Composer · investment strategy
by Composer Technologies · via Composer
Daily it pits a bond fund (IEI) against a high‑beta stock fund (SPHB). If bonds are stronger it chooses from aggressive ETFs; else from inverse ETFs. It then buys the recent laggard, betting on a short‑term rebound. Heavy use of 2x/3x funds; expect big swings.
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.
2 positions as of 2026-10-11
: 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% · 2026-10-11 ()
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% · 2026-10-11 ()
14 of 17 funds in its are : DRV, EDC, HIBL, JDST, LABU, PSQ, SARK, TARK, TECL, TMF, TMV, TYO, UPRO, YINN
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 Aggressive risk 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.
4 missing
The text the rules are quoted from, with where it came from.
Each day it compares the recent 7‑day “strength score” (0–100 from up vs down days) of a bond fund (IEI) with a high‑volatility stock fund (SPHB). If bonds look stronger, it picks 1 ETF from an aggressive list; otherwise from inverse/short ETFs. In either case it buys the one that fell most over ~4 days, aiming for a bounce. ~95% goes to the main pick and ~5% to a small side pick. Rebalanced daily.
Daily it pits a bond fund (IEI) against a high‑beta stock fund (SPHB). If bonds are stronger it chooses from aggressive ETFs; else from inverse ETFs. It then buys the recent laggard, betting on a short‑term rebound. Heavy use of 2x/3x funds; expect big swings.
Out-of-sample annualized return ~89.8% vs S&P ~22.4%, with beta ~1 and Calmar ~2.13, signaling strong risk-adjusted upside. Higher gains but larger drawdowns in downturns; suited for risk-tolerant investors seeking short-term upside.
In this trading strategy, the selection of assets to invest in is based on the relative strength index (RSI) of two tickers: "IEI" and "SPHB". "IEI" is the ticker for iShares 3-7 Year Treasury Bond ETF, which tracks the performance of US Treasury bonds with 3-7 years to maturity. "SPHB" is the ticker for Invesco S&P 500 High Beta ETF, which tracks the performance of high beta stocks in the S&P 500 index. The RSI is a technical analysis indicator that measures the strength of a security's price action. It is calculated based on the average gain and average loss of the security over a given time period (in this case, 7 days). The RSI is expressed as a value between 0 and 100, where a value above 70 is considered overbought, and a value below 30 is considered oversold. In this trading strategy, if the RSI of "IEI" is greater than the RSI of "SPHB", it suggests that investors have a higher preference for safety and are therefore buying US Treasury bonds. Conversely, if the RSI of "SPHB" is greater than or equal to the RSI of "IEI", it suggests that investors have a higher appetite for risk and are therefore buying high beta stocks. The idea behind this trading strategy is that if investors are more risk-averse (as indicated by a higher RSI for "IEI"), it might be a good idea to invest in a more defensive asset that can provide stability in uncertain times. On the other hand, if investors are more risk-seeking (as indicated by a higher RSI for "SPHB"), it might be a good idea to invest in high beta stocks that have the potential to provide higher returns but are also riskier. Overall, this trading strategy attempts to capture investor sentiment based on the RSI of two key tickers and adjust its investments accordingly. parking 130 in this strategy. really can just go to zero but interesting to see how it goes. if SPHB Then lowest of these assets TARK TECL UPRO TMF YINN EDC SOXX If IEI Then Lowest of these assets SARK PSQ TM DRV TYO
Every value on file, each labelled with its calculation basis and as-of date.
| Backtest final value (from $10,000) | $3.0M | 2026-10-11 | |
| Backtest regulatory fees | $12k | 2026-10-11 | |
| Backtest slippage cost | $98k | 2026-10-11 |
| AI categories (Composer) | daily rebalancing, inverse etfs, leveraged etfs, mean reversion, momentum comparison, risk-on/risk-off, rsi signal, single-position, tactical allocation | 2026-10-11 | |
| Asset classes / instruments | equities | 2026-10-11 |
| Logic complexity (node count) | 43 | 2026-10-11 | |
| Rebalance frequency | daily | 2026-10-11 |
| Concentration (Herfindahl index, out-of-sample, as Composer reports it) | 0.97 | 2026-10-11 | |
| Ticker universe (assets the logic can hold) | show[ "DRV", "EDC", "HIBL", "IEI", "JDST", "LABU", "PSQ", "SARK", "SOXX", "SPHB", "TARK", "TECL", "TMF", "TMV", "TYO", "UPRO", "YINN" ] | 2026-10-11 |
| Alpha vs SPY, out-of-sample (out-of-sample) | 0.59 | 2026-10-11 | |
| Beta vs SPY, out-of-sample (out-of-sample) | 1.00 | 2026-10-11 | |
| Correlation (R) vs SPY, out-of-sample (out-of-sample) | 0.26 | 2026-10-11 |
| Remixes (copies) | 71 | 2026-10-11 | |
| Watchers | 36 | 2026-10-11 |
| Community review status | ACTIVE | 2026-10-11 |
| Backtest length | 1,110 | 2026-10-11 | |
| Out-of-sample length | 853 | 2026-10-11 | |
| Return, backtest period (annualized) (backtest) | 263.38% | 2026-10-11 | |
| Return, backtest period (cumulative) (backtest) | 29k% | 2026-10-11 | |
| Return, out-of-sample period (annualized) (out-of-sample) | 89.85% | 2026-10-11 | |
| Return, out-of-sample period (cumulative) (out-of-sample) | 777.94% | 2026-10-11 | |
| Return, trailing 1 day (out-of-sample) | 3.36% | 2026-10-11 | |
| Return, trailing 1 month (out-of-sample) | 4.91% | 2026-10-11 | |
| Return, trailing 1 week (out-of-sample) | 6.84% | 2026-10-11 | |
| Return, trailing 1 year (backtest) | 117.22% | 2026-10-11 | |
| Return, trailing 1 year (out-of-sample) | 117.16% | 2026-10-11 | |
| Return, trailing 2 weeks (out-of-sample) | 6.89% | 2026-10-11 | |
| Return, trailing 3 months (out-of-sample) | 14.91% | 2026-10-11 | |
| SPY annualized return over the backtest window (backtest) | 17.16% | 2026-10-11 |
| Calmar ratio, backtest period (backtest) | 6.25 | 2026-10-11 | |
| Calmar ratio, out-of-sample period (out-of-sample) | 2.13 | 2026-10-11 | |
| Maximum drawdown, backtest period (backtest) | -42.11% | 2026-10-11 | |
| Maximum drawdown, out-of-sample period (out-of-sample) | -42.11% | 2026-10-11 | |
| Sharpe ratio, backtest period (backtest) | 2.35 | 2026-10-11 | |
| Sharpe ratio, out-of-sample period (out-of-sample) | 1.42 | 2026-10-11 | |
| Sortino ratio, backtest period (backtest) | 4.05 | 2026-10-11 | |
| Sortino ratio, out-of-sample period (out-of-sample) | 2.20 | 2026-10-11 | |
| Standard deviation, backtest period (backtest) | 63.45% | 2026-10-11 | |
| Standard deviation, out-of-sample period (out-of-sample) | 56.45% | 2026-10-11 |
| Annualized turnover, backtest period (backtest) | 133.90 | 2026-10-11 | |
| Annualized turnover, out-of-sample period (out-of-sample) | 130.68 | 2026-10-11 | |
| Daily win rate, backtest period (backtest) | 53.33% | 2026-10-11 | |
| Daily win rate, out-of-sample period (out-of-sample) | 52.05% | 2026-10-11 |
Composer Technologies · Composer
Composer Technologies · Composer