Econometrics for financial applications / Ly H. Anh, Le Si Dong, Vladik Kreinovich, Nguyen Ngoc Thach, editors.
2018
HB139
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Details
Title
Econometrics for financial applications / Ly H. Anh, Le Si Dong, Vladik Kreinovich, Nguyen Ngoc Thach, editors.
ISBN
9783319731506 (electronic book)
3319731505 (electronic book)
9783319731490
3319731505 (electronic book)
9783319731490
Published
Cham, Switzerland : Springer, 2018.
Language
English
Description
1 online resource (xiii, 1081 pages) : illustrations.
Other Standard Identifiers
10.1007/978-3-319-73150-6 doi
Call Number
HB139
Dewey Decimal Classification
330.01/5195
Summary
This book addresses both theoretical developments in and practical applications of econometric techniques to finance-related problems. It includes selected edited outcomes of the International Econometric Conference of Vietnam (ECONVN2018), held at Banking University, Ho Chi Minh City, Vietnam on January 15-16, 2018. Econometrics is a branch of economics that uses mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. An extremely important part of economics is finances: a financial crisis can bring the whole economy to a standstill and, vice versa, a smart financial policy can dramatically boost economic development. It is therefore crucial to be able to apply mathematical techniques of econometrics to financial problems. Such applications are a growing field, with many interesting results ? and an even larger number of challenges and open problems.
Note
Includes author index.
Access Note
Access limited to authorized users.
Source of Description
Online resource; title from PDF title page (SpringerLink, viewed January 5, 2018).
Added Author
Anh, Ly H. editor.
Dong, Le Si, editor.
Kreinovich, Vladik, editor.
Thach, Nguyen Ngoc, editor.
Dong, Le Si, editor.
Kreinovich, Vladik, editor.
Thach, Nguyen Ngoc, editor.
Series
Studies in computational intelligence ; v. 760.
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Table of Contents
Testing, Prediction, and Cause in Econometric Models
Information Criteria for Statistical Modeling in Data-Rich Era
An invitation to quantum econometrics
GL+ and GL- Regressions
What If We Do Not Know Correlations?
Markowitz Portfolio Theory Helps Decrease Medicines' Side Effect and Speed Up Machine Learning.
Information Criteria for Statistical Modeling in Data-Rich Era
An invitation to quantum econometrics
GL+ and GL- Regressions
What If We Do Not Know Correlations?
Markowitz Portfolio Theory Helps Decrease Medicines' Side Effect and Speed Up Machine Learning.