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Book
Technical Trading Rule Profitability and Foreign Exchange Intervention
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Year: 1996 Publisher: Cambridge, Mass. National Bureau of Economic Research

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Technical trading rule profitability and foreign exchange intervention
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Year: 1996 Publisher: Cambridge, Mass.

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Book
A dynamic structural model for stock return volatility and trading volume
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Year: 1995 Publisher: Cambridge, Mass. National Bureau of Economic Research

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Book
Technical Trading Rule Profitability and Foreign Exchange Intervention
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Year: 1996 Publisher: Cambridge, Mass. National Bureau of Economic Research

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There is reliable evidence that simple rules used by traders have some predictive value over the future movement of foreign exchange prices. This paper will review some of this evidence and discuss the economic magnitude of this predictability. The profitability of these trading rules will then be analyzed in connection with central bank activity using intervention data from the Federal Reserve. The objective is to find out to what extent foreign exchange predictability can be confined to periods of central bank activity in the foreign exchange market. The results indicate that after removing periods in which the Federal Reserve is active, exchange rate predictability is dramatically reduced.


Book
Liquidity Constraints in Production Based Asset Pricing Models
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Year: 1989 Publisher: Cambridge, Mass. National Bureau of Economic Research

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This paper explores the time series implications of introducing credit constraints into a production based asset pricing model. Simulations are performed choosing parameter values which generate reasonable values for aggregate fluctuations. These results show that mean reversion in simulated returns series, measured by variance ration tests, is enhanced with the introduction of binding credit constraints. Without these constraints there is very little evidence of mean reversion. This is consistent with financial market data where the weak evidence for mean reversion is stronger in small firm returns. Other tests are run on the simulated series including checking the standard deviation, skewness, and kurtosis. These other tests do not show strong differences between the constrained and unconstrained firms in the model.


Book
A Dynamic Structural Model for Stock Return Volatility and Trading Volume
Authors: --- ---
Year: 1995 Publisher: Cambridge, Mass. National Bureau of Economic Research

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This paper seeks to develop a structural model that lets data on asset returns and trading volume speak to whether volatility autocorrelation comes from the fundamental that the trading process is pricing or, is caused by the trading process itself. Returns and volume data argue, in the context of our model, that persistent volatility is caused by traders experimenting with different beliefs based upon past profit experience and their estimates of future profit experience. A major theme of our paper is to introduce adaptive agents in the spirit of Sargent (1993) but have them adapt their strategies on a time scale that is slower than the time scale on which the trading process takes place. This will lead to positive autocorrelation in volatility and volume on the time scale of the trading process which generates returns and volume data. Positive autocorrelation of volatility and volume is caused by persistence of strategy patterns that are associated with high volatility and high volume. Thee following features seen in the data: (i) The autocorrelation function of a measure of volatility such as squared returns or absolute value of returns is positive with a slowly decaying tail. (ii) The autocorrelation function of a measure of trading activity such as volume or turnover is positive with a slowly decaying tail. (iii) The cross correlation function of a measure of volatility such as squared returns is about zero for squared returns with past and future volumes and is positive for squared returns with current volumes. (iv) Abrupt changes in prices and returns occur which are hard to attach to 'news.' The last feature is obtained by a version of the model where the Law of Large Numbers fails in the large economy limit.


Book
Agent Based Models for Economic Policy Advice

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This special issue of the Journal of Economics and Statistics is devoted to the use of agent-based models for economic policy advice. It presents a collection of research papers in different fields of applications. Special emphasis is laid on discussing the potential and possible limitations of agent-based models for economic policy advice. The editorial provides an overview on the role of agent-based modeling in economic policy referring also to the papers presented. Furthermore, it highlights the strength of the approach, i.e., the explicit microfoundation and the modeling of heterogenous agents. Finally, we also report on current limitations of the method with regard to economic policy advice and point at some areas deserving further research.

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