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    Investors and Markets: Portfolio Choices, Asset Prices, and Investment Advice
    Dark Markets: Asset Pricing and Information Transmission in Over-the-Counter Markets
    Neoclassical Finance
    Ebook series4 titles

    Princeton Lectures in Finance Series

    By Stephen A. Ross, William F. Sharpe, Stefan Nagel and Darrell Duffie

    4/5

    ()

    About this series

    A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing

    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. In this book, Stefan Nagel 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, Nagel then 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.

    Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.

    LanguageEnglish
    PublisherPrinceton University Press
    Release dateJan 1, 1981
    Investors and Markets: Portfolio Choices, Asset Prices, and Investment Advice
    Dark Markets: Asset Pricing and Information Transmission in Over-the-Counter Markets
    Neoclassical Finance

    Titles in the series (4)

    • 4

      Neoclassical Finance
      Neoclassical Finance

      Neoclassical Finance

      Stephen A. Ross
      0 ratings
      0 ratings

      Neoclassical Finance provides a concise and powerful account of the underlying principles of modern finance, drawing on a generation of theoretical and empirical advances in the field. Stephen Ross developed the no arbitrage principle, tying asset pricing to the simple proposition that there are no free lunches in financial markets, and jointly with John Cox he developed the related concept of risk-neutral pricing. In this book Ross makes a strong case that these concepts are the fundamental pillars of modern finance and, in particular, of market efficiency. In an efficient market prices reflect the information possessed by the market and, as a consequence, trading schemes using commonly available information to beat the market are doomed to fail. By stark contrast, the currently popular stance offered by behavioral finance, fueled by a number of apparent anomalies in the financial markets, regards market prices as subject to the psychological whims of investors. But without any appeal to psychology, Ross shows that neoclassical theory provides a simple and rich explanation that resolves many of the anomalies on which behavioral finance has been fixated. Based on the inaugural Princeton Lectures in Finance, sponsored by the Bendheim Center for Finance of Princeton University, this elegant book represents a major contribution to the ongoing debate on market efficiency, and serves as a useful primer on the fundamentals of finance for both scholars and practitioners.

      Neoclassical Finance provides a concise and powerful account of the underlying principles of modern finance, drawing on a generation of theoretical and empirical advances in the field. Stephen Ross developed the no arbitrage principle, tying asset pricing to the simple proposition that there are no free lunches in financial markets, and jointly with John Cox he developed the related concept of risk-neutral pricing. In this book Ross makes a strong case that these concepts are the fundamental pillars of modern finance and, in particular, of market efficiency. In an efficient market prices reflect the information possessed by the market and, as a consequence, trading schemes using commonly available information to beat the market are doomed to fail. By stark contrast, the currently popular stance offered by behavioral finance, fueled by a number of apparent anomalies in the financial markets, regards market prices as subject to the psychological whims of investors. But without any appeal to psychology, Ross shows that neoclassical theory provides a simple and rich explanation that resolves many of the anomalies on which behavioral finance has been fixated. Based on the inaugural Princeton Lectures in Finance, sponsored by the Bendheim Center for Finance of Princeton University, this elegant book represents a major contribution to the ongoing debate on market efficiency, and serves as a useful primer on the fundamentals of finance for both scholars and practitioners.

    • 5

      Investors and Markets: Portfolio Choices, Asset Prices, and Investment Advice
      Investors and Markets: Portfolio Choices, Asset Prices, and Investment Advice

      Investors and Markets: Portfolio Choices, Asset Prices, and Investment Advice

      William F. Sharpe
      4/5 - 3 ratings
      4/5 - 3 ratings

      In Investors and Markets, Nobel Prize-winning financial economist William Sharpe shows that investment professionals cannot make good portfolio choices unless they understand the determinants of asset prices. But until now asset-price analysis has largely been inaccessible to everyone except PhDs in financial economics. In this book, Sharpe changes that by setting out his state-of-the-art approach to asset pricing in a nonmathematical form that will be comprehensible to a broad range of investment professionals, including investment advisors, money managers, and financial analysts. Bridging the gap between the best financial theory and investment practice, Investors and Markets will help investment professionals make better portfolio choices by being smarter about asset prices. Based on Sharpe's Princeton Lectures in Finance, Investors and Markets presents a method of analyzing asset prices that accounts for the real behavior of investors. Sharpe makes this technique accessible through a new, one-of-a-kind computer program (available for free on his Web site, at http://www.stanford.edu/~wfsharpe/apsim/index.html) that enables users to create virtual markets, setting the starting conditions and then allowing trading until equilibrium is reached and trading stops. Program users can then analyze the final portfolios and asset prices, see expected returns, and measure risk. In addition to popularizing the most sophisticated form of asset-price analysis, Investors and Markets summarizes much of Sharpe's most important previous work and reflects a lifetime of thinking about investing by one of the leading minds in financial economics. Any serious investment professional will benefit from Sharpe's unique insights.

      In Investors and Markets, Nobel Prize-winning financial economist William Sharpe shows that investment professionals cannot make good portfolio choices unless they understand the determinants of asset prices. But until now asset-price analysis has largely been inaccessible to everyone except PhDs in financial economics. In this book, Sharpe changes that by setting out his state-of-the-art approach to asset pricing in a nonmathematical form that will be comprehensible to a broad range of investment professionals, including investment advisors, money managers, and financial analysts. Bridging the gap between the best financial theory and investment practice, Investors and Markets will help investment professionals make better portfolio choices by being smarter about asset prices. Based on Sharpe's Princeton Lectures in Finance, Investors and Markets presents a method of analyzing asset prices that accounts for the real behavior of investors. Sharpe makes this technique accessible through a new, one-of-a-kind computer program (available for free on his Web site, at http://www.stanford.edu/~wfsharpe/apsim/index.html) that enables users to create virtual markets, setting the starting conditions and then allowing trading until equilibrium is reached and trading stops. Program users can then analyze the final portfolios and asset prices, see expected returns, and measure risk. In addition to popularizing the most sophisticated form of asset-price analysis, Investors and Markets summarizes much of Sharpe's most important previous work and reflects a lifetime of thinking about investing by one of the leading minds in financial economics. Any serious investment professional will benefit from Sharpe's unique insights.

    • 6

      Dark Markets: Asset Pricing and Information Transmission in Over-the-Counter Markets
      Dark Markets: Asset Pricing and Information Transmission in Over-the-Counter Markets

      Dark Markets: Asset Pricing and Information Transmission in Over-the-Counter Markets

      Darrell Duffie
      4/5 - 2 ratings
      4/5 - 2 ratings

      A concise introduction to modeling over-the-counter markets Over-the-counter (OTC) markets for derivatives, collateralized debt obligations, and repurchase agreements played a significant role in the global financial crisis. Rather than being traded through a centralized institution such as a stock exchange, OTC trades are negotiated privately between market participants who may be unaware of prices that are currently available elsewhere in the market. In these relatively opaque markets, investors can be in the dark about the most attractive available terms and who might be offering them. This opaqueness exacerbated the financial crisis, as regulators and market participants were unable to quickly assess the risks and pricing of these instruments. Dark Markets offers a concise introduction to OTC markets by explaining key conceptual issues and modeling techniques, and by providing readers with a foundation for more advanced subjects in this field. Darrell Duffie covers the basic methods for modeling search and random matching in economies with many agents. He gives an overview of asset pricing in OTC markets with symmetric and asymmetric information, showing how information percolates through these markets as investors encounter each other over time. This book also features appendixes containing methodologies supporting the more theory-oriented of the chapters, making this the most self-contained introduction to OTC markets available.

      A concise introduction to modeling over-the-counter markets Over-the-counter (OTC) markets for derivatives, collateralized debt obligations, and repurchase agreements played a significant role in the global financial crisis. Rather than being traded through a centralized institution such as a stock exchange, OTC trades are negotiated privately between market participants who may be unaware of prices that are currently available elsewhere in the market. In these relatively opaque markets, investors can be in the dark about the most attractive available terms and who might be offering them. This opaqueness exacerbated the financial crisis, as regulators and market participants were unable to quickly assess the risks and pricing of these instruments. Dark Markets offers a concise introduction to OTC markets by explaining key conceptual issues and modeling techniques, and by providing readers with a foundation for more advanced subjects in this field. Darrell Duffie covers the basic methods for modeling search and random matching in economies with many agents. He gives an overview of asset pricing in OTC markets with symmetric and asymmetric information, showing how information percolates through these markets as investors encounter each other over time. This book also features appendixes containing methodologies supporting the more theory-oriented of the chapters, making this the most self-contained introduction to OTC markets available.

    • 8

      Machine Learning in Asset Pricing
      Machine Learning in Asset Pricing

      Machine Learning in Asset Pricing

      Stefan Nagel
      0 ratings
      0 ratings

      A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing 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. In this book, Stefan Nagel 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, Nagel then 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. Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.

      A groundbreaking, authoritative introduction to how machine learning can be applied to asset pricing 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. In this book, Stefan Nagel 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, Nagel then 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. Machine Learning in Asset Pricing presents the exciting possibilities of using cutting-edge methods in research on financial asset valuation.

    Author

    Stephen A. Ross

    Stephen A. Ross is the Franco Modigliani Professor of Finance and Economics at the Massachusetts Institute of Technology. Best known as the originator of arbitrage pricing theory and as the codiscoverer of risk-neutral pricing and the binomial model for pricing derivatives, he is the coauthor of the best-selling textbook series in finance, Corporate Finance.

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