Understanding Pricing Dynamics through Cell Analysis in Bangladeshi Industries

This study delves into the pricing dynamics of listed stocks in Bangladeshi industries through cell analysis, aiming to differentiate value, growth, undervalued, overvalued, and normalized growth stocks. It explores how portfolio managers can categorize stocks and the discrepancy between market and analyst perceptions. The research findings are relevant for portfolio managers, academicians, and investors in the DSE & CSE markets.

• Pricing Dynamics
• Cell Analysis
• Bangladeshi Industries
• Portfolio Management
• Stock Classification

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1. Understanding Pricing Dynamics through Understanding Pricing Dynamics through Cell Analysis: A study on selected Cell Analysis: A study on selected Bangladeshi industries Bangladeshi industries

2. Introduction Background of the study A value stock is often generally characterized with low P/E, low P/BV multiples; whereas most of the practitioners characterize a growth stock with higher relative valuations and EPS growth. The above-mentioned conceptual difference between value and growth investing may be reasonably straightforward, but classifying individual stocks into the appropriate style is not always simple in practice. Relative value based characterizations often overlap. Cell analysis refers to a conceptual framework whereby detailed and precise characterization of listed stocks can be performed at an intra- industry and across-industry level. Cell analysis is conducted either taking market pricing mechanism at its face value or through developing analyst s own relative pricing mechanism.

3. Introduction Rationale of the study A portfolio manager s job is far more intricate than just characterizing stocks as per value and growth stock definition. A portfolio manager should at least have the ability to categorize stocks into value stock, growth stock, undervalued stock, overvalued stock, normalized growth stock. A portfolio manager should be able to understand the undefined zone and predict the possible paradigm shifts in this undefined zone. A P/E and P/BV driven cell analysis helps a portfolio manager to define value stock, growth stock, undervalued stock, overvalued stock, normalized growth stock and inconclusive stocks at an intra-industry and across-industry level. For conducting a cell analysis we do not need to assume that market prices deviate from intrinsic value but that they correct themselves over long periods, rather we assume that markets are on average right and that while individual firms in a sector or market may be mispriced, the sector or overall market is fairly priced.(Damodaran, 2004).

4. Introduction - Objectives and scope of the Study Research objectives: To understand pricing dynamics for DSE listed stocks through cell analysis. To characterize listed stocks representing different industries into different segments value stock, growth stock, overvalued stock, undervalued stock, normalized growth stock. To investigate whether the broad-based market perception of stock classification differs from that of an analyst s perception or not. Scope: Research findings are only relevant for portfolio managers, academicians and investors working in DSE & CSE.

5. Key literatures Academic Literatures that investigates how a market prices a security can be broadly categorized into two segments. One stream of academic knowledge focuses on how market categorize a growth and a value stock; another stream of learning focuses on why market fails to identify the true potentiality of firm (intrinsic value) and why intrinsic value often remains far away from the market value (overvalued and undervalued stock). According to Graham & Dodd (1934), value stocks are stocks whose price-to- earnings, price-to-book, and/or price-to cash flow is/are low relative to the market average. This definition is shared by multiple scholars (Capaul et al, 1993; Lakonishok et al, 1994; Fama & French, 1998; Leladakis & Davidson, 2001; Bourguignon & De Jong, 2003; Chan & Lakonishok, 2004; Cahine, 2008; Athanassakos, 2009). Growth stocks are characterized as those stocks whose earnings expectation and growth rates are substantially higher than the market averages and continuous to raise further (Babson, 1951; La Porta, et al, 1997; Leladakis & Davidson, 2001; Bourguignon & De Jong, 2003). These stocks, in which investors believe in a continuous rise, are referred to as growth (also called glamour) stocks (La Porta, et al, 1997). Based on the review of the literature, stock selection guideline in a price-inefficient market can be developed.

6. Research Methodology Technique of Analysis: Cell Analysis based on trailing P/E and Market defined P/BV 1. Cell Analysis based on Residual Earnings and AEG (abnormal 2. earnings growth) RE (residual earning is the relevant growth measure when evaluating price-to-book ratio. Abnormal earning growth (AEG) is the relevant growth measure when evaluating P/E ratio. Sample Size: DSE listed 74 companies of total 9 manufacturing Industries. Since manufacturing industries P/BV dynamics are different from that of financial industries , stocks of banking, NBFI, insurance and Mutual fund industries were not considered in the study. Time Frame: 2008-2015 (8 years)

7. Research Methodology (Continued) P/E of different stocks has been categorized into three spectrums high P/E, normal P/E and Low P/E. P/BV of different stocks has been categorized into three spectrums high P/E, normal P/E and Low P/E. Under the trailing P/E approach, the market P/E has been compared with the calculated trailing P/E for all the listed firms with respect to the previously mentioned market sectors. Under the Residual earning approach, each-year s residual earning and the expected residual earning (equal to the historical average) has been calculated.

8. Research Methodology (Continued) Trailing P/E = (1+ ke) / ke Cost of equity was calculated through CAPM (capital asset pricing method). Risk-free was defined as the 28-day Treasury-bill rate for the respective time. Beta was referred as the ratio between covariance of stock and market return and the variance of the market return. The time frame selected for calculating the market return was 2008 2015, a period, which experienced market s uptrend and downtrend. For tracking the long-term pattern of beta, the researcher has used Blume s adjustment as well. Securities having negative EPS were avoided in this study.

9. Research Methodology (Continued) Residual earning = Net income CSE * ke It was net income based definition of residual income that was used in the study; other researchers have opted out for CI (comprehensive income) as well. The researcher used Balance sheet based definition of equity; so hidden dirty surplus s impact on equity was not considered. Securities having negative BV were avoided in this study.

10. Research Methodology (Continued)

12. Research Methodology (Continued) Hypothesis 1: For each investigated industry, there will be cell- matching. So, it was expected that stocks categorized under the market pricing-led approach would exactly match with the analyst s perceived pricing approach (led by RE and AEG method). Hypothesis 2: Majority of the cases will fall on the prime diagonal line. So, it was expected that a high P/E firm will be a high P/BV firm, a normal P/E firm will be a normal P/BV firm and a low P/BV firm will be a normal P/E firm. This hypothesis symbolizes that market at large understand the P/E and P/BV dynamics. Hypothesis 3: There will be significant change of paradigms for undefined stocks. This hypothesis symbolizes that even if market s pricing trajectory is not perfect, its correction pace is brisk.

13. Analysis & Findings

14. Fuel & Power 120% 100% 80% 60% 40% 20% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 89% 100% 70% 70% 50% 63% 56% Growth 0% 0% 0% 0% 10% 13% 11% Value 11% 0% 10% 30% 30% 25% 0% Undervalued 0% 0% 20% 0% 0% 0% 22% Inconclusive 0% 0% 0% 0% 10% 0% 11% Stock Classification based on Trailing P/E

15. Fuel & Power 70% 60% 50% 40% 30% 20% 10% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 30% 40% 20% 50% 20% 40% 60% Growth 10% 10% 20% 0% 10% 10% 10% Value 40% 30% 50% 20% 40% 10% 10% Undervalued 20% 20% 10% 30% 20% 20% 10% Inconclusive 0% 0% 0% 0% 10% 20% 10% Stock Classification Based on Residual Earnings

16. Engineering 120% 100% 100% 89% 100% 86% 83% 78% 78% 80% 60% 40% 22% 22% 14% 17% 11% 20% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 100% 100% 89% 86% 83% 78% 78% Growth 0% 0% 0% 14% 17% 22% 22% Value 0% 0% 11% 0% 0% 0% 0% Stock Classification Based on Trailing P/E

17. Engineering 70% 60% 50% 40% 30% 20% 10% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 40% 20% 30% 40% 30% 20% 20% Growth 20% 10% 20% 30% 60% 30% 30% Value 0% 20% 10% 0% 10% 10% 20% Undervalued 40% 50% 40% 20% 0% 30% 30% Inconclusive 0% 0% 0% 10% 0% 10% 0% Stock Classification Based on Residual Earnings

18. Pharmaceuticals & Chemicals 120% 100% 100% 100% 83.33% 84.62% 83.33% 80% 91.67% 75% 60% 40% 25% 16.67% 15.38% 16.67% 20% 8.33% 0% 0% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 100% 100% 84.62% 75% 83.33% 91.67% 83.33% Growth 0% 0% 15.38% 25% 16.67% 8.33% 16.67% Stock Classification Based on Trailing P/E

19. Pharmaceuticals & Chemicals 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 15% 15% 31% 46% 46% 23% 23% Growth 15% 23% 39% 31% 46% 15% 15% Value 31% 38% 23% 8% 8% 23% 31% Undervalued 31% 15% 8% 15% 15% 31% 31% Inconclusive 8% 8% 0% 0% 0% 8% 0% Stock Classification Based on Residual Earnings

20. Textile Industry 120.0% 100.0% 100.0% 92.3% 88.2% 86.7% 80.0% 71.4% 68.8% 60.0% 50.0% 37.5% 40.0% 18.8% 14.3% 20.0% 13.3% 11.8% 12.5% 7.7% 6.3% 7.14% 0.0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 92.3% 100.0% 88.2% 71.4% 86.7% 68.8% 50.0% Growth 7.7% 0.0% 11.8% 14.3% 13.3% 18.8% 37.5% Value 0.0% 0.0% 0.0% 0.0% 0.0% 6.3% 12.5% Undervalued 0.0% 0.0% 0.0% 7.14% 0.0% 0.0% 0.0% Inconclusive 0.0% 0.0% 0.0% 7.14% 0.0% 6.3% 0.0% Stock Classification Based on Trailing P/E

21. Textile Industry 60% 50% 40% 30% 20% 10% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 18% 6% 0% 0% 12% 18% 6% Growth 53% 53% 29% 24% 35% 24% 35% Value 0% 12% 18% 12% 6% 0% 12% Undervalued 24% 18% 47% 41% 41% 47% 35% Inconclusive 6% 12% 6% 18% 6% 12% 12% Stock Classification Based on Residual Earnings

22. Food & Allied 120% 100% 100% 88% 88% 88% 86% 83% 83% 80% 60% 40% 17% 17% 20% 13% 13% 13% 14% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 88% 100% 88% 86% 88% 83% 83% Growth 0% 0% 13% 14% 13% 0% 0% Value 13% 0% 0% 0% 0% 0% 0% Undervalued 0% 0% 0% 0% 0% 17% 17% Stock Classification Based on Trailing P/E

23. Food & Allied 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 33% 33% 42% 8% 0% 17% 25% Growth 17% 17% 17% 33% 33% 25% 33% Value 8% 8% 0% 33% 42% 17% 8% Undervalued 42% 42% 33% 25% 25% 33% 25% Inconclusive 0% 0% 8% 0% 0% 8% 8% Stock Classification Based on Residual Earnings

24. Cement Industry 120% 100% 100% 100% 100% 100% 100% 100% 80% 75% 60% 40% 25% 20% 0% 0% 0% 0% 0% 0% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 100% 100% 100% 75% 100% 100% 100% Valued 0% 0% 0% 25% 0% 0% 0% Stock Classification Based on Trailing P/E

25. Cement Industry 60% 50% 40% 30% 20% 10% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 25% 50% 50% 0% 0% 50% 25% Growth 0% 50% 50% 25% 0% 25% 25% Value 25% 0% 0% 50% 50% 0% 0% Undervalued 50% 0% 0% 25% 50% 25% 50% Stock Classification Based on Residual Earnings

26. Ceramics 120% 100% 80% 60% 40% 20% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 100% 100% 100% 50% 67% 67% 33% Growth 0% 0% 0% 50% 33% 33% 67% Stock Classification Based on Trailing P/E

27. Ceramics 120% 100% 80% 60% 40% 20% 0% 2009 2010 2011 2012 2013 2014 2015 Growth 50% 25% 25% 25% 75% 100% 75% Undervalued 50% 75% 75% 75% 25% 0% 25% Stock Classification Based on Residual Earnings

28. Service & Real Estate 120% 100% 80% 60% 40% 20% 0% 2009 2010 2011 2012 2013 2014 2015 Overvalued 100% 100% 100% 66.67% 100% 66.67% 66.67% Growth 0% 0% 0% 33.33% 0% 33.33% 33.33% Stock Classification Based on Trailing P/E

29. Service & Real Estate 80.00% 70.00% 60.00% 50.00% 40.00% 30.00% 20.00% 10.00% 0.00% 2009 2010 2011 2012 2013 2014 2015 Overvalued 33.33% 0% 0% 0% 0% 0% 33.33% Growth 0.0% 0.0% 33.33% 33.33% 33.33% 33.33% 33.33% Value 33.33% 66.67% 66.67% 66.67% 66.67% 66.67% 33.33% Undervalued 33.33% 33.33% 0% 0% 0% 0% 0% Stock Classification Based on Residual Earnings

30. Summarized research findings Findings 1: For each investigated industry, there was no evidence of extract cell-matching. So, stocks categorized under the market pricing-led approach did not exactly match up with the analyst s perceived pricing approach (led by RE and AEG method). Findings 2:Majority of the cases fell on the prime diagonal line (so a significant portion of the studied stocks were either overvalued or undervalued; prevalence of value stock and growth stock was modest). So, this research finding bears the testimony that Bangladesh market at large understand the P/E and P/BV dynamics. Findings 3: There were no significant evidence of change in paradigms for undefined stocks. So, this research finding bears the testimony that Bangladesh stock market s pricing trajectory is not perfect and its price correction pace is not efficient either.

31. Conclusion (Limitation of the study) Usage of CAPM while calculating cost of equity and residual income (cost of equity and residual income calculations could have performed at a robust level) Not considering hidden dirty-surplus while defining comprehensive income (since firms of Bangladesh generally do not issue contingent claims over its equity, it is expected not to pose a big threat) Depending on the balance-sheet definition of CSE (should have been based on reformulated balance sheet) Using historical average of RE as the proxy for expected RE (this calculation could have been dealt with better modeling.)

32. Conclusion (Scope for further study) Cell analysis led study can be extended to non-manufacturing industries as well. Since non-manufacturing industries' assets are efficiently priced a better P/BV criteria for stock characterization can be developed. Out of 9 possible quadrants, the researcher has categorized five quadrants and the other four quadrants have been kept undefined. Further research can be conducted on the possible drifts in this undefined segment; one needs to remember drift from the existing cell structure is a symbol of market s efficient pricing behavior.