Description

I specialized in algo/quant trading and alpha research for leaders in the financial industry.

Strong of my background in quantitative finance, machine learning for financial market and entrepreneurship mindset, I now look to provide value to leaders, traders, researchers and investors in the financial industry to have an edge with state of the art tools on the market

Tradingview/ Pinescript/ Python/ IBKR/ Quant/ Machine learning/ Options/ Algo Trading/ Automated Trading/ Alpha Research

Domaines d’expertise

Langues

Français
Bilingue ou natif
Anglais
Bilingue ou natif
Vietnamien
Bilingue ou natif

Préférences en matière de lieu de travail

En télétravail uniquement

Travaille majoritairement à distance

Société Générale - CIB
Quant Model Validation
BANQUE & ASSURANCES
octobre 2021 - septembre 2023 (1 an et 10 mois)
Paris, France
Validation of model’s behavior for linear and exotics products priced in MC, PDE and Regression
o Equity derivatives products June 2022 - Present
▪ Vanilla, Forward, Asian, Var Swap
▪ Built a tool to help decision makers study the impact of dividend yield and IR on products
o Fixed Income products (IR/ FX/ Inflation and Fallback)
▪ Vanilla, Swaption, Callable/ Bermudean, Barrier and trigger options
▪ Validated convexity adjustment for quanto and in arrears delayed payment
• Advised Societe Generale on a strategic plan to write an official document toward the ECB’s models requirements
Python Black Scholes Monte Carlo PDE Trading Equities Fixed Income Git
Société Générale - CIB
Quant Commodity Researcher
BANQUE & ASSURANCES
septembre 2019 - juillet 2020 (10 mois)
Londres, Royaume-Uni
• Built pricing library in python to analyze live trading data, calculate future curves, cost of carry, minimum variance hedge
ratio and fundamental analysis impact on the trading portfolio (pandas, numpy, scikitlearn, scipy)
• Researched commodities strategies: contango/backwardation, cash and carry, roll yield, storage theory, convenience yields,
LME/OTC arbitrage, thus advising traders on underlying pattern
• Identified limitations of current big data management and built a MongoDB database to store daily trading data,
thereby establishing platform for back testing trading strategies
trading strategies Machine learning Time Series arima garch arbitrage trading commodities business Python SQL trading book roll yield cost of carry storage theory convenience yields sentiment analysis Scikit-learn statsmodel Pandas