The comparative better performance of some investment styles in circumstances of varied operating market conditions has been a subject of research interest overtime with investment professionals constantly scouring the literature to identify predictor variables of the superior performance of these investment approaches. With the value stocks outperformance of growth stocks documented phenomenon in mind, this study attempted to increase learning on this occurrence from a Kenyan perspective.
The dissertation employed the methodology implemented by The Brandes Institute (2009) from the pioneering work of Lakonishok et al. (1994). More specifically, equities data over the period 2011-2019 were used. The price-to-book (P/B) value ratios for the Nairobi Securities Exchange All-Share Index (NASI) firms were computed to determine the predictability of the comparatively better returns results of the value stocks over the growth ones.
Using the comparative price to book ratios, a ranking of monthly stocks was carried out. This was followed by constructing subsequent, for each month, four newly constructed portfolios of investment portfolio. The growth stock portfolios constituted the topmost quarter of P/B ratio equity stocks while value portfolio stocks comprised the lowest quarter of P/B ratio stocks. From this, a quartile-based performance was analysed over the subsequent five-year periods. The comparative value to growth portfolio performance was checked against the valuation difference multiple to identify any existence of valuation disparities as well as the subsequent comparative performance results relationship of value vis-à-vis growth stocks. The study found a Nairobi All Share Index (NASI) relationship of the valuation difference multiple and the ensuing return outcome of value and growth portfolios of equity stocks. A higher valuation difference multiple correlated with a higher subsequent superior performance of value equities throughout the following five-year period vis-à-vis the growth counterparts.
The dissertation also researched the returns performance of certain value investment approaches in the Kenyan stock market based on nine company fundamentals from published financial statements of public companies, following the Piotroski (2000) work. The dissertation examined the alternative stock performance forecast combination methods that fully use the financial statements data.
The finance discipline, just like economics, is a social science as the data thereof come from human economic transactions. However, a big portion of research in this field is done by methods that mimic those used in the natural sciences (physical laboratory) tests. The appearance of a semblance of scientificity in this area together with the increased credibility in the research process and outcomes is vitally important, although the research outcomes’ evaluation yardstick varies from that used in the natural sciences. For example, alternative research results that do not confirm the efficient markets hypothesis have traditionally been set aside as outliers and hence leading to the concluding assumption that the entirety of the hypothesis has been validated.
This dissertation assumed the presence of persistent inefficiencies in the stock market from which investors could derive benefits. Using the published financial statements data of firms listed on the Nairobi Securities Exchange (NSE), the correlation significance of firms’ financial ratios and their subsequent stock returns was determined. A few combination methods of the financial statement data derived variables were performed with the aim of increasing the investment strategy’s profitability. The dissertation’s finding was that, generally, classifying securities based on certain internal criteria of financial soundness can separate future winner stocks from loser ones and thus confirmed previous study results on the US market. It showed that a range of combination methods was able to isolate profitable investment strategies with those measuring profitability being the central predictors of the future performance of a stock. It was found that increased complexity in investment methods did not improve the consistency and performance of the simple methods.