Simulated fills
Future simulated fills will use observable market references. Detailed rules are not yet implemented.
ATH3NA PLATFORM
Trading Science Lab Methodology
REAL MARKET DATA • SIMULATED EXECUTION • NO REAL MONEY
Draft methodology. Subject to technical implementation and legal review.
This document defines the public methodological boundary for a future educational simulation environment. It does not claim that the Simulation Engine is currently operational.
Product definition and educational purpose
ATH3NA Platform is an educational market simulation environment designed to teach how financial markets, risk, liquidity, volatility, order types and participant behaviour operate. It supports structured observation, planning, simulated decision-making and review. It is not a broker, venue, adviser or signal service.
Real data and simulated state
Licensed market data may provide prices, timestamps, bid and ask, trades, quotes, candles, volume, market sessions and historical movement. Training capital, accounts, orders, fills, positions, exposure, fees, stops, portfolio value, profit and loss, drawdown and performance metrics remain internal simulated state with no monetary value.
No external transaction is executed. No money is accepted, held or withdrawn. No simulated position becomes a real position, and no order is routed to a broker or venue.
Planned execution methodology
Planned methodology for the Simulation Engine phase.
Bid and ask
Future execution modelling is planned to distinguish bid-side and ask-side references rather than assume frictionless midpoint execution.
Spread and slippage
Future scenarios are planned to account for spread and modelled slippage, with assumptions disclosed alongside each exercise.
Stops and gaps
Future stop handling is planned to distinguish a trigger from a simulated fill and to account for price gaps.
Partial fills
Future liquidity-aware exercises may model partial simulated fills. No partial-fill algorithm is operational in this phase.
Process-based assessment
Assessment is intended to examine risk discipline, position sizing, stop integrity, plan adherence, drawdown control, decision quality, emotional discipline, market understanding, journal completion and consistency. A simulated result is not sufficient evidence of a sound decision process.
Limitations and licensing dependency
Simulation cannot reproduce every feature of real execution. Latency, queue position, venue behaviour, market impact, halts, fragmented liquidity, unavailable quotes and participant behaviour can differ materially from a modelled exercise. Simulated outcomes are hypothetical and do not establish expected real-world results.
Market-data coverage, timing and permitted public display depend on active third-party market-data licences, exchange entitlements and applicable usage rights. Provider selection remains internal and may vary by coverage and jurisdiction.
Current development status
The dual-environment public architecture and this draft methodology are available. The Simulation Engine, training accounts, simulated order lifecycle, portfolio state, historical replay and process scoring are deferred to later implementation phases.