خرید و دانلود نسخه کامل کتاب Applications of computational intelligence in data-driven trading – Original PDF

Two decades of participation in the digital transformation of the trading industry as a system architect, quant, and trader, coupled with the experience of teaching in the Financial-Mathematics program at the University of Chicago, provided me with a unique perspective that I will convey to the reader throughout this book. As both a practitioner and an educator, I wrote this book to assert the fact that the trading indus- try was, and continues to be, a very fertile ground for the adoption of cutting-edge technologies. The central message of this book is that the development of problem-solving skills is much more important for the career advancement of a quantitative practitioner than the accretion and mastering of an ever-increasing set of new tools that are flooding both the technical literature and the higher education curricula. While the majority of these tools become obsolete soon after their release into the public domain, acquir- ing an adequate level of problem-solving expertise will endow the learner with a long-lasting know-how that will transcend ephemeral paradigms and cultural trends. If the use of an exhaustive tool set is providing the solution architect with hori- zontal scalability, mastering the expertise of what tools should be used for any given problem will grant the user with the vertical scalability that is absolutely necessary for implementing intelligent solutions. While the majority of books about the appli- cation of machine intelligence to practical problem domains are focused on how to use tools and techniques, this book is built around six different types of problems that are relevant for the quantitative trading practitioner. The tools and techniques used to solve these problem types are described here in the context of the case studies presented, and not the other way around.