Kulkarni sanjeev (18 Ergebnisse)

Hardcover. Zustand: Very Good. 1. With dust jacket. 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: Very Good. 1st Edition. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

Zustand: New. In English.

Paperback. Zustand: Brand New. 120 pages. 7.50x5.10x0.50 inches. In Stock.

Hardback. Zustand: Good. The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available.

Zustand: Very Good. Pages intact with possible writing/highlighting. Binding strong with minor wear. Dust jackets/supplements may not be included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.

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

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

Zustand: New. pp. 448.

Zustand: New. pp. 232.

Zustand: New. In English.

Zustand: New. In English.

Hardcover. Zustand: Brand New. 1st edition. 320 pages. 9.75x7.00x1.00 inches. In Stock.

Zustand: New. The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available.KlappentextThe modern financial industry has been required to deal with .

Zustand: New. The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Editor(s): Akansu, Ali N.; Kulkarni, Sanjeev R.; Malioutov, Dmitry M.; Pollak, Ilya. Series: Wiley - IEEE. Num Pages: 320 pages, illustrations. BIC Classification: TJK; UYQM; UYS. Category: (P) Professional & Vocational. Dimension: 178 x 251 x 19. Weight in Grams: 626. . 2016. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland.…

Hardcover. Zustand: Brand New. 1st edition. 232 pages. 9.50x6.25x0.50 inches. In Stock.

Buch. Zustand: Neu. Neuware - The modern financial industry has been required to deal with large and diverse portfolios in a variety of asset classes often with limited market data available. Financial Signal Processing and Machine Learning unifies a number of recent advances made in signal processing and machine learning for the design and management of investment portfolios and financial engineering. This book bridges the gap between these disciplines, offering the latest information on key topics including characterizing statistical dependence and correlation in high dimensions, constructing effective and robust risk measures, and their use in portfolio optimization and rebalancing. The book focuses on signal processing approaches to model return, momentum, and mean reversion, addressing theoretical and implementation aspects. It highlights the connections between portfolio theory, sparse learning and compressed sensing, sparse eigen-portfolios, robust optimization, non-Gaussian data-driven risk measures, graphical models, causal analysis through temporal-causal modeling, and large-scale copula-based approaches. Key features: - Highlights signal processing and machine learning as key approaches to quantitative finance. - Offers advanced mathematical tools for high-dimensional portfolio construction, monitoring, and post-trade analysis problems. - Presents portfolio theory, sparse learning and compressed sensing, sparsity methods for investment portfolios. including eigen-portfolios, model return, momentum, mean reversion and non-Gaussian data-driven risk measures with real-world applications of these techniques. - Includes contributions from leading researchers and practitioners in both the signal and information processing communities, and the quantitative finance community.…

Zustand: New. * Serves as a fundamental introduction to statistical learning theory and its role in understanding human learning and inductive reasoning. * Topics of coverage include: probability, pattern recognition, optimal Bayes decision rule, nearest neighbor rule, kernel rules, neural networks, and support vector machines. Series: Wiley Series in Probability and Statistics. Num Pages: 232 pages, Illustrations. BIC Classification: PBT; UYQM. Category: (P) Professional & Vocational. Dimension: 237 x 162 x 17. Weight in Grams: 496. . 2011. 1st Edition. Hardcover. . . . . Books ship from the US and Ireland. …