{"id":21043119,"url":"https://github.com/mrinalxdev/flowtrade","last_synced_at":"2025-12-30T07:26:09.686Z","repository":{"id":212915286,"uuid":"732479156","full_name":"mrinalxdev/FlowTrade","owner":"mrinalxdev","description":"A algorithm for trading built in golang","archived":false,"fork":false,"pushed_at":"2023-12-28T22:42:29.000Z","size":3545,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-20T17:21:58.484Z","etag":null,"topics":["go"],"latest_commit_sha":null,"homepage":"","language":"Go","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/mrinalxdev.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,"publiccode":null,"codemeta":null}},"created_at":"2023-12-16T20:08:13.000Z","updated_at":"2024-05-21T17:05:32.000Z","dependencies_parsed_at":"2024-11-19T14:11:21.553Z","dependency_job_id":"6c1b7b52-ca4c-4029-8474-570768b6922f","html_url":"https://github.com/mrinalxdev/FlowTrade","commit_stats":null,"previous_names":["mrinalxdev/godevs","mrinalxdev/flowtrade"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mrinalxdev%2FFlowTrade","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mrinalxdev%2FFlowTrade/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mrinalxdev%2FFlowTrade/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/mrinalxdev%2FFlowTrade/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/mrinalxdev","download_url":"https://codeload.github.com/mrinalxdev/FlowTrade/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243489812,"owners_count":20298997,"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","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":["go"],"created_at":"2024-11-19T14:11:04.927Z","updated_at":"2025-12-30T07:26:09.648Z","avatar_url":"https://github.com/mrinalxdev.png","language":"Go","readme":"\u003cimg align=\"center\" src=\"banner.png\" alt=\"banner image\"\u003e\n\n\u003eTest algorithmic trading strategies in a risk-free Golang simulator.\n\n```Note the prices inlist are not the real ones```\n\nTradeFlow is a comprehensive financial simulation project developed in Golang that allows users to model and test algorithmic trading strategies in a controlled environment. The project incorporates various components, including a trading algorithm, portfolio management, market data simulation, and utilities for random data generation.\n\n\u003cimg src=\"algo.png\" alt=\"screenshot\" align=\"center\"\u003e\n\n## Key Features of the algorithm \n\n1. Trading Algorithm : The simulator includes a robust trading algorithm that executes buy and sell orders based on user-defined parameters. It considers factors such as order size, risk per trade, trailing stop loss, and simple moving average to make informed trading decisions.\n\n2. Portfolio Management : The portfolio management module tracks the user's portfolio, managing cash, open positions, and overall risk exposure. It allows for deposits, withdrawals, and provides a historical record of trades.\n\n3. Market Data Simulation: Simulated market data introduces realistic price fluctuations for various symbols, enabling users to assess the performance of their trading algorithms under diverse market conditions.\n\n4. Utility Functions: The utility package includes essential functions such as generating unique trade IDs, random prices, and other auxiliary operations crucial for the simulation.\n\n## Advantages in the Real World:\n\n- Risk-Free Strategy Testing: Traders and financial analysts can use this simulator to test and refine their algorithmic trading strategies in a risk-free environment before deploying them in live markets. This can potentially save significant financial losses associated with untested strategies.\n\n- Educational Tool: The simulator serves as an educational tool for students, developers, and anyone interested in algorithmic trading. Users can gain hands-on experience in understanding market dynamics, risk management, and the implementation of trading algorithms.\n\n- Portfolio Management Practice: Traders can experiment with different portfolio management strategies, optimize risk exposure, and learn how to balance positions effectively. This practical experience contributes to more informed decision-making in real-world trading scenarios.\n\n## Use Cases:\n\n- Algorithmic Trading Development: Quantitative analysts and algorithmic traders can use the simulator to develop, test, and optimize their trading algorithms before deploying them in live markets.\n\n- Financial Education: Educational institutions and online learning platforms can leverage the simulator to teach students and enthusiasts about algorithmic trading concepts, market dynamics, and risk management.\n\n- Trader Skill Enhancement: Individual traders can use the simulator to enhance their trading skills, experiment with various strategies, and gain confidence in their decision-making abilities without risking real capital.\n\n- Investment Strategy Validation: Institutional investors and hedge funds can use the simulator to validate and fine-tune their investment strategies, ensuring that their algorithms align with their risk tolerance and overall investment objectives.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmrinalxdev%2Fflowtrade","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmrinalxdev%2Fflowtrade","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmrinalxdev%2Fflowtrade/lists"}