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DECOMPOSING THE PREDICTIVE PERFORMANCE OF THE MOVING AVERAGE TRADING RULE OF TECHNICAL ANALYSIS: THE CONTRIBUTION OF LINEAR AND NON LINEAR DEPENDENCIES IN STOCK RETURNS

 

Alexandros E. Milionis

Bank of Greece and University of the Aegean

 

Evangelia Papanagiotou

University of the Aegean

 

ABSTRACT

On several occasions technical analysis rules have been shown to have predictive power. The main purpose of this work is to decompose the predictive power of the moving average trading rule and isolate the portion that could be attributed to the possible exploitation of linear and non linear dependencies in stock returns. Data for the General Index of the Athens Stock Exchange are filtered using linear filters so that the resulting simulated “returns” exhibit no serial correlation. Applying moving average trading rules to both the original and the simulated indices and using a statistical testing procedure that takes into account the sensitivity of the performance of the trading rule as a function of moving average length, it is found that the predictive power of the trading rule is clearly weakened when applied to the simulated index indicating that a substantial part of the rule’s predictive power is due to the exploitation of linear dependencies in stock returns. It is also found that the contribution of linear dependencies in stock returns to the performance of the trading rule is increased for shorter moving average lengths.

 

Key words: Market Efficiency, Technical Analysis, Moving Average Trading Rules, Athens Stock Exchange.

 

JEL classification: G14, G15, C2

 

Ackowledgements: The authors are grateful to H. Gibson for helpful comments. The views expressed in the paper are those of the authors and do not necessarily reflect those of the Bank of Greece.

 

 

Correspondence:

Alexandros E. Milionis

Bank of Greece,

Department of Statistics

21 E. Venizelos Avenue,

 Athens,  102 50, Greece

Tel.: +30-210 3203855,

e-mail: amilionis@bankofgreece.gr

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