This paper shows that over time, expected market illiquidity positively affects ex ante stock excess return, suggesting that expected stock excess return partly represents an illiquidity premium. This complements the cross-sectional positive return–illiquidity relationship. Also, stock returns are negatively related over time to contemporaneous unexpected illiquidity. The illiquidity measure here is the average across stocks of the daily ratio of absolute stock return to dollar volume, which is easily obtained from daily stock data for long time series in most stock markets. Illiquidity affects more strongly small firm stocks, thus explaining time series variations in their premiums over

Individual investors who hold common stocks directly pay a tremendous performance penalty for active trading. Of 66,465 households with accounts at a large discount broker during 1991 to 1996, those that trade most earn an annual return of 11.4 percent, while the market returns 17.9 percent. The average household earns an annual return of 16.4 percent, tilts its common stock investment toward high-beta, small, value stocks, and turns over 75 percent of its portfolio annually. Overconfidence can explain high trading levels and the resulting poor performance of individual investors. Our central message is that trading is hazardous to your wealth. The investor’s chief problem—and even his worst enemy—is likely to be himself. Benjamin Graham In 1996, approximately 47 percent of equity investments in the United States were held directly by households, 23 percent by pension funds, and 14 percent by mutual funds ~Securities Industry Fact Book, 1997!. Financial economists have extensively analyzed the return performance of equities managed by mutual funds. There is also a fair amount of research on the performance of equities managed by pension funds. Unfortunately, there is little research on the return performance of equities held directly by households, despite their large ownership of equities.

We derive dynamic optimal trading strategies that minimize the expected cost of trading a large block of equity over a fixed time horizon. Specifically, given a fixed block SM of shares to be executed within a fixed finite number of periods , and given a price-impact function that yields the execution price of an individual trade as a function of the shares traded and market conditions, we obtain the optimal sequence of trades as a function of market conditions — closed-form expressions in some cases — that minimizes the expected cost of executing SM within periods. Our analysis is extended to the portfolio case in which price impact across stocks can have an important effect on the total cost of trading a portfolio.

Traditionally and understandably, the microscope of market microstructure has focused on attributes of single assets. Little theoretical attention and virtually no empirical work has been devoted to common determinants of liquidity nor to their empirical manifestation, correlated movements in liquidity. But a wider-angle lens exposes an imposing image of commonality. Quoted spreads, quoted depth, and effective spreads co-move with market- and industry-wide liquidity. After controlling for wellknown individual liquidity determinants, such as volatility, volume, and price, common influences remain signi"cant and material. Recognizing the existence of commonality is a key to uncovering some suggestive evidence that inventory risks and asymmetric information both affect intertemporal changes in liquidity.

We examine changes in the stock trading behavior and investment performance of 1,607 investors who switch from phone based to online trading during the period 1992 to 1995. We document that young men who are active traders with high incomes and a preference for investing in small growth stocks with high market risk are more likely to switch to online trading. We also find that those who switch to online trading experience unusually strong performance prior to going online, beating the market by more than two percent annually. After going online, they trade more actively, more speculatively, and less profitably than before-- lagging the market by more than three percent annually. A rational response to reductions in market frictions (lower trading costs, improved execution speed, and greater ease of access) does not explain these findings. The increase in trading and reduction in performance of online investors can be explained by overconfidence augmented by self-attribution bias, the illusion of knowledge, and the illusion of control.

We describe how episodic illiquidity arises from a breakdown in cooperation between market participants. We first solve a one-period trading game in continuous-time, using an asset pricing equation that accounts for the price impact of trading. Then, in a multi-period framework, we describe an equilibrium in which traders cooperate most of the time through repeated interaction, providing apparent liquidity to one another. Cooperation breaks down when the stakes are high, leading to predatory trading and episodic illiquidity. Equilibrium strategies that involve cooperation across markets lead to less frequent episodic illiquidity, but cause contagion when cooperation breaks down.

Traditionally, volume has provided the link between trading activity and returns. We focus on a hitherto unexplored but intuitive measure of trading activity: the aggregate daily order imbalance, buy orders less sell orders, on the New York Stock Exchange. Order imbalance increases following market declines and vice versa, which reveals that investors are contrarians on aggregate. Order imbalances in either direction, excess buy or sell orders, reduce liquidity. Marketwide returns are strongly affected by contemporaneous and lagged order imbalances. Market returns reverse themselves after high-negative-imbalance, large-negative-return days. Even after controlling for aggregate volume and liquidity, market returns are affected by order imbalance.

American Finance Association meetings for helpful comments. Empirical research in finance documented the existence of a permanent price impact asym-metry between buyer and seller-initiated block trades: the permanent price impact of buys is larger than that of sells. This paper develops a theoretical model to explain and investigate the asymmetry phenomenon. The model formalizes an intuition that the dynamic trading strategy of profit-maximizing institutional portfolio managers creates a difference between the information content of buys and sells. It is this difference that causes the expected per-manent price impact asymmetry. The model produces new empirical implications concerning the relationship between the asymmetry phenomenon and the economic environment. The main implication of the model is that the history of price performance influences the asym-metry. The longer the run-up in a stock’s price, the less is the asymmetry. The greater the trading intensity of institutional investors or the more �informationally-active � a stock, the more pronounced is the asymmetry when a stock’s price has not been going up or is at the beginning of a price run-up. The opposite result appears after a long period of (abnormal) price appreciation. Price Impact Asymmetry of Block Trades: An Institutional Trading Explanation Empirical research on block transactions and institutional trades has produced a seem-ingly puzzling result: markets react differently to buy and sell orders. Beginning with Kraus and Stoll (1972), researchers have found that block purchases have a larger permanent price

R. Stoll Market microstructure deals with the purest form of financial intermediation-- the trading of a financial asset, such as a stock or a bond. In a trading market, assets are not transformed but are simply transferred from one investor to another. The field of market microstructure studies the cost of trading securities and the impact of trading costs on the short-run behavior of securities prices. Costs are reflected in the bid-ask spread (and related measures) and in commissions. The focus of this chapter is on the determinants of the spread rather than on commissions. After an introduction to markets, traders and the trading process, I review the theory of the bid-ask spread in section II and examine the implications of the spread for the short run behavior of prices in section III. In section IV, the empirical evidence on the magnitude and nature of trading costs is summarized, and inferences are drawn about the importance of various sources of the spread. Price impacts of trading from block trades, from herding or from other sources, are considered in section V. Issues in the design of a trading market, such as the functioning of call versus

We consider the problem of optimal position liquidation with the aim of maximizing the expected cash flow stream from the transaction in the presence of temporary or permanent market impact. We use a stochastic programming approach to derive trading strategies that differentiate decisions with respect to observed market conditions. The scenario set consists of a collection of sample paths representing possible future realizations of state variable processes (price of the security, trading volume etc.) At each time moment the set of paths is partitioned into several groups according to specified criteria, and each group is controlled by its own decision variable(s), which allows for adequate representation of uncertainties in market conditions and circumvents anticipativity in the solutions. In contrast to traditional dynamic programming approaches, the presented formulation admits incorporation of different types of constraints in the trading strategy, e.g. risk constraints, various decision-making policies, etc. Numerical results and optimal trading patterns for different forms of market impact are presented.