Analytics in Finance and Risk Management

Table of contents

1. Cover
2. Half Title
3. Series Page
4. Title Page
5. Copyright Page
6. Table of Contents
7. Editors
8. List of Contributors
9. Chapter 1 Does the effectiveness of accounting information system intensify sustainability risk management? An insight into the enabling role of the Blockchain-enabled Intelligent Internet of Things Architecture with Artificial Intelligence
   1. 1 Introduction
   2. 2 Theoretical understanding and foundation
      1. 2.1 Adoption model
      2. 2.2 Conceptual respect
   3. 3 Substantiation of research hypotheses
   4. 4 Methodological approach
      1. 4.1 Research design
      2. 4.2 Operationalization of variables for measurement
      3. 4.3 Sampling procedure and data collection
      4. 4.4 Statistical analysis and calculations
   5. 5 Result analysis
      1. 5.1 Statistics for demographic variables
      2. 5.2 Validity test of the model
      3. 5.3 Correlations among the constructs
   6. 6 Conclusion
      1. 6.1 Theoretical contribution
      2. 6.2 Practical implication
      3. 6.3 Boundaries and further opportunities
   7. Acknowledgement
   8. References
10. Chapter 2 Determining the liquidity level of businesses registered on the Polish Stock exchange
    1. 1 Introduction
    2. 2 Literature review
    3. 3 Proposed work
       1. 3.1 Purpose, scope, and limitations of the study
       2. 3.2 Data collection techniques
       3. 3.3 Research method
    4. 4 Results and discussion
    5. 5 Conclusion and future work
    6. References
11. Chapter 3 The reporting comprehensiveness of financial asset risk and company value
    1. 1 Introduction
       1. 1.1 Theoretical background
       2. 1.2 Comprehensiveness as a qualitative characteristic of financial statements
       3. 1.3 The concept of financial asset risk in reporting
    2. 2 Literature review
    3. 3 Proposed work
    4. 4 Results and discussion
       1. 4.1 Analysis of the reporting comprehensiveness of the risk of financial assets accounted by Polish enterprises
       2. 4.2 Examination of correlation relationships between the reporting comprehensiveness of financial asset risk and the size of the company
    5. 5 Conclusion
    6. References
12. Chapter 4 Gold as an alternative investment in times of turmoil
    1. 1 Introduction
    2. 2 Literature review
    3. 3 Proposed work
    4. 4 Results and discussion
       1. 4.1 Development of the Covid-19 pandemic
       2. 4.2 The gold market during the Covid-19 pandemic
       3. 4.3 The impact of the Covid-19 pandemic on gold prices
       4. 4.4 Russia–Ukraine armed conflict and the gold market
    5. 4 Conclusions and future work
    6. References
13. Chapter 5 Use of artificial neural networks and decision trees for cost estimation of software projects – A model proposal
    1. 1 Introduction
    2. 2 Theoretical framework of data mining and application in software project management
    3. 3 Theoretical framework of predictive modeling: artificial neural networks and decision trees
    4. 4 Process of building a predictive model – research and results according to the SEMMA methodology
       1. 4.1 Description of data and selection of variables
       2. 4.2 Data sampling and exploration: selection of variables
       3. 4.3 Data modification
       4. 4.4 Modeling
       5. 4.5 Model assessment
    5. 5 Conclusions and recommendations
    6. References
14. Chapter 6 Data accounting
    1. 1 Introduction
    2. 2 Literature review
       1. 2.1 Database view update problem
       2. 2.2 Event sourcing
       3. 2.3 Automated debugging
       4. 2.4 Philosophy and axiomatisation of accounting
       5. 2.5 Accounting measure
       6. 2.6 Requirements for error impact reporting
       7. 2.7 Railroad-oriented programming
    3. 3 Proposed work
       1. 3.1 Motivating example
       2. 3.2 Outline
       3. 3.3 Definitions
       4. 3.4 Data space
    4. 4 Data space summarisation
       1. 4.1 Example summarisation
       2. 4.2 For example the table order_details from Table 6.4
       3. 4.3 Partition of data space
       4. 4.4 Tensor products
    5. 5 Discussion
       1. 5.1 Error aggregates vs error estimates
       2. 5.2 Replacing relational algebra in analytics
       3. 5.3 Limitations
    6. 6 Conclusion
    7. Bibliography
15. Chapter 7 A deep reinforcement learning approach for portfolio optimization and risk management – Case studies
    1. 1 Introduction
    2. 2 Literature review
       1. 2.1 Overview of portfolio optimization methods
       2. 2.2 Reinforcement learning
       3. 2.3 Deep reinforcement learning
       4. 2.4 Reinforcement learning in economics
       5. 2.5 Reinforcement learning in trading and portfolio optimization
    3. 3 Proposed work
       1. 3.1 Research problem
       2. 3.2 Experimental setting
    4. 4 Results and discussion
    5. 5 Conclusions and future work
    6. Literature
16. Chapter 8 Leveraging the intelligent internal audit informatization for risk management to pave a route toward circular economy: Does the forensic accounting skill make it different?
    1. 1 Introduction
    2. 2 Theoretical understanding and foundation
       1. 2.1 Theoretical foundation
       2. 2.2 Conceptual respect
    3. 3 Substantiation of research hypotheses
    4. 4 Research methodology
       1. 4.1 Research procedure
       2. 4.2 Operationalization of the measured variables
       3. 4.3 Sampling procedure and data collection
       4. 4.4 Statistical analyses and computations
    5. 5 Interpretation of analytical results and discussion observations
       1. 5.1 Sociodemographic characteristics
       2. 5.2 Reliability and validity evaluation
       3. 5.3 Discriminant validity evaluation
       4. 5.4 Overall model fit evaluation
       5. 5.5 Correlations among the constructs
    6. 6 Final deliberation and future enlargements
       1. 6.1 Theoretical implications
       2. 6.2 Managerial and policy implications
       3. 6.3 Research limitations
    7. Acknowledgement
    8. References
17. Chapter 9 Designing a framework for guest experience management in the hotel industry based on data analysis
    1. 1 Introduction
    2. 2 Theoretical background
       1. 2.1 Customer experience management
       2. 2.2 Guest experience management in the hospitality industry
    3. 3 Proposing a framework for analyzing online guest experience management quality in the hospitality industry
       1. 3.1 Guest satisfaction
       2. 3.2 Hotel star rating
    4. 4 Methodology of customer experience in the hotel industry using data analysis
       1. 4.1 Satisfaction
       2. 4.2 Hotel star rating
    5. 5 Results
       1. 5.1 Data
       2. 5.2 Guest satisfaction
       3. 5.3 Hotel star rating
       4. 5.4 Discussion
    6. 6 Conclusion
    7. References
18. Chapter 10 Use of automated accounting information systems and operational risk in preparation of financial statements: An experimental study
    1. 1 Introduction
    2. 2 Theoretical background
       1. 2.1 Accounting information systems (AIS)
    3. 3 Automation in AIS
       1. 3.1 Risk classification
    4. 4 Categories of operational risk
    5. 5 Operational risk management
    6. 6 Hypothesis development and research design
    7. 7 Research method
       1. 7.1 Research results
       2. 7.2 Implications for practice and research
       3. 7.3 Study limitations and future research
    8. 8 Conclusion
    9. Notes
    10. References
19. Chapter 11 Machine learning in analytical procedures in audit
    1. 1 Introduction
    2. 2 Theoretical framework
    3. 3 Literature review
    4. 4 Methodology
    5. 5 The results
    6. 6 Discussion
    7. 7 Conclusions and policy implications/recommendation
    8. References
20. Chapter 12 Application of advanced tools to bolster the business performance of companies in the new normal
    1. 1 Introduction
       1. 1.1 Background of the problem
    2. 2 Review of literature and proposed work
       1. 2.1 AI technologies
       2. 2.2 Application of AI tools and capabilities
       3. 2.3 Risks underway
    3. 3 The disguised side of AI systems and remedies ahead
    4. 4 Conclusion, limitations and future research agenda
       1. 4.1 Limitations
    5. References
21. Chapter 13 Examine manipulation of financial statements of commercial banks – Evidence from an emerging country
    1. 1 Introduction
    2. 2 Literature review
       1. 2.1 Model to detect fraud or manipulation probability in non-financial companies
       2. 2.2 Model to examine fraud or manipulation probability in financial institutions
    3. 3 Theoretical background
       1. 3.1 Financial statement fraud
       2. 3.2 M-score model
    4. 4 Research methodology and results
       1. 4.1 Research methodology
       2. 4.2 Research results
    5. 5 Conclusions
    6. References
22. Chapter 14 Investments & alternate investment options in India
    1. 1 Introduction
       1. 1.1 Why alternate investments
       2. 1.2 Current scenario of alternate investments in India
       3. 1.3 The future of AIF in India
    2. 2 What are alternative investments?
       1. 2.1 Types of alternative investment funds/different categories of AIFs
       2. 2.2 AIFs becoming popular
       3. 2.3 Who can invest in alternative funds?
       4. 2.4 Reason to invest view in AIF
       5. 2.5 Investors’ limit regarding AIF
    3. 3 Conclusion
    4. 4 Limitations
    5. Bibliography
23. Chapter 15 Risk and return dynamics in portfolio theory
    1. 1 Introduction
       1. 1.1 Portfolio risk & return
       2. 1.2 Beta (market risk)
       3. 1.3 Phases of portfolio management
       4. 1.4 Portfolio optimization
    2. 2 Background and overview of contemporary portfolio theory
       1. 2.1 Modern portfolio theory
    3. 3 Efficient frontier
       1. 3.1 Capital asset pricing model (CAPM)
       2. 3.2 CAPM formula
       3. 3.3 Asset allocation
       4. 3.4 Proposed work: constructing smart portfolio
       5. 3.5 Return concerns of portfolio
    4. 4 Conclusion
    5. Bibliography
24. Chapter 16 Use of machine learning for software project cost estimation based on ISO/IEC standards
    1. 1 Introduction
    2. 2 Problems with proper cost estimation of software projects – Theoretical framework and effects in practice
    3. 3 Software project cost estimation based on the functional size measurement methods approved by ISO/IEC – Literature and standards review
       1. 3.1 Software system functional size measurement
       2. 3.2 Measurement standardization in software engineering
       3. 3.3 ISO/IEC 14143 standard for software system functional size measurement
       4. 3.4 ISO/IEC standards for software system functional size measurement methods
    4. 4 Importance of generalized benchmarking data in software project cost estimation – Basis of research
    5. 5 Use of machine learning algorithms for software project cost estimation – Proposed work, results, discussion
       1. 5.1 Data mining
       2. 5.2 Use of machine learning algorithms – Related work
       3. 5.3 Example of using machine learning algorithms
    6. 6 Conclusions and future work
    7. References
25. Chapter 17 The application of partial least squares structural equation modeling (PLS-SEM) algorithm to brand image and consumer loyalty at shoe shops
    1. 1 Introduction
    2. 2 Literature review
       1. 2.1 Consumer loyalty (CL)
       2. 2.2 Brand image (BI)
       3. 2.3 Client satisfaction (CS)
    3. 3 Research methodology
       1. 3.1 Sample approach
       2. 3.2 Measurement
       3. 3.3 Analytical approach
    4. 4 Result and discussion
       1. 4.1 Partial least squares structural equation modeling (PLS-SEM) algorithm
       2. 4.2 Discussion
    5. 5 Conclusion and limitations
    6. References
26. Chapter 18 Effect of the general government fiscal deficit on the inflation rate: OECD countries with the upper middle income
    1. 1 Introduction
    2. 2 Literature review
       1. 2.1 Theoretical literature
       2. 2.2 Empirical literature
    3. 3 Development of IRs and FDs in OECD countries with upper middle incomes
    4. 4 Proposed work
       1. 4.1 Examination of descriptive statistics of the panel data model
       2. 4.2 Determining the estimation method of the model
       3. 4.3 Testing the assumptions of the model
    5. 5 Result and discussion
    6. 6 Conclusion and future work
    7. References
27. Index