Iurii Ermakov

AI Researcher

Shenzhen, Guangdong, China1 yr 1 mo experience

Key Highlights

Expert in quantitative research and algorithmic trading
Proven track record in developing market making models
Strong programming skills in Python and C++

Stackforce AI infers this person is a Fintech expert specializing in quantitative research and algorithmic trading.

Contact

Skills

Core Skills

Quantitative ResearchMachine LearningAlgorithmic TradingMarket MakingQuantitative AnalyticsStatistical ArbitrageEconometrics

Other Skills

Stochastic ModelingHigh-Frequency TradingPython (Programming Language)C++BacktestingProgrammingStochastic ControlStatisticsData ProcessingPythonData analysisRisk managementRefinitiv EikonRQuantitative Finance

Experience

世纪前沿资产 century frontier asset management

Quantitative Researcher

Sep 2025 – Present · 6 mos · Shenzhen, Guangdong, China

Machine LearningStochastic ModelingQuantitative ResearchHigh-Frequency TradingPython (Programming Language)C++

深圳前海千惠资产管理有限公司

Quantitative Researcher

Jun 2025 – Aug 2025 · 2 mos · Shenzhen, Guangdong, China

Commodity futures hft market making

Machine LearningStochastic ModelingAlgorithmic TradingQuantitative ResearchMarket MakingHigh-Frequency Trading+3

伯兄投资(berkeley brothers)

Quantitative Researcher

Feb 2025 – Jun 2025 · 4 mos · Shanghai, China

Market making mathematical model development – ad-hoc expansion of the Guéant and Bergault models for the LOB-adapted case with the constrained action space, short-term alpha & trend signals, and dynamic lob queue-based intensity estimation (Bayesian filtering). Further implementation of the theoretical model and improvement of the position unwinding via cross-asset hedging and liquidity-taker agents.
Developed an LOB queue position estimator and a local matching engine – estimates placed orders’ queue position based on the L2 and trades data streams. Estimation of market cancellations’ positions via conditional distributions, dynamically handles inconsistencies.
Implemented a market making agent and a local back testing system based on historical data.

Quantitative AnalyticsMachine LearningStochastic ModelingAlgorithmic TradingQuantitative ResearchMarket Making+7

艾氪科技

HFT Quantitative Researcher

Jul 2024 – Feb 2025 · 7 mos · Shenzhen, Guangdong, China · On-site

Novel vine copula-based statistical arbitrage model development and implementation. Detection of co-movement anomalies amongst highly-correlated asset groups via vine copulas. Custom C++ implementation of statistical tools & fitting techniques, risk management, order management, trade execution, etc. (C++, Python bindings)
ML factor-based alpha prediction. Configured deep-learning models (transformers) for short-term trend prediction, designed and developed data pipelines, including feature generation, prediction, signal incorporation into the trading system, etc. Tested on live data (Python, PyTorch)

Quantitative AnalyticsMachine LearningAlgorithmic TradingQuantitative ResearchHigh-Frequency TradingProgramming+5

Sargent institute of quantitative economics and finance

Research Assistant

Sep 2023 – Jul 2024 · 10 mos · Shenzhen, Guangdong, China

Drafted and summarized weekly "Brown Bag" research meetings
Graded student assignments and provided constructive feedback

Quantitative ResearchProgrammingData analysisPython (Programming Language)Data Processing

Center of mathematical finance

Quantitative Analytics Student

Sep 2023 – Feb 2024 · 5 mos

Enhanced Avellaneda & Stoikov market making strategy with ML-based predictions based on L2 order book and trade data features
Developed European and American FX option pricing models alongside with their risk metrics (Greeks)
Studied and back tested various low- and mid-frequency trading strategies based on ML signals or statistical anomalies

Quantitative AnalyticsMachine LearningQuantitative ResearchRisk managementProgrammingPython (Programming Language)+2