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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.
For years, traders and investors have been using unproven assumptions about popular patterns such as breakouts, momentum, new highs, new lows, market breadth, put/call ratios and more without knowing if there is a statistical edge. Common wisdom holds that the stock markets are ever changing. But, as it turns out, common wisdom can be wrong. Offering a comprehensive look back at the way the markets have acted over the last two decades, How Markets Really Work: A Quantitative Guide to Stock Market Behavior, Second Edition shows that nothing has changed, that the markets behave the same way today as they have in years past, and that understanding this puts you in a prime position to profit. Written by two top financial experts and filled with charts and graphs that illustrate the market concepts they develop, the book takes a sometimes contrarian view of everything from market edges to historical volatility, and from volume to put/call ratio, giving you all that you need to truly understand how the markets function. Fully revised and updated, How Markets Really Work, Second Edition takes a level-headed, data-driven look at the markets to show how they function and how you can apply that information intelligently when making investment decisions.
In this book readers will find technological discussions on the existing and emerging technologies across the different stages of the big data value chain. They will learn about legal aspects of big data, the social impact, and about education needs and requirements. And they will discover the business perspective and how big data technology can be exploited to deliver value within different sectors of the economy. The book is structured in four parts: Part I “The Big Data Opportunity” explores the value potential of big data with a particular focus on the European context. It also describes the legal, business and social dimensions that need to be addressed, and briefly introduces the European Commission’s BIG project. Part II “The Big Data Value Chain” details the complete big data lifecycle from a technical point of view, ranging from data acquisition, analysis, curation and storage, to data usage and exploitation. Next, Part III “Usage and Exploitation of Big Data” illustrates the value creation possibilities of big data applications in various sectors, including industry, healthcare, finance, energy, media and public services. Finally, Part IV “A Roadmap for Big Data Research” identifies and prioritizes the cross-sectorial requirements for big data research, and outlines the most urgent and challenging technological, economic, political and societal issues for big data in Europe. This compendium summarizes more than two years of work performed by a leading group of major European research centers and industries in the context of the BIG project. It brings together research findings, forecasts and estimates related to this challenging technological context that is becoming the major axis of the new digitally transformed business environment.
What is macroeconomics and how does it work? What are the practical implications of macroeconomic data? How can you apply this knowledge to improve your investment results? For the first time, a practical and accessible handbook explains the mechanisms of macroeconomics as they apply to financial investments. Within this book you will learn the basics of macroeconomics and how to apply them in managing your investment portfolio. In particular, you will discover: - How to use macroeconomics to make informed investment decisions. - How to find the main sources of global macroeconomic data. - How to identify and manage investment risks. - Concrete case studies showing the practical application of the knowledge acquired in the book. - Tests and food for thought for your own investing activities. - And much more! From global sources of macroeconomic data to long-term investment strategies, risk management and financial market analysis, this book provides the know-how you need to start applying the principles of macroeconomics to investing. Don't waste any more time with useless and expensive theoretical textbooks: with this guide you will have the basic knowledge you need to understand what is happening in the financial markets in a more informed way.
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.
Risk management solutions for today's high-speed investing environment Real-Time Risk is the first book to show regular, institutional, and quantitative investors how to navigate intraday threats and stay on-course. The FinTech revolution has brought massive changes to the way investing is done. Trading happens in microsecond time frames, and while risks are emerging faster and in greater volume than ever before, traditional risk management approaches are too slow to be relevant. This book describes market microstructure and modern risks, and presents a new way of thinking about risk management in today's high-speed world. Accessible, straightforward explanations shed light on little-understood topics, and expert guidance helps investors protect themselves from new threats. The discussion dissects FinTech innovation to highlight the ongoing disruption, and to establish a toolkit of approaches for analyzing flash crashes, aggressive high frequency trading, and other specific aspects of the market. Today's investors face an environment in which computers and infrastructure merge, regulations allow dozens of exchanges to coexist, and globalized business facilitates round-the-clock deals. This book shows you how to navigate today's investing environment safely and profitably, with the latest in risk-management thinking. Discover risk management that works within micro-second trading Understand the nature and impact of real-time risk, and how to protect yourself Learn why flash crashes happen, and how to mitigate damage in advance Examine the FinTech disruption to established business models and practices When technology collided with investing, the boom created stratospheric amounts of data that allows us to plumb untapped depths and discover solutions that were unimaginable 20 years ago. Real-Time Risk describes these solutions, and provides practical guidance for today's savvy investor.
Expand your enterprise into new regions using systems engineering and data analysis In Data Driven Decisions: Systems Engineering to Understand Corporate Valuation and Intangible Assets, investment banker, systems engineer, and Cornell University lecturer Joshua Michael Jahani delivers an incisive and unique unveiling of how to use the tools of systems engineering to value your organization, its intangible assets, and how to gauge or prepare its readiness for an overseas or cross-border expansion. In the book, you’ll learn to implement a wide range of systems engineering tools, including context diagrams, decision matrices, Goal-Question-Metric analyses, and more. You’ll also discover the following: How to communicate corporate value measurements and their impact to owners, executives, and investors. Explorations of the relevant topics when considering an international expansion, including macroeconomics, joint ventures, market entry, corporate valuations, mergers and acquisitions, and company culture. A comprehensive framework and methodology for examining available global regions in your search for the perfect expansion target. A deep understanding of specific sectors in which intangible assets have a particular impact, including branded consumer products, ad-tech, and healthcare. A must-have resource for business owners, managers, executives, directors, and other corporate leaders, Data-Driven Decisions will also prove invaluable to consultants and other professionals who serve companies considering expansion or growth into new regions.