At the same time, unilateralism is on the rise, and the Chinese government has set the “domestic circulation” development strategy. In this dual context, this paper mainly discusses how the production network reflecting the domestic circulation affects the accuracy of analysts’ earnings forecasts.Based on the earnings forecast of listed companies released by security analysts during 2007-2018 and industry input-output data, this paper explores the impact of production networks on analysts’ earnings forecasts. It is found that the production network has an information spillover effect on analysts’ earnings forecasts. That is, when the industry of analyst-following companies is closely related in the production network, the deviation of the earnings forecast issued by analyst-following companies is lower. After measuring primary and secondary industries by tracking ratio, it is found that the spillover direction is from primary to secondary. The mitigating effect of production network correlation and its spillover effect on the information asymmetry at the industry and firm levels faced by analysts provide a specific explanation for the reduction of forecast bias. In addition, the cross-sectional analysis based on industrial policy shows that the marginal effect of production network correlation on analysts’ forecasts is more obvious in non-key supporting industries. Further analysis shows that the role of production network correlation analyst is effective, which promotes the integration of specific production network information into stock prices and reduces the synchronization between the firm and the market portfolio. After classifying the information hierarchy, it is found that analysts mainly increase the interpretation intensity of information at the industry level.The marginal contribution of this paper lies in that: It enriches the relevant literature on the quality of analysts’ earnings forecasts from the industry perspective, and highlights the importance of industry correlation that may have been neglected in the early stage. Different from the micro-perspectives of suppliers and customers, this paper extends the information spillover of industrial chain to the multi-dimensional production network, and enriches the research on industry association from the perspective of network. On the practical level, from the perspective of the inter-industry input-output that forms the domestic circulation, the emphasis on the role of production network and analysts is of certain practical significance for improving the efficiency of market information and promoting the professional reform.

International Real Estate Review

Ambrose et al. (2007) find significant evidence of information spillover effects between index real estate investment trusts (REITs) and nonindex REITs in the US markets using the inclusion of REITs into the S&P general market indices in an event study. This study, however, examines the effects of REIT index inclusion events by using non-index real estate operating company (REOC) returns in the US and Singapore. The study finds that REOC returns are more correlated with the general market index returns after REIT index inclusion events, but the spillover effects are smaller for REOCs in Singapore. The spillover effects of the REIT inclusion events are larger on non-index REITs than non-index REOCs in the US. When examining REIT inclusion events in Singapore, we find evidence of increases in betas only in the REIT market, but the changes in REOC betas are insignificant. However, we find that the REIT index inclusions significantly reduce the systematic risks of REOCs that sponsor the index REITs.

Information Flow Effect Between the Housing Market and the Chonsei Market

This paper examines the information spillover effects between housing sales and chonsei markets using EGARCH model as time series data for the housing sales and chonsei price index. The EGARCH model was used to examine the asymmetric volatility of information, and the overall analysis period is from January 1986 to December 2020, the empirical analysis was conducted by dividing the period from January 1986 to December 1997 before the foreign exchange crisis, and from January 1998 to December 2020 after the foreign exchange crisis. The result of the study is as follows. First, the EGARCH(1,1) model considering asymmetric volatility is suitable. Second, the price spillover effect between housing sales and chonsei markets was positive during the post-exchange crisis period, and the volatility spillover effect was found to have a minor negative effect in both markets. Third, the asymmetric volatility spillover effect exists in two markets, but it is significant in the post-exchange crisis period, indicating that the coupling phenomenon between the two markets is close. The housing market is also more sensitive to good news than bad news. Therefore, policies need to be implemented from a mutually organic perspective to stabilize the housing market.

Information Spillover Effects of Real Estate Markets: Evidence from Ten Metropolitan Cities in China

With the rapid development of information communication technology and the Internet, information spillover between cities in real estate markets is becoming more frequent. The influence of information spillover in real estate markets is becoming more and more prominent. However, the current research of information spillover between cities is still relatively insufficient. In view of this research gap, this paper builds a research framework on the information conduction effect in the real estate markets of 10 Chinese cities by using Baidu search data, text mining and principal component analysis and analyzes the information interaction and dynamic influence of the real estate markets in each city by using the vector autoregressive model empirically. The results show that the information interaction among the real estate markets in each city has a network pattern and there is a significant two-way information spillover effect in most cities. When the “information distance” becomes closer, the information interaction between the markets of the cities becomes closer and it is easier for cities to influence each other. The results help to explain the information spillover mechanism behind the house price spillover and to improve the ability to predict and analyze the information spillover process in real estate markets.

Analyzing the time-frequency connectedness among oil, gold prices and BRICS geopolitical risks

Based on the Barunik and Křehlik (2018) and Diebold Yilmaz (2012) methods, we examine the dynamic characteristics of the information spillover effect among gold, oil and BRICS geopolitical risks in different time and frequency domains. The results show that return and volatility spillovers are stronger in the short term than in the long term. The overall spillover is caused mainly by short-term spillover effects. In most cases, the oil market has a strong spillover relationship with the gold market. Furthermore, China's geopolitical risks have the greatest impact on gold, oil, and other countries' geopolitical risks. In addition, China's geopolitical risks are the only net contributor in the time domain, which indicates that China occupies an important position in the BRICS. Furthermore, geopolitical events can significantly increase the connectivity of the entire framework.

Understanding the attenuation of the accommodation recommendation spillover effect in view of spatial distance

AbstractThis brief communication aims to reveal whether the recommendation information's spillover effect decays with geographical distance. A unique dataset of Airbnb listings in Beijing is collected to perform an empirical analysis and a model simulation. The results of this study demonstrate that the spillover of listings' recommendation information decays with spatial distance and this decay follows a certain attenuation mode (i.e., has a certain attenuation rate and attenuation point). As one of the first to investigate the attenuation mechanism of information spillover, this communication enriches the current research on information transmission and brings a novel topic to the attention of the community.

An Study on the Information Spillover Effect of Returns, Volatility, and volume in the KOSPI200 Spot and Futures Market

An Study on the Information Spillover Effect of Returns, Volatility, and volume in the KOSPI200 Spot and Futures Market

Exploring the Open Innovation Information Spillover Effect: Conceptual Framework Construction and Exploratory Analysis

Since its launch, open innovation has been one of the hottest research topics in the field of innovation management. However, most of the current literature focuses on open innovation participants, severing the link between actors engaging in open innovation activities and social third-party firms, i.e., lacks discussions of the social attributes of open innovation. Therefore, via the perspective of the evolution of open innovation participants, this paper reviews current research from the aspects of unilateral subjects, bilateral subjects, and third-party subjects. Integrating the perspective with a sociological view, this paper theoretically constructs a framework for the open innovation information spillover effect. Moreover, taking Huawei Technologies Co., Ltd., as an example, this paper verifies the practical existence of the information spillover effect among firms' open innovation activities. This paper aims to extend the research boundary of open innovation, thereby providing a theoretical reference for further studies.

The Empirical Information Spillover Effect between the Housing Market and the Stock Market

The Empirical Information Spillover Effect between the Housing Market and the Stock Market