Collective2 · investment strategy
by Collective2
Fully automated, no emotional trading!
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.
No rules extracted from this strategy’s text yet.
No published holdings for this strategy.
Fitted to 252 returns (hypothetical) from 2025-10-27 to 2026-10-13. An estimate, not holdings: it can't name stocks.
· : 0.23 · Too loose a fit for a verdict; shown as a guide.
Beta to the S&P 500: 8.16 (90%: 7.09 to 10.15)
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.
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.
4 missing
The text the rules are quoted from, with where it came from.
As a data analyst with nine years of experience, I deeply understand that formulating a successful trading strategy is not possible without thorough stock screening, monitoring market trends, implementing technical analysis strategies, continuous backtesting of data, and analyzing backtest results. Fortunately, my background in knowledge supports me through the entire process, and I've successfully implemented fully automated trading. This includes automated data feeding, automated calculations, and the automatic generation of trading signals according to predefined strategies. Most importantly, I use it on my own money in my Interactive Brokers account. In this age where data can easily be manipulated, you may find it reassuring to know that there are individuals who use the system for real trading in their own accounts. The fluctuations on my statements represent my actual investments, with no exaggerations or false claims of profits. My automated trading strategy strives to exit positions when stock prices reach relative highs and enter when they are relatively low, eliminating emotional trading. Ultimately, this approach allows for stability and the realization of deserved profits in the market. It's that simple! I maintain a disciplined routine of checking the market every hour while trading, making necessary adjustments, and potentially entering or exiting positions. I also personally monitor the connection of my automated trading system to Interactive Brokers to prevent any unnecessary losses. You're welcome to replicate my trades now and join me in experiencing stable growth in the market for your assets!
Fully automated, no emotional trading!
Every value on file, each labelled with its calculation basis and as-of date.
| Asset classes / instruments | stocks | ||
| Leaderboard views (Collective2) | old_timers, popular, tos |
| Subscription price per month | $100 | ||
| Suggested minimum capital | $360k |
| Strategy age | 1,118 |
| Alpha vs S&P 500, strategy life (hypothetical model account) | 0.04 | 2026-10-20 | |
| Beta vs S&P 500, strategy life (hypothetical model account) | 2.76 | 2026-10-20 | |
| Correlation to S&P 500, strategy life (hypothetical model account) | 0.46 | 2026-10-20 |
| Annual return compounded, strategy life (hypothetical model account) | 43.60% | ||
| Annualized return since inception (Lighthorse, daily, hypothetical) | 41.14% | 2026-10-13 | |
| Monthly returns (hypothetical model account) | show{
"2023-Dec": 0.09506,
"2023-Nov": 0.21401,
"2023-Oct": -0.053899999999999997,
"2023-Sep": 0.03143,
"2023-YTD": 0.29728,
"2024-Apr": -0.18159,
"2024-Aug": -0.01818,
"2024-Dec": 0.08786,
"2024-Feb": 0.20793,
"2024-Jan": 0.08215,
"2024-Jul": -0.08651999999999999,
"2024-Jun": 0.08396,
"2024-Mar": 0.09968,
"2024-May": 0.15936,
"2024-Nov": 0.05908,
"2024-Oct": -0.06083,
"2024-Sep": 0.01146,
"2024-YTD": 0.45119,
"2025-Apr": 0.04995,
"2025-Aug": 0.13295,
"2025-Dec": 0.17402,
"2025-Feb": -0.19317,
"2025-Jan": 0.17839,
"2025-Jul": 0.10907,
"2025-Jun": 0.15942,
"2025-Mar": -0.28678000000000003,
"2025-May": 0.18316,
"2025-Nov": -0.2854,
"2025-Oct": 0.07298,
"2025-Sep": 0.09133,
"2025-YTD": 0.20562999999999998,
"2026-Apr": 0.82319,
"2026-Aug": 0.08823,
"2026-Feb": 0.0291,
"2026-Jan": 0.33893,
"2026-Jul": -0.7823,
"2026-Jun": 0.43008,
"2026-Mar": -0.11657999999999999,
"2026-May": 0.8161799999999999,
"2026-Oct": -0.498,
"2026-Sep": 0.30869,
"2026-YTD": -0.10300000000000001
} | 2026-10-20 | |
| Return, 1 month (hypothetical model account) | 11.99% | ||
| Return, 3 months (hypothetical model account) | 50.41% | ||
| Return, 6 months (hypothetical model account) | 36.43% | ||
| Return, last 365 days (Lighthorse, daily, hypothetical) | 2.25% | 2026-10-13 |
| Maximum drawdown since inception (Lighthorse, daily, hypothetical) | -85.45% | 2026-10-13 | |
| Maximum drawdown, last 365 days (Lighthorse, daily, hypothetical) | -85.45% | 2026-10-13 | |
| Maximum drawdown, strategy life (hypothetical model account) | -85.50% | ||
| Sharpe ratio since inception (Lighthorse, daily, hypothetical) | 0.82 | 2026-10-13 | |
| Sharpe ratio, last 365 days (Lighthorse, daily, hypothetical) | 0.83 | 2026-10-13 | |
| Sharpe ratio, strategy life (hypothetical model account) | 0.72 | ||
| Sortino ratio, last 365 days (Lighthorse, daily, hypothetical) | 1.21 | 2026-10-13 | |
| Sortino ratio, strategy life (hypothetical model account) | 0.80 | 2026-10-20 | |
| Volatility since inception (Lighthorse, daily, hypothetical) | 109.54% | 2026-10-13 | |
| Volatility, last 365 days (Lighthorse, daily, hypothetical) | 166.76% | 2026-10-13 |
| Heart Attack Index (Collective2) | 62 |
| Average leverage | 2.84 | ||
| Average position time | 14,521 | ||
| Maximum daily leverage | 5.75 | 2026-10-20 | |
| Number of trades | 1,842 | 2026-10-20 | |
| Percent of trades profitable | 57.39% | ||
| Profit factor | 1.17 | ||
| Win:loss ratio | 1.17 |