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学者姓名：高扬
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Abstract ：
This study investigates liquidity spillover effects within Chinese green financial markets and their implications for investment strategy construction. Utilizing time-varying parameter vector autoregression and quantile connectedness methods, we analyze the interconnectedness of these markets from both temporal and quantile perspectives. Our findings reveal that liquidity spillovers exhibit notable time-varying characteristics, with spillover effects being weaker in low and intermediate quantiles and more pronounced in high quantile. The minimum connectedness portfolio analysis demonstrates superior performance with more stable and higher cumulative returns surpassing most individual assets. Furthermore, including green bonds in these portfolios is an effective strategy for mitigating portfolio risk.
Keyword ：
Minimum connectedness portfolio Minimum connectedness portfolio Liquidity spillover Liquidity spillover Quantile connectedness Quantile connectedness Green financial markets Green financial markets
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| GB/T 7714 | Gao, Yang , Zhou, Yueyi , Zhao, Wandi . Liquidity spillover and investment strategy construction among Chinese green financial markets [J]. | INTERNATIONAL REVIEW OF ECONOMICS & FINANCE , 2025 , 98 . |
| MLA | Gao, Yang 等. "Liquidity spillover and investment strategy construction among Chinese green financial markets" . | INTERNATIONAL REVIEW OF ECONOMICS & FINANCE 98 (2025) . |
| APA | Gao, Yang , Zhou, Yueyi , Zhao, Wandi . Liquidity spillover and investment strategy construction among Chinese green financial markets . | INTERNATIONAL REVIEW OF ECONOMICS & FINANCE , 2025 , 98 . |
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Abstract ：
Combining internet text and stock trading data, we construct two investor sentiment proxies for 78 carbon-neutral stocks in Chinese stock markets based on the FinBERT model and principal component analysis. We then examine the effects of the two investor sentiment indices on carbonneutral stock returns using dynamic panel models. We also investigate the mediating role of liquidity on the effects of investor sentiment. Our results reveal that both trading and internet sentiment negatively affect stock returns through the mediating effect of liquidity. This finding holds after robustness checks for dividing the sample into pre and post-epidemics. However, due to the effects of COVID-19, carbon-neutral stock returns are found to be more susceptible to investor sentiment.
Keyword ：
Mediation effect Mediation effect Internet sentiment Internet sentiment FinBERT FinBERT Trading sentiment Trading sentiment Carbon-neutral stock Carbon-neutral stock
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| GB/T 7714 | Gao, Yang , Zhao, Chengjie , Wang, Yaojun . Investor sentiment and stock returns: New evidence from Chinese carbon-neutral stock markets based on multi-source data [J]. | INTERNATIONAL REVIEW OF ECONOMICS & FINANCE , 2024 , 92 : 438-450 . |
| MLA | Gao, Yang 等. "Investor sentiment and stock returns: New evidence from Chinese carbon-neutral stock markets based on multi-source data" . | INTERNATIONAL REVIEW OF ECONOMICS & FINANCE 92 (2024) : 438-450 . |
| APA | Gao, Yang , Zhao, Chengjie , Wang, Yaojun . Investor sentiment and stock returns: New evidence from Chinese carbon-neutral stock markets based on multi-source data . | INTERNATIONAL REVIEW OF ECONOMICS & FINANCE , 2024 , 92 , 438-450 . |
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Abstract ：
In this paper, the network connectedness of informed trading between industries and its contagion structure are studied in the time and frequency domains based on Chinese stock markets. Using the spillover index method, we find significant interindustry spillover effects of informed trading. Specifically, Industrials, Consumer Discretionary, and Materials are the primary spillover sources that have strong outward spillover effects on all other industries, while Communication Services and Financial represent the top recipients in the market. In addition, using the network community detection algorithm, a 2-community structure of contagion is further revealed. The two communities are driven by Industrials and Consumer Discretionary, respectively. More important, the strong outward effects of Industrials, Consumer Discretionary, and Materials and their interlinkages would cause both intracommunity and intercommunity spillovers and result in market-wide informed trading contagion. Furthermore, the frequency decomposition analysis illustrates that interindustry spillovers of informed trading are usually dominated by low-frequency (6-200 days) connectedness. Finally, the contributing factor analysis demonstrates that macroeconomic changes are the main determinants of informed trading spillovers.
Keyword ：
Network community detection Network community detection Informed trading Informed trading Industry board Industry board Spillover effect Spillover effect
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| GB/T 7714 | Zhao, Wandi , Gao, Yang . Network connectedness and the contagion structure of informed trading: Evidence from the time and frequency domains [J]. | INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS , 2023 , 90 . |
| MLA | Zhao, Wandi 等. "Network connectedness and the contagion structure of informed trading: Evidence from the time and frequency domains" . | INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS 90 (2023) . |
| APA | Zhao, Wandi , Gao, Yang . Network connectedness and the contagion structure of informed trading: Evidence from the time and frequency domains . | INTERNATIONAL REVIEW OF FINANCIAL ANALYSIS , 2023 , 90 . |
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Abstract ：
Although social media has highly facilitated people's daily communication and dissemination of information, it has unfortunately been an ideal hotbed for the breeding and dissemination of Internet rumors. Therefore, automatically monitoring rumor dissemination in the early stage is of great practical significance. However, the existing detection methods fail to take full advantage of the semantics of the microblog information propagation graph. To address this shortcoming, this study models the information transmission network of a microblog as a heterogeneous graph with a variety of semantic information and then constructs a Microblog-HAN, which is a graph-based rumor detection model, to capture and aggregate the semantic information using attention layers. Specifically, after the initial textual and visual features of posts are extracted, the node-level attention mechanism combines neighbors of the microblog nodes to generate three groups of node embeddings with specific semantics. Moreover, semantic-level attention fuses different semantics to obtain the final node embedding of the microblog, which is then used as a classifier's input. Finally, the classification results of whether the microblog is a rumor or not are obtained. The experimental results on two real-world microblog rumor datasets, Weibo2016 and Weibo2021, demonstrate that the proposed Microblog-HAN can detect microblog rumors with an accuracy of over 92%, demonstrating its superiority over the most existing methods in identifying rumors from the view of the whole information transmission graph.
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| GB/T 7714 | Bi, Bei , Wang, Yaojun , Zhang, Haicang et al. Microblog-HAN: A micro-blog rumor detection model based on heterogeneous graph attention network [J]. | PLOS ONE , 2022 , 17 (4) . |
| MLA | Bi, Bei et al. "Microblog-HAN: A micro-blog rumor detection model based on heterogeneous graph attention network" . | PLOS ONE 17 . 4 (2022) . |
| APA | Bi, Bei , Wang, Yaojun , Zhang, Haicang , Gao, Yang . Microblog-HAN: A micro-blog rumor detection model based on heterogeneous graph attention network . | PLOS ONE , 2022 , 17 (4) . |
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Abstract ：
The measurement of liquidity based on low-frequency data is a crucial issue in the financial market microstructure literature. This paper extends the commonly used LOT liquidity model by incorporating the characterization of the volatility dynamics and distributional properties of return series, thereby significantly improving both the goodness-of-fit of liquidity model and the estimation performance of the existing low-frequency liquidity measures. The new models, which have a special form of heavy-tailed Censored-GARCH model, have challenges in estimation. We then provide an approximate maximum likelihood estimation method to circumvent this problem. A real data analysis is conducted to evaluate the performance of the new liquidity measures. The results show overwhelming evidence that our new measures have advantages over the existing measures in both estimation error and correlation coefficient with high-frequency bid-ask spread. The robustness check analysis further illustrates that the advantages of our new measures are stable across different stock industries and different turnover levels.
Keyword ：
t-Distribution t-Distribution Liquidity Liquidity GARCH Model GARCH Model LOT Model LOT Model
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| GB/T 7714 | Zhao, Wandi , Gao, Yang , Wang, Mingjin . Measuring liquidity with return volatility: An analytical approach based on heavy-tailed Censored-GARCH model [J]. | NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE , 2022 , 62 . |
| MLA | Zhao, Wandi et al. "Measuring liquidity with return volatility: An analytical approach based on heavy-tailed Censored-GARCH model" . | NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE 62 (2022) . |
| APA | Zhao, Wandi , Gao, Yang , Wang, Mingjin . Measuring liquidity with return volatility: An analytical approach based on heavy-tailed Censored-GARCH model . | NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE , 2022 , 62 . |
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Abstract ：
To avoid the effects of systemic financial risks caused by extreme fluctuations in housing price, the Chinese government has been exploring the most effective policies for regulating the housing market. Measuring the effect of real estate regulation policies has been a challenge for present studies. This study innovatively employs big data technology to obtain Internet search data (ISD) and construct market concern index (MCI) of policy, and hedonic price theory to construct hedonic price index (HPI) based on building area, age, ring number, and other hedonic variables. Then, the impact of market concerns for restrictive policy, monetary policy, fiscal policy, security policy, and administrative supervision policy on housing prices is evaluated. Moreover, compared with the common housing price index, the hedonic price index considers the heterogeneity of houses and could better reflect the changes in housing prices caused by market supply and demand. The results indicate that (1) a long-term interaction relationship exists between housing prices and market concerns for policy (MCP); (2) market concerns for restrictive policy and administrative supervision policy effectively restrain rising housing prices while those for monetary and fiscal policy have the opposite effect. The results could serve as a useful reference for governments aiming to stabilize their real estate markets.
Keyword ：
housing prices housing prices hedonic price hedonic price Real estate policy Real estate policy market concerns for policy market concerns for policy Internet search data Internet search data
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| GB/T 7714 | Zhou, Wenwen , Chen, Mengyao , Gao, Yang et al. Research on the Impact of Market Concern for Real Estate Policy on Housing Prices: Evidence from Internet Search and Hedonic Price Theory [J]. | CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES , 2022 , 131 (3) : 1635-1652 . |
| MLA | Zhou, Wenwen et al. "Research on the Impact of Market Concern for Real Estate Policy on Housing Prices: Evidence from Internet Search and Hedonic Price Theory" . | CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES 131 . 3 (2022) : 1635-1652 . |
| APA | Zhou, Wenwen , Chen, Mengyao , Gao, Yang , Feng, Ruilin . Research on the Impact of Market Concern for Real Estate Policy on Housing Prices: Evidence from Internet Search and Hedonic Price Theory . | CMES-COMPUTER MODELING IN ENGINEERING & SCIENCES , 2022 , 131 (3) , 1635-1652 . |
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Abstract ：
Purpose This paper aims to explore the interaction between investor attention and green security markets, including green bonds and stocks. Design/methodology/approach This study takes the Baidu index of "green finance" as the proxy for investor attention and constructs several generalized prediction error variance decomposition models to investigate the interdependence. It further analyzes the dynamic interaction between investor attention and the return and volatility of green security markets using the rolling time window. Findings The empirical analysis and robustness test results reveal that the spillovers between investor attention and the return and volatility of the green bond market are relatively stable. In contrast, the spillover level between investor attention and the green stock market displays significant time-varying and asymmetric effects. Moreover, the volatility spillover between investor attention and green securities is vulnerable to major financial events, while the return spillover is extremely sensitive to market performance. Originality/value The conclusion further expands the practical application and theoretical framework of behavioral finance in green finance and provides a new reference for investors and regulators. Besides, this study also lays a theoretical basis for investors to focus on the practical application of volatility prediction and risk management in green securities.
Keyword ：
Green stock Green stock Interaction effect Interaction effect Investor attention Investor attention Green bond Green bond Generalized forecast error variance decomposition Generalized forecast error variance decomposition
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| GB/T 7714 | Gao, Yang , Li, Yangyang , Wang, Yaojun . The dynamic interaction between investor attention and green security market: an empirical study based on Baidu index [J]. | CHINA FINANCE REVIEW INTERNATIONAL , 2021 , 13 (1) : 79-101 . |
| MLA | Gao, Yang et al. "The dynamic interaction between investor attention and green security market: an empirical study based on Baidu index" . | CHINA FINANCE REVIEW INTERNATIONAL 13 . 1 (2021) : 79-101 . |
| APA | Gao, Yang , Li, Yangyang , Wang, Yaojun . The dynamic interaction between investor attention and green security market: an empirical study based on Baidu index . | CHINA FINANCE REVIEW INTERNATIONAL , 2021 , 13 (1) , 79-101 . |
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Abstract ：
This study investigated the dynamic return and volatility spillovers, together with the network connectedness analysis between China's green bond and main financial markets. Based on a multidimensional DCC-GJRGARCH model and the spillover index method, we found significant two-way risk spillovers between the green bond market and traditional bond markets. Moreover, the green bond market was subject to one-way risk spillover from the stock and commodities markets. Meanwhile, risk spillovers between the green bond market, forex market, and monetary market were not significant. Finally, network connectedness analysis provided specific information about connectivity and strength during different subperiods corresponding to financial events. The analysis indicated that under the influence of emergencies, China's financial market will enhance the risk-spillover level by transforming the same type of market's internal spillover into cross-market spillover.
Keyword ：
DCC-GJRGARCH model DCC-GJRGARCH model Volatility spillover Volatility spillover Network connectedness Network connectedness Green bond market Green bond market
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| GB/T 7714 | Gao, Yang , Li, Yangyang , Wang, Yaojun . Risk spillover and network connectedness analysis of China's green bond and financial markets: Evidence from financial events of 2015-2020 [J]. | NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE , 2021 , 57 . |
| MLA | Gao, Yang et al. "Risk spillover and network connectedness analysis of China's green bond and financial markets: Evidence from financial events of 2015-2020" . | NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE 57 (2021) . |
| APA | Gao, Yang , Li, Yangyang , Wang, Yaojun . Risk spillover and network connectedness analysis of China's green bond and financial markets: Evidence from financial events of 2015-2020 . | NORTH AMERICAN JOURNAL OF ECONOMICS AND FINANCE , 2021 , 57 . |
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Abstract ：
For each industry in the era of big data, a steady stream of data is generated continually. Due to the enormous information contained in big data, how to maximally extract the value from big data with lower cost to provide decision-making, guide production and resource allocation for the enterprises has attracted more and more attention of most enterprises. This paper proposes a data analysis solution in the era of big data-data factory, and implements a software system to build a data factory for an enterprise promptly and efficiently. By processing, analyzing and modeling the data in a workshop-based production mode similar to the traditional factories using raw materials, our data factory will acquire the analysis results and prediction models and then realize the clustering, classification, evaluation, and prediction data analysis. Moreover, the application of deploying data factory for an enterprise reveals that data factory is an efficient solution for big data analysis, and it improves the efficiency of enterprise data analysis. © 2020 IEEE.
Keyword ：
Big data Big data Data streams Data streams Decision making Decision making Predictive analytics Predictive analytics
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| GB/T 7714 | Wang, Yaojun , Li, Yangyang , Sui, Jingyan et al. Data Factory: An Efficient Data Analysis Solution in the Era of Big Data [C] . 2020 : 28-32 . |
| MLA | Wang, Yaojun et al. "Data Factory: An Efficient Data Analysis Solution in the Era of Big Data" . (2020) : 28-32 . |
| APA | Wang, Yaojun , Li, Yangyang , Sui, Jingyan , Gao, Yang . Data Factory: An Efficient Data Analysis Solution in the Era of Big Data . (2020) : 28-32 . |
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Abstract ：
This paper examines the liquidity dynamics around intraday price jumps in the Chinese stock index futures markets by identifying the specific intraday timing of the jumps. The contributions of the liquidity shocks and some pre-scheduled macroeconomic news announcements to intraday jumps are further explored. Three key measures, the number of trades, the open interest change, and the ratio of trading volume to open interest, are found to be the key drivers for intraday jumps. It is the largely increased trading demand, not the withdrawing of market participants, that causes price jumps. Positive jumps seem to bring more speculative trades in the futures market than negative jumps do. The pre-scheduled macro announcements fail to show their significance in driving the intraday jumps. (C) 2019 Elsevier B.V. All rights reserved.
Keyword ：
Market liquidity Market liquidity Order-driven market Order-driven market Intraday jump Intraday jump Macroeconomic announcements Macroeconomic announcements
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| GB/T 7714 | Sun, Bianxia , Gao, Yang . Market liquidity and macro announcement around intraday jumps: Evidence from Chinese stock index futures markets [J]. | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS , 2020 , 541 . |
| MLA | Sun, Bianxia et al. "Market liquidity and macro announcement around intraday jumps: Evidence from Chinese stock index futures markets" . | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS 541 (2020) . |
| APA | Sun, Bianxia , Gao, Yang . Market liquidity and macro announcement around intraday jumps: Evidence from Chinese stock index futures markets . | PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS , 2020 , 541 . |
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