‘Interconnectedness’ was considered to be a cause of the 2008 financial crisis, stimulating a number of studies into the topology of financial markets. Yet the analysis of instability within networks has tended to focus on a type of ‘contagion’ which imagines serial insolvencies, with non-performance of due obligations causing solvency issues for connected institutions. A more realistic assessment of the 2008 crisis was that it was due to a drying-up of available cash. A taxonomy of contagion is proposed, and the illiquidity model of contagion is then analyzed with reference to the observed core-periphery structure of financial market networks. Finally, the post-crisis reforms are judged against the view of ‘interconnectedness’ which emerges.
{"title":"Untying Interconnectedness: Topology, Stability and the Post-crisis Reforms","authors":"Dermot Turing","doi":"10.2139/ssrn.3565870","DOIUrl":"https://doi.org/10.2139/ssrn.3565870","url":null,"abstract":"‘Interconnectedness’ was considered to be a cause of the 2008 financial crisis, stimulating a number of studies into the topology of financial markets. Yet the analysis of instability within networks has tended to focus on a type of ‘contagion’ which imagines serial insolvencies, with non-performance of due obligations causing solvency issues for connected institutions. A more realistic assessment of the 2008 crisis was that it was due to a drying-up of available cash. A taxonomy of contagion is proposed, and the illiquidity model of contagion is then analyzed with reference to the observed core-periphery structure of financial market networks. Finally, the post-crisis reforms are judged against the view of ‘interconnectedness’ which emerges.<br>","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128617012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Heikki Lehkonen, Kari Heimonen, Kuntara Pukthuanthong
Using several million news and social media articles related to currencies, we examine the role of media tone in predicting the exchange rate returns of 12 developed and 24 emerging markets from 1998 to 2016. The text-based currency Media tone is a strong positive predictor of currency excess returns beyond fundamentals of one to three months ahead and six months cumulatively, with the average in-sample and out-of-sample R^2s of 4.45% and 9.03% in the US. The one-month predictability is observed in four other developed markets and 18 emerging market currencies, with the latter showing a stronger pattern. This predictability encompasses previous month currency returns, currency factors, macro fundamentals, and market sentiment and is stronger for currencies that are freely floating, less liquid, difficult to value, costly to arbitrage, and which have high interest rates. The effect is channeled through expectation errors and driven by the forecasting component rather than risk. The predictability of Media tone is driven by non-mainstream financial media.
{"title":"Media Tone Goes Viral: Global Evidence from the Currency Market","authors":"Heikki Lehkonen, Kari Heimonen, Kuntara Pukthuanthong","doi":"10.2139/ssrn.3560587","DOIUrl":"https://doi.org/10.2139/ssrn.3560587","url":null,"abstract":"Using several million news and social media articles related to currencies, we examine the role of media tone in predicting the exchange rate returns of 12 developed and 24 emerging markets from 1998 to 2016. The text-based currency Media tone is a strong positive predictor of currency excess returns beyond fundamentals of one to three months ahead and six months cumulatively, with the average in-sample and out-of-sample R^2s of 4.45% and 9.03% in the US. The one-month predictability is observed in four other developed markets and 18 emerging market currencies, with the latter showing a stronger pattern. This predictability encompasses previous month currency returns, currency factors, macro fundamentals, and market sentiment and is stronger for currencies that are freely floating, less liquid, difficult to value, costly to arbitrage, and which have high interest rates. The effect is channeled through expectation errors and driven by the forecasting component rather than risk. The predictability of Media tone is driven by non-mainstream financial media.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116881498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
I look at the cryptocurrency market through the prism of standard multi-factor asset-pricing models with particular attention to the downside market risk. The analysis for 1,700 coins reveals that there is a significant heterogeneity in the exposure to the downside market risk, and that a higher downside risk exposure is associated with higher average returns. The extra downside risk is priced with a statistically significant premium in cross-sectional regressions. Adding the downside risk component to the CAPM and the 3-factor model for cryptocurrencies improves the explanatory power of the models significantly. The downside risk is orthogonal to the size and momentum risks and constitutes an important forth component in the multi-factor cryptocurrency pricing model.
{"title":"Is Downside Risk Priced in Cryptocurrency Market","authors":"V. Dobrynskaya","doi":"10.2139/ssrn.3623359","DOIUrl":"https://doi.org/10.2139/ssrn.3623359","url":null,"abstract":"I look at the cryptocurrency market through the prism of standard multi-factor asset-pricing models with particular attention to the downside market risk. The analysis for 1,700 coins reveals that there is a significant heterogeneity in the exposure to the downside market risk, and that a higher downside risk exposure is associated with higher average returns. The extra downside risk is priced with a statistically significant premium in cross-sectional regressions. Adding the downside risk component to the CAPM and the 3-factor model for cryptocurrencies improves the explanatory power of the models significantly. The downside risk is orthogonal to the size and momentum risks and constitutes an important forth component in the multi-factor cryptocurrency pricing model.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122047532","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The financial crisis of 2008-2009 demonstrated the need for a comprehensive approach to risk management of financial institutions and financial area as a whole. Since then, a large number of macroprudential policy studies are published each year. In this paper we provide an overview of the main findings of 19 research papers in 2019. This allows us to draw conclusions about the main directions of current studies and to outline directions for future research.
{"title":"Macroprudential Policy Research in 2019: Working Papers Review","authors":"M. Sakovich","doi":"10.2139/ssrn.3776606","DOIUrl":"https://doi.org/10.2139/ssrn.3776606","url":null,"abstract":"The financial crisis of 2008-2009 demonstrated the need for a comprehensive approach to risk management of financial institutions and financial area as a whole. Since then, a large number of macroprudential policy studies are published each year. In this paper we provide an overview of the main findings of 19 research papers in 2019. This allows us to draw conclusions about the main directions of current studies and to outline directions for future research.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130438971","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Canada was lauded for surviving the 2007-08 global financial crisis relatively unscathed. In part, this was due to the success of our financial services sector. This resilience, especially in contrast to the US banking sector, is partly explained by the smaller size of the non-bank financial intermediation (NBFI) sector in Canada – more popularly known as “shadow banking.” But signs of robust growth in Canada’s NBFI sector after the crisis suggest this resilience might be under threat. The assets of those institutions engaged in non-bank financial intermediation have continued to grow in Canada since the global financial crisis, and now account for a larger share of total financial assets than prior to the crisis. A more important NBFI sector has multiple effects on the financial system and on the economy. On the one hand, intermediaries in the sector, or NBFIs, provide alternatives for both depositors and borrowers that improve the functioning of the economy by increasing competition. On the other hand, they also might increase vulnerabilities, since they are often not as closely regulated, and deposit insurance does not cover their liabilities. We find that, as NBFI deposit growth increases in importance, it can dilute the effectiveness of monetary policy. This drag might be the result of depositors shifting between NBFIs and traditional banks, an effect that is exacerbated as the NBFI sector grows. We also find that contractionary monetary policy causes an increase in business credit growth for NBFIs and a fall in chartered bank business loan growth. Although the overall effect on business credit growth is the desired decrease, the increase in NBFI business loans both decreases monetary policy effectiveness and results in a riskier composition. Lastly, we find the insignificant effect on overall mortgage credit growth following a contractionary monetary policy shock appears to be driven by a shift of credit from traditional banks to NBFIs, and could be a concern from a financial stability perspective. Overall, these results highlight the importance of a growing NBFI sector for monetary policy and financial stability. Our findings suggest that both the traditional monetary policy tool of the overnight rate and tightening mortgage underwriting standards through macroprudential policy might have the unintended side effect of increasing financial instability. One way to reduce this potential side effect is to limit the migration of loans between traditional banks and NBFIs by tightening regulation of NBFIs to level the playing field between the two types of financial institutions. At a minimum, the systemically important NBFIs should face capital requirements and underwriting standards similar to those imposed on traditional banks. We hope these results help the Bank of Canada as it continues to evaluate and model the evolution of monetary policy transmission in the Canadian economy. To that end, NBFIs should be front and centre when the four coor
{"title":"Water in the Wine? Monetary Policy and the Impact of Non-bank Financial Intermediaries","authors":"Jeremy M. Kronick, Yan Wendy Wu","doi":"10.2139/ssrn.3534297","DOIUrl":"https://doi.org/10.2139/ssrn.3534297","url":null,"abstract":"Canada was lauded for surviving the 2007-08 global financial crisis relatively unscathed. In part, this was due to the success of our financial services sector. This resilience, especially in contrast to the US banking sector, is partly explained by the smaller size of the non-bank financial intermediation (NBFI) sector in Canada – more popularly known as “shadow banking.” But signs of robust growth in Canada’s NBFI sector after the crisis suggest this resilience might be under threat. The assets of those institutions engaged in non-bank financial intermediation have continued to grow in Canada since the global financial crisis, and now account for a larger share of total financial assets than prior to the crisis. A more important NBFI sector has multiple effects on the financial system and on the economy. On the one hand, intermediaries in the sector, or NBFIs, provide alternatives for both depositors and borrowers that improve the functioning of the economy by increasing competition. On the other hand, they also might increase vulnerabilities, since they are often not as closely regulated, and deposit insurance does not cover their liabilities. We find that, as NBFI deposit growth increases in importance, it can dilute the effectiveness of monetary policy. This drag might be the result of depositors shifting between NBFIs and traditional banks, an effect that is exacerbated as the NBFI sector grows. We also find that contractionary monetary policy causes an increase in business credit growth for NBFIs and a fall in chartered bank business loan growth. Although the overall effect on business credit growth is the desired decrease, the increase in NBFI business loans both decreases monetary policy effectiveness and results in a riskier composition. Lastly, we find the insignificant effect on overall mortgage credit growth following a contractionary monetary policy shock appears to be driven by a shift of credit from traditional banks to NBFIs, and could be a concern from a financial stability perspective. Overall, these results highlight the importance of a growing NBFI sector for monetary policy and financial stability. Our findings suggest that both the traditional monetary policy tool of the overnight rate and tightening mortgage underwriting standards through macroprudential policy might have the unintended side effect of increasing financial instability. One way to reduce this potential side effect is to limit the migration of loans between traditional banks and NBFIs by tightening regulation of NBFIs to level the playing field between the two types of financial institutions. At a minimum, the systemically important NBFIs should face capital requirements and underwriting standards similar to those imposed on traditional banks. We hope these results help the Bank of Canada as it continues to evaluate and model the evolution of monetary policy transmission in the Canadian economy. To that end, NBFIs should be front and centre when the four coor","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-02-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128206476","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
By employing the bootstrap full-sample Granger causality test and sub-sample rolling window causality test, this paper attempts to disentangle the causal nexus between financial instability and monetary policy uncertainty in the US, Japan, and Greece. The bootstrap full sample causality test reveals that there is unidirectional causality from monetary policy uncertainty to financial instability in the US, while there exists the reverse channel in Japan and Greece. Nonparametric Granger causality test further demonstrates that there is no causal relationship in each country, indicating the potential time-varying relationship between two variables. To allow the dynamic relationship between them, we use the bootstrap sub-sample rolling window Granger causality test and conclude that there are bidirectional causal relationships between financial instability and monetary policy uncertainty in specific subperiods for all three countries, such as during regional and global crisis. Overall, this paper helps us better understand the intricate mechanisms between financial instability and monetary policy uncertainty from the predictive perspective.
{"title":"The Causality between Financial Instability and Monetary Policy Uncertainty: Who Predicts Whom?","authors":"Meng Yan","doi":"10.2139/ssrn.3523400","DOIUrl":"https://doi.org/10.2139/ssrn.3523400","url":null,"abstract":"By employing the bootstrap full-sample Granger causality test and sub-sample rolling window causality test, this paper attempts to disentangle the causal nexus between financial instability and monetary policy uncertainty in the US, Japan, and Greece. The bootstrap full sample causality test reveals that there is unidirectional causality from monetary policy uncertainty to financial instability in the US, while there exists the reverse channel in Japan and Greece. Nonparametric Granger causality test further demonstrates that there is no causal relationship in each country, indicating the potential time-varying relationship between two variables. To allow the dynamic relationship between them, we use the bootstrap sub-sample rolling window Granger causality test and conclude that there are bidirectional causal relationships between financial instability and monetary policy uncertainty in specific subperiods for all three countries, such as during regional and global crisis. Overall, this paper helps us better understand the intricate mechanisms between financial instability and monetary policy uncertainty from the predictive perspective.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126066814","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Klenio Barbosa, Dakshina G. De Silva, Liyu Yang, Hisayuki Yoshimoto
This paper documents the existence of primary dealers' losses in Treasury bond markets and investigates how these losses affect dealers' market value. Using a novel data set that tracks more than 2,350 primary-to-secondary transactions, we find that bond losses for primary dealers are prevalent and were severe during the financial crisis. Our results indicate that liquidity constraints are a major source of bond losses observed in primary-to-secondary trades. We also find that financial sector value is correlated with these losses. Using an alternating market experiment, we show that bond losses are higher under discriminatory auctions as compared to uniform auctions.
{"title":"Bond Losses and Systemic Risk","authors":"Klenio Barbosa, Dakshina G. De Silva, Liyu Yang, Hisayuki Yoshimoto","doi":"10.2139/ssrn.3512531","DOIUrl":"https://doi.org/10.2139/ssrn.3512531","url":null,"abstract":"This paper documents the existence of primary dealers' losses in Treasury bond markets and investigates how these losses affect dealers' market value. Using a novel data set that tracks more than 2,350 primary-to-secondary transactions, we find that bond losses for primary dealers are prevalent and were severe during the financial crisis. Our results indicate that liquidity constraints are a major source of bond losses observed in primary-to-secondary trades. We also find that financial sector value is correlated with these losses. Using an alternating market experiment, we show that bond losses are higher under discriminatory auctions as compared to uniform auctions.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134432974","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Over the period 1980–2012, large U.S. commercial banks raise and retain less equity during credit expansions, which amplifies their leverage. The decrease in equity issuance is large relative to subsequent banking losses. I consider a variety of explanations for why banks resist raising equity and find evidence consistent with the diminishment of creditor market discipline due to government guarantees. I test this explanation by analyzing the removal of government guarantees to German Landesbank creditors and find that creditor market discipline and equity issuance increase. These findings help explain why banks resist raising equity, making financial distress more likely. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.
{"title":"Countercyclical Bank Equity Issuance","authors":"Matthew Baron","doi":"10.2139/SSRN.2902505","DOIUrl":"https://doi.org/10.2139/SSRN.2902505","url":null,"abstract":"\u0000 Over the period 1980–2012, large U.S. commercial banks raise and retain less equity during credit expansions, which amplifies their leverage. The decrease in equity issuance is large relative to subsequent banking losses. I consider a variety of explanations for why banks resist raising equity and find evidence consistent with the diminishment of creditor market discipline due to government guarantees. I test this explanation by analyzing the removal of government guarantees to German Landesbank creditors and find that creditor market discipline and equity issuance increase. These findings help explain why banks resist raising equity, making financial distress more likely.\u0000 Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129199255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
We create and test two novel network-based measures of interconnectedness in the financial industry during 1996 to 2013. A network based on informed trading in financial firms predicts firm-specific risk and performance, while one formed on financial firm returns predicts future macroeconomic risk. The measure of informed trading is robust to variable order arrival rates more common in modern algorithmic trading. A trading strategy based on informed trading network centrality in the financial sector delivers an annualized risk-adjusted return of 7.73%. This risk-adjusted return shows that the network centrality has an economic impact that is relevant beyond the statistical results of the paper.
{"title":"Information Networks in the Financial Sector and Systemic Risk","authors":"Paul Borochin, Stephen Rush","doi":"10.2139/ssrn.3516784","DOIUrl":"https://doi.org/10.2139/ssrn.3516784","url":null,"abstract":"We create and test two novel network-based measures of interconnectedness in the financial industry during 1996 to 2013. A network based on informed trading in financial firms predicts firm-specific risk and performance, while one formed on financial firm returns predicts future macroeconomic risk. The measure of informed trading is robust to variable order arrival rates more common in modern algorithmic trading. A trading strategy based on informed trading network centrality in the financial sector delivers an annualized risk-adjusted return of 7.73%. This risk-adjusted return shows that the network centrality has an economic impact that is relevant beyond the statistical results of the paper.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"19 4","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114033037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
C. Gouriéroux, A. Monfort, Sarah Mouabbi, Jean-Paul Renne
We define a disastrous default as the default of a systemic entity. Such an event is expected to have a negative effect on the economy and to be contagious. Bringing macroeconomic structure to a no-arbitrage asset-pricing framework, we exploit prices of disaster-exposed assets (credit and equity derivatives) to extract information on (i) the expected influence of a disastrous default on consumption and (ii) the probability of a financial meltdown. Using European data, we find that the returns of disaster-exposed assets are consistent with a systemic default being followed by a 2% decrease in consumption. The recessionary influence of disastrous defaults implies that financial instruments whose payoffs are exposed to such credit events carry substantial risk premiums. We also produce systemic risk indicators based on the probability of observing a certain number of systemic defaults or a sharp drop of consumption.
{"title":"Disastrous Defaults","authors":"C. Gouriéroux, A. Monfort, Sarah Mouabbi, Jean-Paul Renne","doi":"10.2139/ssrn.3188085","DOIUrl":"https://doi.org/10.2139/ssrn.3188085","url":null,"abstract":"\u0000 We define a disastrous default as the default of a systemic entity. Such an event is expected to have a negative effect on the economy and to be contagious. Bringing macroeconomic structure to a no-arbitrage asset-pricing framework, we exploit prices of disaster-exposed assets (credit and equity derivatives) to extract information on (i) the expected influence of a disastrous default on consumption and (ii) the probability of a financial meltdown. Using European data, we find that the returns of disaster-exposed assets are consistent with a systemic default being followed by a 2% decrease in consumption. The recessionary influence of disastrous defaults implies that financial instruments whose payoffs are exposed to such credit events carry substantial risk premiums. We also produce systemic risk indicators based on the probability of observing a certain number of systemic defaults or a sharp drop of consumption.","PeriodicalId":123550,"journal":{"name":"Financial Crises eJournal","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-01-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134274648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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