Statistical Machine Learning for Quantitative Finance
Annual Review of Statistics and Its Application, 2023 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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, 2017 [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|||0000-0002-8304-4177 +2 more
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Order Statistics and Their Applications to Quantitative Finance
Order Statistics and Their Applications to Quantitative FinanceThis 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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Complementary and substitution effects of digital finance and green finance on corporate green innovation. [PDF]
Sci RepTan S, Tao S.
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Impact of crowdfunding, entrepreneurial finance and varieties of entrepreneurial ecosystems after COVID pandemic for rural women. [PDF]
PLoS OneLyu Z, Murtaza N.
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Digital finance and climate risk information disclosure. [PDF]
PLoS OneRen H, Huang J, Ren J.
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Flexible Target Prediction for Quantitative Trading in the American Stock Market: A Hybrid Framework Integrating Ensemble Models, Fusion Models and Transfer Learning. [PDF]
Entropy (Basel)Yan K +6 more
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Empirical analysis of the correlation between China's Macroeconomic Market and Crude Oil Market based on mixed-frequency group factor model. [PDF]
PLoS OneZhao J, Yin J.
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Development and external validation of nomograms for predicting prostate cancer and clinically significant prostate cancer in patients with PSA between 4 and 20 ng/mL. [PDF]
BMC UrolWu K +7 more
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