Asset Pricing under Asymmetric Information: Bubbles, Crashes, Technical Analysis, and Herding

By Markus K. Brunnermeier | Go to book overview

4 Dynamic Trading Models, Technical Analysis, and the Role of Trading Volume

In the previous chapter we discussed closed-form solution models in which each individual trader optimized his trades only at one period in time. Traders had no opportunity to resell their acquired positions in later trading rounds. In most cases the stock was liquidated and the liquidation value of the stock was paid out before re-trade could occur. In this chapter we consider models in which individual traders are active in the market place in multiple trading rounds. This both enriches and complicates the analysis. Models in Section 4.1 illustrate how traders try to learn additional information from past prices. Technical analysis has positive value and allows traders to make better investment decisions. They are able to better interpret new information if they make use of information reflected in past prices. Furthermore, technical analysis gives them a better idea about the true value of the underlying asset. Learning from past prices alters their trading strategy and thus also affects the price process. Section 4.2 illustrates how learning induces serial correlation in the price process. The section also highlights the infinite regress problem which might arise if traders try to forecast others' forecasts by inferring information from endogenous variables. Section 4.3 covers multiperiod competitive REE models starting with two models in which information is hierarchical, that is, the information of one group of traders encompasses the others' information. The first model is set in continuous time whereas the second model is in discrete time and incorporates the role of trading volume. Both models also illustrate that it is rational for uninformed traders to follow the trend. In the last multiperiod model in Section 4.3 , information is dispersed among many traders. The model in Section 4.4 analyzes the informational content of past trading volume data. The final section departs from competitive REE models and considers models with strategic traders who take into account the fact that their trading

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