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author Philip Vanstraceele - February 19, 2013

The problem with single-factor valuation ratios is that they move “in and out of favor” and can significantly underperform the overall market over any given 10-year period despite their long-term outperformance.

The solution ?

A valuation factor that uses a few valuation measures overcomes this problem by giving you a list of companies that are undervalued based on a few valuation measures and thus more consistent returns.

The use of a “value composite” to measure undervaluation rather using the single valuation ratio of for example price-to-sales or book to market.

O’Shaughnessy found that stocks selected based on the value composite outperformed stocks scoring highest on any single value factor 82% of the time in all 10-year rolling periods between 1964 and 2009. So, a composite that combines several different value factors delivers stronger returns and more consistency than any individual factor !

The VC1 factor or the value composite one is calculated using the following five valuation ratios:

  • Price to book value
  • Price to sales
  • Earnings before interest, taxes, depreciation and amortization (EBITDA) to Enterprise value (EV)
  • Price to free cash flow
  • Price to earnings

How is VC1 calculated?

To calculate the VC1 factor we assign a percentile ranking (1 to 100) to each of the five valuation ratios for each company...[more]

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author Tim du Toit - November 13, 2012

Dear Fellow Investor

We honestly didn't think it would work as well.

  • In 2010 the newsletter tracked the index as the portfolio was started.
  • In 2011 during the sovereign debt crisis the newsletter gave up a bit of outperformance.
  • In 2012 the value subscribers invested in was finally recognised and outperformance really took off.

For the year to date the newsletter has outperformed the STOXX 600 index (incl...[more]

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author Philip Vanstraceele - October 8, 2012

Over the course of the last decades, the analysis of structural reasons for equity out- or underperformance has been a widely discusses academic topic. New explanatory factors, such as accruals (Sloan, 1996), were established and former explanatory factors lost some of their predictive power, as Fama and French (2003) show in the case of beta.

One of the more recent explanatory factors is the F-Score (Piotroski, 2000), which has strong practical utility in separating winners from losers in the value segment of the market. In his paper, our friend Jan Mohr provides evidence on the utility of F-Score in the growth segment of the market. This study was done in collaboration with MFIE...[more]

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author Fraser Dawson - September 29, 2012

In response to many questions from the Short Selling Blog:

Short Algorithm

The screen that featured in the article can be described as follows:

US companies with market capitalisation greater than one billion dollars and with 20 day average trading volume greater than 100,000 shares. These companies are less volatile than their smaller brethren and much more likely to be borrowable. ADRs are excluded. This gives a typical starting universe of about 1700 large, liquid US-based companies.

Then a 5 year earnings yield (EY5) is found for each...[more]

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