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  • Conference proceedings
  • © 2018

Predictive Econometrics and Big Data

  • Presents recent research on Predictive Econometrics and Big Data

  • Introduces readers to the theoretical foundations and applications

  • Written by respected experts in the field

  • Includes edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018

Part of the book series: Studies in Computational Intelligence (SCI, volume 753)

Conference series link(s): TES: International Conference of the Thailand Econometrics Society

Conference proceedings info: TES 2018.

Buying options

eBook USD 259.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-70942-0
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 329.99
Price excludes VAT (USA)
Hardcover Book USD 499.99
Price excludes VAT (USA)

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Table of contents (55 papers)

  1. Front Matter

    Pages i-xii
  2. Keynote Address

    1. Front Matter

      Pages 1-1
    2. Data in the 21st Century

      • Chaitanya Baru
      Pages 3-17
  3. Fundamental Theory

    1. Front Matter

      Pages 19-19
    2. Model-Assisted Survey Estimation with Imperfectly Matched Auxiliary Data

      • F. Jay Breidt, Jean D. Opsomer, Chien-Min Huang
      Pages 21-35
    3. COBra: Copula-Based Portfolio Optimization

      • Marc S. Paolella, Paweł Polak
      Pages 36-77
    4. Bayesian Forecasting for Tail Risk

      • Cathy W. S. Chen, Yu-Wen Sun
      Pages 122-145
    5. Kuznets Curve: A Simple Dynamical System-Based Explanation

      • Thongchai Dumrongpokaphan, Vladik Kreinovich
      Pages 177-181
    6. A Calibration-Based Method in Computing Bayesian Posterior Distributions with Applications in Stock Market

      • Dung Tien Nguyen, Son P. Nguyen, Uyen H. Pham, Thien Dinh Nguyen
      Pages 182-191
    7. How to Gauge Accuracy of Processing Big Data: Teaching Machine Learning Techniques to Gauge Their Own Accuracy

      • Vladik Kreinovich, Thongchai Dumrongpokaphan, Hung T. Nguyen, Olga Kosheleva
      Pages 198-204
    8. How Better Are Predictive Models: Analysis on the Practically Important Example of Robust Interval Uncertainty

      • Vladik Kreinovich, Hung T. Nguyen, Songsak Sriboonchitta, Olga Kosheleva
      Pages 205-213
    9. Quantitative Justification for the Gravity Model in Economics

      • Vladik Kreinovich, Songsak Sriboonchitta
      Pages 214-221
    10. The Decomposition of Quadratic Forms Under Skew Normal Settings

      • Ziwei Ma, Weizhong Tian, Baokun Li, Tonghui Wang
      Pages 222-232
    11. Joint Plausibility Regions for Parameters of Skew Normal Family

      • Ziwei Ma, Xiaonan Zhu, Tonghui Wang, Kittawit Autchariyapanitkul
      Pages 233-245

Other Volumes

  1. Predictive Econometrics and Big Data

About this book

This book presents recent research on predictive econometrics and big data. Gathering edited papers presented at the 11th International Conference of the Thailand Econometric Society (TES2018), held in Chiang Mai, Thailand, on January 10-12, 2018, its main focus is on predictive techniques – which directly aim at predicting economic phenomena; and big data techniques – which enable us to handle the enormous amounts of data generated by modern computers in a reasonable time. The book also discusses the applications of more traditional statistical techniques to econometric problems.

Econometrics is a branch of economics that employs mathematical (especially statistical) methods to analyze economic systems, to forecast economic and financial dynamics, and to develop strategies for achieving desirable economic performance. It is therefore important to develop data processing techniques that explicitly focus on prediction. The more data we have, the better our predictions will be. As such, these techniques are essential to our ability to process huge amounts of available data.

Keywords

  • Computational Intelligence
  • Econometrics
  • Precitive Econometrics
  • Big Data
  • Models of Economic Phenomena
  • TES 2018

Editors and Affiliations

  • Computer Science Department, University of Texas at El Paso, El Paso, USA

    Vladik Kreinovich

  • International College, Chiang Mai University, Chiang Mai, Thailand

    Songsak Sriboonchitta, Nopasit Chakpitak

Bibliographic Information

Buying options

eBook USD 259.00
Price excludes VAT (USA)
  • ISBN: 978-3-319-70942-0
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book USD 329.99
Price excludes VAT (USA)
Hardcover Book USD 499.99
Price excludes VAT (USA)