The Journal of Finance

Trading Volume and Cross‐Autocorrelations in Stock Returns

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.00231

Tarun Chordia, Bhaskaran Swaminathan

This paper finds that trading volume is a significant determinant of the lead‐lag patterns observed in stock returns. Daily and weekly returns on high volume portfolios lead returns on low volume portfolios, controlling for firm size. Nonsynchronous trading or low volume portfolio autocorrelations cannot explain these findings. These patterns arise because returns on low volume portfolios respond more slowly to information in market returns. The speed of adjustment of individual stocks confirms these findings. Overall, the results indicate that differential speed of adjustment to information is a significant source of the cross‐autocorrelation patterns in short‐horizon stock returns.

Estimating the Intertemporal Risk–Return Tradeoff Using the Implied Cost of Capital

Published: 11/11/2008   |   DOI: 10.1111/j.1540-6261.2008.01415.x

ĽUBOŠ PÁSTOR, MEENAKSHI SINHA, BHASKARAN SWAMINATHAN

We argue that the implied cost of capital (ICC), computed using earnings forecasts, is useful in capturing time variation in expected stock returns. First, we show theoretically that ICC is perfectly correlated with the conditional expected stock return under plausible conditions. Second, our simulations show that ICC is helpful in detecting an intertemporal risk–return relation, even when earnings forecasts are poor. Finally, in empirical analysis, we construct the time series of ICC for the G–7 countries. We find a positive relation between the conditional mean and variance of stock returns, at both the country level and the world market level.

Price Momentum and Trading Volume

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.00280

Charles M.C. Lee, Bhaskaran Swaminathan

This study shows that past trading volume provides an important link between “momentum” and “value” strategies. Specifically, we find that firms with high (low) past turnover ratios exhibit many glamour (value) characteristics, earn lower (higher) future returns, and have consistently more negative (positive) earnings surprises over the next eight quarters. Past trading volume also predicts both the magnitude and persistence of price momentum. Specifically, price momentum effects reverse over the next five years, and high (low) volume winners (losers) experience faster reversals. Collectively, our findings show that past volume helps to reconcile intermediate‐horizon “underreaction” and long‐horizon “overreaction” effects.

What is the Intrinsic Value of the Dow?

Published: 12/17/2002   |   DOI: 10.1111/0022-1082.00164

Charles M. C. Lee, James Myers, Bhaskaran Swaminathan

We model the time‐series relation between price and intrinsic value as a cointegrated system, so that price and value are long‐term convergent. In this framework, we compare the performance of alternative estimates of intrinsic value for the Dow 30 stocks. During 1963–1996, traditional market multiples (e.g., B/P, E/P, and D/P ratios) have little predictive power. However, a V/P ratio, where V is based on a residual income valuation model, has statistically reliable predictive power. Further analysis shows time‐varying interest rates and analyst forecasts are important to the success of V. Alternative forecast horizons and risk premia are less important.