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Zustand: New. In English.

Hardcover. Zustand: Very Good. 1st ed. 2020. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.

Zustand: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.

PAP. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

Zustand: New. pp. 350.

Zustand: New.

Zustand: New. In English.

Zustand: New. In English.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

HRD. Zustand: New. New Book. Shipped from UK. Established seller since 2000.

paperback. Zustand: Gut. 573 Seiten; 9783030410704.3 Gewicht in Gramm: 1.

Kartoniert / Broschiert. Zustand: New. 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 contr.

Zustand: New. In English.

Zustand: New.

Paperback. Zustand: Brand New. 573 pages. 9.25x6.10x1.17 inches. In Stock.

Hardcover. Zustand: Brand New. 548 pages. 9.50x6.50x1.25 inches. In Stock.

Hardcover. Zustand: Brand New. 300 pages. 6.24x0.85x9.24 inches. In Stock.

Zustand: New. Introduces fundamental concepts in machine learning for canonical modeling and decision frameworks in financePresents a unified treatment of machine learning, financial econometrics and discrete time stochastic control problems in financeChapters.

Buch. Zustand: Neu. Neuware - Upgrade your programming language to more effectively handle high-frequency data Machine Learning and Big Data with KDB+/Q offers quants, programmers and algorithmic traders a practical entry into the powerful but non-intuitive kdb+ database and q programming language. Ideally designed to handle the speed and volume of high-frequency financial data at sell- and buy-side institutions, these tools have become the de facto standard; this book provides the foundational knowledge practitioners need to work effectively with this rapidly-evolving approach to analytical trading. The discussion follows the natural progression of working strategy development to allow hands-on learning in a familiar sphere, illustrating the contrast of efficiency and capability between the q language and other programming approaches. Rather than an all-encompassing 'bible'-type reference, this book is designed with a focus on real-world practicality to help you quickly get up to speed and become productive with the language. Understand why kdb+/q is the ideal solution for high-frequency data Delve into 'meat' of q programming to solve practical economic problems Perform everyday operations including basic regressions, cointegration, volatility estimation, modelling and more Learn advanced techniques from market impact and microstructure analyses to machine learning techniques including neural networks The kdb+ database and its underlying programming language q offer unprecedented speed and capability. As trading algorithms and financial models grow ever more complex against the markets they seek to predict, they encompass an ever-larger swath of data - more variables, more metrics, more responsiveness and altogether more 'moving parts.' Traditional programming languages are increasingly failing to accommodate the growing speed and volume of data, and lack the necessary flexibility that cutting-edge financial modelling demands. Machine Learning and Big Data with KDB+/Q opens up the technology and flattens the learning curve to help you quickly adopt a more effective set of tools. …

Hardcover. Zustand: Brand New. 548 pages. 9.50x6.50x1.25 inches. In Stock.