کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
382818 660791 2014 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A prediction scheme using perceptually important points and dynamic time warping
ترجمه فارسی عنوان
یک طرح پیش بینی با استفاده از نقاط مهم ادراک شده و انحراف زمان پویا
کلمات کلیدی
نکات قابل توجه مهم، انحراف زمان دینامیک، پیش بینی غیر خطی، فرضیه بازار کارآمد
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• A novel, prediction scheme combining two celebrated data mining tools is proposed.
• PIPs are used to dynamically segment price series into subsequences.
• Dynamic time warping (DTW) is used to find similar historical subsequences.
• Predictions are made based from the mappings of the most similar subsequences.
• The proposed algorithm captures the deterministic structure in examined series.

An algorithmic method for assessing statistically the efficient market hypothesis (EMH) is developed based on two data mining tools, perceptually important points (PIPs) used to dynamically segment price series into subsequences, and dynamic time warping (DTW) used to find similar historical subsequences. Then predictions are made from the mappings of the most similar subsequences, and the prediction error statistic is used for the EMH assessment. The predictions are assessed on simulated price paths composed of stochastic trend and chaotic deterministic time series, and real financial data of 18 world equity markets and the GBP/USD exchange rate. The main results establish that the proposed algorithm can capture the deterministic structure in simulated series, confirm the validity of EMH on the examined equity indices, and indicate that prediction of the exchange rates using PIPs and DTW could beat at cases the prediction of last available price.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 41, Issue 15, 1 November 2014, Pages 6848–6860
نویسندگان
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