[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-118071-en":3,"doc-seo-118071-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},118071,137441390410,"Hazel","https://ap-avatar.wpscdn.com/avatar/2000252f4ab5702993?_k=1776741390130283984",8,"Research & Report","STOCK MARKET VALUE PREDICTION BASED ON MACHINE LEARNING APPROACH","Stock market price prediction is positioned as an engaging research direction, especially within Machine Learning and time series analysis. A strong prediction model is argued to help investors maximize returns while keeping risks low, yet the document emphasizes that conventional investment does not always guarantee gains. It highlights the role of AI in improving prediction accuracy and reducing the need for extensive technical and financial expertise, while acknowledging that market volatility can trigger emotional decision-making. The study focuses on building and validating machine-learning-based stock predictors with visual outputs to support rational investment decisions even for beginners.","STOCK MARKET VALUE PREDICTION BASED ON MACHINE LEARNING APPROACH  \nCHEW MIN WEI  \nBachelor of Computer Science (Software Engineering) with Honors  \nUNIVERSITI MALAYSIA PAHANG  \nUNIVERSITI MALAYSIA PAHANG  \n\n| DECLARATION OF THESIS AND COPYRIGHT\u003Cbr>Author’s Full Name : CHEW MIN WEI\u003Cbr>Date ofBirth\u003Cbr>Title : STOCK MARKET VALUE PREDICTION BASED ON\u003Cbr>MACHINE LEARNING APPROACH\u003Cbr>Academic Session : SEMESTER I 2022/2023\u003Cbr>I declare that this thesis is classified as: |  |  |\n| --- | --- | --- |\n| 􀂅 CONFIDENTIAL\u003Cbr>􀂅 RESTRICTED | (Contains confidential information under the Official Secret Act 1997)*\u003Cbr>(Contains restricted information as specified by the |  |\n| organization where research was done)*\u003Cbr>􀀻 OPEN ACCESS I agree that my thesis to be published as online open access\u003Cbr>(Full Text)\u003Cbr>I acknowledge that Universiti Malaysia Pahang reserves the following rights:\u003Cbr>1. The Thesis is the Property of Universiti Malaysia Pahang\u003Cbr>2. The Library of Universiti Malaysia Pahang has the right to make copies of the thesis for the purpose of research only.\u003Cbr>3. The Library has the right to make copies of the thesis for academic exchange. |  |  |\n| Certified by:\u003Cbr>(Student’s Signature)\u003Cbr>New IC/Passport Number Date: 10 February 2023 |  | (Supervisor’s Signature)\u003Cbr>\u003Cbr>_______________________\u003Cbr>Name of Supervisor Date: 16/02/2023 |\n\nNOTE : * If the thesis is CONFIDENTIAL or RESTRICTED, please attach a thesis declaration letter.  \nTHESIS DECLARATION LETTER (OPTIONAL)  \nLibrarian,  \nPerpustakaan Universiti Malaysia Pahang,  \nUniversiti Malaysia Pahang, Lebuhraya Tun Razak, 26300, Gambang, Kuantan.  \nDear Sir,  \nCLASSIFICATION OF THESIS AS RESTRICTED  \nPlease be informed that the following thesis is classified as RESTRICTED for a period of three (3) years from the date of this letter. The reasons for this classification are as listed below.  \nAuthor’s Name  \nThesis Title  \nReasons (i)  \n(ii)  \n(iii)  \nThank you.  \nYours faithfully,  \n(Supervisor’s Signature)  \nDate:  \nStamp:  \nNote: This letter should be written by the supervisor, addressed to the Librarian, Perpustakaan Universiti Malaysia Pahang with its copy attached to the thesis.  \nSUPERVISOR’S DECLARATION  \nI/We* hereby declare that I/We* have checked this thesis/project* and in my/our* opinion, this thesis/project* is adequate in terms of scope and quality for the award of the degree of *Doctor of Philosophy/ Master of Engineering/ Master of Science in  \n(Supervisor’s Signature)  \nFull Name Position Date  \n(Co-supervisor’s Signature) Full Name :  \nPosition :  \nDate :  \nSTUDENT’S DECLARATION  \nI hereby declare that the work in this thesis is based on my original work except for quotations and citations which have been duly acknowledged. I also declare that it has not been previously or concurrently submitted for any other degree at Universiti Malaysia Pahang or any other institutions.  \n CHEW   \n(Student’s Signature) Full Name : CHEW MIN WEI  \nID Number : CB19049  \nDate : 10 February 2022  \nSTOCK MARKET VALUE PREDICTION BASED ON MACHINE LEARNING APPROACH  \nCHEW MIN WEI  \nThesis submitted in fulfillment of the requirements for the award of the degree of  \nBachelor of Computer Science (Software Engineering) with Honors  \nFaculty of Computing  \nUNIVERSITI MALAYSIA PAHANG  \nFEBRUARY 2023  \nACKNOWLEDGEMENTS  \nFirst of all, I cannot express enough thanks to my supervisor, Dr. Kohbalan A/LMoorthy and Final Year Project coordinator, Dr. Danakorn Nincarean A/L Eh Phon for all the guidance, patience, encouragement and assistance in completing this research project. Thanks to my parent, Mr Chew Chong Ee and Mrs Nai Siew Heok for their encouragement along the way. Last but not least, I would like to thank all my friends that motivates and assist me throughout the research.  \nABSTRAK  \nRamalan harga pasaran saham telah menjadi bidang yang menarik kepada ramaipenyelidik terutamanya dalam bidang Pembelajaran Mesin (ML) dan analisis siri masa. Dengan model ramalan yang baik, pelabur boleh mema","cbCaie5qYNvOWy1D","https://ap.wps.com/l/cbCaie5qYNvOWy1D","pdf",1638530,1,59,"English","en",105,"# Declarations and Copyright\n## Thesis classification (confidential, restricted, open access)\n# Declarations\n## Supervisor’s declaration\n## Student’s declaration\n# Acknowledgements\n# Abstract\n## Malay abstract\n## English abstract","[{\"question\":\"What is the document’s main research topic?\",\"answer\":\"It focuses on stock market value/price prediction using a machine learning approach, particularly in the context of machine learning and time series analysis.\"},{\"question\":\"Why does the document argue that investors may benefit from machine learning predictors?\",\"answer\":\"It states that a good prediction model can help maximize returns with minimal risks and reduce the need for extensive technical and financial knowledge required by traditional approaches.\"},{\"question\":\"How does the document say the model should be validated and presented?\",\"answer\":\"It indicates that the predictor should generate visual graphs for validation and verification so the model’s efficiency and accuracy can be followed even by beginners.\"}]","STOCK MARKET VALUE PREDICTION BASED ON MACHINE LEARNING APPROACH | 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