Abstract

The econometric analysis of financial markets has recently focussed on the effects of possible non-linearities in the returns time series for the market efficiency hypothesis. In fact, one of the empirical regularities next to the lack of autocorrelation in the returns is the time dependence in positive-valued non-linear functions of the returns themselves. The lack of independence in the returns signals that there exists a structure which calls for deeper economic interpretation and statistical analysis. In this paper we focus on the link between the tools used by technical analysts and widely popular among traders to isolate the most suitable moments to purchase or sell securities, and the econometric/statistical methodology used to study conditional volatility of returns. In particular we want to analyze whether the presence of a consensus on the short-run trend of prices translates into an impact on volatility introducing asymmetric effects whether the technical signals relate to sales or purchases. The applications are performed on daily data from the New York Stock Exchange.

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