Profitability in Asset Pricing Models for Chinese Equities 1996-2016

I follow Novy Marx (2011, 2013) to investigate and compare firms’ gross profit, operating leverage as predictors of returns for a cross-section of traded Chinese equities spanning from1996-2016. I use portfolio tests and Fama-MacBeth regressions, find that gross-profit-to-market-capitalization ratios significantly predict returns on sampled stocks. I also find that sorting portfolios by gross profitability and size outperforms in the Chinese market. Hence, I create a Market-Profitability-Size model that captures profitability and size premium among returns of sampled stocks. Based on Gibbons-Ross-Shanken test and economic value, I demonstrate that my enhanced model outperforms Fama-French multiple-factor model in isolating influences on equity returns.

Hence, finding a new factor which is closely related to the value factor, and can explain cross-sections of stock returns better is the motivation of this paper.
In this study I have focused on Novy-Marx (2011), who uses real option theory to prove that operating leverage generates a value premium generally, and suggests that operating leverage plays important roles in generating the cross-sectional variation of expected returns (see e.g., Carlson et al., 2004;Kisser, 2014).
Also, Novy-Marx (2013) shows that gross profitability is the other side of the value. Ball et al. (2015) reveals that profitability earns a high positive premium and helps to capture most asset-pricing anomalies that plague the Fama-French (1993) three-factor model.
These studies show that operating leverage and profitability exert power in predicting returns, meanwhile, they can replace value factor among US equities, but scant literature investigates Chinese equities.
First,  finds operating leverage effect in China (2003China ( -2013, I will continue to research operating leverage effects by expanding timeline samples. Second, Liu (2017),  find that gross profitability is a statistically significant predictor of Chinese equity returns. These studies, however, merely test the factor effects in China, and do not add the new factor into asset-pricing model on Chinese equities. My study resolves this deficiency in the earlier literature section. I characterize the firms' characteristics comprehensively using gross profit, operating leverage to assure robustness in predicting equity returns. I confirm that gross-profit-to-market capitalization is a superior proxy for predicting equity returns. My results endorse those of Novy-Marx (2011, 2013 and support existence of operating leverage and gross profitability premium for Chinese equities. In addition, I mirror Fama-French three-factor (1993) and five-factor models (2015a), delete the redundant factor, and create a new Market-Profitability-Size (MKT-RMW-SMB) model to explain expected returns on Chinese equities, which is more appropriate than the Fama-French three-factor model. This paper proceeds follows. Section 2 describes our data and variable. Section 3 presents methods and empirical results. Section 4 concludes.

Data and Variable
Financial statement data are from the FactSet database (Note 1). Empirical research covers Chinese equities listed on shanghai A share and Shenzhen A share (SSE and SZSE) that have usable data during 1996-2016 (240 months). Financial firms are excluded for their distinctive high-leverage/low-equity capital structures. Our samples cover 281 companies in 1996, and, adjusted yearly, reaching 2,258 in 2016.
To construct factors that might influence equity returns, we assemble annual financial statement data for sales (SALE), cost of goods sold (COGS), sales-general-administrative expenses (SGA), book value of total assets (AT), and book equity (BE) measured as AT minus total liabilities (LT). LOG (ME) (GP) is SALE minus COGS. Operating costs (OL) is SALE plus COGS. Based on Novy-Marx (2011, 2013, I define operating leverage as operating costs divided by market capitalization, gross profitability as gross profit divided by market capitalization.

Fama-MacBeth Univariate Regressions
I use monthly Fama and MacBeth (1973) cross-sectional regressions to examine whether profitability convincingly forecasts stock returns.  Table 1 shows regressed monthly returns of individual stocks on lagged operating leverage, profitability, market capitalization, the book-to-market ratio. I focus on t-values to compare the explanatory power of variables. Gross profitability and operating leverage have significantly predicted power, while size (log(ME)), book-to-market ratio (B/M) have no significant predicting power. Gross profitability has the most power, with a test-statistic of 3.24.    (4) shows that when controlled operating leverage, gross profitability still shows strongest effect, with a test-statistic of 4.14. However, operating leverage loses much of its power to predict returns. Based on Novy-Marx's (2013) explanation, the operating leverage on its power is absorbed by profitability. Hence, I abandon operating leverage as an investigative variable.

Fama-MacBeth Multivariate Regression
Overall, I reconfirm the existence of strong gross profitability effects among Chinese equities per . Size premium still have power. However, Due to the speculative nature of the Chinese capital markets and low quality in the accounting information, the value factor shows no effect on returns of sampled equities, consistent with prior study.

Construction of Mimicking Factors
I perform portfolio tests as a more predictive exercise that escapes biased results of Fama and MacBeth (1973)     Panel B shows average excess returns for 25 value-weighted (VW) portfolios from independent (5x5 Size-GP sorting). The "R-W" profitability spread portfolio is computed as long the most robust profitability decile and short the weakest decile. The "S-B" profitability spread portfolio is computed as In the Size-GP formulation, holding GP roughly constant, average return typically falls as size increases. The S-B portfolios (size premium) in column 1, 2, 3 are significant. Holding size roughly constant, average return typically increases with GP, R-W portfolios (gross profitability premium) in row 2, 3, 4, 5 are significant. Small size and robust profitability portfolio performs best with 2.16% monthly returns. The finding reveals GP quintiles outperform size quintiles  Overall, I confirm that controlling GP improves performance of size strategies and controlling for size improves performance of profitability strategies. Results in Table 3 suggest sorting of gross profitability and size portfolios outperform among the sampled equities.

Summary of Factor Model
Following Fama-French (1993, 2015a, to construct factor, I sort independently to assign stocks to two size groups, three B/M groups, and three profitability groups (GP). The size breakpoint is a median market cap. B/M or GP breakpoints are the 30th and 70th percentiles. MKT (Rm-Rf) is the value-weighted return on the market portfolio of all sampled stocks minus the risk-free rate. SMB is the return on a diversified portfolio of small-cap stocks minus the return on a diversified portfolio of big-cap stocks. HML is the difference between returns on diversified portfolios of high and low B/M stocks. In addition, RMW is the difference between returns on diversified portfolios of stocks with robust and weak gross profitability.
First, analyzing the correlation among the factor premium. That is MKT (market premium), SMB (size premium), HML (value premium) and RMW (profitability premium).     Table 6 reports results from the Gibbons-Ross-Shaken test (Gibbons et al., 1989). Comprehensively, the GRS P value indicates statistical significance. The bigger the P value, the greater the model

Conclusion
McLean and Pontiff (2016) argue that some stock market anomalies are less anomalous after being published. Repeatedly cited size and value factors naturally are less anomalous over time which also impels me to seek new effective factors and new-factor models.
The conclusions are as follows.
Gross-profit-to-market-capitalization explains the sampled cross-section of expected returns better than other variables on Chinese equities. Value premium for the sampled equities sheds predictive power over time and becomes redundant. Operating leverage premium loses powers when adding to profitability factor. Size premium remains strong among our sampled equities. Hence, I create a new MKT-RMW-SMB factor model and investigate the applicability of a Fama-French three factor model on my sampled equities. Tests reveal that the model featuring gross profitability outperforms the Fama-French three factor model.