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Machine Learning in Finance
This book introduces machine learning methods in finance. It presents a unified treatment of machine learning and various statistical and computational disciplines in quantitative finance, such as financial econometrics and discrete time stochastic control, with an emphasis on how theory and hypothesis tests inform the choice of algorithm for financial data modeling and decision making. With the trend towards increasing computational resources and larger datasets, machine learning has grown into an important skillset for the finance industry. This book is written for advanced graduate students and academics in financial econometrics, mathematical finance and applied statistics, in addition t...
Computers and Education
This book contains a selection of contributions presenting the latest research in the field of computers in education and, more specifically, in e-Learning. It reflects the diverse scenario of the application of computers in the educational field by describing previous experiences and addressing some of the present key issues. These include issues such as Learning Management Systems as well as innovative aspects such as personalized or ubiquitous learning.
Machine Learning for Asset Managers
Successful investment strategies are specific implementations of general theories. An investment strategy that lacks a theoretical justification is likely to be false. Hence, an asset manager should concentrate her efforts on developing a theory rather than on backtesting potential trading rules. The purpose of this Element is to introduce machine learning (ML) tools that can help asset managers discover economic and financial theories. ML is not a black box, and it does not necessarily overfit. ML tools complement rather than replace the classical statistical methods. Some of ML's strengths include (1) a focus on out-of-sample predictability over variance adjudication; (2) the use of computational methods to avoid relying on (potentially unrealistic) assumptions; (3) the ability to "learn" complex specifications, including nonlinear, hierarchical, and noncontinuous interaction effects in a high-dimensional space; and (4) the ability to disentangle the variable search from the specification search, robust to multicollinearity and other substitution effects.
Machine Learning for Financial Engineering
Preface v 1 On the History of the Growth-Optimal Portfolio M.M. Christensen 1 2 Empirical Log-Optimal Portfolio Selections: A Survey L. Györfi Gy. Ottucsáak A. Urbán 81 3 Log-Optimal Portfolio-Selection Strategies with Proportional Transaction Costs L. Györfi H. Walk 119 4 Growth-Optimal Portfoho Selection with Short Selling and Leverage M. Horváth A. Urbán 153 5 Nonparametric Sequential Prediction of Stationary Time Series L. Györfi Gy. Ottucsák 179 6 Empirical Pricing American Put Options L. Györfi A. Telcs 227 Index 249.
The Girls Next Door
To boost soldiers’ morale and remind them of the stakes of victory, the American military formalized a recreation program that sent respectable young women, along with famous entertainers, overseas. This history of the women who talked and listened, danced and sang, adds an intimate chapter to the story of war and its ties to life in peacetime.
Bayesian Reasoning and Machine Learning
A practical introduction perfect for final-year undergraduate and graduate students without a solid background in linear algebra and calculus.
Big Data Science in Finance
Explains the mathematics, theory, and methods of Big Data as applied to finance and investing Data science has fundamentally changed Wall Street—applied mathematics and software code are increasingly driving finance and investment-decision tools. Big Data Science in Finance examines the mathematics, theory, and practical use of the revolutionary techniques that are transforming the industry. Designed for mathematically-advanced students and discerning financial practitioners alike, this energizing book presents new, cutting-edge content based on world-class research taught in the leading Financial Mathematics and Engineering programs in the world. Marco Avellaneda, a leader in quantitative...
Introduction To Islamic Finance
The objective of organizing economic activities in any nation is the production of products and services to satisfy human wants. In the modern era, however, where division of labor and specialization are on the rise, those who produce products and services are not typically the same as those who consume or use them. Consequently, it is necessary to substitute one commodity for another. Barter required a 'double coincidence of desires'; B needed to possess both what A desired and what A could offer in exchange. This arrangement restricted the types of transactions that could be conducted, occupied additional time that could have been spent on production, and impeded the specialization of production. The limitations that the barter system placed on human ambitions lead to the evolution of money.
The Effortless Experience
A new breakthrough idea about how to win customer loyalty from Matthew Dixon, the bestselling author of The Challenger Sale Everyone knows that the best way to create customer loyalty is with service so good, so over the top, that it surprises and delights. But what if everyone is wrong? In their acclaimed bestseller The Challenger Sale, Matthew Dixon and his colleagues at CEB busted longstanding myths about sales. Now they've turned to a new vital business subject - customer loyalty - with a book that turns conventional wisdom on its head. Companies devote untold time and resources trying to dazzle customers. Yet CEB's careful research proves that is wildly overrated: loyalty has a lot more...
