Following is a list of the factors users can choose to select stocks:
In short, cheap stocks outperform expensive stocks.
Value investing was established by Benjamin Graham in his book Security Analysis from 1934.
Value anomally is one of the best known and has been popularized by Warren Buffett (arguably one of the best active investors).
Our algorithm ranks all stocks based on Enterprise Value/EBIT from the smallest (cheapest) to the highest (most expensive).
There are various measures of cheapness (mentioned EV/EBIT, Price/Earnings, Price/Book Value, ...). However, all of them provide similar results.
- Graham B. (1934): “Security Analysis”, available from Amazon
- Gray W. and Carlisle T. (2013): “Quantitative Value: A Practitioner’s Guide to Automating Intelligent Investment and Eliminating Behavioral Errors”, available at Amazon
- Asness C. S., Moskowitz T. J. and Pedersen L. H. (2009): “Value and Momentum Everywhere”, available at SSRN
- Sloan R. G., Chee S. and Uysal A. (2013): “A Framework for Value Investing”, available at SSRN
- Asness C., Frazzini A. and Pedersen L. (2014): “Quality Minus Junk”, available at SSRN
In short, high quality companies outperform low quality companies.
Quality can be expressed using different measures, however we use the simplest one: Return on Assets.
Various studies confirm, that quality is an important factor in determining whether the stock will perform well in the future.
Stocks are sorted on their ROA, and the ones with the highest ROA are selected.
- Haugen R. and Baker N. (1996): “Commonality in the determinants of expected stock returns”, available in Journal of Financial Economics
- Novy-Marx R. (2012): “The Quality Dimension of Value Investing” available as a Working Paper
- Cheng L., Novy-Marx R. and Zhang L. (2011): “An Alternative Three-Factor Model”, available at SSRN
- Zaremba, A. (2013): “Quality Investing and the Cross-Section of Country Returns”, available at SSRN
In short, low-volatility stocks outperform high-volatility stocks.
Volatility (stock price fluctuations) is a way to define risk. In finance it is generally accepted that risk is positively related to return.
However results of empirical studies on low-volatility effect show the opposite. The investors who hold high-volatility stocks are not compensated enough.
The pioneer of low-volatility investing - Robert Haugen - published the first empirical study in 1972. The studies covering low-volatility anomally document its existence since 1926. Quite a few ETFs have been created recently based on low-volatility anomally: * PowerShares S&P 500 Low Volatility Portfolio * iShares MSCI USA Minimum Volatility Index * iShares MSCI Emerging Markets Minimum Volatility Index * SPDR Russell 2000 Low Volatility ETF
- Haugen R. (2012): “Low Risk Stocks Outperform within All Observable Markets of the World”, available at SSRN
- Falkenstein e. (2012) “The Missing Risk Premium: Why Low Volatility Investing Works”, available at Amazon
- van Vliet P. (2012): “Low-Volatility Investing: Collected Robeco Articles”, available at Robeco Investment Engineers
- Blitz D., Pang J. and van Vliet P. (2012): “The Volatility Effect in Emerging Markets”, available at SSRN
- Hsu J. and Li F. (2013): “Low-Volatility Investing”, published in The Journal of Index Investing
- Li F. (2013): “Making Sense of Low Volatility Investing”, available at Research Affiliates
In short, companies with low asset growth outperform companies with high asset growth.
Firms with rapidly growing balance sheets via equity offering or debt perform worse than companies with decreasing balance sheet due to spinoffs, share repurchases or debt repayments.
Higher asset growth usually creates hopes too high for investors. Analyst forecasts are then often revised downward and earnings dissapoint.
- Li X. and Sullivan R. (2014): “Investing in the Asset Growth Anomaly Across the Globe”, available at SSRN
- Cooper m., Gulen h. and Schill m. (2009) “The Asset Growth Effect in Stock Returns” , available as Darden Business School Working Paper
- Watanabe A., Xu Y., Yao T. and Yu T. (2013): “The Asset Growth Effect: Insights from International Equity Markets”, available at Journal of Financial Economics
- Wen Q. (2014): “Asset Growth and Stock Market Returns: A Time-Series Analysis”, available at SSRN
- Lipson M., Mortal S. and Schill M. (2009): “What Explains the Asset Growth Effect in Stock Returns?”, available at SSRN
In short, companies with big accrual component of earnings perform worse than companies with small accrual component.
Earnings consist of cash flow and accruals.
Accruals involve higher degree of uncertainty than cash flow.
Academic research defines accruals as the change in non-cash working capital less depreciation expense.
Accruals incorporate estimates of future cash flows, deferrals of past cash flows, allocations and valuations, all of which involve higher subjectivity than simply measuring periodic cash flow.
Accruals lead to lower earnings persistence and investors do not fully anticipate this lower persistence, leading to significant security mispricing.
- Dechow P., Khimich N. and Sloan R. (2011): “The Accrual Anomaly”, available at SSRN
- Richardson S, Sloan R., Soliman M. and Tuna A. (2005): “Accrual Reliability, Earnings Persistence and Stock Prices”, available in Journal of Accounting and Economics
- Han I., Kim B., Lee J. and Park S. (2013): “Information Asymmetry and the Accrual Anomaly”, available at SSRN
- Lev B. and Nissim D. (2004): “The Persistence of the Accruals Anomaly”, available at SSRN
- LaFond R. (2005): “Is the Accrual Anomaly a Global Anomaly?”, available at SSRN
- Allen E., Larson Ch. and Sloan R. (2013): “Accrual Reversals, Earnings and Stock Returns”, available in Journal of Accounting and Economics
In short, stocks with high momentum outperform stocks with low momentum.
Momentum has first been mentioned in Jegadeesh study in 1993.
Various studies document existence of momentum in equity markets since 1801, thus in over 200-year history.
Studies find that stocks that have performed well in the past 3 to 12 months tend to continue performing well up to 12 months in the future.
- Jegadeesh N. and Titman S. (2011): “Momentum”, available at SSRN
- Korajczyk R. and Sadka R. (2003): “Are Momentum Profits Robust to Trading Costs?”, available at SSRN
- Asness C., Frazzini A., Israel R. and Moskowitz T. (2014): “Fact, Fiction and Momentum Investing”, available at The Journal of Portfolio Management
- Jegadeesh N. and Titman S. (1993): “Returns to Buying Winners and Selling Losers: Implications for Stock Market Efficiency”, available in The Journal of Finance
- Faber M. (2007): “A Quantitative Approach to Tactical Asset Allocation”, available in The Journal of Wealth Management