Rewrite M-series: crypto trading engine + market prediction sims

The initial M-series specs were wrong (text digestion pipeline). Replaced
with the actual economy organ architecture:

  M0  hub (independent system, scoped autonomy, multi-layered braking)
  M1  Marketplace (multi-trader harness, deterministic law script, veto)
  M2  Data Feeds (RSS + live market, bridges Marketplace ↔ Sims)
  M3  Sims hub + 7 sub-specs (always-running, bounded predictions):
      M3a statistical, M3b sociological, M3c AMM/liquidity,
      M3d MEV/adversarial, M3e tokenomics/macro, M3f consensus/staking,
      M3g market microstructure
  M4  Wallets (sovereign custody, our keys only, 1:1 trader binding)
  M5  Traders (AI actors, wallet-bound, all tool calls monitored)
  M6  Conductor (supervisory AI, veto, pause/investigate, SAE intake)
  M7  SAE monitor (trader surveillance, Brain-compatible message format)

Grounded in AMM invariant mechanics, MEV game theory, SDE tokenomics,
and evolutionary consensus games. Tax stub for Verschwörern Veregeister.

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

core/docs/plans/M3c-amm-liquidity-sims.md

@@ -0,0 +1,66 @@
+# M3c — AMM & liquidity pool sims
+
+## 1. Component
+Automated Market Maker simulation: models **constant-product invariant mechanics, impermanent
+loss, and the non-cooperative game between liquidity providers and arbitrageurs**. Pops here are
+**LP positions and arbitrage bots** operating on the $x \cdot y = k$ curve. Grounded in the DEX/AMM
+literature [1,2].
+
+## 2. Status / certainty
+DESIGN-FIRST · ABSENT. Mathematical foundations C5 (constant product invariant is proven);
+impermanent loss formula C5 (closed-form: $\text{IL}(r) = \frac{2\sqrt{r}}{1+r} - 1$);
+simulation parameterization C1.
+
+## 3. Language & location
+TBD · `src/economy/sims/amm/`. Needs precise fixed-point or arbitrary-precision arithmetic for
+invariant calculations (Solidity-equivalent precision). Python, Rust, or Julia.
+
+## 4. Does / does-not
+- **Does:** simulate constant-product pools with fee parameter $\gamma$:
+  $(x + \gamma \Delta x)(y - \Delta y) = k$; model impermanent loss as a function of price ratio
+  shift $r$; simulate LP strategies (provide, withdraw, rebalance) against arbitrageur behavior;
+  model non-linear price slippage from the curve geometry; produce bounded predictions on pool
+  profitability, IL risk, and optimal LP ranges.
+- **Does-not:** model consensus mechanics (M3f); model social behavior (M3b); execute real swaps
+  (Marketplace does).
+
+## 5. Interface contract
+- Implements `query(PredictionQuery) -> BoundedPrediction` per M3 hub.
+- **Output bounds:** IL ranges and pool return intervals.
+  Example: `{ value: -0.034, lower_bound: -0.058, upper_bound: -0.012, confidence: 0.90,
+  time_horizon: "7d", sim_type: "amm_liquidity" }` — projected impermanent loss for ETH/USDC pool.
+  Example: `{ value: 0.082, lower_bound: 0.041, upper_bound: 0.127, confidence: 0.85,
+  time_horizon: "30d", sim_type: "amm_liquidity" }` — net LP return (fees − IL).
+- **Prediction types:** `impermanent_loss`, `pool_return`, `optimal_range`, `slippage_estimate`,
+  `lp_withdrawal_threshold`.
+- Calibration: ingests `dex_pool_state` and `price_tick` from M2.
+
+## 6. Dependencies & stubs
+- M2 Data Feeds — pool state and price data; *stub:* canned pool snapshots.
+- M3 Sims hub — lifecycle management; *stub:* manual init.
+
+## 7. Invariants / laws
+- **L1 (C5):** the **constant product invariant** $x \cdot y = k$ (adjusted for fees $\gamma$)
+  is the ground truth — all pool state transitions must satisfy the invariant or the sim is wrong.
+- **L2 (C5):** **impermanent loss** follows the proven formula
+  $\text{IL}(r) = \frac{2\sqrt{r}}{1+r} - 1$ — the sim must reproduce this exactly for the
+  base case (no fees, no concentrated liquidity).
+- **L3 (C4):** LP withdrawal thresholds are **derived from IL, not hardcoded** — the sim
+  calculates at what price ratio a rational LP withdraws, based on the IL formula and fee income.
+
+## 8. Build steps
+1. Implement the constant-product pool simulator with fee parameter.
+2. Verify IL formula reproduction against known inputs.
+3. Add LP pop strategies (passive hold, active rebalance, just-in-time liquidity).
+4. Add arbitrageur pops (sandwich, backrun).
+5. Wire M2 pool state data → calibration.
+
+## 9. Tests
+Invariant: every swap satisfies $(x + \gamma \Delta x)(y - \Delta y) = k$. IL formula: matches
+closed-form for known price ratios. Slippage: large swaps produce greater slippage than small.
+LP threshold: LP withdraws when IL exceeds fee income. Bounds: all outputs bounded.
+
+## 10. Open items
+- Concentrated liquidity (Uniswap v3 style) — extends the base model significantly.
+- Multi-pool routing (split swaps across pools).
+- Which specific pools to simulate (ETH/USDC? stablecoin pairs?).