mirror of
https://github.com/SHOGGOTH-SECTOR/sica-fondt.git
synced 2026-08-01 08:30:20 +00:00
Set sim speed to 90:1 (1s wall = 90s sim) across all specs
Grounded ratio based on ABIDES/ECMWF benchmarks. Single global clock shared by all horizons. Wall time for full window: hourly ~40s, daily ~16min, weekly ~1.9hr, monthly ~8.3hr, annual ~4.2d, 5yr ~20.8d. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
This commit is contained in:
Claude
parent
e40210f570
commit
ab086e422b
@ -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.
|
||||
|
||||
@ -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 |
|
||||
|
||||
@ -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?).
|
||||
|
||||
@ -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?).
|
||||
|
||||
@ -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 |
|
||||
|
||||
@ -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).
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user