{"product_id":"deep-learning-tools-for-predicting-stock-market-movements-hardback-9781394214303","title":"Deep Learning Tools for Predicting Stock Market Movements (Hardback) 9781394214303","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eDeep Learning Tools for Predicting Stock Market Movements\u003c\/font\u003e\u003cbr\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003c\/p\u003e\n\u003cp\u003e\u003cfont size=\"4\"\u003eRenuka Sharma (Edited by), Sharma (Author), Kiran Mehta (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394214303, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 19 April 2024\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e496 pages\u003cbr\u003e22.9 x 15.2 x 3 cm, 0.989 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cb\u003eDEEP LEARNING TOOLS for PREDICTING STOCK MARKET MOVEMENTS\u003c\/b\u003e \u003cp\u003e \u003cb\u003eThe book provides a comprehensive overview of current research and developments in the field of deep learning models for stock market forecasting in the developed and developing worlds.\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eThe book delves into the realm of deep learning and embraces the challenges, opportunities, and transformation of stock market analysis. Deep learning helps foresee market trends with increased accuracy. With advancements in deep learning, new opportunities in styles, tools, and techniques evolve and embrace data-driven insights with theories and practical applications. Learn about designing, training, and applying predictive models with rigorous attention to detail. This book offers critical thinking skills and the cultivation of discerning approaches to market analysis. \u003c\/p\u003e\n\u003cp\u003eThe book: \u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003edetails the development of an ensemble model for stock market prediction, combining long short-term memory and autoregressive integrated moving average;\u003c\/li\u003e \u003cli\u003eexplains the rapid expansion of quantum computing technologies in financial systems;\u003c\/li\u003e \u003cli\u003eprovides an overview of deep learning techniques for forecasting stock market trends and examines their effectiveness across different time frames and market conditions;\u003c\/li\u003e \u003cli\u003eexplores applications and implications of various models for causality, volatility, and co-integration in stock markets, offering insights to investors and policymakers.\u003c\/li\u003e\n\u003c\/ul\u003e \u003cp\u003e\u003cb\u003eAudience\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eThe book has a wide audience of researchers in financial technology, financial software engineering, artificial intelligence, professional market investors, investment institutions, and asset management companies.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003ePreface xvii\u003c\/p\u003e \u003cp\u003eAcknowledgments xxv\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Design and Development of an Ensemble Model for Stock Market Prediction Using LSTM, ARIMA, and Sentiment Analysis 1\u003c\/b\u003e\u003cbr\u003e\u003ci\u003ePoorna Shankar, Kota Naga Rohith and Muthukumarasamy Karthikeyan\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 2\u003c\/p\u003e \u003cp\u003e1.2 Significance of the Study 3\u003c\/p\u003e \u003cp\u003e1.3 Problem Statement 5\u003c\/p\u003e \u003cp\u003e1.4 Research Objectives 6\u003c\/p\u003e \u003cp\u003e1.5 Expected Outcome 6\u003c\/p\u003e \u003cp\u003e1.6 Chapter Summary 7\u003c\/p\u003e \u003cp\u003e1.7 Theoretical Foundation 8\u003c\/p\u003e \u003cp\u003e1.8 Research Methodology 13\u003c\/p\u003e \u003cp\u003e1.9 Analysis and Results 22\u003c\/p\u003e \u003cp\u003e1.10 Conclusion 33\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Unraveling Quantum Complexity: A Fuzzy AHP Approach to Understanding Software Industry Challenges 39\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eKiran Mehta and Renuka Sharma\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction 39\u003c\/p\u003e \u003cp\u003e2.2 Introduction to Quantum Computing 41\u003c\/p\u003e \u003cp\u003e2.3 Literature Review 43\u003c\/p\u003e \u003cp\u003e2.4 Research Methodology 45\u003c\/p\u003e \u003cp\u003e2.5 Research Questions 46\u003c\/p\u003e \u003cp\u003e2.6 Designing Research Instrument\/Questionnaire 48\u003c\/p\u003e \u003cp\u003e2.7 Results and Analysis 49\u003c\/p\u003e \u003cp\u003e2.8 Result of Fuzzy AHP 50\u003c\/p\u003e \u003cp\u003e2.9 Findings, Conclusion, and Implication 54\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 Analyzing Open Interest: A Vibrant Approach to Predict Stock Market Operator's Movement 61\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eAvijit Bakshi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 62\u003c\/p\u003e \u003cp\u003e3.2 Methodology 64\u003c\/p\u003e \u003cp\u003e3.3 Concept of OI 64\u003c\/p\u003e \u003cp\u003e3.4 OI in Future Contracts 65\u003c\/p\u003e \u003cp\u003e3.5 OI in Option Contracts 79\u003c\/p\u003e \u003cp\u003e3.6 Conclusion 85\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Stock Market Predictions Using Deep Learning: Developments and Future Research Directions 89\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRenuka Sharma and Kiran Mehta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Background and Introduction 90\u003c\/p\u003e \u003cp\u003e4.2 Studies Related to the Current Work, i.e., Literature Review 97\u003c\/p\u003e \u003cp\u003e4.3 Objective of Research and Research Methodology 100\u003c\/p\u003e \u003cp\u003e4.4 Results and Analysis of the Selected Papers 100\u003c\/p\u003e \u003cp\u003e4.5 Overview of Data Used in the Earlier Studies Selected for the Current Research 102\u003c\/p\u003e \u003cp\u003e4.6 Data Source 103\u003c\/p\u003e \u003cp\u003e4.7 Technical Indicators 105\u003c\/p\u003e \u003cp\u003e4.8 Stock Market Prediction: Need and Methods 106\u003c\/p\u003e \u003cp\u003e4.9 Process of Stock Market Prediction 107\u003c\/p\u003e \u003cp\u003e4.10 Reviewing Methods for Stock Market Predictions 110\u003c\/p\u003e \u003cp\u003e4.11 Analysis and Prediction Techniques 111\u003c\/p\u003e \u003cp\u003e4.12 Classification Techniques (Also Called Clustering Techniques) 111\u003c\/p\u003e \u003cp\u003e4.13 Future Direction 112\u003c\/p\u003e \u003cp\u003e4.14 Conclusion 114\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 Artificial Intelligence and Quantum Computing Techniques for Stock Market Predictions 123\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRajiv Iyer and Aarti Bakshi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 124\u003c\/p\u003e \u003cp\u003e5.2 Literature Survey 125\u003c\/p\u003e \u003cp\u003e5.3 Analysis of Popular Deep Learning Techniques for Stock Market Prediction 132\u003c\/p\u003e \u003cp\u003e5.4 Data Sources and Methodology 139\u003c\/p\u003e \u003cp\u003e5.5 Result and Analysis 141\u003c\/p\u003e \u003cp\u003e5.6 Challenges and Future Scope 142\u003c\/p\u003e \u003cp\u003e5.7 Conclusion 144\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Various Model Applications for Causality, Volatility, and Co-Integration in Stock Market 147\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSwaty Sharma\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 147\u003c\/p\u003e \u003cp\u003e6.2 Literature Review 149\u003c\/p\u003e \u003cp\u003e6.3 Objectives of the Chapter 153\u003c\/p\u003e \u003cp\u003e6.4 Methodology 153\u003c\/p\u003e \u003cp\u003e6.5 Result and Discussion 154\u003c\/p\u003e \u003cp\u003e6.6 Implications 155\u003c\/p\u003e \u003cp\u003e6.7 Conclusion 156\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Stock Market Prediction Techniques and Artificial Intelligence 161\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eJeevesh Sharma\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 162\u003c\/p\u003e \u003cp\u003e7.2 Financial Market 163\u003c\/p\u003e \u003cp\u003e7.3 Stock Market 164\u003c\/p\u003e \u003cp\u003e7.4 Stock Market Prediction 166\u003c\/p\u003e \u003cp\u003e7.5 Artificial Intelligence and Stock Prediction 170\u003c\/p\u003e \u003cp\u003e7.6 Benefits of Using AI for Stock Prediction 173\u003c\/p\u003e \u003cp\u003e7.7 Challenges of Using AI for Stock Prediction 175\u003c\/p\u003e \u003cp\u003e7.8 Limitations of AI-Based Stock Prediction 176\u003c\/p\u003e \u003cp\u003e7.9 Conclusion 178\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Prediction of Stock Market Using Artificial Intelligence Application 185\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eShaina Arora, Anand Pandey and Kamal Batta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 186\u003c\/p\u003e \u003cp\u003e8.2 Objectives 189\u003c\/p\u003e \u003cp\u003e8.3 Literature Review 190\u003c\/p\u003e \u003cp\u003e8.4 Future Scope 195\u003c\/p\u003e \u003cp\u003e8.5 Sources of Study and Importance 196\u003c\/p\u003e \u003cp\u003e8.6 Case Study: Comparison of AI Techniques for Stock Market Prediction 197\u003c\/p\u003e \u003cp\u003e8.7 Discussion and Conclusion 198\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 Stock Returns and Monetary Policy 203\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eBaki Cem Sahin\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 204\u003c\/p\u003e \u003cp\u003e9.2 Literature 205\u003c\/p\u003e \u003cp\u003e9.3 Data and Methodology 209\u003c\/p\u003e \u003cp\u003e9.4 Index-Based Analysis 211\u003c\/p\u003e \u003cp\u003e9.5 Firm-Level Analysis 212\u003c\/p\u003e \u003cp\u003e9.5.1 Sectoral Difference 213\u003c\/p\u003e \u003cp\u003e9.6 The Impact of Financial Constraints 216\u003c\/p\u003e \u003cp\u003e9.7 Discussion and Conclusion 219\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Revolutionizing Stock Market Predictions: Exploring the Role of Artificial Intelligence 227\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRajani H. Pillai and Aatika Bi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 227\u003c\/p\u003e \u003cp\u003e10.2 Review of Literature 229\u003c\/p\u003e \u003cp\u003e10.3 Research Methods 234\u003c\/p\u003e \u003cp\u003e10.4 Results and Discussion 236\u003c\/p\u003e \u003cp\u003e10.5 Conclusion 241\u003c\/p\u003e \u003cp\u003e10.6 Significance of the Study 242\u003c\/p\u003e \u003cp\u003e10.7 Scope of Further Research 243\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 A Comparative Study of Stock Market Prediction Models: Deep Learning Approach and Machine Learning Approach 249\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eSwati Jain\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 250\u003c\/p\u003e \u003cp\u003e11.2 Stock Market Prediction 253\u003c\/p\u003e \u003cp\u003e11.3 Models for Prediction in Stock Market 257\u003c\/p\u003e \u003cp\u003e11.4 Conclusion 266\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Machine Learning and its Role in Stock Market Prediction 271\u003c\/b\u003e\u003cbr\u003e\u003ci\u003ePawan Whig, Pavika Sharma, Ashima Bhatnagar Bhatia, Rahul Reddy Nadikattu and Bhupesh Bhatia\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 272\u003c\/p\u003e \u003cp\u003e12.2 Literature Review 274\u003c\/p\u003e \u003cp\u003e12.3 Standard ML 277\u003c\/p\u003e \u003cp\u003e12.4 DL 279\u003c\/p\u003e \u003cp\u003e12.5 Implementation Recommendations for ML Algorithms 280\u003c\/p\u003e \u003cp\u003e12.6 Overcoming Modeling and Training Challenges 281\u003c\/p\u003e \u003cp\u003e12.7 Problems with Current Mechanisms 283\u003c\/p\u003e \u003cp\u003e12.8 Case Study 284\u003c\/p\u003e \u003cp\u003e12.9 Research Objective 284\u003c\/p\u003e \u003cp\u003e12.10 Conclusion 294\u003c\/p\u003e \u003cp\u003e12.11 Future Scope 294\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Systematic Literature Review and Bibliometric Analysis on Fundamental Analysis and Stock Market Prediction 299\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRenuka Sharma, Archana Goel and Kiran Mehta\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 300\u003c\/p\u003e \u003cp\u003e13.2 Fundamental Analysis 301\u003c\/p\u003e \u003cp\u003e13.3 Machine Learning and Stock Price Prediction\/Machine Learning Algorithms 302\u003c\/p\u003e \u003cp\u003e13.4 Related Work 303\u003c\/p\u003e \u003cp\u003e13.5 Research Methodology 303\u003c\/p\u003e \u003cp\u003e13.6 Analysis and Findings 304\u003c\/p\u003e \u003cp\u003e13.7 Discussion and Conclusion 336\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Impact of Emotional Intelligence on Investment Decision 341\u003c\/b\u003e\u003cbr\u003e\u003ci\u003ePooja Chaturvedi Sharma\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 342\u003c\/p\u003e \u003cp\u003e14.2 Literature Review 343\u003c\/p\u003e \u003cp\u003e14.3 Research Methodology 347\u003c\/p\u003e \u003cp\u003e14.4 Data Analysis 348\u003c\/p\u003e \u003cp\u003e14.5 Discussion, Implications, and Future Scope 357\u003c\/p\u003e \u003cp\u003e14.6 Conclusion 358\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Influence of Behavioral Biases on Investor Decision-Making in Delhi-NCR 363\u003c\/b\u003e\u003cbr\u003e\u003ci\u003ePooja Gahlot, Kanika Sachdeva, Shikha Agnihotri and Jagat Narayan Giri\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 364\u003c\/p\u003e \u003cp\u003e15.2 Literature Review 367\u003c\/p\u003e \u003cp\u003e15.3 Research Hypothesis 373\u003c\/p\u003e \u003cp\u003e15.4 Methodology 373\u003c\/p\u003e \u003cp\u003e15.5 Discussion 379\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 Alternative Data in Investment Management 391\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eRangapriya Saivasan and Madhavi Lokhande\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction 391\u003c\/p\u003e \u003cp\u003e16.2 Literature Review 393\u003c\/p\u003e \u003cp\u003e16.3 Research Methodology 395\u003c\/p\u003e \u003cp\u003e16.4 Results and Discussion 396\u003c\/p\u003e \u003cp\u003e16.5 Implications of This Study 403\u003c\/p\u003e \u003cp\u003e16.6 Conclusion 404\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 Beyond Rationality: Uncovering the Impact of Investor Behavior on Financial Markets 409\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eAnu Krishnamurthy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction 410\u003c\/p\u003e \u003cp\u003e17.2 Statement of the Problem 418\u003c\/p\u003e \u003cp\u003e17.3 Need for the Study 418\u003c\/p\u003e \u003cp\u003e17.4 Significance of the Study 419\u003c\/p\u003e \u003cp\u003e17.5 Discussions 422\u003c\/p\u003e \u003cp\u003e17.6 Implications 424\u003c\/p\u003e \u003cp\u003e17.7 Scope for Further Research 424\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 Volatility Transmission Role of Indian Equity and Commodity Markets 429\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eHarpreet Kaur and Amita Chaudhary\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction 430\u003c\/p\u003e \u003cp\u003e18.2 Literature Review 431\u003c\/p\u003e \u003cp\u003e18.3 Data and Methodology 434\u003c\/p\u003e \u003cp\u003e18.4 Results and Discussions 435\u003c\/p\u003e \u003cp\u003e18.5 Conclusion 438\u003c\/p\u003e \u003cp\u003eReferences 439\u003c\/p\u003e \u003cp\u003eGlossary 445\u003c\/p\u003e \u003cp\u003eIndex 457\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52433207951640,"sku":"9781394214303","price":165.29,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394214303.jpg?v=1784851841","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/deep-learning-tools-for-predicting-stock-market-movements-hardback-9781394214303","provider":"Freshly Printed Books","version":"1.0","type":"link"}