Vasilis Kotopoulos

Systematic Alpha Researcher

I design, test, and kill systematic strategies.

I research, develop, and validate systematic trading strategies using a self-built, AI-native research framework. From initial hypothesis to robustness testing and shadow deployment, my focus is on finding repeatable edges that survive rigorous scrutiny.

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Experience

Background

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    Research

    How ideas are tested, incubated, and archived

    Process and infrastructure first, then the strategy log — accepted tracks, kills, and caveat rows, tiered strictly.

    1 · Research framework

    My Research Framework

    Nine steps from hypothesis to conditional live deployment. Tap a step for detail.

    1. 1 Hypothesis formulation

      Ideas originate from newsletters, books, academic and industry research, exploratory data analysis, and TQG-assisted idea generation.

    2. 2 Data and OOS protocol

      Define data source, universe, sample period, information availability, and a frozen out-of-sample split before testing. Search stays before the study-specific cut (often 2025-01-01).

    3. 3 Strategy implementation in TQG

      Implement and backtest with safeguards aimed at mitigating lookahead and survivorship bias; their effectiveness is validated rather than assumed perfect.

    4. 4 Parameter sensitivity (PSA)

      Seek a stable high-Sharpe plateau, not a single best point; choose a representative/median configuration or an ensemble using development data only.

    5. 5 Robustness battery

      Fees, slippage, and a 2× cost stress on OOS. When a trial matrix exists: DSR, PBO / CSCV, shift nulls, and beat-random-search checks. Each row’s Robustness Score (0–10) ranks out-of-sample delivery — a comparison hint in this log, not a forecast of future profits.

    6. 6 Final verdict and archive

      Publish qualifying research tracks and archive rejected or no-edge hypotheses with transparent decisions. Every hypothesis receives a verdict.

    7. 7 Quantified expectations

      Monte Carlo simulations and stress scenarios estimate plausible variability, drawdown ranges, and failure conditions for candidate systems.

    8. 8 Shadow incubation

      Paper trade and monitor operational behavior, realized signal generation, and divergence from research assumptions before any capital commitment.

    9. 9 Live deployment

      A conditional future stage under explicit capital, operational, and risk controls. This site does not imply live trading where it has not occurred.

    2 · Sleeve blend

    Equal-weight blend of the strategy log

    An illustrative research composite: shared NAV, equal weight among live published sleeves, daily rebalance, and a 5 bp book turnover cost. Nested composites are dropped so parents and legs are not double-funded. Not a scored strategy-log row — a diversification study that shows why keeping a log is useful.

    3 · Strategy log

    Strategy log

    Curated strategy studies that cleared enough scrutiny to be interesting. Click a row for details and the equity curve.

    Strategy ID Strategy Class Sharpe Max DD Robustness Score*

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    Let's Connect

    Open to fractional research engagements, full-time opportunities, and collaborations in systematic trading and quantitative research. Always happy to connect with others in the field.

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