About this skill

Problem It Addresses

Macro trading often collapses into narrative-following: price momentum is treated as fundamental evidence, while reflexive feedback between market perception and underlying conditions is ignored. Soros-style reflexivity is useful, but concepts such as fallibility and participating rarely translate into position sizing, stop-loss, and exit rules. This skill converts that judgment into a repeatable workflow, helping analysts identify dominant bias before choosing Long, Short, or Out in bubbles, crashes, geopolitical shocks, and credit cycles.

How It Works

The skill follows a five-step framework:
- Dominant bias identification: break down mainstream narratives, their assumptions, and the weakest premise, then score narrative confidence for contrarian setups.
- Reflexive loop mapping: classify cognitive-led versus participation-led loops and estimate feedback strength using F = price change% / fundamental change%.
- BISES quantification: score current account, inflation expectations, economic state, exit mechanisms, and sustainability, then derive a weighted reflexivity level.
- Super-cycle positioning: combine price deviation, leverage growth, and consensus tone to locate early, mid, or late stage and define a breaking point.
- Position and exit design: set max exposure, stop width, leverage cap, and force the maximum single-trade loss to stay within 2% of total capital.

Boundaries

It is suited to macro trends, turning points, bubbles and crashes, credit cycles, and fixed-exchange-rate stress. The output includes reflexive assessment, BISES score, super-cycle positioning, and a monitoring checklist. It is not a real-time data source or risk-management system; thresholds and historical parameters must be rechecked against current data, and low-liquidity assets, sudden policy shifts, and liquidity gaps can invalidate the signals.