Following the crash of 1987, one contentious regulatory issue has been whether margin activity exacerbated the decline in equity values. We contrast the crash behavior of NASDAQ securities eligible for margin trading with the behavior of ineligible ones. Consistent with the hypothesis that margin‐eligible securities were more frequently subjected to margin calls and forced sales, we find that abnormal volumes were uniformly larger for eligible securities. However, there is no evidence that this activity provoked additional price depreciation. Margin‐eligible securities actually fell by one percent less than the ineligible securities over the period.

We use predictions of aggregate stock return variances from daily data to estimate time-varying monthly variances for size-ranked portfolios. We propose and estimate a single factor model of heteroskedasticity for portfolio returns. This model implies time-varying betas. Implications of heteroskedasticity and time-varying betas for tests of the capital asset pricing model (CAPM) are then documented. Accounting for heteroskedasticity increases the evidence that risk-adjusted returns are related to firm size. We also estimate a constant correlation model. Portfolio volatilities predicted by this model are similar to those predicted by more complex multivariate generalized-autoregressive-conditional-heteroskedasticity (GARCH) procedures.

Hendrik Bessembinder, Paul J. Seguin, Price Volatility, Trading Volume, and Market Depth: Evidence from Futures Markets, The Journal of Financial and Quantitative Analysis, Vol. 28, No. 1 (Mar., 1993), pp. 21-39

We examine whether greater futures‐trading activity (volume and open interest) is associated with greater equity volatility. We partition each trading activity series into expected and unexpected components, and document that while equity volatility covaries positively with unexpected futures‐trading volume, it is negatively related to forecastable futures‐trading activity. Further, though futures‐trading activity is systematically related to the futures contract life cycle, we find no evidence of a relation between the futures life cycle and spot equity volatility. These findings are consistent with theories predicting that active futures markets enhance the liquidity and depth of the equity markets.

We investigate the relations between trading volumes and our proxies for information flows and divergences in opinions. We view S&P 500 Index futures' open interest as a useful proxy for divergences of traders' opinions, and find that volumes are higher on days when open interest increases than on days with declines. Volume in individual equities is more closely related to firm-specific information flows, while equity basket volume is more closely associated with market information. This differential impact is greatest for small capitalization stocks where market-wide news has no explanatory power.

We investigate IPO market efficiency using a sample of equity carve-outs offered during the period of 1985–2005. Unlike IPOs examined in previous studies where trading during the pre-IPO book-building period does not exist and trading on the IPO date is rationed, in equity carve-outs, investors can trade in the non-rationed market for shares of the parent, which holds a significant fraction of the subsidiary. We find that the subsidiary's initial day return is significantly related to its parent's return over the book-building period, but unrelated to its parent's contemporaneous return. Neither the pre-IPO price revision of the subsidiary nor the return to the parent on the initial trading day can be predicted. While the portion of the subsidiary's initial return unpredictable from information available during the book-building period is significantly related to its parent's contemporaneous return, the predictable component of the initial return is not. We interpret these results as evidence consistent with market efficiency.

Trading halts increase, rather than reduce, both volume and volatility. Volume (volatility) in the first full trading day after a trading halt is 230 percent (50 to 115 percent) higher than following “pseudohalts”: nonhalt control periods matched on time of day, duration, and absolute net‐of‐market returns. These results are robust over different halt types and news categories. Higher posthalt volume is observed into the third day while higher posthalt volatility decays within hours. The extent of media coverage is a partial determinant of volume and volatility following both halts and pseudohalts, but a separate halt effect remains after controlling for the media effect.

Trading halts increase, rather than reduce, both volume and volatility. Volume (volatility) in the first full trading day after a trading halt is 230 percent (50 to 115 percent) higher than following “pseudohalts”: nonhalt control periods matched on time of day, duration, and absolute net-of-market returns. These results are robust over different halt types and news categories. Higher posthalt volume is observed into the third day while higher posthalt volatility decays within hours. The extent of media coverage is a partial determinant of volume and volatility following both halts and pseudohalts, but a separate halt effect remains after controlling for the media effect.