Ferhat Akbas

Smart Money, Dumb Money, and Capital Market Anomalies

We investigate the dual notions that “dumb money” exacerbates well-known stock return anomalies and “smart money” attenuates these anomalies. We find that aggregate flows to mutual funds (dumb money) appear to exacerbate cross-sectional mispricing, particularly for growth, accrual, and momentum anomalies. In contrast, hedge fund flows (smart money) appear to attenuate aggregate mispricing. Our results suggest that aggregate flows to mutual funds can have real adverse allocation effects in the stock market and that aggregate flows to hedge funds contribute to the correction of cross-sectional mispricing.

The Calm before the Storm

I provide evidence that stocks experiencing unusually low trading volume over the week prior to earnings announcements have more unfavorable earnings surprises. This effect is more pronounced among stocks with higher short-selling constraints. These findings support the view that unusually low trading volume signals negative information, since, under short-selling constraints, informed agents with bad news stay by the sidelines. Changes in visibility or risk-based explanations are insufficient to explain the results. This evidence provides insights into why unusually low trading volume predicts price declines.

Capital Market Efficiency and Arbitrage Efficacy

Market efficiency requires that arbitrageurs are able to raise the capital needed to arbitrage away mispricing in the cross-section of stock returns. We identify a set of capital constraints that impede the flow of funds to arbitrage strategies. When this flow is particularly curtailed, investors are unable to fully implement arbitrage strategies, allowing some level of inefficiency to persist. In turn, this leads to higher cross-sectional return predictability and stronger performance of arbitrage strategies in the future, as mispricing is eventually corrected. Thus, the degree of market efficiency is not a static concept but varies across time as arbitrage agents face time-varying constraints to arbitrage capital.Efficiency in the capital markets requires that capital flows are sufficient to arbitrage anomalies away. We examine the relation between flows to a quantitative (quant) strategy that is based on capital market anomalies and the subsequent performance of this strategy. When these flows are high, quant funds are able to implement arbitrage strategies more effectively, which in turn leads to lower profitability of market anomalies in the future, and vice versa. Thus, the degree of cross-sectional equity market efficiency varies across time with the availability of arbitrage capital.

Short Interest, Returns, and Fundamentals

We show that short interest predicts future bad news, negative earnings surprises, and downward revisions in analyst earnings forecasts. Moreover, short interest is a better predictor of changes in firm fundamentals for stocks that are harder to short and short sellers appear to have information about these events several months before they become public. Most importantly, the well-known cross-sectional relation between short interest and future stock returns vanishes after controlling for short sellers’ information about future fundamental news. Thus, short sellers contribute in a significant manner to price discovery about firm fundamentals.

Mispricing Following Public News: Overreaction for Losers, Underreaction for Winners

We document an important relation between two well-established anomalies: momentum and short-term reversal. Only stocks with negative momentum experience short-term reversal. Using Chans (2003) news database, we show that the market appears to overreact to public news following bad past performance and underreact following strong past performance. The results are robust to using alternative methodologies. Stocks with current good news and negative momentum earn on average -9.3% annual raw returns during the subsequent month, while stocks with current good news and positive momentum earn 32.2%. The large, negative raw returns point to cognitive biases, rather than risk-based explanations, as the source of abnormal returns.

Determinants and Consequences of Information Processing Delay: Evidence from the Thomson Reuters Institutional Brokers’ Estimate System

We present new evidence that highlights the role of information intermediaries in the distribution and processing of earnings estimates in capital markets. We find that the time taken to activate an analysts earnings forecast in the Thomson Reuters Institutional Brokers’ Estimate System is related to measures of investor demand for timely information processing, processing difficulty, and limited attention. Furthermore, we find that forecast announcement returns are muted and post-announcement drift is magnified for forecasts with longer unexpected activation delay and that market inefficiency is concentrated in neglected stocks and potentially exploitable. Finally, analyzing intraday returns, we find that activations facilitate price discovery.

Do Director Networks Improve Managerial Learning from Stock Prices

We examine whether boardroom connections help managers identify non-fundamental price shocks. We find that managers of well-connected firms are less likely to cut investment in response to exogenous non-fundamental drops in stock prices. Moreover, firms with stronger corporate governance and less managerial entrenchment are more successful at cultivating the informational benefits of boardroom connections. We further find that executive networks and director connections to board members at firms in the same industry are more effective at insulating firm investment from the adverse effects of exogenous non-fundamental shocks. Taken together, our findings suggest that improving managers’ assessment of firm fundamentals is an important channel through which director networks add value to the firm.

Disagreement, Aggregate Trading Volume, and Excess Market Returns

Unusually high aggregate stock trading volume in one week predicts higher excess market returns in the following week, especially when accompanied by high market volatility. This predictive relation is robust across alternative measures of aggregate trading volume. In out-of-sample forecasting tests, unusually high aggregate volume outperforms a host of other variables that have been shown to forecast the equity premium. Our evidence is most consistent with a risk premium associated with shocks to market-wide disagreement among market participants. Return autocorrelations, visibility effects, and market sentiment do not explain our findings.

Do Individual Investors Have Information Processing Skills

Combining a large archive of public corporate news events with retail trading records from NYSE, we examine the profitability of individual investors’ trades around public news releases. We find that individual investors benefit significantly from the news releases when trading. The relation between net trading by individual investors and future returns is four times as large on positive news days as that on no news days. Moreover, the results are more pronounced for firms with higher information uncertainty and at times of high market uncertainty. Individual investors do not anticipate news and our results are not explained by liquidity provision, higher investor attention, or changes in liquidity around news days. Overall, the evidence suggests that an important channel through which individual traders predict future stock returns is their ability to successfully process the information revealed in the news events.Combining a large archive of public corporate news events with retail trading records from NYSE, we examine the profitability of individual investors’ trades around public news releases. We find that individual investors benefit significantly from the news releases when trading. The relation between net trading by individual investors and future returns is four times as large on positive news days as that on no news days. Moreover, the results are more pronounced for firms with higher information uncertainty and at times of high market uncertainty. Individual investors do not anticipate news and our results are not explained by liquidity provision, higher investor attention, or changes in liquidity around news days. Overall, the evidence suggests that an important channel through which individual traders predict future stock returns is their ability to successfully process the information revealed in the news events.

Determinants and consequences of information processing delay: Evidence from the Thomson Reuters Institutional Brokers’ Estimate System

We present new evidence that highlights the role of information intermediaries in the distribution and processing of earnings estimates in capital markets. We find that the time taken to activate an analysts earnings forecast in the Thomson Reuters Institutional Brokers’ Estimate System is related to measures of investor demand for timely information processing, processing difficulty, and limited attention. Furthermore, we find that forecast announcement returns are muted and post-announcement drift is magnified for forecasts with longer unexpected activation delay and that market inefficiency is concentrated in neglected stocks and potentially exploitable. Finally, analyzing intraday returns, we find that activations facilitate price discovery.