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"rule": "reportArgumentType",
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"rule": "reportArgumentType",
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"rule": "reportArgumentType",
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"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"timeframe\" of type \"str\" in function \"timeframe_to_prev_date\"\n Type \"Any | None\" is not assignable to type \"str\"\n \"None\" is not assignable to \"str\"",
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"file": "quickadapter/user_data/strategies/QuickAdapterV3.py",
"message": "Argument of type \"float | None\" cannot be assigned to parameter \"x\" of type \"ConvertibleToFloat\" in function \"__new__\"\n Type \"float | None\" is not assignable to type \"ConvertibleToFloat\"\n Type \"None\" is not assignable to type \"ConvertibleToFloat\"\n \"None\" is not assignable to \"str\"\n \"None\" is incompatible with protocol \"Buffer\"\n \"__buffer__\" is not present\n \"None\" is incompatible with protocol \"SupportsFloat\"\n \"__float__\" is not present\n \"None\" is incompatible with protocol \"SupportsIndex\"\n ...",
"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/QuickAdapterV3.py",
"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"timeframe\" of type \"str\" in function \"get_analyzed_dataframe\"\n Type \"Any | None\" is not assignable to type \"str\"\n \"None\" is not assignable to \"str\"",
"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/QuickAdapterV3.py",
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"rule": "reportOperatorIssue",
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"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/QuickAdapterV3.py",
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"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/QuickAdapterV3.py",
"message": "Argument of type \"str\" cannot be assigned to parameter \"order\" of type \"OrderType\" in function \"reversal_confirmed\"\n Type \"str\" is not assignable to type \"OrderType\"\n \"str\" is not assignable to type \"Literal['entry']\"\n \"str\" is not assignable to type \"Literal['exit']\"",
"rule": "reportArgumentType",
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"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/QuickAdapterV3.py",
"message": "Argument of type \"datetime | None\" cannot be assigned to parameter \"current_candle_date\" of type \"datetime\" in function \"_normalize_final_take_profit_state\"\n Type \"datetime | None\" is not assignable to type \"datetime\"\n \"None\" is not assignable to \"datetime\"",
"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/QuickAdapterV3.py",
"message": "Argument of type \"Any | None\" cannot be assigned to parameter \"timeframe\" of type \"str\" in function \"get_analyzed_dataframe\"\n Type \"Any | None\" is not assignable to type \"str\"\n \"None\" is not assignable to \"str\"",
"rule": "reportArgumentType",
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"rule": "reportArgumentType",
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"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/QuickAdapterV3.py",
"message": "Argument of type \"LocalTrade\" cannot be assigned to parameter \"trade\" of type \"Trade\" in function \"get_trade_annotation_line_start_date\"\n \"LocalTrade\" is not assignable to \"Trade\"",
"rule": "reportArgumentType",
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"rule": "reportArgumentType",
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"rule": "reportArgumentType",
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"message": "Argument of type \"LocalTrade\" cannot be assigned to parameter \"trade\" of type \"Trade\" in function \"get_trade_entry_date\"\n \"LocalTrade\" is not assignable to \"Trade\"",
"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/QuickAdapterV3.py",
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"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/Utils.py",
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"rule": "reportReturnType",
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"file": "quickadapter/user_data/strategies/Utils.py",
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"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/Utils.py",
"message": "Argument of type \"Scalar\" cannot be assigned to parameter \"x\" of type \"ConvertibleToInt\" in function \"__new__\"\n Type \"Scalar\" is not assignable to type \"ConvertibleToInt\"\n Type \"complex\" is not assignable to type \"ConvertibleToInt\"\n \"complex\" is not assignable to \"str\"\n \"complex\" is incompatible with protocol \"Buffer\"\n \"__buffer__\" is not present\n \"complex\" is incompatible with protocol \"SupportsInt\"\n \"__int__\" is not present\n \"complex\" is incompatible with protocol \"SupportsIndex\"\n ...",
"rule": "reportArgumentType",
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"file": "quickadapter/user_data/strategies/Utils.py",
"message": "Type \"float\" is not assignable to return type \"T@get_distance\"\n Type \"float\" is not assignable to type \"T@get_distance\"",
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4. Open trades use the custom volatility-based stoploss, which never loosens,
including after partial exits. The strategy stoploss is -2.5%; leverage,
execution and exchange conditions affect the actual outcome.
-5. Three take-profit stages request 40%, 30% and 20% of the stake remaining at
- each stage. Exchange minimums can turn a partial request into a full close.
- The final target arms a persisted trailing full exit: a material adverse
- retracement exits, not elapsed stagnation alone. Open orders block new staged
- adjustments.
+5. The exit ladder targets equal shares of the initial stake: nominally 1/N
+ per rung, or 25% with the four default stages. Partial rungs request
+ `1 / (N - k)` of the remaining stake at zero-based stage `k`; the final
+ exit closes the remainder. Adding or removing a rung in `exit_stages`
+ changes the nominal shares. Exchange lot precision, minimum-stake limits
+ and canceled partially filled orders can change the realized shares;
+ minimums can reduce a partial request or turn it into a full close.
+ An executable partial lot is preserved through stake conversion; if no
+ callback stake reproduces the selected lot, the strategy requests a full close.
+ The last rung's target arms a persisted trailing full exit: a material
+ adverse retracement exits, not elapsed stagnation alone. Open orders
+ block new staged adjustments.
6. Model expiration (`do_predict=2`) requests an exit. A valid opposite extrema
signal requests an exit only after price-reversal confirmation. Outlier
predictions are counted per candle; that count is not itself an unconditional
### Exit pricing
-| Path | Runtime fallback | Type / Range | Description |
-| -------------------------------------------------------------- | ---------------------- | ------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
-| exit_pricing.trade_natr_method | `moving_average` | enum {`moving_average`,`quantile_interpolation`,`weighted_average`} | Trade NATR (Normalized Average True Range) aggregation for stoploss and take-profit distances. `moving_average` uses KAMA to preserve nonnegative volatility. The stoploss never loosens, including after partial exits, and remains unchanged on order fills. |
-| exit_pricing.final_take_profit_retracement_fraction | 0.5 | float (0,1] | Fraction of the final take-profit target distance used as the frozen trailing retracement distance after the final target arms the exit. The final exit tracks the best subsequent per-candle rate and exits only after this material adverse move; elapsed stagnation alone does not exit. Plot annotations show only the current trail boundary from the candle that established it; earlier boundaries are not retained. |
-| exit_pricing.take_profit_stage_natr_multiplier_fraction_series | `fibonacci_extensions` | enum {`fibonacci_extensions`,`pi_extensions`} | Partial target distances from entry, as percentages of the full target distance: approximately 23.6%, 38.2% and 61.8% for `fibonacci_extensions`, or 3.2%, 10.1% and 31.8% for `pi_extensions`. Pi places partial targets closer to entry. Stake reduction percentages and the final target are unchanged. Invalid values use the default. |
+| Path | Runtime fallback | Type / Range | Description |
+| -------------------------------------------------------------- | ---------------------- | ------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| exit_pricing.trade_natr_method | `moving_average` | enum {`moving_average`,`quantile_interpolation`,`weighted_average`} | Trade NATR (Normalized Average True Range) aggregation for stoploss and take-profit distances. `moving_average` uses KAMA to preserve nonnegative volatility. The stoploss never loosens, including after partial exits, and remains unchanged on order fills. |
+| exit_pricing.final_take_profit_retracement_fraction | 0.5 | float (0,1] | Fraction of the final take-profit target distance used as the frozen trailing retracement distance after the final target arms the exit. The final exit tracks the best subsequent per-candle rate and exits only after this material adverse move; elapsed stagnation alone does not exit. Plot annotations show only the current trail boundary from the candle that established it; earlier boundaries are not retained. |
+| exit_pricing.take_profit_stage_natr_multiplier_fraction_series | `fibonacci_extensions` | enum {`fibonacci_extensions`,`pi_extensions`} | With the default four rungs, partial target distances are approximately 23.6%, 38.2% and 61.8% of the full target distance for `fibonacci_extensions`, or 3.2%, 10.1% and 31.8% for `pi_extensions`. Pi places partial targets closer to entry. Partial fractions are recomputed when the rung count changes; the final rung always uses the full distance. This setting changes target distances only, not nominal stake shares; execution constraints are described in the decision cycle. Invalid values use the default. |
### Reversal confirmation
from QuickAdapterV3 import QuickAdapterV3
from Utils import (
TAKE_PROFIT_STAGE_NATR_MULTIPLIER_FRACTION_SERIES,
+ get_exit_stage_stake_fractions,
get_take_profit_stage_natr_multiplier_fractions,
)
long_trade = trade()
# One candle of duration, a two-value trade NATR window and multiplier 3.0 make the
# distance open_rate * 0.07 * 3.0 * fraction * log10(10), and log10(10) is exactly 1.
- for stage in sorted(QuickAdapterV3.partial_exit_stages):
+ fractions = model.exit_stage_natr_multiplier_fractions
+ self.assertEqual(sorted(fractions), sorted(QuickAdapterV3.exit_stages))
+ for stage, fraction in fractions.items():
with self.subTest(stage=stage):
- fraction = model.partial_exit_stage_natr_multiplier_fractions[stage]
self.assertIsInstance(fraction, float)
self.assertGreater(fraction, 0.0)
- self.assertLess(fraction, 1.0)
distance = 100.0 * 0.07 * MULTIPLIER * fraction
target = model.get_take_profit_target(frame, long_trade, stage)
self.assertIsNotNone(target)
assert_allclose(target[0], 100.0 + distance, rtol=1e-9, atol=1e-9)
assert_allclose(target[1], distance, rtol=1e-9, atol=1e-9)
- for stage in (QuickAdapterV3._FINAL_EXIT_STAGE, 99, -1):
- with self.subTest(final_stage=stage):
- target = model.get_take_profit_target(frame, long_trade, stage)
- assert_allclose(
- target[0],
- 100.0 * (1 + 0.07 * MULTIPLIER * QuickAdapterV3._FINAL_EXIT_STAGE_PARAMS[0]),
- rtol=1e-9,
- atol=1e-9,
- )
- stages = [
- model.get_take_profit_target(frame, long_trade, stage)[1]
- for stage in (0, 1, 2, QuickAdapterV3._FINAL_EXIT_STAGE)
- ]
- self.assertEqual(stages, sorted(stages))
-
- def test_the_fibonacci_extensions_define_the_default_partial_ladder(self):
+ # Partial rungs stay inside the full distance; only the final one reaches it.
+ for stage in sorted(QuickAdapterV3.exit_stages):
+ if stage != QuickAdapterV3.final_exit_stage():
+ self.assertLess(fractions[stage], 1.0)
+ self.assertEqual(fractions[QuickAdapterV3.final_exit_stage()], 1.0)
+ # A stage the ladder does not define is priced at the full distance.
+ self.assertEqual(model.get_exit_stage_natr_multiplier_fraction(99), 1.0)
+ self.assertEqual(model.get_exit_stage_natr_multiplier_fraction(-1), 1.0)
+
+ def test_the_fibonacci_extensions_define_the_default_ladder(self):
# Frozen reference rungs, not a restatement of the formula: a change of
- # base or of the stage count must fail here. They are phi**-3, phi**-2
- # and phi**-1 rounded to six decimals.
+ # base or of the stage count must fail here. Three partial rungs are
+ # phi**-3, phi**-2 and phi**-1, then the full distance.
assert_allclose(
- tuple(strategy().partial_exit_stage_natr_multiplier_fractions.values()),
- (0.236068, 0.381966, 0.618034),
+ tuple(strategy().exit_stage_natr_multiplier_fractions.values()),
+ (0.236068, 0.381966, 0.618034, 1.0),
rtol=1e-6,
)
- self.assertEqual(strategy().get_exit_stage_natr_multiplier_fraction(99), 1.0)
def test_every_series_raises_its_fraction_with_the_stage_index(self):
for series in TAKE_PROFIT_STAGE_NATR_MULTIPLIER_FRACTION_SERIES:
with self.subTest(series=series):
# Stage fractions follow stage indices, not insertion order.
- reordered_stages = dict(
- sorted(QuickAdapterV3.partial_exit_stages.items(), reverse=True)
- )
- with mock.patch.object(QuickAdapterV3, "partial_exit_stages", reordered_stages):
+ reordered_stages = dict(sorted(QuickAdapterV3.exit_stages.items(), reverse=True))
+ with mock.patch.object(QuickAdapterV3, "exit_stages", reordered_stages):
model = strategy(fraction_series=series)
- by_stage = model.partial_exit_stage_natr_multiplier_fractions
- stages = sorted(QuickAdapterV3.partial_exit_stages)
+ by_stage = model.exit_stage_natr_multiplier_fractions
+ stages = sorted(QuickAdapterV3.exit_stages)
self.assertEqual(sorted(by_stage), stages)
for earlier, later in pairwise(stages):
- self.assertLess(by_stage[earlier], by_stage[later])
+ self.assertLessEqual(by_stage[earlier], by_stage[later])
- def test_no_series_ladder_reaches_the_final_stage_fraction(self):
+ def test_no_series_ladder_reaches_the_final_stage_fraction_early(self):
for series in TAKE_PROFIT_STAGE_NATR_MULTIPLIER_FRACTION_SERIES:
with self.subTest(series=series):
fractions = tuple(
- strategy(
- fraction_series=series
- ).partial_exit_stage_natr_multiplier_fractions.values()
+ strategy(fraction_series=series).exit_stage_natr_multiplier_fractions.values()
)
- self.assertNotIn(1.0, fractions)
- self.assertEqual(max(fractions), fractions[-1])
+ # Only the last rung carries the full distance.
+ self.assertEqual(fractions[-1], 1.0)
+ self.assertNotIn(1.0, fractions[:-1])
def test_the_ladder_is_indexed_by_the_stage_count(self):
self.assertEqual(
self.assertEqual(len(fractions), count)
self.assertEqual(max(fractions), fractions[-1])
- def test_the_pi_extensions_define_the_partial_ladder(self):
+ def test_the_pi_extensions_define_the_ladder(self):
assert_allclose(
tuple(
strategy(
fraction_series="pi_extensions"
- ).partial_exit_stage_natr_multiplier_fractions.values()
+ ).exit_stage_natr_multiplier_fractions.values()
),
- (0.03225153, 0.10132118, 0.31830989),
+ (0.03225153, 0.10132118, 0.31830989, 1.0),
rtol=1e-6,
)
fibonacci = strategy(fraction_series="fibonacci_extensions")
pi = strategy(fraction_series="pi_extensions")
self.assertEqual(pi.take_profit_stage_natr_multiplier_fraction_series, "pi_extensions")
- for stage in sorted(QuickAdapterV3.partial_exit_stages):
+ partial_stages = list(QuickAdapterV3.partial_exit_stages())
+ for stage in partial_stages:
with self.subTest(stage=stage):
fibonacci_distance = fibonacci.get_take_profit_target(frame, long_trade, stage)[1]
pi_distance = pi.get_take_profit_target(frame, long_trade, stage)[1]
self.assertLess(pi_distance, fibonacci_distance)
# The final distance is independent of the partial extension series.
self.assertEqual(
- fibonacci.get_take_profit_target(frame, long_trade, QuickAdapterV3._FINAL_EXIT_STAGE),
- pi.get_take_profit_target(frame, long_trade, QuickAdapterV3._FINAL_EXIT_STAGE),
+ fibonacci.get_take_profit_target(frame, long_trade, QuickAdapterV3.final_exit_stage()),
+ pi.get_take_profit_target(frame, long_trade, QuickAdapterV3.final_exit_stage()),
)
def test_fraction_series_validates_names_and_stage_counts(self):
with self.assertRaises(ValueError):
get_take_profit_stage_natr_multiplier_fractions("fibonacci_extensions", -1)
+ def test_the_remaining_stake_share_grows_with_the_stage_index(self):
+ # Shares apply to the stake still open, so each rung closes a larger
+ # fraction of a smaller remainder than the one before it, and the last
+ # rung closes everything that is left.
+ assert_allclose(get_exit_stage_stake_fractions(4), (0.25, 1 / 3, 0.5, 1.0), rtol=1e-15)
+ for count in (1, 2, 3, 4, 5, 8):
+ with self.subTest(stage_count=count):
+ fractions = get_exit_stage_stake_fractions(count)
+ self.assertEqual(len(fractions), count)
+ for earlier, later in pairwise(fractions):
+ self.assertLess(earlier, later)
+ self.assertEqual(fractions[-1], 1.0)
+
+ def test_a_ladder_without_any_stage_is_rejected(self):
+ for invalid in (0, -1):
+ with self.subTest(stage_count=invalid), self.assertRaises(ValueError):
+ get_exit_stage_stake_fractions(invalid)
+
+ def test_only_the_last_stage_share_closes_the_whole_position(self):
+ # Every earlier rung must leave something behind.
+ for count in (1, 2, 3, 4, 5, 8):
+ with self.subTest(stage_count=count):
+ fractions = get_exit_stage_stake_fractions(count)
+ remaining = 1.0
+ for fraction in fractions:
+ self.assertGreater(fraction, 0.0)
+ remaining *= 1.0 - fraction
+ self.assertAlmostEqual(remaining, 0.0, places=12)
+
+ def test_the_stake_shares_follow_the_configured_stage_count(self):
+ # Adding or removing a rung re-sizes every share without any literal.
+ for count in (1, 2, 4):
+ with self.subTest(stage_count=count):
+ stages = dict.fromkeys(range(count), "lime")
+ with mock.patch.object(QuickAdapterV3, "exit_stages", stages):
+ model = strategy()
+ self.assertEqual(
+ model.exit_stage_stake_fractions,
+ dict(zip(range(count), get_exit_stage_stake_fractions(count), strict=True)),
+ )
+
def test_a_short_take_profit_target_flips_the_sign(self):
model = strategy()
frame = candles([100.0, 100.0, 100.0], natr=[1.0, 4.0, 8.0], multiplier=MULTIPLIER)
underwater = model.get_take_profit_target(
candles([100.0, 100.0, 100.0], natr=[1.0, 400.0, 800.0], multiplier=MULTIPLIER),
trade(open_rate=1e-9, is_short=True),
- QuickAdapterV3._FINAL_EXIT_STAGE,
+ QuickAdapterV3.final_exit_stage(),
)
self.assertIsNone(underwater)
import datetime
import math
import unittest
-from types import SimpleNamespace
+from types import MethodType, SimpleNamespace
from unittest import mock
import numpy as np
import pandas as pd
-from freqtrade.enums import RunMode
+from ccxt import DECIMAL_PLACES, SIGNIFICANT_DIGITS, TICK_SIZE
+from freqtrade.enums import RunMode, TradingMode
+from freqtrade.exchange import Exchange
+from freqtrade.exchange.exchange_utils import amount_to_contract_precision, contracts_to_amount
+from freqtrade.freqtradebot import FreqtradeBot
from freqtrade.persistence import Order, Trade
from qa_support import PAIR, QaTestCase, model_config, temporary_directory
from QuickAdapterV3 import QuickAdapterV3
0.2,
0.2,
)
- stake_reduction = -100.0 * QuickAdapterV3.partial_exit_stages[0][0]
+ # Four exits release the position in equal shares, so the
+ # first one closes a quarter of the 100 stake.
+ stake_reduction = -25.0
direction = "short" if short else "long"
self.assertEqual(after, (stake_reduction, f"take_profit_{direction}_0"))
+ def _filled_order(self, position, amount, rate, tag=None):
+ return Order(
+ order_id=str(len(position.orders)),
+ ft_pair=PAIR,
+ ft_order_side=position.entry_side if tag is None else position.exit_side,
+ ft_is_open=False,
+ status="closed",
+ filled=amount,
+ amount=amount,
+ price=rate,
+ average=rate,
+ cost=amount * rate,
+ order_date=self.now - datetime.timedelta(minutes=5),
+ order_filled_date=self.now,
+ ft_order_tag=tag,
+ )
+
+ def _filled_position(
+ self,
+ short=False,
+ leverage=2.0,
+ amount=2.0,
+ open_rate=123.4,
+ lot=0.01,
+ contract_size=1.0,
+ precision_mode=TICK_SIZE,
+ ):
+ position = Trade(
+ pair=PAIR,
+ open_rate=open_rate,
+ open_date=self.now - datetime.timedelta(minutes=5),
+ is_short=short,
+ stake_amount=amount * open_rate / leverage,
+ amount=amount,
+ leverage=leverage,
+ exchange="binance",
+ fee_open=0.0,
+ fee_close=0.0,
+ amount_precision=lot,
+ precision_mode=precision_mode,
+ contract_size=contract_size,
+ orders=[],
+ )
+ position.orders.append(self._filled_order(position, amount, open_rate))
+ position.recalc_trade_from_orders()
+ self.custom_data(position)
+ return position
+
+ def _native_partial_exit(self, position, rate, min_cost=1.0, min_amount=None):
+ # Only market data, wallet availability and order submission are isolated.
+ exchange = SimpleNamespace(
+ markets={
+ PAIR: {
+ "contractSize": position.contract_size,
+ "limits": {
+ "cost": {"min": min_cost, "max": None},
+ "amount": {"min": min_amount, "max": None},
+ },
+ }
+ },
+ _config={},
+ trading_mode=TradingMode.FUTURES,
+ _get_max_notional_from_tiers=lambda pair, leverage: None,
+ get_rates=lambda *args: (rate, rate),
+ amount_to_contract_precision=lambda pair, amount: amount_to_contract_precision(
+ amount, position.amount_precision, position.precision_mode, position.contract_size
+ ),
+ )
+ for name in (
+ "get_contract_size",
+ "_contracts_to_amount",
+ "_get_stake_amount_limit",
+ "_get_stake_amount_considering_leverage",
+ "get_min_pair_stake_amount",
+ "get_max_pair_stake_amount",
+ ):
+ setattr(exchange, name, MethodType(getattr(Exchange, name), exchange))
+ self.model.dp._exchange = exchange
+ bot = object.__new__(FreqtradeBot)
+ bot.strategy = self.model
+ bot.exchange = exchange
+ bot.wallets = SimpleNamespace(get_available_stake_amount=lambda: 1000.0)
+ fills = []
+
+ def fill(trade, price, *, sub_trade_amt, exit_tag, **kwargs):
+ fills.append(sub_trade_amt)
+ trade.orders.append(self._filled_order(trade, sub_trade_amt, price, exit_tag))
+ trade.recalc_trade_from_orders()
+
+ bot.execute_trade_exit = fill
+ bot.check_and_call_adjust_trade_position(position)
+ return fills
+
+ def test_native_fills_preserve_non_idempotent_contract_quantities(self):
+ for precision_mode, precision in (
+ (TICK_SIZE, 1),
+ (DECIMAL_PLACES, 0),
+ (SIGNIFICANT_DIGITS, 2),
+ ):
+ for short in (False, True):
+ with self.subTest(precision_mode=precision_mode, short=short):
+ position = self._filled_position(
+ short=short,
+ amount=contracts_to_amount(110, 1 / 3),
+ open_rate=100.0,
+ lot=precision,
+ contract_size=1 / 3,
+ precision_mode=precision_mode,
+ )
+ target = self.model.get_take_profit_target(self.frame, position, 0)[0]
+ rate = target * (0.9 if short else 1.1)
+ self.assertEqual(
+ self._native_partial_exit(position, rate, min_cost=None, min_amount=1),
+ [8.999999999999998],
+ )
+ self.assertEqual(position.amount, 27.666666666666664)
+ self.assertAlmostEqual(position.stake_amount, 1383.3333333333333)
+ self.assertEqual(position.open_rate, 100.0)
+
+ def test_native_roundtrip_adjusts_up_and_down_to_preserve_the_selected_lot(self):
+ cases = (
+ (
+ "up",
+ {"amount": 2.0, "open_rate": 123.4, "lot": 0.01},
+ 0.5,
+ 1.5,
+ 61.7,
+ ),
+ (
+ "down",
+ {
+ "amount": contracts_to_amount(0.38, 1 / 3),
+ "open_rate": 100.0,
+ "lot": 7,
+ "contract_size": 1 / 3,
+ "precision_mode": DECIMAL_PLACES,
+ },
+ 0.03166663333333333,
+ 0.09500003333333332,
+ 3.166667777777777,
+ ),
+ )
+ for direction, inputs, filled_amount, remaining_amount, remaining_stake in cases:
+ for short in (False, True):
+ with self.subTest(direction=direction, short=short):
+ position = self._filled_position(short=short, leverage=3.0, **inputs)
+ target = self.model.get_take_profit_target(self.frame, position, 0)[0]
+ rate = target * (0.9 if short else 1.1)
+ self.assertEqual(
+ self._native_partial_exit(position, rate, min_cost=None, min_amount=1e-7),
+ [filled_amount],
+ )
+ self.assertEqual(position.amount, remaining_amount)
+ self.assertAlmostEqual(position.stake_amount, remaining_stake)
+ self.assertEqual(position.open_rate, inputs["open_rate"])
+
+ def test_native_minimum_clamp_preserves_a_representable_fractional_contract(self):
+ original_model = self.model
+ self.addCleanup(setattr, self, "model", original_model)
+ with mock.patch.object(QuickAdapterV3, "exit_stages", {0: "lime", 1: "yellow"}):
+ self.model = QuickAdapterV3(original_model.config)
+ self.model.freqai_info = original_model.config["freqai"]
+ self.model.bot_start()
+ self.model.dp = original_model.dp
+ for short in (False, True):
+ with self.subTest(short=short):
+ position = self._filled_position(
+ short=short,
+ leverage=1.0,
+ amount=2.01e-18,
+ open_rate=1e18,
+ lot=1,
+ contract_size=3e-20,
+ )
+ rate, min_cost = (1e17, 3.126e18) if short else (1e19, 3.126e20)
+ self.assertEqual(
+ self._native_partial_exit(position, rate, min_cost=min_cost), [9.9e-19]
+ )
+ self.assertEqual(position.amount, 1.02e-18)
+ self.assertEqual(position.stake_amount, 1.02)
+
+ def test_native_unrepresentable_selected_lots_request_the_full_quantity(self):
+ cases = (
+ (
+ "native-quantity-grid",
+ 2,
+ {"amount": 2e-18, "open_rate": 1e18, "lot": 1, "contract_size": 1e-20},
+ 1e19,
+ 9.329e20,
+ ),
+ (
+ "callback-float-grid",
+ 8,
+ {
+ "amount": 61063600.9973608,
+ "open_rate": 0.000736753283349331,
+ "lot": 9,
+ "precision_mode": DECIMAL_PLACES,
+ },
+ None,
+ 0.0,
+ ),
+ )
+ original_model = self.model
+ self.addCleanup(setattr, self, "model", original_model)
+ for name, stage_count, inputs, rate, min_cost in cases:
+ with (
+ self.subTest(name=name),
+ mock.patch.object(
+ QuickAdapterV3, "exit_stages", dict.fromkeys(range(stage_count), "lime")
+ ),
+ ):
+ self.model = QuickAdapterV3(original_model.config)
+ self.model.freqai_info = original_model.config["freqai"]
+ self.model.bot_start()
+ self.model.dp = original_model.dp
+ position = self._filled_position(leverage=1.0, **inputs)
+ if rate is None:
+ rate = self.model.get_take_profit_target(self.frame, position, 0)[0] * 1.1
+ self.assertEqual(
+ self._native_partial_exit(position, rate, min_cost=min_cost),
+ [inputs["amount"]],
+ )
+
+ def test_native_fills_release_equal_lots_and_leave_one_share_for_the_final_exit(self):
+ original_model = self.model
+ self.addCleanup(setattr, self, "model", original_model)
+ for stage_count in (2, 3, 4, 5):
+ with mock.patch.object(
+ QuickAdapterV3, "exit_stages", dict.fromkeys(range(stage_count), "lime")
+ ):
+ self.model = QuickAdapterV3(original_model.config)
+ self.model.freqai_info = original_model.config["freqai"]
+ self.model.bot_start()
+ self.model.dp = original_model.dp
+ for leverage in (1.0, 2.0, 5.0):
+ for short in (False, True):
+ with self.subTest(stage_count=stage_count, leverage=leverage, short=short):
+ position = self._filled_position(
+ short, leverage, amount=0.5 * stage_count
+ )
+ initial_stake = position.stake_amount
+ for stage in range(stage_count - 1):
+ target = self.model.get_take_profit_target(
+ self.frame, position, stage
+ )[0]
+ rate = target + (-1.0 if short else 1.0)
+ before = position.stake_amount
+ self.assertEqual(self._native_partial_exit(position, rate), [0.5])
+ self.assertAlmostEqual(
+ before - position.stake_amount, initial_stake / stage_count
+ )
+ self.assertEqual(position.amount, 0.5)
+ self.assertAlmostEqual(
+ position.stake_amount, initial_stake / stage_count
+ )
+ self.assertEqual(self._native_partial_exit(position, rate), [])
+
+ def test_native_minimum_does_not_turn_a_representable_share_into_a_full_close(self):
+ for leverage in (1.0, 2.0, 5.0):
+ with self.subTest(leverage=leverage):
+ position = self._filled_position(leverage=leverage)
+ self.assertEqual(self._native_partial_exit(position, 135.74), [0.5])
+ # 64 with the native 5% reserve needs 67.2 quote; 0.50 meets it, 0.49 does not.
+ self.assertEqual(self._native_partial_exit(position, 135.74, min_cost=64.0), [0.5])
+ self.assertEqual(position.amount, 1.0)
+
+ def test_native_minimum_can_still_clamp_a_share_to_preserve_the_remainder(self):
+ position = self._filled_position()
+ for _ in range(2):
+ self.assertEqual(self._native_partial_exit(position, 135.74), [0.5])
+ self.assertEqual(self._native_partial_exit(position, 150.0, min_cost=73.1 / 1.05), [0.49])
+ exchange = self.model.dp._exchange
+ exit_min = exchange.get_min_pair_stake_amount(PAIR, 150.0, 0.0, position.leverage)
+ remaining_min = exchange.get_min_pair_stake_amount(
+ PAIR, 150.0, self.model.stoploss, position.leverage
+ ) * (1.0 + QuickAdapterV3._PARTIAL_EXIT_MIN_STAKE_MARGIN)
+ self.assertGreaterEqual(0.49 * 150.0, exit_min * position.leverage)
+ self.assertGreaterEqual(position.amount * 150.0, remaining_min * position.leverage)
+
+ def test_native_stake_conversion_keeps_a_lot_with_a_sub_decimal_quantum_stake(self):
+ position = self._filled_position(leverage=10.0, amount=0.02, open_rate=1e-16, lot=0.001)
+ self.assertEqual(self._native_partial_exit(position, 1.0, min_cost=0.0), [0.005])
+ self.assertEqual(position.amount, 0.015)
+
+ def test_native_quantity_ceiling_preserves_a_representable_fractional_contract(self):
+ with mock.patch.object(QuickAdapterV3, "exit_stages", {0: "lime", 1: "yellow"}):
+ position = self._filled_position(
+ leverage=1.0, amount=2.7e-18, open_rate=1e18, lot=1, contract_size=3e-19
+ )
+ self.assertEqual(self._native_partial_exit(position, 1e19, min_cost=0.0), [9e-19])
+ self.assertEqual(position.amount, 1.8e-18)
+
def test_expired_models_exit_before_order_stage_and_date_guards(self):
self.frame.loc[self.frame.index[-1], "date"] = pd.NaT
self.frame["do_predict"] = 2
https://github.com/sponsors/robcaulk
"""
- version = "3.13.0-rc.14"
+ version = "3.13.0-rc.15"
_CALIBRATION_START_KEY: Final[str] = "quickadapter_calibration_start"
_DEPLOYMENT_COORDINATE_MARKER_KEY: Final[str] = "quickadapter_deployment_coordinates"
get_custom_protections_config,
get_distance,
get_exit_pricing_config,
+ get_exit_stage_stake_fractions,
get_fit_live_predictions_candles,
get_label_defaults,
get_label_horizon_candles,
_ANNOTATION_LINE_OFFSET_CANDLES: Final[int] = 10
def version(self) -> str:
- return "3.13.0-rc.14"
+ return "3.13.0-rc.15"
timeframe = "5m"
timeframe_minutes = timeframe_to_minutes(timeframe)
position_adjustment_enable = True
- # {stage: (stake_percent, color)}. The reciprocal-extension fractions are
- # not literals here: they resolve from the configured
- # ``exit_pricing.take_profit_stage_natr_multiplier_fraction_series`` ladder,
- # which is their single source of truth. The final rung stays the literal.
- partial_exit_stages: ClassVar[dict[int, tuple[float, str]]] = {
- 0: (0.4, "lime"),
- 1: (0.3, "yellow"),
- 2: (0.2, "coral"),
+ # {stage: color} for the whole exit ladder, the final full exit included.
+ # The entry count is the single source of truth for the ladder: distances,
+ # stake shares and the final rung all derive from it. Adding or removing a
+ # rung is the only edit needed.
+ exit_stages: ClassVar[dict[int, str]] = {
+ 0: "lime",
+ 1: "yellow",
+ 2: "coral",
+ 3: "deepskyblue",
}
- # (natr_multiplier_fraction, stake_percent, color)
- _FINAL_EXIT_STAGE_PARAMS: Final[tuple[float, float, str]] = (
- 1.0,
- 1.0,
- "deepskyblue",
- )
-
- # Final full-exit stage, derived from the configured partial exits.
- _FINAL_EXIT_STAGE: Final[int] = max(partial_exit_stages.keys(), default=-1) + 1
-
# ``get_trade_exit_stage`` derives a stage from the number of filled take-profit
# exits, so every stage it can reach must exist here. A gap would price a
# missing stage at the final rung instead of arming it.
- assert sorted(partial_exit_stages) == list(range(len(partial_exit_stages)))
+ assert sorted(exit_stages) == list(range(len(exit_stages)))
_TAKE_PROFIT_ORDER_TAG_PREFIX: Final[str] = "take_profit_"
_FINAL_TAKE_PROFIT_STATE_KEY: Final[str] = "final_take_profit_state"
return str(self.exit_pricing["take_profit_stage_natr_multiplier_fraction_series"])
@cached_property
- def partial_exit_stage_natr_multiplier_fractions(self) -> dict[int, float]:
- """Reciprocal-extension fractions of the full take-profit distance, by stage."""
+ def exit_stage_natr_multiplier_fractions(self) -> dict[int, float]:
+ """Target distance of each stage as a fraction of the full distance.
+
+ Partial rungs follow the configured reciprocal-extension series; the
+ final rung sits at the full distance.
+ """
+ partial_stages = QuickAdapterV3.partial_exit_stages()
fractions = get_take_profit_stage_natr_multiplier_fractions(
self.take_profit_stage_natr_multiplier_fraction_series,
- len(QuickAdapterV3.partial_exit_stages),
+ len(partial_stages),
)
- return dict(zip(sorted(QuickAdapterV3.partial_exit_stages), fractions, strict=True))
+ ladder = dict(zip(partial_stages, fractions, strict=True))
+ ladder[QuickAdapterV3.final_exit_stage()] = 1.0
+ return ladder
+
+ @cached_property
+ def exit_stage_stake_fractions(self) -> dict[int, float]:
+ """Nominal share of the stake still open that each stage requests.
+
+ With ``n`` stages, stage ``k`` requests ``1 / (n - k)`` of the remaining
+ stake: nominally ``1 / n`` of the initial stake with complete fills and
+ no exchange sizing adjustments. The last stage closes the remainder.
+ """
+ fractions = get_exit_stage_stake_fractions(len(QuickAdapterV3.exit_stages))
+ return dict(zip(sorted(QuickAdapterV3.exit_stages), fractions, strict=True))
def get_exit_stage_natr_multiplier_fraction(self, exit_stage: int) -> float:
- """Return a partial reciprocal-extension fraction or the final fraction ``1.0``."""
- fractions = self.partial_exit_stage_natr_multiplier_fractions
- if exit_stage in fractions:
- return fractions[exit_stage]
- return QuickAdapterV3._FINAL_EXIT_STAGE_PARAMS[0]
+ """Return the stage's distance fraction, or the full distance if unknown."""
+ return self.exit_stage_natr_multiplier_fractions.get(exit_stage, 1.0)
+
+ @staticmethod
+ def partial_exit_stages() -> tuple[int, ...]:
+ """Every rung but the last, which closes the remainder."""
+ return tuple(sorted(QuickAdapterV3.exit_stages)[:-1])
+
+ @staticmethod
+ def final_exit_stage() -> int:
+ """The last rung, which closes whatever the earlier ones left."""
+ return max(QuickAdapterV3.exit_stages)
+
+ @staticmethod
+ def is_partial_exit_stage(exit_stage: int) -> bool:
+ """Whether ``exit_stage`` releases one slice rather than the remainder."""
+ return exit_stage in QuickAdapterV3.partial_exit_stages()
@cached_property
def reversal_confirmation(self) -> dict[str, int | float]:
trade_natr_method = self.trade_natr_method
final_take_profit_retracement_fraction = self.final_take_profit_retracement_fraction
fraction_series = self.take_profit_stage_natr_multiplier_fraction_series
- partial_exit_stage_fractions = self.partial_exit_stage_natr_multiplier_fractions
protections = self.protections
logger.info("=" * 60)
f" natr_multiplier_fraction: {format_number(QuickAdapterV3._CUSTOM_STOPLOSS_NATR_MULTIPLIER_FRACTION)}"
)
- logger.info("Partial Take-Profit Stages:")
- for stage, (
- stake_percent,
- color,
- ) in QuickAdapterV3.partial_exit_stages.items():
+ stage_count = len(QuickAdapterV3.exit_stages)
+ distance_fractions = self.exit_stage_natr_multiplier_fractions
+ stake_fractions = self.exit_stage_stake_fractions
+ logger.info(f"Exit Stages: {stage_count} nominally equal shares of the initial stake")
+ for stage in sorted(QuickAdapterV3.exit_stages):
logger.info(
f" stage {stage}: natr_multiplier_fraction="
- f"{format_number(partial_exit_stage_fractions[stage])}, "
- f"stake_percent={format_number(stake_percent)}, color={color}"
+ f"{format_number(distance_fractions[stage])}, "
+ f"stake_fraction_of_remaining={format_number(stake_fractions[stage])}, "
+ f"stake_share_of_initial={format_number(1 / stage_count)}, "
+ f"color={QuickAdapterV3.exit_stages[stage]}"
+ + (
+ " (final, closes the remainder)"
+ if stage == QuickAdapterV3.final_exit_stage()
+ else ""
+ )
)
- logger.info("Final Exit:")
- logger.info(
- f" natr_multiplier_fraction: {format_number(QuickAdapterV3._FINAL_EXIT_STAGE_PARAMS[0])}"
- )
- logger.info(f" stake_percent: {format_number(QuickAdapterV3._FINAL_EXIT_STAGE_PARAMS[1])}")
- logger.info(f" color: {QuickAdapterV3._FINAL_EXIT_STAGE_PARAMS[2]}")
-
logger.info("Protections:")
if protections:
for protection in protections:
for order in trade.select_filled_orders(trade.exit_side)
if (order.ft_order_tag or "").startswith(QuickAdapterV3._TAKE_PROFIT_ORDER_TAG_PREFIX)
)
- return min(n_filled_take_profit_exits, QuickAdapterV3._FINAL_EXIT_STAGE)
+ return min(n_filled_take_profit_exits, QuickAdapterV3.final_exit_stage())
@staticmethod
@lru_cache(maxsize=_CACHE_MAXSIZE_LARGE)
return None
trade_exit_stage = QuickAdapterV3.get_trade_exit_stage(trade)
- if trade_exit_stage not in QuickAdapterV3.partial_exit_stages:
+ if not QuickAdapterV3.is_partial_exit_stage(trade_exit_stage):
return None
df, _ = self.dp.get_analyzed_dataframe(pair=pair, timeframe=self.config.get("timeframe"))
),
)
if trade_partial_exit:
- trade_stake_percent = QuickAdapterV3.partial_exit_stages[trade_exit_stage][0]
- trade_partial_stake_amount = trade_stake_percent * trade.stake_amount
+ remaining_stages = len(QuickAdapterV3.exit_stages) - trade_exit_stage
tag = (
f"{QuickAdapterV3._TAKE_PROFIT_ORDER_TAG_PREFIX}"
f"{trade.trade_direction}_{trade_exit_stage}"
current_position_value = trade.amount * current_exit_rate
if current_position_value <= remaining_minimum_value:
return -trade.stake_amount, tag
- trade_partial_stake_amount = min(
- trade_partial_stake_amount,
- trade.stake_amount * (1 - remaining_minimum_value / current_position_value),
- )
- exit_amount = exchange.amount_to_contract_precision(
- pair,
- abs(
- float(
- FtPrecise(trade_partial_stake_amount)
- * FtPrecise(trade.amount)
- / FtPrecise(trade.stake_amount)
- )
- ),
+ raw_exit_amount = min(
+ float(FtPrecise(trade.amount) / FtPrecise(remaining_stages)),
+ trade.amount - remaining_minimum_value / current_exit_rate,
)
+ exit_amount = exchange.amount_to_contract_precision(pair, raw_exit_amount)
if (
exit_amount <= 0
or exit_amount * current_exit_rate < exit_minimum_value
or (trade.amount - exit_amount) * current_exit_rate < remaining_minimum_value
):
return -trade.stake_amount, tag
- return (
- -trade_partial_stake_amount,
- tag,
+ # Use a native-domain antecedent; exchange quantization need not be idempotent.
+ native_raw_exit_amount = FtPrecise(raw_exit_amount) / FtPrecise(1)
+ native_raw_exit_quantity = float(native_raw_exit_amount)
+ if (
+ native_raw_exit_quantity != raw_exit_amount
+ and exchange.amount_to_contract_precision(pair, native_raw_exit_quantity)
+ != exit_amount
+ ):
+ native_raw_exit_quantity = float(native_raw_exit_amount + FtPrecise("1e-18"))
+ if (
+ exchange.amount_to_contract_precision(pair, native_raw_exit_quantity)
+ != exit_amount
+ ):
+ return -trade.stake_amount, tag
+ trade_partial_stake_amount = (
+ native_raw_exit_quantity / trade.amount * trade.stake_amount
)
+ rounding_up = None
+ while 0.0 < trade_partial_stake_amount < trade.stake_amount:
+ roundtrip_amount = exchange.amount_to_contract_precision(
+ pair,
+ abs(
+ float(
+ FtPrecise(trade_partial_stake_amount)
+ * FtPrecise(trade.amount)
+ / FtPrecise(trade.stake_amount)
+ )
+ ),
+ )
+ if roundtrip_amount == exit_amount:
+ return -trade_partial_stake_amount, tag
+ if rounding_up is None:
+ rounding_up = roundtrip_amount < exit_amount
+ elif (roundtrip_amount < exit_amount) != rounding_up:
+ # Adjacent callback floats straddle the lot: no exact request exists.
+ break
+ trade_partial_stake_amount = math.nextafter(
+ trade_partial_stake_amount, math.inf if rounding_up else 0.0
+ )
+ return -trade.stake_amount, tag
return None
return None
trade_exit_stage = QuickAdapterV3.get_trade_exit_stage(trade)
- if trade_exit_stage in QuickAdapterV3.partial_exit_stages:
+ if QuickAdapterV3.is_partial_exit_stage(trade_exit_stage):
return None
if not has_valid_candle_date:
trade_exit_stage = QuickAdapterV3.get_trade_exit_stage(trade)
- for take_profit_stage in QuickAdapterV3.partial_exit_stages:
+ for take_profit_stage in QuickAdapterV3.partial_exit_stages():
if take_profit_stage < trade_exit_stage:
continue
"end": end_date,
"y_start": partial_take_profit_price,
"y_end": partial_take_profit_price,
- "color": QuickAdapterV3.partial_exit_stages[take_profit_stage][1],
+ "color": QuickAdapterV3.exit_stages[take_profit_stage],
"line_style": "solid",
"width": 1,
"label": f"Partial Take-Profit Stage {take_profit_stage}",
}
annotations.append(take_profit_line_annotation)
- final_exit_stage = QuickAdapterV3._FINAL_EXIT_STAGE
+ final_exit_stage = QuickAdapterV3.final_exit_stage()
raw_final_take_profit_state = trade.get_custom_data(
QuickAdapterV3._FINAL_TAKE_PROFIT_STATE_KEY
)
"end": end_date,
"y_start": final_take_profit_price,
"y_end": final_take_profit_price,
- "color": QuickAdapterV3._FINAL_EXIT_STAGE_PARAMS[2],
+ "color": QuickAdapterV3.exit_stages[
+ QuickAdapterV3.final_exit_stage()
+ ],
"line_style": "solid",
"width": 1,
"label": "Final Take-Profit Trail (current)",
"end": end_date,
"y_start": final_take_profit_price,
"y_end": final_take_profit_price,
- "color": QuickAdapterV3._FINAL_EXIT_STAGE_PARAMS[2],
+ "color": QuickAdapterV3.exit_stages[QuickAdapterV3.final_exit_stage()],
"line_style": "solid",
"width": 1,
"label": "Final Take-Profit Arming Target",
# These fractions place partial targets inside the full take-profit distance;
# they do not extend it. Fibonacci uses integer powers of phi; pi uses integer
# powers of pi as a custom geometric construction, not a trading convention.
-# The final fraction ``1.0`` is the separate ``_FINAL_EXIT_STAGE_PARAMS``
-# literal.
+# The strategy appends the final fraction ``1.0`` to the generated
+# partial-target distance ladder.
_TAKE_PROFIT_STAGE_NATR_MULTIPLIER_FRACTION_BASES: Final[dict[str, float]] = {
"fibonacci_extensions": (1.0 + math.sqrt(5.0)) / 2.0,
"pi_extensions": math.pi,
return fractions
+@lru_cache(maxsize=_CACHE_MAXSIZE_SMALL)
+def get_exit_stage_stake_fractions(stage_count: int) -> tuple[float, ...]:
+ """Return each exit's share of the stake still open at that stage.
+
+ A position split across ``stage_count`` exits releases ``1 / stage_count``
+ of its initial stake at each one. The stake remaining before stage ``k`` is
+ ``(stage_count - k) / stage_count`` of the initial one, so releasing
+ ``1 / (stage_count - k)`` of it closes exactly one share. The last stage
+ takes the whole remainder.
+ """
+ if stage_count <= 0:
+ raise ValueError(f"Invalid stage_count value {stage_count!r}: must be >= 1")
+ return tuple(1.0 / (stage_count - stage) for stage in range(stage_count))
+
+
SPARSE_TRAINING_MASS_THRESHOLD: Final[float] = 0.05
DEFAULT_FIT_LIVE_PREDICTIONS_CANDLES: Final[int] = 100
repositories / freqai-strategies.git / commitdiff
