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Statistical Machine Learning for Quantitative Finance
We survey the active interface of statistical learning methods and quantitative finance models. Our focus is on the use of statistical surrogates, also known as functional approximators, for learning input–output relationships relevant for financial tasks.
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[ES] Los cambios en la orientación de la docencia como consecuencia de la necesaria adaptación al Espacio Europeo de Educación Superior incluyen la adopción de un nuevo paradigma, modificando la orientación docente. Así, se ha pasado de una enseñanza por contenidos a otra orientada a los resultados de aprendizaje y el desarrollo de competencias.
Cervelló Royo, Roberto Elías +2 more
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Quantitative analytics has assumed a growing role in Philippine policy research as government and sectoral databases have become increasingly central to planning, monitoring, and resource allocation. This review synthesizes recent work in education, energy, agriculture, health, and finance to examine how forecasting, statistical forensics, and ...
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Order Statistics and Their Applications to Quantitative Finance
This study concerns about order statistics and their applications to quantitative finance. So far, theories and applications of order statistics have been well developed and applied to many scientific fields ranging from conventional statistical problems to recent biostatistical researches.
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Drivers and Performance Outcomes of Social Responsibility Accounting: An Integrated Model for SMEs in the Mekong Delta. [PDF]
Nguyen Thien P +2 more
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The local government bond channel of China's monetary policy. [PDF]
Bai J, Xia H, Zhang L.
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Decoding Market Voices: Beyond the Charts Analysis of Cryptocurrency Market Microstructure. [PDF]
Sharma N, Manohar S, Rao ABS.
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The role of IT and English education in shaping cognitive and behavioral responses to green economic volatility. [PDF]
Yang H.
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Quantum computing in finance: a literature review and future directions for trustworthy financial AI. [PDF]
Muzzioli S +4 more
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