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Combining Measures of Signal Complexity and Machine Learning for Time Series Analyis: A Review

Sebastian Raubitzek, Thomas Neubauer
<span title="2021-12-13">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4d3elkqvznfzho6ki7a35bt47u" style="color: black;">Entropy</a> </i> &nbsp;
Measures of signal complexity, such as the Hurst exponent, the fractal dimension, and the Spectrum of Lyapunov exponents, are used in time series analysis to give estimates on persistency, anti-persistency  ...  They have proven beneficial when doing time series prediction using machine and deep learning and tell what features may be relevant for predicting time-series and establishing complexity features.  ...  ., in [16] , a hybrid approach of fuzzy logic, fractal dimension, and a neural network are used to make predictions of time series.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e23121672">doi:10.3390/e23121672</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/34945978">pmid:34945978</a> <a target="_blank" rel="external noopener" href="https://pubmed.ncbi.nlm.nih.gov/PMC8700684/">pmcid:PMC8700684</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/ppvnllvlhvemtpxkitg4aapvxe">fatcat:ppvnllvlhvemtpxkitg4aapvxe</a> </span>
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A Performance Comparison of Neural Networks in Forecasting Stock Price Trend

Binghui Wu, Tingting Duan
<span title="">2017</span> <i title="Atlantis Press"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/wjdkfhqywrdefeqoyzjz3os76i" style="color: black;">International Journal of Computational Intelligence Systems</a> </i> &nbsp;
After comparing network structures of different neural networks, the conclusions show Elman neural network has an obvious advantage over BP neural network in predicting price trend of Chinese stock market  ...  both in theory and practice.  ...  [12] discussed the fractal characteristics of stock market using time times and validation of time series model. Chimanga and Mlambo in Ref.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.2991/ijcis.2017.10.1.23">doi:10.2991/ijcis.2017.10.1.23</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/vcl6zoq2wzbupfbk62kau7zb7a">fatcat:vcl6zoq2wzbupfbk62kau7zb7a</a> </span>
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Application of Artificial Intelligence in Stock Market Forecasting: A Critique, Review, and Research Agenda

Ritika Chopra, Gagan Deep Sharma
<span title="2021-11-04">2021</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/6lgjjxyslvc5dad6vnqucsvtbi" style="color: black;">Journal of Risk and Financial Management</a> </i> &nbsp;
This paper reviews 148 studies utilizing neural and hybrid-neuro techniques to predict stock markets, categorized based on 43 auto-coded themes obtained using NVivo 12 software.  ...  Our findings highlight that AI techniques can be used successfully to study and analyze stock market activity.  ...  Acknowledgments: We would like to extend our gratitude towards Guru Gobind Singh Indraprastha University for providing us with the facilities and the infrastructure.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/jrfm14110526">doi:10.3390/jrfm14110526</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/jthkt5lwnfa3vmh43vtgoo3kue">fatcat:jthkt5lwnfa3vmh43vtgoo3kue</a> </span>
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Financial Time Series Image Algorithm Based on Wavelet Analysis and Data Fusion

Wuwei Liu, Jingdong Yan
<span title="">2021</span> <i title="Hindawi Limited"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/zlknqk4ahbcsthbafxw55emm7a" style="color: black;">Journal of Sensors</a> </i> &nbsp;
This paper mainly discusses a financial time series image algorithm based on wavelet analysis and data fusion.  ...  We use wavelet neural network with different input neurons and hidden neurons to predict, respectively.  ...  Neural networks are used for time series modeling, and time needs to be embedded in the network structure.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1155/2021/5577852">doi:10.1155/2021/5577852</a> <a target="_blank" rel="external noopener" href="https://doaj.org/article/d05eb40ee8cf401b913f6b292e8ac068">doaj:d05eb40ee8cf401b913f6b292e8ac068</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/33l5oxxpeffara6heeidf5xuja">fatcat:33l5oxxpeffara6heeidf5xuja</a> </span>
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Applications of neuro fuzzy systems: A brief review and future outline

Samarjit Kar, Sujit Das, Pijush Kanti Ghosh
<span title="">2014</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/spnlkxfb7fevrarnlb7rv32roy" style="color: black;">Applied Soft Computing</a> </i> &nbsp;
AI methods are mainly comprised of fuzzy logic, neural networks, genetic programming and hybrid approaches such as neuro fuzzy systems, genetic fuzzy systems and genetic programming neural networks etc  ...  Neuro-fuzzy systems refer to combinations of artificial neural network and fuzzy logic in the field of artificial intelligence, which was proposed by Jang [1] in 1993.  ...  Acknowledgment The authors wish to express sincere gratitude to the anonymous reviewers for their constructive comments and helpful suggestions, which lead to substantial improvements of this paper.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.asoc.2013.10.014">doi:10.1016/j.asoc.2013.10.014</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/iochb6rlgbhb5dmpmx7jeh54mu">fatcat:iochb6rlgbhb5dmpmx7jeh54mu</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170808235841/http://romisatriawahono.net/lecture/rm/survey/softcomputing/Kar%20-%20Neuro%20Fuzzy%20Systems%20-%202014.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/91/cb/91cb47a2cc0d1bb0f61b39e39d0c53a736b83f8d.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.asoc.2013.10.014"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> elsevier.com </button> </a>

Complexity testing techniques for time series data: A comprehensive literature review

Ling Tang, Huiling Lv, Fengmei Yang, Lean Yu
<span title="">2015</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/m277ldcfivaenohvc5kjxuddvi" style="color: black;">Chaos, Solitons &amp; Fractals</a> </i> &nbsp;
Complexity may be one of the most important measurements for analysing time series data; it covers or is at least closely related to different data characteristics within nonlinear system theory.  ...  In particular, a weaker self-similarity, a more complex structure of attractor, and a higherlevel disorder state of a system consistently indicate that the observed time series data are at a higher level  ...  , NSFC no. 71433001 and NSFC no. 71301006), National Program for Support of Top-Notch Young Professionals and the Fundamental Research Funds for the Central Universities in BUCT.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.chaos.2015.09.002">doi:10.1016/j.chaos.2015.09.002</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/mazo3tksxfbazgzea2njrb6w2i">fatcat:mazo3tksxfbazgzea2njrb6w2i</a> </span>
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Information Theoretic Measures and Their Applications

Osvaldo A. Rosso, Fernando Montani
<span title="2020-12-07">2020</span> <i title="MDPI AG"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/4d3elkqvznfzho6ki7a35bt47u" style="color: black;">Entropy</a> </i> &nbsp;
The concept of entropy, an ever-growing physical magnitude that measured the degree of decay of order in a physical system, was introduced by Rudolf Clausius in 1865 through an elegant formulation of the  ...  second law of thermodynamics [...]  ...  Acknowledgments: We express our thanks to the authors of the above contributions, the reviewers for their feedback on the manuscripts, and to the Entropy and MDPI for their support during this work.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e22121382">doi:10.3390/e22121382</a> <a target="_blank" rel="external noopener" href="https://www.ncbi.nlm.nih.gov/pubmed/33297309">pmid:33297309</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/tzuewqpdmrhvxep7uqukpyhrei">fatcat:tzuewqpdmrhvxep7uqukpyhrei</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20201211105005/https://res.mdpi.com/d_attachment/entropy/entropy-22-01382/article_deploy/entropy-22-01382.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/1d/ab/1dab05a75ff82a2c69e84c2576ef2155a779af24.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.3390/e22121382"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> mdpi.com </button> </a>

Cryptocurrency Trading: A Comprehensive Survey [article]

Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, Lingbo Li, David Martinez-Regoband, Fan Wu
<span title="2022-01-28">2022</span> <i > arXiv </i> &nbsp; <span class="release-stage" >pre-print</span>
and extreme conditions, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).  ...  This paper provides a comprehensive survey of cryptocurrency trading research, by covering 146 research papers on various aspects of cryptocurrency trading (e.g., cryptocurrency trading systems, bubble  ...  Conclusions We provided a comprehensive overview and analysis of the research work on cryptocurrency trading. This survey presented a nomenclature of the definitions and current state of the art.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener" href="https://arxiv.org/abs/2003.11352v5">arXiv:2003.11352v5</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/l7eih2yoazbq5i5lv4wh7c24ha">fatcat:l7eih2yoazbq5i5lv4wh7c24ha</a> </span>
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Cryptocurrency trading: a comprehensive survey

Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, David Martinez-Rego, Fan Wu, Lingbo Li
<span title="2022-02-07">2022</span> <i title="Springer Science and Business Media LLC"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/fbo3kqq2t5cetjcpypcwevp5yq" style="color: black;">Financial Innovation</a> </i> &nbsp;
and extreme condition, prediction of volatility and return, crypto-assets portfolio construction and crypto-assets, technical trading and others).  ...  This paper provides a comprehensive survey of cryptocurrency trading research, by covering 146 research papers on various aspects of cryptocurrency trading (e.g., cryptocurrency trading systems, bubble  ...  LSTM/RNN/GRUs include papers using neural networks that exploit the temporal structure of the data, a technology especially suitable for time series prediction and financial trading.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40854-021-00321-6">doi:10.1186/s40854-021-00321-6</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/d3d2pkxy5fgcfa4s6gi4h2snua">fatcat:d3d2pkxy5fgcfa4s6gi4h2snua</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20220207121928/https://jfin-swufe.springeropen.com/track/pdf/10.1186/s40854-021-00321-6.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/ea/42/ea42c1f6dbdd36a4776e4cd42ea7b06a1df252b8.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1186/s40854-021-00321-6"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="unlock alternate icon" style="background-color: #fb971f;"></i> springer.com </button> </a>

Program

<span title="">2009</span> <i title="IEEE"> 2009 International Joint Conference on Neural Networks </i> &nbsp;
Eva Kaslik P124 Effect of Refractoriness on Learning Performance of a Pattern Sequence Susumu Nagatoishi and Osamu Araki P125 Nonlinear Time Series Online Prediction Using Reservoir Kalman Filter Min Han  ...  Meher 5:40PM From an Artificial Neural Network to a Stock Market Day-Trading System: A Case Study on The BMF BOVESPA Leonardo Martinez, Diego Hora, Joao Palotti, Wagner Meira and Gisele Pappa 6:00PM  ...  P1325 Stegnalysis of MP3stego  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ijcnn.2009.5178575">doi:10.1109/ijcnn.2009.5178575</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/kxaceopferd23ps5uyrn3m7xjy">fatcat:kxaceopferd23ps5uyrn3m7xjy</a> </span>
<a target="_blank" rel="noopener" href="https://web.archive.org/web/20170830080122/https://www.computer.org/web/csdl/index/-/csdl/proceedings/ijcnn/2009/3548/00/05178575.pdf" title="fulltext PDF download" data-goatcounter-click="serp-fulltext" data-goatcounter-title="serp-fulltext"> <button class="ui simple right pointing dropdown compact black labeled icon button serp-button"> <i class="icon ia-icon"></i> Web Archive [PDF] <div class="menu fulltext-thumbnail"> <img src="https://blobs.fatcat.wiki/thumbnail/pdf/f3/9d/f39d4c6ab9aa5316b9af6b15ddf5580856482c8a.180px.jpg" alt="fulltext thumbnail" loading="lazy"> </div> </button> </a> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1109/ijcnn.2009.5178575"> <button class="ui left aligned compact blue labeled icon button serp-button"> <i class="external alternate icon"></i> ieee.com </button> </a>

Persistence in complex systems

S. Salcedo-Sanz, D. Casillas-Pérez, J. Del Ser, C. Casanova-Mateo, L. Cuadra, M. Piles, G. Camps-Valls
<span title="">2022</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/jpqyz5yp6vdibnpfaxmvgvtise" style="color: black;">Physics reports</a> </i> &nbsp;
The study of complex systems' persistence involves different definitions and uses different techniques, depending on whether short-term or long-term persistence is considered.  ...  Firstly, the most used definitions of persistence in short-term and long-term cases are presented. The most relevant methods to characterize persistence are then discussed in both cases.  ...  Acknowledgments This research has been partially supported by the project PID2020-115454GB-C21 of the Spanish Ministry of Science and Innovation (MICINN).  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1016/j.physrep.2022.02.002">doi:10.1016/j.physrep.2022.02.002</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/gkemhragnnaixplufrruyca4ci">fatcat:gkemhragnnaixplufrruyca4ci</a> </span>
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Econophysics of cryptocurrency crashes: an overview

Andrii Bielinskyi, Oleksandr Serdyuk, Serhiy Semerikov, Vladimir Soloviev, S. Semerikov, V. Soloviev, L. Kibalnyk, O. Chernyak, H. Danylchuk
<span title="">2021</span> <i title="EDP Sciences"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/dbuzp3mfvbefnluvdapck2fut4" style="color: black;">SHS Web of Conferences</a> </i> &nbsp;
We review the econophysics analysis methods and models adopted in or invented for financial time series and their subtle properties, which are applicable to time series in other disciplines.  ...  Cryptocurrencies refer to a type of digital asset that uses distributed ledger, or blockchain technology to enable a secure transaction.  ...  of the theory of quantum computation and quantum information [375] [376] [377] [378] where it would be interesting to see their influence on blockchain and cryptocurrencies.  ... 
<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1051/shsconf/202110703001">doi:10.1051/shsconf/202110703001</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/yoto2g5kb5gmnes5slz7hfcr7e">fatcat:yoto2g5kb5gmnes5slz7hfcr7e</a> </span>
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Book reports

<span title="">2002</span> <i title="Elsevier BV"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/nkrwe4pmozafvnd72yxufztpku" style="color: black;">Computers and Mathematics with Applications</a> </i> &nbsp;
Linear time series analysis. 11.1. Time series and noise. 11.2. ARIMA (p,d,q). 11.3. ARIMA model of time estimation. 11.4. Mixed regression-ARIMA model of psychophysical judgment. 12.  ...  Neural algorithms and applications. 11. Word recognition system using neural networks (H.Y.Y. Sanossian). I2. Self-organised evolutionary neural networks: Algorithms and applications (S.D.  ... 
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INCET 2020Conference Main Schedule

<span title="">2020</span> <i title="IEEE"> 2020 International Conference for Emerging Technology (INCET) </i> &nbsp;
network 12.00 PM 12.15 PM 5 341 Srinath Ravikumar and Prasad Saraf Prediction of Stock Prices using Machine Learning (Regression,Classification) Algorithms 12.15 PM 12.30 PM 6 376  ...  using Neural Networks 3.16 PM 3.30 PM 8 458 Harshit Barot, Arya Kothari, Pramod Bide, Bhavya Ahir and Romit Kankaria Analysis and Prediction for the Indian Premier League 3.31 PM 3.45 PM  ... 
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Complexity of Economical Systems

G. P. Pavlos, Democri tus University of Thrace, Department of Electrical Engineering, Xanthi, A. C. Iliopoulos, L. P. Karakatsanis, M. Xenakis, E. Pavlos, Democri tus University of Thrace, Department of Electrical Engineering, Xanthi, Democri tus University of Thrace, Department of Electrical Engineering, Xanthi, German Research School for Simulation Sciences, Aachen, Germany, Department of Physics, Aristotle University of Thessaloniki
<span title="">2015</span> <i title="Eastern Macedonia and Thrace Institute of Technology"> <a target="_blank" rel="noopener" href="https://fatcat.wiki/container/bdh2aivq6feixdfzfu2el5io6q" style="color: black;">Journal of Engineering Science and Technology Review</a> </i> &nbsp;
In addition a summary of an extended algorithm of nonlinear time series analysis is provided which is applied not only in economical time series but also in other physical complex systems (e.g. [22, 24  ...  In general, Economy is a vast and complicated set of arrangements and actions wherein agents-consumers, firms, banks, investors, government agencies-buy and sell, speculate, trade, oversee, bring products  ...  Acknowledgments The authors would like to thank the Organizing Committee of the 2nd International Conference on Econophysics. ______________________________ References  ... 
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