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Raymond YUEN
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YUEN is a finance professional with over 20 years practical experience in financial accounting, financial management and investment. He is a freelance trainer and grader. He also holds a PhD(Management) with research interest in market crash and Fractal Theory. He served Qualification Program of... More
  • Growth Quality Analysis 0 comments
    Mar 18, 2013 10:30 AM

    Growth Quality Analysis

    YUEN Wai Pong Raymond

    18 March 2013

    Abstract

    Securities and Exchange Commission of the United States had announced that a data-driven analytical model will be used to check the earnings quality of companies listed in the USA. The model employed is a mutant of the Modified Jones Model. As there are a trove of researches on using Modified Jones Model to gauge the quality of earnings reported by listed companies.

    However, model to measure the quality of growth of listed companies is limited. The writer is enlightened to do a data-driven analytical model to check the quality of growth of the listed companies in the Hong Kong stock market.

    Body of Article

    Quality of earnings check is important to avoid falling trap to value trap and creative accounting mischief. This check is important for value investing as value investors look for cheap stocks. However, some time, cheap stocks are cheap with a reason: value trap.

    However, beside value investing, another school of fundamental analysis is growth investing. However, the data-driven analytical tools to check the quality of growth is limited. However, this is an important check for the growth investors.

    In this research paper, an akin model of the Modified Jones Model is to check the quality of growth is designed to check the quality of growth.

    The model uses cross section data of stocks in the Hong Kong stock market with market cap larger than HK$40 billion as a data set for the research. There are 91 companies in the Hong Kong stock market with market cap larger than HK$40 billion on 17 March 2013. Out of these 91 companies, some companies are removed from the dataset, namely, banks and insurance companies are excluded from the dataset for research. The reason is because banks basically have no sales figures to estimate the sales growth which is one of the factors in the model and insurance companies do not have short term debt for meaningful reporting purpose because of Hong Kong Financial Reporting Standard.

    After the exclusion, there are 70 companies for analysis. The model hypothesizes that profit growth should be impacted by sales growth, operating profit margin and short term debt.

    It is obvious that sales growth will have an impact on the profit growth and more revenue will drive the profitability of the company and cover the fixed cost. The model posits a positive relationship.

    For operating margin, the higher the operating margin, the lower the profit growth. This is because the high operating profit margin reduces the sales growth and attract competitors and new entrant.

    For short term debt, the short term debt to total asset ratio is used. This is to uniting the short term debt because companies with different size has different short term debt amount. The total asset is used as a method to render the figures comparable across different companies. The model postulates that the higher the short term debt, the lower the sales growth. This is because usually companies with weak profit growth will use short term debt to finance the slowing operation.

    In mathematical form:

    EG = a + b1 SG + b2 OPM + b3 STDR = e

    Where EG = earnings growth

    SG = sales growth

    OPM = operating profit margin

    STDR = short term debt to total asset ratio

    The results of the regression are marginally satisfactory with R Square equal to 0.178 which is not very good but still with some predictive power.

    The beta of sales growth is 0.73 which is with a strong impact on the profit growth. This confirms the hypothesis. Furthermore, it is statistically very significant with a t-statistics of 3.47.

    The beta of the operating profit margin is -0.12 which is a negative impact on the profit growth. This also confirms the hypothesis. The effect of operating profit margin is also statistically significant with a t-statistics of 1.4.

    The beta of the short term debt to total asset ratio is -0.27 which is a negative impact on the profit growth also. This also supports the hypothesis. However, the effect is not statistically significant.

    The above research is an ex-ante basis results which historical profit growth used for regressing with the independent variable.

    To further check the quality of growth, an ex-post basis research has also been done. The further proposition is that the historical price earnings ratios are the best predictor of the future profit growth. The higher the historical price earnings ratios, the higher the future profit growth. This is consistent with the think of investment cognoscente, Mr. Peter Lynch with espouse the usage of the PEG ratio to check the fairness of the price paid comparing with the growth prospect.

    Similarly, high historical the sales growth will have a negative impact on the future profit growth as a high historical sales growth will render slower sales growth in the future because of larger base, larger market share, the larger share of the economy by the industry and higher competition in future. The model posits a negative relationship with PE ratio.

    For operating margin, the higher the operating margin, the lower the future profit growth and lower the PE ratio. This is because the high operating profit margin reduces the sales growth and attract competitors and new entrant.

    For short term debt, the short term debt to total asset ratio is used. This is to uniting the short term debt because companies with different size has different short term debt amount. The total asset is used as a method to render the figures comparable across different companies. The model postulates that the higher the short term debt, the higher future profit growth. This is because usually companies with good future profit growth are willing to use short term debt to finance the possible future profit growth.

    In mathematical form:

    FEG = a + b1 SG + b2 OPM + b3 STDR + e

    Where FEG = future earnings growth

    SG = sales growth

    OPM = operating profit margin

    STDR = short term debt to total asset ratio

    The results of the regression are marginally satisfactory with R Square equal to 0.169 which is not very good but still with some predictive power.

    The beta of sales growth is -0. 05 which is with a negative impact on the historical PE ratio (a predictor of future profit growth). This confirms the hypothesis. However, it is statistically not significant with a t-statistics of 0.81.

    The beta of the operating profit margin is -0.07 which is a negative impact on the historical PE or future profit growth. This also confirms the hypothesis. The effect of operating profit margin is also statistically significant with a t-statistics of 2.9.

    The beta of the short term debt to total asset ratio is 0.34 which is a positive impact on the historical PE ratio or future profit growth also. This also supports the hypothesis. However, the effect is fairly statistically significant.

    Conclusion

    The model confirms that quality of growth is in the ex-ante sense: positively related to sales growth, negatively related to operating profit margin and negatively related to short term debt burden. The model confirms that quality of future growth is in the ex-post sense: negatively related to sales growth, negatively related to operating profit margin and positively related to short term debt burden.

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