Dynamic use of survey data and high frequency model forecasting, a,
Автор: Hautsch, Nikolaus Название: Econometrics of Financial High-Frequency Data ISBN: 3642219241 ISBN-13(EAN): 9783642219245 Издательство: Springer Рейтинг: Цена: 25853.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The availability of financial data recorded on high-frequency level has inspired a research area which over the last decade emerged to a major area in econometrics and statistics. The growing popularity of high-frequency econometrics is driven by technological progress in trading systems and an increasing importance of intraday trading, liquidity risk, optimal order placement as well as high-frequency volatility. This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models. It discusses implementation details, provides insights into properties of high-frequency data as well as institutional settings and presents applications to volatility and liquidity estimation, order book modelling and market microstructure analysis.
Автор: Franses Название: Expert Adjustments of Model Forecasts ISBN: 1107081599 ISBN-13(EAN): 9781107081598 Издательство: Cambridge Academ Рейтинг: Цена: 8078.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Written for academics and practitioners with an interest in forecasting methodology, this book tests the notion that many forecasters feel they can improve the accuracy of forecasts based on their intuition. Current research is collated to examine `expert adjustment` from an econometric perspective and guidelines for improvement are suggested.
Автор: Degiannakis Stavros Название: Modelling and Forecasting High Frequency Financial Data ISBN: 1137396482 ISBN-13(EAN): 9781137396488 Издательство: Springer Рейтинг: Цена: 11179.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is an accessible practitioners guide to the most cutting-edge models used in high-frequency finance modelling, providing advanced techniques and tools for understanding market microstructure and more generally for analyzing financial markets using recent HF data.
Описание: Non-extensive Entropy Econometrics for Low Frequency Series provides a new and robust power-law-based, non-extensive entropy econometrics approach to the economic modelling of ill-behaved inverse problems.
Автор: Nikolaus Hautsch Название: Econometrics of Financial High-Frequency Data ISBN: 3642427723 ISBN-13(EAN): 9783642427725 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides a state-of-the art overview on the major approaches in high-frequency econometrics, including univariate and multivariate autoregressive conditional mean approaches for different types of high-frequency variables, intensity-based approaches for financial point processes and dynamic factor models.
Автор: Hallin M., Lippi M., Barigozzi M., Forni M., Zaffaroni P. Название: Time Series in High Dimensions: The General Dynamic Factor Model ISBN: 9813278005 ISBN-13(EAN): 9789813278004 Издательство: World Scientific Publishing Рейтинг: Цена: 33264.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Factor models have become the most successful tool in the analysis and forecasting of high-dimensional time series. This monograph provides an extensive account of the so-called General Dynamic Factor Model methods. The topics covered include: asymptotic representation problems, estimation, forecasting, identification of the number of factors, identification of structural shocks, volatility analysis, and applications to macroeconomic and financial data.
Автор: Nicolas Vandeput Название: Data Science for Supply Chain Forecasting ISBN: 3110671107 ISBN-13(EAN): 9783110671100 Издательство: Walter de Gruyter Рейтинг: Цена: 8359.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Using data science in order to solve a problem requires a scientific mindset more than coding skills. Data Science for Supply Chain Forecasting, Second Edition contends that a true scientific method which includes experimentation, observation, and constant questioning must be applied to supply chains to achieve excellence in demand forecasting.
This second edition adds more than 45 percent extra content with four new chapters including an introduction to neural networks and the forecast value added framework. Part I focuses on statistical traditional models, Part II, on machine learning, and the all-new Part III discusses demand forecasting process management. The various chapters focus on both forecast models and new concepts such as metrics, underfitting, overfitting, outliers, feature optimization, and external demand drivers. The book is replete with do-it-yourself sections with implementations provided in Python (and Excel for the statistical models) to show the readers how to apply these models themselves.
This hands-on book, covering the entire range of forecasting--from the basics all the way to leading-edge models--will benefit supply chain practitioners, forecasters, and analysts looking to go the extra mile with demand forecasting.
Check out the webinar on the book, which discusses the general issues and challenges of demand forecasting. The panelists have extensive professional experience in this area, providing insights into best practices (process, models) and discussing how data science and machine learning impact those forecasts: https: //www.youtube.com/watch?v=1rXjXcabW2s&t=2s
Автор: Peter Fuleky Название: Macroeconomic Forecasting in the Era of Big Data ISBN: 303031149X ISBN-13(EAN): 9783030311490 Издательство: Springer Рейтинг: Цена: 34937.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book surveys big data tools used in macroeconomic forecasting and addresses related econometric issues, including how to capture dynamic relationships among variables; Accordingly, the book offers a valuable resource for researchers, professional forecasters, and students of quantitative economics.
Автор: Clarke, Bertrand S. (university Of Nebraska, Lincoln) Clarke, Jennifer L. (university Of Nebraska, Lincoln) Название: Predictive statistics ISBN: 1107028280 ISBN-13(EAN): 9781107028289 Издательство: Cambridge Academ Рейтинг: Цена: 12514.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Aimed at statisticians and machine learners, this retooling of statistical theory asserts that high-quality prediction should be the guiding principle of modeling and learning from data, then shows how. The fully predictive approach to statistical problems outlined embraces traditional subfields and `black box` settings, with computed examples.
Автор: Abdol S. Soofi; Liangyue Cao Название: Modelling and Forecasting Financial Data ISBN: 1461353106 ISBN-13(EAN): 9781461353102 Издательство: Springer Рейтинг: Цена: 41925.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Modelling and Forecasting Financial Data brings together a coherent and accessible set of chapters on recent research results on this topic.
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