Examples
To run the ccxt examples from any folder type one of the following commands in console.
node path/to/example.js # substitute for actual filename hereThese examples might require the following super-useful high-quality Node.js modules by xpl:
- ololog: Platform-agnostic logging with blackjack and hookers (ololog @ npm)
- ansicolor: A quality JavaScript library for the ANSI color/style management (ansicolor @ npm)
- as-table: A simple function that prints objects as ASCII tables (as-table @ npm)
All of the modules above are installed with the ccxt library devDependencies by npm automatically.
php -f path/to/example.php # substitute for actual filename here
python path/to/example.py # substitute for actual filename here-
Do Whitepaper Claims Predict Market Behavior?
2026, Murad Farzulla (Dissensus AI, King’s College London) -
An Adaptive Neuro-Fuzzy Blockchain–AI Framework for Secure and Intelligent FinTech Transactions
2026, Gunjan Mishraa, Yash Mishrab (Lakshmipat University) -
A Unified GRU Model for Cryptocurrency Price Prediction and Harsh Price Movement Detection Using Enhanced Sentiment Analysis
2026, Mahmood Mohammadi Nezhad, Saeed Rouhani, Navid Mohammadi (University of Tehran), Ali Shahedi (Sharif University of Technology) -
Bitcoin Price Prediction Using Machine Learning in Python
2025, Thillainayagi S, Pavan P, Shashank S, Preetham LV, Vishwanath BY (East West College of Engineering, Bangalore, India) -
Evaluating machine learning models for predictive
2025, Shavez Mushtaq Qureshi, Asad Rehman Khattak, Muhammad Shah Rukh (Qarshi University), Atif Saeed, Farooq Ahmad (COMSATS University Islamabad), Sultan H. Almotiri, Mohammed A. Al Ghamdi (Umm Al-Qura University) -
Machine Learning-Based Detection of Pump-and-Dump Schemes in Real-Time
2024, Manuel Bolz, Kevin Bründler, Liam Kane, Panagiotis Patsias, Liam Tessendorf, Krzysztof M. Gogol, Taehoon Kim, Claudio J. Tessone (University of Zurich) -
Forecasting cryptocurrency's buy signal with a bagged tree learning approach to enhance purchase decisions
2024, Raed Alsini, Abdulaziz A Alsulami, Abdulaziz A Alqurashi, Nawaf Alhebaishi, Badraddin Alturki, Mouhamad D Mashat (King Abdulaziz University), Qasem Abu Al-Haija (Jordan University of Science and Technology), Ali Alqahtani, (Najran University) -
A Hybrid COMTE-LEFTIST Time-Series Explanation Method For a Time-series Classification Bitcoin Recommendation System
2024, Lucas Rabelo de Araujo Morais, Teresa Bernarda Ludermir (Universidade Federal de Pernambuco) -
Deep Complex Networks: Applications in Financial Systems Modeling
2024, Antonio Briola (University College London) -
FTX’s downfall and Binance’s consolidation: the fragility of Centralized Digital Finance
2023, David Vidal-Tom´as, Antonio Briola, Tomaso Astea (University College London) -
Detecting Pump-and-Dumps with Crypto-Assets
2023, Dean Fantazzini, Yufeng Xiao (Moscow State University) -
Detecting Depegs: Towards Safer Passive Liquidity Provision on Curve Finance
2023, Thomas Cintra, Max Holloway (Xenophon Labs) -
Development Of A Cryptocurrency Bot
2023, José Manuel Rodríguez Lomeña (Universitat Polit`ecnica de Catalunya) -
Dependency Structures in Cryptocurrency Market from High to Low Frequency
2022, Antonio Briola (University College London), Tomaso Astea (London School Of Economics) -
Anatomy of a Stablecoin’s failure: the Terra-Luna case
2022, Antonio Briola, David Vidal-Tom´as, Yuanrong Wanga (University College London), Tomaso Astea (London School Of Economics) -
FreqAI: generalizing adaptive modeling for chaotic time-series forecasting
2022, Robert A. Caulk, Elin Törnquist, Matthias Voppichler, Andrew R. Lawless, Ryan McMullan, Wagner Costa Santos, Timothy C. Pogue, Johan van der Vlugt, Stefan P. Gehring, Pascal Schmidt (Freqtrade) -
Analysis and Implementation of Arbitrage Bots in Centralized and Decentralized Finance
2022, Claudio Gebbia (University of Zurich) -
Hybrid Cryptocurrency Pump and Dump Detection
2020, Hadi Mansourifar, Weidong Shi (University of Houston), Lin Chen (Texas Tech University) -
Cryptocurrency Trading: A Comprehensive Survey
2020, Fan Fang, Carmine Ventre, Michail Basios, Leslie Kanthan, David Martinez-Rego, Fan Wu, Lingbo Li (King’s College London) -
Algorithm for cryptocurrency price discrepancy detection
2020, Imre Lendak, Marta Patiño Martínez, Gergely Tyukodi, Daniel Minguez Camacho (Universidad Politécnica de Madrid) -
An Empirical Analysis of the Python Package Index (PyPI)
2019, Ethan Bommarito, Michael J Bommarito II (University of Michigan) -
To the moon: defining and detecting cryptocurrency pump-and-dumps
2018, Josh Kamps (VU University Amsterdam), Bennett Kleinberg (University College London)