Harry Markowitz (1952, 1959) portfolio problem reveals that assets cannot be selected only on characteristics that are unique to them. Past studies on diversification focused on the “extent” of diversification. The purpose of this study was on the interaction of complex investment constraints and diversification on portfolio efficiency in the soft drink industry in western Kenya. The study was a descriptive survey design with a target population of 250 respondents selected by a census sampling technique. Both primary and secondary data were used in this study; an interview schedule was used whose reliability was provided using Cronbach’s Alpha; the results of analysis found Cronbach’s Alpha of 0.970 which suggest strong internal consistency of the research instrument compared to its standard of 0.70. Secondary data was obtained from the firm’s financial statements relating to firm’s assets. Descriptive statistics involved the use of percentages and means, and regression equations to establish the relationship between complex investment constraints, diversification and portfolio efficiency. capital structure as a constraint doesn’t have any significant contribution to diversification; level of investment information and level of investment risk significantly contribute to investment diversification; a strong association exists between complex investment constraints and diversification (R = 0.984) and the variation in investment diversification can be accounted for upto 96.7% by firm’s capital structure, level of investment information and level of investment risk and with a significant relationship (F= 2428.043, p < 0.005); a positive correlation for the diversification alternatives to portfolio efficiency; worst diversification alternative (0.458 ** ), average diversified alternative (0.713 ** ); and best diversified alternative (0.890 ** ); and this correlation was significant at (p<0.01; 2-tailed. Results indicate a significant relationship between investment alternatives (WDA, ADA, and BDA) and portfolio efficiency ( F = 398.020; p 0.000< 0.05 ). The contribution of diversification alternative towards portfolio efficiency shows that only ADA and BDA have positive contribution while WDA has negative contribution to portfolio efficiency; there exist a significant relationship between ADA, BDA and portfolio efficiency; the results indicate that portfolio efficiency depends on diversification sets constructed by investors; PORT.EFF. = 2.103E-16 – 2.795E-15 WDA+ 0.231ADA + 0.769 BDA; results for part analysis of ADA, BDA and portfolio efficiency show improved performance in portfolio efficiency; the R is 0.911, R 2 is 0.829; and adjusted R 2 has a dismal increase; but the F value increased from 398.020 to 599.45; this indicate that ADA and BDA are better in influencing portfolio efficiency, but BDA is the best model for selection of efficient portfolio ( F = 947.112; R = 0.890; R 2 = 0.792; p < 0.05).
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