In this study, we use Chinese A-share stock market data from 1995 to 2005 to test the persistence of the size and valueeffect and the robustness of the Fama-French three-factor model in explaining the variation in sto...In this study, we use Chinese A-share stock market data from 1995 to 2005 to test the persistence of the size and valueeffect and the robustness of the Fama-French three-factor model in explaining the variation in stock returns.Wefind that the three-factor model can explain the common variation in stock returns well.However, it is mis-specifiedfor the Chinese stock market.We demonstrate that the size effect and the book-to-market effect are significant andpersistent over our sample period.Interestingly, the book-to-market effect for China is much stronger than the averageones in mature markets and other emerging markets documented by Fama and French (1998).Moreover, we find noevidence to support the argument that seasonal effects can explain the results of the multifactor model.Last, our mixedobservations on firm-specific fundamentals suggest that the risk-based explanation proposed by Fama and French(1995) cannot shed light on the size and BM effect for China.In view of the features of the Chinese stock market, weinstead argue that China’s size and book-to-market effect may be attributed to syndicate speculators’ manipulation andmispricing caused by irrational investor behavior.展开更多
Soil respiration(Rs)is important for transport-ing or fixing carbon dioxide from the atmosphere,and even diminutive variations can profoundly influence the carbon cycle.However,the R_(s) dynamics in a loess alpine hil...Soil respiration(Rs)is important for transport-ing or fixing carbon dioxide from the atmosphere,and even diminutive variations can profoundly influence the carbon cycle.However,the R_(s) dynamics in a loess alpine hilly region with representative sensitivity to climate change and fragile ecology remains poorly understood.This study investigated the correlation and degree of control between R_(s) and its photosynthetic and environmental factors in five subalpine forest cover types.We examined the correlations between R_(s) and variables temperature(T_(10)) and soil moisture content at 10 cm depth(W_(10)),net photosynthetic rate(P_(n))and soil properties to establish multiple models,and the variables were measured for diurnal and monthly vari-ations from September 2018 to August 2019.The results showed that soil physical factors are not the main drivers of R_(s) dynamics at the diel scale;however,the trend in the monthly variation in R_(s) was consistent with that of T_(10)and P_(n).Further,R_(s) was significantly affected by pH,providing further evidence that coniferous forest leaves contribute to soil acidification,thus reducing R_(s).Significant exponential and linear correlations were established between R_(s) and T_(10)and W_(10),respectively,and R_(s) was positively correlated with P_(n).Accordingly,we established a two-factor model and a three-factor model,and the correlation coefficients(R_(2))was improved to different degrees compared with models based only on T_(10) and W_(10).Moreover,temperature sensitivity(Q_(10))was the highest in the secondary forest and lowest in the Larix principis-rupprechtii forest.Our findings suggest that the control of R_(s) by the environment(moisture and tempera-ture)and photosynthesis,which are interactive or comple-mentary effects,may influence spatial and temporal homeo-stasis in the region and showed that the models appropriately described the dynamic variation in R_(s) and the carbon cycle in different forest covers.In addition,total phosphorus(TP)and total potassium(TK)significantly affected the dynamic changes in R_(s).In summary,interannual and seasonal variations in forest R_(s) at multiple scales and the response forces of related ecophysiological factors,especially the interactive driving effects of soil temperature,soil moisture and photo-synthesis,were clarified,thus representing an important step in predicting the impact of climate change and formulating forest carbon management policies.展开更多
In this paper, we empirically test a new model with the data of US services sector, which is an extension of the 5-factor model in Fama and French (2015) [1]. 3 types of 5 factors (Global, North American and US) are c...In this paper, we empirically test a new model with the data of US services sector, which is an extension of the 5-factor model in Fama and French (2015) [1]. 3 types of 5 factors (Global, North American and US) are compared. Empirical results show the Fama-French 5 factors are still alive! The new model has better in-sample fit than the 5-factor model in Fama and French (2015).展开更多
In this paper, we analyze US stock market with a new 5-factor model in Zhou and Li (2016) [1]. Data we use are 48 industry portfolios (Jul. 1963-Jan. 2017). Parameters are estimated by MLE. LR and KS are used for mode...In this paper, we analyze US stock market with a new 5-factor model in Zhou and Li (2016) [1]. Data we use are 48 industry portfolios (Jul. 1963-Jan. 2017). Parameters are estimated by MLE. LR and KS are used for model diagnostics. Model comparison is done with AIC. The results show Fama-French 5 factors are still alive. This new model in Zhou and Li (2016) [1] fits the data better than the one in Fama and French (2015) [2].展开更多
国外动态财务分析(DFA)的投资产生器中以往都是采用CAPM对权益型资产进行定价。鉴于CAPM在中国资本市场的适用性尚存较大疑问,本文用较为精确的F am a和F rench的三因子模型对动态财务分析中的CAPM进行替代。并且利用历史数据对FF三因...国外动态财务分析(DFA)的投资产生器中以往都是采用CAPM对权益型资产进行定价。鉴于CAPM在中国资本市场的适用性尚存较大疑问,本文用较为精确的F am a和F rench的三因子模型对动态财务分析中的CAPM进行替代。并且利用历史数据对FF三因子模型的参数进行了估算,并对其解释能力进行了评估,保证了FF三因子模型可行。最后比较了FF三因子模型和CAPM在动态财务分析D ynaM o 3.0平台下的预测能力。得出在DFA下FF三因子模型的解释能力和预测准确性都强于CAPM的结论,建立了适合中国市场状况的投资产生器。展开更多
文摘In this study, we use Chinese A-share stock market data from 1995 to 2005 to test the persistence of the size and valueeffect and the robustness of the Fama-French three-factor model in explaining the variation in stock returns.Wefind that the three-factor model can explain the common variation in stock returns well.However, it is mis-specifiedfor the Chinese stock market.We demonstrate that the size effect and the book-to-market effect are significant andpersistent over our sample period.Interestingly, the book-to-market effect for China is much stronger than the averageones in mature markets and other emerging markets documented by Fama and French (1998).Moreover, we find noevidence to support the argument that seasonal effects can explain the results of the multifactor model.Last, our mixedobservations on firm-specific fundamentals suggest that the risk-based explanation proposed by Fama and French(1995) cannot shed light on the size and BM effect for China.In view of the features of the Chinese stock market, weinstead argue that China’s size and book-to-market effect may be attributed to syndicate speculators’ manipulation andmispricing caused by irrational investor behavior.
基金This work was supported financially by the National Key Research and Development Plan Projects of China(2017YFC0504604).
文摘Soil respiration(Rs)is important for transport-ing or fixing carbon dioxide from the atmosphere,and even diminutive variations can profoundly influence the carbon cycle.However,the R_(s) dynamics in a loess alpine hilly region with representative sensitivity to climate change and fragile ecology remains poorly understood.This study investigated the correlation and degree of control between R_(s) and its photosynthetic and environmental factors in five subalpine forest cover types.We examined the correlations between R_(s) and variables temperature(T_(10)) and soil moisture content at 10 cm depth(W_(10)),net photosynthetic rate(P_(n))and soil properties to establish multiple models,and the variables were measured for diurnal and monthly vari-ations from September 2018 to August 2019.The results showed that soil physical factors are not the main drivers of R_(s) dynamics at the diel scale;however,the trend in the monthly variation in R_(s) was consistent with that of T_(10)and P_(n).Further,R_(s) was significantly affected by pH,providing further evidence that coniferous forest leaves contribute to soil acidification,thus reducing R_(s).Significant exponential and linear correlations were established between R_(s) and T_(10)and W_(10),respectively,and R_(s) was positively correlated with P_(n).Accordingly,we established a two-factor model and a three-factor model,and the correlation coefficients(R_(2))was improved to different degrees compared with models based only on T_(10) and W_(10).Moreover,temperature sensitivity(Q_(10))was the highest in the secondary forest and lowest in the Larix principis-rupprechtii forest.Our findings suggest that the control of R_(s) by the environment(moisture and tempera-ture)and photosynthesis,which are interactive or comple-mentary effects,may influence spatial and temporal homeo-stasis in the region and showed that the models appropriately described the dynamic variation in R_(s) and the carbon cycle in different forest covers.In addition,total phosphorus(TP)and total potassium(TK)significantly affected the dynamic changes in R_(s).In summary,interannual and seasonal variations in forest R_(s) at multiple scales and the response forces of related ecophysiological factors,especially the interactive driving effects of soil temperature,soil moisture and photo-synthesis,were clarified,thus representing an important step in predicting the impact of climate change and formulating forest carbon management policies.
文摘In this paper, we empirically test a new model with the data of US services sector, which is an extension of the 5-factor model in Fama and French (2015) [1]. 3 types of 5 factors (Global, North American and US) are compared. Empirical results show the Fama-French 5 factors are still alive! The new model has better in-sample fit than the 5-factor model in Fama and French (2015).
文摘In this paper, we analyze US stock market with a new 5-factor model in Zhou and Li (2016) [1]. Data we use are 48 industry portfolios (Jul. 1963-Jan. 2017). Parameters are estimated by MLE. LR and KS are used for model diagnostics. Model comparison is done with AIC. The results show Fama-French 5 factors are still alive. This new model in Zhou and Li (2016) [1] fits the data better than the one in Fama and French (2015) [2].
文摘国外动态财务分析(DFA)的投资产生器中以往都是采用CAPM对权益型资产进行定价。鉴于CAPM在中国资本市场的适用性尚存较大疑问,本文用较为精确的F am a和F rench的三因子模型对动态财务分析中的CAPM进行替代。并且利用历史数据对FF三因子模型的参数进行了估算,并对其解释能力进行了评估,保证了FF三因子模型可行。最后比较了FF三因子模型和CAPM在动态财务分析D ynaM o 3.0平台下的预测能力。得出在DFA下FF三因子模型的解释能力和预测准确性都强于CAPM的结论,建立了适合中国市场状况的投资产生器。
