Epstein Secrets

and parallel processing in C++, Java; RDB and KM design, development, FIX, International equity markets; EXPERIENCE October 2012 — December 2012, Buttonwood Group, Chicago • Deployed and readied for production strategy Malachite, described below. October 2011 — August 2012, Independent work, IVC ■ Implemen

P, Adaptive filtering, Kalman filters, Hidden Markov Model • Kernel 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

and parallel processing in C++, Java; RDB and KDB design, development, FIX, International equity markets; EXPERIENCE October 2012 — December 2012, Buttonwood Group, Chicago • Deployed and readied for production strategy Malachite, described below. October 2011 - August 2012, Independent work, IVC • Implemen

, Adaptive filtering, Kalman filters, Hidden Igarkov Model • Kernel 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 tree

and parallel processing in C++, Java; RDB and KDB design, development, FIX, International equity markets; EXPERIENCE October 2012 — December 2012, Buttonwood Group, Chicago • Deployed and readied for production strategy Malachite, described below. October 2011 — August 2012, Independent work, IVC ■ Implemen

P, Adaptive filtering, Kalman filters, Hidden Markov Model • Kernel 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