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ISBN: 1108837182 1108938558 1108944914 1108945678 Year: 2022 Publisher: Cambridge, United Kingdom ; New York, NY : Cambridge University Press,
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Public companies now face constant pressure to meet investor expectations. A company must continually deliver strong short-term performance every quarter to maintain its stock price. This valuation treadmill creates incentives for corporations to deceive investors. Published more than twenty years after the passage of Sarbanes-Oxley, which requires all public companies to invest in measures to ensure the accuracy of their disclosures, The Valuation Treadmill shows how securities fraud became a major regulatory concern. Drawing on case studies of paradigmatic securities enforcement actions involving Xerox, Penn Central, Apple, Enron, Citigroup, and General Electric, the book argues that corporate securities fraud emerged as investors increasingly valued companies based on their future performance. Corporations now have an incentive to issue unrealistically optimistic disclosure to convince markets that their success will continue. Securities regulation must do more to protect the integrity of public companies from the pressure of the valuation treadmill.
Securities fraud. --- Securities --- Corporations. --- Valuation. --- Business corporations --- C corporations --- Corporations, Business --- Corporations, Public --- Limited companies --- Publicly held corporations --- Publicly traded corporations --- Public limited companies --- Stock corporations --- Subchapter C corporations --- Business enterprises --- Corporate power --- Disincorporation --- Stocks --- Trusts, Industrial --- Blue sky laws --- Capitalization (Finance) --- Investment securities --- Portfolio --- Scrip --- Securities law --- Underwriting --- Investments --- Investment banking --- Stock fraud --- Fraud --- Law and legislation
Book
Year: 2020 Publisher: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute
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Symmetry-adapted machine learning has shown encouraging ability to mitigate the security risks in information and communication technology (ICT) systems. It is a subset of artificial intelligence (AI) that relies on the principles of processing future events by learning past events or historical data. The autonomous nature of symmetry-adapted machine learning supports effective data processing and analysis for security detection in ICT systems without the interference of human authorities. Many industries are developing machine-learning-adapted solutions to support security for smart hardware, distributed computing, and the cloud. In our Special Issue book, we focus on the deployment of symmetry-adapted machine learning for information security in various application areas. This security approach can support effective methods to handle the dynamic nature of security attacks by extraction and analysis of data to identify hidden patterns of data. The main topics of this Issue include malware classification, an intrusion detection system, image watermarking, color image watermarking, battlefield target aggregation behavior recognition model, IP camera, Internet of Things (IoT) security, service function chain, indoor positioning system, and crypto-analysis.
ISBN: 0901956546 Year: 1993 Publisher: Bradford : Society of Dyers and Colourists,
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Year: 1925 Publisher: London : Philadelphia : C. Griffin ; J. B. Lippincott,
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Year: 1921 Publisher: London : Griffin,
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Year: 1927 Publisher: London: Griffin,
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Year: 1918 Publisher: London: Griffin,
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ISBN: 0892311002 9780892311002 Year: 1983 Publisher: Minneapolis: Existential books,
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Year: 1989 Publisher: Leicester : Dymatecs,
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Year: 1670 Publisher: Amsterdam : Christoffel Cunradus,
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