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Euro Bonds : Markets, Infrastructure and Trends / Marida Bertocchi...[et al]
Singapore : World Scientific Publishing Company, 2014
xxviii, 259 pages. : illustrations ; 24 cm.
Ký hiệu phân loại (DDC): 332.632
Euro Bonds: Markets, Infrastructure and Trends presents the most recent developments in the Euro bond market. It discusses the problems of the Euro countries, the proposed solutions advocated by European as well as international institutions and investors. Particular emphasis is given to systemic risk and contagion as well as to specific innovative instruments such as structured financial products which protect various classes of investors. This self-contained title provides an organized and comprehensive overview of the current financial situation in Europe and accords the reader the opportuni
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Investments / Zvi Bodie, Alex Kane, Alan J. Marcus
New York, NY : McGraw-Hill Education, 2024
1072 pages. : color illustrations ; 26 cm.
Ký hiệu phân loại (DDC): 332.6
The past three decades witnessed rapid and profound change in the investments industry as well as a financial crisis of historic magnitude. The vast expansion of financial markets during this period was due in part to innovations in securitization and credit enhancement that gave birth to new trading strategies. These strategies were in turn made feasible by developments in communication and information technology, as well as by advances in the theory of investments. Yet the financial crisis of 2008-2009 also was rooted in the cracks of these developments. Many of the innovations in security design facilitated high leverage and an exaggerated notion of the efficacy of risk transfer strategies. This engendered complacency about risk that was coupled with relaxation of regulation as well as reduced transparency, masking the precarious condition of many big players in the system. Of necessity, our text has evolved along with financial markets and their influence on world events. 'Investments', Thirteenth Edition, is intended primarily as a textbook for courses in investment analysis. Our guiding principle has been to present the material in a framework that is organized by a central core of consistent fundamental principles. We attempt to strip away unnecessary mathematical and technical detail, and we have concentrated on providing the intuition that may guide students and practitioners as they confront new ideas and challenges in their professional lives. This text will introduce you to major issues currently of concern to all investors. It can give you the skills to assess watershed current issues and debates covered by both the popular media and more-specialized finance journals. Whether you plan to become an investment professional, or simply a sophisticated individual investor, you will find these skills essential, especially in today's rapidly evolving environment
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Python for algorithmic trading : from idea to cloud deployment / Yves J. Hilpisch
Sebastopol, CA : O'Reilly, 2021
379 pages. : illustrations ; cm.
Ký hiệu phân loại (DDC): 332.64
Financial trading, once the exclusive domain of institutional players, is now open to small organizations and individual traders using online platforms. The tool of choice for many traders today is Python and its ecosystem of powerful packages. In this practical book, author Yves Hilpisch shows students, academics, and practitioners how to use Python in the fascinating field of algorithmic trading. You'll learn several ways to apply Python to different aspects of algorithmic trading, such as backtesting trading strategies and interacting with online trading platforms. Some of the biggest buy- and sell-side institutions make heavy use of Python. By exploring options for systematically building and deploying automated algorithmic trading strategies, this book will help you level the playing field. Set up a proper Python environment for algorithmic trading Learn how to retrieve financial data from public and proprietary data sources Explore vectorization for financial analytics with NumPy and pandas Master vectorized backtesting of different algorithmic trading strategies Generate market predictions by using machine learning and deep learning Tackle real-time processing of streaming data with socket programming tools Implement automated algorithmic trading strategies with the OANDA and FXCM platforms
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