Algorithmic trading support¶

ASRQuant 1.0.0 provides a safe bridge from target portfolio weights to order-level paper trading. Live execution is intentionally adapter-based and disabled unless a user supplies an explicit broker implementation.

Paper trading from a QuantLab¶

import asrquant as asr

lab = asr.open_lab("prices.csv", date_column="Date")
weights = lab.strategy("sma", fast=20, slow=100)

paper = lab.paper_trade(
    weights,
    initial_capital=100_000,
    commission_bps=1,
    slippage_bps=2,
    policy=asr.RiskPolicy(
        max_gross_leverage=1.0,
        max_position_weight=0.20,
        max_daily_turnover=0.50,
        max_drawdown=0.15,
    ),
)

Paper trading from a research project¶

paper = project.paper_trade(
    commission_bps=1,
    slippage_bps=2,
)

Order model¶

order = asr.Order(
    symbol="SPY",
    quantity=10,
    side=asr.OrderSide.BUY,
    order_type=asr.OrderType.LIMIT,
    limit_price=500.0,
)

Order statuses are CREATED, ACCEPTED, PARTIALLY_FILLED, FILLED, REJECTED and CANCELLED.

Broker-neutral adapter¶

A real or third-party paper broker can implement:

class MyBroker:
    def submit_order(self, order, market_price): ...
    def cancel_order(self, order_id): ...
    def positions(self): ...
    def cash_balance(self): ...

The type contract is exposed as asr.BrokerAdapter.

Risk policy¶

RiskPolicy supports:

maximum gross leverage;
maximum position weight;
maximum order notional;
maximum daily turnover;
maximum drawdown kill switch;
short-selling permission;
minimum cash balance.

Current execution boundary¶

ASRQuant does not yet include venue-specific live adapters, exchange authentication, asynchronous order reconciliation, broker callbacks, queue-position models or high-frequency limit-order-book simulation. These capabilities require separate operational security, broker certification and venue-specific testing.