Anne M. Anderson

Trading Volume: NASDAQ and the NYSE

Historically, reported trading volume has been overstated for NASDAQ stocks relative to NYSE stocks. Because NASDAQ volume may be overcounted, many researchers use an adjustment factor to make it comparable to NYSE volumes. Today, electronic communication networks account for about 75 percent of the trading volume for NASDAQ stocks. Many believe that the increased level of trading on ECNs and changes to the order-handling rules have lessened the discrepancy between the exchanges. To investigate, this study examined the relationship between reported trading volume to shares outstanding for a matched sample of NYSE and NASDAQ companies. The evidence indicates that the discrepancy has not diminished but widened. Historically, reported trading volume has been overstated for stocks on NASDAQ (a dealer market) vis-à-vis stocks on the NYSE (an auction market). Market practitioners know that NASDAQ volume may be double-counted, so they frequently use an adjustment factor of 50 percent or so to make it comparable to NYSE volumes. Electronic communications networks (ECNs), however, now account for about 75 percent of the trading in NASDAQ stocks, which should make the NASDAQ resemble an auction market. Reported trading volume matters for two reasons. First, various U.S. securities regulations are based on trading volume. For example, U.S. SEC Rule 144 limits an individual’s sales of restricted common stock during a three-month period to either the average weekly trading volume in the stock during the preceding four weeks or 1 percent of the shares outstanding. Second, reported trading volume matters because trading volume is an important measure, for portfolio managers and other practitioners, of a stock’s liquidity. Practitioners need to know when trading volume is “real” and when it is overcounted as a result of dealer trades and, therefore, misleading. Moreover, some firms, deciding that reported volume figures in the two markets are now roughly equivalent, have already stopped adjusting for the historical difference in reported volume. We looked for evidence that the way volume is reported has indeed become equivalent in the two markets. Thus, we examined the structure of reported trading volumes on the NYSE and NASDAQ before and after the changes that occurred from 1997 to 2002. Specifically, we compared trading during 1990–1996 with trading during 2003–2005 to determine whether any meaningful change has occurred in the relationship between reported trading volume in the two markets from the former period to the latter period. We related reported trading volume on the NYSE and NASDAQ to the number of shares outstanding for a group of comparable companies trading on the two exchanges; we controlled for nonlinearity, stock price level, and volatility. We used the regression model to investigate the proposition that the widely acknowledged discrepancy between reported trading volumes for NYSE and NASDAQ stocks that existed before 1997 has diminished or vanished because of such recent developments as the change in order-handling rules for NASDAQ stocks and the increasing role of electronic order books in trading NASDAQ stocks. Surprisingly, we found no evidence that the discrepancy has either narrowed or vanished. On the contrary, our results suggest that the discrepancy may have widened, perhaps because of increased interdealer trading. We also found that the association between volatility and reported trading volume has increased dramatically in recent years for both NYSE and NASDAQ stocks. The absence of any basic change in the relative structure of reported trading volume between NASDAQ and the NYSE is a major puzzle in view of the fact that the majority of the trading in NASDAQ-listed securities has been via electronic order books in recent years. One auction market should look much like another, but we see no signs of convergence between NASDAQ and the NYSE with regard to the structure of trading volume.

The Cost of Being Good

This paper examines the performance of U.S. equities through the use of socially responsible investment screens. We extend the socially responsible investing literature by examining a broader study of social screens. We examine the returns and risk-adjusted returns to investing in socially responsible investment portfolios using twenty social screens from KLD. The approach introduces a simple model of asset returns based on a utility function that incorporates social goals. We also extend the socially responsible investment (SRI) research by examining the persistence in performance of SRI screens using Jensens alpha and conditional alphas. We find that there is no cost to being good by investing according to SRI screens. Investors are no worse off investing in accordance with their social beliefs.

Do Investors Care About Director Tenure? Insights from Executive Cognition and Social Capital Theories

Governance scholars debate the value of directors as an effective governance mechanism. We suggest that this value varies with director tenure. We study both how shareholder assessments of the value of individual directors vary with director tenure and whether director tenure actually makes a practical difference to governance effectiveness. Using data from abnormal stock price reactions to the sudden deaths of 274 outside directors, and integrating executive cognition and social capital perspectives applied to the dual roles of director monitoring and advising, our results confirm a curvilinear relationship between the assessed value of directors and tenure. We find that directors are more highly valued by investors over a tenure period between 7 and 18 years, moderated by director involvement on key committees. Further, in examining the S&P 1,500, we find that a one standard deviation increase in the percentage of outside directors in this prime tenure period strengthens the CEO pay-performance linkage ...

Contingent Claims Analysis Applied in Credit Risk Modeling

A fundamental in credit risk analysis is estimation of the probability that fixed-income securities will migrate to different bond rating categories. Unlike historical transition probabilities, several contingent claims credit risk methodologies simulate the value of a firms assets and/or debt ratio to create bond rating probability distributions. This study tests the validity of using empirically calculated debt ratios to assign bond ratings. The empirical tests provide evidence supporting the use of such methodologies, with some caveats. Debt ratios are industry-specific and time-dependent, so care must be taken in estimating model parameters from historical relationships.

Market Evolution: 1996-2012

We trace the evolution of U.S. stock markets during four time periods: Before Decimalization, from 1996 to 2000, After Decimalization, from 2001 to 2005, Electronic Trading I, from 2006 to 2010, and Electronic Trading II, from 2011 to 2012. The analysis shows how the influence of the basic variables that determine trading volume—shares outstanding, stock prices, and volatility—changed over this time span. The increase in trading volume is related to the decimalization of stock prices, the emergence of electronic stock exchanges in the last decade, and the concomitant increase in algorithmic trading.

Divergent Market Responses to Human Capital Reorganizations

The stock market response to human capital downsizing events is on average negative. Firms maximize value by signalling to investors the types and nature of their capital budgeting decisions. Human capital restructuring is one such capital budgeting signal. This paper expands on previous research by examining market reactions to firm characteristics, specific firm decisions and certain external macroeconomic conditions. We find that the market response to the human capital downsizing events is firm specific and depends on macroeconomic conditions. We confirm our results using robustness testing. For firms responding positively to the downsizing event, size or analyst following, the firm’s technological intensity and simultaneous asset reorganization are significant contributors to the market response. For the positive subsample, a positive movement in the business cycle and the commercialization of the internet are associated with positive market returns for downsizing events. Significant factors for firms responding negatively include potential financial distress and offshoring. Technological intensity is also a significant influence, but is different for the two subsamples. For positive responding firms, the market may perceive that the firm is pro-actively managing its costs. For the negative responding firms, the market may perceive that knowledge workers may not be available when and if the firm recovers. For the negative subsample, commercialization of the internet and white-collar outsourcing intensify the negative market response.