Market Created Risk

We develop a multiperiod rational expectations model of securities market equilibrium in which equilibrium prices may move between periods even though it is common knowledge that no new information has arrived about ultimate security payoffs. This happens because investors know they have imperfect information about the endowments of other investors and this knowledge affects their probability beliefs about the prices that will prevail at the intermediate trading date. These beliefs are reflected in the equilibrium at the initial trading date when investors focus on the probabilities of intermediate capital gains and losses, rather than ultimate payoffs.     

A Theory of Trading Volume

A theory of trading volume is developed based on assumptions that market agents frequently revise their demand prices and randomly encounter potential trading partners. The model describes two distinct ways informational events affect trading volume. One is consistent with conjectures made by empirical researchers that investor disagreement leads to increased trading. But the observation of abnormal trading volume does not necessarily imply disagreement, and volume can increase even if investors interpret the information identically, if they also have had divergent prior expectations. Simulation tests support the model and are used to contrast the random-pairing environment with costless market clearing. Volume is lower in the costly market, and volume increases caused by an informational event persist after the event period. This is consistent with existing empirical evidence and suggests that markets do not immediately clear all orders or that investors have demands to recontract.     

Crushed by a rational stampede: Strategic share dumping and shareholder insurrections

In this paper, we develop a dynamic model of institutional share dumping surrounding control events. Institutional investors sometimes dump shares, despite trading losses, in order to manipulate share prices and trigger activism by “relationship” investors. These institutional investors are motivated to trade not only by trading profits but also by a desire to protect the value of their inventory and to disguise the quality of their own information. Relationship investor profit from targeting firms both by improving firm performance and by generating private information.     

Optimal stock trading with personal taxes: Implications for prices and the abnormal January returns

The tax law confers upon the investor a timing option - to realize capital losses and defer capital gains. With the tax rate on long term gains and losses being about half the short term rate, the law provides a second timing option - to realize losses short term and gains long term, if at all. Our theory and simulation over the 1962–1977 period establish that taxable investors should realize long term gains in high variance stocks and repurchase stock in order to realize potential future losses short term. Tax trading does not explain the small-firm anomaly but predicts a seasonal pattern in trading volume which maps into a seasonal pattern in stock prices, the January anomaly, only if investors are irrational or ignorant of the price seasonality.     

Endogenous informed trading in the presence of trading costs: Theory and evidence

The basic premise of the model we propose is that market frictions (trading costs) force traders with market-wide information to strategically choose which securities to trade in. We study the effect of recognizing trading costs on the choices of informed traders and the resulting statistical properties of security prices. Specifically, we show that (1) stocks with intermediate β's have the least informative prices, even though they are traded by the greatest number of informed traders; (2) for high β securities, the contemporaneous correlation of prices is close to the correlation in fundamental values; (3) a security with a higher β, higher volume of liquidity trading and lower idiosyncratic variance is more likely to lead another security. With market capitalization as a proxy for the level of liquidity trading, these specific predictions of the model on the lead–lag relationship are also shown to be strongly supported by the data.     

The Size and Incidence of the Losses from Noise Trading

Recent empirical research has identified a significant amount of volatility in stock prices that cannot easily be explained by changes in fundamentals; one interpretation is that asset prices respond not only to news but also to irrational “noise trading.” We assess the welfare effects and incidence of such noice trading using an overlapping-generations model that gives investors short horizons. We find that the additional risk generated by noise trading can reduce the capital stock and consumption of the economy, and we show that part of that cost may be borne by rational investors. We conclude that the welfare costs of noise trading may be large if the magnitude of noise in aggregate stock prices is as large as suggested by some of the recent empirical litrature on the excess volatility of the market.     

FT coverage and UK target price run-ups

We focus on the market expectation hypothesis to explain the increase in share prices and trading volume of target firms before their merger announcements that have conventionally been attributed to either insider trading or market expectation. We use Financial Times (FT) coverage as a proxy of merger expectation and search for relevant articles for 783 UK target firms between 1998 and 2010. We identify a total of 1049 rumour articles and find that the FT market expectation proxy explains a small percentage of the target price run-ups. Results are strong during the sample period, even though the magnitude for both returns and trading volume tends to decrease within recent years. There is also a strong contemporaneous relation between abnormal returns and trading volume. Unexplained increases in target prices and trading volume may be attributed to insider trading.     

Trading around macroeconomic announcements: Are all traders created equal?

This paper examines the effects of macroeconomic announcements on equity index markets using high frequency transactions data for the regular and E-mini S&P 500 index futures contracts. For ten types of announcements that significantly affect prices, we analyze the price adjustment process and the trading patterns of exchange locals and off-exchange customers around the announcements. We find a large increase in trading activity immediately after the announcement. The results also show that during this initial surge in trading activity, locals are able to time their trades better than off-exchange traders even when locals do not have the advantage of access to the order flow. The trading strategy followed by exchange locals in the first 20 seconds after the announcement tends to be profitable, while off-exchange traders tend to make losing trades over the same time period. These results lend evidence that local traders tend to react to the macroeconomic information faster than off-exchange traders.     

Market ecologies: The effect of information on the interaction and profitability of technical trading strategies

Technical trading strategies make profits by identifying and exploiting patterns in market prices—patterns generated by the interaction of market participants. Using a model market populated by individuals using a range of trading rules we show that the presence of technical traders may be beneficial, in some cases reducing volatility and increasing price efficiency. In particular, contrarian traders who base their decisions on high frequency data have the largest positive effect. It is also found that if technical traders condition their actions using ‘real time’ information, they partially emulate arbitrageurs and make positive profits.     

An evolutionary multi‐objective optimization of trading rules in call markets

We evaluate an agent‐based model featuring near‐zero‐intelligence traders operating in a call market with a wide range of trading rules governing the determination of prices and which orders are executed, as well as a range of parameters regarding market intervention by market makers and the presence of informed traders. We optimize these trading rules using a multi‐objective population‐based incremental learning algorithm seeking to maximize the trading volume and minimize the bid–ask spread. Our results suggest that markets should choose a small tick size if concerns about the bid–ask spread are dominating and a large tick size if maximizing trading volume is the main aim. We also find that unless concerns about trading volume dominate, time priority is the optimal priority rule. Copyright © 2011 John Wiley & Sons, Ltd.     

Price trends and patterns in technical analysis: A theoretical and empirical examination

While many technical trading rules are based upon patterns in asset prices, we lack convincing explanations of how and why these patterns arise, and why trading rules based on technical analysis are profitable. This paper provides a model that explains the success of certain trading rules that are based on patterns in past prices. We point to the importance of confirmation bias, which has been shown to play a key role in other types of decision making. Traders who acquire information and trade on the basis of that information tend to bias their interpretation of subsequent information in the direction of their original view. This produces autocorrelations and patterns of price movement that can predict future prices, such as the “head-and-shoulders” and “double-top” patterns. The model also predicts that sequential price jumps for a particular stock will be positively autocorrelated. We test this prediction and find that jumps exhibit statistically and economically significant positive autocorrelations.     

The capital gain lock-in effect with short sales constraints

This paper develops a post-tax asset pricing model under the assumption that investors cannot defer the taxation of capital gains by costlessly short selling tax exempt perfect substitute securities. Contrary to existing literature, it is demonstrated that trading rules of immediate realization of losses and voluntary deferral of gains may not be optimal. Further, equilibrium prices are shown to be higher for stocks held by investors with large accrued capital gains and lower for stocks held by investors with small accrued capital gains or losses.     

Utility maximizing portfolio insurance strategies when hedgers consider the impact of their trading on security prices

Portfolio insurance strategies can destabilize markets to such an extent that they may be counterproductive. Destabilization results when hedgers take share prices as given and follow exogenously specified price-based trading rules. We recognize that such trading rules may not be utility maximizing and that hedging affects share prices. Accordingly, we develop a portfolio insurance strategy where hedgers consider the impact of their trading on prices and endogenize their trading rule which is obtained by maximizing expected utility. Moreover, our strategy does not require the dissemination of information about the extent of portfolio-insurance based hedging activity in the economy.     

Trading activity,dealer concentration and foreign exchange market quality

We study the relation between foreign exchange market quality and both trading activity and dealer concentration by considering two currency pairs with significant differences along both dimensions – the Euro–US dollar and Canadian dollar–US dollar. A variance ratio test reveals over-reaction in currency prices, but that this is smallest when trading activity is high and dealer concentration at its peak. A GARCH model shows that over-reaction declines as trading activity and dealer concentration increase, with the results being stronger for the Euro. Our results confirm that trading activity is an important determinant of market quality, but also point to a significant role for dealer concentration.     

Clustering in US Stock Prices after Decimalisation

Early in 2001, US equity markets transitioned from trading in discrete price fractions to a smoother decimal format with a tick size of one penny. Theory suggests in an unconstrained world, stock prices should be distributed uniformly, particularly if the cost of defeating time priority is low. This regime change provides a natural experiment to test whether investors prefer to trade at particular price points even when their choices are essentially unconstrained by regulation. Instead of uniformity, we find widespread evidence of price clustering at increments of five and ten cents (nickels and dimes); the overall magnitude of clustering is double in scale of what is otherwise expected. Previous studies which documented clustering around even‐eighths argued that these patterns were a rational market response to trading impediments. We report consistent findings, but also find that the overall level of post‐decimalisation clustering is far more extensive than is reasonably explained by prior hypotheses. The evidence instead suggests a more fundamental human bias for prominent numbers as discussed in the psychology literature. Contrary to previous studies, we find no difference in price clustering, ceteris paribus, between the Nasdaq and NYSE after decimalisation. Should regulators choose to revisit the notion of tick size, our evidence suggests that for many stocks there would be only minor impact between the transaction prices that prevail now and those that would occur if the tick size were increased to five cents.     

Trading activity and price reversals in futures markets

We use the standard contrarian portfolio approach to examine short-horizon return predictability in 24 US futures markets. We find strong evidence of weekly return reversals, similar to the findings from equity market studies. When interacting between past returns and lagged changes in trading activity (volume and/or open interest), we find that the profits to contrarian portfolio strategies are, on average, positively associated with lagged changes in trading volume, but negatively related to lagged changes in open interest. We also show that futures return predictability is more pronounced if interacting between past returns and lagged changes in both volume and open interest. Our results suggest that futures market overreaction exists, and both past prices and trading activity contain useful information about future market movements. These findings have implications for futures market efficiency and are useful for futures market participants, particularly commodity pool operators.     

Intraday trading volume and international spillover effects

The objective of this paper is to explore whether lagged trading activity in one market contributes to the return and volatility process in other markets, using 5-min concurrent data from German and British equity market. Our results lend support to our initial premise that if international investors have access to the same information set as domestic traders, then after observing foreign trading activity, market makers adjust prices to reflect their expectation of the security value, conditional upon all available information, including prior trades. Our findings clearly indicate that intraday trading volume contains predictive power for cross-border return and volatility processes. Moreover, these volume effects are found to be asymmetric in the sense that the impact of positive volume changes upon foreign stock market volatility is greater than is the impact of negative changes.     

Intraday pairs trading strategies on high frequency data: the case of oil companies

This paper introduces novel ‘doubly mean-reverting’ processes based on conditional modelling of model spreads between pairs of stocks. Intraday trading strategies using high frequency data are proposed based on the model. This model framework and the strategies are designed to capture ‘local’ market inefficiencies that are elusive for traditional pairs trading strategies with daily data. Results from real data back-testing for two periods show remarkable returns, even accounting for transaction costs, with annualized Sharpe ratios of 3.9 and 7.2 over the periods June 2013–April 2015 and 2008, respectively. By choosing the particular sector of oil companies, we also confirm the observation that the commodity price is the main driver of the share prices of commodity-producing companies at times of spikes in the related commodity market.     

Financial Markets Where Traders Neglect the Informational Content of Prices

We model a financial market where some traders of a risky asset do not fully appreciate what prices convey about others' private information. Markets comprising solely such “cursed” traders generate more trade than those comprising solely rationals. Because rationals arbitrage away distortions caused by cursed traders, mixed markets can generate even more trade. Per‐trader volume in cursed markets increases with market size; volume may instead disappear when traders infer others' information from prices, even when they dismiss it as noisier than their own. Making private information public raises rational and “dismissive” volume, but reduces cursed volume given moderate noninformational trading motives.