*3.1. Summary Statistics*

Table 1 shows the summary statistics of the returns of the buy-and-hold strategy, *Rj*,*t*, the returns of the 20-day moving average timing strategy, - *Rj*,*t*,*L*, and the difference between the two, *MAPj*,*t*,*L*. The average return of our proposed trading strategy, *TLSMA*,*t*,*L*, and the difference between the new strategy and the traditional BM strategy, *TLSMAP*,*t*,*L*, are also reported at the bottom.

The average BM ratios for all 10 portfolios are less than one and range from 0.12 (portfolio 1) to 0.85 (portfolio 10), suggesting that the average book values of the sample stocks are smaller than their average market values in the China market. We further investigate the change of sample stocks' BM ratios over time and find that there exist stocks with BM ratios bigger than one after 2008, but the proportion is very small.

In panel A, we present the results for equally-weighted portfolios. For the decile BM portfolios, the simple average returns range from 5.51 basis points to 10.28 basis points (we use "points" to refer to basis points hereafter) and increase monotonically as a whole except for the return of portfolio 8 (9.45 points), which is slightly smaller than that of portfolio 7 (9.46 points). Seven (two) of the average returns are significant at the 5% (1%) level. The average high-minus-low return is 4.77 point with a *t*-value of 2.071, which is significant at the 5% level. This provides preliminary evidence that BM effect exists in China market. The values of the standard deviations are increasing monotonically, which indicates that portfolios with higher average returns tend to have higher standard deviations in China. The standard deviation for the high-minus-low portfolio is about half of the value of the other BM portfolios, which is consistent with the nature of a zero-cost hedging portfolio. The skewness of the portfolios is very small, with most of the values lower than 0.6.

For the 20-day moving average (MA(20)) timing portfolios, we find that the average returns of MA20 portfolios range from 10.73 to 14.40 points and there is no obvious trend in the returns. We find that the average returns of MA timing portfolios are at least double those of the buy-and-hold portfolios. However, we observe that the standard deviations are smaller than those of the BM portfolios, which demonstrates that when we apply MA(20) strategy to the BM portfolios, we receive higher returns but lower total risks, which is a promising result. We check whether these profits (higher returns) are due to risk exposure or not in our later tests.

<sup>1</sup> We report Newey and West (1987) *t*-statistics in parenthesis to adjust for the possible effects of serial correlation and heteroscedasticity.



the highest and lowest MAP, respectively. TLSMA represents the proposed technical analysis enhanced BM strategy. TLSMAP represents the difference between the prosed strategy and

the buy-and-hold strategy. Simple *t*-statistics are reported in column *t* and Newey and West (1987) *t*-statistics are reported in the parentheses.

The di fferences between MA(20) and BM portfolios, MAPs, are all positive and range from 1.77 to 5.57 points. Interestingly, we observe the special pattern that the average MAPs are generally decreasing as portfolio BM ratios increase, which indicates that the moving average technical analysis is more successful for portfolios with lower BM ratios.

For the proposed trading strategy, we can see that the average high-minus-low return of the MA(20) portfolios is very small (0.86 points) and insignificant (*t* = 0.40), much smaller than that of the BM portfolios (4.77 points). We conjecture that the small and insignificant result is caused by the misuse of the moving average timing signals. The high-minus-low return of MA(20) can be regarded as longing the highest MA(20) and shorting the lowest MA(20) portfolios. Shorting the lowest portfolio means that we will sell the assets when the last trading price *Pj*,*t*−<sup>1</sup> is higher than the last 20-day moving average indicator *Aj*,*t*−1,*L*, whose signal indicates that the price will increase. In other words, we will sell the assets that we think will grow, which is logically wrong. Therefore, we conduct our trading strategy with the correct use of the moving average indicator for the lowest BM portfolio, which we discussed in the methodology section. The *TSLMA*,*t*,*<sup>L</sup>* is 16.43 points, which is substantially higher than that of the buy-and-hold strategy (4.77 points). The average significant di fference between the two strategies (*TSLMAP*,*t*,*<sup>L</sup>*) is 11.23 points, which represents the additional profits from the new TLS strategy, which is 2.36 times the buy-and-hold strategy.

In panel B, we present the performance of the value-weighted portfolios to check the size e ffect on the result. We find that the magnitude of the portfolio average returns is only slightly bigger than the return of the corresponding equally-weighted portfolios. The simple average return of the buy-and-hold strategy ranges from 5.34 to 10.79 points, with portfolio 10 (3) getting the highest (lowest) average return. In addition, all deciles with the MA(20) strategy have higher returns than the BM portfolios, ranging from 9.76 to 13.03 points. All of the MAP returns are positive and have lower standard deviations. The daily average return of the new trading strategy, *TSLMA*,*t*,*L*, is 15.34 points (*t* = 4.50), which is 221.13% higher than the high-minus-low return of the BM portfolio (4.78 points) but lower than the corresponding equally-weighted portfolios. The di fference between MA(20) and buy-and-hold strategies, *TSLMAP*,*t*,*L*, is 9.94 points (*t* = 3.95), which is also slightly lower than that of the corresponding equally-weighted portfolios.

Overall, Table 1 shows that the value premium e ffect exists in the China stock market and that the moving average technical analysis strategy is useful in producing positive and significant excess returns. In addition, the proposed strategy, *TSLMA*,*t*,*L*, clearly outperforms the traditional buy-and-hold BM strategy.
