AWP Futures
Trades Own Strategy BrokerTransmit
- hypothetical · Cumul. Return
- 15.5%
- Max Drawdown
- 3.6%
- Trades
- 15
- Win Trades
- 60.0%
- Profit Factor
- 4.20
- Win Months
- —
About this strategy
AWP stands for All Weather Portfolio. It is a systematic, seven-pod strategy designed to pursue long-term growth while managing volatility and drawdowns across changing market environments.
The model does not depend on a single market, indicator, or forecast. Each pod evaluates opportunities independently and can reduce risk when conditions become unfavorable.
The proprietary signals, parameters, and allocation rules will remain confidential.
Diversification by Strategy
AWP Futures combines several quantitative approaches, including trend, momentum, relative strength, cross-asset analysis, volatility, and defensive positioning.
Because the seven pods respond to different market information, the portfolio is less dependent on any single strategy continuing to perform.
When opportunities are limited, unused allocations can remain in short-term Treasury instruments rather than being forced into the market.
This is diversification by strategy, not merely by ticker.
The individual pods followed distinctly different paths. Combining them produced a smoother and more consistent historical equity curve than relying on any one pod alone.
That is the central premise of AWP Futures: its strength comes from the interaction of complementary return streams.
Built for Futures Implementation
AWP Futures is designed primarily for implementation through liquid futures and micro futures contracts.
Futures provide efficient access to equity, Treasury, commodity, currency, precious-metal, and other markets while allowing unused capital to remain in Treasury bills.
The production system translates its signals into a next-session trading blotter showing target exposures, contract quantities, total notional exposure, and Treasury allocations.
Futures are being used for efficient implementation—not as justification for uncontrolled leverage. When a futures contract is too large to represent the intended allocation accurately, the corresponding ETF may be used instead.
Historical Performance
The finalized portfolio was backtested from February 2016 through July 2026.
SPY produced greater ending wealth over the period, but it did so with a substantially more volatile return path. AWP Futures 1× delivered competitive growth with considerably lower historical volatility and drawdown.
The comparison illustrates the model’s objective: strong compounding with less dependence on traditional equity-market risk.
Exposure Comparison
Because AWP Futures is implemented through futures, I also evaluated the portfolio at 2× and 3× exposure.
These results were calculated by applying leverage to each daily portfolio return and recompounding the complete series. They were not created by simply multiplying the 1× statistics.
The chart shows how the same underlying return stream compounded at different exposure levels. Higher exposure increased historical returns significantly, but it also magnified volatility and drawdowns.
The 2× and 3× simulations are risk-scaling studies—not return forecasts.
Designed Around Robustness
An attractive backtest is not enough. Quantitative strategies can appear exceptional when their rules are overly fitted to historical data.
AWP Futures was therefore developed around robustness rather than the highest isolated backtest result. The research process included:
Point-in-time signal construction
Execution after signals became observable
Independent analysis of every pod
Full-history and trailing-period evaluation
Rolling-return and drawdown analysis
Parameter-neighborhood testing
Allocation-sensitivity testing
Turnover analysis
Comparison with passive equity exposure
Reconciliation of model targets with executable futures positions
The final configuration was selected from a stable range of results—not from a single optimization peak.
Risk Management Within the Architecture
AWP Futures does not rely on one stop-loss or discretionary decision to control risk.
Each pod independently determines whether conditions are favorable. Predetermined portfolio weights limit dependence on any one strategy, while unused allocations can move into defensive Treasury exposure.
Overlapping positions are combined before futures contracts are calculated, and micro futures are used where practical to improve sizing precision.
This architecture cannot eliminate losses. Future drawdowns may be materially larger than those observed in the backtest, and several pods can lose money simultaneously.
The objective is to take risk selectively and systematically—not to suggest that risk has disappeared.
Entering Production
AWP Futures is now entering production.
Its positioning and performance will be documented here on Substack and tracked on Collective2, creating an ongoing record as the strategy moves from historical research into real-world validation.
I will share material positioning changes, performance updates, drawdowns, and observations while keeping the model’s proprietary rules confidential.
The backtest is encouraging. The live record will be the more important test.
This article is for educational and informational purposes only. It is not investment advice, a recommendation, or an offer to buy or sell any security. Backtested results are hypothetical, depend on data and implementation assumptions, and do not represent actual trading. Past performance does not guarantee future results.
Trend-following Momentum
Statistics
Overview
| Strategy began | 7/26/2026 |
|---|---|
| Suggested Minimum Capital | $100,000 |
| Age | 28 days |
| C2 Rank | Top 8.6% |
| What it trades | Futures |
| # Trades | 15 |
| # Profitable | 9 |
| % Profitable | 60.0% |
| Avg trade duration | 7.5 days |
| Max peak-to-valley drawdown | 3.6% |
| drawdown period | Aug 17, 2026 - Aug 18, 2026 |
| Avg win | $2,317 |
| Avg loss | $829 |
Ratios
| W:L ratio | 4.20 |
|---|---|
| Sharpe Ratio | — |
| Sortino Ratio | — |
| Calmar Ratio | — |
CORRELATION STATISTICS
| Return Percent SP500 (cumu) during strategy life | 3.5% |
|---|---|
| Return of Strat Pcnt - Return of SP500 Pcnt (cumu) | 12.0% |
Return Statistics
| Ann Return (w trading costs) | 429.2% |
|---|---|
| Return Pcnt (Compound or Annual, age-based, NFA compliant) | 0.2% |
| Return Pcnt Since TOS Status | 0.0% |
| Ann Return (Compnd, No Fees) | 529.0% |
Slump
| Current Slump as Pcnt Equity | 1.0% |
|---|---|
| Current Slump, time of slump as pcnt of strategy life | 0.1% |
Instruments
| Percent Trades Forex | 0.0% |
|---|---|
| Percent Trades Futures | 1.0% |
| Percent Trades Options | 0.0% |
| Short Options - Percent Covered | 100.0% |
| Percent Trades Stocks | 0.0% |
Risk of Ruin (Monte-Carlo)
| Chance of 10% account loss | 0.0% |
|---|---|
| Chance of 20% account loss | 0.0% |
| Chance of 30% account loss | 0.0% |
| Chance of 40% account loss | 0.0% |
| Chance of 50% account loss | 0.0% |
| Chance of 60% account loss (Monte Carlo) | 0.0% |
| Chance of 70% account loss (Monte Carlo) | 0.0% |
| Chance of 80% account loss (Monte Carlo) | 0.0% |
| Chance of 90% account loss (Monte Carlo) | 0.0% |
Automation
| Percentage Signals Automated | 0.0% |
|---|
Popularity
| Popularity (Today) | 920 |
|---|---|
| Popularity (Last 6 weeks) | 955 |
| C2 Score | 914 |
| Popularity (7 days, Percentile 1000 scale) | 948 |
Trading Style
| Any stock shorts? 0/1 | 0 |
|---|
Trades-Own-System Certification
| Trades Own System? | 187648 |
|---|---|
| TOS percent | 100.0% |
Win / Loss
| Avg Loss | $828 |
|---|---|
| Avg Win | $2,317 |
| # Winners | 9 |
| Sum Trade PL (losers) | $4,971 |
| Sum Trade PL (winners) | $20,856 |
| Num Months Winners | 2 |
| # Losers | 6 |
| % Winners | 60.0% |
Dividends
| Dividends Received in Model Acct | 0 |
|---|
Age
| Num Months filled monthly returns table | 2 |
|---|
Frequency
| Avg Position Time (mins) | 10830.77 |
|---|---|
| Avg Position Time (hrs) | 180.51 |
| Avg Trade Length | 7.50 |
| Last Trade Ago | 2 |
Leverage
| Daily leverage (average) | 2.95 |
|---|---|
| Daily leverage (max) | 4.52 |
Maximum Adverse Excursion (MAE)
| Hold-and-Hope Ratio | 0.53 |
|---|
DRAW DOWN STATISTICS
| Strat Max DD how much worse than SP500 max DD during strat life? | -404223360 |
|---|---|
| Max Equity Drawdown (num days) | 1 |
| Last 4 Months - Pcnt Negative | 0.0% |
Trading record
Placed 37 trades in real-life brokerage accounts.
| Symbol | Side | Qty | Opened | Closed | P/L |
|---|---|---|---|---|---|
| QMGC V6 | long | 2 | Aug 18, 2026 | Aug 19, 2026 | $1,129 |
| QMCL U6 | long | 2 | Aug 6, 2026 | Aug 17, 2026 | $1,069 |
| QMGC V6 | long | 2 | Aug 13, 2026 | Aug 14, 2026 | $24 |
| QMGC V6 | long | 2 | Aug 6, 2026 | Aug 12, 2026 | $3,395 |
| QMGC Z6 | long | 2 | Aug 6, 2026 | Aug 6, 2026 | ($466) |
| MES U6 | long | 3 | Jul 31, 2026 | Aug 6, 2026 | $3,120 |
| MNQ U6 | long | 1 | Jul 28, 2026 | Aug 6, 2026 | $3,203 |
| QMCL U6 | long | 3 | Jul 28, 2026 | Aug 6, 2026 | ($453) |
| DX U6 | long | 1 | Jul 28, 2026 | Aug 6, 2026 | ($1,523) |
| QMGC Q6 | long | 2 | Aug 6, 2026 | Aug 6, 2026 | $393 |
Past results are not necessarily indicative of future results.
These results are based on simulated or hypothetical performance results that have certain inherent limitations. Unlike the results shown in an actual performance record, these results do not represent actual trading. Also, because these trades have not actually been executed, these results may have under-or over-compensated for the impact, if any, of certain market factors, such as lack of liquidity. Simulated or hypothetical trading programs in general are also subject to the fact that they are designed with the benefit of hindsight. No representation is being made that any account will or is likely to achieve profits or losses similar to these being shown.