MGPraxis6,400 papers identified by name

Utilizing RNN for Real-time Cryptocurrency Price Prediction and Trading Strategy Optimization

Shamima Nasrin Tumpa, Kehelwala Dewage Gayan Maduranga·2024

“The project follows a structured approach involving data collection, preprocessing, and model refinement, followed by rigorous backtesting for profitability and risk assessment.”

AssetCryptospot crypto
StrategyMachine learning
TechniqueRecurrent neural networkfeedforward network
ClaimProfit

Missing from abstract: benchmark, out-of-sample test, costs, multiple testing, universe

Institutional-grade audit of this strategy.
£5 — Request the audit
  • Audit of the paper claims accounting for costs, luck, crises, originality, geography, etc.
  • Reproduction code integratable into Bloomberg, IBKR, etc.
  • Bias-free datasets for backtesting included
  • Delivered in 2 working days
The paper's neighbourhoodMachine learning return prediction by year
■ crypto■ equities■ commodities■ bonds and credit■ other assets20102015202011This paper2024622026■ crypto■ equities■ commodities■ bonds and credit■ other assets20102015202011This paper2024
The family is counted across the whole universe. Asset, method and authors are counted inside the family.
Similar paperscitationsame methodsame assetsame authors
Meta-Learning Reinforcement Learning for Crypto-Return Prediction by Wang et al.2026
Cryptocurrency return prediction: A machine learning analysis by Li et al.2024
Exploring the Advantages of Transformers for High-Frequency Trading by Barez et al.2023
Constructing trading strategy ensembles by classifying market states by Balcerak and Schmelzer2020
Bitcoin Technical Trading With Artificial Neural Network by Nakano et al.2018
Not yet audited by MarketGraphs Praxis. Tags from the abstract. Counts from the universe.
RSS · Contacts