Information Spillovers Research Articles

Dynamic linkage of the bitcoin market and energy consumption:An analysis across time

With the control of the cryptocurrency market in environmental protection, investors pay attention to the risk conduction mechanism between energy consumption and the Bitcoin market. This paper applies quantile connectedness to analyse the overall situation and dynamic evolution of information spillover in the system of the Bitcoin market. The results show that the hashrate and electricity demand are the primary sources of risk in the information network, and their fluctuations have intensified the risk spillover effects in the system. In addition, the spillover level is more prominent in extreme cases, which means the information linkage in the system is integrated. The spillover effect of each variable fluctuates and is uncertain with time. This helps in the sustainable development of Bitcoin and guides the government's policy development and supervision of cryptocurrencies. The risk infection path helps prevent the risk of infection in the Bitcoin market and improves the sustainability of the encrypted market.

COVID-19 and China commodity price jump behavior: An information spillover and wavelet coherency analysis

Jumps in commodity prices can make asset risk management challenging. This study explores the influence feature of the COVID-19 epidemic on China's commodity price jumps, using 5-min intraday high-frequency futures data of three China's commodity markets (energy, chemical, and metal) from January 23, 2020 to June 10, 2022. We find that firstly the information spillover from the COVID-19 spread situation to China's energy price jumps is relatively weak, and the COVID-19 epidemic shows the most substantial jump information spillover pattern to China's chemical price. The information spillover pattern is time-varying across the COVID-19 spread situation phase. Secondly, there are co-movement patterns between China's commodity price and China/global COVID-19 confirmed cases. This co-movement feature mainly occurs at the medium- or long-run time scales, and varies across commodities. Thirdly, the demand elasticity for China's commodities and its dependence on imports and exports are the main factors influencing the sensitivity of its price jumps to the COVID-19 outbreak.

Information Spillovers Prior to M&A Announcements

In this paper, I study trading activities prior to M&A announcements pertaining to the rivals of the merging firms. I find that not only acquirers and targets experience increases in abnormal trading activities in stock and option markets, but also their rivals. The rise in option trading is especially strong for options that informed traders are most likely to trade. I find that the implied volatility spread (IV spread) constructed from a rival’s option prices the day before the announcement can predict this rival’s cumulative abnormal return (CAR) over the M&A announcement window. As the IV spread is widely adopted as a proxy for informed trading activities in the option market, my findings provide evidence for information spillovers from merging firms to their rivals prior to the announcements of the M&A deals.

Information exchange and multiple peer groups: A natural experiment in an online community

We utilise a quasi-experimental setup to identify causal effects of having additional peer groups on information exchange in a large online maternity community. The information exchange is a key performance indicator for the community as well as a public good among users. Pregnant users join default peer groups based on estimated due date (EDD). Natural uncertainties of EDD can lead to multiple peer groups. Using EDD as an instrumental variable, we find that additional peer group(s) reduces information exchange in both default peer group and total peer groups. Having more advanced groups mitigates the reduction, likely due to information spillovers.

Dynamic Multiscale Information Spillover among Crude Oil Time Series.

This study investigated information spillovers across crude oil time series at different time scales, using a network combined with a wavelet transform. It can detect the oil price, which plays an important role in the dynamic process of spillovers, and it can also analyze the dynamic feature of systematic risk based on entropy at different scales. The results indicate that the network structure changes with time, and the important roles of an oil price can be identified. WTI and Brent act as important spillover transmitters, and other prices are important spillover receivers at a scale. With the increase in time scale, both the number of neighbors and the importance of spillovers of Brent and WTI as spillover transmitters show downward trends. The importance for spillovers of China–Shengli and Dubai as spillover receivers shows a downward trend. This paper provides new evidence for explaining WTI and Brent as global benchmark oil prices. In addition, systematic risk is time-varying, and it is smaller at short-term scale than at long-term scale. The trend of systematic risk is also discussed when typical oil-related events occur. This paper provides a new perspective for exploring dynamic spillovers and systematic risk that offers important implications for policymakers and market investors.

Competitive investments between basic R&D and applied R&D with information spillovers

The impacts of information spillovers on Research and Development (R&D) choices are investigated in a two-stage Cournot duopoly where two firms simultaneously and non-cooperatively determine their levels of applied R&D aiming at the creation of a new process and basic R&D devoted to the improvement of absorptive capacity. Through a comparative static analysis, it is demonstrated that as more information associated with applied R&D spills out, each firm will shift its R&D expenditure from applied R&D to basic R&D if the efficiency of basic R&D is relatively low. Similarly, a relatively higher spillover degree of basic R&D induces each firm to invest less in basic R&D and more in applied R&D. However, in some cases both firms will reduce their efforts in the two types of R&D as more R&D know-how leaks out. Furthermore, the increase in applied R&D spillovers always contributes to the two firms and the society. Assuming that the efficiency of basic R&D is sufficiently low, as basic R&D becomes more appropriable, firms’ profits and social welfare will be decreased (improved), provided that the spillover level of basic R&D is relatively small (large).

Public peers, accounting comparability, and value relevance of private firms’ financial reporting

We examine whether higher accounting comparability between public and private firms leads to higher value relevance of private firms’ reported financial information. To help develop our hypotheses, we conduct a series of interviews with M&A valuation experts. The experts indicate that comparable accounting between public and private firms allows them to apply public firms’ valuation multiples directly to private firms, which facilitates the use of private firms’ financial reporting in their valuations. Using a large sample of M&A transactions with private target firms in the European Union around the mandatory adoption of IFRS by public firms, we find that private firms’ reported financial information has higher value relevance when it has higher accounting comparability to that of public firms. Furthermore, we find that the impact of accounting comparability is stronger when public peer information is more precise. Our findings are consistent with higher accounting comparability facilitating a spillover of valuation information from public to private markets, which leads to greater value relevance of private firms’ reported financial information.

Modelling international sovereign risk information spillovers: A multilayer network approach

Applying the TVP-VAR model, we creatively construct multilayer information spillover networks containing return spillover layer, volatility spillover layer and extreme risk spillover layer among 23 countries in the G20 to explore international sovereign risk spillovers. From the perspective of system-level and country-level measures, this article explores the topological structures of static and dynamic multilayer networks. We observe that (i) at the system-level, multilayer measures containing uniqueness edge ratio and average edge overlap show each layer has unique network structures and spillover evolution behavior, especially for dynamic networks. Average connectedness strength shows volatility and extreme risk spillover layers are more sensitive to extreme events. Meanwhile, three layers have highly intertwined and interrelated relations. Notably, their spillovers all show a great upsurge during the crisis (financial and European debt crisis) and the COVID-19 pandemic period. (ii) At the country-level, average overlapping net-strength shows that countries’ roles are different during distinct periods. Multiplex participation coefficient on out-strength indicates we’ll focus on countries with highly heterogeneous connectedness among three layers during the stable period since their underestimated spillovers soar in extreme events or crises. Multilayer networks supply comprehensive information that cannot obtain by single-layer.

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.

Guanxi in an age of digitalization: toward assortation and value homophily in new tie-formation

How do people form personal ties? A consensus holds in sociological and social network scholarship that in-person networks are dominated by status homophily and that guanxi networks rely extensively on balance. This article argues that social networking sites (SNSs) reconceptualize the character of homophily and tie-formation altogether in guanxi networks. Drawing on 50 semi-structured interviews with Hong Kong youth from 2017 to 2020, this article examines how the technical capabilities of SNSs and principles of guanxi culture come together to erode status boundaries, create access to larger networks, and cause spillovers of information and tie strength. As a result, the basis of tie-formation in guanxi networks on SNSs shifts from balance to assortation and status homophily to value homophily. In this transformed calculus of tie-formation, two typologies of values rise to the fore: substantive values that reflect opinions and interests, as well as structural values that reflect networkability.

Spatial Correlation Network of Water Use in the Yangtze River Delta Urban Agglomeration, China

The increasingly severe water crisis is restricting sustainable development of the Yangtze River Delta Urban Agglomeration (YRDUA), highlighting the importance of collaborative water resources management. Based on the dataset from 26 cities between 2001 and 2020 in the YRDUA, this study applies Social Network Analysis to research the spatial correlation of urban water utilization, which helps identify the interaction of water use behaviors among different cities. Results show that the close relationships among urban water consumption in the YRDUA have formed a network, and there is no isolated city in the water use correlation network. During the research period, the water network affinity and network density showed an overall upward trend, meaning the number of actual connections in the network was increasing. However, the network hierarchy first decreased and then raised, and the network efficiency first increased and then decreased, indicating the structural evolution of the water network was gradually detrimental to the effective dissemination of water use information. The urban water consumption correlation network also shows a core-peripheral structure. Shanghai, Wuxi, Suzhou, and Hangzhou have higher coreness and centralities, dominating the water network and controlling major information spillover channels. Therefore, it is essential to focus on the overflow effects of urban water consumption and management among different regions, optimize the structure of the water consumption correlation network, exploit the core cities’ radiation effects, and realize collaborative management for regional water resources.

Efficient markets are more connected: An entropy-based analysis of the energy, industrial metal and financial markets

This is the first article to jointly study the efficiency and connectedness of commodity markets, using the novel method combination of fuzzy entropy and multivariate transfer entropy analysis. We examine this issue in the nexus of energy, industrial metals and financial markets. We identify the existence of a relationship between market efficiency and connectedness, which opens a new direction for investigating the sources of market connectedness. The results indicate that the efficient markets process more information and are more connected in the system. Moreover, efficient markets are net transmitters of information to the less efficient markets. Stronger connectedness does not necessarily exist within the same market sector but emerges among the efficient markets irrespective of their sector categorization. The relationship between market efficiency and connectedness is more pronounced during extreme events. During the turbulence of COVID-19, there are stronger connectedness and higher information spillover from the efficient to less efficient markets. Specifically, we find the industrial metals are on average the most efficient sector, followed by the energy and then the financial markets. The relatively more efficient natural gas and industrial metal markets exhibit strong connectedness and transmit information to the less efficient crude oil and financial markets. These findings imply that the market connectedness can be the result of information dissemination and alleviate the concerns that higher connectedness may compromise the price discovery mechanism.

Information transmission among energy markets, cryptocurrencies, and stablecoins under pandemic conditions

This paper investigates the directional causal relationship and information transmission among the returns of West Texas Intermediate (WTI), Brent, major cryptocurrencies, and stablecoins by drawing on daily data from July 2019 to July 2020. Applying effective transfer entropy, a non-parametric statistic, the results show that the direction of the causal relationship and the nature of information spillovers changed after the COVID-19 pandemic. More precisely, our findings reveal that WTI and Brent are leading the prices of Bitcoin and Bitcoin Cash. Conversely, Bitcoin futures and stablecoins (TrueUSD and USD Coin) are leading WTI and Brent prices. In addition, the stablecoin Tether became a leader against Brent prices after the pandemic, although it is still following WTI prices. Moreover, Ethereum and USD coin preserved their position as leaders against Brent prices. Interestingly, our results also reveal that Ethereum, Litecoin, and Ripple preserved their position as leaders of WTI prices. The change in the nature of directional causality and the spillover effect after the COVID-19 crisis provide valuable information for practitioners, investors, and policymakers on how the ongoing pandemic influences the connection and network correlation among the energy, cryptocurrency, and stablecoin markets.

Information Spillovers to Discipline Politicians

Information Spillovers to Discipline Politicians

When FinTech Competes for Payment Flows

Abstract We study the impact of FinTech competition in payment services when a monopolist bank uses payment data to learn about consumers’ credit quality. Competition from FinTech payment providers disrupts this information spillover. The bank’s price for payment services and its loan offers are affected. FinTech competition promotes financial inclusion, may hurt consumers with a strong bank preference, and has an ambiguous effect on the loan market. Both FinTech data sales and consumer data portability increase bank lending, but the effects on consumer welfare are ambiguous. Under mild conditions, consumer welfare is higher under data sales than with data portability.

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

Does Internet Use Aggravate Public Distrust of Doctors? Evidence from China

The internet has exacerbated the spillover of medical information, and changes in the quantity, quality, and scope of information supply also affect public trust in doctors, which is of great significance to the construction of a harmonious physician–patient relationship. The objective of this study is to explore the relationship between internet use and residents’ trust in doctors using data from the China Family Panel Studies for 2018. The empirical investigation utilizes an endogenous switching regression model (ESR) to overcome the endogeneity bias. Our results indicate that internet use is negatively associated with residents’ trust in doctors (β = 0.07, p < 0.05). Specifically, the patient trust of internet users is nearly 7 percent less than that of non-internet users. Nevertheless, residents with higher dependence on traditional media such as television, newspapers, magazines and radio as an information channel show stronger patient trust. Finally, the results of the subsample analysis indicate a need to focus on older and less-educated residents, who are more vulnerable and more likely to be affected.

Bond market information disclosure and industry spillover effect

PurposeThe aim of this paper is to examine the effect of information disclosure by unlisted bond issuers on the stock price informativeness of listed firms in the same industry.Design/methodology/approachThis paper takes advantage of information disclosure during the bond issuance and examines the spillover effect of unlisted bond issuers' information disclosure on listed firms in the stock market. The sample is composed of A-share firms listed on the Shanghai and Shenzhen stock exchanges from 2007 to 2018. All the data are obtained from the China Stock Market and Accounting Research and WIND databases. The impact of bond market information disclosure on price informativeness of listed firms in the same industry is identified through multivariate regression analyses.FindingsEmpirical results show that price informativeness of listed firms has a significantly positive association with the information disclosure of same-industry unlisted bond issuers. Further analyses show that the above finding is more significant when information disclosure of bond issuers is a more important channel for acquiring industry information (i.e. when industry is more concentrated, when economic uncertainty is high, and when industry information is less transparent) and understanding the industry competitive landscape (i.e. when bond issuers are relatively large, when bond issuers and listed firms have more direct product competition, when bond issuance firms are large-scale state-owned business groups), and when there are more cross-market information intermediaries (i.e. more cross-market institutional investors and more sell-side analysts). This paper indicates that information disclosure of bond issuers has a positive spillover effect on the stock market.Originality/valueThe novelty of the research is that the authors examine industry information spillover from unlisted firms to listed firms leveraging on unlisted firms' information disclosure in bond markets.

Givers never lack: Nigerian oil & gas asymmetric network analyses

Analyzing the Nigerian oil and gas industry network system from May 5th, 2014 to January 23rd, 2020, this paper presents empirical evidence of the connectedness in a network of the six leading oil and gas companies in Nigeria with the WTI crude oil market. The results show that Forte oil is a safe-haven for the Nigerian oil & gas investment market. The Forte market is the leading giver or transmitter of all the return (overall, good news, and bad news) information spillover in the network; truly, ‘givers never lack!’. Conversely, Total oil and Mobil oil are the net receivers under different network designs. Truly. Under the volatility system network design, Seplat oil is the leading net transmitter of return volatility while the crude oil market is the largest net receiver. Under all the system network designs, the WTI crude oil market is a net receiver of information in the system. This depicts the true producer-trader flow of price information. Both the sensitivity and the robustness analysis confirm the findings from the main network connectedness analysis. Based on these findings, practical investment portfolio management policies are recommended for the Nigerian oil and gas investment market.