{"id":21062569,"url":"https://github.com/paragon279/stock-predict","last_synced_at":"2025-05-16T02:31:10.606Z","repository":{"id":203476252,"uuid":"707775824","full_name":"paragon279/stock-predict","owner":"paragon279","description":"Predicts stock price","archived":false,"fork":false,"pushed_at":"2023-11-08T21:43:06.000Z","size":33,"stargazers_count":8,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-04-03T18:40:56.762Z","etag":null,"topics":["cpp","machine-learning","prediction","stock-price-prediction"],"latest_commit_sha":null,"homepage":"","language":"C++","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/paragon279.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}},"created_at":"2023-10-20T16:21:44.000Z","updated_at":"2025-03-30T04:56:56.000Z","dependencies_parsed_at":null,"dependency_job_id":"85449145-d5e6-4cb8-8564-be571a0e35ce","html_url":"https://github.com/paragon279/stock-predict","commit_stats":{"total_commits":9,"total_committers":2,"mean_commits":4.5,"dds":"0.11111111111111116","last_synced_commit":"6e6ad7ddf55de9c50d272cfe0972137f5e0903cf"},"previous_names":["yinyangwarrior0928/stock-predict","c0r2a-lab/stock-predict","paragon279/stock-predict"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paragon279%2Fstock-predict","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paragon279%2Fstock-predict/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paragon279%2Fstock-predict/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/paragon279%2Fstock-predict/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/paragon279","download_url":"https://codeload.github.com/paragon279/stock-predict/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":254455738,"owners_count":22074045,"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":["cpp","machine-learning","prediction","stock-price-prediction"],"created_at":"2024-11-19T17:39:17.164Z","updated_at":"2025-05-16T02:31:06.488Z","avatar_url":"https://github.com/paragon279.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Stockast\n[![FOSSA Status](https://app.fossa.io/api/projects/git%2Bgithub.com%2FRajdeepKonwar%2Fstockast.svg?type=shield)](https://app.fossa.io/projects/git%2Bgithub.com%2FRajdeepKonwar%2Fstockast?ref=badge_shield)\n\n## Stock Market Forecasting using Parallel (OpenMP) Monte-Carlo Simulations\n\n![Stockast Image](https://i.imgur.com/dHf0aRO.png)\n\n### Compile Instructions\n\n#### Windows\n- Open `stockast.sln`\n- [Optional] Right-click Solution 'stockast' in the Solution Explorer and select `Retarget solution`\n- Build and run!\n\n\n#### Linux\n```shell\nmake\n```\nType make clean to clean object files and the executable.\n\n\n### Run Instructions\n\n#### Windows\nSimply run from Visual Studio or double-click the executable created inside x64\\{config}\\stockast.exe.\n\nBy default, the program will try and utilize the maximum system threads available. To use a specific number of threads, set the environment variable OMP_NUM_THREADS equal to the number of threads you want.\n\n#### Linux\n\nSet the number of threads to be used for computation:\n```shell\nexport OMP_NUM_THREADS=number_of_threads\n```\nFor example, \n```shell\nexport OMP_NUM_THREADS=8\n```\nThen run the program:\n```shell\n./stockast\n```\n### General Info\n1. The input file \"data.csv\" contains the stock-price values for 3 hours prior to run-time; this acts as the history data and helps estimate market volatility.\n2. The output file \"opt.csv\" contains the output (most likely outcome) price-vector from our code. You can use Excel or gnuplot to plot the resulting line graph of the predicted stock pricing.\n3. (Linux only) The script \"profiling.sh\" runs the parallel code from 1 to the specified number of threads. To use the script:\n```shell\n./profiling.sh \"number_of_threads\"\n```\nFor example, \n```shell\n./profiling.sh 8\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fparagon279%2Fstock-predict","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fparagon279%2Fstock-predict","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fparagon279%2Fstock-predict/lists"}