Identification of market trends with string and D2-brane maps

Bartoš, Erik; Pinčák, Richard

doi:10.1016/j.physa.2017.03.014

Cited by 13 publications

(5 citation statements)

References 29 publications

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“…Erik and Richard [75] proposed multidimensional string models which can be used for time series forecasting. They enhanced the 1-endpoint open string model with a 2-endpoint open string model combined with D2-brane.…”

Section: Pattern Based Methodsmentioning

confidence: 99%

“…Recurrent reinforcement learning (RL), dynamic model averaging (DMA), dynamic conditional correlation (DCC) algorithm, etc., were explored by the researchers. Pattern-based approaches also proved their versatile adapt-ability through their uses in different models [73][74][75][76][77][78][79]. Some systems based on patterns can change the statistics of the predictors by using the object properties [75] that can be applied to design a variety of time series systems.…”

Section: Pattern Based Methodsmentioning

confidence: 99%

“…Pattern-based approaches also proved their versatile adapt-ability through their uses in different models [73][74][75][76][77][78][79]. Some systems based on patterns can change the statistics of the predictors by using the object properties [75] that can be applied to design a variety of time series systems. However, some pattern-based systems are contradictory to each other, as some models perform well and provide good results with a specific algorithm [76], while other systems perform just the opposite [73].…”

Section: Pattern Based Methodsmentioning

confidence: 99%

See 2 more Smart Citations

A Review on Recent Advancements in FOREX Currency Prediction

Islam¹,

Hossain

Rahman³

et al. 2020

Algorithms

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In recent years, the foreign exchange (FOREX) market has attracted quite a lot of scrutiny from researchers all over the world. Due to its vulnerable characteristics, different types of research have been conducted to accomplish the task of predicting future FOREX currency prices accurately. In this research, we present a comprehensive review of the recent advancements of FOREX currency prediction approaches. Besides, we provide some information about the FOREX market and cryptocurrency market. We wanted to analyze the most recent works in this field and therefore considered only those papers which were published from 2017 to 2019. We used a keyword-based searching technique to filter out popular and relevant research. Moreover, we have applied a selection algorithm to determine which papers to include in this review. Based on our selection criteria, we have reviewed 39 research articles that were published on “Elsevier”, “Springer”, and “IEEE Xplore” that predicted future FOREX prices within the stipulated time. Our research shows that in recent years, researchers have been interested mostly in neural networks models, pattern-based approaches, and optimization techniques. Our review also shows that many deep learning algorithms, such as gated recurrent unit (GRU) and long short term memory (LSTM), have been fully explored and show huge potential in time series prediction.

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Section: Pattern Based Methodsmentioning

confidence: 99%

Section: Pattern Based Methodsmentioning

confidence: 99%

Section: Pattern Based Methodsmentioning

confidence: 99%

See 1 more Smart Citation

A Review on Recent Advancements in FOREX Currency Prediction

Islam¹,

Hossain

Rahman³

et al. 2020

Algorithms

View full text Add to dashboard Cite

show abstract

“…In [26][27][28], we introduced a new representation of the genetic code in the time series using a modeling by strings and D-branes. By applying a spinor field to a superspace in time series data [29], the method allows us to develop supersymmetry for living organisms.…”

Section: Spinor Fields In Biological Systemsmentioning

confidence: 99%

Application of Spin-Orbit Coupling in Exotic Graphene Structures and Biology

Pinčák¹,

Bartoš²

2020

Solid State Physics [Working Title]

Self Cite

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An important measurable quantity in the carbon nanostructures, including the nanotubular part of the graphitic wormhole, is the spin-orbit coupling. We will present in this chapter spin-orbit coupling for the fermions located in exotic graphene structures as is graphene wormhole and also in biological systems. Considering this influence, the two-component Dirac equation is changed into the usual four-component form. As a consequence, the chiral fermions should be detected close to the wormhole bridge. We will show that the smaller is the radius of the wormhole bridge, the stronger this effect should be. Finally, we will describe the role of spinor fields in the time series of genetic code. The reversed transcription process of the gene expression could be defined by a moduli state space model of a coupling spinor field between the gene of a viral particle and the host cell. As a general result, all states of codon can be computed by the Chern-Simons 3-forms.

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“…Here, we introduce a new representation of the genetic code in the time series for a string and a D-brane [48][49][50][51] modeling by applying a spinor field to a superspace in a time series data [52,53] over the viral glycoprotein [54] and a viral replication gene [55]. The method allows to develop supersymmetry for living organisms.…”

Section: Introductionmentioning

confidence: 99%

The Chern‐Simons Current in Systems of DNA‐RNA Transcriptions

et al. 2018

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A Chern-Simons current, coming from ghost and anti-ghost fields of supersymmetry theory, can be used to define a spectrum of gene expression in new time series data where a spinor field, as alternative representation of a gene, is adopted instead of using the standard alphabet sequence of bases A, T, C, G, U . After a general discussion on the use of supersymmetry in biological systems, we give examples of the use of supersymmetry for living organism, discuss the codon and anti-codon ghost fields and develop an algebraic construction for the trash DNA, the DNA area which does not seem active in biological systems. As a general result, all hidden states of codon can be computed by Chern-Simons 3 forms. Finally, we plot a time series of genetic variations of viral glycoprotein gene and host T-cell receptor gene by using a gene tensor correlation network related to the Chern-Simons current. An empirical analysis of genetic shift, in host cell receptor genes with separated cluster of gene and genetic drift in viral gene, is obtained by using a tensor correlation plot over time series data derived as the empirical mode decomposition of Chern-Simons current.

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Identification of market trends with string and D2-brane maps

Cited by 13 publications

References 29 publications

A Review on Recent Advancements in FOREX Currency Prediction

A Review on Recent Advancements in FOREX Currency Prediction

Application of Spin-Orbit Coupling in Exotic Graphene Structures and Biology

The Chern‐Simons Current in Systems of DNA‐RNA Transcriptions

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