{"id":18538277,"url":"https://github.com/lastancientone/technology_investment","last_synced_at":"2025-04-09T17:37:26.246Z","repository":{"id":166030323,"uuid":"641462869","full_name":"LastAncientOne/Technology_Investment","owner":"LastAncientOne","description":"Analyzing and investing Technology Stocks","archived":false,"fork":false,"pushed_at":"2024-03-17T01:51:03.000Z","size":2843,"stargazers_count":5,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"main","last_synced_at":"2025-03-24T09:46:51.146Z","etag":null,"topics":["excel","fundamentals","investing","investment","investment-analysis","investment-strategies","python","r","ratio-analysis","regression-analysis","technical-analysis","technology"],"latest_commit_sha":null,"homepage":"","language":"R","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/LastAncientOne.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":"2023-05-16T14:16:35.000Z","updated_at":"2024-11-26T21:20:42.000Z","dependencies_parsed_at":null,"dependency_job_id":"5bb2a69c-c68a-4b59-8e20-cd9860438e5f","html_url":"https://github.com/LastAncientOne/Technology_Investment","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LastAncientOne%2FTechnology_Investment","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LastAncientOne%2FTechnology_Investment/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LastAncientOne%2FTechnology_Investment/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/LastAncientOne%2FTechnology_Investment/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/LastAncientOne","download_url":"https://codeload.github.com/LastAncientOne/Technology_Investment/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248078396,"owners_count":21044098,"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":["excel","fundamentals","investing","investment","investment-analysis","investment-strategies","python","r","ratio-analysis","regression-analysis","technical-analysis","technology"],"created_at":"2024-11-06T19:42:59.086Z","updated_at":"2025-04-09T17:37:25.709Z","avatar_url":"https://github.com/LastAncientOne.png","language":"R","funding_links":[],"categories":[],"sub_categories":[],"readme":"\u003cimg src=\"Technology.PNG\"\u003e\n\u003ch1 align=\"center\"\u003eTechnology Investment\u003c/h1\u003e\n\n#### This project involves conducting long-term investment analysis to determine which technology company is a suitable choice for long-term investment. The analysis includes examining historical data spanning 10 years, calculating performance measurements, conducting back-testing, forecasting, and utilizing the Capital Asset Pricing Model. Various trading strategies are tested with the aim of identifying stocks with the lowest risks and highest returns.  \n\n\n#### Use income, balance, and cashflow statements and historical price in Excel, Python, and R for Stocks Analysis.  \n\n# Prerequistes  \n#### Python 3.7  \n#### Jupyter Notebook Python 3.7   \n#### Excel 2016  \n#### R  \n\n### Stock Tickers:\nADBE Adobe Inc.  \nAMAT Applied Materials, Inc.  \nAMD Advanced Micro Devices, Inc.  \nAVGO Broadcom Inc.  \nBABA Alibaba Group Holding Limited  \nCSCO Cisco Systems, Inc.  \nETSY Etsy, Inc.  \nGOOGL Alphabet Inc.  \nINTC Intel Corporation  \nLRCX Lam Research Corporation  \nLUMN Lumen Technologies, Inc.  \nMETA Meta Platforms, Inc.  \nMSFT Microsoft Corporation  \nMU Micron Technology, Inc.  \nNFLX Netflix, Inc.  \nNVDA NVIDIA Corporation  \nPYPL PayPal Holdings, Inc.  \nQCOM QUALCOMM Incorporated  \nSTX Seagate Technology Holdings plc  \nTSM Taiwan Semiconductor Manufacturing Company Limited  \n\n### Sharpe Ratios \n#### Using PerformanceAnalytics to calculate Sharpe Ratios  \nADBE (0.5995)  \nAMAT (0.6347)  \nAMD (0.9207)  \nAVGO (0.6232)  \nBABA (0.0464)  \nCSCO (0.03296)  \nETSY (0.7830)  \nGOOGL (0.4547)  \nINTC (-0.1046)  \nLRCX (0.6292)  \nLUMN (-0.4699)  \nMETA (0.0612)  \nMSFT (0.8349)  \nMU (0.4172)  \nNFLX (0.3370)  \nNVDA (1.0307)  \nPYPL (0.2773)  \nQCOM (0.3124)   \nSTX (0.1312)  \nTSM (0.5998)  \n\n### Information Ratio  \nAMD     (0.064884185)  \nNVDA    (0.068458849)  \nMSFT    (0.059647883)  \nGOOGL   (0.035844059)  \nQCOM    (0.035545590)   \nBABA    (0.016188351)  \nTSM     (0.050755716)  \nMETA    (0.016299578)  \nNFLX    (0.034327497)  \nADBE    (0.045139104)  \nPYPL    (0.028956244)  \nAVGO    (0.052428076)  \nMU      (0.038994102)  \nAMAT    (0.050709841)  \nINTC    (0.009309534)  \nSTX     (0.029457974)  \nLUMN   (-0.006516516)  \nETSY    (0.059062384)  \nLRCX    (0.050977054)  \nCSCO    (0.035562899)  \n \n### Monthly Returns  \nFebruary, June, December and September seem to be the best times to buy more shares or start investing in tech stocks.  \n\n## Author:  \n### Tin Hang  \n\n## Disclaimer\n### 🔴 This is not financial advice. Please conduct your own research and refrain from using this code for investing or trading in stocks. If you are interested in the stock market, consider reading books on investment, trading, and finance. It is advisable to consult with a professional investment advisor before making any investment decisions. Remember, this information is for educational purposes only.  \n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flastancientone%2Ftechnology_investment","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flastancientone%2Ftechnology_investment","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flastancientone%2Ftechnology_investment/lists"}