Application of Wavelets to Detect Trend Reversals on Brazilian Stock Market ()
ABSTRACT
This study develops a method to detect trend
reversals followed by significant drops in Brazilian Stock Market using
wavelets. Applying the concept of the log-periodic
power-law, whose oscillations present reduction in amplitude and period as the critical moment approaches (where there is a higher
probability of market drop), it used the Continuous Wavelet Transform to detect
the increasing oscillation frequency in the stock price, time series and
generate sell signals. An algorithm was developed to test different kinds of wavelets and parameters to calculate the Wavelet Index, evaluating whose combination of parameters brings the best results
and comparing these results with the existing Technical
Analysis tools. The results show that the proposed method to calculate the Wavelet Index detects successfully the
significant drops (over 10%) in the Brazilian Stock Market. Considering
drops over 15%, there were losses due to early sales of 45% (average) in the
search set and 43.9% in the
test set, without false negatives, using mainly the Meyer wavelet. Its
performance was also better than existing Technical Analysis tools, like MACD
and RSI.
Share and Cite:
Penof, D. and Belardi, A. (2017) Application of Wavelets to Detect Trend Reversals on Brazilian Stock Market.
iBusiness,
9, 61-73. doi:
10.4236/ib.2017.94005.
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