Karel Hrazdil

The price, liquidity and information asymmetry changes associated with new S&P 500 additions

Purpose - Using S&P 500 additions, the purpose of this paper is to test the permanence of abnormal returns around the index inclusion announcement and effective implementation dates to differentiate among competing explanations for the index inclusion premia puzzle. Design/methodology/approach - The event study methodology is used to examine abnormal returns and volume effects around the announcement dates (ADs) and implementation dates of index additions. Findings - This study documents a twofold increase in trading volume and significant permanent abnormal returns at the ADs that are correlated with subsequent decreases in bid-ask spreads. There is a fivefold increase in trading volume, but only temporary abnormal returns, around the effective dates (EDs). Taken collectively, the evidence indicates that the permanent return at announcement is best explained by liquidity/information cost explanation, but the temporary return and large trading increases at the ED can best be attributed to the price pressure hypothesis. Research limitations/implications - These results do not support the well documented long-run downward-sloping demand curve as the primary explanation for the abnormal returns observed on these dates. Originality/value - This study contributes to the body of literature on the index inclusion effect by providing supporting evidence for the liquidity/information cost explanation, and by extending the previously analyzed index additions with an additional five-year period from 2000-2004.

The effect of demand on stock prices: new evidence from S&P 500 weight adjustments

Purpose - Many papers have argued that there are long-run downward-sloping demand curves (LRDDC) for stocks. The purpose of this paper is to analyze this hypothesis using a new, unique, and ostensibly information-free event: the re-weighting of the Standard & Poor (S&P) 500 index from market based to free-float based, which involves a significant shift in supply that, under the LRDDC, should result in significant and permanent price movements. Design/methodology/approach - Event study methodology is used to examine abnormal returns and trading activity around the free-float weight implementation dates for S&P 500 firms with various investable weight factors. Findings - As a result of S&P 500 index re-weighting, affected stocks experience statistically significant excess returns of -1.54 percent during the event week. This return is reversed during the following 30 days as trading volume returns to normal levels. These results are contrary to previous studies that analyze ostensibly informational events and/or different exchanges. Research limitations/implications - Results of this study indicate that arbitrage appears to be effective in eliminating a long-term mispricing, which challenges the validity of the LRDDC hypothesis. Originality/value - This study contributes to the body of literature on the S&P 500 index firms by providing supporting evidence for the price-pressure hypothesis.

S&P 500 Index Inclusion Announcements: Does the S&P Committee Tell Us Something New?

Purpose - The purpose of this paper is to directly examine the information hypothesis of S&P 500 index inclusion announcements by investigating the degree to which information beyond Standard & Poors eight stated criteria enters the inclusion decision. Design/methodology/approach - Isolating a sample of S&P 500 additions and their eligible candidates during 1987-2004, this paper employs logistic analysis that identifies factors Findings - The evidence indicates that, when choosing among new S&P 500 candidates, the S&Ps committee relies primarily on publicly available information related to enterprise risk and historical performance. Material, private insight into future value-relevant information plays at most a small part in the selection. Research limitations/implications - The results suggest that index additions convey limited new information about added firms. Studies analysing index additions should start with the presumption that index inclusion announcements are information-free events, and focus on the consequences of index inclusions such as liquidity, awareness or arbitrage risk, in their relation to index premia. Originality/value - The results indicate that the previous evidence supporting the information hypothesis using the S&P 500 inclusions is not compelling.

Industry classification and the efficiency of intra-industry information transfers

Purpose - – Motivated by recent studies that demonstrate the superiority of the Global Industry Classification System (GICS) relative to the Standard Industry Classification (SIC) system in capital market research, the authors revisit the stock market anomaly documented by Thomas and Zhang (TZ) (“Overreaction to intra-industry information transfers?” Design/methodology/approach - – The authors first replicate TZ and test whether stock prices of late announcers in response to earnings reported by early announcers in the same SIC industry are significantly related to subsequent price responses of late announcers to their own earnings reports. In the multivariate setting, the authors then evaluate whether the magnitude and significance of the overreaction anomaly changes under the more comprehensive GICS and across different time periods. Findings - – The authors first confirm the over-reaction anomaly based on SIC as documented by TZ. Utilizing a larger sample of firms based on the GICS and extending TZ for a new time period, the authors then demonstrate that the overreaction anomaly disappears during recent years, a period that is characterized by markedly higher trading activity. Research limitations/implications - – The findings provide new insights and contributions to the debate on whether or not market significantly misprices information transfers. Originality/value - – The authors are first to utilize the GICS in evaluating intra-industry information transfers.

Disclosure quantity and the efficiency of price discovery: Evidence from the Toronto Stock Exchange

Purpose - We investigate the effect of the information disclosure quantity on the pricing efficiency of stocks. Design/methodology/approach - Using a sample of large and actively traded Canadian companies listed on the Toronto Stock Exchange, we utilize annual reports filed on SEDAR between 2003 and 2013 to estimate the amount of publicly available information and find that the length and size of annual reports are important determinants of short-horizon return predictability from historical order flows, which is an inverse indicator of market efficiency. Findings - Our results show that longer and larger annual reports are associated with reduced information asymmetry, lower cost of immediacy, higher trading activity, and an overall improvement in the efficiency of price discovery. The results are robust to the inclusion of controls for various determinants of short-horizon return predictability, such as trading costs, volatility, informational effects, and other firm-specific characteristics. Research limitations/implications - Collectively, our findings provide empirical support for the benefits of detailed corporate disclosure in Canada. Originality/value - We are the first study to utilize the short-horizon return predictability approach to evaluate the efficiency of price discovery in relation to the amount of information disclosure.

Speed of convergence to market efficiency in the ETFs market

Purpose - The aim of this paper is to examine the informational efficiency of prices of all exchange traded funds (ETFs) that are actively traded on the NYSE Arca, based on methodology developed by Chordia Design/methodology/approach - The authors estimate the speed of convergence to market efficiency based on short-horizon return predictability from past order flows of 273 ETFs that were traded every day on the NYSE Arca during the first six months of 2008, and compare the resulting price formation process to that of shares traded on the NYSE and NYSE Arca. Findings - Despite the significant differences in trading costs, volatility, and informational effects between ETFs and regular stocks, the paper documents that price adjustments to new information for ETFs occur in about 30?minutes, which is comparable to price adjustments for traditional stocks traded on Arca. In multivariate setting, the paper further shows that the speed of convergence to market efficiency of ETFs is not only significantly driven by volume, but also by the probability of informed trading. Research limitations/implications - The findings provide direct answers and insights to questions posed in a recent SEC concept release document. The analysis of the speed of convergence provides a feasible measure to assess how efficiently prices of ETFs respond to new information. Originality/value - The authors are first to utilize the short-horizon return predictability from historical order flow approach to evaluate the price formation process of ETFs and to provide evidence on the determinants of its efficiency.

Measuring CEO Personality Using Machine-Learning Algorithms: A Study of CEO Risk Tolerance and Audit Fees

We rely on recent developments in machine learning and artificial intelligence and use the IBM Watson Personality Insights service to measure personality based on transcripts of Q&A sessions of conference calls made by CEOs. We obtain Big-five personality traits and compute a measure for risk tolerance. We conduct a number of validation tests to show that all personality traits are CEO-specific and not related to firm characteristics and firm performance. We then examine the relation between CEO risk tolerance and audit fees. We find that higher CEO risk tolerance is associated with significantly higher audit fees and that this association is consistent across several Big Five index components. Moreover, we find some evidence that the influence of the CEO’s risk tolerance on audit fees is greater when CEO power is greater. Consistent with upper echelons theory, our results suggest that CEO personalities have an incremental impact on auditors’ assessment of engagement risk.

The effect of industry classification on analyst following and the properties of their earnings forecasts

ABSTRACT Using a comprehensive data set, we compare four broadly available industry classification schemes (Standard Industrial Classification (SIC), North American Industry Classification System (NAICS), Fama–French classification (FF) and Global Industry Classification Standard (GICS)) in their effectiveness to group analysts and their earnings forecast properties. We demonstrate the advantage of the GICS to be consistent across different forecasting properties and across different groups of firms. Our results suggest that GICS should be utilized in research designs, either in the primary analysis or as a necessary corroboration.