[Technical analysis, or the use of past prices to infer private information, has value in a model in which prices are not fully revealing and traders have rational conjectures about the relation between prices and signals. A two-period dynamic model of equilibrium is used to demonstrate that rational investors use historical prices in forming their demands and to illustrate the sensitivity of the value of technical analysis to changes in the values of the exogenous parameters.]

This work compares a dealer market and a limit-order book. Dealers commonly observe order flow and collect information from multiple market orders. They may be better informed than other traders, although they do not earn rents from this information. Dealers earn rents as suppliers of liquidity and their decisions to enter or exit the market are independent of the degree of adverse selection. Introduction of a limit-order book lowers the execution-price risk faced by speculators and leads them to trade more aggressively on their information. Introduction of the book also lowers dealer profits but increases the informational efficiency of prices.

A new representation of nonmarketable (NM) income is introduced in this essay. Using this representation and continuous trading, there exists a set of individuals who do not participate in the asset market and who consume at the rate of nonmarketable income derived from human capital. Because these individuals remain nonparticipants for a range of stochastic processes governing the NM income, consumption betas are not generally unique in value and the consumption‐based CAPM (CCAPM) does not obtain. However, the intertemporal CAPM (ICAPM) of Merton remains valid.

A new representation of nonmarketable (NM) income is introduced in this essay. Using this representation and continuous trading, there exists a set of individuals who do not participate in the asset market and who consume at the rate of nonmarketable income derived from human capital. Because these individuals remain nonparticipants for a range of stochastic processes governing the NM income, consumption betas are not generally unique in value and the consumption-based CAPM (CCAPM) does not obtain. However, the intertemporal CAPM (ICAPM) of Merton remains valid.

Technical analysis, or the use of past prices to infer private information, has value in a model in which prices are not fully revealing and traders have rational conjectures about the relation between prices and signals. A two-period dynamic model of equilibrium is used to demonstrate that rational investors use historical prices in forming their demands and to illustrate the sensitivity of the value of technical analysis to changes in the values of the exogenous parameters.

We analyze myopic trader models of noisy prices in financial markets. Unlike extant analysis, such as De Long et al. (1990a), a classical equilibrium exists in our analysis, e.g., a riskless perpetuity is priced by arbitrage and its price does not vary with noise. A unique noisy equilibrium exists only when i) noise traders' beliefs are rational regarding volatility and irrational regarding expected returns, and ii) noise traders can hold infinite positions. In the absence of these strong assumptions, multiple noisy equilibria can coexist with the classical equilibrium, but these equilibria exhibit conflicting comparative statics. Furthermore, the price of a long-lived asset with risky cash flows can vary with noise even when investors are not myopic. One conclusion is that myopia is neither a necessary nor a sufficient condition for noisy prices. A second is that it is difficult, if not impossible, to use myopic trader models to derive implications for investment or regulatory policy.

This work compares a dealer market and a limit-order book. Dealers commonly observe order flow and collect information from multiple market orders. They may be better informed than other traders, although they do not earn rents from this information. Dealers earn rents as suppliers of liquidity, and their decisions to enter or exit the market are independent of the degree of adverse selection. Introduction of a limit-order book lowers the execution-price risk faced by speculators and leads them to trade more aggressively on their information. Introduction of the book also lowers dealer profits, but increases the informational efficiency of prices.

This work compares a dealer market and a limit‐order book. Dealers commonly observe order flow and collect information from multiple market orders. They may be better informed than other traders, although they do not earn rents from this information. Dealers earn rents as suppliers of liquidity, and their decisions to enter or exit the market are independent of the degree of adverse selection. Introduction of a limit‐order book lowers the execution‐price risk faced by speculators and leads them to trade more aggressively on their information. Introduction of the book also lowers dealer profits, but increases the informational efficiency of prices.

Utility‐based models of asset pricing may be estimated with or without assuming a distribution for security returns; both approaches are developed and compared here. The chief strength of a parametric estimator lies in its computational simplicity and statistical efficiency when the added distributional assumption is true. In contrast, the nonparametric estimator is robust to departures from any particular distribution, and it is more consistent with the spirit underlying utility‐based asset pricing models since the distribution of asset returns remains unspecified even in the empirical work. The nonparametric approach turns out to be easy to implement with precision nearly indistinguishable from its parametric counterpart in this particular application. The application shows that log utility is consistent with the data over the period 1926–1981.

Utility-based models of asset pricing may be estimated with or without assuming a distribution for security returns; both approaches are developed and compared here. The chief strength of a parametric estimator lies in its computational simplicity and statistical efficiency when the added distributional assumption is true. In contrast, the nonparametric estimator is robust to departures from any particular distribution, and it is more consistent with the spirit underlying utility-based asset pricing models since the distribution of asset returns remains unspecified even in the empirical work. The nonparametric approach turns out to be easy to implement with precision nearly indistinguishable from its parametric counterpart in this particular application. The application shows that log utility is consistent with the data over the period 1926–1981.