Dr. Christophe Koudella

Senior Quantitative Research Scientist, QuantOne (Mar 2016 – present) • Quantitative cash equities trading. • Front to end development of a deep learning trading strategy (python, google tensorflow). • Signal research (python, google tensorflow). • Multi-signal portfolio construction and optimization (C++, python, KDB+). • Upstream market data modeling work for backtesting, features generation, cost modeling (KDB+). • General use of machine learning and deep learning techniques (python, tensorflow).

• Market making for swaptions, mid-curves, curve options, Bermudan callables & light exotics. • Managed client flow, execution, risk & trade management, market signal/news monitoring. • Extensive use of systematic relative value approach for OTC vs listed interest rate options (python). • Analysis and systematic trading of eurodollar futures convexity (C++, python). • Wrote an auto-spreader for eurodollar futures and cash against a third party trading system API (C++).

Macro Relative Value Group (2011 – 2012), Quantitative Researcher • In charge of modeling, risk & PL for highly profitable rates & FX volatility pod. • Productionized relative value strategy for short-expiry mid-curve interest rate volatility (C++, python). • Built profitable implied/empirical market model RV gamma strategy (python). • Productionized affine curve model & systematic relative value strategy (C++, python). • Developed production interest rate curves and volatility analytics. (C++)

• Rolled out a Libor market model for valuation & risk (C++). • Quant analytics projects/tools for volatility and correlation products. • Go-to-guy for the rates structuring team. • Exotic interest rate derivatives desk support. • Extensive G10 rate curves design and implementation (C++, COM). • Developed OTC and listed interest rate products pricing and risk engines (C++, COM). • Linear (front-end, swaps, basis, treasuries) and convexity (flow & exotic) desk support.

Stochastic simulations & Brownian dynamics of bio-polymers; distributed scientific computing (C++).

Computational fluid dynamics for atmospheric and oceanic processes, atmospheric experimental data analysis (Fortran/C).

Hydrodynamic instability and turbulence of internal gravity waves, partial differential equations, distributed computing, computational fluid dynamics (Fortran/C).