A Theory of the Dynamics of Security Returns around Market Closures

Numerous empirical studies document patterns in the means and variances of security returns measured over periods that are punctuated by market closures. This article develops a multiperiod model in which closures delay the resolution of uncertainty, thereby redistributing risk across time and agents. Since agents are risk averse in the model, this redistribution affects the equilibrium price, altering risk premia, liquidity costs, and the degree of informational asymmetry. As a consequence, closures alter both the means and variances of returns. The article demonstrates that closures can generate a variety of mean and variance effects, including those that mirror the empirical phenomena.     

The Relation Between Common Stock Returns Trading Activity and Market Value

This study examines the relation between common stock returns, trading activity and market value. Our results indicate that although firm size and trading activity are highly correlated, differences in trading activity are not the underlying reason for the firm size anomaly, the finding of systematic differences in risk adjusted returns across stocks of firms of different size.     

Insider Trading Activity,Different Market Regimens,and Abnormal Returns

This paper show that corporate insiders earn abnormal returns by adjusting their own firm's stock trading to future market movements. Insider trading activity in bear markets is characterized by decreases in insider sales and increases in purchases, consistent with the view that those markets are followed by improved economic conditions. Conversely, insider sales increase and purchases decrease in bull markets, consistent with the view that inferior market conditions tend to follow those periods.     

Correlated Trading and Returns

A German broker's clients place similar speculative trades and therefore tend to be on the same side of the market in a given stock during a given day, week, month, and quarter. Aggregate liquidity effects, short sale constraints, the systematic execution of limit orders (coordinated through price movements) or the correlated trading of other investors who pick off retail limit orders do not fully explain why retail investors trade similarly. Correlated market orders lead returns, presumably due to persistent speculative price pressure. Correlated limit orders also predict subsequent returns, consistent with executed limit orders being compensated for accommodating liquidity demands.     

Individual Investor Trading and Stock Returns

This paper investigates the dynamic relation between net individual investor trading and short‐horizon returns for a large cross‐section of NYSE stocks. The evidence indicates that individuals tend to buy stocks following declines in the previous month and sell following price increases. We document positive excess returns in the month following intense buying by individuals and negative excess returns after individuals sell, which we show is distinct from the previously shown past return or volume effects. The patterns we document are consistent with the notion that risk‐averse individuals provide liquidity to meet institutional demand for immediacy.     

再通胀交易下的国际外汇市场

今年以来,再通胀交易成为影响国际外汇市场走势的重要因素。多项利好支持美元指数反弹,英镑伴随全民高接种率迎来“疫苗行情”,澳元等商品货币基本面良好汇率坚挺,欧元、日元等负利率货币相对弱势,港币受资本市场走势影响显著。展望后市,再通胀交易逻辑有望延续,重点关注通胀和就业两大关键数据、美国后续基建投资、各大央行政策走向。     

Trading Volume and Cross-Autocorrelations in Stock Returns

This paper finds that trading volume is a significant determinant of the lead-lag patterns observed in stock returns. Daily and weekly returns on high volume portfolios lead returns on low volume portfolios, controlling for firm size. Nonsynchronous trading or low volume portfolio autocorrelations cannot explain these findings. These patterns arise because returns on low volume portfolios respond more slowly to information in market returns. The speed of adjustment of individual stocks confirms these findings. Overall, the results indicate that differential speed of adjustment to information is a significant source of the cross-autocorrelation patterns in short-horizon stock returns.     

投资者分歧、异常交易量和股票横截面收益率预测——基于中国股票市场的经验证据

本文定义月度异常交易量为本月与上个月交易金额的比值,发现中国市场月度收益率与滞后一个月的异常交易量显著负相关。在控制了公司规模、账面市值比、流动性以及动量效应等指标后仍然具有显著的解释作用。进一步研究表明,在出现高异常交易量后的12个月内,换手率和特质性波动率都有大幅上升。本文认为,交易量上升代表着市场分歧程度和受关注程度的增加,在卖空约束下会使得股票价值高估,从而造成未来收益率下降。     

On Stock Market Returns and Returns on Investment

This article presents general conditions under which it is possible to obtain asset pricing relations from the intertemporal optimal investment decision of the firm. Under the assumption of linear homogeneous production and adjustment cost functions (the Hayashi (1982) conditions), it is possible to establish, state by state, the equality between the return on investment and the market return of the financial claims issued by the firm. This result proves to be, in essence, robust to the consideration of very general constraints on investment and the inclusion of taxes.     

Retail Trading and IPO Returns in the Aftermarket

Using trade size from the Trade and Quote (TAQ) data set as a proxy for individual versus institutional trading, this paper finds that the effects of trading of these two types of investors on initial public offering (IPO) returns on the first trading day depend on the hotness of the IPO. My regression results reveal that IPOs’ open-to-close returns are positively related to small trade participation, small trade purchases, and small trade order imbalance in the hot IPO sample, but not in the cold and neutral IPO samples. In addition, the aftermarket prices of cold and neutral IPOs are primarily driven by the trading of institutional investors, who are less likely to be driven by sentiment.     

The Trading Decision and Market Clearing under Transaction Price Uncertainty

This paper models an individual's trading decision, given: (1) his/her demand function to hold shares of an asset, (2) his/her expectation on what the market clearing price will be, and (3) the design of the market which determines how orders will be translated into trades. The particular market design we consider is the batched trading (periodic call) regime. Assuming investors are distributed according to their propensities to hold shares, we model the aggregation of orders to obtain market clearing values of price and volume and to show the way in which, with trading friction, these solutions differ from Pareto efficient values. The importance of this analysis for various issues concerning market design is noted.     

Dynamic Trading with Predictable Returns and Transaction Costs

We derive a closed‐form optimal dynamic portfolio policy when trading is costly and security returns are predictable by signals with different mean‐reversion speeds. The optimal strategy is characterized by two principles: (1) aim in front of the target, and (2) trade partially toward the current aim. Specifically, the optimal updated portfolio is a linear combination of the existing portfolio and an “aim portfolio,” which is a weighted average of the current Markowitz portfolio (the moving target) and the expected Markowitz portfolios on all future dates (where the target is moving). Intuitively, predictors with slower mean‐reversion (alpha decay) get more weight in the aim portfolio. We implement the optimal strategy for commodity futures and find superior net returns relative to more naive benchmarks.     

Corrections for Trading Frictions in Multivariate Returns

When observed stock returns are obtained from trades subject to friction, it is known that an individual stock's beta and covariance are measured with error. Univariate models of additive error adjustment are available and are often applied simultaneously to more than one stock. Unfortunately, these multivariate adjustments produce non-positive definite covariance and correlation matrices, unless the return sample sizes are very large. To prevent this, restrictions on the adjustment matrix are developed and a correction is proposed, which dominates the uncorrected estimator. The estimators are illustrated with asset opportunity set estimates where daily returns have trading frictions.     

Stock Market Returns and Consumption

This paper employs Swedish data on households' stock holdings to investigate how consumption responds to changes in stock market returns. We instrument the actual capital gains and dividend payments with past portfolio weights. Unrealized capital gains lead to a marginal propensity to consume of 23% for the bottom 50% of the wealth distribution and about 3% for the top 30% of the wealth distribution. Household consumption is significantly more responsive to dividend payouts across all parts of the wealth distribution. Our findings are consistent with households treating capital gains and dividends as separate sources of income.     

Trading Mechanisms and Stock Returns: An Empirical Investigation

This paper examines the effects of the mechanism by which securities are traded on their price behavior. We compare the behavior of open-to-open and close-to-close returns on NYSE stocks, given the differences in execution methods applied in the opening and closing transactions. Opening returns are found to exhibit greater dispersion, greater deviations from normality and a more negative and significant autocorrelation pattern than closing returns. We study the effects of the bid-ask spread and the price-adjustment process on the estimated return variances and covariances and discuss the associated biases. We conclude that the trading mechanism has a significant effect on stock price behavior.     

A Model of Returns and Trading in Futures Markets

This paper develops an equilibrium model of a competitive futures market in which investors trade to hedge positions and to speculate on their private information. Equilibrium return and trading patterns are examined. (1) In markets where the information asymmetry among investors is small, the return volatility of a futures contract decreases with time-to-maturity (i.e., the Samuelson effect holds). (2) However, in markets where the information asymmetry among investors is large, the Samuelson effect need not hold. (3) Additionally, the model generates rich time-to-maturity patterns in open interest and spot price volatility that are consistent with empirical findings.     

Market Liquidity and Trading Activity

Previous studies of liquidity span short time periods and focus on the individual security. In contrast, we study aggregate market spreads, depths, and trading activity for U.S. equities over an extended time sample. Daily changes in market averages of liquidity and trading activity are highly volatile and negatively serially dependent. Liquidity plummets significantly in down markets. Recent market volatility induces a decrease in trading activity and spreads. There are strong day-of-the-week effects; Fridays accompany a significant decrease in trading activity and liquidity, while Tuesdays display the opposite pattern. Long- and short-term interest rates influence liquidity. Depth and trading activity increase just prior to major macroeconomic announcements.     

High-Frequency Trading and Market Performance

We study the consequences of, and potential policy responses to, high-frequency trading (HFT) via the tradeoff between liquidity and information production. Faster speeds facilitate HFT, with consequences for this tradeoff: Information production decreases because informed traders have less time to trade before HFTs react, but liquidity (measured by the bid-ask spread) improves because informational asymmetries decline. HFT also pushes outcomes inside the frontier of this tradeoff. However, outcomes can be restored to the frontier by replacing the limit order book with one of two alternative mechanisms: delaying all orders except cancellations or implementing frequent batch auctions.     

Market Efficiency and the Returns to Simple Technical Trading Rules: New Evidence from U.S. Equity Market and Chinese Equity Markets

Numerous studies in the finance literature have investigated technical analysis to determine its validity as an investment tool. This study is an attempt to explore whether some forms of technical analysis can predict stock price movement and make excess profits based on certain trading rules in markets with different efficiency level. To avoid using arbitrarily selected 26 trading rules as did by Brock, Lakonishok and LeBaron (1992) and later by Bessembinder and Chan (1998), this paper examines predictive power and profitability of simple trading rules by expanding their universe of 26 rules to 412 rules. In order to find out the relationship between market efficiency and excess return by applying trading rules, we examine excess return over periods in U.S. markets and also compare the excess returns between U.S. market and Chinese markets. Our results found that there is no evidence at all supporting technical forecast power by these trading rules in U.S. equity index after 1975. During the 1990s break-even costs turned to be negative, –0.06%, even failing to beat a buy-holding strategyin U.S. equity market. In comparison, our results provide support for the technical strategies even in the presence of trading cost in Chinese stock markets.