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Market Microstructure in Practice comments on the consequences of Reg NMS and MiFID on market microstructure. It covers changes in market design, electronic trading, and investor and trader behaviors. The emergence of high frequency trading and critical events like the ""Flash Crash"" of 2010 are also analyzed in depth. Edited by Charles-Albert Lehalle and Sophie Laruelle, and with contributions from Romain Burgot, Stéphanie Pelin and Matthieu Lasnier, this book uses a quantitative viewpoint to help students, academics, regulators, policy makers, and practitioners understand how an attrition o
Capital market. --- Finance. --- Stock exchanges. --- Bulls and bears --- Commercial corners --- Corners, Commercial --- Equity markets --- Exchanges, Securities --- Exchanges, Stock --- Securities exchanges --- Stock-exchange --- Stock markets --- Funding --- Funds --- Capital markets --- Market, Capital --- Capital market --- Efficient market theory --- Speculation --- Economics --- Currency question --- Finance --- Financial institutions --- Loans --- Money market --- Securities --- Crowding out (Economics) --- Stock exchanges --- E-books
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Leveraging the research efforts of more than sixty experts in the area, this volume reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence.
Machine learning --- Learning, Machine --- Artificial intelligence --- Machine theory --- Finance --- Machine learning. --- Financial institutions. --- Capital market. --- Data processing. --- Money market. Capital market --- Artificial intelligence. Robotics. Simulation. Graphics
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Capital market --- Finance --- Stock exchanges
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Leveraging the research efforts of more than sixty experts in the area, this volume reviews cutting-edge practices in machine learning for financial markets. Instead of seeing machine learning as a new field, the authors explore the connection between knowledge developed by quantitative finance over the past forty years and techniques generated by the current revolution driven by data sciences and artificial intelligence.
Finance --- Machine learning. --- Financial institutions. --- Capital market. --- Data processing.
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Microfinance --- Securities --- Securities --- Stock exchanges --- Prices
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