swarmex
Unverified ML strategy on Forex by JurgenPalsma. BotFinder score 18 out of 100.
Optimising a FOREX trading strategy with nature inspired algorithms
Source: github
BotFinder analysis pending.
swarmex
Optimizing FOREX trading strategies with natured-inspired machine learning The goal of the project is to optimize trading strategies based on Directional Changes using nature inspired optimization algorithms. Algorithms used: - Particle Swarm Optimization (PSO) - A custom algo based on shuffled frog leaping - Continuous Shuffled Frog Leaping (CSFLA) To do so, I use the trading strategy provided by [[1]](http://www.kampouridis.net/papers/DC-GA.pdf) which use Genetic Algorithms to find a suitable set of parameters for a Directional Change - based strategy. The problem can be resumed to optimizing a fitness function - which is the performance of the trading strategy given a set of parameters. To ensure robustness of my proposed algorithms, I test them with the same configuration that the authors in [[1]](http://www.kampouridis.net/papers/DC-GA.pdf). Contents This repository contains: 1. Custom, from scratch implementations of the PSO and CSFLA algorithms, in the .py files in the root of the repository 2. 12 months of 10-min FOREX data on 4 currency pairs, in the data/ folder, used to tr
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