Yoshi (Josh) graduated from the University of Warsaw with a Master's degree in Quantitative Finance and received the Semkow Prize for his innovative research on High-Frequency Trading (HFT). He also studied Machine Learning and Reinforcement Learning at NYU Tandon School of Engineering. In the past years he has provided technical consulting services to several quantitative hedge funds and trading firms, where he did R&D on, inter alia, the application of Deep Reinforcement Learning (DRL) to financial markets and on Multi-Agent Simulation (MAS) for market risk analysis and trading strategy design. He also has expertise in blockchain and served as a technical advisor at early blockchain startups. Prior to entering the financial industry, he developed a 3D graphics engine from scratch in the gaming industry, where he gained expertise in high-performance computing in C/C++ with x86 code optimization.
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yoshi2233(at)gmail.com
OvercookedGPT: Long-Horizon Reasoning & Task Planning
with LLMs in Multi-Agent Simulations
(2023)
-> Code
DeFinetti: Simulating a Dynamic Liquidity
Provision Strategy for Uniswap v3
(2021)
-> Video
Gamma Squeeze & Short Squeeze Agent-Based
Simulation (ABS) in a Limit Order Book
(2021)
-> Video
"Model-Free Reinforcement Learning for
Financial Portfolios: A Brief Survey"
(2019)
-> White Paper
"A Flash Crash Simulator:
Analyzing HFT's Impact on Market Quality"
(2016)
-> White Paper
Trend-Following Buyback Achievers
(2016)
-> White Paper
"A Multithreaded FX Algo Backtesting System"
(2015)
-> White Paper
More on HFT & Quantitative Trading
Real-Time 3D Graphics Engine
(2004-2008)
Gallery
To see more photos, visit my VSCO page.