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From the Financial Times's global finance correspondent, the incredible true story of the iconoclastic geeks who defied conventional wisdom and endured Wall Street's scorn to launch the index fund revolution, democratizing investing and saving hundreds of billions of dollars in fees that would have otherwise lined fat cats' pockets. Fifty years ago, the Manhattan Project of money management was quietly assembled in the financial industry's backwaters, unified by the heretical idea that even many of the world's finest investors couldn't beat the market in the long run. The motley crew of nerds—including economist wunderkind Gene Fama, humiliated industry executive Jack Bogle, bull-headed and computer-obsessive John McQuown, and avuncular former WWII submariner Nate Most—succeeded beyond their wildest dreams. Passive investing now accounts for more than $20 trillion, equal to the entire gross domestic product of the US, and is today a force reshaping markets, finance and even capitalism itself in myriad subtle but pivotal ways. Yet even some fans of index funds and ETFs are growing perturbed that their swelling heft is destabilizing markets, wrecking the investment industry and leading to an unwelcome concentration of power in fewer and fewer hands. In Trillions, Financial Times journalist Robin Wigglesworth unveils the vivid secret history of an invention Wall Street wishes was never created, bringing to life the characters behind its birth, growth, and evolution into a world-conquering phenomenon. This engrossing narrative is essential reading for anyone who wants to understand modern finance—and one of the most pressing financial uncertainties of our time.
From bestselling author Glen Arnold, this is a jargon-busting book that describes how financial markets work, where they are located and how they impact on everyday life. It assumes no specialised prior knowledge of finance theory and provides an authoritative and comprehensive run-down of the workings of the modern financial system. Using real world examples from media such as the Financial Times, Arnold gives an international perspective on the financial markets with frequent comparisons in the workings of major financial centres such as the Bank of England and the City, the Federal Reserve System and Wall Street, the Japanese Central Bank, the European Central Bank and IMF and World Bank. The full text downloaded to your computer With eBooks you can: search for key concepts, words and phrases make highlights and notes as you study share your notes with friends eBooks are downloaded to your computer and accessible either offline through the Bookshelf (available as a free download), available online and also via the iPad and Android apps. Upon purchase, you'll gain instant access to this eBook. Time limit The eBooks products do not have an expiry date. You will continue to access your digital ebook products whilst you have your Bookshelf installed.
This Dictionary consists of some 100,000 terms in both Spanish and English, drawn from the whole range of business, finance and banking terminology. Over 45 subject areas are covered, compiled by a team of international terminologists
Originally published in 1996, The International Guide to Securities Market Indices provides a comprehensive overview of the securities market indices and offers assistance to professionals as well as individual investors in the selection of an appropriate securities market index, on a worldwide basis. The Guide’s identifies and catalogues available performance indicators along with their publishers and describes their relevant characteristics and a perspective on their historical price and total return performance. It also contains descriptive profiles along with historical performance data on 400 of the world’s leading global, regional and local securities market indices and sub-indices covering 10 asset classes.
This book brings together real-world cases illustrating how to analyse volatile financial time series in order to provide a better understanding of their past behavior and robust forecasting of their future behavioural patterns. Using time series data from diverse financial sectors, it shows how the concepts and techniques of statistical analysis, machine learning, and deep learning are applied to build robust predictive models, as well as the ways in which these models can be used for forecasting the future prices of stocks and constructing profitable portfolios of investments. All the concepts and methods used in the book have been implemented using Python and R languages on TensorFlow and Keras frameworks. The volume will be particularly useful for advanced postgraduate and doctoral students of finance, economics, econometrics, statistics, data science, computer science, and information technology.