Market Structure and Stock Splits

Enhanced liquidity is one possible motivation for stock splits but empirical research frequently documents declines in liquidity following stock splits. Despite almost thirty years of inquiry, little is known about all the changes in a stock's trading activity following a stock split. We examine how liquidity measures change around more than 2,500 stock splits and find a pervasive decline in most measures. Large stock splits exhibit a more severe liquidity decline than small stock splits, especially on Nasdaq. We also examine a longer time period around stock splits and find that the differences between small and large stocks may be short-lived. Following the 1997 changes in order handling rules and reduction in tick size, liquidity declines following stock splits continue, however, the declines are not as severe on Nasdaq, suggesting the change in order handling rules may have been effective.

Modelling Adverse Selection on Electronic Order-Driven Markets

The vast majority of models that decompose the bid/ask spread assume the quote-driven, specialist structure of the NYSE. This paper critically evaluates these models to construct a model specific for an electronic order-driven exchange. The model not only captures adverse selection and the impact of order flows on price discovery but it includes the imbalance of supply and demand inherent in the public limit order book. With this new model we investigate the change to anonymity on the Australian Securities Exchange (ASX). Following the change to anonymity, both adverse selection and the demand/supply imbalance have an increased impact on prices while order flow has a decreased influence, suggesting the change to anonymity has improved market efficiency. The model also uncovers a change in traders’ behavior once their fear of front-running is reduced. We show that the model is stable and robust across high liquidity stocks as well as stocks with as few as 5 trades per day.bid-ask spread models; adverse selection; anonymity

Intraday REIT Liquidity

Real Estate Investment Trusts (REITs) may be classified as a real estate investment or more generally as an equity investment. While REITs are more liquid than direct real estate investments, the liquidity relationship between REITs and common stocks is less clear-cut. This study measures and analyzes the liquidity differences between REITs and other common stocks. The intraday variations documented in this study have implications for: 1) the appropriate timing of trades to minimize transaction costs and, 2) the substitutability of investments if illiquidity is priced. Our results reveal intraday patterns indicating lower liquidity for REITs than for common stocks when the liquidity measure is friction-based. In contrast, activity measures exhibit higher liquidity levels for REITs than for common stocks but this difference is only statistically significant at the beginning of the trading day. Finally, from an economic perspective we find that the ability to trade without influencing prices is 15-25% greater for non-REITS compared to REITs, and the price of immediacy is 7% higher for REITs.

The Impact of Specialist and Multiple Dealer Market Structures on Intraday Price Formation and Bid-Ask Spread Components.

This dissertation investigates specialist and multiple dealer markets. In the first of four essays, simultaneous trading in two market structures on the Paris Bourse is used to evaluate intraday price formation. Specialists are found to exacerbate the end of day price rise. Stock volatility and bid-ask spreads are found to be larger when a specialist is present, in contrast to existing literature that compares market structures on different exchanges. The second essay estimates the components of the bid-ask spread and trade execution costs on the Paris Bourse. Estimates of the adverse selection cost component do not resolve the conflicting findings in existing literature regarding the relative size of this component in different market structures. A larger inventory holding cost component is identified for stocks that trade with the aid of a specialist, confirming the specialists\u27 cost of maintaining an inventory. Higher trading costs are found for those stocks that trade with the aid of a specialist in contrast to existing literature, suggesting previous findings are exchange-specific. Long-term inventory changes are investigated and the impact on the inventory holding cost component is found to be twice as large for those stocks with a specialist. The third essay examines specialist firms on the New York Stock Exchange. Differences are observed in the bid-ask spread, volatility and bid and ask depths. Likewise, final transaction returns differ across specialist firms indicating that the end of day price rise may be a method used by specialist firms to manage end of day prices. This is corroborated by observing minimal differences within each specialist firm. Short-term changes in inventory are investigated and extreme inventory changes are shown to have smaller bid-ask spreads. Depletion of inventory is associated with a larger bid-ask spread than a build-up. Essay four investigates the change in the rules governing market on close orders on the New York Stock Exchange. The new rules require earlier submission of orders. Minimal differences in the end of day price rise are found between the period before and after the rule change, however, volatility levels are found to decline for nine of thirty-seven specialist firms

Price discovery in stock and options markets

Using new empirical measures of information leadership, we find that the role of options in price discovery is up to five times larger than previously thought. Approximately one-quarter of new information is reflected in options prices before being transmitted to stock prices, with options playing a more important role in price discovery around information events. Using unique data on traders prosecuted for insider trading, we find that they often choose to trade in options, attracted by their leverage, and when they do the options share of price discovery is higher. Our results help interpret conflicting findings in the existing literature

Turnover, account value and diversification of real traders: evidence of collective portfolio optimizing behavior

Despite the availability of very detailed data on financial market, agent-based modeling is hindered by the lack of information about real trader behavior. This makes it impossible to validate agent-based models, which are thus reverse-engineering attempts. This work is a contribution to the building of a set of stylized facts about the traders themselves. Using the client database of Swissquote Bank SA, the largest on-line Swiss broker, we find empirical relationships between turnover, account values and the number of assets in which a trader is invested. A theory based on simple mean-variance portfolio optimization that crucially includes variable transaction costs is able to reproduce faithfully the observed behaviors. We finally argue that our results bring into light the collective ability of a population to construct a mean-variance portfolio that takes into account the structure of transaction costsComment: 26 pages, 9 figures, Fig. 8 fixe

The rise and fall of single-letter ticker symbols

A single-letter stock ticker symbol is a limited resource - only 26 possibilities are available in a stock universe of over 475,000 possible one-, two-, three- or four-letter ticker symbols. These symbols were first allocated based on trading volume therefore some of the most important companies at the time were initially placed into this group. This paper examines the history of this group of stocks and documents a decline in the importance of these firms due to a natural turnover in commercial leadership and no established mechanism to remove the single-letter designation from firms that lost their prominence.ticker symbols, American big business, New York Stock Exchange,

The Effects of High Frequency Trading in a Multi-Asset Model

High frequency traders have largely replaced human liquidity providers in US equity markets. This has increased market efficiency, reduced transaction costs, and increased volumes. We develop a model that can explain how and why this has occurred: -Similar to the Glosten and Milgrom (1985) model, but with multiple securities. -We add an automated market maker who trades across securities and understands the relationships between their end-of-period values. -This new participant: 1. Transacts the majority of orders. 2. Makes prices more efficient. 3. Increases informed and decreases uninformed traders transaction costs. -As a result: 1. Volumes increase. 2. Overall transaction costs are reduc

Stock Splits and Bond Yields: Isolating the Signaling Hypothesis

One explanation offered for stock splits is that the split signals positive information by reducing the stock price range in expectation of improved future prospects. Price declines also lead to changes in stock price dynamics, but related securities are not subject to these other changes and therefore can be used to provide a separate assessment of the markets' interpretation of the split. We examine corporate bond issues around stock splits and find a significant decline in the bond yield spread following stock splits, supporting the signaling hypothesis. We also confirm improvements in forecasted and realized earnings subsequent to stock splits. Copyright (c) 2010, The Eastern Finance Association.