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 hill...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
China is the largest emerging market and attracts a great deal of attention from investors and researchers worldwide.The Fama-French three-factor model is the outcome of decades of research on US stock returns.To what...China is the largest emerging market and attracts a great deal of attention from investors and researchers worldwide.The Fama-French three-factor model is the outcome of decades of research on US stock returns.To what extent the three factors explain the variation in Chinese stock returns is an intriguing question.This paper documents empirical evidence on this issue and identifies some pitfalls that arise in the application of the three-factor model to Chinese stock returns.We find that several special features in China affect the three factors considerably and also influence the explanatory power of the three-factor model.展开更多
This paper explores the performances of some frequently used asset pricing factors and their investment implications in Chinese stock market. It is noted that CAPM model can hardly be applied to Chinese market as port...This paper explores the performances of some frequently used asset pricing factors and their investment implications in Chinese stock market. It is noted that CAPM model can hardly be applied to Chinese market as portfolios based on 13 values cannot generate high return against high risk. However, two factors （Size and B/M） from Fama-French model （1992） deliver better performances. Such findings indicate that models based on theoretical analysis are somewhat away from practice, and those risk factors from empirical studies are more applicable though not based on theories. Therefore, further researches are desirable concerning asset pricing factors.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China is the largest emerging market and attracts a great deal of attention from investors and researchers worldwide.The Fama-French three-factor model is the outcome of decades of research on US stock returns.To what extent the three factors explain the variation in Chinese stock returns is an intriguing question.This paper documents empirical evidence on this issue and identifies some pitfalls that arise in the application of the three-factor model to Chinese stock returns.We find that several special features in China affect the three factors considerably and also influence the explanatory power of the three-factor model.
文摘This paper explores the performances of some frequently used asset pricing factors and their investment implications in Chinese stock market. It is noted that CAPM model can hardly be applied to Chinese market as portfolios based on 13 values cannot generate high return against high risk. However, two factors （Size and B/M） from Fama-French model （1992） deliver better performances. Such findings indicate that models based on theoretical analysis are somewhat away from practice, and those risk factors from empirical studies are more applicable though not based on theories. Therefore, further researches are desirable concerning asset pricing factors.
