Collective2 · investment strategy
by Collective2
Trades the 3x and -3x leveraged Nasdaq-100 index 3x leveraged ETFs (TQQQ and SQQQ) on daily basis just before market close.
Description from Collective2
of the return and risk figures:as the source publishes them
What $10,000 would have become, from the strategy's own published history, against the S&P 500 over the same dates. The basis is labelled.
Each rule is quoted word for word from the strategy's own documents.
“We trade TQQQ (3x Bull) and SQQQ (3x Bear).”
“Trades the 3x and -3x leveraged Nasdaq-100 index 3x leveraged ETFs (TQQQ and SQQQ) on daily basis just before market close.”
“The system employs sell stops on all open day positions to strictly limit intraday downside risk.”
“maximizing the daily Sharpe ratio while aiming for a volatility target of 2x the Nasdaq-100”
“The strategy utilizes a proprietary Nearest-Neighbor (KNN) Machine Learning Algorithm”
No published holdings for this strategy.
Fitted to 252 returns (hypothetical) from 2025-10-29 to 2026-10-16. An estimate, not holdings: it can't name stocks.
· : 0.15 · Too loose a fit for a verdict; shown as a guide.
Beta to the S&P 500: 1.11 (90%: 0.35 to 1.69)
Compares the stated rules with the holdings (or, where none are published, a mix estimated from returns), using tests fixed before any results were seen.
No holdings on file, so nothing to test.
Strategies that share its Tactical allocation label, from other sources first, strongest risk-adjusted return first.
Composer Technologies · Composer
Composer Technologies · Composer
How much of what we look for this strategy has, and why anything is missing. Fields that don't apply to it aren't counted.
3 missing
Rebalance schedule taken from a stated rule.
The text the rules are quoted from, with where it came from.
Adaptive Investments is a 100% automated quantitative strategy designed to capitalize on the volatility of the Nasdaq-100 index. Recently optimized to trade highly liquid 3x leveraged ETFs (TQQQ and SQQQ), this system aims to capture directional alpha by adapting to changing market regimes. The Core Philosophy: "Do what would have worked best, given historically similar conditions." How It Works The strategy utilizes a proprietary Nearest-Neighbor (KNN) Machine Learning Algorithm to predict the Nasdaq-100’s next-day return. * Pattern Matching: Every trading day, the algorithm scans 20 years of historical data to find days that statistically resemble the current market setup. * Daily Optimization: It targets a specific risk profile—maximizing the daily Sharpe ratio while aiming for a volatility target of 2x the Nasdaq-100. * Signal Generation: Just before the market closes, the system determines whether to increase, decrease, or hold leverage based on the projected close-to-close change. Instruments & Leverage * Assets: We trade TQQQ (3x Bull) and SQQQ (3x Bear). * Dynamic Exposure: By adjusting the allocation between these funds and cash, the effective account leverage varies dynamically from -300% (Short) to +300% (Long) in increments of 100%. Risk Management The model has been trained and validated on a 20-year dataset, ensuring the approach is generalized across various market cycles (bull runs, crashes, and chopping periods). The system employs sell stops on all open day positions to strictly limit intraday downside risk. Subscriber Guide: Best Practices To replicate this strategy effectively, please note the following: * Automation is Critical: Trades are executed approximately 15-20 seconds before the market close. Because timing is essential to the strategy's accuracy, we highly recommend using C2’s "Auto-Trade" feature rather than manual execution. * Frequency: Expect a maximum of two trades per day (typically executing the rotation from one ETF to another or to cash). Important Note on Performance Data: Please be aware that strategy development and backtest performance data are not released. We strongly recommend reviewing the Statistics Tab on this profile to analyze various performance attributes under live market conditions.
Trades the 3x and -3x leveraged Nasdaq-100 index 3x leveraged ETFs (TQQQ and SQQQ) on daily basis just before market close.
Every value on file, each labelled with its calculation basis and as-of date.
| Asset classes / instruments | stocks | ||
| Leaderboard views (Collective2) | ira_account, popular, tos |
| Subscription price per month | $495 | ||
| Suggested minimum capital | $15k |
| Strategy age | 813 |
| Alpha vs S&P 500, strategy life (hypothetical model account) | 0.14 | 2026-10-19 | |
| Beta vs S&P 500, strategy life (hypothetical model account) | 0.63 | 2026-10-19 | |
| Correlation to S&P 500, strategy life (hypothetical model account) | 0.29 | 2026-10-19 |
| Annual return compounded, strategy life (hypothetical model account) | 82.00% | ||
| Annualized return since inception (Lighthorse, daily, hypothetical) | 74.06% | 2026-10-16 | |
| Monthly returns (hypothetical model account) | show{
"2024-Aug": 0.08291,
"2024-Dec": 0.03895,
"2024-Jul": -0.03762,
"2024-Nov": 0.05322,
"2024-Oct": -0.07879,
"2024-Sep": -0.00502,
"2024-YTD": 0.045259999999999995,
"2025-Apr": 0.5074000000000001,
"2025-Aug": 0.10933,
"2025-Dec": 0.10715,
"2025-Feb": 0.0008,
"2025-Jan": 0.08476,
"2025-Jul": 0.033,
"2025-Jun": 0.04549,
"2025-Mar": 0.00616,
"2025-May": 0.07591,
"2025-Nov": 0.12354,
"2025-Oct": 0.062240000000000004,
"2025-Sep": 0.00001,
"2025-YTD": 1.80448,
"2026-Apr": 0.20347,
"2026-Aug": 0.028130000000000002,
"2026-Feb": 0.23419,
"2026-Jan": 0.14135,
"2026-Jul": -0.0387,
"2026-Jun": -0.08922000000000001,
"2026-Mar": -0.20854,
"2026-May": -0.06129,
"2026-Oct": -0.055999999999999994,
"2026-Sep": 0.09278,
"2026-YTD": 0.16899999999999998
} | 2026-10-19 | |
| Return, 1 month (hypothetical model account) | 10.94% | ||
| Return, 3 months (hypothetical model account) | 8.69% | ||
| Return, 6 months (hypothetical model account) | 7.16% | ||
| Return, last 365 days (Lighthorse, daily, hypothetical) | 43.75% | 2026-10-16 |
| Maximum drawdown since inception (Lighthorse, daily, hypothetical) | -33.10% | 2026-10-16 | |
| Maximum drawdown, last 365 days (Lighthorse, daily, hypothetical) | -33.10% | 2026-10-16 | |
| Maximum drawdown, strategy life (hypothetical model account) | -33.10% | ||
| Sharpe ratio since inception (Lighthorse, daily, hypothetical) | 1.38 | 2026-10-16 | |
| Sharpe ratio, last 365 days (Lighthorse, daily, hypothetical) | 0.97 | 2026-10-16 | |
| Sharpe ratio, strategy life (hypothetical model account) | 1.53 | ||
| Sortino ratio, last 365 days (Lighthorse, daily, hypothetical) | 1.53 | 2026-10-16 | |
| Sortino ratio, strategy life (hypothetical model account) | 2.60 | 2026-10-19 | |
| Volatility since inception (Lighthorse, daily, hypothetical) | 41.95% | 2026-10-16 | |
| Volatility, last 365 days (Lighthorse, daily, hypothetical) | 41.06% | 2026-10-16 |
| Heart Attack Index (Collective2) | 8 |
| Average leverage | 2.36 | ||
| Average position time | 3,417 | ||
| Maximum daily leverage | 4.38 | 2026-10-19 | |
| Number of trades | 279 | 2026-10-19 | |
| Percent of trades profitable | 49.64% | ||
| Profit factor | 1.56 | ||
| Win:loss ratio | 1.56 |
Composer Technologies · Composer
Composer Technologies · Composer