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Forecasting the Si Effect 161<br />

stocks. For holding periods of 1 year, abnormal returns were positive,<br />

but only weakly significant.<br />

schultz (1983) extended the analysis to Amex stocks. Using<br />

this broader universe, he found that smaller stocks exhibited significant<br />

risk-adjusted returns after transaction costs, even over short<br />

holding periods. Schultz also noted that transaction costs cannot<br />

plain the periodic sign reversal found by Brown, Kleidon, and<br />

Marsh (1983) or the abnormal January behavior of smaller firms.<br />

M u d and Mendelson (1986a and 1986b) hypothesized that<br />

investors demand compensation for illiquidity, and the that size effect<br />

proxies for an illiquidity premium. They employed bid/ask the<br />

spread as a measure of market thinness. This spread is inversely<br />

correlated with attributes that reflect liquidity, such as trading volume,<br />

number of shareholders, number of dealers making a market,<br />

and degree of price continuity. They found that returns, both gross<br />

and net of trading costs, were an increasing function of the bid/ask<br />

spread; the effect of firm size was negligible after controlling li- for<br />

quidity.<br />

Chiang and Venkatesh (1988) maintained that the higher<br />

spread for small firms is not due to illiquidity, but results rather<br />

from the higher proportion of “insiders” trading these stocks. The<br />

presence of such informed traders leads dealers to raise the spread,<br />

which in turn causes ordinary investors<br />

require a higher expected<br />

return on small stocks.<br />

Slze and Risk Measurement<br />

Roll (1981~) proposed that a bias in beta estimates leads to an overstatement<br />

of the small-firm effect. Because small stocks trade less<br />

frequently than large stocks, their risk as estimated from daily returns<br />

understates their actual risk. Roll estimated the impact of<br />

nonsynchronous trading on beta by using Dimson‘s (1979) aggregated<br />

coefficients method. (Dimson betas are formed by regressing<br />

security returns on lagged, contemporaneous, and leading market<br />

returns, then summing the three slope coefficients.) The use of<br />

Dimson betas moderated the observed small-firm effect, but<br />

Reinganum (1982) found it insufficient to explain the full magnitude<br />

of the effect.

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