Do Candlestick Patterns Work in Cryptocurrency Trading?

Ho, Kin-Hon; Chan, Tse-Tin; Pan, Haoyuan; Li, Chin

doi:10.1109/bigdata52589.2021.9671826

Cited by 6 publications

(2 citation statements)

References 12 publications

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“…We will furthermore discuss existing techniques and services for SOR, which aim to reduce the slippage. Work that addresses fraud detection 12,13 or price prediction [14][15][16][17] is neglected in our presentation of the related work because it does not include order books to date.…”

Section: Related Workmentioning

confidence: 99%

Athena: Smart order routing on centralized crypto exchanges using a unified order book

Henker,

Atzberger,

Vollmer

et al. 2024

Int J Network Mgmt

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SummaryMost cryptocurrency spot trading occurs on centralized crypto exchanges, where offers for buying and selling are organized via an order book. In liquid markets, the price achieved for buying and selling deviates only slightly from the assumed reference price, that is, trading is associated with low implicit costs. However, compared to traditional finance, crypto markets are still illiquid, and consequently, the reduction of implicit costs is crucial for any trading strategy and of high interest, especially for institutional investors. This paper describes the design and implementation of Athena, a system that automatically splits orders across multiple exchanges to minimize implicit costs. For this purpose, order books are collected from several centralized crypto exchanges and merged into an internal unified order book. In addition to price and quantity, the entries in the unified order book are enriched with information about the exchange. This enables a smart order routing algorithm to split an order into several slices and execute these on several exchanges to reduce implicit costs and achieve a better price. An extensive evaluation shows the savings of using the smart order routing algorithm.

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Section: Related Workmentioning

confidence: 99%

Athena: Smart order routing on centralized crypto exchanges using a unified order book

Henker,

Atzberger,

Vollmer

et al. 2024

Int J Network Mgmt

View full text Add to dashboard Cite

show abstract

“…Another method, using diagrams, is candlestick patterns, which are understood as a pre-defined set of candlesticks that can signal investors to buy or sell. However, this method might have higher chances of success when used with stocks or the forex market; it has no value for cryptocurrency traders (Ho, Chan, Pan, Li, 2021).…”

Section: Introductionmentioning

confidence: 99%

How many neurons are needed to make a short-term prediction of the Bitcoin exchange rate?

Frontczak

Hachaj

2022

Tech.Trans.

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The goal of our work was to select a neural network architecture that would give the best prediction of the Bitcoin exchange rate using historical data. Our work fits into the very important topic of predicting the value of the cryptocurrency exchange rate, and makes use of recent data which, as a result of the high Bitcoin exchange rate dynamics of the last year, differs significantly from those of previous years. We propose and test a number of neural network-based architectures and conduct a discussion of the results. Unlike previous state-of-the-art works, we conducted a comprehensive comparison of three different neural network-based models: MLP (multilayer perceptron), LSTM (long short-term memory) and CNN (convolutional neural network). We tested them for a wide range of parameters. The results we present are, to the best of our knowledge, the most up to date when it comes to the application of artificial intelligence methods for the prediction of cryptocurrency exchange rates. The best-performing architectures were used for a website that gives real-time predictions of the Bitcoin exchange rate. The website is available at http://stpbtc-ii.up.krakow.pl/. Source codes of our research are available to download in order to make our experiment reproducible.

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Hephaistos: A Management System for Massive Order Book Data from Multiple Centralized Crypto Exchanges with an Internal Unified Order Book

Henker,

Atzberger,

Vollmer

et al. 2023

2023 IEEE International Conference on Blockchain and Cryptocurrency (ICBC)

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Do Candlestick Patterns Work in Cryptocurrency Trading?

Cited by 6 publications

References 12 publications

Athena: Smart order routing on centralized crypto exchanges using a unified order book

Athena: Smart order routing on centralized crypto exchanges using a unified order book

How many neurons are needed to make a short-term prediction of the Bitcoin exchange rate?

Hephaistos: A Management System for Massive Order Book Data from Multiple Centralized Crypto Exchanges with an Internal Unified Order Book

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