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.     

Investor Sentiment,Trading Behavior and Informational Efficiency in Index Futures Markets

This paper shows that traders in index futures markets are positive feedback traders—they buy when prices increase and sell when prices decline. Positive feedback trading appears to be more active in periods of high investor sentiment. This finding is consistent with the notion that feedback trading is driven by expectations of noise traders. Consistent with the noise trading hypothesis, order flow in index futures markets is less informative when investors are optimistic. Transitory volatility measured at high frequencies also appears to decline in periods of bullish sentiment, suggesting that sentiment‐driven trading increases market liquidity.     

Volatility increases Subsequent to NYSE and AMEX Stock Splits

The post-split increase in daily returns volatility is less for AMEX stocks than for NYSE stocks. The exchange trading location is a significant factor in explaining the volatility shift even after stock price and firm size are considered. Furthermore, when measured on a weekly basis, there is no increase in AMEX stocks' returns volatility. These results suggest that measurement errors created by bid-ask spreads and the 1/8 effect, and also one or more of the elements that make the NYSE different from the AMEX, explain why the estimated volatility of daily stock returns increases after the ex split date.     

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.     

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.     

Are margin traders informed?

The literature offers contradictory views on the informativeness of margin trading using various measures of information content. Utilising data from a Chinese margin‐trading pilot programme initiated in 2010, this paper investigates whether margin traders are informed by directly examining the return predictability of margin‐trading activity. We find that margin‐trading activities cannot positively predict future stock returns. Moreover, we explore some non‐informational trading strategies used by margin traders, e.g., positive‐feedback strategies and moving‐average trading rules. These results suggest that margin traders are noise traders rather than informed traders, and margin trading conveys no new firm‐specific information.     

INFORMATION AND NOISE IN FINANCIAL MARKETS: EVIDENCE FROM THE E‐MINI INDEX FUTURES

I examine the informational contributions and effects on transitory volatility of trades initiated by different types of traders in three actively traded index futures markets. The results show that trades initiated by exchange member firms account for more than 60% of price discovery during the trading day. These institutional trades appear to be more informative than trades of individual exchange members or off‐exchange traders. I also find that off‐exchange traders introduce more noise into the prices than do exchange members. My findings provide new evidence on the role of different types of traders in the price formation process.     

INFORMATION ASYMMETRY AND OPTIONS TRADING

This paper demonstrates that options trading does not have a uniform impact on the volatility of underlying stocks. Although uninformed traders are able to hedge the risk of underlying stocks by maintaining opposite positions in the options market, informed traders hold outright options positions to capitalize on their information. This hedging behavior tends to reduce noise in the stock market, whereas the speculating behavior tends to generate noise in the stock market. As a result, stocks that were originally volatile, i.e., traded primarily by uninformed traders, will be stabilized by the introduction of options. Conversely, stocks that were more stable become destabilized by options trading.     

Individual Investors and Volatility

We show that retail trading activity has a positive effect on the volatility of stock returns, which suggests that retail investors behave as noise traders. To identify this effect, we use a reform of the French stock market that raises the relative cost of speculative trading for retail investors. The daily return volatility of the stocks affected by the reform falls by 20 basis points (a quarter of the sample standard deviation of the return volatility) relative to other stocks. For affected stocks, we also find a significant decrease in the magnitude of return reversals and the price impact of trades.     

A microstructure examination of trading activity following stock splits

In a study of 1,131 stock splits spanning the period 1983–1989 we observe an increase in the number of trades as well as a reduction in the mean trade size following the split. Combined with earlier reported findings of an increase in the number of shareholders postsplit, we conclude that the number of liquidity traders increases after a split. We confirm the previously observed increase in the bid-ask spread following a split, and upon decomposition of the spread find an increase in its adverse selection component in the postsplit period. This is consistent with the finding by Brennan and Hughes (1991) of an increase in the number of analysts following a stock after a split. Further, observing a decrease in market depth following a split we determine that Kyle-type models incorporating diverse private information for informed traders most correctly describe the nature of security trading. Since this decrease in postsplit market depth is not related to the trading volume or the split factor, we reject price correction explanations for stock splits.     

Emerging from Bankruptcy with When‐Issued Trading

We examine the set of firms that emerged from Chapter 11 bankruptcy and traded on a when‐issued basis before their official return to the regular way in NASDAQ, Amex, or NYSE. We find that this when‐issued market is liquid and price efficient. The when‐issued closing price is a good indicator of the first closing price in the regular way market. Emerging firms that have when‐issued trading experience lower regular way volatility and smaller relative spreads than those without when‐issued trading. Our probit regressions show that firm size is an important determinant of the adoption of when‐issued trading.     

Insider trading,stock return volatility,and the option market's pricing of the information content of insider trading

We find strong evidence that net insider selling is positively associated with future stock return volatility, consistent with insider selling increasing outside investors’ uncertainty. The positive effect of net insider selling is significantly stronger when the volatility is measured around the earnings announcement. Apparently, option prices do not fully reflect the information content of insider trading for future volatility. More specifically, we find no evidence that option traders adjust the implied volatility for the insider trading effect in a timely manner. Consequently, net insider selling is significantly associated with future option straddle returns and delta neutral returns.     

Noise traders, excess volatility, and a securities transactions tax

Proponents of a securities transactions tax have suggested that such a tax may reduce stock return volatility. The argument is that, to the extent that short-term speculative trading volume is the source of excess volatility, a tax that reduces such volume will reduce volatility. In the context of a simple general equilibrium model, it is shown that this partial equilibrium argument is misleading and in large part incorrect. In the absence of a tax, the model generates equilibria in which the risky asset's price exhibits excess volatility and agents engage in excess trading activity owing to the presence of destabilizing noise traders. Within the context of the model, it is shown that, although a transactions tax can reduce the volatility of the risky asset's price, the reduction in price volatility is accompanied by a fall in the asset's price as agents discount the future tax liability associated with risky asset ownership. Consequently, although price volatility may decrease slightly, the fall in equilibrium prices more than compensates, and the volatiltiy of risky asset returns unambiguously increases with the level of the transactions tax.Board of Governors of the Federal Reserve SystemThe conclusions herein are those of the author and do not represent the views of the Federal Reserve Board or any of the Federal Reserve Banks.     

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.     

Competition among Trading Venues: Information and Trading on Electronic Communications Networks

This paper explores the competition between two trading venues, Electronic Communication Networks (ECNs) and Nasdaq market makers. ECNs offer the advantages of anonymity and speed of execution, which attract informed traders. Thus, trades are more likely to occur on ECNs when information asymmetry is greater and when trading volume and stock‐return volatility are high. ECN trades have greater permanent price impacts and more private information is revealed through ECN trades than though market‐maker trades. However, ECN trades have higher ex ante trading costs because market makers can preference or internalize the less informed trades and offer them better executions.     

Does Price Discreteness Affect the Increase in Return Volatility Following Stock Splits?

Stock return volatility tends to increase significantly following stock splits. One potential cause of this is the trading of stocks in discrete price intervals called ticks. This study provides a direct test of price discreteness as a determinant of this phenomenon by examining variance increases before and after the 1997 date when the exchanges reduced the tick size from 1/8 to 1/16. Results generally show that the post-split variance increase was unaffected by the reduction in tick size even after controlling for other factors. AMEX stocks proved the exception, with slightly lower variance increases following the tick size reduction.     

The UK equity market around the ex-split date

Using UK stock market data this study unveils positive abnormal returns on and around the ex-split date. These excess returns are partially predictable using the publicly available information prior to the ex-split date. There is also a persistent increase in the post-split volatility of these stocks with the results being robust to the choice of the volatility proxy. Post-split volatility is found to be positively related to trading activity. Contrary to the US findings, volatility dynamics following the stock split are better captured by changes in the daily trading volume rather than by the number of trades.     

Entry, exit and trading profits: A look at the trading strategies of a proprietary trading team

We examine the behavior of a 15 strong proprietary stock trading team and show how consistent intraday trading profits were generated. The team, who worked for a large US direct access trading firm, executed over 96 thousand trades in 3 months in 2000. Profitable intraday trading occurred in an anonymous dealer capacity, on both long and short positions, especially when volume and price volatility were higher. The traders rapidly entered long (short) positions when the number of dealers and size become greater on the bid (offer) side of the spread. Profits were taken early against the trend.     

The innovations of e-mini contracts and futures price volatility components: The empirical investigation of S&P 500 stock index futures

The effect of the initiation of e-mini stock index futures (ESIFs) on the volatility components of S&P 500 stock index futures is herein investigated. The study decomposes S&P 500 stock index-related observed volatilities into unobserved fundamental volatility and transitory noise and utilizes the decomposition to test two hypotheses: the “clientele factor hypothesis” and the “information adjustment hypothesis”. The first hypothesis proposes that the ESIFs attract more noisy traders who prefer trading the friendly-size futures contracts. The second one proposes that the innovations of ESIFs improve the information flow of the futures markets. Using a stochastic volatility model, the empirical results are consistent with both of our proposed hypotheses.