{"id":25132021,"url":"https://github.com/taleblou/arima-price-prediction","last_synced_at":"2025-04-03T00:11:53.408Z","repository":{"id":269028012,"uuid":"905126299","full_name":"taleblou/ARIMA-Price-Prediction","owner":"taleblou","description":"This repository implements an ARIMA model for predicting financial prices such as stocks, currencies, and cryptocurrencies. It focuses on time series forecasting to capture temporal dependencies and improve prediction accuracy across different financial datasets.","archived":false,"fork":false,"pushed_at":"2024-12-22T12:18:42.000Z","size":3083,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-08T14:16:16.152Z","etag":null,"topics":["arima-model","cryptocurrency-prediction","currency-prediction","financial-predictions","stock-price-prediction"],"latest_commit_sha":null,"homepage":"https://taleblou.ir/","language":"Python","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/taleblou.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":"2024-12-18T08:04:37.000Z","updated_at":"2024-12-23T19:13:46.000Z","dependencies_parsed_at":"2024-12-20T12:30:53.533Z","dependency_job_id":"485d33d0-3a60-44e0-958f-cd28a83fe082","html_url":"https://github.com/taleblou/ARIMA-Price-Prediction","commit_stats":null,"previous_names":["taleblou/arima-price-prediction"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/taleblou%2FARIMA-Price-Prediction","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/taleblou%2FARIMA-Price-Prediction/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/taleblou%2FARIMA-Price-Prediction/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/taleblou%2FARIMA-Price-Prediction/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/taleblou","download_url":"https://codeload.github.com/taleblou/ARIMA-Price-Prediction/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246911470,"owners_count":20853657,"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":["arima-model","cryptocurrency-prediction","currency-prediction","financial-predictions","stock-price-prediction"],"created_at":"2025-02-08T14:16:18.234Z","updated_at":"2025-04-03T00:11:53.390Z","avatar_url":"https://github.com/taleblou.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# **ARIMA Model for Financial Predictions**\n\n\n\nThis repository contains an implementation of an ARIMA model, specifically designed for predicting the prices of financial instruments such as currencies, stocks, and cryptocurrencies. The ARIMA model leverages sequential data to capture temporal dependencies in price movements. This approach enhances the accuracy and robustness of price forecasts across various datasets.\n\nThis is the original code sample for the ARIMA model. Explore my GitHub repository for additional models and implementations that cater to different financial prediction needs.\n\n\n\n## **Performance Metrics**\n\n### \n\n### **BTC-USD (Bitcoin)**\n\n| Metric | Open | High | Low | Close |\n| ----- | ----- | ----- | ----- | ----- |\n| Mean Squared Error | 0.0004220947 | 0.0003331435 | 0.0003984997 | 0.0004212805 |\n| Mean Absolute Error | 0.0146372866 | 0.0126685872 | 0.0146607014 | 0.0146472946 |\n| R-squared | 0.9810292825 | 0.9853395246 | 0.9817388777 | 0.9815021491 |\n| Median Absolute Error | 0.0098635477 | 0.0090989897 | 0.0110105436 | 0.0099024771 |\n| Explained Variance Score | 0.9818170543 | 0.9860428103 | 0.9824947986 | 0.9822664621 |\n\n\n### **![][image1]**\n\n### **GC=F (Gold Futures)**\n\n| Metric | Open | High | Low | Close |\n| ----- | ----- | ----- | ----- | ----- |\n| Mean Squared Error | 0.0004573659 | 0.0003971889 | 0.0004150386 | 0.0004928941 |\n| Mean Absolute Error | 0.0167200327 | 0.0159885584 | 0.0158186869 | 0.0180250496 |\n| R-squared | 0.9778359028 | 0.9805231187 | 0.9799143807 | 0.9758534936 |\n| Median Absolute Error | 0.0135381585 | 0.0136399818 | 0.0121453137 | 0.0159585536 |\n| Explained Variance Score | 0.9807082959 | 0.9832689722 | 0.9825208334 | 0.9786981397 |\n\n\n### **![][image2]**\n\n### **EURUSD (Euro/US Dollar)**\n\n\n| Metric | Open | High | Low | Close |\n| ----- | ----- | ----- | ----- | ----- |\n| Mean Squared Error | 0.0002369469 | 0.0001820074 | 0.0001921452 | 0.0002373472 |\n| Mean Absolute Error | 0.0116501358 | 0.0101599818 | 0.0100425842 | 0.0116962016 |\n| R-squared | 0.9450968898 | 0.9586449824 | 0.9564474468 | 0.9451307259 |\n| Median Absolute Error | 0.0094959702 | 0.0077570867 | 0.0078760936 | 0.0094959108 |\n| Explained Variance Score | 0.9455610091 | 0.9590999878 | 0.9568867818 | 0.9456283529 |\n\n\n### \n\n### **![][image3]**\n\n### **GSPC (S\\\u0026P 500 Index)**\n\n\n| Metric | Open | High | Low | Close |\n| ----- | ----- | ----- | ----- | ----- |\n| Mean Squared Error | 0.0002943897 | 0.0002285942 | 0.0002763461 | 0.0003238685 |\n| Mean Absolute Error | 0.0131037101 | 0.0112381038 | 0.0125061849 | 0.0138794599 |\n| R-squared | 0.9781312129 | 0.9838436549 | 0.9794671490 | 0.9771475967 |\n| Median Absolute Error | 0.0109432769 | 0.0086268191 | 0.0099983815 | 0.0114295848 |\n| Explained Variance Score | 0.9805361261 | 0.9859285360 | 0.9817389733 | 0.9797225138 |\n\n\n### **![][image4]**\n\n## **Related Websites**\n\n\nThe experiences of these codes and the initial models you see have been used on the following sites:\n\n### [**Predict Price**](https://predict-price.com/)\n\nFree AI-powered short-term (5/10/30 days) \u0026 long-term (6 months/1/2 years) forecasts for cryptocurrencies, stocks, ETFs, currencies, indices, and mutual funds. Predict Price employs a unique ARIMA model that analyzes historical data in both forward and reverse directions, capturing intricate temporal patterns. This advanced methodology ensures precise and reliable forecasts, setting it apart in the market.\n\n### [**Magical Prediction**](https://magicalprediction.com/)\n\nGet free trading signals generated by advanced AI models. These models utilize state-of-the-art machine learning techniques to analyze market dynamics, identify trends, and predict potential price movements. Examples of successful signals include precise predictions of market reversals and breakout points, helping users optimize their trading strategies with confidence.\n\n### [**Magical Analysis**](https://magicalanalysis.com/)\n\nDiscover free trading signals powered by expert technical analysis. This platform employs a variety of technical analysis methods, such as trendline studies, Fibonacci retracements, and moving average strategies, to generate actionable insights. These techniques provide users with detailed real-time market updates, enabling them to refine their forex, stock, and crypto trading strategies effectively.\n\n**About This Project**\n\nThis ARIMA model is an initial implementation, released for public use. The project demonstrates the potential of deep learning models for financial predictions. While this repository focuses on ARIMA, I have also utilized other models, the code for which is available on my GitHub.\n\nHow to Use\n\nClone this repository.\n\nInstall the required libraries: pip install \\-r requirements.txt\n\nPrepare your dataset and follow the instructions in the notebook or script.\n\nRun the model and evaluate its performance using the provided metrics.\n\nLicense\n\nThis project is open-source and available for public use under the MIT License. Contributions and feedback are welcome\\!\n\n[image1]: \u003chttps://raw.githubusercontent.com/taleblou/ARIMA-Price-Prediction/refs/heads/main/Plot/ARIMA_BTC-USD.png\u003e\n[image2]: \u003chttps://raw.githubusercontent.com/taleblou/ARIMA-Price-Prediction/refs/heads/main/Plot/ARIMA_GC%3DF.png\u003e\n[image3]: \u003chttps://raw.githubusercontent.com/taleblou/ARIMA-Price-Prediction/refs/heads/main/Plot/ARIMA_EURUSD%3DX.png\u003e\n[image4]: \u003chttps://raw.githubusercontent.com/taleblou/ARIMA-Price-Prediction/refs/heads/main/Plot/ARIMA_%5EGSPC.png\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftaleblou%2Farima-price-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftaleblou%2Farima-price-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftaleblou%2Farima-price-prediction/lists"}