{"id":25452830,"url":"https://github.com/yllvar/obi_rfclassifier","last_synced_at":"2025-10-10T04:36:36.093Z","repository":{"id":227902165,"uuid":"772676606","full_name":"yllvar/OBI_RFclassifier","owner":"yllvar","description":"Random Forest Classifier over Kucoin Futures Order Book Imbalance Data and RSI ","archived":false,"fork":false,"pushed_at":"2024-03-15T17:13:00.000Z","size":13,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-10-10T04:36:35.034Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/yllvar.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2024-03-15T17:02:47.000Z","updated_at":"2024-03-15T17:07:20.000Z","dependencies_parsed_at":"2024-03-15T18:28:17.128Z","dependency_job_id":"bbef0cc7-4466-44ed-9359-d0c4e04c235d","html_url":"https://github.com/yllvar/OBI_RFclassifier","commit_stats":null,"previous_names":["yllvar/obi_rfclassifier"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/yllvar/OBI_RFclassifier","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yllvar%2FOBI_RFclassifier","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yllvar%2FOBI_RFclassifier/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yllvar%2FOBI_RFclassifier/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yllvar%2FOBI_RFclassifier/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/yllvar","download_url":"https://codeload.github.com/yllvar/OBI_RFclassifier/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/yllvar%2FOBI_RFclassifier/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":279002667,"owners_count":26083442,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","status":"online","status_checked_at":"2025-10-10T02:00:06.843Z","response_time":62,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2025-02-17T23:41:45.066Z","updated_at":"2025-10-10T04:36:36.065Z","avatar_url":"https://github.com/yllvar.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# OBI_RFclassifier\n### Introduction:\n\nThis strategy blends technical analysis with machine learning for cryptocurrency trading decisions. While promising, it requires thorough validation, robust risk management, and cautious deployment in live trading. Continuous monitoring and adaptation are essential for optimal outcomes in evolving market conditions.\n\n### Strategy Overview:\nThis Python-based trading strategy combines technical indicators and machine learning to guide decisions in cryptocurrency trading. It identifies opportunities by analyzing indicators like the Relative Strength Index (RSI) and order book imbalances.\n\n### Components and Functionalities:\n1. **Initialization**: Sets up API connections, logging, and parameters.\n2. **Data Collection**: Fetches OHLCV data and order book info.\n3. **Technical Analysis**:\n   - **RSI Calculation**: Identifies market conditions (overbought/oversold).\n   - **Order Book Analysis**: Assesses market liquidity and buy/sell imbalances.\n4. **Machine Learning Integration**:\n   - **Data Preprocessing**: Scales and prepares historical data.\n   - **Model Training**: Trains a Random Forest Classifier.\n   - **Prediction**: Predicts market directions using the model.\n5. **Trade Execution**:\n   - **Signal Generation**: Generates trading signals based on indicators.\n   - **Order Placement**: Places limit orders with take-profit and stop-loss levels.\n6. **Logging and Monitoring**:\n   - **Logging**: Records signals, analysis results, and errors.\n   - **Error Handling**: Implements mechanisms for graceful error handling.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyllvar%2Fobi_rfclassifier","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyllvar%2Fobi_rfclassifier","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyllvar%2Fobi_rfclassifier/lists"}