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Author: Alexander Denev
Publisher: John Wiley & Sons
ISBN: 1119601797
Category : Business & Economics
Languages : en
Pages : 416
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Book Description
The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors—leading experts in financial modeling, machine learning, and quantitative research and analytics—employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book: Provides an integrated modeling approach to extract value from multiple types of datasets Treats the processes needed to make alternative data signals operational Helps investors and risk managers rethink how they engage with alternative datasets Features practical use case studies in many different financial markets and real-world techniques Describes how to avoid potential pitfalls and missteps in starting the alternative data journey Explains how to integrate information from different datasets to maximize informational value The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.
Author: Alexander Denev
Publisher: John Wiley & Sons
ISBN: 1119601797
Category : Business & Economics
Languages : en
Pages : 416
Get Book Here
Book Description
The first and only book to systematically address methodologies and processes of leveraging non-traditional information sources in the context of investing and risk management Harnessing non-traditional data sources to generate alpha, analyze markets, and forecast risk is a subject of intense interest for financial professionals. A growing number of regularly-held conferences on alternative data are being established, complemented by an upsurge in new papers on the subject. Alternative data is starting to be steadily incorporated by conventional institutional investors and risk managers throughout the financial world. Methodologies to analyze and extract value from alternative data, guidance on how to source data and integrate data flows within existing systems is currently not treated in literature. Filling this significant gap in knowledge, The Book of Alternative Data is the first and only book to offer a coherent, systematic treatment of the subject. This groundbreaking volume provides readers with a roadmap for navigating the complexities of an array of alternative data sources, and delivers the appropriate techniques to analyze them. The authors—leading experts in financial modeling, machine learning, and quantitative research and analytics—employ a step-by-step approach to guide readers through the dense jungle of generated data. A first-of-its kind treatment of alternative data types, sources, and methodologies, this innovative book: Provides an integrated modeling approach to extract value from multiple types of datasets Treats the processes needed to make alternative data signals operational Helps investors and risk managers rethink how they engage with alternative datasets Features practical use case studies in many different financial markets and real-world techniques Describes how to avoid potential pitfalls and missteps in starting the alternative data journey Explains how to integrate information from different datasets to maximize informational value The Book of Alternative Data is an indispensable resource for anyone wishing to analyze or monetize different non-traditional datasets, including Chief Investment Officers, Chief Risk Officers, risk professionals, investment professionals, traders, economists, and machine learning developers and users.
Author: Kashi R Balachandran
Publisher: World Scientific
ISBN: 9811220484
Category : Business & Economics
Languages : en
Pages : 715
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Book Description
Can there be reliable information that is also relevant to decision making? Information for Efficient Decision Making: Big Data, Blockchain and Relevance focuses on the consolidation of information to facilitate making decisions in firms, in order to make their operations efficient to reduce their costs and consequently, increase their profitability. The advent of blockchain has generated great interest as an alternative to centralized organizations, where the data is gathered through a centralized ledger keeping of activities of the firm. The decentralized ledger keeping is one of the main features of blockchain that has given rise to many issues of technology, development, implementation, privacy, acceptance, evaluation and so on. Blockchain concept is a follow-up to big data environment facilitated by enormous progress in computer hardware, storage capacities and technological prowess. This has resulted in the rapid acquiring of data not considered possible earlier. With shrewd modeling analytics and algorithms, the applications have grown to significant levels. This handbook discusses the progress in data collection, pros and cons of collecting information on decentralized publicly available ledgers and several applications.
Author: Tony Guida
Publisher: John Wiley & Sons
ISBN: 1119522196
Category : Business & Economics
Languages : en
Pages : 308
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Book Description
Get to know the ‘why’ and ‘how’ of machine learning and big data in quantitative investment Big Data and Machine Learning in Quantitative Investment is not just about demonstrating the maths or the coding. Instead, it’s a book by practitioners for practitioners, covering the questions of why and how of applying machine learning and big data to quantitative finance. The book is split into 13 chapters, each of which is written by a different author on a specific case. The chapters are ordered according to the level of complexity; beginning with the big picture and taxonomy, moving onto practical applications of machine learning and finally finishing with innovative approaches using deep learning. • Gain a solid reason to use machine learning • Frame your question using financial markets laws • Know your data • Understand how machine learning is becoming ever more sophisticated Machine learning and big data are not a magical solution, but appropriately applied, they are extremely effective tools for quantitative investment — and this book shows you how.
Author: Susanne Chishti
Publisher: John Wiley & Sons
ISBN: 1119218934
Category : Business & Economics
Languages : en
Pages : 315
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Book Description
A front-line industry insider's look at the financial technology explosion The FINTECH Book is your primary guide to the financial technology revolution, and the disruption, innovation and opportunity therein. Written by prominent thought leaders in the global fintech investment space, this book aggregates diverse industry expertise into a single informative volume to provide entrepreneurs, bankers and investors with the answers they need to capitalize on this lucrative market. Key industry developments are explained in detail, and critical insights from cutting-edge practitioners offer first-hand information and lessons learned. The financial technology sector is booming, and entrepreneurs, bankers, consultants, investors and asset managers are scrambling for more information: Who are the key players? What's driving the explosive growth? What are the risks? This book collates insights, knowledge and guidance from industry experts to provide the answers to these questions and more. Get up to speed on the latest industry developments Grasp the market dynamics of the 'fintech revolution' Realize the sector's potential and impact on related industries Gain expert insight on investment and entrepreneurial opportunities The fintech market captured over US$14 billion in 2014, a three-fold increase from the previous year. New startups are popping up at an increasing pace, and large banks and insurance companies are being pushed toward increasing digital operations in order to survive. The financial technology sector is booming and The FINTECH Book is the first crowd-sourced book on the subject globally, making it an invaluable source of information for anybody working in or interested in this space.
Author: Richard Bateson
Publisher: World Scientific
ISBN: 1800612184
Category : Business & Economics
Languages : en
Pages : 288
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Book Description
Welcome to the secretive club of modern hedge funds, where important players in the world of investing and capital markets have invested close to $4 trillion globally.If you're intrigued by the inner workings of hedge funds, investment techniques and technologies they use to source investment alpha, this book is for you. Focusing on the author's three decades of trading experience at leading banks and hedge funds, it covers both discretionary and computer-driven strategies and perspectives on AI-based and quantamental investing using new alternative data, which includes numerous examples and insights of real trades and investment strategies. No mathematical knowledge is required, with the relevant algorithms detailed in the appendices.Discretionary investing details equity and credit investing across the corporate capital structure. Through trading equities, bonds and loans, event-driven trades can target profitable special situations and relative value opportunities. Systematic trading involves computer-driven strategies derived from a scientific and statistical analysis of liquid markets. The investment strategies of both commodity trading advisors (CTAs) and long/short equity funds are detailed, from trend-following to factor-based approaches. AI investing is fashionable but does the reality for hedge funds correspond to the AI hype present in other non-financial domains? AI using neural nets and other machine learning techniques are outlined along with their practical application in regards to investing.Quantitative Hedge Funds also discusses environmental, social and governance (ESG) investing, which has rapidly evolved as the public and institutions demand solutions to global problems such as climate change, pollution and unethical labour practices. ESG investment strategies are migrating out of the long-only space and into hedge funds.Finally, the advent of big data has led to multiple alternative datasets available for hedge fund managers. The integration of alternative data into the investment process is discussed, together with the rise of so-called quantamental investing, a hybrid of the best of human skill and computer-based technologies.Related Link(s)
Author: Matthew Krantz
Publisher: John Wiley & Sons
ISBN: 111926359X
Category : Business & Economics
Languages : en
Pages : 427
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Book Description
Determine the strength of any business with fundamental analysis Have you ever wondered the key to multibillionaire Warren Buffet's five-decade run as the most successful investor in history? The answer is simple: fundamental analysis. In this easy-to-understand, practical, and savvy guide, you'll discover how it helps you assess a business' overall financial performance by using historical and present data to forecast its future monetary value—and why this powerful tool is particularly important to investors in times of economic downturn. It's more important than ever for investors to know the true financial stability of a business, and this new edition of Fundamental Analysis For Dummies shows you how. Whether you're a seasoned investor or just want to learn how to make more intelligent and prudent investment decisions, this plain-English guide gives you practical tips, tricks, and trade secrets for using fundamental analysis to manage your portfolio and enhance your understanding of shrewdly selecting stocks! Predict the future value of a business based on its current and historical financial data Gauge a company's performance against its competitors Determine if a company's credit standing is in jeopardy Apply fundamental analysis to other investment vehicles, like currency, bonds, and commodities With the help of Fundamental Analysis For Dummies, you just may find the bargains that could make you the next Warren Buffet!
Author: Gautam Mitra
Publisher: CRC Press
ISBN: 1000897982
Category : Business & Economics
Languages : en
Pages : 488
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Book Description
Handbook of Alternative Data in Finance, Volume I motivates and challenges the reader to explore and apply Alternative Data in finance. The book provides a robust and in-depth overview of Alternative Data, including its definition, characteristics, difference from conventional data, categories of Alternative Data, Alternative Data providers, and more. The book also offers a rigorous and detailed exploration of process, application and delivery that should be practically useful to researchers and practitioners alike. Features Includes cutting edge applications in machine learning, fintech, and more Suitable for professional quantitative analysts, and as a resource for postgraduates and researchers in financial mathematics Features chapters from many leading researchers and practitioners
Author: Frederik Ahlemann
Publisher: Springer Nature
ISBN: 3030867978
Category : Computers
Languages : en
Pages : 786
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Book Description
This book presents the current state of research in information systems and digital transformation. Due to the global trend of digitalization and the impact of the Covid 19 pandemic, the need for innovative, high-quality research on information systems is higher than ever. In this context, the book covers a wide range of topics, such as digital innovation, business analytics, artificial intelligence, and IT strategy, which affect companies, individuals, and societies. This volume gathers the revised and peer-reviewed papers on the topic "Technology" presented at the International Conference on Information Systems, held at the University of Duisburg-Essen in 2021.
Author: Graham Elliott
Publisher: Elsevier
ISBN: 0444627405
Category : Business & Economics
Languages : en
Pages : 667
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Book Description
The highly prized ability to make financial plans with some certainty about the future comes from the core fields of economics. In recent years the availability of more data, analytical tools of greater precision, and ex post studies of business decisions have increased demand for information about economic forecasting. Volumes 2A and 2B, which follows Nobel laureate Clive Granger's Volume 1 (2006), concentrate on two major subjects. Volume 2A covers innovations in methodologies, specifically macroforecasting and forecasting financial variables. Volume 2B investigates commercial applications, with sections on forecasters' objectives and methodologies. Experts provide surveys of a large range of literature scattered across applied and theoretical statistics journals as well as econometrics and empirical economics journals. The Handbook of Economic Forecasting Volumes 2A and 2B provide a unique compilation of chapters giving a coherent overview of forecasting theory and applications in one place and with up-to-date accounts of all major conceptual issues. - Focuses on innovation in economic forecasting via industry applications - Presents coherent summaries of subjects in economic forecasting that stretch from methodologies to applications - Makes details about economic forecasting accessible to scholars in fields outside economics
Author: Chung-Chi Chen
Publisher: Springer Nature
ISBN: 9811628815
Category : Application software
Languages : en
Pages : 102
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Book Description
Opinion mining is a prevalent research issue in many domains. In the financial domain, however, it is still in the early stages. Most of the researches on this topic only focus on the coarse-grained market sentiment analysis, i.e., 2-way classification for bullish/bearish. Thanks to the recent financial technology (FinTech) development, some interdisciplinary researchers start to involve in the in-depth analysis of investors' opinions. These works indicate the trend toward fine-grained opinion mining in the financial domain. When expressing opinions in finance, terms like bullish/bearish often spring to mind. However, the market sentiment of the financial instrument is just one type of opinion in the financial industry. Like other industries such as manufacturing and textiles, the financial industry also has a large number of products. Financial services are also a major business for many financial companies, especially in the context of the recent FinTech trend. For instance, many commercial banks focus on loans and credit cards. Although there are a variety of issues that could be explored in the financial domain, most researchers in the AI and NLP communities only focus on the market sentiment of the stock or foreign exchange. This open access book addresses several research issues that can broaden the research topics in the AI community. It also provides an overview of the status quo in fine-grained financial opinion mining to offer insights into the futures goals. For a better understanding of the past and the current research, it also discusses the components of financial opinions one-by-one with the related works and highlights some possible research avenues, providing a research agenda with both micro- and macro-views toward financial opinions.
