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AWP Futures

Futures · Futures · Started Jul 2026

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
Subscribe Full access for $199/month

About this strategy

Most portfolios diversify by holding more assets. AWP Futures diversifies by combining different sources of return.

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 began7/26/2026
Suggested Minimum Capital$100,000
Age28 days
C2 RankTop 8.6%
What it tradesFutures
# Trades15
# Profitable9
% Profitable60.0%
Avg trade duration7.5 days
Max peak-to-valley drawdown3.6%
drawdown periodAug 17, 2026 - Aug 18, 2026
Avg win$2,317
Avg loss$829

Ratios

W:L ratio4.20
Sharpe Ratio
Sortino Ratio
Calmar Ratio

CORRELATION STATISTICS

Return Percent SP500 (cumu) during strategy life3.5%
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 Status0.0%
Ann Return (Compnd, No Fees)529.0%

Slump

Current Slump as Pcnt Equity1.0%
Current Slump, time of slump as pcnt of strategy life0.1%

Instruments

Percent Trades Forex0.0%
Percent Trades Futures1.0%
Percent Trades Options0.0%
Short Options - Percent Covered100.0%
Percent Trades Stocks0.0%

Risk of Ruin (Monte-Carlo)

Chance of 10% account loss0.0%
Chance of 20% account loss0.0%
Chance of 30% account loss0.0%
Chance of 40% account loss0.0%
Chance of 50% account loss0.0%
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 Automated0.0%

Popularity

Popularity (Today)920
Popularity (Last 6 weeks)955
C2 Score914
Popularity (7 days, Percentile 1000 scale)948

Trading Style

Any stock shorts? 0/10

Trades-Own-System Certification

Trades Own System?187648
TOS percent100.0%

Win / Loss

Avg Loss$828
Avg Win$2,317
# Winners9
Sum Trade PL (losers)$4,971
Sum Trade PL (winners)$20,856
Num Months Winners2
# Losers6
% Winners60.0%

Dividends

Dividends Received in Model Acct0

Age

Num Months filled monthly returns table2

Frequency

Avg Position Time (mins)10830.77
Avg Position Time (hrs)180.51
Avg Trade Length7.50
Last Trade Ago2

Leverage

Daily leverage (average)2.95
Daily leverage (max)4.52

Maximum Adverse Excursion (MAE)

Hold-and-Hope Ratio0.53

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 Negative0.0%

Trading record

Placed 37 trades in real-life brokerage accounts.

SymbolSideQtyOpenedClosedP/L
QMGC V6long2Aug 18, 2026Aug 19, 2026$1,129
QMCL U6long2Aug 6, 2026Aug 17, 2026$1,069
QMGC V6long2Aug 13, 2026Aug 14, 2026$24
QMGC V6long2Aug 6, 2026Aug 12, 2026$3,395
QMGC Z6long2Aug 6, 2026Aug 6, 2026($466)
MES U6long3Jul 31, 2026Aug 6, 2026$3,120
MNQ U6long1Jul 28, 2026Aug 6, 2026$3,203
QMCL U6long3Jul 28, 2026Aug 6, 2026($453)
DX U6long1Jul 28, 2026Aug 6, 2026($1,523)
QMGC Q6long2Aug 6, 2026Aug 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.