We're a closed fund sharing our systematic quantitative strategy's backtested performance for entertainment, education, and building a trading community.
Historical backtesting results (Feb 2012 - April 2025) demonstrating our machine learning-driven global macro strategy's performance for community learning and discussion.
| Symbol | Shares | Entry Price | Current Price | Unrealized P&L | Weight |
|---|---|---|---|---|---|
AAPL | 2150 | $185 | $198 | +$28,488 | 8.2% |
MU | 480 | $820 | $875 | +$26,482 | 7.8% |
MSFT | 1050 | $410 | $426 | +$16,139 | 6.1% |
The fund allocates across U.S. indexes and ETFs, creating diversified exposure in our educational backtesting model.
Closed Fund: The Picasso M1 strategy uses machine learning models analyzing macroeconomic indicators from 20+ countries. Our Global Regime Model (GGM1) categorizes markets into Risk-On vs Risk-Off periods, dynamically adjusting allocations.
Backtested Performance (2012-2025): Our systematic approach delivered 26.29% CAGR vs S&P 500's 13.46% (1.95× higher), with 1.71 Sortino ratio vs 1.19 (1.44× higher), 21.69% volatility vs 16.39%, and -33.33% max drawdown vs -32.05%. Expected yearly return: 24.64% vs S&P's 12.66%.
Daily risk management with systematic position sizing across highly liquid U.S. indexes and ETFs, demonstrated in our closed educational backtesting model.
Machine learning models process weekly and monthly macroeconomic data to identify market regime shifts for educational demonstration of systematic trading.
Complete transparency in our closed fund's methodology - sharing backtested results and strategy details to educate and build trading community knowledge.
Auto-trade the full strategy, simulate it first on Collective2, or follow along with free daily picks by email.
Hands-off investing
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