Risk-Reward Agility of the Benjamin Graham and Joel Greenblatt’s Investing Philosophy in the Indian Stock Market

There are various value stocks picking methods and various studies on value investing in past. Still there is disbelieve related to effectiveness of value investing. Various studies on value investing inferred that value investing resulted higher returns than market average. The Graham stock selection criteria is widely appreciated and acknowledged across the globe. This methodological framework for stock investing is well lived and demonstrated by the equally agile and legend investor Warren Buffet for sustained wealth creation. But the investment literature supports even more robustness of the Greenblatt‟s magic formula for a similar purpose. The study tested the two stock selection criteria, viz. Benjamin Graham‟s investing strategy and Joel Greenblatt‟s Magic Formula from 2010 to 2018 and compared the portfolios return with the market benchmark NSE 50 and NSE 500. In the study, in Graham portfolio returns out of 8 year in 5 years are better than market benchmark (NSE 50) average returns and out of 8 years in 5 years have beaten the market benchmark (NSE 500) average returns but Greenblatt portfolio returns in 6 years generated superior than the market benchmark (NSE 500 and NSE 50) average returns as well as Graham portfolio average returns. Unsystematic risk (standard deviation) and systematic risk (beta) both in Graham are less in comparison to market benchmark as well as Greenblaltt selection criterion. In terms of risk- reward measure viz., Sharpe ratio, Treynor ratio, Sortino ratio, and Jensen‟s alpha of Graham criterion demonstrated superior returns than the market benchmark (NSE 50 and NSE 500) and Greenblatt demonstrate that the portfolio performed better than market benchmark (NSE 50 and NSE 500) as well as Graham. On the whole, the study results documented a superiority of the Greenblatt measure over the Benjamin Graham criterion both in terms of return generation as well as risk – reward trade off in Indian stock market during the study period, January 2010 through December 2018.