Improving N calculation of the RSI financial indicator using neural networks

Rodríguez‐González, Alejandro; Guldris-Iglesias, Fernando; Colomo‐Palacios, Ricardo; Alor-Hernández, Giner; Posada-Gómez, Rubén

doi:10.1109/icife.2010.5609252

Cited by 2 publications

(1 citation statement)

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“…There are many tools which technicians use to first describe and later identify the patterns in stock movements. These range from charting, where traders visually identify patterns in charts, technical market indicators, which usually consist of some mathematical formula encompassing a sliding window view of the market, to more complex tools, such as neural networks or a combination of neural networks and technical market indicators [20,21].…”

Section: Introductionmentioning

confidence: 99%

Rigorous specification and low-latency implementation of technical market indicators

Bakanov

Spence

Vandierendonck

et al. 2014

Proceedings of the First Workshop on Parallel Programming for Analytics Applications

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Technical market indicators are tools used by technical analysts to understand trends in trading markets. Technical (market) indicators are often calculated in real-time, as trading progresses. This paper presents a mathematicallyfounded framework for calculating technical indicators. Our framework consists of a domain specific language for the unambiguous specification of technical indicators, and a runtime system based on Click, for computing the indicators. We argue that our solution enhances the ease of programming due to aligning our domain-specific language to the mathematical description of technical indicators, and that it enables executing programs in kernel space for decreased latency, without exposing the system to users' programming errors.

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Section: Introductionmentioning

confidence: 99%