The Science of Algorithmic Trading and Portfolio Management
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Trading systems expert Robert Pardo is back, and in TheEvaluation and Optimization of Trading Strategies, a thoroughlyrevised and updated edition of his classic text Design, Testing,and Optimization of Trading Systems, he reveals how he hasperfected the programming and testing of trading systems using asuccessful battery of his own time-proven techniques.
With thisbook, Pardo delivers important information to readers, from thedesign of workable trading strategies to measuring issues likeprofit and risk.
Written in a straightforward and accessible style,this detailed guide presents traders with a way to develop andverify their trading strategy no matter what form they arecurrently using—stochastics, moving averages, chart patterns,RSI, or breakout methods. Whether a trader is seeking to enhancetheir profit or just getting started in testing, The Evaluationand Optimization of Trading Strategies offers practicalinstruction and expert advice on the development, evaluation, andapplication of winning mechanical trading systems.
Optimal Sports Math, Statistics, and Fantasy also illustrates modeling techniques that can be used to decode and demystify the mysterious computer ranking schemes that are often employed by post-season tournament selection committees in college and professional sports. These methods offer readers a verifiable and unbiased approach to evaluate and rank teams, and the proper statistical procedures to test and evaluate the accuracy of different models.
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Optimal Sports Math, Statistics, and Fantasy delivers a proven best-in-class quantitative modeling framework with numerous applications throughout the sports world. Account Options Sign in. The Science of Algorithmic Trading and Portfolio Management , with its emphasis on algorithmic trading processes and current trading models, sits apart from others of its kind.
Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into ways to develop, test, and build trading algorithms. Readers learn how to evaluate market impact models and assess performance across algorithms, traders, and brokers, and acquire the knowledge to implement electronic trading systems.
Prepares readers to evaluate market impact models and assess performance across algorithms, traders, and brokers. Helps readers design systems to manage algorithmic risk and dark pool uncertainty. Summarizes an algorithmic decision making framework to ensure consistency between investment objectives and trading objectives. Flowing text, Original pages. Web, Tablet, Phone, eReader.
EconPapers: The Science of Algorithmic Trading and Portfolio Management
It syncs automatically with your account and allows you to read online or offline wherever you are. Please follow the detailed Help center instructions to transfer the files to supported eReaders. Multi-Asset Risk Modeling describes, in a single volume, the latest and most advanced risk modeling techniques for equities, debt, fixed income, futures and derivatives, commodities, and foreign exchange, as well as advanced algorithmic and electronic risk management.
Beginning with the fundamentals of risk mathematics and quantitative risk analysis, the book moves on to discuss the laws in standard models that contributed to the financial crisis and talks about current and future banking regulation. During his college years, Dr.
It was during this time as a student athlete where he began applying math and statistics to sports modeling problems. Thus, making this book the byproduct of decades of successful research. Kissell has a Ph.
Brian Peterson rated it really liked it Nov 02, Document, Internet resource Document Type: Portfolio management topics, including quant factors and black box models, are discussed, and an accompanying website includes examples, data sets supplementing exercises in the book, and large projects. Please re-enter recipient e-mail address es. Alexandr Dainov marked it as to-read Mar 11,
Robert Kissell, the first author to discuss algorithmic trading across the various asset classes, provides key insights into Access Online via Elsevier Bolero Ozon. C marked it as to-read Jun 26, David Litner is currently reading it Jul 19, Hayden marked it as to-read Aug 03, Megustalibros marked it as to-read Nov 20, Bill marked it as to-read Dec 29, Valters Bondars marked it as to-read Jan 10, Jorge Lopez added it Jan 27, Alexandr Dainov marked it as to-read Mar 11, Kevin marked it as to-read Apr 28, Maksym marked it as to-read Oct 04, Steve Cao marked it as to-read Jan 19, Arturo marked it as to-read Feb 08, Jon added it Mar 04, Yich marked it as to-read Jun 09, Jackson Bi marked it as to-read Jun 28, Aryeh Newman marked it as to-read Jul 07, Jan-Christian Gerlach marked it as to-read Sep 05, Jobber added it Sep 19, Brett Quada marked it as to-read Feb 21, Milan marked it as to-read Feb 22, Daniel marked it as to-read Mar 12,