Sum of Absolute Rank Differences: An Investment Approach

Thomas Lind Petersen & Espen Sverdrup Tandberg

Student thesis: Master thesis

Abstract

The aim of this thesis is to investigate whether a multiple valuation investment strategy based on the sum of absolute rank differences approach can produce higher risk-adjusted returns than the market. The central point of the thesis’ theoretical basis is the work of Knudsen, Kold, and Plenborg (2017) who developed a combination of fundamental analysis and industry classification to find comparable firms, called the sum of absolute rank differences (SARD). We use proxies for the drivers of multiples; profitability, growth and risk, to find fundamentally comparable firms within industries. We create 10 portfolios based on the multiples P/E, P/B, EV/EBIT, EV/Sales and combinations thereof. The number of portfolios are doubled as we create 2 strategies. One where we create 10 long-only portfolios where we invest in the most undervalued companies according to our model, and one with 10 long- short portfolios, where we also short the most overvalued stocks. We form the portfolios on selected stocks from the S&P 1500 index from 1995 to 2016 by valuing all companies in the sample on March 31st every year, investing in the 45 most undervalued stocks and shorting the 45 most overvalued stocks. We perform robustness checks by using the Fama French three factor model (1993). We use our own sample and the S&P 1500 index as benchmarks. We find that the SARD approach is able to find undervalued firms to create high returns in our long-only portfolios, which perform much better than the benchmarks. However, the SARD approach is not very good at finding overvalued firms, as the long-short strategies perform much worse than the long-only strategies and slightly worse than our sample mean, when you look at the raw returns. Yet, when you combine the modest returns with the very low standard deviation, the long-short strategies experience extremely high Sharpe ratios and significantly higher returns than the S&P 1500 for our best strategies. We also find that the EV/Sales multiple leads to the highest returns, for both long and long-short strategies.

EducationsMSc in Finance and Strategic Management, (Graduate Programme) Final ThesisMSc in Finance and Investments, (Graduate Programme) Final Thesis
LanguageEnglish
Publication date2017
Number of pages130
SupervisorsThomas Plenborg