This paper analyzes the relationship between the proportion of institutional investors’ shareholding and the probability of stock manipulation using 252 cases of manipulation disclosed in public administrative penalty decision of the China Securities Regulatory Commission (CSRC) from 2007 to 2019. The empirical results show that the higher the proportion of institutional investors’ shareholding, the lower the probability of market manipulation. Further analysis shows that the effect is mainly shown in non-shortable stocks. Moreover, controlling for the endogeneity using exogenous policy shocks, the effect of institutional investors on restraining market manipulation still exists. In the end, considering the fact that the cases of market manipulation detected by the CSRC are only a part of the real cases, this paper uses Bivariate Probit model with partial observability and finds that the higher the proportion of institutional investors’ shareholding, the lower the probability of stocks being manipulated and the higher probability of being detected after manipulation.
{"title":"Can Institutional Investors Restrain Stock Market Manipulation?--Empirical Evidence From an Emerging Market","authors":"Jie Liu, Chonglin Wu, Lin Yuan","doi":"10.2139/ssrn.3614890","DOIUrl":"https://doi.org/10.2139/ssrn.3614890","url":null,"abstract":"This paper analyzes the relationship between the proportion of institutional investors’ shareholding and the probability of stock manipulation using 252 cases of manipulation disclosed in public administrative penalty decision of the China Securities Regulatory Commission (CSRC) from 2007 to 2019. The empirical results show that the higher the proportion of institutional investors’ shareholding, the lower the probability of market manipulation. Further analysis shows that the effect is mainly shown in non-shortable stocks. Moreover, controlling for the endogeneity using exogenous policy shocks, the effect of institutional investors on restraining market manipulation still exists. In the end, considering the fact that the cases of market manipulation detected by the CSRC are only a part of the real cases, this paper uses Bivariate Probit model with partial observability and finds that the higher the proportion of institutional investors’ shareholding, the lower the probability of stocks being manipulated and the higher probability of being detected after manipulation.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132731597","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}
Ellie Papavassiliou, Nikolas Topaloglou, S. Zenios
We show that GDP-linked bonds can provide diversification benefits to investors. We use a stochastic spanning methodology which makes no assumptions on the distributional characteristics of the returns of these innovative instruments and apply to test both floaters and linkers. We find that both types of GDP-linked bonds are not spanned by a benchmark set of stocks, bonds, and cash assets, thus providing a new asset class. Spanning is ruled out for a wide and reasonable range of bond design parameters. In out-of-sample testing we find significant diversification benefits for investors, with strongly statistically significant increases in Sharpe ratios in the range 0.10-0.43 for floaters and 0.05-0.17 for linkers over an optimal benchmark portfolio. The results for linkers depend on the risk premium that these instruments will trade, while floaters are less sensitive to the premium, but the benefits remain for the range of premia estimated in existing literature. Our finding are further explained by documenting the finance and macro factors that drive the performance of GDP-linked bonds, using generalized method of moments regressions.
{"title":"GDP-Linked Bonds as a New Asset Class","authors":"Ellie Papavassiliou, Nikolas Topaloglou, S. Zenios","doi":"10.2139/ssrn.3611636","DOIUrl":"https://doi.org/10.2139/ssrn.3611636","url":null,"abstract":"We show that GDP-linked bonds can provide diversification benefits to investors. We use a stochastic spanning methodology which makes no assumptions on the distributional characteristics of the returns of these innovative instruments and apply to test both floaters and linkers. We find that both types of GDP-linked bonds are not spanned by a benchmark set of stocks, bonds, and cash assets, thus providing a new asset class. Spanning is ruled out for a wide and reasonable range of bond design parameters. In out-of-sample testing we find significant diversification benefits for investors, with strongly statistically significant increases in Sharpe ratios in the range 0.10-0.43 for floaters and 0.05-0.17 for linkers over an optimal benchmark portfolio. The results for linkers depend on the risk premium that these instruments will trade, while floaters are less sensitive to the premium, but the benefits remain for the range of premia estimated in existing literature. Our finding are further explained by documenting the finance and macro factors that drive the performance of GDP-linked bonds, using generalized method of moments regressions.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130656900","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}
This paper shows that robust inference under weak identification is important to the evaluation of many influential macro asset pricing models, including (time‐varying) rare‐disaster risk models and long‐run risk models. Building on recent developments in the conditional inference literature, we provide a novel conditional specification test by simulating the critical value conditional on a sufficient statistic. This sufficient statistic can be intuitively interpreted as a measure capturing the macroeconomic information decoupled from the underlying content of asset pricing theories. Macro‐finance decoupling is an effective way to improve the power of the specification test when asset pricing theories are difficult to refute because of a severe imbalance in the information content about the key model parameters between macroeconomic moment restrictions and asset pricing cross‐equation restrictions. We apply the proposed conditional specification test to the evaluation of a time‐varying rare‐disaster risk model and the construction of robust model uncertainty sets.
{"title":"Macro-Finance Decoupling: Robust Evaluations of Macro Asset Pricing Models","authors":"Xu Cheng, W. Dou, Z. Liao","doi":"10.2139/ssrn.3609627","DOIUrl":"https://doi.org/10.2139/ssrn.3609627","url":null,"abstract":"This paper shows that robust inference under weak identification is important to the evaluation of many influential macro asset pricing models, including (time‐varying) rare‐disaster risk models and long‐run risk models. Building on recent developments in the conditional inference literature, we provide a novel conditional specification test by simulating the critical value conditional on a sufficient statistic. This sufficient statistic can be intuitively interpreted as a measure capturing the macroeconomic information decoupled from the underlying content of asset pricing theories. Macro‐finance decoupling is an effective way to improve the power of the specification test when asset pricing theories are difficult to refute because of a severe imbalance in the information content about the key model parameters between macroeconomic moment restrictions and asset pricing cross‐equation restrictions. We apply the proposed conditional specification test to the evaluation of a time‐varying rare‐disaster risk model and the construction of robust model uncertainty sets.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115645698","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}
Economic and reporting development factors affect the timing and non-timing roles of accruals, which in turn affect the correlation between accruals and operating cash flows (CFO). We show that the strength of the accrual anomaly varies predictably with the economic determinants of the accruals-CFO relation, including intangible intensity, the length of operating cycles, extreme positive and negative financial performance, the magnitude of the non-timing-related accruals, and firm-specific estimation of the accruals-CFO relation in a cross-section analysis. Next, using variations in the correlation between accruals and CFO, we explain several seemingly unrelated empirical regularities of the accrual anomaly. First, we explain the stronger accrual anomaly among profit firms, large-sized firms, firms with higher covariation between accruals and the employment growth rate, and firms with higher earnings response coefficients. Second, we explain the inverted U-shape relation between accruals and future stock returns in the recent two decades and the time-series decline of abnormal returns of the accrual anomaly. Third, we further demonstrate that the strength of the return predictability of components of accruals depends on the strength of the correlation between individual accrual components and CFO. Finally, we extend our analysis to a large class of accounting-based return predictors that are related to accruals, and still find stronger return predictability for firms with more negative correlations between the predicting variables and CFO.
{"title":"Back to Fundamentals: The Accrual–Cash Flow Correlation, the Inverted-U Pattern, and Stock Returns","authors":"Ran An, Peng-Chia Chiu, Yinglei Zhang","doi":"10.2139/ssrn.3603096","DOIUrl":"https://doi.org/10.2139/ssrn.3603096","url":null,"abstract":"Economic and reporting development factors affect the timing and non-timing roles of accruals, which in turn affect the correlation between accruals and operating cash flows (CFO). We show that the strength of the accrual anomaly varies predictably with the economic determinants of the accruals-CFO relation, including intangible intensity, the length of operating cycles, extreme positive and negative financial performance, the magnitude of the non-timing-related accruals, and firm-specific estimation of the accruals-CFO relation in a cross-section analysis. Next, using variations in the correlation between accruals and CFO, we explain several seemingly unrelated empirical regularities of the accrual anomaly. First, we explain the stronger accrual anomaly among profit firms, large-sized firms, firms with higher covariation between accruals and the employment growth rate, and firms with higher earnings response coefficients. Second, we explain the inverted U-shape relation between accruals and future stock returns in the recent two decades and the time-series decline of abnormal returns of the accrual anomaly. Third, we further demonstrate that the strength of the return predictability of components of accruals depends on the strength of the correlation between individual accrual components and CFO. Finally, we extend our analysis to a large class of accounting-based return predictors that are related to accruals, and still find stronger return predictability for firms with more negative correlations between the predicting variables and CFO.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121541645","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 propose a simulation-based strategy to estimate and empirically assess a class of asset pricing models that account for rare but severe consumption contractions that can extend over multiple periods. Our approach expands the scope of prevalent calibration studies and tackles the inherent sample selection problem associated with measuring the effect of rare disaster risk on asset prices. An analysis based on postwar U.S. and historical multi-country panel data yields estimates of investor preference parameters that are economically plausible and robust with respect to alternative specifications. The estimated model withstands tests of validity; the model-implied key financial indicators and timing premium all have reasonable magnitudes. These findings suggest that the rare disaster hypothesis can help restore the nexus between the real economy and financial markets when allowing for multi-period disaster events. Our methodological contribution is a new econometric framework for empirical asset pricing with rare disaster risk.
{"title":"Empirical Asset Pricing with Multi-Period Disaster Risk: A Simulation-Based Approach","authors":"J. Sönksen, J. Grammig","doi":"10.2139/ssrn.3377345","DOIUrl":"https://doi.org/10.2139/ssrn.3377345","url":null,"abstract":"We propose a simulation-based strategy to estimate and empirically assess a class of asset pricing models that account for rare but severe consumption contractions that can extend over multiple periods. Our approach expands the scope of prevalent calibration studies and tackles the inherent sample selection problem associated with measuring the effect of rare disaster risk on asset prices. An analysis based on postwar U.S. and historical multi-country panel data yields estimates of investor preference parameters that are economically plausible and robust with respect to alternative specifications. The estimated model withstands tests of validity; the model-implied key financial indicators and timing premium all have reasonable magnitudes. These findings suggest that the rare disaster hypothesis can help restore the nexus between the real economy and financial markets when allowing for multi-period disaster events. Our methodological contribution is a new econometric framework for empirical asset pricing with rare disaster risk.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122745373","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}
In this paper, we document vanilla interest-rate options (caps, floors and swaptions) newly introduced in China. The underlying rates are the RMB loan prime rates (LPRs), the foremost interest rates that matter to almost all businesses and households in China. They are digital with a tick size of five basis points, and the changes only occur at predetermined monthly announcement times. Although the current literature on interest-rate options is vast, these unique stylised features bring a new challenge for interest-rate option pricing. We propose a novel market model built upon the integer-valued Skellam distribution, named Skellam market model. It is simple and analytically tractable, which leads to pricing formulas in closed forms. We advocate that it is more meaningful to quote the LPR option prices in terms of the implied intensity rather than the conventional implied volatility. Our preliminary empirical work finds intensity frown implied from cap prices and intensity skew implied from swaption prices.
{"title":"Loan Prime Rate Options","authors":"Zhanyu Chen, Kai Zhang, Hongbiao Zhao","doi":"10.2139/ssrn.3605156","DOIUrl":"https://doi.org/10.2139/ssrn.3605156","url":null,"abstract":"In this paper, we document vanilla interest-rate options (caps, floors and swaptions) newly introduced in China. The underlying rates are the RMB loan prime rates (LPRs), the foremost interest rates that matter to almost all businesses and households in China. They are digital with a tick size of five basis points, and the changes only occur at predetermined monthly announcement times. Although the current literature on interest-rate options is vast, these unique stylised features bring a new challenge for interest-rate option pricing. We propose a novel market model built upon the integer-valued Skellam distribution, named Skellam market model. It is simple and analytically tractable, which leads to pricing formulas in closed forms. We advocate that it is more meaningful to quote the LPR option prices in terms of the implied intensity rather than the conventional implied volatility. Our preliminary empirical work finds intensity frown implied from cap prices and intensity skew implied from swaption prices.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130013955","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}
Pricing of capital share risks provides a novel link between macroeconomics and finance. Our paper adopts the Epstein-Zin type utility framework and the Bansal and Yaron’s (2004) long-run risk model to derive an heterogeneous asset pricing model that extends Lettau et al.’s (2019) capital share study. Our model introduce heterogeneity within the stock market and highlights the role of elevated consumption volatility of high income stockholders in capital risks. We also uncover contracting evidences as the capital share growth has strong volatility effects in the short-run and capital share variability enters systematic risks in the long-run.
资本份额风险的定价为宏观经济和金融之间提供了一种新的联系。本文采用Epstein-Zin型效用框架和Bansal and Yaron(2004)的长期风险模型，推导了一种异构资产定价模型，该模型扩展了Lettau et al.(2019)的资本份额研究。我们的模型引入了股票市场内部的异质性，并强调了高收入股东的消费波动性在资本风险中的作用。资本份额增长在短期内具有较强的波动效应，而资本份额变异性在长期内进入系统性风险。
{"title":"Capital Share, Consumption Volatility and Long-run Redistribution Risks","authors":"Xiaoyu Zong","doi":"10.2139/ssrn.3649112","DOIUrl":"https://doi.org/10.2139/ssrn.3649112","url":null,"abstract":"Pricing of capital share risks provides a novel link between macroeconomics and finance. Our paper adopts the Epstein-Zin type utility framework and the Bansal and Yaron’s (2004) long-run risk model to derive an heterogeneous asset pricing model that extends Lettau et al.’s (2019) capital share study. Our model introduce heterogeneity within the stock market and highlights the role of elevated consumption volatility of high income stockholders in capital risks. We also uncover contracting evidences as the capital share growth has strong volatility effects in the short-run and capital share variability enters systematic risks in the long-run.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114746509","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}
A market recovery model, defined as a jump-diffusion model for the asset price where the jumps and the diffusion are not independent, is proposed. In this model a jump will be triggered when there is an unusually large downward movement over a certain time interval, and the jump size is correlated to this downward drop. We show that the market data supports such a model and parameter estimates based on market data is discussed. An explicit formula for the risk-neutral drift will be presented so that the option prices based on this model can be computed through Monte-Carlo simulation of the asset price. The characteristic function for the asset price is derived, through which the option prices can be computed by numerical integration. The volatility of asset classes in this model, defined by the variance swap (VIX) equation, is analyzed. A sensitivity study of the volatility with respect to jump parameters is performed. Results are compared to other well-known jump models.
{"title":"A Jump-Diffusion Process for Asset Price with Non-Independent Jumps","authors":"Yihren Wu, Majnu John","doi":"10.2139/ssrn.3089996","DOIUrl":"https://doi.org/10.2139/ssrn.3089996","url":null,"abstract":"A market recovery model, defined as a jump-diffusion model for the asset price where the jumps and the diffusion are not independent, is proposed. In this model a jump will be triggered when there is an unusually large downward movement over a certain time interval, and the jump size is correlated to this downward drop. We show that the market data supports such a model and parameter estimates based on market data is discussed. An explicit formula for the risk-neutral drift will be presented so that the option prices based on this model can be computed through Monte-Carlo simulation of the asset price. The characteristic function for the asset price is derived, through which the option prices can be computed by numerical integration. The volatility of asset classes in this model, defined by the variance swap (VIX) equation, is analyzed. A sensitivity study of the volatility with respect to jump parameters is performed. Results are compared to other well-known jump models.<br>","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130069987","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}
This study combines model-free conditional estimators for the risk-neutral and the physical distribution of equity returns to obtain daily measures for the pricing kernel at the monthly time horizon. Despite their time-varying nature, our pricing kernels are non-parametric, forward-looking, agnostic about preferences, economic state variables or their dynamics and rely only on minimal technical constraints. Still, our realized pricing kernel estimates are clearly linked to economic state variables like the term spread, the credit spread or liquidity. We decompose the expected variance of the log pricing kernel and find that jumps contribute a considerable portion to overall pricing kernel risk. Building on statistical tests, we confirm an U-shape in the pricing kernel at all times and find a strong link between variations in its magnitude and the variance risk premium. A central hump in the pricing kernel can be confirmed unconditionally, but appears to fade during crisis times.
{"title":"Characteristics of Model-Free Pricing Kernels","authors":"Maxim Ulrich, Simon Walther","doi":"10.2139/ssrn.3733838","DOIUrl":"https://doi.org/10.2139/ssrn.3733838","url":null,"abstract":"This study combines model-free conditional estimators for the risk-neutral and the physical distribution of equity returns to obtain daily measures for the pricing kernel at the monthly time horizon. Despite their time-varying nature, our pricing kernels are non-parametric, forward-looking, agnostic about preferences, economic state variables or their dynamics and rely only on minimal technical constraints. Still, our realized pricing kernel estimates are clearly linked to economic state variables like the term spread, the credit spread or liquidity. We decompose the expected variance of the log pricing kernel and find that jumps contribute a considerable portion to overall pricing kernel risk. Building on statistical tests, we confirm an U-shape in the pricing kernel at all times and find a strong link between variations in its magnitude and the variance risk premium. A central hump in the pricing kernel can be confirmed unconditionally, but appears to fade during crisis times.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126947696","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 consider the performance of cryptocurrencies in the light of fundamental asset pricing and portfolio theory. We observe how a traditional focus on reducing asset return volatility with Markowitz diversification actually misses the significance of such volatility for growth. The recognition that asset growth is more likely subject to exponential or continuously-compounding growth characteristics reveals that asset volatility can be exploited both across assets and across investment periods to deliver superior returns.
{"title":"Investment in Cryptocurrencies: A Perspective from Asset Pricing and Portfolio Theory","authors":"M. Dempsey, Huy Nguyen Anh Pham, V. Ramiah","doi":"10.2139/ssrn.3783764","DOIUrl":"https://doi.org/10.2139/ssrn.3783764","url":null,"abstract":"We consider the performance of cryptocurrencies in the light of fundamental asset pricing and portfolio theory. We observe how a traditional focus on reducing asset return volatility with Markowitz diversification actually misses the significance of such volatility for growth. The recognition that asset growth is more likely subject to exponential or continuously-compounding growth characteristics reveals that asset volatility can be exploited both across assets and across investment periods to deliver superior returns.","PeriodicalId":209192,"journal":{"name":"ERN: Asset Pricing Models (Topic)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2020-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133485537","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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