{"id":16135641,"url":"https://github.com/thevickypedia/throne-trader","last_synced_at":"2026-04-02T02:06:19.116Z","repository":{"id":182929457,"uuid":"669338330","full_name":"thevickypedia/throne-trader","owner":"thevickypedia","description":"A collection of algorithms to analyze, categorize and predict stocks.","archived":false,"fork":false,"pushed_at":"2024-05-18T05:53:46.000Z","size":423,"stargazers_count":2,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-01-01T00:58:58.520Z","etag":null,"topics":["analysis-algorithms","buy-and-sell-indicator","machine-learning-algorithms","prediction-algorithm","stock-analyzer"],"latest_commit_sha":null,"homepage":"https://vigneshrao.com/stock-analysis","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/thevickypedia.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2023-07-22T01:13:03.000Z","updated_at":"2025-02-24T07:11:45.000Z","dependencies_parsed_at":"2023-07-22T05:39:11.431Z","dependency_job_id":"fe51d866-82ec-4c58-93b5-4ec596525026","html_url":"https://github.com/thevickypedia/throne-trader","commit_stats":null,"previous_names":["thevickypedia/trading-algorithm"],"tags_count":4,"template":false,"template_full_name":null,"purl":"pkg:github/thevickypedia/throne-trader","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thevickypedia%2Fthrone-trader","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thevickypedia%2Fthrone-trader/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thevickypedia%2Fthrone-trader/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thevickypedia%2Fthrone-trader/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/thevickypedia","download_url":"https://codeload.github.com/thevickypedia/throne-trader/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/thevickypedia%2Fthrone-trader/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":31294398,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-04-02T01:43:37.129Z","status":"online","status_checked_at":"2026-04-02T02:00:08.535Z","response_time":89,"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":["analysis-algorithms","buy-and-sell-indicator","machine-learning-algorithms","prediction-algorithm","stock-analyzer"],"created_at":"2024-10-09T23:08:49.447Z","updated_at":"2026-04-02T02:06:19.094Z","avatar_url":"https://github.com/thevickypedia.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"[![made-with-python](https://img.shields.io/badge/Made%20with-Python-blue?style=for-the-badge\u0026logo=Python)](https://python.org)\n\n![Python](https://img.shields.io/badge/python-3.8%20%7C%203.9%20%7C%203.10%20%7C%203.11-orange)\n\n[![pypi-publish](https://github.com/thevickypedia/throne-trader/actions/workflows/python-publish.yml/badge.svg)](https://github.com/thevickypedia/throne-trader/actions/workflows/python-publish.yml)\n[![pages-build-deployment](https://github.com/thevickypedia/throne-trader/actions/workflows/pages/pages-build-deployment/badge.svg)](https://github.com/thevickypedia/throne-trader/actions/workflows/pages/pages-build-deployment)\n\n# ThroneTrader\n\nA collection of algorithms to analyze, categorize and predict stocks.\n\nThese algorithms are used to assess stocks, and make predictions about future stock prices.\n\nThe collection of algorithms leverage data analysis, machine learning, and statistical methods to achieve its objectives in the context of financial markets and investments.\n\n## Installation\n```shell\npython -m pip install throne-trader\n```\n\n## Usage\n**Predict future stock prices using machine learning**\n```python\nfrom thronetrader import Predictions\n\npredictions = Predictions(symbol=\"AAPL\")\nprint(predictions.linear_regression_prediction())\nprint(predictions.gradient_boosting_prediction())\n```\n\n**Generate buy/sell/hold signals based on real-time data**\n```python\nfrom thronetrader import RealTimeSignals\n\nrealtime_signals = RealTimeSignals(symbol=\"AAPL\")\n\nprint(realtime_signals.get_financial_signals())\nprint(realtime_signals.get_insider_signals())\n\nseries1, series2 = realtime_signals.get_trading_volume()\nprint(series1.name)\nprint(series1.to_dict())\nprint(series2.name)\nprint(series2.to_dict())\n```\n\n**Generate buy/sell/hold signals based on strategic algorithms**\n```python\nfrom thronetrader import StrategicSignals\n\nstrategic_signals = StrategicSignals(symbol=\"AAPL\")\n\nprint(strategic_signals.get_bollinger_bands_signals())\nprint(strategic_signals.get_breakout_signals())\nprint(strategic_signals.get_crossover_signals())\nprint(strategic_signals.get_macd_signals())\nprint(strategic_signals.get_rsi_signals())\n```\n\n\u003e :bulb: While individual algorithms may lack optimal accuracy, the aggregation of multiple algorithms proves valuable and effective in enhancing overall prediction accuracy.\n\n\u003e :warning: Please note that stock prediction is inherently challenging, and the accuracy of any prediction model will depend on the quality and relevance of the data used, the choice of algorithms, and the changing dynamics of the stock market. Continuous evaluation and improvement of the model are essential to enhance its predictive capabilities.\n\n## Components\n- [**Predict stock price using deep learning models**][dl_trade]\n- [**Analyze stock price using machine learning models**][ml_trade]\n- [**Generate buy/sell/hold signals using real time data**][realtime]\n- [**Generate buy/sell/hold signals using financial strategies**][strategies]\n\n## Sample Notebooks\n- [**Long Short-Term Memory**][lstm]\n- [**Gradient Boosting**][gradient]\n- [**Linear Regression**][linear]\n\n## Disclaimer\nRemember to thoroughly backtest and paper trade any strategy before using real funds, and always exercise caution and risk management when trading stocks.\n\n\u003cbr\u003e\n\n\u003cdetails\u003e\n\u003csummary\u003eWhy \u003ccode\u003ethrone-trader\u003c/code\u003e?\u003c/summary\u003e\n\n\u003cbr\u003e\n\n\u003ci\u003eThis name draws inspiration from the \"Game of Thrones\" series, where various characters vie for the Iron Throne, \nsymbolizing power, wealth, and influence.\n\u003cbr\u003e\u003cbr\u003e\n\"ThroneTrader\" signifies the algorithm's quest for dominance in the financial markets, much like the characters in the \nshow strive to sit upon the Iron Throne.\u003c/i\u003e\n\n\u003c/details\u003e\n\n## Coding Standards\nDocstring format: [`Google`](https://google.github.io/styleguide/pyguide.html#38-comments-and-docstrings) \u003cbr\u003e\nStyling conventions: [`PEP 8`](https://www.python.org/dev/peps/pep-0008/) \u003cbr\u003e\nClean code with pre-commit hooks: [`flake8`](https://flake8.pycqa.org/en/latest/) and \n[`isort`](https://pycqa.github.io/isort/)\n\n## [Release Notes](https://github.com/thevickypedia/throne-trader/blob/main/release_notes.rst)\n**Requirement**\n```shell\npython -m pip install gitverse\n```\n\n**Usage**\n```shell\ngitverse-release reverse -f release_notes.rst -t 'Release Notes'\n```\n\n## Linting\n`PreCommit` will ensure linting, and the doc creation are run on every commit.\n\n**Requirement**\n```shell\npip install sphinx==5.1.1 pre-commit recommonmark pytest\n```\n\n**Usage**\n```shell\npre-commit run --all-files\n```\n\n## Pypi Package\n[![pypi-module](https://img.shields.io/badge/Software%20Repository-pypi-1f425f.svg)][pypi]\n\n## Runbook\n[![made-with-sphinx-doc](https://img.shields.io/badge/Code%20Docs-Sphinx-1f425f.svg)][docs]\n\n## License \u0026 copyright\n\n\u0026copy; Vignesh Rao\n\nLicensed under the [MIT License][license]\n\n[dl_trade]: https://github.com/thevickypedia/throne-trader/blob/main/markdown/DL_ALGORITHMS.md\n[ml_trade]: https://github.com/thevickypedia/throne-trader/blob/main/markdown/ML_ALGORITHMS.md\n[realtime]: https://github.com/thevickypedia/throne-trader/blob/main/markdown/REALTIME.md\n[strategies]: https://github.com/thevickypedia/throne-trader/blob/main/markdown/STRATEGIES.md\n[license]: https://github.com/thevickypedia/throne-trader/blob/main/LICENSE\n[docs]: https://thevickypedia.github.io/throne-trader/\n[pypi]: https://pypi.org/project/throne-trader\n[lstm]: https://github.com/thevickypedia/throne-trader/blob/main/notebook/lstm.ipynb\n[gradient]: https://github.com/thevickypedia/throne-trader/blob/main/notebook/gradient_boosting.ipynb\n[linear]: https://github.com/thevickypedia/throne-trader/blob/main/notebook/linear_regression.ipynb\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthevickypedia%2Fthrone-trader","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fthevickypedia%2Fthrone-trader","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fthevickypedia%2Fthrone-trader/lists"}