The risk of household financial portfolio in China: too conservative or overly aggressive?
(2.School of International Business Administration, Shanghai University of Finance and Economics)
(3.Research Institute of Economics and Management, and China Household Finance Survey, Southwestern University of Finance and Economics)
【Abstract】Using the data of China Household Finance Survey in 2011, 2013 and 2015, this study analyzes the risk of household financial portfolio. We find that, compared to the European Union and the US, the distribution of portfolio risk in China presents a “U-shape,” that is, both conservative and aggressive households take up large shares. Further analysis shows that the concentration of financial allocation towards stock is the direct reason of the bipolarization of the portfolio risk in China. The household heterogeneity in total assets, age, education, financial literacy, risk attitude and risk tolerance of the household head has not well explained this phenomenon. The supply structure and investment threshold of the financial market may also be important reasons.
【Keywords】 household finance; asset allocation; portfolio risk;
. ① The data are obtained from the National Bureau of Statistics of China. [^Back]
. ② It is calculated according to the SCF data in 2013. The SCF is a long-term sample questionnaire on the income, assets, and liabilities of US households conducted by the Federal Reserve and the University of Chicago. The survey began in 1983 and is conducted door to door every three years. The US data below are all taken from the SCF. [^Back]
. ③ It is calculated according to the CHFS data in 2015. The Chinese data below are all taken from CHFS. [^Back]
. ④ The average age of population in CHFS in 2011 was 2.09 years older than that in the 2010 national census of NBS. This may be due to the fact that the CHFS survey samples do not include business dormitories, such as the Foxconn Tech Group’s dorms for their staff, in which people are relatively young. [^Back]
. ⑤ Although the demand deposit has interest, the interest rate is very low and can be ignored. Similarly, we do not include cash and demand deposit when analyzing the risk of household financial portfolio in the following parts. [^Back]
. ⑥ The CSI Composite Index is a cross-market bond index that comprehensively reflects the overall trend of treasury bonds, financial bonds, corporate bonds, central bank bills and short-term financing bills between banks and in exchange market. The sample is constructed based on the sample of the CSI Aggregate Bond Index and added with central bank bills, short-term financing bills, and government bonds, financial bonds and corporate bonds less than one year. [^Back]
. ⑦ Since the base of the CSI Composite Index is December 31, 2002, the historical return rate for deposit-type, bond-type, and stock-type assets is calculated from 2003, and the data come from the Wind database. It is calculated that the annual return rates of China’s bonds and stocks from 2003 to 2011 were 3.30% and 11.33%, and the standard deviation were 0.0235 and 0.3071. The annual return rates of China’s bonds and stocks from 2003 to 2013 were 2.98% and 9.27%, and the standard deviation were 0.0229 and 0.2915. The annual return rates of China’s bonds and stocks were 3.83% and 12.64% from 2003 to 2015, and the standard deviation were 0.0232 and 0.2924. The covariance of bonds and stocks was about −0.001, and the correlation coefficient is between −0.14 and 0.18. It can be seen that the annual return rate of stocks is much higher than that of bonds, but the standard deviation is also greater than that of bonds. Stocks and bonds have a negative correlation. [^Back]
. ⑧ Deposit-type asset income is calculated based on one-year deposit interest rate in the US; bond-type asset income is calculated according to the US Barclays Aggregate Bond index, which is a comprehensive index covering various types of investment bonds such as treasury bills, government bonds, and corporate bonds; stock-type asset income is calculated based on the Standard & Poor’s index. The period the historical data cover is the same as Chinese data. US household deposit-type assets include savings deposits, money market deposits, certificates of deposit, savings bonds, and the part of the pension that is used for savings; bond-type assets include the directly purchased bonds, currency funds, bond funds, and the part of the pension that is invested in bonds; stock-type assets include directly purchased stocks, stock funds, and the part of the pension that is invested in stocks. [^Back]
. ⑨ The reason is that the risk of China’s stock market is far greater than that of the US stock market. The household with the highest portfolio risk is the one that puts all the money into the stock, for whom the portfolio risk value is equal to the risk value of the stock. [^Back]
. ⑩ See the Value at Risk VAR, CITIC press, 2010. [^Back]
. ⑪ The following study also analyzes the CHFS data in 2011 and 2013, and the conclusions are consistent. [^Back]
. ⑫ The sample for calculating the stock market participation rate and stock investment ratio includes 10,462 households, that is, households with financial portfolios. [^Back]
. ⑬ The portfolio risk distribution of the 60-year-old and above group is similar to those in the lowest-asset group, which will not be repeated here. [^Back]
. ⑭ The three questions about financial literacy included in the CHFS questionnaire are as follows. The first question is “assume that the annual interest rate of the bank is 4%. If CNY 100 is kept for one-year-fixed term deposit, the principal and interest obtained after one year are (1) less than CNY 104; (2) equal to CNY 104; (3) greater than CNY 104; (4) I do not know.” The second question is “assume that the annual interest rate of the bank is 5%, the inflation rate is 3% per year, if CNY 100 is saved in the bank, how much will be obtained after one year? (1) more than that a year ago; (2) As much as that a year ago; (3) less than that a year ago; (4) I do not know.” The third question is “in general, which one do you think is more risky, stock or fund? (1) stock; (2) fund; (3) never heard of stock; (4) never heard of fund; (5) never heard of both.” [^Back]
. ⑮ CHFS questionnaire includes a question on the risk attitude of the household head as follows. “If you have a sum of money for investment, what kind of investment project do you prefer? (1) projects with high risk and return; (2) projects with slightly high risk and return; (3) projects with average risk and return; (4) projects with slightly low risk and return; (5) unwilling to bear any risks.” Referring to the answers to this question, we divide the households into three types, risk-loving, risk-neutral, and risk-averse. If the household head chooses the first two options, the household is defined as a risk-loving household; if the household head chooses the third option, the household is defined as a risk-neutral household; if the household head chooses the last two options, the household is defined as a risk-averse household. [^Back]
. ⑯ The selection of the explanatory variables are based on the existing literature on factors affecting household participation in risk market, see Yoo (1994), McCathy (2004), Mankiw and Zeldes (1991),Campbell (2006), and Bertocchi et al. (2011). [^Back]
. ⑰ Household member younger than 15 is classified as kids, and household member older than 60 is classified as the elderly. [^Back]
. ⑱ According to the city classification by China Business Weekly, the first-tier cities include Beijing, Shanghai, Guangzhou and Shenzhen, four in total. The new first-tier cities include Tianjin, Chongqing, Xi’an, Nanjing, Wuhan, Chengdu, Shenyang, Dalian, Hangzhou, Ningbo, Qingdao, Jinan, Xiamen, Fuzhou and Changsha, 15 in total. The second-tier cities include Haerbin, Changchun, Daqing, Ningbo, Suzhou, Kunming, Hefei, Zhengzhou, Fushan, Nanchang, Guiyang, Nanning, Shijiazhuang, Taiyuan, Wenzhou, Yantai, Zhuhai, Changzhou, Nantong, Yangzhou, Xuzhou, Dongguan, Weihai, Huaian, Hohhot, Zhenjiang, Weifang, Zhongshan, Linyi, Xianyang, Baotou, Jiaxing, Huizhou, Quanzhou, Qinhuangdao and Luoyang, 36 in total. In this study, we classify both the new first-tier cities and the second-tier cities as the second-tier cities. [^Back]
. ⑲ The predicted value with a Tobit model may be a negative number. To be comparable, we set the negative predicted value as 0. [^Back]
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