Epstein Secrets

me series methods, statistical machine learning, digital signal processing and optimization methods; Mathematical language environments: It, S-PLUS; Maple, OOD and parallel processing in C++, Java; RDB and KM design, development, FIX, International equity markets; EXPERIENCE October 2012 — December 2

el Methods, Support Vector Machines • Cointegration and Error Correction models, Vector Auto Regression, ARCH and Granger causality, GARCH models, ARIMA. Panel data modeling Fixed and Variable effects models • MARS, Boosting methods, Regression trees, Cluster analysis: Markovian (MCL), spectral and

ime series methods, statistical machine learning, digital signal processing and optimization methods; Mathematical language environments: R, S-PLUS; Maple, OOD and parallel processing in C++, Java; RDB and KDB design, development, FIX, International equity markets; EXPERIENCE October 2012 — December

el Methods, Support Vector Machines • Cointegration and Error Correction models, Vector Auto Regression, ARCH and Granger causality, GARCH models, ARIMA. Panel data modeling: Fixed and Variable effects models • MARS, Boosting methods, Regression trees, Cluster analysis: Markovian (MCL), spectral and

ime series methods, statistical machine learning, digital signal processing and optimization methods; Mathematical language environments: R, S-PLUS; Maple, OOD and parallel processing in C++, Java; RDB and KDB design, development, FIX, International equity markets; EXPERIENCE October 2012 — December

el Methods, Support Vector Machines • Cointegration and Error Correction models, Vector Auto Regression, ARCH and Granger causality, GARCH models, ARIMA. Panel data modeling Fixed and Variable effects models • MARS, Boosting methods, Regression trees, Cluster analysis: Markovian (MCL), spectral and