Stanislaw Michal Kubik

Published

February 17, 2026

Quantitative Trader
stanislaw.kubik@proton.me | +41 77 287 65 28 | Lugano, Switzerland

Experience

Butterfly.Trading | Quantitative Trader & Desk Lead

Lugano, Switzerland | Jul 2025 – Present

  • Desk Leadership: Leads a team of two developers, managing the end-to-end systematic arbitrage desk across crypto, options, and prediction markets. Accountable for overall desk results and translating venue-specific mechanics into deployable trading structures.
  • Strategy Development: Specializes in targeting niche venues to execute rapid 1-day prototyping that evolves into live trading strategies.
  • Forecasting Pipeline: Built and currently maintains an intraday realized variance forecasting pipeline for short-dated crypto derivatives, utilizing a time-series model with intraday seasonality.
  • Infrastructure & DevOps: Oversees real-time production stacks on AWS/Linux, managing REST/WebSocket ingestion, backtesting/replay engines, execution services, and full observability (monitoring, alerting, and incident response).
  • ML Infrastructure: Bult a serverless GPU compute pipeline to scale Transformer inference, automating the semantic reconciliation of prediction market events for arbitrage execution.

ACT Commodities Group | Market Intelligence Analyst (Intern & Working student)

Amsterdam, Netherlands | Sep 2023 – May 2024

  • Volatility Modeling: Leveraged autoregressive models to analyze trends and forecast volatility in environmental commodity markets, directly generating actionable insights for the trading desk.
  • Market Analysis: Produced detailed monthly analysis reports on European & UK compliance carbon markets, distributed to over 500 clients.
  • Automation: Designed and automated data extraction and processing for large carbon certificate datasets using Python and SQL, significantly improving internal desk processes.

Coachways Q.R.U. | Family Company

Krakow, Poland & Remote | Oct 2021 – Jul 2025

  • Managed a diversified passive investment portfolio for a family company, allocating capital across multiple sectors to ensure balanced growth and risk management.

Education

University of Oxford, Saïd Business School

MSc Financial Economics | 2024 – 2025

  • Grade: Merit
  • Key Modules: Financial Econometrics, Macroeconomics, Continuous Time Finance, Asset Pricing, Macrofinance, Fixed Income and Derivatives, Financial Microeconomics, Trading.

Erasmus University Rotterdam, Rotterdam School of Management

BSc International Business Administration | 2021 – 2024

  • Honors: Cum Laude
  • Specialisation: Finance

Technical Projects

SOFR curve fitting from SR1 and SR3 futures | Feb 2026
Built a SOFR curve fitting report that fits a stepwise SOFR forward curve from SR1/SR3 futures via a progressive Stage 1–5 pipeline (OLS → turns+fixings → smoothing → liquidity weighting → Huber).
Fixed Income PCA Mean Reversion | Jan 2026
Built a PCA-neutral US Treasury butterfly backtest that neutralizes level/slope (PC1/PC2) in walk-forward estimation and trades mean reversion in a standardized PC3 residual.
Vectorised Backtesting Python Library | Jan 2026
Wrote vectorised-backtesting, a compact research library for fast vectorised backtesting and portfolio construction with consistent timing/lag assumptions, cash and turnover accounting, and guardrails that prevent silent bad results during rapid strategy prototyping.
Summaries AI Agent | Jan 2026
Built Summaries AI agent, an open-source workflow that produces concise, intuition-first maths and statistics summaries for quantitative finance using a fixed LaTeX template, automated PDF compilation/cleanup, and optional MCP-enabled paper discovery (arXiv, Crossref, Semantic Scholar) with web-search fallback.
Crypto Carry Factor | Dec 2025
Extended Koijen et al. (2018) methodology to Binance USDT perpetuals (2021–2025) and built a Python pipeline (Binance REST API) to construct a top-30 liquidity long/short funding carry factor. Reported Sharpe 0.31 overall; carry attribution Sharpe 3.55.
Volatility Forecasting Pipeline | Jan 2025
Developed a Python-based Value-at-Risk (VaR) forecasting pipeline using arch and statsmodels on 20+ years of global equity index data. Implemented volatility model selection frameworks, utilizing Filtered Historical Simulation and RiskMetrics forecasts with recursive/rolling window updates.

Skills & Interests

Category Skills
Quantitative Finance Time series & cross-sectional forecasting, Volatility modelling, Feature engineering, Derivatives Pricing
Programming Python (Pandas, NumPy, Scikit-learn), SQL, AI Agents, Rust (Basic proficiency)
Infrastructure AWS (EC2, VPC, S3, IAM), Docker, Git, Linux environments
Languages English (Professional), Polish (Native)

Certifications & Activities:

  • GMAT: 750 (99th percentile)
  • Certificates: Level 4 in Applied Asset Management (LFBI/AmplifyMe).
  • Activities: Oxford Saïd Asset Management Masterclass, Poker (30th/140 in Financial Markets Charity Poker), Endurance Sports (Oxford Half-Marathon).

Work Authorization

Polish Nationality, Swiss B Residence Permit