Data Analytics and AI for Quantitative Risk Assessment and Financial Computation PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Data Analytics and AI for Quantitative Risk Assessment and Financial Computation PDF full book. Access full book title Data Analytics and AI for Quantitative Risk Assessment and Financial Computation by Galety, Mohammad Gouse. Download full books in PDF and EPUB format.
Author: Galety, Mohammad Gouse
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 640
Get Book Here
Book Description
In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape.
Author: Galety, Mohammad Gouse
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 640
Get Book Here
Book Description
In today's fast-paced financial landscape, professionals face an uphill battle in effectively integrating data analytics and artificial intelligence (AI) into quantitative risk assessment and financial computation. The constantly increasing volume, velocity, and variety of data generated by digital transactions, market exchanges, and social media platforms offer unparalleled financial analysis and decision-making opportunities. However, professionals need sophisticated AI technologies and data analytics methodologies to harness this data for predictive modeling, risk assessment, and algorithmic trading. Navigating this complex terrain can be daunting, and a comprehensive guide that bridges theory and practice is necessary. Data Analytics and AI for Quantitative Risk Assessment and Financial Computation is an all-encompassing reference for finance professionals, risk managers, data scientists, and students seeking to leverage the transformative power of AI and data analytics in finance. The book encapsulates this integration's theoretical underpinnings, practical applications, challenges, and future directions, empowering readers to enhance their analytical capabilities, make informed decisions, and stay ahead in the competitive financial landscape.
Author: William Johnson
Publisher: HiTeX Press
ISBN:
Category : Business & Economics
Languages : en
Pages : 370
Get Book Here
Book Description
"Quantitative Investment Analysis: Techniques for Active Portfolio Management" offers a comprehensive exploration of the advanced methodologies used in the modern financial landscape to structure, analyze, and optimize investment portfolios. This engaging book demystifies the intersection of finance and quantitative analysis, making complex theories accessible to both novice investors and seasoned professionals. By delving into the intricacies of financial markets, readers are equipped with essential tools to evaluate diverse asset classes, develop robust trading strategies, and manage risk with precision. Through its detailed chapters, the book covers a spectrum of critical topics, from portfolio theory and equity valuation to the innovative application of machine learning and algorithmic trading. Each section provides actionable insights into optimizing returns, understanding market anomalies, and making informed decisions guided by a rigorous, quantitative framework. This text not only fosters a deep understanding of theoretical concepts but also presents real-world applications, empowering readers to navigate the challenges of contemporary financial markets with confidence and strategic acumen. Whether seeking to refine investment strategies or gain an edge in a competitive market, this book serves as an invaluable resource for mastering the art and science of quantitative investing.
Author: Singh, Amandeep
Publisher: IGI Global
ISBN:
Category : Business & Economics
Languages : en
Pages : 285
Get Book Here
Book Description
Today, algorithms steer and inform more than 75% of modern trades. These mathematical constructs play an intricate role in automating processes, predicting market trends, optimizing portfolios, and fortifying decision-making in the financial domain. In an era where algorithms underpin the very foundation of financial services, it is imperative to hold a deep understanding of the intricate web of computational finance. Algorithmic Approaches to Financial Technology: Forecasting, Trading, and Optimization takes a comprehensive approach, spotlighting the fusion of artificial intelligence(AI) and algorithms in financial operations. The chapters explore the expansive landscape of algorithmic applications, from scrutinizing market trends to managing risks. The emphasis extends to AI-driven personnel selection, implementing trusted financial services, crafting recommendation systems for financial platforms, and critical fraud detection. This book serves as a vital resource for researchers, students, and practitioners. Its core strength lies in discussing AI-based algorithms as a catalyst for evolving market trends. It provides algorithmic solutions for stock markets, portfolio optimization, and robust financial fraud detection mechanisms.
Author: Kumar, Raghvendra
Publisher: IGI Global
ISBN: 1668493195
Category : Computers
Languages : en
Pages : 502
Get Book Here
Book Description
With the rapid evolution of technology, identifying new risks is a constantly moving target. The metaverse is a virtual space that is interconnected with cloud computing and with companies, organizations, and even countries investing in virtual real estate. The questions of what new risks will become evident in these virtual worlds and in augmented reality and what real-world impacts they will have in an ever-expanding internet of things (IoT) need to be answered. Within continually connected societies that require uninterrupted functionality, cyber security is vital, and the ability to detect potential risks and ensure the security of computing systems is crucial to their effective use and success. Proper utilization of the latest technological advancements can help in developing more efficient techniques to prevent cyber threats and enhance cybersecurity. Risk Detection and Cyber Security for the Success of Contemporary Computing presents the newest findings with technological advances that can be utilized for more effective prevention techniques to protect against cyber threats. This book is led by editors of best-selling and highly indexed publications, and together they have over two decades of experience in computer science and engineering. Featuring extensive coverage on authentication techniques, cloud security, and mobile robotics, this book is ideally designed for students, researchers, scientists, and engineers seeking current research on methods, models, and implementation of optimized security in digital contexts.
Author: Cheng-Few Lee
Publisher: Springer Science & Business Media
ISBN: 0387771174
Category : Business & Economics
Languages : en
Pages : 1700
Get Book Here
Book Description
Quantitative finance is a combination of economics, accounting, statistics, econometrics, mathematics, stochastic process, and computer science and technology. Increasingly, the tools of financial analysis are being applied to assess, monitor, and mitigate risk, especially in the context of globalization, market volatility, and economic crisis. This two-volume handbook, comprised of over 100 chapters, is the most comprehensive resource in the field to date, integrating the most current theory, methodology, policy, and practical applications. Showcasing contributions from an international array of experts, the Handbook of Quantitative Finance and Risk Management is unparalleled in the breadth and depth of its coverage. Volume 1 presents an overview of quantitative finance and risk management research, covering the essential theories, policies, and empirical methodologies used in the field. Chapters provide in-depth discussion of portfolio theory and investment analysis. Volume 2 covers options and option pricing theory and risk management. Volume 3 presents a wide variety of models and analytical tools. Throughout, the handbook offers illustrative case examples, worked equations, and extensive references; additional features include chapter abstracts, keywords, and author and subject indices. From "arbitrage" to "yield spreads," the Handbook of Quantitative Finance and Risk Management will serve as an essential resource for academics, educators, students, policymakers, and practitioners.
Author: Sandeep Kautish
Publisher: Springer Nature
ISBN: 9819953545
Category : Technology & Engineering
Languages : en
Pages : 523
Get Book Here
Book Description
This book covers the applications of computational intelligence techniques in business systems and advocates how these techniques are useful in modern business operations. The book redefines the computational intelligence foundations, the three pillars - neural networks, evolutionary computation, and fuzzy systems. It also discusses emerging areas such as swarm intelligence, artificial immune systems (AIS), support vector machines, rough sets, and chaotic systems. The other areas have also been demystified in the book to strengthen the range of computational intelligence techniques such as expert systems, knowledge-based systems, and genetic algorithms. Therefore, this book will redefine the role of computational intelligence techniques in modern business system operations such as marketing, finance & accounts, operations, personnel management, supply chain management, and logistics. Besides, this book guides the readers through using them to model, discover, and interpret new patterns that cannot be found through statistical methods alone in various business system operations. This book reveals how computational intelligence can inform the design and integration of services, architecture, brand identity, and product portfolio across the entire enterprise. The book will provide insights into research gaps, open challenges, and unsolved computational intelligence problems. The book will act as a premier reference and instant material for all the users who are contributing/practicing the adaptation of computational intelligence modern techniques in business systems.
Author: David Dollar
Publisher: Brookings Institution Press
ISBN: 0815739567
Category : Business & Economics
Languages : en
Pages : 342
Get Book Here
Book Description
Describes how China is in the lead in transforming finance for the digital age This book is the product of a joint research project between economists at the National School of Development, especially the affiliated Institute of Digital Finance, at Peking University and at the Brookings Institution. It investigates the impact of financial technology on job creation, income distribution, and consumer welfare in China. It also examines larger systemic issues such as monetary policy, stability of the banking sector, and international trade and payments.
Author: Naim, Arshi
Publisher: IGI Global
ISBN:
Category : Technology & Engineering
Languages : en
Pages : 422
Get Book Here
Book Description
The world is addressing the insistent challenge of climate change, and the need for innovative solutions has become paramount. In this period of technical developments, artificial intelligence (AI) has emerged as a powerful instrument with enormous prospects to combat climate change and other environmental subjects. AI's ability to process vast amounts of data, identify patterns, and make intelligent predictions offers unprecedented opportunities to tackle this global crisis. High-Performance Computing (HPC) or super-computing environments address these large and complex challenges with individual nodes (computers) working together in a cluster (connected group) to perform massive amounts of computing in a short period. Creating and removing these clusters is often automated in the cloud to reduce costs. Computer networks, communication systems, and other IT infrastructures have a growing environmental footprint due to significant energy consumption and greenhouse gas emissions. To address this seemingly self-defeating conundrum, and create a truly sustainable environment, new energy models, algorithms, methodologies, platforms, tools, and systems are required to support next-generation computing and communication infrastructures. Harnessing High-Performance Computing and AI for Environmental Sustainability navigates through AI-driven solutions from sustainable agriculture and land management to energy optimization and smart grids. It unveils how AI algorithms can analyze colossal datasets, offering unprecedented insights into climate modeling, weather prediction, and long-term climate trends. Integrating AI-powered optimization algorithms revolutionizes energy systems, propelling the transition towards a low-carbon future by reducing greenhouse gas emissions and enhancing efficiency. This book is ideal for educators, environmentalists, industry professionals, and researchers alike, and it explores the ethical dimensions and policies surrounding AI's contribution to environmental development.
Author:
Publisher: John Wiley & Sons
ISBN: 0470035498
Category : Mathematics
Languages : en
Pages : 2163
Get Book Here
Book Description
Leading the way in this field, the Encyclopedia of Quantitative Risk Analysis and Assessment is the first publication to offer a modern, comprehensive and in-depth resource to the huge variety of disciplines involved. A truly international work, its coverage ranges across risk issues pertinent to life scientists, engineers, policy makers, healthcare professionals, the finance industry, the military and practising statisticians. Drawing on the expertise of world-renowned authors and editors in this field this title provides up-to-date material on drug safety, investment theory, public policy applications, transportation safety, public perception of risk, epidemiological risk, national defence and security, critical infrastructure, and program management. This major publication is easily accessible for all those involved in the field of risk assessment and analysis. For ease-of-use it is available in print and online.
Author: Utku Kose
Publisher: CRC Press
ISBN: 1040203884
Category : Computers
Languages : en
Pages : 349
Get Book Here
Book Description
This book provides an examination of cutting-edge research and developments in the field of artificial intelligence. It seeks to extend the view in both technical and societal evaluations to ensure a well-defined balance for societal outcomes. It explores hot topics such as generative artificial intelligence, artificial intelligence in law, education, and climate change. Artificial Intelligence: Technical and Societal Advancements seeks to bridge the gap between theory and practical applications of AI by giving readers insight into recent advancements. It offers readers a deep dive into the transformative power of AI for the present and future world. As artificial intelligence continues to revolutionize various sectors, the book discusses applications from healthcare to finance and from entertainment to industrial areas. It discusses the technical aspects of intelligent systems and the effects of these aspects on humans. To this point, this book considers technical advancements while discussing the societal pros and cons in terms of human-machine interaction in critical applications. The authors also stress the importance of deriving policies and predictions about how to make future intelligent systems compatible with humans through a necessary level of human management. Finally, this book provides the opinions and views of researchers and experts (from public/private sector) including educators, lawyers, policymakers, managers, and business-related representatives. The target readers of this book include academicians; researchers; experts; policymakers; educators; and B.S., M.S., and Ph.D. students in the context of target problem fields. It can be used accordingly as a reference source and even supportive material for artificial intelligence-oriented courses.
