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AI Summary & Key Takeaways
AI Insight⚡ TL;DR(Too Long; Didn't Read)
With the well-known time series analysis tools, we show that the future market values are sequentially unpredictable.
📌 3 Key Takeaways
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Objective & Hypothesis:In nonlinear time series analysis, the largest Lyapunov exponent, which, if positive, is the evidence for chaos.
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Key Findings & Data:In this paper, we investigate chaos in IMKB100 time series data with Lyapunov Exponent Method.
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Conclusion & Impact:With the well-known time series analysis tools, we show that the future market values are sequentially unpredictable.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Lyapunov Üsteli · Kaos teorisi · Borsa
Abstract
In nonlinear time series analysis, the largest Lyapunov exponent, which, if positive, is the evidence for chaos. In this paper, we investigate chaos in IMKB100 time series data with Lyapunov Exponent Method. With the well-known time series analysis tools, we show that the future market values are sequentially unpredictable.
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Cite This Article
ALPAR, O., EREN, Ö. (2016). INVESTIGATION OF CHAOS IN IMKB100 CHANGE VALUES VIA LYAPUNOV EXPONENT METHOD. İstanbul Aydın Üniversitesi Sosyal Bilimler Dergisi, Cilt: 8 - Sayı: 30, 151–174. https://ajindex.com/articles/771810