This book offers an overview of state-of-the-art econometric techniques, with a special emphasis on financial econometrics. There is a major need for such techniques, since the traditional way of designing mathematical models – based on researchers’ insights – can no longer keep pace with the ever-increasing data flow. To catch up, many application areas have begun relying on data science, i.e., on techniques for extracting models from data, such as data mining, machine learning, and innovative statistics. In terms of capitalizing on data science, many application areas are way ahead of economics. To close this gap, the book provides examples of how data science techniques can be used in economics. Corresponding techniques range from almost traditional statistics to promising novel ideas such as quantum econometrics. Given its scope, the book will appeal to students and researchers interested in state-of-the-art developments, and to practitioners interested in using data science techniques.  
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To catch up, many application areas have begun relying on data science, i.e., on techniques for extracting models from data, such as data mining, machine learning, and innovative statistics.
A Theory-based Lasso for Time-Series Data.- Invariance-Based Explanation.- Composition of Quantum Operations and Their Fixed Points.- Information quality: the contribution of fuzzy methods.- Parameter-Centric Analysis Grossly Exaggerates Certainty.- Three Approaches to the Comparison of Random Variables.- A QP framework: a contextual representation of agents' preferences in investment choice.- How to Make a Decision Based on the Minimum Bayes Factor (MBF): Explanation of the Jeffreys Scale.- Extending the A Priori Procedure (APP) to Address Correlation Coefficients.- Variable Selection and Estimation in Kink Regression Model.- Performance of microfinance institutions in Vietnam.- Factors Influencing on University Reputation in Viet Nam: Model Selection by AIC.- Impacts of Internal and External Macro Factors on Firm Stock Price in an Expansion Econometric Model – A Case in Vietnam Real Estate Industry.- How Values Influence Economic Progress? An Evidence from South And Southeast Asian Countries.- The Effect of Governance Characteristics on Firm Performance: Evidence from Vietnam.- Does Capital Affect Bank Risk in Vietnam: A Bayesian Approach.
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This book offers an overview of state-of-the-art econometric techniques, with a special emphasis on financial econometrics. There is a major need for such techniques, since the traditional way of designing mathematical models – based on researchers’ insights – can no longer keep pace with the ever-increasing data flow. To catch up, many application areas have begun relying on data science, i.e., on techniques for extracting models from data, such as data mining, machine learning, and innovative statistics. In terms of capitalizing on data science, many application areas are way ahead of economics. To close this gap, the book provides examples of how data science techniques can be used in economics. Corresponding techniques range from almost traditional statistics to promising novel ideas such as quantum econometrics. Given its scope, the book will appeal to students and researchers interested in state-of-the-art developments, and to practitioners interested in using data science techniques.  
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Presents recent findings and ideas on applying data science techniques to economic phenomena – and, in particular, financial phenomena Inspires practitioners to learn how to apply various data science techniques to economic problems and encourages researchers to further improve the existing techniques and to come up with new data science-based techniques for economics Written by respected experts in the field
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Produktdetaljer

ISBN
9783030488550
Publisert
2021-11-14
Utgiver
Vendor
Springer Nature Switzerland AG
Høyde
235 mm
Bredde
155 mm
Aldersnivå
Research, P, 06
Språk
Product language
Engelsk
Format
Product format
Heftet