52 lines
1.5 KiB
Python
52 lines
1.5 KiB
Python
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from __future__ import annotations
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from dataclasses import dataclass
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import pandas as pd
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from market_costs import okx_fee, estimate_slippage_rate
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from intrabar import entry_slippage_row
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@dataclass
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class TradeState:
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cash: float = 1000.0
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qty: float = 0.0
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entry_px: float | None = None
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max_px: float | None = None
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stop_loss_frac: float = 0.02
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fee_bps: float = 10.0
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slippage_bps: float = 2.0
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def enter_long(state: TradeState, price: float) -> dict:
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if state.qty > 0:
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return {}
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px = entry_slippage_row(price, 0.0, state.slippage_bps)
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qty = state.cash / px
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fee = okx_fee(state.fee_bps, state.cash)
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state.qty = max(qty - fee / px, 0.0)
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state.cash = 0.0
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state.entry_px = px
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state.max_px = px
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return {"side": "BUY", "price": px, "qty": state.qty, "fee": fee}
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def maybe_trailing_stop(state: TradeState, price: float) -> float:
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if state.qty <= 0:
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return float("inf")
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state.max_px = max(state.max_px or price, price)
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trail_px = state.max_px * (1.0 - state.stop_loss_frac)
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return trail_px
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def exit_long(state: TradeState, price: float) -> dict:
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if state.qty <= 0:
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return {}
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notional = state.qty * price
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slip = estimate_slippage_rate(state.slippage_bps, notional)
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fee = okx_fee(state.fee_bps, notional)
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cash_back = notional - slip - fee
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event = {"side": "SELL", "price": price, "qty": state.qty, "fee": fee, "slippage": slip}
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state.cash = cash_back
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state.qty = 0.0
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state.entry_px = None
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state.max_px = None
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return event
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