Quality-at-reasonable-price: developing a UK equity portfolio

Equity investing has evolved significantly since its formalisation during the early twentieth century. Two major recent evolutions are Quality investing and Value investing. Asness et al. (2019) demonstrate fundamentally strong stocks have higher expected returns. Solt and Statman (1989) show that strong companies can be bad investments. Therefore, it is important that investors do not overpay for quality. In this research, I demonstrate that a quality-at-reasonableprice equity portfolio outperforms on an absolute and risk-adjusted basis. Using the non-financial FTSE 350 constituents at the end of December of each year from 2000 to 2016, I develop a multidimensional approach using Quality and Value variables that generate a significant outperformance. Before risk adjustment, the portfolio produces an average monthly return of 0.99% with an annualised Sharpe ratio of 0.73. This compares with an average monthly return of 0.46% and an annualised Sharpe ratio of 0.30 for the remaining stocks in the benchmark. Regression analysis demonstrates that the investment approach produces statistically significant Alpha. Adjusting for risk using the Fama and French (1993) and Carhart (1997) four-factor model, the portfolio earns a statistically highly significant (t = 4.4) abnormal return of 0.56% per month. This compares with a weakly significant (t = 1.5) abnormal return of 0.16% per month for the remaining stocks in the benchmark. In this project, I propose an optimised approach to equity investing relative to passive indexing and traditional active stock selection. Unlike most academic research which works with all stocks including small and micro stocks (e.g. Fama and French (1992, 1993, 1996), Piotroski (2000) and Bartram and Grinblatt (2018)), I consider only the larger stocks in the UK by restricting my sample to the non-financial members of the FTSE 350 index. Since I use only large and more liquid stocks, my strategy can be easily implemented by investors.