Author: Mohammad Zoynul Abedin
Publisher: Routledge
ISBN: 1000394115
Category : Business & Economics
Languages : en
Pages : 259
Book Description
• A useful guide to financial product modeling and to minimizing business risk and uncertainty • Looks at wide range of financial assets and markets and correlates them with enterprises’ profitability • Introduces advanced and novel machine learning techniques in finance such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches and applies them to analyze finance data sets • Real world applicable examples to further understanding
The Essentials of Machine Learning in Finance and Accounting
Author: Mohammad Zoynul Abedin
Publisher: Routledge
ISBN: 1000394115
Category : Business & Economics
Languages : en
Pages : 259
Book Description
• A useful guide to financial product modeling and to minimizing business risk and uncertainty • Looks at wide range of financial assets and markets and correlates them with enterprises’ profitability • Introduces advanced and novel machine learning techniques in finance such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches and applies them to analyze finance data sets • Real world applicable examples to further understanding
Publisher: Routledge
ISBN: 1000394115
Category : Business & Economics
Languages : en
Pages : 259
Book Description
• A useful guide to financial product modeling and to minimizing business risk and uncertainty • Looks at wide range of financial assets and markets and correlates them with enterprises’ profitability • Introduces advanced and novel machine learning techniques in finance such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches and applies them to analyze finance data sets • Real world applicable examples to further understanding
The Essentials of Machine Learning in Finance and Accounting
Author: Mohammad Zoynul Abedin
Publisher: Routledge
ISBN: 1000394123
Category : Business & Economics
Languages : en
Pages : 275
Book Description
This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data. Business risk and uncertainty are two of the toughest challenges in the financial industry. This book will be a useful guide to the use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.
Publisher: Routledge
ISBN: 1000394123
Category : Business & Economics
Languages : en
Pages : 275
Book Description
This book introduces machine learning in finance and illustrates how we can use computational tools in numerical finance in real-world context. These computational techniques are particularly useful in financial risk management, corporate bankruptcy prediction, stock price prediction, and portfolio management. The book also offers practical and managerial implications of financial and managerial decision support systems and how these systems capture vast amount of financial data. Business risk and uncertainty are two of the toughest challenges in the financial industry. This book will be a useful guide to the use of machine learning in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.
Novel Financial Applications of Machine Learning and Deep Learning
Author: Mohammad Zoynul Abedin
Publisher: Springer Nature
ISBN: 3031185528
Category : Business & Economics
Languages : en
Pages : 235
Book Description
This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study. The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice. The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.
Publisher: Springer Nature
ISBN: 3031185528
Category : Business & Economics
Languages : en
Pages : 235
Book Description
This book presents the state-of-the-art applications of machine learning in the finance domain with a focus on financial product modeling, which aims to advance the model performance and minimize risk and uncertainty. It provides both practical and managerial implications of financial and managerial decision support systems which capture a broad range of financial data traits. It also serves as a guide for the implementation of risk-adjusted financial product pricing systems, while adding a significant supplement to the financial literacy of the investigated study. The book covers advanced machine learning techniques, such as Support Vector Machine, Neural Networks, Random Forest, K-Nearest Neighbors, Extreme Learning Machine, Deep Learning Approaches, and their application to finance datasets. It also leverages real-world financial instances to practice business product modeling and data analysis. Software code, such as MATLAB, Python and/or R including datasets within a broad range of financial domain are included for more rigorous practice. The book primarily aims at providing graduate students and researchers with a roadmap for financial data analysis. It is also intended for a broad audience, including academics, professional financial analysts, and policy-makers who are involved in forecasting, modeling, trading, risk management, economics, credit risk, and portfolio management.
Machine Learning and Artificial Intelligence with Industrial Applications
Author: Diego Carou
Publisher: Springer Nature
ISBN: 3030910067
Category : Technology & Engineering
Languages : en
Pages : 216
Book Description
This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.
Publisher: Springer Nature
ISBN: 3030910067
Category : Technology & Engineering
Languages : en
Pages : 216
Book Description
This book presents the tools used in machine learning (ML) and the benefits of using such tools in facilities. It focus on real life business applications, explaining the most popular algorithms easily and clearly without the use of calculus or matrix/vector algebra. Replete with case studies, this book provides a working knowledge of ML current and future capabilities and the impact it will have on every business. It demonstrates that it is also possible to carry out successful ML and AI projects in any manufacturing plant, even without fully fulfilling the five V (Volume, Velocity, Variety, Veracity and Value) usually associated with big data. This book takes a closer look at how AI and ML are also able to work for industrial area, as well as how you could adapt some of the standard tips and techniques (usually for big data) for your own needs in your SME. Organizations which first understand these tools and know how to use them will benefit at the expense of their rivals.
Cyber Security and Business Intelligence
Author: Mohammad Zoynul Abedin
Publisher: Taylor & Francis
ISBN: 1003817882
Category : Business & Economics
Languages : en
Pages : 257
Book Description
To cope with the competitive worldwide marketplace, organizations rely on business intelligence to an increasing extent. Cyber security is an inevitable practice to protect the entire business sector and its customer. This book presents the significance and application of cyber security for safeguarding organizations, individuals’ personal information, and government. The book provides both practical and managerial implications of cyber security that also supports business intelligence and discusses the latest innovations in cyber security. It offers a roadmap to master degree students and PhD researchers for cyber security analysis in order to minimize the cyber security risk and protect customers from cyber-attack. The book also introduces the most advanced and novel machine learning techniques including, but not limited to, Support Vector Machine, Neural Networks, Extreme Learning Machine, Ensemble Learning, and Deep Learning Approaches, with a goal to apply those to cyber risk management datasets. It will also leverage real-world financial instances to practise business product modelling and data analysis. The contents of this book will be useful for a wide audience who are involved in managing network systems, data security, data forecasting, cyber risk modelling, fraudulent credit risk detection, portfolio management, and data regulatory bodies. It will be particularly beneficial to academics as well as practitioners who are looking to protect their IT system, and reduce data breaches and cyber-attack vulnerabilities.
Publisher: Taylor & Francis
ISBN: 1003817882
Category : Business & Economics
Languages : en
Pages : 257
Book Description
To cope with the competitive worldwide marketplace, organizations rely on business intelligence to an increasing extent. Cyber security is an inevitable practice to protect the entire business sector and its customer. This book presents the significance and application of cyber security for safeguarding organizations, individuals’ personal information, and government. The book provides both practical and managerial implications of cyber security that also supports business intelligence and discusses the latest innovations in cyber security. It offers a roadmap to master degree students and PhD researchers for cyber security analysis in order to minimize the cyber security risk and protect customers from cyber-attack. The book also introduces the most advanced and novel machine learning techniques including, but not limited to, Support Vector Machine, Neural Networks, Extreme Learning Machine, Ensemble Learning, and Deep Learning Approaches, with a goal to apply those to cyber risk management datasets. It will also leverage real-world financial instances to practise business product modelling and data analysis. The contents of this book will be useful for a wide audience who are involved in managing network systems, data security, data forecasting, cyber risk modelling, fraudulent credit risk detection, portfolio management, and data regulatory bodies. It will be particularly beneficial to academics as well as practitioners who are looking to protect their IT system, and reduce data breaches and cyber-attack vulnerabilities.
Applications of Block Chain technology and Artificial Intelligence
Author: Mohammad Irfan
Publisher: Springer Nature
ISBN: 3031473248
Category :
Languages : en
Pages : 304
Book Description
Publisher: Springer Nature
ISBN: 3031473248
Category :
Languages : en
Pages : 304
Book Description
Cutting-Edge Business Technologies in the Big Data Era
Author: Saad G. Yaseen
Publisher: Springer Nature
ISBN: 3031424557
Category :
Languages : en
Pages : 438
Book Description
Publisher: Springer Nature
ISBN: 3031424557
Category :
Languages : en
Pages : 438
Book Description
Contemporary Issues in Quantitative Finance
Author: Ahmet Can Inci
Publisher: Taylor & Francis
ISBN: 1000859363
Category : Business & Economics
Languages : en
Pages : 302
Book Description
Contemporary quantitative finance connects the abstract theory and the practical use of financial innovations, such as ultra-high-frequency trading and cryptocurrencies. It teaches students how to use cutting-edge computational techniques, mathematical tools, and statistical methodologies, with a focus on real-life applications. The textbook opens with chapters on financial markets, global finance, and financial crises, setting the subject in its historical and international context. It then examines key topics in modern quantitative finance, including asset pricing, exchange-traded funds, Monte Carlo simulations, options, alternative investments, artificial intelligence, and big data analytics in finance. Complex theory is condensed to intuition, with appendices presenting advanced mathematical or statistical techniques. Each chapter offers Excel-based implementations, conceptual questions, quantitative problems, and a research project, giving students ample opportunity to develop their skills. Clear chapter objectives, summaries, and key terms also support student learning. Digital supplements, including code and PowerPoint slides, are available for instructors. Assuming some prior financial education, this textbook is suited to upper-level undergraduate and postgraduate courses in quantitative finance, financial engineering, and derivatives.
Publisher: Taylor & Francis
ISBN: 1000859363
Category : Business & Economics
Languages : en
Pages : 302
Book Description
Contemporary quantitative finance connects the abstract theory and the practical use of financial innovations, such as ultra-high-frequency trading and cryptocurrencies. It teaches students how to use cutting-edge computational techniques, mathematical tools, and statistical methodologies, with a focus on real-life applications. The textbook opens with chapters on financial markets, global finance, and financial crises, setting the subject in its historical and international context. It then examines key topics in modern quantitative finance, including asset pricing, exchange-traded funds, Monte Carlo simulations, options, alternative investments, artificial intelligence, and big data analytics in finance. Complex theory is condensed to intuition, with appendices presenting advanced mathematical or statistical techniques. Each chapter offers Excel-based implementations, conceptual questions, quantitative problems, and a research project, giving students ample opportunity to develop their skills. Clear chapter objectives, summaries, and key terms also support student learning. Digital supplements, including code and PowerPoint slides, are available for instructors. Assuming some prior financial education, this textbook is suited to upper-level undergraduate and postgraduate courses in quantitative finance, financial engineering, and derivatives.
Achieving Sustainable Business Through AI, Technology Education and Computer Science
Author: Allam Hamdan
Publisher: Springer Nature
ISBN: 3031712137
Category :
Languages : en
Pages : 726
Book Description
Publisher: Springer Nature
ISBN: 3031712137
Category :
Languages : en
Pages : 726
Book Description
The Economics of COVID-19
Author: Badi H. Baltagi
Publisher: Emerald Group Publishing
ISBN: 1800716958
Category : Business & Economics
Languages : en
Pages : 143
Book Description
The Economics of COVID-19 contains selected contributions analysing the effects of the global pandemic on macroeconomics, computable general equilibrium models and financial markets, as well as health studies proposing to improve the traditional epidemic models.
Publisher: Emerald Group Publishing
ISBN: 1800716958
Category : Business & Economics
Languages : en
Pages : 143
Book Description
The Economics of COVID-19 contains selected contributions analysing the effects of the global pandemic on macroeconomics, computable general equilibrium models and financial markets, as well as health studies proposing to improve the traditional epidemic models.