Analysis of outliers and public information arrivals using wavelet transform modulus maximum

Che, Wen-Gang; Chi, Kai; Zhao, Qingjiang

doi:10.1109/icife.2010.5609276

Cited by 3 publications

(2 citation statements)

References 7 publications

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“…Previously, we already proposed a singular point detection method in stock time series based on wavelet transform, where singularity using wavelet modulus maxima determination is employed [1]. In [2], we also proposed another method to determine the singularity point from sliding windows.…”

Section: Introductionmentioning

confidence: 99%

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The Motif Detection of Short-term Tendency in Stock Time Series

Che¹

2015

Proceedings of the 2015 International Conference on Applied Science and Engineering Innovation

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Abstract.A stock time series is composed of a sequence of prices measured from a continuous trade day. Stock motifs are approximately similar segments in a group of different stock time series or market dataset. In this paper, at first, a definition of short-term tendency is defined; secondly, a motif of short-term tendency is introduced in the stock time series. And then a simple and effective method of stock motif detection is proposed to predict the short-term tendency in the stock time series analysis. Finally, a new motif detection of short-term tendency is introduced to predict the trend of temporal stock market trend. An empirical analysis is made to show the efficiency of the proposed method.

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Section: Introductionmentioning

confidence: 99%

“…Therefore, a method to find a particular pattern and tuning point are more practical and interested. As we know, there are already some results presented in this area, such as the ones based on wavelet analysis [1], density [2], boundary and distance [3], clustering [4] and motif of k-NN clustering algorithm [5] etc.…”

Section: Introductionmentioning

confidence: 99%

The Motif Detection of Short-term Tendency in Stock Time Series

Che¹

2015

Proceedings of the 2015 International Conference on Applied Science and Engineering Innovation

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A Study on the Motif Pattern of Dark-Cloud Cover in the Securities

Long

Che

et al. 2017

MATEC Web Conf.

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Morphological analysis is the analysis and mining of the graphics formed of the securities price changes. Investors need to forecast the trend of future before buying and selling points, which can avoid great loss. Therefore, the analysis of motif pattern of K-line in the form of futures investment technology analysis is very significant. Based on the thoughts of short-term trend clustering, this paper proposes a method of detecting the motif pattern of Dark-Cloud Cover in stock time series by analysing stock historic data and K-line shape, in order to predict the stock market trends. And we prove the effectiveness and practicality of the method by a series of experimental analysis. The related definitionsThe models, commonly used by traditional financial time series analysis are mostly a comprehensive description

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Remarks on outliers in time series of stock prices based on density

Zhao

Gan

Che

2012

Proceedings of the 10th World Congress on Intelligent Control and Automation

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How to detect the outlier of stock prices effectively has become an intense concern of scholars in many fields. In this paper, the thoughts of Statistical theory and local density are introduced for researching the outliers in stock time series. A method detecting the outlier of stock time series based on density is proposed. Study on the outlier of time series in stock market is dealt with in two stages. In the first stage, the time series is partitioned by means of the sliding window with fixed length. In the second stage, the density-based method is introduced to detect the outliers with the local outlier factor. Empirical study, based on the daily closing price of SSE Composite Index, proved that the method is feasible and effective.

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Analysis of outliers and public information arrivals using wavelet transform modulus maximum

Cited by 3 publications

References 7 publications

The Motif Detection of Short-term Tendency in Stock Time Series

The Motif Detection of Short-term Tendency in Stock Time Series

A Study on the Motif Pattern of Dark-Cloud Cover in the Securities

Remarks on outliers in time series of stock prices based on density

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