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It then presents machine learning and deep learning approaches such as Random Forest, XGBoost, LSTM, and GRU, followed by methodological steps for data collection, volatility computation, and comparative evaluation across models.",{"@graph":14,"@context":73},[15,34,56],{"@type":16,"itemListElement":17},"BreadcrumbList",[18,23,27,31],{"item":19,"name":20,"@type":21,"position":22},"https://docshare.wps.com","Home","ListItem",1,{"item":24,"name":25,"@type":21,"position":26},"https://docshare.wps.com/document/","Document",2,{"item":28,"name":29,"@type":21,"position":30},"https://docshare.wps.com/document/research-report/","Research & 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\nوزرارة التعليم العالي والبحث العلمي  \nMinistry of Higher Education and Scientific Research  \nجامعة محمد بوضياف بالمسيلة  \nUniversity Mohamed Boudiaf of M’sila  \nكلية الرياضيات والإعلام الآلي  \nFaculty of Mathematics and Informatics  \nقسم الإعلام الآلي  \nDepartment of Computer Science  \nDomain: Mathematics and Computer Science  \nThesis Presented to Fulfill the Partial Requirement for Master's Degree in Computer Science  \nSpecialty: Artificial Intelligence Prepared By: Amari Mohammed Elamin Supervised By:  \nProf. Sayad Lamri  \nEntitled  \nForecasting Volatility of Cryptocurrencies Using Machine Learning and Deep Learning  \nJury Members  \n\n| Mustapha Bourahla | President |\n| --- | --- |\n| Lamri Sayad | Supervisor |\n| Salah Guesmia | Examiner |\n\nAcademic Year 2024/2025  \nDedication  \n“Without a family, man, alone in the world, trembles with the cold”—André Maurois.  \nTo my parents and family.  \nTo my grandmother.  \nOne more milestone reached thanks to you.  \nHopefully not the last.  \nAcknowledgement  \nI would like to express my gratitude to my supervising teacher Prof. Lamri Sayad, for his guidance, patience, and insightful feedback—All of which were vital for the completion of this  \nwork.  \nTable of Contents  \nDedication ................................................................................................................................. ii  \nAcknowledgement....................................................................................................................iii  \nTable of Contents .................................................................................................................... iv  \nList of Figures........................................................................................................................ viii  \nList of Tables ........................................................................................................................... ix  \nList of Acronyms ...................................................................................................................... x  \nGeneral Introduction ............................................................................................................... 1  \nChapter 1: Literature Review.............................................................................................. 3  \n1.1. Introduction: ............................................................................................................... 3  \n.1.2 Definition of Cryptocurrencies: ................................................................................... 3  \n1.3. Characteristics of Cryptocurrency Market: .................................................................. 3  \n1.4. Cryptocurrency Volatility:........................................................................................... 4  \n1.4.1. Definition of Volatility: ........................................................................................... 4  \n1.4.2. Why Are Cryptocurrencies So Volatile:................................................................... 4  \n1.5. Traditional Volatility Forecasting Methods: ................................................................ 5  \n1.5.1. ARCH and GARCH Models: .................................................................................. 5  \n1.5.1.1. How ARCH/GARCH Works: .......................................................................... 5  \n1.5.1.2. GARCH-type Models: ..................................................................................... 6  \n1.5.2. Stochastic Volatility Models:................................................................................... 7  \n1.6. The Application of Traditional Volatility Forecasting Models to Cryptocurrencies:..... 8  \n1.7. Limitations of Traditional Volatility Forecasting Models: ........................................... 8  \n1.8. Machine Learning/Deep ","cbCaicWEstT9enoi","https://ap.wps.com/l/cbCaicWEstT9enoi","pdf",5582166,86,"English","# General Introduction\n# Chapter 1: Literature Review\n## 1.1. Introduction\n## 1.2 Definition of Cryptocurrencies\n## 1.3 Characteristics of Cryptocurrency Market\n## 1.4 Cryptocurrency Volatility\n## 1.5 Traditional Volatility Forecasting Methods\n## 1.6 The Application of Traditional Volatility Forecasting Models to Cryptocurrencies\n## 1.7 Limitations of Traditional Volatility Forecasting Models\n## 1.8 Machine Learning/Deep Learning Volatility Forecasting Methods\n## 1.9 Conclusion\n# Chapter 2: Methodology\n## 2.1. Introduction\n## 2.2. Data collection\n## 2.3. Volatility Calculation","[{\"question\":\"What is the main objective of the thesis?\",\"answer\":\"To forecast cryptocurrency volatility using machine learning and deep learning approaches, supported by a review of traditional methods and their limitations.\"},{\"question\":\"Which traditional volatility models are discussed?\",\"answer\":\"The literature review includes ARCH and GARCH models, explains how ARCH/GARCH works, and also covers stochastic volatility models.\"},{\"question\":\"What machine learning and deep learning methods are used for volatility forecasting?\",\"answer\":\"The thesis addresses traditional machine learning models such as Random Forest and XGBoost, and deep learning models such as LSTM and GRU, along with comparative studies.\"}]","Forecasting Volatility of Cryptocurrencies Using Machine Learning and Deep Learning | PDF",217]