diff --git a/core/docs/plans/M0-economy-organ-hub.md b/core/docs/plans/M0-economy-organ-hub.md index d4eeccf..04cc588 100644 --- a/core/docs/plans/M0-economy-organ-hub.md +++ b/core/docs/plans/M0-economy-organ-hub.md @@ -23,11 +23,13 @@ TBD · new location e.g. `src/economy/`. The organ is polyglot by nature: tradin ## 4. Does / does-not - **Does:** host crypto/NFT trading via the Marketplace (M1); run always-on market prediction Sims (M3) fed by live Data Feeds (M2); manage sovereign-custody Wallets (M4); supervise - Traders (M5) via a Conductor (M6) and SAE monitor (M7); collect taxes on trader income and - stub transfer to Verschwörern Veregeister wallets. + Traders (M5) via a Conductor (M6); guard against anomalies via SAE monitor (M7); collect taxes + on trader income and stub transfer to Verschwörern Veregeister wallets; maintain a **ledger of + economy-related memories and patterns** (trade history, learned market patterns, calibration + state). - **Does-not:** consult the organism's Brain for trade decisions (scoped autonomy); route around - Ada for organism-bound messages (S1); store organism memories (E*); act as the organism's - conscience (that's Eth-Int / A6). + Ada for organism-bound messages (S1); store **organism** memories (E*) — economy-specific + memories stay local; act as the organism's conscience (that's Eth-Int / A6). ## 5. Interface contract - **Ichor interface (outbound):** `Envelope(Stomach, AdaBorder, OrganSecretion, payload)` — market @@ -35,14 +37,15 @@ TBD · new location e.g. `src/economy/`. The organ is polyglot by nature: tradin - **Ichor interface (inbound):** organism directives arrive via Ichor (e.g. risk posture changes, budget adjustments from A2 energy). - **Internal wiring:** Marketplace (M1) ↔ Data Feeds (M2) ↔ Sims (M3). Wallets (M4) bind to - Traders (M5). Conductor (M6) supervises Traders via SAE (M7). All trader actions route through - Marketplace. + Traders (M5). Conductor (M6) supervises Traders (M5). SAE (M7) acts as an independent + antivirus / guarddog / alarm bell — monitors via Ichor-routed messages and alerts M6. + All trader actions route through Marketplace. - **Tax stub:** `transfer_tax(amount, source_wallet, dest_wallet) -> receipt` — automation hook for Verschwörern Veregeister internal wallet-to-wallet transfer. **Out of scope** — stub only. ## 6. Dependencies & stubs - Ichor bus (D2) — existing `Broker` + `Envelope`. -- Ada border (D1) — screens outbound organism messages; *stub:* Ichor `Barrier`. +- Ada border (D1) — outbound economy envelopes cross here (S1); *stub:* Ichor `Barrier`. - A2 energy — potential consumer of economic signals; *stub:* no integration initially. - Verschwörern Veregeister wallets — tax destination; *stub:* log transfer, no real wallet. @@ -58,10 +61,10 @@ TBD · new location e.g. `src/economy/`. The organ is polyglot by nature: tradin SAE surveillance (M7), and wallet-level limits (M4) each independently constrain risk. ## 8. Build steps -1. Define the internal wiring topology (how M1–M7 connect). +1. Build sub-components (M1–M7) individually — each with defined success criteria and ablative tests. 2. Extend the existing `Stomach` primitive in Ichor to carry the hub facade. -3. Wire sub-components as their specs land. -4. Implement the tax stub for Verschwörern Veregeister transfer. +3. Define internal wiring topology and connect tested sub-components. +4. Implement tax stub and Verschwörern Veregeister transfer last. ## 9. Tests Hub smoke: Marketplace reachable; Sims running and queryable; Wallet bound to Trader; Conductor diff --git a/core/docs/plans/M1-marketplace.md b/core/docs/plans/M1-marketplace.md index 903c583..de91c84 100644 --- a/core/docs/plans/M1-marketplace.md +++ b/core/docs/plans/M1-marketplace.md @@ -23,7 +23,9 @@ signing (M4), and the Conductor (M6). Deterministic law script must be auditable (Wallets do); supervise behavior (Conductor + SAE do). ## 5. Interface contract -- `submit_action(trader_id, action: MarketAction, wallet_id) -> { accepted | vetoed | law_violation | no_wallet }`. +- `submit_action(trader_id, action: MarketAction, wallet_id) -> { succeeded | failed }`. + Diagnostic reasons (law violation, veto, missing wallet) are internal — routed to Conductor + (M6) for upstream output. Immune system is a separate organ (out of scope here). `MarketAction` ∈ { `buy`, `sell`, `mint`, `provide_liquidity`, `withdraw_liquidity`, `claim_rewards`, … }. - `law_check(action: MarketAction) -> { pass | violation(rule_id, reason) }` — deterministic, pure function. The law script is loaded at startup and **immutable at runtime** (mirrors S3 / @@ -35,18 +37,19 @@ signing (M4), and the Conductor (M6). Deterministic law script must be auditable - `tax_event(trader_id, income_amount) -> receipt` — triggers tax collection. ## 6. Dependencies & stubs -- M4 Wallets — signing + execution; *stub:* mock wallet that logs transactions. -- M5 Traders — action source; *stub:* canned trade requests. -- M6 Conductor — veto authority; *stub:* always-approve. -- M7 SAE — action log consumer; *stub:* print actions. -- Blockchain RPCs — on-chain execution; *stub:* simulated chain responses. +- M4 Wallets — signing + execution; *stub:* "if finished, would sign and broadcast tx [details]". +- M5 Traders — action source; *stub:* "if finished, would submit [action] for [asset] at [price]". +- M6 Conductor — veto authority; *stub:* "if finished, would evaluate [action] against risk policy; approving". +- M7 SAE — action log consumer; *stub:* "if finished, would analyze [action] for behavioral anomalies". +- Blockchain RPCs — on-chain execution; *stub:* "if finished, would execute [action] on [chain], returning tx_hash". ## 7. Invariants / laws - **L1 (C5):** **all market actions route through the Marketplace** — no direct on-chain execution by any trader. This is the economy organ's S1. - **L2 (C5):** the **deterministic law script is immutable at runtime** — loaded at startup, never modified by traders, conductor, or sims. Changes require a restart with a new script - version. Mirrors the COBOL vault (S3). + version **and a pair of signatures from the operator and the Homunculus**. Mirrors the COBOL + vault (S3). - **L3 (C4):** **no wallet, no access** — a trader without a bound wallet cannot submit actions. The Marketplace enforces this before any other check. - **L4 (C4):** **veto is checked after law, before execution** — law violations are rejected @@ -73,3 +76,4 @@ Tax: income event triggers tax stub. Immutability: law script cannot be modified - Position limits, drawdown stops, and other risk parameters — live in the law script or in the Conductor's judgment? - Tax rate / calculation method (fixed %, tiered, per-asset?). +- Non-Turing law script design — to discuss (format, expressiveness, bounds). diff --git a/core/docs/plans/M2-data-feeds.md b/core/docs/plans/M2-data-feeds.md index c2750c5..dcde588 100644 --- a/core/docs/plans/M2-data-feeds.md +++ b/core/docs/plans/M2-data-feeds.md @@ -11,7 +11,7 @@ DESIGN-FIRST · ABSENT. Role C3; implementation C1. ## 3. Language & location TBD · `src/economy/feeds/`. Needs async I/O for streaming data (WebSockets, SSE, RSS polling). -Pony actors are a natural fit (async, backpressure-aware). Python or Rust for API client libs. +Pony actors are a natural fit (async, backpressure-aware). ## 4. Does / does-not - **Does:** ingest live market data from external sources (RSS, price APIs, DEX subgraphs, @@ -30,8 +30,8 @@ Pony actors are a natural fit (async, backpressure-aware). Python or Rust for AP - `query_history(feed_type, time_range) -> [NormalizedDatum]` — sims and traders can pull historical data within the session window. - `NormalizedDatum { feed_type, source, timestamp, payload, confidence }` — common shape. - `confidence` ∈ [0.0, 1.0] — data source reliability (exchange-reported price = high; RSS - sentiment = lower). + `confidence` ∈ [0.0, 10.0] — data source reliability per position produced (exchange-reported + price = high; RSS sentiment = lower). Sims produce even finer-grained confidence. ## 6. Dependencies & stubs - External data sources (price APIs, RSS, RPC nodes) — *stub:* canned market data replay. diff --git a/core/docs/plans/M3-sims-hub.md b/core/docs/plans/M3-sims-hub.md index 7882039..44bfaf8 100644 --- a/core/docs/plans/M3-sims-hub.md +++ b/core/docs/plans/M3-sims-hub.md @@ -15,9 +15,9 @@ DESIGN-FIRST · ABSENT. Role C3; implementation C1. Mathematical foundations C4 established); specific model parameters C1. ## 3. Language & location -TBD · `src/economy/sims/`. Numerical computing (Julia, Python/NumPy, Octave, or Rust) for the -simulation cores. A query facade accessible to Traders. Each sim type (M3a–M3g) may use a -different runtime suited to its math. +TBD · `src/economy/sims/`. Numerical computing (Julia, Octave, Fortran, R, Solidity, or C++) +for the simulation cores. A query facade accessible to Traders. Each sim type (M3a–M3g) may use +a different runtime suited to its math. ## 4. Does / does-not - **Does:** tick-advance continuously at **90:1** (1 wall-second = 90 simulated seconds) @@ -29,11 +29,11 @@ different runtime suited to its math. | Horizon | Window | Tick step | Effective ratio | Wall time for window | |---------|--------|-----------|-----------------|---------------------| | Tick–hourly | Next 1–60 min | 1s | 90:1 | ~40s | - | Daily | Next 24h | 1 min | 5,400:1 | ~16s | - | Weekly | Next 7d | 10 min | 54,000:1 | ~11s | - | Monthly | Next 30d | 1 hr | 324,000:1 | ~8s | - | Annual | Next 365d | 6 hr | 1,944,000:1 | ~16s | - | 5-year | Next 1825d | 1 day | 7,776,000:1 | ~20s | + | Daily | Next 24h | 24s | 2,160:1 | ~40s | + | Weekly | Next 7d | ~3 min | 15,120:1 | ~40s | + | Monthly | Next 30d | 12 min | 64,800:1 | ~40s | + | Annual | Next 365d | ~2.5 hr | ~788,000:1 | ~40s | + | 5-year | Next 1825d | 12 hr | ~3,942,000:1 | ~40s | - **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 90:1. @@ -44,7 +44,10 @@ different runtime suited to its math. `tokenomics_macro`, `consensus_staking`, `market_microstructure` } (M3a–M3g). - `BoundedPrediction { value, lower_bound, upper_bound, confidence, time_horizon, sim_type, timestamp }`. Every output is bounded — no point estimates without uncertainty ranges. - Example: `{ value: 7.2, lower_bound: 5.8, upper_bound: 8.9, confidence: 0.73, + `confidence` ∈ [0.00, 10.00] — printed as `7.62/10.00`. Gain rates print as + `lower - value - upper / 10.00` (e.g. `2.31 - 4.44 - 7.11 / 10.00 gain over next 30 days`); + the denominator aids legibility — gain is not capped at 10.00. + Example: `{ value: 7.2, lower_bound: 5.8, upper_bound: 8.9, confidence: 7.30, time_horizon: "4h", sim_type: "amm_liquidity" }`. - `status(sim_type?) -> { running, pop_count, last_calibration, data_freshness }` — health check. - `calibrate(sim_type, feed_data: [NormalizedDatum])` — Data Feeds (M2) pushes live data for @@ -62,8 +65,9 @@ different runtime suited to its math. unbounded point estimates. Uncertainty is a first-class value, not an afterthought. - **L3 (C5):** all sims are **tick-advanced and continuous** — fine-grained ticks (RTS-style). Base speed **90:1** (1s wall = 90s sim). Longer horizons run at higher velocity with coarser - steps and update less frequently. Each horizon runs **in parallel** — they are concurrent, - not sequential. No horizon runs slower than 90:1. + steps and update less frequently. Each horizon completes its forecast window in **~40s wall + time**. Each horizon runs **in parallel** — they are concurrent, not sequential. No horizon + runs 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/M3a-statistical-sims.md b/core/docs/plans/M3a-statistical-sims.md index 896c298..d54c0e2 100644 --- a/core/docs/plans/M3a-statistical-sims.md +++ b/core/docs/plans/M3a-statistical-sims.md @@ -16,10 +16,10 @@ execution C5 (industry standard since 2001). Jump-diffusion C5 (Merton 1976). Pa for crypto markets C1. ## 3. Language & location -TBD · `src/economy/sims/statistical/`. Python (NumPy/SciPy), Julia, or R for numerical -computing. Needs efficient matrix operations, SDE solvers, and distribution sampling. Fractional -Brownian motion generation requires specialized libraries (e.g. `fbm` in Python, or spectral -methods). +TBD · `src/economy/sims/statistical/`. Julia, R, Fortran, or Octave for numerical computing. +Needs efficient matrix operations, SDE solvers, and distribution sampling. Fractional Brownian +motion generation uses spectral methods (Hosking 1984, Wood & Chan 1994) or Cholesky +decomposition of the covariance matrix. ## 4. Does / does-not - **Does:** run Monte Carlo price simulations (GBM, Merton jump-diffusion, Heston stochastic @@ -52,11 +52,11 @@ methods). | Weekly–monthly | Jump-diffusion Monte Carlo, regime-conditional forecasts | Hourly roll | | Annual–5yr | SDE mean-reversion long-run $\theta$, macro regime priors | Daily roll | - Examples: - `{ value: 1847.30, lower_bound: 1790.15, upper_bound: 1905.60, confidence: 0.95, + `{ value: 1847.30, lower_bound: 1790.15, upper_bound: 1905.60, confidence: 9.50, time_horizon: "24h", sim_type: "statistical" }` — 95% CI on ETH price. - `{ value: 0.72, lower_bound: 0.58, upper_bound: 0.89, confidence: 0.90, + `{ value: 0.72, lower_bound: 0.58, upper_bound: 0.89, confidence: 9.00, time_horizon: "1h", sim_type: "statistical" }` — Heston instantaneous vol $\sqrt{\nu_t}$. - `{ value: "bear", lower_bound: null, upper_bound: null, confidence: 0.83, + `{ value: "bear", lower_bound: null, upper_bound: null, confidence: 8.30, time_horizon: "current", sim_type: "statistical" }` — HMM regime state. - **Prediction types:** `price_forecast`, `volatility_surface`, `var_calculation`, `correlation_matrix`, `regime_state`, `rough_vol_estimate`, `jump_intensity`. @@ -68,10 +68,12 @@ methods). ## 7. Invariants / laws - **L1 (C5):** bounds are **statistical confidence intervals** — derived from the model's - distribution, not hand-picked. The confidence level (e.g. 0.95) is explicit in the output. -- **L2 (C5):** **six time horizons run concurrently** — tick-level rough vol, hourly regime - detection, daily Heston surface, weekly Monte Carlo, annual mean-reversion, and 5-year macro - forecasts coexist; none blocks the others. + distribution, not hand-picked. Three distinct metrics in every output: **confidence** (how sure + the model is of this prediction), **correctness** (how accurate the model has been historically), + and **certainty** (how stable the estimate is across perturbations). All on the 0.00–10.00 scale. +- **L2 (C5):** **six time horizons run concurrently** — models span multiple horizons (e.g. + Monte Carlo runs daily and annual, rough vol runs tick and hourly, Heston runs daily and + weekly). All coexist; none blocks the others. - **L3 (C4):** model parameters are **re-estimated on each calibration** from live data — no stale parameters carried across regime changes. Regime transitions trigger immediate re-estimation of conditional parameters. diff --git a/core/docs/plans/M3b-sociological-sims.md b/core/docs/plans/M3b-sociological-sims.md index 79b6d23..f2e17c8 100644 --- a/core/docs/plans/M3b-sociological-sims.md +++ b/core/docs/plans/M3b-sociological-sims.md @@ -17,9 +17,9 @@ solvers C3). Crypto pump-and-dump ABM C3 (3-agent protocol validated on historic Pop behavioral models C1. ## 3. Language & location -TBD · `src/economy/sims/sociological/`. Agent-based modeling frameworks (Mesa/Python, NetLogo, -or custom). Needs efficient population iteration, strategy mutation, PDE solvers for MFG -(HJB + Fokker-Planck), and bandit algorithms (UCB/Thompson). +TBD · `src/economy/sims/sociological/`. Agent-based modeling frameworks (NetLogo, or custom). +Needs efficient population iteration, strategy mutation, PDE solvers for MFG (HJB + +Fokker-Planck), and bandit algorithms (UCB/Thompson). Julia, R, or Fortran. ## 4. Does / does-not - **Does:** simulate populations of behavioral archetypes competing in a market; apply @@ -59,14 +59,16 @@ or custom). Needs efficient population iteration, strategy mutation, PDE solvers | Annual | Long-run evolutionary stable strategies (ESS) | Monthly roll | | 5-year | MFG stationary equilibria, structural population shifts | Quarterly roll | - Examples: - `{ value: 7.3, lower_bound: 5.0, upper_bound: 9.1, confidence: 0.68, + `{ value: 7.3, lower_bound: 5.0, upper_bound: 9.1, confidence: 6.80, time_horizon: "12h", sim_type: "sociological" }` — herd-panic index (0–10). - `{ value: 0.42, lower_bound: 0.31, upper_bound: 0.55, confidence: 0.72, + `{ value: 0.42, lower_bound: 0.31, upper_bound: 0.55, confidence: 7.20, time_horizon: "1w", sim_type: "sociological" }` — fraction of pops in "contrarian" strategy. - `{ value: "promotion", lower_bound: null, upper_bound: null, confidence: 0.61, + `{ value: "promotion", lower_bound: null, upper_bound: null, confidence: 6.10, time_horizon: "current", sim_type: "sociological" }` — pump-and-dump phase detection. - `{ value: 0.78, lower_bound: 0.65, upper_bound: 0.88, confidence: 0.70, + `{ value: 0.78, lower_bound: 0.65, upper_bound: 0.88, confidence: 7.00, time_horizon: "30d", sim_type: "sociological" }` — MFG equilibrium stability index. + Models span multiple horizons — e.g. replicator dynamics runs hourly through annual; MFG + produces weekly equilibria and 5-year stationary states. The table shows primary assignments. - **Prediction types:** `sentiment_index`, `herd_threshold`, `strategy_distribution`, `cascade_probability`, `coordination_stability`, `opinion_cluster_count`, `pump_dump_phase`, `mfg_equilibrium_stability`, `narrative_regime`. diff --git a/core/docs/plans/M3c-amm-liquidity-sims.md b/core/docs/plans/M3c-amm-liquidity-sims.md index eff6850..e91701b 100644 --- a/core/docs/plans/M3c-amm-liquidity-sims.md +++ b/core/docs/plans/M3c-amm-liquidity-sims.md @@ -13,7 +13,8 @@ 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. +invariant calculations. Solidity for on-chain-equivalent precision; Julia or Octave for +analytical models. ## 4. Does / does-not - **Does:** simulate constant-product pools with fee parameter $\gamma$: @@ -27,9 +28,9 @@ invariant calculations (Solidity-equivalent precision). Python, Rust, or Julia. ## 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, + Example: `{ value: -0.034, lower_bound: -0.058, upper_bound: -0.012, confidence: 9.00, 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, + Example: `{ value: 0.082, lower_bound: 0.041, upper_bound: 0.127, confidence: 8.50, time_horizon: "30d", sim_type: "amm_liquidity" }` — net LP return (fees − IL). - **Time-horizon mapping** (all run concurrently, tick-advanced, 90:1 (1s wall = 90s sim)): | Horizon | Primary models | Update cadence | diff --git a/core/docs/plans/M3d-mev-adversarial-sims.md b/core/docs/plans/M3d-mev-adversarial-sims.md index 013b3bb..ba0128e 100644 --- a/core/docs/plans/M3d-mev-adversarial-sims.md +++ b/core/docs/plans/M3d-mev-adversarial-sims.md @@ -19,9 +19,9 @@ optimization C3 (emerging — SMFRL solvers); Kolokoltsov adversarial C3 (non-li WENO discretization established but crypto application novel). Parameterization C1. ## 3. Language & location -TBD · `src/economy/sims/mev/`. Needs combinatorial optimization (PuLP/OR-Tools for knapsack), +TBD · `src/economy/sims/mev/`. Needs combinatorial optimization (OR-Tools for knapsack), continuous-time auction modeling, PDE solvers (WENO for shock-capturing in adversarial dynamics), -and bilevel optimization (DSMFG). Python, Rust, or Julia. +and bilevel optimization (DSMFG). Julia, Fortran, or C++. ## 4. Does / does-not - **Does:** simulate Priority Gas Auctions where multiple searcher bots compete for the same @@ -57,11 +57,11 @@ and bilevel optimization (DSMFG). Python, Rust, or Julia. | Annual | Kolokoltsov adversarial long-run dynamics | Monthly roll | | 5-year | Structural MEV regime shifts, protocol-level policy effects | Quarterly roll | - Examples: - `{ value: 0.23, lower_bound: 0.11, upper_bound: 0.38, confidence: 0.80, + `{ value: 0.23, lower_bound: 0.11, upper_bound: 0.38, confidence: 8.00, time_horizon: "next_block", sim_type: "mev_adversarial" }` — sandwich probability. - `{ value: 14.7, lower_bound: 8.2, upper_bound: 22.5, confidence: 0.75, + `{ value: 14.7, lower_bound: 8.2, upper_bound: 22.5, confidence: 7.50, time_horizon: "next_block", sim_type: "mev_adversarial" }` — optimal gas bid (gwei). - `{ value: 0.034, lower_bound: 0.018, upper_bound: 0.052, confidence: 0.82, + `{ value: 0.034, lower_bound: 0.018, upper_bound: 0.052, confidence: 8.20, time_horizon: "1h", sim_type: "mev_adversarial" }` — cross-chain arb profit (ETH). - **Prediction types:** `sandwich_probability`, `frontrun_risk`, `optimal_gas_bid`, `block_inclusion_probability`, `mev_exposure`, `cross_chain_arb_profit`, diff --git a/core/docs/plans/M3e-tokenomics-macro-sims.md b/core/docs/plans/M3e-tokenomics-macro-sims.md index 4f6ba52..35e80f6 100644 --- a/core/docs/plans/M3e-tokenomics-macro-sims.md +++ b/core/docs/plans/M3e-tokenomics-macro-sims.md @@ -21,7 +21,7 @@ composable yield optimization C4 (Yearn v3, Beefy, production-validated). Specif ## 3. Language & location TBD · `src/economy/sims/tokenomics/`. Needs SDE solvers (Euler-Maruyama, Milstein), state-space estimation, and VAR (vector autoregression) for credit exposure impulse responses. -Julia (DifferentialEquations.jl), Python (scipy), or Octave. +Julia (DifferentialEquations.jl) or Octave. ## 4. Does / does-not - **Does:** simulate token state dynamics via the SDE framework: @@ -59,13 +59,13 @@ Julia (DifferentialEquations.jl), Python (scipy), or Octave. | Annual | Halving/burn policy impacts, inflation trajectory | Monthly roll | | 5-year | Token supply long-run equilibrium, protocol lifecycle | Quarterly roll | - Examples: - `{ value: 2.1, lower_bound: 1.4, upper_bound: 3.2, confidence: 0.90, + `{ value: 2.1, lower_bound: 1.4, upper_bound: 3.2, confidence: 9.00, time_horizon: "90d", sim_type: "tokenomics_macro" }` — annualized inflation rate (%). - `{ value: 0.67, lower_bound: 0.58, upper_bound: 0.74, confidence: 0.85, + `{ value: 0.67, lower_bound: 0.58, upper_bound: 0.74, confidence: 8.50, time_horizon: "30d", sim_type: "tokenomics_macro" }` — staking ratio. - `{ value: 0.83, lower_bound: 0.78, upper_bound: 0.91, confidence: 0.88, + `{ value: 0.83, lower_bound: 0.78, upper_bound: 0.91, confidence: 8.80, time_horizon: "1h", sim_type: "tokenomics_macro" }` — Aave ETH utilization rate. - `{ value: 0.12, lower_bound: 0.04, upper_bound: 0.25, confidence: 0.72, + `{ value: 0.12, lower_bound: 0.04, upper_bound: 0.25, confidence: 7.20, time_horizon: "7d", sim_type: "tokenomics_macro" }` — systemic contagion risk index. - **Prediction types:** `supply_trajectory`, `inflation_rate`, `staking_ratio`, `velocity_estimate`, `halving_impact`, `treasury_runway`, `utilization_rate`, diff --git a/core/docs/plans/M3f-consensus-staking-sims.md b/core/docs/plans/M3f-consensus-staking-sims.md index d807da5..4836ccb 100644 --- a/core/docs/plans/M3f-consensus-staking-sims.md +++ b/core/docs/plans/M3f-consensus-staking-sims.md @@ -15,7 +15,7 @@ simulation parameterization C1. ## 3. Language & location TBD · `src/economy/sims/consensus/`. Needs Markov chain solvers and game-theoretic equilibrium -computation. Python, Julia, or R. +computation. Julia, R, or Fortran. ## 4. Does / does-not - **Does:** simulate validator populations where honesty evolves via **evolutionary game theory** @@ -34,10 +34,10 @@ computation. Python, Julia, or R. ## 5. Interface contract - Implements `query(PredictionQuery) -> BoundedPrediction` per M3 hub. - **Output bounds:** equilibrium stability ranges and yield intervals. - Example: `{ value: 0.89, lower_bound: 0.82, upper_bound: 0.94, confidence: 0.88, + Example: `{ value: 0.89, lower_bound: 0.82, upper_bound: 0.94, confidence: 8.80, time_horizon: "7d", sim_type: "consensus_staking" }` — fraction of validators honest in equilibrium. - Example: `{ value: 4.2, lower_bound: 3.6, upper_bound: 5.1, confidence: 0.82, + Example: `{ value: 4.2, lower_bound: 3.6, upper_bound: 5.1, confidence: 8.20, time_horizon: "30d", sim_type: "consensus_staking" }` — annualized staking yield (%). - **Time-horizon mapping** (all run concurrently, tick-advanced, 90:1 (1s wall = 90s sim)): | Horizon | Primary models | Update cadence | diff --git a/core/docs/plans/M3g-market-microstructure-sims.md b/core/docs/plans/M3g-market-microstructure-sims.md index 78da588..dfcae6e 100644 --- a/core/docs/plans/M3g-market-microstructure-sims.md +++ b/core/docs/plans/M3g-market-microstructure-sims.md @@ -16,8 +16,8 @@ Kurz CMC thesis). DEX-specific microstructure C2 (emerging). Implementation C1. ## 3. Language & location TBD · `src/economy/sims/microstructure/`. Needs high-frequency data handling, event-driven -simulation, and Riccati equation solvers for optimal execution trajectories. Rust, C++, or -Python with optimized event loop. +simulation, and Riccati equation solvers for optimal execution trajectories. C++, Fortran, +or Julia. ## 4. Does / does-not - **Does:** simulate order flow across venues (DEXs and CEXs); model bid-ask spread dynamics as a @@ -46,11 +46,11 @@ Python with optimized event loop. | Annual | Microstructure regime (DEX vs CEX share evolution) | Monthly roll | | 5-year | Venue topology evolution, structural impact trends | Quarterly roll | - Examples: - `{ value: 0.0034, lower_bound: 0.0018, upper_bound: 0.0052, confidence: 0.85, + `{ value: 0.0034, lower_bound: 0.0018, upper_bound: 0.0052, confidence: 8.50, time_horizon: "next_trade", sim_type: "market_microstructure" }` — slippage (%) for 10 ETH. - `{ value: 12400, lower_bound: 8200, upper_bound: 18600, confidence: 0.78, + `{ value: 12400, lower_bound: 8200, upper_bound: 18600, confidence: 7.80, time_horizon: "1h", sim_type: "market_microstructure" }` — depth (USD) within 50bps. - `{ value: [0.3, 0.3, 0.2, 0.1, 0.1], lower_bound: null, upper_bound: null, confidence: 0.80, + `{ value: [0.3, 0.3, 0.2, 0.1, 0.1], lower_bound: null, upper_bound: null, confidence: 8.00, time_horizon: "30min", sim_type: "market_microstructure" }` — Almgren-Chriss optimal execution schedule (fraction per 6-min bucket for 100 ETH sell). - **Prediction types:** `slippage_estimate`, `spread_forecast`, `depth_profile`,