diff --git a/core/docs/plans/M3-sims-hub.md b/core/docs/plans/M3-sims-hub.md index f7fb02c..4574bd2 100644 --- a/core/docs/plans/M3-sims-hub.md +++ b/core/docs/plans/M3-sims-hub.md @@ -20,23 +20,23 @@ simulation cores. A query facade accessible to Traders. Each sim type (M3a–M3g different runtime suited to its math. ## 4. Does / does-not -- **Does:** tick-advance continuously at **≥ 360:1** (1 wall-second = 1 sim-hour minimum) +- **Does:** tick-advance continuously at **90:1** (1 wall-second = 90 simulated seconds) across **six concurrent time horizons** — tick/hourly, daily, weekly, monthly, annual, and 5-year forecast windows; every tick advances every sim; maintain populations of Pops whose behaviors emerge from the sim's mathematical model; ingest live data from Data Feeds (M2) for calibration; respond to Trader queries with bounded predictions; produce outputs with **explicit upper/lower bounds** on every prediction value. - | Horizon | Window | Speed (1s wall =) | Ratio | Wall time for window | - |---------|--------|-------------------|-------|---------------------| - | Tick–hourly | Next 1–60 min | 1h sim | 3,600:1 | <1s | - | Daily | Next 24h | 1d sim | 86,400:1 | 1s | - | Weekly | Next 7d | 1w sim | 604,800:1 | 1s | - | Monthly | Next 30d | 1d sim | 86,400:1 | 30s | - | Annual | Next 365d | 1w sim | 604,800:1 | ~52s | - | 5-year | Next 1825d | 1mo sim | 2,592,000:1 | ~60s | + | Horizon | Window | Wall time for window | + |---------|--------|---------------------| + | Tick–hourly | Next 1–60 min | ~40s | + | Daily | Next 24h | ~16 min | + | Weekly | Next 7d | ~1.9 hr | + | Monthly | Next 30d | ~8.3 hr | + | Annual | Next 365d | ~4.2 days | + | 5-year | Next 1825d | ~20.8 days | - **Does-not:** trade (Traders/Marketplace do); make decisions for traders (it informs, they decide); enforce laws (Marketplace does); supervise behavior (Conductor/SAE do); skip ticks; - run slower than 360:1. + run slower than 90:1. ## 5. Interface contract - `query(sim_type: SimType, query: PredictionQuery) -> BoundedPrediction`. @@ -61,10 +61,8 @@ different runtime suited to its math. - **L2 (C5):** every prediction output includes **explicit upper and lower bounds** — no unbounded point estimates. Uncertainty is a first-class value, not an afterthought. - **L3 (C5):** all sims are **tick-advanced and continuous** — they advance every tick, never - skip. Each time horizon runs at its own rated speed (see §4 table). Hourly through weekly - cover their full window in ≤ 1 wall-second; monthly through 5-year dial down to coarser - ticks (daily/weekly/monthly steps) and take 30–60 wall-seconds for a full window pass. - No horizon may run slower than its rated speed. + skip. Global sim speed: **1 wall-second = 90 simulated seconds** (90:1). All horizons share + this clock. No sim may run slower than 90:1. - **L4 (C4):** sims are **read-only from traders' perspective** — a query never mutates sim state. Calibration happens only from Data Feeds (M2). - **L5 (C4):** each sim type is **independent** — failure in one sim does not cascade to others. diff --git a/core/docs/plans/M3c-amm-liquidity-sims.md b/core/docs/plans/M3c-amm-liquidity-sims.md index e64d46e..eff6850 100644 --- a/core/docs/plans/M3c-amm-liquidity-sims.md +++ b/core/docs/plans/M3c-amm-liquidity-sims.md @@ -31,7 +31,7 @@ invariant calculations (Solidity-equivalent precision). Python, Rust, or Julia. 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). -- **Time-horizon mapping** (all run concurrently, tick-advanced, ≥ 360:1 (1s wall = 1h sim)): +- **Time-horizon mapping** (all run concurrently, tick-advanced, 90:1 (1s wall = 90s sim)): | Horizon | Primary models | Update cadence | |---------|---------------|----------------| | Tick–hourly | Slippage curves, invariant state, JIT liquidity | Every swap event | diff --git a/core/docs/plans/M3d-mev-adversarial-sims.md b/core/docs/plans/M3d-mev-adversarial-sims.md index f5db7e5..013b3bb 100644 --- a/core/docs/plans/M3d-mev-adversarial-sims.md +++ b/core/docs/plans/M3d-mev-adversarial-sims.md @@ -47,7 +47,7 @@ and bilevel optimization (DSMFG). Python, Rust, or Julia. - Implements `query(PredictionQuery) -> BoundedPrediction` per M3 hub. - **Output bounds:** extraction probability ranges, gas cost intervals, cross-chain profit bounds, DSMFG equilibrium stability ranges. -- **Time-horizon mapping** (all run concurrently, tick-advanced, ≥ 360:1 (1s wall = 1h sim)): +- **Time-horizon mapping** (all run concurrently, tick-advanced, 90:1 (1s wall = 90s sim)): | Horizon | Primary models | Update cadence | |---------|---------------|----------------| | Tick–hourly | PGA auctions, sandwich detection, cross-chain arb | Every block | @@ -103,7 +103,7 @@ under gas limit. Sandwich: known sandwich-vulnerable trade flagged; non-vulnerab Cross-chain: inventory path preferred when latency advantage exceeds capital cost. DSMFG: leader policy converges to fixed point with follower equilibrium. Kolokoltsov: WENO captures shock discontinuities in adversarial strategy distribution. Bounds: all outputs bounded. Pre-trade: -query does not submit any transaction. Speed: sim tick-advances ≥ 360:1 (1s wall = 1h sim). +query does not submit any transaction. Speed: sim tick-advances at 90:1. ## 10. Open items - Mempool data access (public mempool? private order flow?). diff --git a/core/docs/plans/M3e-tokenomics-macro-sims.md b/core/docs/plans/M3e-tokenomics-macro-sims.md index e2cdf4d..4f6ba52 100644 --- a/core/docs/plans/M3e-tokenomics-macro-sims.md +++ b/core/docs/plans/M3e-tokenomics-macro-sims.md @@ -6,7 +6,7 @@ burns, inflation), lending protocol dynamics, DeFi systemic risk, and stock-flow stochastic differential equations (SDEs), state-space models, kinked interest rate curves, and inter-protocol credit exposure networks. Pops here are **aggregate behavioral cohorts** (miners/validators, holders, speculators, protocol treasuries, borrowers/lenders) whose collective -behavior drives token-level dynamics across **six concurrent time horizons** at tick-advanced, ≥ 360:1 (1s wall = 1h sim). +behavior drives token-level dynamics across **six concurrent time horizons** at tick-advanced, 90:1 (1s wall = 90s sim). Grounded in Vienna complex-systems token modeling [7], ResearchGate engineering token economy frameworks [6], Aave/Compound kinked interest rate models (industry standard), and DeXposure @@ -49,7 +49,7 @@ Julia (DifferentialEquations.jl), Python (scipy), or Octave. ## 5. Interface contract - Implements `query(PredictionQuery) -> BoundedPrediction` per M3 hub. - **Output bounds:** SDE confidence bands, utilization rate ranges, contagion impact intervals. -- **Time-horizon mapping** (all run concurrently, tick-advanced, ≥ 360:1 (1s wall = 1h sim)): +- **Time-horizon mapping** (all run concurrently, tick-advanced, 90:1 (1s wall = 90s sim)): | Horizon | Primary models | Update cadence | |---------|---------------|----------------| | Hourly | Lending rates, utilization, liquidation risk | Every block | @@ -107,7 +107,7 @@ Lending: rate curve exhibits kink at $U_{\text{opt}}$; liquidation cascades trig collateral ratio breached. DeXposure: shock to protocol A propagates to protocol B through shared collateral; isolated protocols unaffected. Yield: optimizer rebalances toward highest risk-adjusted APY. Calibration: state estimate converges to observed data. Bounds: SDE confidence bands cover -realized paths on backtest. Speed: sim tick-advances ≥ 360:1 (1s wall = 1h sim). +realized paths on backtest. Speed: sim tick-advances at 90:1. ## 10. Open items - Which tokens to model initially (ETH? BTC? a specific alt?). diff --git a/core/docs/plans/M3f-consensus-staking-sims.md b/core/docs/plans/M3f-consensus-staking-sims.md index 1dd8b56..d807da5 100644 --- a/core/docs/plans/M3f-consensus-staking-sims.md +++ b/core/docs/plans/M3f-consensus-staking-sims.md @@ -27,7 +27,7 @@ computation. Python, Julia, or R. $-\partial_t u + H(x, \nabla u) = F(x, m)$, $\partial_t m - \nabla \cdot (m \nabla_p H) = 0$ — captures emergent staking coordination without enumerating every validator; predict slashing risk, validator set stability, and staking yield across **six concurrent time horizons** at - tick-advanced, ≥ 360:1 (1s wall = 1h sim); produce bounded predictions on consensus health and staking returns. + tick-advanced, 90:1 (1s wall = 90s sim); produce bounded predictions on consensus health and staking returns. - **Does-not:** validate blocks (this is a simulator); model AMM pools (M3c); model token supply (M3e — but consumes staking ratio from M3e as input). @@ -39,7 +39,7 @@ computation. Python, Julia, or R. equilibrium. Example: `{ value: 4.2, lower_bound: 3.6, upper_bound: 5.1, confidence: 0.82, time_horizon: "30d", sim_type: "consensus_staking" }` — annualized staking yield (%). -- **Time-horizon mapping** (all run concurrently, tick-advanced, ≥ 360:1 (1s wall = 1h sim)): +- **Time-horizon mapping** (all run concurrently, tick-advanced, 90:1 (1s wall = 90s sim)): | Horizon | Primary models | Update cadence | |---------|---------------|----------------| | Hourly | Markov chain validator state transitions | Every epoch | diff --git a/core/docs/plans/M3g-market-microstructure-sims.md b/core/docs/plans/M3g-market-microstructure-sims.md index 5549bdb..78da588 100644 --- a/core/docs/plans/M3g-market-microstructure-sims.md +++ b/core/docs/plans/M3g-market-microstructure-sims.md @@ -7,7 +7,7 @@ optimal execution, and cross-exchange arbitrage** at the fastest time scales. Po **Almgren-Chriss optimal execution framework** for minimizing market impact of large orders. Operates at the highest temporal resolution — where M3a provides statistical forecasts and M3c models pool mechanics, M3g models the *plumbing* of how orders actually execute, across **six -concurrent time horizons** at tick-advanced, ≥ 360:1 (1s wall = 1h sim). +concurrent time horizons** at tick-advanced, 90:1 (1s wall = 90s sim). ## 2. Status / certainty DESIGN-FIRST · ABSENT. Order-book microstructure theory C4 (established). Almgren-Chriss @@ -36,7 +36,7 @@ Python with optimized event loop. ## 5. Interface contract - Implements `query(PredictionQuery) -> BoundedPrediction` per M3 hub. - **Output bounds:** execution cost ranges, liquidity intervals, optimal trajectory envelopes. -- **Time-horizon mapping** (all run concurrently, tick-advanced, ≥ 360:1 (1s wall = 1h sim)): +- **Time-horizon mapping** (all run concurrently, tick-advanced, 90:1 (1s wall = 90s sim)): | Horizon | Primary models | Update cadence | |---------|---------------|----------------| | Tick–hourly | Almgren-Chriss execution, slippage, spread, arb decay | Every tick | @@ -90,7 +90,7 @@ Slippage: larger orders produce greater slippage. Spread: spread widens under ad Almgren-Chriss: optimal trajectory minimizes total cost vs. naive execution on backtest; impact parameters update when market conditions change. Arb decay: detected arb opportunity closes over time. Depth: depth profile matches order book state. Bounds: all outputs bounded. Resolution: -predictions update at tick frequency. Speed: sim tick-advances ≥ 360:1 (1s wall = 1h sim). +predictions update at tick frequency. Speed: sim tick-advances at 90:1. ## 10. Open items - CEX order book data access (API limitations, costs).