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Abstract
This article studies the performance improvement of technical analysis with the application of empirical mode decomposition. The study employs data from the Hong Kong stock market and addresses issues arising from gaps in intraday data. The results support the use of empirical mode decomposition in technical analysis to improve performance.
TOPICS: Technical analysis, emerging markets, statistical methods, performance measurement
Key Findings
▪ Empirical mode decomposition improves technical analysis profitability via denoising before candlestick construction.
▪ Empirical results show 68 basis points of profitability improvement a year on average in the Hong Kong stock market.
▪ Empirical results are robust regardless of the methods to handle the lunch gap in the data.
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