Data Driven Investing
Author | : Mitchell R. Hardy |
Publisher | : COGNITION CAPITAL MANAGEMEN |
Total Pages | : 540 |
Release | : 2004 |
Genre | : Business & Economics |
ISBN | : 0975584200 |
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Author | : Mitchell R. Hardy |
Publisher | : COGNITION CAPITAL MANAGEMEN |
Total Pages | : 540 |
Release | : 2004 |
Genre | : Business & Economics |
ISBN | : 0975584200 |
Author | : Matei Zatreanu |
Publisher | : Wiley |
Total Pages | : 0 |
Release | : 2025-04-29 |
Genre | : Business & Economics |
ISBN | : 9781119429630 |
Implement a data-driven investment strategy The investing landscape is increasingly driven by big data and artificial intelligence. For most finance professionals, big data, statistics, and programming are outside their comfort zone. Yet, proficiency in these areas is becoming a prerequisite for successful investing. And while there are plenty of resources on these individual topics, what is missing is a framework for combining these disciplines for investment purposes. Data-Driven Investing shows readers how investment decisions can be made or improved through the use of alternative datasets and inference techniques. The author covers artificial intelligence algorithms, data visualization, and data sourcing to show how these components come together to form a more robust investment strategy. The goal is to help finance professionals prepare for an investing landscape increasingly driven by big data and artificial intelligence. Shows how investing wisdom can be harnessed through science and augmented by data Demonstrates how an augmented investing philosophy promises a deeper understanding of future economic performance Is essential reading for fund managers, research analysts, quantitative investors, data scientists, and general finance professionals Includes a companion website with code, data sets, and videos providing more in-depth information on augmented/data-driven investing This book comes at a time of increasing investor anxiety with lackluster hedge fund performance, which is causing many funds to explore data-driven investing as a possible evolution of their strategies.
Author | : Amal Bhatnagar |
Publisher | : |
Total Pages | : 176 |
Release | : 2021-12-20 |
Genre | : |
ISBN | : 9781637306437 |
Poor data quality costs the United States $3.1 trillion dollars every year. Data Driven: Solving the Biggest Problems in Startup Investing explores how new venture capitalists and data scientists can leverage data to invest in startups more efficiently and successfully. Author Amal Bhatnagar aims to teach you how to make better investment decisions by creating your own data-driven organization. You'll hear stories from industry leaders like: David Coats, the Managing Director at Correlation Ventures, who created the world's most complete and accurate database of US-based venture capital financings Will Bricker, a Principal at the Hustle Fund, who built systems to handle 40 percent of all startup investment opportunities without human intervention Tim Harsch, the Chief Executive Officer of Owler, who created data on 13 million+ companies and the world's second largest business community Jonathan Hsu, Tribe Capital's Co-Founder, who uses data science techniques to handle more than $1.3 billion assets under management. This book is a must-read if you are an aspiring investor who wants to make better startup investment decisions or data scientist who wants to build financial products. Here is the first step on the path to building a data-driven competitive edge and a more successful data-driven leadership.
Author | : Timothy Hayes |
Publisher | : McGraw-Hill Companies |
Total Pages | : 328 |
Release | : 2001 |
Genre | : Business & Economics |
ISBN | : |
The editor of "Investment Strategy" shows how individual investors can access institutional-quality tools, data, and indicators and consistently beat the market. Hayes presents walk-through examples of a wide variety of investment models based on more than 100 years of stock market data and research from Ned Davis Research to achieve top results. 120 illustrations. 60 tables.
Author | : Cris Doloc |
Publisher | : John Wiley & Sons |
Total Pages | : 304 |
Release | : 2019-10-31 |
Genre | : Business & Economics |
ISBN | : 1119550521 |
“Life on earth is filled with many mysteries, but perhaps the most challenging of these is the nature of Intelligence.” – Prof. Terrence J. Sejnowski, Computational Neurobiologist The main objective of this book is to create awareness about both the promises and the formidable challenges that the era of Data-Driven Decision-Making and Machine Learning are confronted with, and especially about how these new developments may influence the future of the financial industry. The subject of Financial Machine Learning has attracted a lot of interest recently, specifically because it represents one of the most challenging problem spaces for the applicability of Machine Learning. The author has used a novel approach to introduce the reader to this topic: The first half of the book is a readable and coherent introduction to two modern topics that are not generally considered together: the data-driven paradigm and Computational Intelligence. The second half of the book illustrates a set of Case Studies that are contemporarily relevant to quantitative trading practitioners who are dealing with problems such as trade execution optimization, price dynamics forecast, portfolio management, market making, derivatives valuation, risk, and compliance. The main purpose of this book is pedagogical in nature, and it is specifically aimed at defining an adequate level of engineering and scientific clarity when it comes to the usage of the term “Artificial Intelligence,” especially as it relates to the financial industry. The message conveyed by this book is one of confidence in the possibilities offered by this new era of Data-Intensive Computation. This message is not grounded on the current hype surrounding the latest technologies, but on a deep analysis of their effectiveness and also on the author’s two decades of professional experience as a technologist, quant and academic.
Author | : Zhamak Dehghani |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 387 |
Release | : 2022-03-08 |
Genre | : Computers |
ISBN | : 1492092363 |
Many enterprises are investing in a next-generation data lake, hoping to democratize data at scale to provide business insights and ultimately make automated intelligent decisions. In this practical book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today's organizations. A distributed data mesh is a better choice. Dehghani guides architects, technical leaders, and decision makers on their journey from monolithic big data architecture to a sociotechnical paradigm that draws from modern distributed architecture. A data mesh considers domains as a first-class concern, applies platform thinking to create self-serve data infrastructure, treats data as a product, and introduces a federated and computational model of data governance. This book shows you why and how. Examine the current data landscape from the perspective of business and organizational needs, environmental challenges, and existing architectures Analyze the landscape's underlying characteristics and failure modes Get a complete introduction to data mesh principles and its constituents Learn how to design a data mesh architecture Move beyond a monolithic data lake to a distributed data mesh.
Author | : Yves Hilpisch |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 720 |
Release | : 2018-12-05 |
Genre | : Computers |
ISBN | : 1492024295 |
The financial industry has recently adopted Python at a tremendous rate, with some of the largest investment banks and hedge funds using it to build core trading and risk management systems. Updated for Python 3, the second edition of this hands-on book helps you get started with the language, guiding developers and quantitative analysts through Python libraries and tools for building financial applications and interactive financial analytics. Using practical examples throughout the book, author Yves Hilpisch also shows you how to develop a full-fledged framework for Monte Carlo simulation-based derivatives and risk analytics, based on a large, realistic case study. Much of the book uses interactive IPython Notebooks.
Author | : Lionel Melka |
Publisher | : John Wiley & Sons |
Total Pages | : 325 |
Release | : 2014-02-03 |
Genre | : Business & Economics |
ISBN | : 1118440013 |
A wave of corporate mergers, acquisitions, restructuring, and similar transactions has created unprecedented opportunities for those versed in contemporary risk arbitrage techniques. At the same time, the nature of the merger wave has lent such transactions a much higher degree of predictability than ever before, making risk arbitrage more attractive to investors. Surprisingly, there is little transparency and instruction for investors interested in learning the latest risk arbitrage techniques. Merger Arbitrage – A Fundamental Approach to Event-Driven Investing helps readers understand the inner workings of the strategy and hedge funds which engaged in this investment strategy. Merger arbitrage is one of the most commonly used strategies but paradoxically one of the least known. This book puts it in the spotlight and explains how fund managers are able to benefit from mergers and acquisitions. It describes how to implement this strategy, located at the crossroad of corporate finance and asset management, and where its risks lie through numerous topical examples. The book is split into three parts. The first part, examining the basis of merger arbitrage, looks at the key role of the market in takeover bids. It also assesses the major changes in the financial markets over recent years and their impact on M&A. Various M&A risk and return factors are also discussed, alongside the historical profitability of merger arbitrage, the different approaches used by fund managers and the results of academic studies on the subject. The second part of the book deals with the risk of an M&A transaction failing in terms of financing risk, competition issues, the legal aspects of merger agreements and administrative and political risks. The third part of the book examines specificities of M&A transactions, comprehensively covering hostile takeovers and leveraged buyouts. Each part contains many recent examples and case studies in order to show how the various theories and notions are put into practice. From researching prospects and determining positions, to hedging and trading tactics, Lionel Melka and Amit Shabi present the full complement of sophisticated risk arbitrage techniques, making Merger Arbitrage a must read for finance and investment professionals who want to take advantage of the nearly limitless opportunities afforded by today’s rapidly changing global business environment. The book builds on its authors’ diverse backgrounds and common experience managing a merger arbitrage fund, providing readers with an enriching inside view on M&A operations. Translated by Andrew Fanko and Frances Thomas
Author | : Rado Kotorov |
Publisher | : Business Expert Press |
Total Pages | : 161 |
Release | : 2020-04-21 |
Genre | : Business & Economics |
ISBN | : 195152781X |
Today the fastest growing companies have no physical assets. Instead, they create innovative digital products and new data-driven business models. They capture huge market share fast and their capitalizations skyrocket. The success of these digital giants is pushing all companies to rethink their business models and to start digitizing their products and services. Whether you are a new start-up building a digital product or service, or an employee of an established company that is transitioning to digital, you need to consider how digitization has transformed every aspect of management. Data-driven business models scale not through asset accumulation and product standardization, but through disaggregation of supply and demand. The winners in the new economy master the demand for one and the supply to millions. Throughout the book the author illustrates with examples and use cases how the market competition has changed and how companies adept to the new rules of the game. The economic levers of scale and scope are also different in the digital economy and companies have to learn new tactics how to achieve and sustain their competitive advantage. While data is at the core of all digital business models, the monetization strategies vary across products, services and business models. Our Monetization Matrix is a model that helps managers, marketers, sales professionals, and technical product designers to align the digital product design with the data-driven business model.
Author | : Henry Kaestner |
Publisher | : Tyndale House Publishers, Inc. |
Total Pages | : 185 |
Release | : 2021-08 |
Genre | : Business & Economics |
ISBN | : 1496457234 |
"I'm excited about Faith Driven Entrepreneur. Anyone who is following the example of their creator God can find echoes of their work in this book." --Lecrae Entrepreneurship can be a lonely journey. But it doesn't need to be. God has a purpose and a plan for all those entrepreneurial dreams and creative gifts he gave you. The work you do today--the company you've built, the employees you work with, the customers you serve, the shareholders you report to, all of it--serves as an active part of what God wants to accomplish on earth. You are not alone in this journey. Join other faith-driven entrepreneurs as, together, we identify the values, habits, and traits that empower us to successfully build businesses, serve our communities, and faithfully pursue a loving relationship with God; read stories that exemplify how those values, habits, and traits unfold in everyday life; and discover the potential God wants to unleash through our work. Each book purchase includes access to the eight-session Faith Driven Entrepreneur video series, a discussion guide to encourage conversation among peers, and an invitation to join a Faith Driven Entrepreneur Group to meet other like-minded entrepreneurs.