Investment Analytics In The Dawn Of Artificial Intelligence
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Investment Analytics In The Dawn Of Artificial Intelligence
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Author : Bernard Lee
language : en
Publisher: World Scientific
Release Date : 2019-07-24
Investment Analytics In The Dawn Of Artificial Intelligence written by Bernard Lee and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-24 with Business & Economics categories.
A class of highly mathematical algorithms works with three-dimensional (3D) data known as graphs. Our research challenge focuses on applying these algorithms to solve more complex problems with financial data, which tend to be in higher dimensions (easily over 100), based on probability distributions, with time subscripts and jumps. The 3D research analogy is to train a navigation algorithm when the way-finding coordinates and obstacles such as buildings change dynamically and are expressed in higher dimensions with jumps.Our short title 'ia≠ai' symbolizes how investment analytics is not a simplistic reapplication of artificial intelligence (AI) techniques proven in engineering. This book presents best-of-class sophisticated techniques available today to solve high dimensional problems with properties that go deeper than what is required to solve customary problems in engineering today.Dr Bernard Lee is the Founder and CEO of HedgeSPA, which stands for Sophisticated Predictive Analytics for Hedge Funds and Institutions. Previously, he was a managing director in the Portfolio Management Group of BlackRock in New York City as well as a finance professor who has taught and guest-lectured at a number of top universities globally.Related Link(s)
Ia Not Equal Ai
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Author : Bernard Lee
language : en
Publisher:
Release Date : 2016
Ia Not Equal Ai written by Bernard Lee and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
The Dawn Of Artificial Intelligence In Business
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Author : Davide Gazzotti
language : en
Publisher:
Release Date : 2020-02-18
The Dawn Of Artificial Intelligence In Business written by Davide Gazzotti and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-02-18 with categories.
Today technology is advancing faster and taking less time to be widely adopted than ever before: it took roughly 10,000 years to go from writing to the printing press, but only 500 years more to get the email. It seems we're at the dawn of a new age: the age of Artificial Intelligence, but many businesses are still sitting on the fence waiting for a way to understand if AI fits their needs right away. Artificial intelligence is not a magic box, it is not a robot that supernaturally solves problems, but it's more a series of strategies, compromises, and applications that allow getting closer to the result starting from data. And the result of AI in business is the ability to predict. However, for an accurate prediction, you have to struggle with lots of data, computational power, technologies, return on investment.With simple language and practical examples, "The Dawn of Artificial Intelligence in Business" uncovers the technical basis on which every successful company is building their AI applications nowadays, making use of big data analytics applied to business needs through Artificial Intelligence. If you are a manager, IT enthusiast, or entrepreneur, you will be inspired by real-world applications and stop having doubts about starting to innovate your business in the age of AI.
Artificial Intelligence In Finance Investing
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Author : Robert R. Trippi
language : en
Publisher: McGraw Hill Professional
Release Date : 1996
Artificial Intelligence In Finance Investing written by Robert R. Trippi and has been published by McGraw Hill Professional this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Business & Economics categories.
In Artificial Intelligence in Finance and Investing, authors Robert Trippi and Jae Lee explain this fascinating new technology in terms that portfolio managers, institutional investors, investment analysis, and information systems professionals can understand. Using real-life examples and a practical approach, this rare and readable volume discusses the entire field of artificial intelligence of relevance to investing, so that readers can realize the benefits and evaluate the features of existing or proposed systems, and ultimately construct their own systems. Topics include using Expert Systems for Asset Allocation, Timing Decisions, Pattern Recognition, and Risk Assessment; overview of Popular Knowledge-Based Systems; construction of Synergistic Rule Bases for Securities Selection; incorporating the Markowitz Portfolio Optimization Model into Knowledge-Based Systems; Bayesian Theory and Fuzzy Logic System Components; Machine Learning in Portfolio Selection and Investment Timing, including Pattern-Based Learning and Fenetic Algorithms; and Neural Network-Based Systems. To illustrate the concepts presented in the book, the authors conclude with a valuable practice session and analysis of a typical knowledge-based system for investment management, K-FOLIO. For those who want to stay on the cutting edge of the "application" revolution, Artificial Intelligence in Finance and Investing offers a pragmatic introduction to the use of knowledge-based systems in securities selection and portfolio management.
The Ai Book
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Author : Ivana Bartoletti
language : en
Publisher: John Wiley & Sons
Release Date : 2020-04-09
The Ai Book written by Ivana Bartoletti and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-04-09 with Business & Economics categories.
Written by prominent thought leaders in the global fintech space, The AI Book aggregates diverse expertise into a single, informative volume and explains what artifical intelligence really means and how it can be used across financial services today. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. Coverage includes: · Understanding the AI Portfolio: from machine learning to chatbots, to natural language processing (NLP); a deep dive into the Machine Intelligence Landscape; essentials on core technologies, rethinking enterprise, rethinking industries, rethinking humans; quantum computing and next-generation AI · AI experimentation and embedded usage, and the change in business model, value proposition, organisation, customer and co-worker experiences in today’s Financial Services Industry · The future state of financial services and capital markets – what’s next for the real-world implementation of AITech? · The innovating customer – users are not waiting for the financial services industry to work out how AI can re-shape their sector, profitability and competitiveness · Boardroom issues created and magnified by AI trends, including conduct, regulation & oversight in an algo-driven world, cybersecurity, diversity & inclusion, data privacy, the ‘unbundled corporation’ & the future of work, social responsibility, sustainability, and the new leadership imperatives · Ethical considerations of deploying Al solutions and why explainable Al is so important
Machine Learning And Ai In Finance
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Author : German Creamer
language : en
Publisher: Routledge
Release Date : 2021-04-06
Machine Learning And Ai In Finance written by German Creamer and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-06 with Business & Economics categories.
The significant amount of information available in any field requires a systematic and analytical approach to select the most critical information and anticipate major events. During the last decade, the world has witnessed a rapid expansion of applications of artificial intelligence (AI) and machine learning (ML) algorithms to an increasingly broad range of financial markets and problems. Machine learning and AI algorithms facilitate this process understanding, modelling and forecasting the behaviour of the most relevant financial variables. The main contribution of this book is the presentation of new theoretical and applied AI perspectives to find solutions to unsolved finance questions. This volume proposes an optimal model for the volatility smile, for modelling high-frequency liquidity demand and supply and for the simulation of market microstructure features. Other new AI developments explored in this book includes building a universal model for a large number of stocks, developing predictive models based on the average price of the crowd, forecasting the stock price using the attention mechanism in a neural network, clustering multivariate time series into different market states, proposing a multivariate distance nonlinear causality test and filtering out false investment strategies with an unsupervised learning algorithm. Machine Learning and AI in Finance explores the most recent advances in the application of innovative machine learning and artificial intelligence models to predict financial time series, to simulate the structure of the financial markets, to explore nonlinear causality models, to test investment strategies and to price financial options. The chapters in this book were originally published as a special issue of the Quantitative Finance journal.
Alternative Data And Artificial Intelligence Techniques
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Author : Qingquan Tony Zhang
language : en
Publisher: Springer Nature
Release Date : 2022-10-31
Alternative Data And Artificial Intelligence Techniques written by Qingquan Tony Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-31 with Business & Economics categories.
This book introduces a state-of-art approach in evaluating portfolio management and risk based on artificial intelligence and alternative data. The book covers a textual analysis of news and social media, information extraction from GPS and IoTs data, and risk predictions based on small transaction data, etc. The book summarizes and introduces the advancement in each area and highlights the machine learning and deep learning techniques utilized to achieve the goals. As a complement, it also illustrates examples on how to leverage the python package to visualize and analyze the alternative datasets, and will be of interest to academics, researchers, and students of risk evaluation, risk management, data, AI, and financial innovation.
Artificial Intelligence For Asset Management And Investment
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Author : Al Naqvi
language : en
Publisher: John Wiley & Sons
Release Date : 2021-02-09
Artificial Intelligence For Asset Management And Investment written by Al Naqvi and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-09 with Business & Economics categories.
Make AI technology the backbone of your organization to compete in the Fintech era The rise of artificial intelligence is nothing short of a technological revolution. AI is poised to completely transform asset management and investment banking, yet its current application within the financial sector is limited and fragmented. Existing AI implementations tend to solve very narrow business issues, rather than serving as a powerful tech framework for next-generation finance. Artificial Intelligence for Asset Management and Investment provides a strategic viewpoint on how AI can be comprehensively integrated within investment finance, leading to evolved performance in compliance, management, customer service, and beyond. No other book on the market takes such a wide-ranging approach to using AI in asset management. With this guide, you’ll be able to build an asset management firm from the ground up—or revolutionize your existing firm—using artificial intelligence as the cornerstone and foundation. This is a must, because AI is quickly growing to be the single competitive factor for financial firms. With better AI comes better results. If you aren’t integrating AI in the strategic DNA of your firm, you’re at risk of being left behind. See how artificial intelligence can form the cornerstone of an integrated, strategic asset management framework Learn how to build AI into your organization to remain competitive in the world of Fintech Go beyond siloed AI implementations to reap even greater benefits Understand and overcome the governance and leadership challenges inherent in AI strategy Until now, it has been prohibitively difficult to map the high-tech world of AI onto complex and ever-changing financial markets. Artificial Intelligence for Asset Management and Investment makes this difficulty a thing of the past, providing you with a professional and accessible framework for setting up and running artificial intelligence in your financial operations.
Artificial Intelligence In Financial Markets
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Author : Christian L. Dunis
language : en
Publisher: Springer
Release Date : 2016-11-21
Artificial Intelligence In Financial Markets written by Christian L. Dunis and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-21 with Business & Economics categories.
As technology advancement has increased, so to have computational applications for forecasting, modelling and trading financial markets and information, and practitioners are finding ever more complex solutions to financial challenges. Neural networking is a highly effective, trainable algorithmic approach which emulates certain aspects of human brain functions, and is used extensively in financial forecasting allowing for quick investment decision making. This book presents the most cutting-edge artificial intelligence (AI)/neural networking applications for markets, assets and other areas of finance. Split into four sections, the book first explores time series analysis for forecasting and trading across a range of assets, including derivatives, exchange traded funds, debt and equity instruments. This section will focus on pattern recognition, market timing models, forecasting and trading of financial time series. Section II provides insights into macro and microeconomics and how AI techniques could be used to better understand and predict economic variables. Section III focuses on corporate finance and credit analysis providing an insight into corporate structures and credit, and establishing a relationship between financial statement analysis and the influence of various financial scenarios. Section IV focuses on portfolio management, exploring applications for portfolio theory, asset allocation and optimization. This book also provides some of the latest research in the field of artificial intelligence and finance, and provides in-depth analysis and highly applicable tools and techniques for practitioners and researchers in this field.
Intelligent Optimization Techniques For Business Analytics
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Author : Bansal, Sanjeev
language : en
Publisher: IGI Global
Release Date : 2024-04-15
Intelligent Optimization Techniques For Business Analytics written by Bansal, Sanjeev and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-15 with Business & Economics categories.
Today, the convergence of cutting-edge algorithms and actionable insights in business is paramount for success. Scholars and practitioners grapple with the dilemma of optimizing data to drive efficiency, innovation, and competitiveness. The formidable challenge of effectively harnessing the immense power of intelligent optimization techniques and business analytics only increases as the volume of data grows exponentially, and the complexities of navigating the intricate landscape of business analytics becomes more daunting. This pressing issue underscores the critical need for a comprehensive solution, and Intelligent Optimization Techniques for Business Analytics is poised to provide much-needed answers. This groundbreaking book offers an all-encompassing solution to the challenges that academic scholars encounter in the pursuit of mastering the interplay between learning algorithms and intelligent optimization techniques for business analytics. Through a wealth of diverse perspectives and expert case studies, it illuminates the path to effectively implementing these advanced systems in real-world business scenarios. It caters not only to the scholarly community but also to industry professionals and policymakers, equipping them with the necessary tools and insights to excel in the realm of data-driven decision-making.