Can retail investors exploit stock market anomalies?

Abstract

This article investigates the extent to which small investors can exploit a range of stock market anomalies. The study uses a small number of companies to define both long and short portfolios, and investigates the post-cost profitability of the following strategies: earnings/price, return/assets, price, asset growth, size, dividend/price and overreaction. Transaction cost is estimated when buying underlying shares and when selling short shares with Contracts For Difference (CFDs). Findings show that only the earnings/price strategy can enjoy net gains for small investors showing some evidence against stock market efficiency.

Keywords:

• stock market anomalies
• small investors
• transaction cost
• contracts for difference (CFDs)

JEL Classification::

• G10
• G11
• G14

Acknowledgements

I would like to thank Glasgow Adam Smith Research Foundation for financial support.

Notes

¹ This strategy is the opposite of the one suggested in earlier studies (Basu, 1977). In unreported results, this study employs deciles to define long/short companies and finds that low earnings/price companies keep outperforming high earnings/price within the sample period. This shows that the results in this study are not driven by the small number of companies that are used to define long/short firms.

² This strategy is opposite to the one recommended in earlier studies (Blume and Husic, 1973). In unreported results, this article employs deciles to define long/short firms and finds that the strategy that offers profits remains the one that buys (sells-short) high-priced (low-priced) firms.

³ This strategy is the opposite of the one proposed in early studies (Banz, 1981). In unreported results, this study uses deciles to define long/short companies and finds that large companies keep outperforming small capitalization firms. This concurs with the findings of Dimson and Marsh (1999) who use UK data from 1989 to 1997 and report that the size effect has reversed.

⁴ Notice that the estimation of returns among alternative strategies is based on alternative samples. The aim of this study is not to compare the profitability among the strategies rather than exploring the extent those strategies can offer post-cost profitability. If companies were required to fulfil all conditions to be included in the sample, the study would have reduced the sample size significantly and into a very large capitalization companies.

⁵ Later in the study, findings show that only the earnings/price strategy can generate profits after adjusting for transaction cost and thus, these profits tend to remain strong during the sample period.

⁶ The construction of and factors is in line with Fama and French (1993). Companies with negative book values and financial companies are excluded from the sample and there is a minimum 6-month gap between book values and portfolio selection (each July). Briefly, each year the study splits independently all eligible live (fbrit) and dead (deaduk) UK companies into three book/market portfolios (L-30%, M-40% and H-30%) and into two size portfolios (S and L, based on the median market capitalization values) and generates six portfolios LS, LL, MS, ML, HS and HL. Monthly portfolio returns are then estimated over the following year (July to June). The factor reflects the monthly return difference on the average three small size portfolios (LS, MS and HS) and the average of the three large size portfolios (LL, ML and HL). Accordingly, the factor reflects the monthly return difference between the average of the two high-book/market portfolios (HS and HL) and the average of the two low-book/market portfolios (LS, LL).

⁷ For short position, the costs trading with CFDs (physical trading) are bid/ask spread, commissions and financing proceeds (bid/ask spread, commissions, stamp duty and short-selling fee). For long position, the costs trading with CFDs (physical trading) are bid/ask spread, commissions and financing cost (bid/ask spread, commissions and stamp duty). Norman (2009) and Opong and Siganos (2010) offer comprehensive reviews of CFDs and clear comparisons between CFDs and physical trading. The current study offers only a brief description.

⁸ http://www.halifax.co.uk/sharedealing/charges/share_dealing_charges.asp and http://www.halifax.co.uk/sharedealing/cfds/CFD_Charges.asp (accessed August 2010).

⁹ Almazan et al. (2004) find that 69% of US fund managers are not permitted by their investment policy to short-sell.

¹⁰ The bid–ask spread is estimated using the following formula:

where () is the monthly ask (bid) price for share i at day t and is the number of months where bid and ask prices were recorded by Datastream. The time selection is 12 months before each portfolio formation.