Sanford M. Jacoby
- Published in print:
- 2021
- Published Online:
- May 2022
- ISBN:
- 9780691217208
- eISBN:
- 9780691217215
- Item type:
- book
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691217208.001.0001
- Subject:
- Economics and Finance, Economic History
Since the 1970s, American unions have shrunk dramatically, as has their economic clout. This book traces the search for new sources of power, showing how unions turned financialization to their ...
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Since the 1970s, American unions have shrunk dramatically, as has their economic clout. This book traces the search for new sources of power, showing how unions turned financialization to their advantage. The book catalogs the array of allies and finance-based tactics labor deployed to stanch membership losses in the private sector. By leveraging pension capital, unions restructured corporate governance around issues like executive pay and accountability. In Congress, they drew on their political influence to press for corporate reforms in the wake of business scandals and the financial crisis. The effort restrained imperial CEOs but could not bridge the divide between workers and owners. Wages lagged behind investor returns, feeding the inequality identified by Occupy Wall Street. And labor's slide continued. The book explores the paradox of capital bestowing power to labor in the tumultuous era of Enron, Lehman Brothers, and Dodd-Frank.Less
Since the 1970s, American unions have shrunk dramatically, as has their economic clout. This book traces the search for new sources of power, showing how unions turned financialization to their advantage. The book catalogs the array of allies and finance-based tactics labor deployed to stanch membership losses in the private sector. By leveraging pension capital, unions restructured corporate governance around issues like executive pay and accountability. In Congress, they drew on their political influence to press for corporate reforms in the wake of business scandals and the financial crisis. The effort restrained imperial CEOs but could not bridge the divide between workers and owners. Wages lagged behind investor returns, feeding the inequality identified by Occupy Wall Street. And labor's slide continued. The book explores the paradox of capital bestowing power to labor in the tumultuous era of Enron, Lehman Brothers, and Dodd-Frank.
Stefan Nagel
- Published in print:
- 2021
- Published Online:
- May 2022
- ISBN:
- 9780691218700
- eISBN:
- 9780691218717
- Item type:
- book
- Publisher:
- Princeton University Press
- DOI:
- 10.23943/princeton/9780691218700.001.0001
- Subject:
- Economics and Finance, Financial Economics
Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, ...
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Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. This book examines the promises and challenges of ML applications in asset pricing. Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, the book discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets. The book presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.Less
Investors in financial markets are faced with an abundance of potentially value-relevant information from a wide variety of different sources. In such data-rich, high-dimensional environments, techniques from the rapidly advancing field of machine learning (ML) are well-suited for solving prediction problems. Accordingly, ML methods are quickly becoming part of the toolkit in asset pricing research and quantitative investing. This book examines the promises and challenges of ML applications in asset pricing. Asset pricing problems are substantially different from the settings for which ML tools were developed originally. To realize the potential of ML methods, they must be adapted for the specific conditions in asset pricing applications. Economic considerations, such as portfolio optimization, absence of near arbitrage, and investor learning can guide the selection and modification of ML tools. Beginning with a brief survey of basic supervised ML methods, the book discusses the application of these techniques in empirical research in asset pricing and shows how they promise to advance the theoretical modeling of financial markets. The book presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.