Financial Data Analytics

Theory and Application

Buch | Softcover

XXII, 384 Seiten

2023 | 1st ed. 2022
Springer International Publishing (Verlag)
978-3-030-83801-0 (ISBN)

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This book presents both theory of financial data analytics, as well as comprehensive insights into the application of financial data analytics techniques in real financial world situations. It offers solutions on how to logically analyze the enormous amount of structured and unstructured data generated every moment in the finance sector. This data can be used by companies, organizations, and investors to create strategies, as the finance sector rapidly moves towards data-driven optimization.
This book provides an efficient resource, addressing all applications of data analytics in the finance sector. International experts from around the globe cover the most important subjects in finance, including data processing, knowledge management, machine learning models, data modeling, visualization, optimization for financial problems, financial econometrics, financial time series analysis, project management, and decision making. The authors provide empirical evidence as examples of specific topics. By combining both applications and theory, the book offers a holistic approach.
Therefore, it is a must-read for researchers and scholars of financial economics and finance, as well as practitioners interested in a better understanding of financial data analytics.

lt;b>Sinem Derindere Köseoglu is an associate professor of finance and former professor at Istanbul University (Turkey) and a freelance consultant and trainer. Derindere Köseoglu has published in various renowned international journals and volumes.

PART 1. INTRODUCTION AND ANALYTICS MODELS.- Retraining and Reskilling Financial Participators in the Digital Age.- Basics of Financial Data Analytics.- Predictive Analytics Techniques: Theory and Applications in Finance.- Prescriptive Analytics Techniques: Theory and Applications in Finance.- Forecasting Returns of Crypto Currency - Analyzing Robustness of Auto Regressive and Integrated Moving Average (ARIMA) and Artificial Neural Networks (ANNS).- PART 2. MACHINE LEARNING.- Machine Learning in Financial Markets: Dimension Reduction and Support Vector Machine.- Pruned Random Forests for Effective and Efficient Financial Data Analytics.- Foreign Currency Exchange Rate Prediction Using Long Short Term Memory.- Natural Language Processing (NLP) for Exploring Culture in Finance: Theory and Applications.- PART 3. TECHNOLOGY DRIVEN FINANCE.- Financial Networks: A Review of Models and the Use of Network Similarities.- Optimization of Regulatory Economic-Capital Structured Portfolios: ModelingAlgorithms, Financial Data Analytics and Reinforcement Machine Learning in Emerging Markets.- Transforming Insurance Business with Data Science.- A General Cyber Hygiene Approach for Financial Analytical Environment.

Erscheinungsdatum	28.04.2023
Reihe/Serie	Contributions to Finance and Accounting
Zusatzinfo	XXII, 384 p. 122 illus., 100 illus. in color.
Verlagsort	Cham
Sprache	englisch
Maße	155 x 235 mm
Gewicht	623 g
Themenwelt	Wirtschaft ► Betriebswirtschaft / Management ► Finanzierung
Themenwelt	Wirtschaft ► Volkswirtschaftslehre ► Makroökonomie
Schlagworte	Big Data • Blockchain • cloud services • Deep learning • Digitalization in finance • Emerging Markets • Financial Econometrics • Financial Networks • Financial Sector • Foreign currency exchange • innovative technology • Insurance business with data science • machine learning • Natural Language Processing (NLP) • Optimization of regulatory portfolios • predictive techniques • Prescriptive modeling techniques • Time Series Analysis
ISBN-10	3-030-83801-3 / 3030838013
ISBN-13	978-3-030-83801-0 / 9783030838010
Zustand	Neuware