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  • 1
    UID:
    (DE-627)681255420
    Format: graph. Darst.
    ISSN: 0165-4101
    In: Journal of accounting & economics, Amsterdam [u.a.] : Elsevier, 1979, 52(2011), 2/3 vom: Nov., Seite 126-143, 0165-4101
    In: volume:52
    In: year:2011
    In: number:2/3
    In: month:11
    In: pages:126-143
    Language: English
    Keywords: Aufsatz in Zeitschrift
    Library Location Call Number Volume/Issue/Year Availability
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  • 2
    Online Resource
    Online Resource
    [S.l.] : SSRN
    UID:
    (DE-627)1781147248
    Format: 1 Online-Ressource (51 p)
    Content: I investigate whether information quality affects the cost of equity capital through liquidity risk. Liquidity risk is the sensitivity of stock returns to unexpected changes in market liquidity; recent asset pricing literature has emphasized the importance of this systematic risk. I find that higher information quality is associated with lower liquidity risk and that the reduction in cost of capital due to this association is economically significant. I also find that the negative association between information quality and liquidity risk is stronger in times of large shocks to market liquidity
    Note: Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments March 18, 2011 erstellt
    Language: Undetermined
    Library Location Call Number Volume/Issue/Year Availability
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  • 3
    Online Resource
    Online Resource
    [S.l.] : SSRN
    UID:
    (DE-627)1792672772
    Format: 1 Online-Ressource
    Content: I investigate whether information quality affects the cost of equity capital through liquidity risk. Liquidity risk is the sensitivity of stock returns to unexpected changes in market liquidity; recent asset pricing literature has emphasized the importance of this systematic risk. I find that higher information quality is associated with lower liquidity risk and that the reduction in cost of capital due to this association is economically significant. I also find that the negative association between information quality and liquidity risk is stronger in times of large shocks to market liquidity
    Note: In: Journal of Accounting & Economics (JAE), Forthcoming , Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments March 18, 2011 erstellt , Volltext nicht verfügbar
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 4
    UID:
    (DE-627)796914370
    Format: graph. Darst.
    ISSN: 1380-6653
    In: Review of accounting studies, Norwell, Mass. [u.a.] : Springer, 1996, 19(2014), 3 vom: Sept., Seite 1234-1279, 1380-6653
    In: volume:19
    In: year:2014
    In: number:3
    In: month:09
    In: pages:1234-1279
    Language: English
    Keywords: Aufsatz in Zeitschrift
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  • 5
    UID:
    (DE-627)1792328583
    Format: 1 Online-Ressource
    Content: Regulatory capital guidelines allow for loan loss reserves to be added back as capital. The evidence in this paper suggests that the influence of loan loss reserves added back as regulatory capital (hereafter referred to as “add-backs”) on bank risk cannot be explained by either economic principles underlying the notion of capital, or accounting principles underlying the recording of reserves. Specifically, we observe that in sharp contrast to the economic notion of capital as a buffer against bank failure risk, add-backs are positively associated with the risk of bank failure during the recent economic crisis. Further the positive association of add-backs with bank failure risk is concentrated among cases in which the add-backs are highly likely to increase a bank's total regulatory capital. The evidence cannot thus be fully explained by accounting principles either, since the role of loan loss reserves according to those principles does not depend on whether the reserves generate a regulatory capital increase. Additional analysis suggests that the observed influence of loan loss reserves on bank failure risk may be an unintended consequence of their regulatory treatment as capital
    Note: In: Review of Accounting Studies, Forthcoming , Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments January 15, 2014 erstellt , Volltext nicht verfügbar
    Language: English
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  • 6
    UID:
    (DE-627)1751363732
    Format: 1 Online-Ressource (240 S.)
    Edition: 1.
    ISBN: 9781788833967
    Content: bDelve into the world of real-world financial applications using deep learning, artificial intelligence, and production-grade data feeds and technology with Python/b h4Key Features/h4 ulliUnderstand how to obtain financial data via Quandl or internal systems /li liAutomate commercial banking using artificial intelligence and Python programs /li liImplement various artificial intelligence models to make personal banking easy/li/ul h4Book Description/h4 Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI. You'll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you'll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you'll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you'll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you'll get to grips with some real-world AI considerations in the field of banking. By the end of this book, you'll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI. h4What you will learn/h4 ulliAutomate commercial bank pricing with reinforcement learning /li liPerform technical analysis using convolutional layers in Keras /li liUse natural language processing (NLP) for predicting market responses and visualizing them using graph databases /li liDeploy a robot advisor to manage your personal finances via Open Bank API /li liSense market needs using sentiment analysis for algorithmic marketing /li liExplore AI adoption in banking using practical examples /li liUnderstand how to obtain financial data from commercial, open, and internal sources/li/ul h4Who this book is for/h4 This is one of the most useful artificial intelligence books for machine learning engineers, data engineers, and data scientists working in the finance industry who are looking to implement AI in their business applications. The book will also help entrepreneurs, venture capitalists, investment bankers, and wealth managers who want to understand the importance of AI in finance and banking and how it can help them solve different problems related to these domains. Prior experience in the financial markets or banking domain, and working knowledge of the Python programming language are a must.
    Additional Edition: 9781788830782
    Additional Edition: Erscheint auch als Druck-Ausgabe 9781788830782
    Language: English
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  • 7
    Online Resource
    Online Resource
    Birmingham : Packt Publishing Limited | München : GBI-Genios Wirtschaftsdatenbank GmbH
    UID:
    (DE-603)475680553
    Format: 1 Online-Ressource (240 S.)
    Edition: 1. Auflage
    ISBN: 9781788833967
    Content: bDelve into the world of real-world financial applications using deep learning, artificial intelligence, and production-grade data feeds and technology with Python/b h4Key Features/h4 ulliUnderstand how to obtain financial data via Quandl or internal systems /li liAutomate commercial banking using artificial intelligence and Python programs /li liImplement various artificial intelligence models to make personal banking easy/li/ul h4Book Description/h4 Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI. You'll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you'll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you'll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you'll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you'll get to grips with some real-world AI considerations in the field of banking. By the end of this book, you'll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI. h4What you will learn/h4 ulliAutomate commercial bank pricing with reinforcement learning /li liPerform technical analysis using convolutional layers in Keras /li liUse natural language processing (NLP) for predicting market responses and visualizing them using graph databases /li liDeploy a robot advisor to manage your personal finances via Open Bank API /li liSense market needs using sentiment analysis for algorithmic marketing /li liExplore AI adoption in banking using practical examples /li liUnderstand how to obtain financial data from commercial, open, and internal sources/li/ul h4Who this book is for/h4 This is one of the most useful artificial intelligence books for machine learning engineers, data engineers, and data scientists working in the finance industry who are looking to implement AI in their business applications. The book will also help entrepreneurs, venture capitalists, investment bankers, and wealth managers who want to understand the importance of AI in finance and banking and how it can help them solve different problems related to these domains. Prior experience in the financial markets or banking domain, and working knowledge of the Python programming language are a must.
    Additional Edition: 9781788830782
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 8
    UID:
    (DE-627)1786972417
    Format: 1 Online-Ressource (vi, 220 Seiten) , Illustrationen, Diagramme
    ISBN: 9781788833967
    Content: Remodeling your outlook on banking begins with keeping up to date with the latest and most effective approaches, such as artificial intelligence (AI). Hands-On Artificial Intelligence for Banking is a practical guide that will help you advance in your career in the banking domain. The book will demonstrate AI implementation to make your banking services smoother, more cost-efficient, and accessible to clients, focusing on both the client- and server-side uses of AI. You’ll begin by understanding the importance of artificial intelligence, while also gaining insights into the recent AI revolution in the banking industry. Next, you’ll get hands-on machine learning experience, exploring how to use time series analysis and reinforcement learning to automate client procurements and banking and finance decisions. After this, you’ll progress to learning about mechanizing capital market decisions, using automated portfolio management systems and predicting the future of investment banking. In addition to this, you’ll explore concepts such as building personal wealth advisors and mass customization of client lifetime wealth. Finally, you’ll get to grips with some real-world AI considerations in the field of banking. By the end of this book, you’ll be equipped with the skills you need to navigate the finance domain by leveraging the power of AI.
    Note: Includes bibliographical references and index , Mode of access: World Wide Web.
    Additional Edition: 9781788830782
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 9
    UID:
    (DE-604)BV047070341
    Format: 1 Online-Ressource (vi, 220 Seiten) , Illustrationen, Diagramme (teilweise farbig)
    Edition: First published
    ISBN: 9781788833967
    Content: Hands-On Artificial Intelligence for Banking is a must-have guide for AI developers and machine learning experts looking to build intelligent finance-based applications. This guide will give its readers a complete overview of the global banking business with the help of interesting use-cases, and their implementation using popular Python libraries
    Additional Edition: Erscheint auch als Druck-Ausgabe Shah, Subhash Hands-On Artificial Intelligence for Banking : A Practical Guide to Building Intelligent Financial Applications Using Machine Learning Techniques Birmingham : Packt Publishing, Limited,c2020 ISBN 9781788830782
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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  • 10
    UID:
    (DE-602)b3kat_BV047070341
    Format: 1 Online-Ressource (vi, 220 Seiten) , Illustrationen, Diagramme (teilweise farbig)
    Edition: First published
    ISBN: 9781788833967
    Content: Hands-On Artificial Intelligence for Banking is a must-have guide for AI developers and machine learning experts looking to build intelligent finance-based applications. This guide will give its readers a complete overview of the global banking business with the help of interesting use-cases, and their implementation using popular Python libraries
    Additional Edition: Erscheint auch als Druck-Ausgabe Shah, Subhash Hands-On Artificial Intelligence for Banking : A Practical Guide to Building Intelligent Financial Applications Using Machine Learning Techniques Birmingham : Packt Publishing, Limited,c2020 ISBN 9781788830782
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
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