Composer · investment strategy
by Composer Technologies · via Composer
A daily tactical switch between aggressive AI/tech and defensive hedges. If tech looks stronger than managed‑futures, go risk‑on (AIBU plus a laggard from AIBU/SVXY/FTEC). Otherwise hold the stronger of inverse‑AI (AIBD) or anti‑beta (BTAL). Uses leveraged ETFs.
Description from Composer
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.
This strategy doesn’t publish a performance history we can chart.
Each rule is quoted word for word from the strategy's own documents.
No rules extracted from this strategy’s text yet.
1 positions as of 2026-10-19
: the platform's backtest holdings, not a client account.
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.
0.0% of weight in (IVV: 3.0%)
1 fund (SEC N-PORT, as of 2026-07-31)
This strategy’s rules haven’t been extracted yet, so there’s no claim to compare with. The measurement is still shown. : 100% · 2026-10-19 ()
100.0% of weight in (SPY: 0%)
This strategy’s rules haven’t been extracted yet, so there’s no claim to compare with. The measurement is still shown. : 100% · 2026-10-19 ()
3 of 6 funds in its are : AIBD, AIBU, SVXY
This strategy’s rules haven’t been extracted yet, so there’s no claim to compare with. The measurement is still shown. : 100%
Strategies that share its Thematic label, from other sources first, strongest risk-adjusted return first.
Interactive Advisors
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.
Each day, compare 10‑day RSI (0–100 score of recent up vs down days) of FTEC (US tech) vs KMLM (managed‑futures trend fund). If FTEC’s RSI is higher, hold AIBU (2× AI/Big Data) plus the laggard by recent trend among AIBU, SVXY (benefits from calm volatility), and FTEC—split equally. If not, hold whichever is stronger of AIBD (2× short AI/Big Data) or BTAL (defensive long‑short). Rebalance daily.
A daily tactical switch between aggressive AI/tech and defensive hedges. If tech looks stronger than managed‑futures, go risk‑on (AIBU plus a laggard from AIBU/SVXY/FTEC). Otherwise hold the stronger of inverse‑AI (AIBD) or anti‑beta (BTAL). Uses leveraged ETFs.
Out-of-sample edge: ~23.2% annualized return vs SPY ~18.6%, from a daily AI/tech vs defensive regime switch. Higher upside but larger drawdowns (~38% vs ~19%), with risk controls yielding Calmar ~0.60 and Sharpe ~0.68 and diversification.
Every value on file, each labelled with its calculation basis and as-of date.
| Backtest final value (from $10,000) | $30k | 2026-10-19 | |
| Backtest regulatory fees | $83 | 2026-10-19 | |
| Backtest slippage cost | $574 | 2026-10-19 |
| AI categories (Composer) | ai/tech, daily rebalance, leveraged etfs, managed futures signal, momentum, rsi regime filter, tactical, volatility | ||
| Asset classes / instruments | equities |
| Logic complexity (node count) | 16 | 2026-10-19 | |
| Rebalance frequency | daily |
| Concentration (Herfindahl index, out-of-sample, as Composer reports it) | 0.77 | 2026-10-19 | |
| Ticker universe (assets the logic can hold) | show[ "AIBD", "AIBU", "BTAL", "FTEC", "KMLM", "SVXY" ] | 2026-10-19 |
| Alpha vs SPY, out-of-sample (out-of-sample) | 0.48 | 2026-10-19 | |
| Beta vs SPY, out-of-sample (out-of-sample) | -0.69 | 2026-10-19 | |
| Correlation (R) vs SPY, out-of-sample (out-of-sample) | -0.23 | 2026-10-19 |
| Remixes (copies) | 12 | 2026-10-19 | |
| Watchers | 4 | 2026-10-19 |
| Community review status | ACTIVE | 2026-10-19 |
| Backtest length | 602 | 2026-10-19 | |
| Out-of-sample length | 544 | 2026-10-19 | |
| Return, backtest period (annualized) (backtest) | 57.60% | 2026-10-19 | |
| Return, backtest period (cumulative) (backtest) | 196.99% | 2026-10-19 | |
| Return, out-of-sample period (annualized) (out-of-sample) | 23.21% | ||
| Return, out-of-sample period (cumulative) (out-of-sample) | 56.27% | ||
| Return, trailing 1 day (out-of-sample) | 7.02% | 2026-10-19 | |
| Return, trailing 1 month (out-of-sample) | -3.91% | ||
| Return, trailing 1 week (out-of-sample) | 8.26% | 2026-10-19 | |
| Return, trailing 1 year (backtest) | 50.90% | 2026-10-19 | |
| Return, trailing 1 year (out-of-sample) | 21.93% | ||
| Return, trailing 2 weeks (out-of-sample) | 3.23% | 2026-10-19 | |
| Return, trailing 3 months (out-of-sample) | -4.07% | ||
| SPY annualized return over the backtest window (backtest) | 18.48% | 2026-10-19 |
| Calmar ratio, backtest period (backtest) | 1.50 | 2026-10-19 | |
| Calmar ratio, out-of-sample period (out-of-sample) | 0.60 | ||
| Maximum drawdown, backtest period (backtest) | -38.47% | 2026-10-19 | |
| Maximum drawdown, out-of-sample period (out-of-sample) | -38.47% | ||
| Sharpe ratio, backtest period (backtest) | 1.19 | 2026-10-19 | |
| Sharpe ratio, out-of-sample period (out-of-sample) | 0.68 | ||
| Sortino ratio, backtest period (backtest) | 1.69 | 2026-10-19 | |
| Sortino ratio, out-of-sample period (out-of-sample) | 1.02 | 2026-10-19 | |
| Standard deviation, backtest period (backtest) | 48.66% | 2026-10-19 | |
| Standard deviation, out-of-sample period (out-of-sample) | 49.12% |
| Annualized turnover, backtest period (backtest) | 56.09 | 2026-10-19 | |
| Annualized turnover, out-of-sample period (out-of-sample) | 59.06 | 2026-10-19 | |
| Daily win rate, backtest period (backtest) | 53.32% | 2026-10-19 | |
| Daily win rate, out-of-sample period (out-of-sample) | 52.21% | 2026-10-19 |
Collective2
Composer Technologies · Composer
