Filters, sieves, screens

Investors use filters (aka sieves, screens) to identify shares of the type (e.g. value, growth, recovery, income, etc) that they are looking for. Filtering the shares should only be used to identify potential investments for evaluation of the business, management and valuation (see side bar)

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Amateur investors sometimes think that a share is a bargain based on filters such as low P/E or PEG and high dividend yield without understanding the reasons why the ratios are relatively low or high. This may be due to ignorance of the reasons why the market prices of their filtered shares are "low". Or it may be due to arrogance that makes them believe that other buyers and sellers, whose buying and selling results in the market price, are so incompetent that they cannot recognise what seems to be obviously a bargain to the amateur investor.

I would recommend James O'Shaughnessy's book "What works on Wall Street" (see below) to any investor who hopes to use filters alone to pick shares and outperform the index. Amateur investors have neither the expertise in statistics nor access to vast quantities of data and the time and resources that O'Shaughnessy's meticulous research requires to try to conclude how well individual filters, or combinations, worked. Also, amateur investors are unlikely to be able to manage portfolios of 50 (sometimes 25) shares on which O'Shaughnessy bases his conclusions.

It is inconceivable that institutional investors would not have used their huge resources to research filters that might give them an edge. I doubt whether they have discovered any such thing because they generally under perform the market over long time periods - see "Index trackers" on the left side bar.

Investors should not assume that "strategies" that worked in the past will continue to work:

  1. the blurb about his book "Beating The Dow: A High-Return, Low-Risk Method For Investing In The Dow Jones Industrial Stocks With As Little As $5000" says "In 1991, Michael B. O'Higgins, one of the nation's top money managers, turned the investment world upside down with an ingenious strategy, showing how all investors--from those with only $5,000 to invest to millionaires--could beat the pros 95% of the time by putting 100% of their equity investment into the high-yield, low-risk "dog" stocks of the Dow Jones Industrial Average. His formula spawned a veritable industry, including websites, mutual funds, and $20 billion worth of investments, elevating the theory to legendary status.". Like many such simple, apparently sure fire "strategies", it is based on data mining historical data and not necessarily predictive. Johnson Fry launched a Hy5 fund in 1994 based on this strategy and showed very impressive past records in their promotional launch literature of how the BTD5 strategy applied to FT30 consistently beat the Footsie by a wide margin. The fund failed and was absorbed by another fund with a different strategy.
  2. James O'Shaughnessy wrote a book in 1996 (updated in later editions) titled "What works on Wall Street" based on extensive research on various filters (and combinations of filters) using Standard & Poor's Compustat database from 1950 through 1994. O'Shaughnessy wrote "If there is no sound theoretical or commonsense reason for the relationship, it's most likely a chance occurrence". I agree with that but feel that his conclusions are not supported by sound theoretical reasons as to why what worked in the past should continue to work in the future and do not agree with his assumption that markets do not exploit anomalies in valuations to remove such anomalies in future prices.. O'Shaughnessy is the CEO of O'Shaughnessy Asset Management, a quantitative money management firm in USA. However the web site of the firm does not have data to determine whether he was able to use the conclusions in his book to outperform the market. In the enthusiasm following first publication of the book, portfolios following O'Shaughnessy's "what works" were shown in tip sheets, investment magazines, etc and updated for a while afterwards but abandoned later.

Commonly used filters (including filters used in combinations) include:

  • P/E (aka PER, price earnings ratio)
  • Dividend yield
  • Dividend cover
  • PEG (P/E divided by growth)
  • Gearing (aka leverage)
  • PSR (price divided by sales per share)
  • PBV (price divided by book value)
  • PTBV (price divided by tangible book value)
  • ROCE (return on capital employed)
  • Size (large, medium, small, fledgeling, AIM)
  • Gross profit
  • Sector (retail, telecoms, property, etc.)
  • Share price performance (daily, moving annual totals, relative strength, etc)
  • Directors' holdings
  • Directors' dealings
  • Growth rates (eps, sales, margins, PEG, etc)
  • PRD (price divided by research & development expenditure per share)
  • NAV ps (Net asset value per share)
  • Brokers forecasts (of profits, eps, dividend, etc)
  • Brokers forecast changes
  • PCF (price divided by cash flow per share)