πŸ“„
Developing and testing a custom algorithmic trading strategy using exponential moving average, relative strength index, and sentiment analysis paper by Independent / Community
⭐ 65.6
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Paper

Developing and testing a custom algorithmic trading strategy using exponential moving average, relative strength index, and sentiment analysis

by Independent / Community 01277853d02b0b922082b1db3f236920db6534a7
Free2AITools Nexus Index
65.6
S: Semantic 50

Query-time baseline · scored live at search

A: Authority 76
P: Popularity 51
R: Recency 100
Q: Quality 65
Tech Context
Vital Performance —

Stock trading is a popular and important profession that requires near-to-perfect data analytical skills, mathematical and statistical knowledge, and a broad understanding of buying and selling stocks. Often, due to the number of factors to consider and the intervention of human bias, traders and investors make wrong decisions that cost them millions of dollars. Therefore, automated algorithmic trading has gained traction in the marketplace due to its ability to process huge amounts of data, ...

Source β†’
Semantic Scholar 10 Citations
Paper Information Summary
Entity Passport
Registry ID 01277853d02b0b922082b1db3f236920db6534a7
License ArXiv
Provider semantic_scholar
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Cite this paper

Academic & Research Attribution

BibTeX 
@misc{01277853d02b0b922082b1db3f236920db6534a7,
  author = {Unknown},
  title = {Developing and testing a custom algorithmic trading strategy using exponential moving average, relative strength index, and sentiment analysis Paper},
  year = {2026},
  howpublished = {\url{https://api.semanticscholar.org/01277853d02b0b922082b1db3f236920db6534a7}},
  note = {Accessed via Free2AITools.}
}
APA Style
Unknown. (2026). Developing and testing a custom algorithmic trading strategy using exponential moving average, relative strength index, and sentiment analysis [Paper]. Free2AITools. https://api.semanticscholar.org/01277853d02b0b922082b1db3f236920db6534a7

πŸ”¬Technical Deep Dive

Full Specifications [+]

βš–οΈ Free2AITools Nexus Index V2.0

Methodology How FNI works
Semantic (S) 50

Query-time baseline · scored live at search

Authority (A) 76
Popularity (P) 51
Recency (R) 100
Quality (Q) 65

πŸ’¬ Index Insight

FNI V2.0 for Developing and testing a custom algorithmic trading strategy using exponential moving average, relative strength index, and sentiment analysis: Authority (A:76), Popularity (P:51), Recency (R:100), Quality (Q:65). Semantic (S) is a query-time baseline scored live at search.

Free2AITools Nexus Index

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HuggingFace API GitHub Metadata Arxiv Citation DB Methodology
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πŸ“ Executive Summary

"Stock trading is a popular and important profession that requires near-to-perfect data analytical skills, mathematical and statistical knowledge, and a broad understanding of buying and selling stocks. Often, due to the number of factors to consider and the intervention of human bias, traders and investors make wrong decisions that cost them millions of dollars. Therefore, automated algorithmic trading has gained traction in the marketplace due to its ability to process huge amounts of data, ..."

❝ Cite Node 

@article{Unknown2026Developing,
  title={Developing and testing a custom algorithmic trading strategy using exponential moving average, relative strength index, and sentiment analysis},
  author={},
  note={Indexed by Free2AITools},
  year={2026}
}

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πŸ“Š Research Signals

πŸ“ˆ10CitationsSemantic Scholar
πŸ›οΈ76AuthorityFNI pillar
⏱️100RecencyFNI pillar
βœ…65QualityFNI pillar
πŸ—‚οΈknowledge retrievalField
πŸ“¦Data Source: semantic_scholar
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πŸ†” Identity & Source

source
semantic_scholar
author
Unknown
license
ArXiv
tags
paper, research, academic

βš™οΈ Technical Specs

architecture
null
params billions
null
context length
null
pipeline tag

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citations
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