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The Logistic Indicator: A Foreign Exchange Index Day-Trade Model - Couverture souple

Fang, Jianing

 
9783659780837: The Logistic Indicator: A Foreign Exchange Index Day-Trade Model

Synopsis

The debate about the efficient market hypothesis has been running for decades, but it is growing more contestable and salient as global capital markets grow increasingly intertwined and investors become more engaged through a greater diversity in investment options with the help of the rapid developments in computing and information technologies. To examine this complex and volatile global securities landscape, this book tests the efficient market hypothesis using logistic regressions and develops the Logistic Indicator, a foreign exchange index day-trade model and a practical barometer and security investment tool. Along with an overview of the efficient market hypothesis debate and a broad examination of the globalization of financial markets, this study provides robust evidence of significant correlations between stock exchange indexes through the use of logistic regressions in addition to multiple regression analysis.

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Présentation de l'éditeur

The debate about the efficient market hypothesis has been running for decades, but it is growing more contestable and salient as global capital markets grow increasingly intertwined and investors become more engaged through a greater diversity in investment options with the help of the rapid developments in computing and information technologies. To examine this complex and volatile global securities landscape, this book tests the efficient market hypothesis using logistic regressions and develops the Logistic Indicator, a foreign exchange index day-trade model and a practical barometer and security investment tool. Along with an overview of the efficient market hypothesis debate and a broad examination of the globalization of financial markets, this study provides robust evidence of significant correlations between stock exchange indexes through the use of logistic regressions in addition to multiple regression analysis.

Biographie de l'auteur

Dr. Jianing Fang, CPA, CITP is an Associate Accounting Professor at Marist College. He teaches all areas of accounting, tax, and accounting information systems in the graduate and undergraduate programs. His research interests include Ethics, E-commerce taxation, IFRS, XBRL, Big-data, and analytics and their application on accounting, and finance.

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