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Research profile / Archived system

Gold H4 system

An archived gold-system project combining forecasting and risk controls. Later replay work revisited alternative historical configurations.

Archived systemImplementation privateNo current deployment claim
§Selected results
Read the full context ↗

Different systems.
Different outcomes.

Selected positive-return simulations, not live performance and not the complete research record. Ordered by source-reported Sharpe where available; other ratios are unranked. S17 and the deployed OU configuration are omitted from this view.

  1. Not Sharpe-rankedGold H4 · v1 configurationReported CAGR / vol: 0.92
Source-reported JSON · unvalidated

Gold H4 · v1 configuration

1 Jan 2026 — 21 Aug 2026
Costs excluded

Annualised return
Strategy+29.86%
S&P 500+19.61%
Strategy cumulative: +18.15% · 233 calendar daysGeometric extrapolation · not a forecast
Return / risk ratios
Strategy0.92
S&P 5001.39
Strategy: Reported CAGR / vol · NOT conventional SharpeS&P 500: daily Sharpe · √252 · risk-free rate 0
Maximum drawdown
Strategy-16.74%
S&P 500-9.10%
Strategy: based on saved observationsS&P 500: daily closes, including the pre-window baseline · not intraday lows

Strategy vs S&P 500

Matching window · annualised returns
Gold H4 · v1 configuration+29.86%
S&P 500+19.61%

S&P 500 cumulative: +12.11% · Cumulative gap: +6.04 percentage points above the index.

USD price return · dividends excluded. Recomputed from Yahoo Finance / ^GSPC ↗.

Read this comparison carefully. This is a market reference, not risk-matched alpha: assets, leverage and costs differ. The index excludes dividends; a total-return benchmark would differ. Strategy inputs are source-reported, not independently reconstructed.

Monthly return · partial first / last months
2026-01+14.17%
2026-02+6.05%
2026-030.00%
2026-04-1.64%
2026-05-0.79%
2026-060.00%
2026-070.00%
2026-080.00%

Only six recorded trades. Missing volume changes the leverage behaviour; fills approximate the signal-bar close.

Calculation & evidence Formulas, sources & conventions

Strategy evidence

Configuration:Gold H4 · v1 configuration

The archive calls this Sharpe, but its implementation divides annualised compounded return by daily volatility, not mean excess return by volatility. This is a CAGR/volatility ratio, NOT a conventional Sharpe ratio.

Source:02_gold_v1.json · Archived simulation — not live performance. Source files are retained privately; strategy parameters and execution logic are not published here.

Benchmark & annualisation

Daily observed trading-close returns: mean / sample standard deviation × √252; risk-free rate 0. USD price index, dividends excluded. Drawdown uses closing prices including the pre-window baseline, not intraday lows.

160 observed daily returns. Maximum drawdown peak: 27 Jan 2026; trough: 30 Mar 2026.

Baseline: 2025-12-31 close (6845.50); endpoint: 2026-08-21 close (7674.37). The last close before the window covers the opening holiday. Annualisation uses the same 233-day window as the strategy.

Annualised return = [(1 + cumulative return / 100)^(365 / days) − 1] × 100. Days include both stated dates, using UTC calendar days. Sub-year rates extrapolate the observed period; they are not earned one-year returns. Source-reported inputs remain unvalidated after annualisation. Monthly bars remain actual period returns, not annualised.

Selected results are not a combined portfolio or a complete track record. The ordering is by reported Sharpe values, not a harmonised performance ranking; costs, sample conventions and selection methods differ. OU and Gold use compounded-return/volatility ratios and are not Sharpe-ranked. Recomputing ledger arithmetic does not establish out-of-sample validity or an executable edge.

The research question

What does the model contribute beyond directional commodity exposure?

An archived gold-system project combining forecasting and risk controls. Later replay work revisited alternative historical configurations.

The technical work

Forecast and regime components, risk-aware sizing and comparative analysis of archived model variants.

The challenge is to connect the economic idea to a precise, reviewable experiment. Data transformations, the moment of a decision and the interpretation of the resulting return series all belong to that specification.

What to challenge

These are evaluation considerations for this domain, not a checklist presented as already passed.

  • Exposure and benchmark attribution
  • Contract and currency conventions
  • Regime stability and trade independence
  • Financing, spread and implementation assumptions

The data boundary

Commodity price histories and the instrument-specific costs needed to interpret a simulation.

Descriptions are intentionally high-level. Parameters, execution rules and non-public source data are not published here. Withholding an implementation is different from overstating its evidence.

The interesting question is not whether a backtest looks good. It is what would have to be true for the result to mean something.

For the broader framework, see validation. For the engineering context, see the research stack.

A technical conversation
starts here.

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