> For the complete documentation index, see [llms.txt](https://g-intel.gitbook.io/g-intel-docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://g-intel.gitbook.io/g-intel-docs/mie-meanverse-intelligence-engine/mie-historical-trading-performance.md).

# MIE Historical Trading Performance

Review MIE's historical trading performance from 2025 to 2026 across PG Markets and ProreX Limited, including monthly trading results and performance insights.

### Historical Trading Data | 2025–2026

**Performance Transparency Through Historical Trading Records**

The Meanverse Intelligence Engine (MIE) is developed around a systematic approach to trading execution, monitoring, and strategy evaluation.

GINTEL's Project Overview V1.2 presents historical trading-performance charts covering 2025 and 2026, with results displayed across two brokerage environments:

**PG Markets | ProreX Limited**

These charts provide a historical reference for reviewing the trading outcomes illustrated in the project presentation.

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### 2025 — Historical Trading Performance

#### Monthly Trading Results

The 2025 performance charts present monthly trading outcomes across the two brokerage environments.

The reported results include both positive and negative monthly changes, reflecting the variability of actual trading conditions.

**Brokerage Environments:**

* PG Markets
* ProreX Limited

*Insert Original 2025 Performance Charts Here*

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### 2026 — Historical Trading Performance

#### Monthly Trading Results

The 2026 charts provide an additional historical view of trading activity and monthly performance.

They are intended to illustrate the recorded outcomes shown in the October 2026 project presentation.

**Brokerage Environments:**

* PG Markets
* ProreX Limited

*Insert Original 2026 Performance Charts Here*

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### Understanding Historical Performance

Historical trading records are useful for reviewing past outcomes, but they should not be interpreted as guarantees of future performance.

Performance analysis should consider factors such as market volatility, execution conditions, transaction costs, position exposure, and changes in market behavior.

The charts in the project presentation do not, on their own, establish independently audited performance or a complete risk-adjusted performance record.

***

### Performance Disclosure

**Historical Performance Does Not Guarantee Future Results.**

Trading performance may vary significantly under different market conditions. Algorithmic systems remain exposed to financial-market risks, including the possibility of capital loss.

The performance information presented here is based on historical charts included in **GINTEL Project Overview V1.2, dated 9 October 2026**.

It should not be interpreted as a promise, forecast, or guarantee of future trading returns.