Stock Splits and Liquidity: The Case of the Nasdaq-100 Index Tracking Stock

In an attempt to disentangle the signaling effect from the liquidity effect of stock splits, I examine the liquidity changes following the two‐for‐one split of the Nasdaq‐100 Index Tracking Stock. Since there can be no signaling with an index stock split, any difference between pre‐ and postsplit trading may be driven by liquidity but not signaling effects. I find that though the postsplit relative bid‐ask spread is higher and daily turnover is unchanged, the frequency, share volume, and dollar‐volume of small trades all increased after the split, indicating that the split improved liquidity for small trade‐sizes.     

WHEN‐ISSUED SHARES,SMALL TRADES,AND THE VARIANCE OF RETURNS AROUND STOCK SPLITS

The increases in volatility after stock splits have long puzzled researchers. The usual suspects of discreteness and bid‐ask spread do not provide a complete explanation. We provide new clues to solve this mystery by examining the trading of when‐issued shares that are available before the split. When‐issued trading permits noise traders to compete with a more homogenous set of traders, decreasing the volatility of the stock before the split. Following the split, these noise traders reunite in one market and volatility increases. Thus, the higher volatility after the ex date of a stock split is a function of the introduction of when‐issued trading, the new lower price level after the split date, and the increased activity of small‐volume traders around a stock split.     

Stock Splits, Tick Size, and Sponsorship

A traditional explanation for stock splits is that they increase the number of small shareholders who own the stock. A possible reason for the increase is that the minimum bid-ask spread is wider after a split and brokers have more incentive to promote a stock. I document a large number of small buy orders following Nasdaq and NYSE/AMEX splits during 1993 to 1994. I also find strong evidence that trading costs increase, and weak evidence that costs of market making decline following splits. This is consistent with splits acting as an incentive to brokers to promote stocks.     

CHANGES IN TRADING ACTIVITY FOLLOWING STOCK SPLITS AND THEIR EFFECT ON VOLATILITY AND THE ADVERSE-INFORMATION COMPONENT OF THE BID-ASK SPREAD

We examine changes in trading activity around stock splits and their effect on volatility and the adverse-information component of the bid-ask spread. Even after controlling for microstructure biases, we find a significant increase in volatility after the split. Changes in total volatility and in its permanent component are positively related to changes in the number of trades. This suggests that both informed and noise traders contribute to changes in trading activity. Further, while the adverse-information component of the spread increases unconditionally after the split, the change is negatively related to the change in trading activity. The results suggest that a crucial determinant of liquidity changes after a stock split is the success of the split in attracting new trades in the security.     

TRADING PATTERNS OF SMALL AND LARGE TRADERS AROUND STOCK SPLIT EX-DATES

We investigate the trading patterns of small and large traders around stock split ex-dates. Using the intraday transaction database for the Toronto Stock Exchange during 1983–89, we find that stock splits are associated with significant changes in trading patterns. Although stock splits appear to have little effect on the trading behavior of large traders (trade value of at least $100,000), they are associated with significant decreases in odd-lot trading and increases in small board-lot trading (trade value of less than $10,000). Although the liquidity premia decrease for all trade sizes, trade direction changes significantly from sell to buy after split ex-dates for all but the large trades, where the change is in the opposite direction. The significant increase in variances after split ex-dates is explained by various microstructure-related variables, and small (large) trades appear to be (de)stabilizing.     

The Market Reaction to Stock Splits

In this paper, a model of market reaction to stock splits is presented and tested. We argue that the announcement of a split sets off the following chain of events. The market recognizes that, subsequent to the (reverse) split ex-day, the daily number of transactions along with the raw volume of shares traded will increase (decrease). This increase in volume results in an increase in the noisiness of the security's return process. The increase in noise raises the tax-option value of the stock, and it is this value that generates the announcement effect of stock splits. Empirical evidence using security returns, daily trading volume, and shareholder data strongly supports this theory. The evidence, in conjunction with this theory, also agrees with extant literature that splits result in decreased liquidity, but there is no evidence that this reduction in liquidity is priced.     

Stock‐Split Post‐Announcement Returns: Underreaction or Market Friction?

We explore the relationship between stock splits and subsequent long‐term returns during the period from 1950 to 2000. We find that, contrary to much previous research, firms do not exhibit positive long‐term post‐split returns. Instead, we find that significant positive returns after the announcement date do not persist after the actual date of the stock split. We also observe that abnormal returns are correlated with the price‐delay or market friction. We conclude that the stock‐split post‐announcement “drift” is only of short duration, and it is attributable to trading frictions rather than behavioral biases.     

The information content of stock splits

This study examines whether stock splits contain information content about future operating performance or whether splits are undertaken by firms to realign their share prices and to improve trading liquidity. In the four years following split announcements, splitting firms do not experience improved operating performance relative to non-splitting firms. Furthermore, stock split signals are not related to future profitability. The positive announcement effect can be explained by lower share prices and improved market liquidity following stock splits but not by split signals and post-split operating performance. Our results show very little evidence that stock splits signal improvement in long-run operating performance and are more consistent with the trading range/liquidity hypothesis.     

Stock Splits in Switzerland: To Signal or Not to Signal?

In Switzerland, the existence of a mandatory minimum par value inhibited many companies from splitting their stocks as they already traded at their minimum par value. These Swiss companies could split their stocks only after the legal minimum par value was lowered in July 1992 and again in May 2001. These two events provide rare opportunities to distinguish between stock splits that signal a permanent increase in stock price and splits that are merely a reaction to a regulatory change and thus have other motives. The significant return differences between the two samples are in line with the hypothesis that splits are a means to send positive signals to the stock market. Furthermore, while trading volumes remained largely unaffected after stock splits, relative tick sizes generally increased after a stock split, and bid-ask spreads often increased after a stock split.     

Stock splits, trading continuity, and the cost of equity capital

We hypothesize that managers use stock splits to attract more uninformed trading so that market makers can provide liquidity services at lower costs, thereby increasing investors’ trading propensity and improving liquidity. We examine a large sample of stock splits and find that, consistent with our hypothesis, the incidence of no trading decreases and liquidity risk is lower following splits, implying a decline in latent trading costs and a reduced cost of equity capital. Further, split announcement returns are correlated with the improvements in both liquidity levels and liquidity risk. Our analysis suggests nontrivial economic benefits from liquidity improvements, with less liquid firms benefiting more from stock splits.     

Corporate social responsibility and stock split

This study examines whether socially responsible companies are likely to conduct a stock split. We argue that these companies, compared to their counterparts, could use their strong corporate social responsibility (CSR) performance to reduce information asymmetry with shareholders, and therefore, are less likely to rely on stock splits to signal their future growth potentials. We find empirical evidence to support our hypothesis and investigate the reasons for the lower frequency of stock splits among CSR oriented firms. We find that more socially responsible firms experience a smaller increase in trading volume and a greater increase in bid-ask spread following a stock split than less socially responsible firms. Furthermore, our study finds that, when more socially responsible firms decide to conduct a stock split, they attract a greater proportion of institutional investors with long-term investment horizons.

     

Stock splits to profit insider trading: Lessons from an emerging market

Stock splits have long presented financial puzzles: Why are they undertaken? Why are they associated with abnormal returns? Abnormal returns, particularly those coming shortly before a split’s announcement date, should raise strong suspicions of insider trading, particularly in nations with weak regulatory structures. We examined the 718 split events in the emerging stock market of Vietnam from 2007 through 2011. We found evidence consistent with illegal insider trading, particularly in firms that were vulnerable to insider manipulation and, therefore, more likely to split their stocks. When vulnerable firms’ stocks did split, they provided significant excess short-term returns. Tellingly, the abnormal returns on those stocks prior to the split announcements were also extremely high, indeed higher than their abnormal post-announcement returns. Moreover, trading volume increased prior to the split announcement date. This suspicious pattern is what we would expect if insiders were trading on their knowledge. We propose that illegal insider trading in contexts where it is possible to escape serious penalty provides a previously undiscussed and cogent explanation for both stock splits and abnormal short-term returns.     

Long-run Performance after Stock Splits: 1927 to 1996

We measure the postsplit performance of 12,747 stock splits from 1927 to 1996 using two methods to measure abnormal returns: size and book‐to‐market reference portfolios with bootstrapping, and calendar‐time abnormal returns combined with factor models. Between 1927 and 1996, neither method applied to splits 25 percent or larger finds performance significantly different from zero. Over selected subperiods, subsamples of 2–1 splits restricted by book‐to‐market availability requirements display positive abnormal returns using some methods. However, these samples show small or negligible abnormal returns using the calendar‐time method. Overall, the stock split evidence against market efficiency is neither pervasive nor compelling.     

Noise trading and the price formation process

This study proposes the dispersion in daily net initiated order flow across brokers as a proxy for the level of noise trading in a stock, and applies this proxy to test some basic implications of market microstructure theory. We use data from the Australian Stock Exchange, a computerized limit order market where price, quantity, and broker identity for each incoming order are shown on broker screens. We find daily movements in our noise measure are positively associated with trading volume and market depth, and negatively related to the bid-ask spread. We find monthly movements in our noise measure are negatively associated with the probability of informed trading, and positively correlated with the arrival rate of uninformed traders. We also find the sensitivity of stock prices to net initiated order flow decreases in the level of noise trading. In addition we find that, after controlling for noise trading, the sensitivity of stock prices to net initiated order flow is significantly greater on Mondays. These empirical results consistently support the implications of various models of market microstructure, suggesting that our proxy provides useful information as a daily measure of noise trading.     

A Note on Affordability and the Optimal Share Price

Despite the increase in institutional ownership, decreased trading costs, and increased real personal savings, we find that the average stock price is lower today than it was in the 1920s. In the aggregate, the propensity to split is a function of recent market performance, personal savings, and the desirability of appearing to be a small firm. Our results indicate that, after decades of inflation and the average stock price falling, splitting stocks to return to an "affordable" trading range must be rejected as an explanation. This suggests that other economic forces are behind splits, whether traditional or behavioral in nature.     

Volatility and trading activity following changes in the size of futures contracts

This paper has two purposes. First, we examine the relationship between daily price volatility and trading activity one year before and after a change in contract size by examining the results of contract splits in the Australian share price index futures and the U.K. FTSE-100 futures contracts and a reverse contract split in the Australian Bank Bill Acceptance futures contract. Second, we evaluate the effect of the change in contract size on the use of the particular futures market. We find that after a contract size change, the change in total trading frequency has the power to explain the change in daily price volatility. Specifically, after a contract split, trading frequency increased, resulting in increased daily price volatility, and vice versa after a reverse contract split. Most of the average trade size variable has an immaterial impact on price volatility. However, decomposing the total trading frequency into four trade size classes, we find that the trading frequency for small and large trade size categories are highly significant in explaining changes in daily price volatility after the contract splits. Finally, we find the change in contract size for each futures market was successful because within three years following the change, the adjusted trading volume and open interest surpassed the levels prior to the change and have continued to increase thereafter.     

Do Proprietary Algorithmic Traders Withdraw Liquidity during Market Stress?

We investigate the role of proprietary algorithmic traders in facilitating liquidity in a limit order market. Using order‐level data from the National Stock Exchange of India, we find that proprietary algorithmic traders increase limit order supply following periods of both high short‐term stock‐specific volatility and extreme stock price movement. Even following periods of high marketwide volatility, they do not decrease their supply of liquidity. We define orders from high‐frequency traders as a subclass of orders from proprietary algorithmic traders that are revised in less than three milliseconds. The behavior of high‐frequency trading mimics the behavior of its parent class. This is inconsistent with the theory that fast traders leave the market when stress situations arise, although their limit‐order‐supplying behavior becomes weaker when the increase in short‐term volatility is more informational than transitory. Agency algorithmic traders and nonalgorithmic traders behave opposite to proprietary algorithmic traders by reducing the supply of liquidity during stress situations. The presence of faster traders in the market possibly instills the fear of adverse selection in them. We document that the order imbalance of agency algorithmic traders is positively related to future short‐term returns, whereas the order imbalance of proprietary algorithmic traders is negatively related to future short‐term returns.     

Why Do Traders Split Orders?

We examine factors that influence decisions by U.S. equity traders to execute a string of orders, in the same stock, in the same direction, around the same time. Order splitting is more likely to occur when traders submit larger‐size orders and when market depth and trading activity are lower. Order splitters demand liquidity more and pay higher trading costs, but their overall performance is better. When controlling for execution time, split orders are more informative than single orders. Our results suggest that order splitting arises from a variety of factors, including informational differences, order and trader characteristics, and market conditions.     

Trade Disclosure,Information Learning and Securities Market Performance

In this paper we examine the effect of information disclosure on securities market performance when liquidity traders are able to acquire information about inside trading. We show that the bid-ask spread increases with the liquidity trader's learning efficiency, which is greater when trade information is disclosed. The bid-ask spread is always higher when trade information is not disclosed. However, the discrepancy between the bid-ask spreads with and without information disclosure narrows when the learning efficiency increases. We also show that the gains of the informed traders in a market without trade information disclosure are reduced in the presence of the liquidity trader's learning. Nevertheless, liquidity traders do not necessarily benefit from increased transparency. In particular, liquidity traders may face higher trading costs.     

Do Market Makers Suffer from Splitting Headaches?

Studies of transactions surrounding stock split ex-dates often conclude that splitting firms either experience a decline or an improvement in their stock's liquidity, based on independent measures of trading costs and trading activity. In contrast, our evidence suggests that splits from outside into what often is deemed to be the optimal stock price range of $10.00 to $39.99 are nonevents for market makers: The spread-setting behavior of the market does not change after a split. Our analysis accounts for the interdependencies between bid-ask spreads and market microstructure effects and distinguishes between optimal and all other splitting firms.