Market structure and the intraday pattern of bid-ask spreads for NASDAQ securities

Article Abstract:

Acomparison is made of the intraday trading patterns of stocks listed in NASDAQ and stocks listed in the New York Stock Exchange (NYSE). The intraday trading patterns show that bid-ask spreads of NASDAQ stocks are relatively stable for much of the trading day and narrow only toward the close. This trading pattern differs significantly from the U-shaped pattern exhibited by the bid-ask spreads of stocks listed in the NYSE. The differences in the intraday trading patterns of these two exchanges can be traced to the differences in the structural charcteristics of specialist markets such as the NYSE and dealer markets such as the NASDAQ. Specifically, declines toward the close of markets reflect inventory control measures among NASDAQ dealers, while wider spreads indicate the power of specialists in the NYSE.

Securities and Commodity Exchanges, Security and commodity exchanges, Securities Exchanges, Analysis, Stock-exchange, Stock exchanges, Exchanges, Securities listing, New York Stock Exchange Inc., NASDAQ Market System

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On the contrarian investment strategy

Article Abstract:

The contrarian investment strategy involves buying losing stocks and and selling short stocks that have been winning. The contrarian strategy is based on the premise that the market over-reacts to news. Winning stocks therefore tend to be over-valued and losing stocks are undervalued. An alternative interpretation of the performance of the contrarian strategy is offered. The risks of the winners and losers are not constant. As a result, the estimation of the return of this strategy is sensitive to the method used. Only small abnormal returns are realized when there is control for risk changes. The standard Capital Assets Pricing Model is used as the model of risk and return.

Portfolio management

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Some further evidence on the stochastic properties of systematic risk

Article Abstract:

The beta risk of equity securities is generally thought to be stochastic; whether this variation is random or shows auto-correlation through time is uncertain. To resolve this question, a model is used that allows beta to simultaneously exhibit both autoregressive and random behavior. This model is tested on a large sample of randomly formed portfolios and individual securities. The results indicate that about one-quarter of the beta variation for securities and portfolios is auto-correlated.

Methods, Stochastic analysis, Stochastic processes, Financial research

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