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Merge branch 'develop' into add-plot-feature-importance

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Robert Caulk 2022-09-18 00:02:46 +02:00 committed by GitHub
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3
docs/exchanges.md
View File

@ -57,7 +57,8 @@ This configuration enables kraken, as well as rate-limiting to avoid bans from t
Binance supports [time_in_force](configuration.md#understand-order_time_in_force). Binance supports [time_in_force](configuration.md#understand-order_time_in_force).
!!! Tip "Stoploss on Exchange" !!! Tip "Stoploss on Exchange"
Binance supports `stoploss_on_exchange` and uses `stop-loss-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.. Binance supports `stoploss_on_exchange` and uses `stop-loss-limit` orders. It provides great advantages, so we recommend to benefit from it by enabling stoploss on exchange.
On futures, Binance supports both `stop-limit` as well as `stop-market` orders. You can use either `"limit"` or `"market"` in the `order_types.stoploss` configuration setting to decide which type to use.
### Binance Blacklist ### Binance Blacklist

13
docs/freqai.md
View File

@ -190,19 +190,6 @@ The FreqAI strategy requires the user to include the following lines of code in
# passed to any single indicator) # passed to any single indicator)
startup_candle_count: int = 20 startup_candle_count: int = 20
def informative_pairs(self):
whitelist_pairs = self.dp.current_whitelist()
corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
informative_pairs = []
for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
for pair in whitelist_pairs:
informative_pairs.append((pair, tf))
for pair in corr_pairs:
if pair in whitelist_pairs:
continue # avoid duplication
informative_pairs.append((pair, tf))
return informative_pairs
def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame: def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
# the model will return all labels created by user in `populate_any_indicators` # the model will return all labels created by user in `populate_any_indicators`

7
freqtrade/exchange/binance.py
View File

@ -31,7 +31,7 @@ class Binance(Exchange):
"ccxt_futures_name": "future" "ccxt_futures_name": "future"
} }
_ft_has_futures: Dict = { _ft_has_futures: Dict = {
"stoploss_order_types": {"limit": "stop"}, "stoploss_order_types": {"limit": "limit", "market": "market"},
"tickers_have_price": False, "tickers_have_price": False,
} }
@ -48,13 +48,12 @@ class Binance(Exchange):
Returns True if adjustment is necessary. Returns True if adjustment is necessary.
:param side: "buy" or "sell" :param side: "buy" or "sell"
""" """
order_types = ('stop_loss_limit', 'stop', 'stop_market')
ordertype = 'stop' if self.trading_mode == TradingMode.FUTURES else 'stop_loss_limit'
return ( return (
order.get('stopPrice', None) is None order.get('stopPrice', None) is None
or ( or (
order['type'] == ordertype order['type'] in order_types
and ( and (
(side == "sell" and stop_loss > float(order['stopPrice'])) or (side == "sell" and stop_loss > float(order['stopPrice'])) or
(side == "buy" and stop_loss < float(order['stopPrice'])) (side == "buy" and stop_loss < float(order['stopPrice']))

686
freqtrade/exchange/binance_leverage_tiers.json
View File

@ -81,6 +81,104 @@
} }
} }
], ],
"1000LUNC/USDT": [
{
"tier": 1.0,
"currency": "USDT",
"minNotional": 0.0,
"maxNotional": 5000.0,
"maintenanceMarginRate": 0.01,
"maxLeverage": 25.0,
"info": {
"bracket": "1",
"initialLeverage": "25",
"notionalCap": "5000",
"notionalFloor": "0",
"maintMarginRatio": "0.01",
"cum": "0.0"
}
},
{
"tier": 2.0,
"currency": "USDT",
"minNotional": 5000.0,
"maxNotional": 25000.0,
"maintenanceMarginRate": 0.025,
"maxLeverage": 20.0,
"info": {
"bracket": "2",
"initialLeverage": "20",
"notionalCap": "25000",
"notionalFloor": "5000",
"maintMarginRatio": "0.025",
"cum": "75.0"
}
},
{
"tier": 3.0,
"currency": "USDT",
"minNotional": 25000.0,
"maxNotional": 100000.0,
"maintenanceMarginRate": 0.05,
"maxLeverage": 10.0,
"info": {
"bracket": "3",
"initialLeverage": "10",
"notionalCap": "100000",
"notionalFloor": "25000",
"maintMarginRatio": "0.05",
"cum": "700.0"
}
},
{
"tier": 4.0,
"currency": "USDT",
"minNotional": 100000.0,
"maxNotional": 250000.0,
"maintenanceMarginRate": 0.1,
"maxLeverage": 5.0,
"info": {
"bracket": "4",
"initialLeverage": "5",
"notionalCap": "250000",
"notionalFloor": "100000",
"maintMarginRatio": "0.1",
"cum": "5700.0"
}
},
{
"tier": 5.0,
"currency": "USDT",
"minNotional": 250000.0,
"maxNotional": 1000000.0,
"maintenanceMarginRate": 0.125,
"maxLeverage": 2.0,
"info": {
"bracket": "5",
"initialLeverage": "2",
"notionalCap": "1000000",
"notionalFloor": "250000",
"maintMarginRatio": "0.125",
"cum": "11950.0"
}
},
{
"tier": 6.0,
"currency": "USDT",
"minNotional": 1000000.0,
"maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5,
"maxLeverage": 1.0,
"info": {
"bracket": "6",
"initialLeverage": "1",
"notionalCap": "5000000",
"notionalFloor": "1000000",
"maintMarginRatio": "0.5",
"cum": "386950.0"
}
}
],
"1000SHIB/BUSD": [ "1000SHIB/BUSD": [
{ {
"tier": 1.0, "tier": 1.0,
@ -1109,6 +1207,88 @@
} }
} }
], ],
"AMB/BUSD": [
{
"tier": 1.0,
"currency": "BUSD",
"minNotional": 0.0,
"maxNotional": 25000.0,
"maintenanceMarginRate": 0.025,
"maxLeverage": 20.0,
"info": {
"bracket": "1",
"initialLeverage": "20",
"notionalCap": "25000",
"notionalFloor": "0",
"maintMarginRatio": "0.025",
"cum": "0.0"
}
},
{
"tier": 2.0,
"currency": "BUSD",
"minNotional": 25000.0,
"maxNotional": 100000.0,
"maintenanceMarginRate": 0.05,
"maxLeverage": 10.0,
"info": {
"bracket": "2",
"initialLeverage": "10",
"notionalCap": "100000",
"notionalFloor": "25000",
"maintMarginRatio": "0.05",
"cum": "625.0"
}
},
{
"tier": 3.0,
"currency": "BUSD",
"minNotional": 100000.0,
"maxNotional": 250000.0,
"maintenanceMarginRate": 0.1,
"maxLeverage": 5.0,
"info": {
"bracket": "3",
"initialLeverage": "5",
"notionalCap": "250000",
"notionalFloor": "100000",
"maintMarginRatio": "0.1",
"cum": "5625.0"
}
},
{
"tier": 4.0,
"currency": "BUSD",
"minNotional": 250000.0,
"maxNotional": 1000000.0,
"maintenanceMarginRate": 0.125,
"maxLeverage": 2.0,
"info": {
"bracket": "4",
"initialLeverage": "2",
"notionalCap": "1000000",
"notionalFloor": "250000",
"maintMarginRatio": "0.125",
"cum": "11875.0"
}
},
{
"tier": 5.0,
"currency": "BUSD",
"minNotional": 1000000.0,
"maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5,
"maxLeverage": 1.0,
"info": {
"bracket": "5",
"initialLeverage": "1",
"notionalCap": "5000000",
"notionalFloor": "1000000",
"maintMarginRatio": "0.5",
"cum": "386875.0"
}
}
],
"ANC/BUSD": [ "ANC/BUSD": [
{ {
"tier": 1.0, "tier": 1.0,
@ -3300,13 +3480,13 @@
"tier": 6.0, "tier": 6.0,
"currency": "USDT", "currency": "USDT",
"minNotional": 1000000.0, "minNotional": 1000000.0,
"maxNotional": 30000000.0, "maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5, "maintenanceMarginRate": 0.5,
"maxLeverage": 1.0, "maxLeverage": 1.0,
"info": { "info": {
"bracket": "6", "bracket": "6",
"initialLeverage": "1", "initialLeverage": "1",
"notionalCap": "30000000", "notionalCap": "5000000",
"notionalFloor": "1000000", "notionalFloor": "1000000",
"maintMarginRatio": "0.5", "maintMarginRatio": "0.5",
"cum": "386950.0" "cum": "386950.0"
@ -4880,13 +5060,13 @@
"tier": 6.0, "tier": 6.0,
"currency": "USDT", "currency": "USDT",
"minNotional": 1000000.0, "minNotional": 1000000.0,
"maxNotional": 30000000.0, "maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5, "maintenanceMarginRate": 0.5,
"maxLeverage": 1.0, "maxLeverage": 1.0,
"info": { "info": {
"bracket": "6", "bracket": "6",
"initialLeverage": "1", "initialLeverage": "1",
"notionalCap": "30000000", "notionalCap": "5000000",
"notionalFloor": "1000000", "notionalFloor": "1000000",
"maintMarginRatio": "0.5", "maintMarginRatio": "0.5",
"cum": "386940.0" "cum": "386940.0"
@ -8333,6 +8513,104 @@
} }
} }
], ],
"FOOTBALL/USDT": [
{
"tier": 1.0,
"currency": "USDT",
"minNotional": 0.0,
"maxNotional": 5000.0,
"maintenanceMarginRate": 0.01,
"maxLeverage": 25.0,
"info": {
"bracket": "1",
"initialLeverage": "25",
"notionalCap": "5000",
"notionalFloor": "0",
"maintMarginRatio": "0.01",
"cum": "0.0"
}
},
{
"tier": 2.0,
"currency": "USDT",
"minNotional": 5000.0,
"maxNotional": 25000.0,
"maintenanceMarginRate": 0.025,
"maxLeverage": 20.0,
"info": {
"bracket": "2",
"initialLeverage": "20",
"notionalCap": "25000",
"notionalFloor": "5000",
"maintMarginRatio": "0.025",
"cum": "75.0"
}
},
{
"tier": 3.0,
"currency": "USDT",
"minNotional": 25000.0,
"maxNotional": 100000.0,
"maintenanceMarginRate": 0.05,
"maxLeverage": 10.0,
"info": {
"bracket": "3",
"initialLeverage": "10",
"notionalCap": "100000",
"notionalFloor": "25000",
"maintMarginRatio": "0.05",
"cum": "700.0"
}
},
{
"tier": 4.0,
"currency": "USDT",
"minNotional": 100000.0,
"maxNotional": 250000.0,
"maintenanceMarginRate": 0.1,
"maxLeverage": 5.0,
"info": {
"bracket": "4",
"initialLeverage": "5",
"notionalCap": "250000",
"notionalFloor": "100000",
"maintMarginRatio": "0.1",
"cum": "5700.0"
}
},
{
"tier": 5.0,
"currency": "USDT",
"minNotional": 250000.0,
"maxNotional": 1000000.0,
"maintenanceMarginRate": 0.125,
"maxLeverage": 2.0,
"info": {
"bracket": "5",
"initialLeverage": "2",
"notionalCap": "1000000",
"notionalFloor": "250000",
"maintMarginRatio": "0.125",
"cum": "11950.0"
}
},
{
"tier": 6.0,
"currency": "USDT",
"minNotional": 1000000.0,
"maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5,
"maxLeverage": 1.0,
"info": {
"bracket": "6",
"initialLeverage": "1",
"notionalCap": "5000000",
"notionalFloor": "1000000",
"maintMarginRatio": "0.5",
"cum": "386950.0"
}
}
],
"FTM/BUSD": [ "FTM/BUSD": [
{ {
"tier": 1.0, "tier": 1.0,
@ -12123,6 +12401,104 @@
} }
} }
], ],
"LUNA2/USDT": [
{
"tier": 1.0,
"currency": "USDT",
"minNotional": 0.0,
"maxNotional": 5000.0,
"maintenanceMarginRate": 0.015,
"maxLeverage": 25.0,
"info": {
"bracket": "1",
"initialLeverage": "25",
"notionalCap": "5000",
"notionalFloor": "0",
"maintMarginRatio": "0.015",
"cum": "0.0"
}
},
{
"tier": 2.0,
"currency": "USDT",
"minNotional": 5000.0,
"maxNotional": 25000.0,
"maintenanceMarginRate": 0.025,
"maxLeverage": 20.0,
"info": {
"bracket": "2",
"initialLeverage": "20",
"notionalCap": "25000",
"notionalFloor": "5000",
"maintMarginRatio": "0.025",
"cum": "50.0"
}
},
{
"tier": 3.0,
"currency": "USDT",
"minNotional": 25000.0,
"maxNotional": 100000.0,
"maintenanceMarginRate": 0.05,
"maxLeverage": 10.0,
"info": {
"bracket": "3",
"initialLeverage": "10",
"notionalCap": "100000",
"notionalFloor": "25000",
"maintMarginRatio": "0.05",
"cum": "675.0"
}
},
{
"tier": 4.0,
"currency": "USDT",
"minNotional": 100000.0,
"maxNotional": 250000.0,
"maintenanceMarginRate": 0.1,
"maxLeverage": 5.0,
"info": {
"bracket": "4",
"initialLeverage": "5",
"notionalCap": "250000",
"notionalFloor": "100000",
"maintMarginRatio": "0.1",
"cum": "5675.0"
}
},
{
"tier": 5.0,
"currency": "USDT",
"minNotional": 250000.0,
"maxNotional": 1000000.0,
"maintenanceMarginRate": 0.125,
"maxLeverage": 2.0,
"info": {
"bracket": "5",
"initialLeverage": "2",
"notionalCap": "1000000",
"notionalFloor": "250000",
"maintMarginRatio": "0.125",
"cum": "11925.0"
}
},
{
"tier": 6.0,
"currency": "USDT",
"minNotional": 1000000.0,
"maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5,
"maxLeverage": 1.0,
"info": {
"bracket": "6",
"initialLeverage": "1",
"notionalCap": "5000000",
"notionalFloor": "1000000",
"maintMarginRatio": "0.5",
"cum": "386925.0"
}
}
],
"MANA/USDT": [ "MANA/USDT": [
{ {
"tier": 1.0, "tier": 1.0,
@ -13028,10 +13404,10 @@
"minNotional": 0.0, "minNotional": 0.0,
"maxNotional": 5000.0, "maxNotional": 5000.0,
"maintenanceMarginRate": 0.01, "maintenanceMarginRate": 0.01,
"maxLeverage": 50.0, "maxLeverage": 25.0,
"info": { "info": {
"bracket": "1", "bracket": "1",
"initialLeverage": "50", "initialLeverage": "25",
"notionalCap": "5000", "notionalCap": "5000",
"notionalFloor": "0", "notionalFloor": "0",
"maintMarginRatio": "0.01", "maintMarginRatio": "0.01",
@ -13805,6 +14181,88 @@
} }
} }
], ],
"PHB/BUSD": [
{
"tier": 1.0,
"currency": "BUSD",
"minNotional": 0.0,
"maxNotional": 25000.0,
"maintenanceMarginRate": 0.025,
"maxLeverage": 20.0,
"info": {
"bracket": "1",
"initialLeverage": "20",
"notionalCap": "25000",
"notionalFloor": "0",
"maintMarginRatio": "0.025",
"cum": "0.0"
}
},
{
"tier": 2.0,
"currency": "BUSD",
"minNotional": 25000.0,
"maxNotional": 100000.0,
"maintenanceMarginRate": 0.05,
"maxLeverage": 10.0,
"info": {
"bracket": "2",
"initialLeverage": "10",
"notionalCap": "100000",
"notionalFloor": "25000",
"maintMarginRatio": "0.05",
"cum": "625.0"
}
},
{
"tier": 3.0,
"currency": "BUSD",
"minNotional": 100000.0,
"maxNotional": 250000.0,
"maintenanceMarginRate": 0.1,
"maxLeverage": 5.0,
"info": {
"bracket": "3",
"initialLeverage": "5",
"notionalCap": "250000",
"notionalFloor": "100000",
"maintMarginRatio": "0.1",
"cum": "5625.0"
}
},
{
"tier": 4.0,
"currency": "BUSD",
"minNotional": 250000.0,
"maxNotional": 1000000.0,
"maintenanceMarginRate": 0.125,
"maxLeverage": 2.0,
"info": {
"bracket": "4",
"initialLeverage": "2",
"notionalCap": "1000000",
"notionalFloor": "250000",
"maintMarginRatio": "0.125",
"cum": "11875.0"
}
},
{
"tier": 5.0,
"currency": "BUSD",
"minNotional": 1000000.0,
"maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5,
"maxLeverage": 1.0,
"info": {
"bracket": "5",
"initialLeverage": "1",
"notionalCap": "5000000",
"notionalFloor": "1000000",
"maintMarginRatio": "0.5",
"cum": "386875.0"
}
}
],
"QTUM/USDT": [ "QTUM/USDT": [
{ {
"tier": 1.0, "tier": 1.0,
@ -14008,10 +14466,10 @@
"minNotional": 0.0, "minNotional": 0.0,
"maxNotional": 5000.0, "maxNotional": 5000.0,
"maintenanceMarginRate": 0.01, "maintenanceMarginRate": 0.01,
"maxLeverage": 50.0, "maxLeverage": 25.0,
"info": { "info": {
"bracket": "1", "bracket": "1",
"initialLeverage": "50", "initialLeverage": "25",
"notionalCap": "5000", "notionalCap": "5000",
"notionalFloor": "0", "notionalFloor": "0",
"maintMarginRatio": "0.01", "maintMarginRatio": "0.01",
@ -14478,13 +14936,13 @@
"tier": 6.0, "tier": 6.0,
"currency": "USDT", "currency": "USDT",
"minNotional": 1000000.0, "minNotional": 1000000.0,
"maxNotional": 30000000.0, "maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5, "maintenanceMarginRate": 0.5,
"maxLeverage": 1.0, "maxLeverage": 1.0,
"info": { "info": {
"bracket": "6", "bracket": "6",
"initialLeverage": "1", "initialLeverage": "1",
"notionalCap": "30000000", "notionalCap": "5000000",
"notionalFloor": "1000000", "notionalFloor": "1000000",
"maintMarginRatio": "0.5", "maintMarginRatio": "0.5",
"cum": "386950.0" "cum": "386950.0"
@ -14576,13 +15034,13 @@
"tier": 6.0, "tier": 6.0,
"currency": "USDT", "currency": "USDT",
"minNotional": 1000000.0, "minNotional": 1000000.0,
"maxNotional": 30000000.0, "maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5, "maintenanceMarginRate": 0.5,
"maxLeverage": 1.0, "maxLeverage": 1.0,
"info": { "info": {
"bracket": "6", "bracket": "6",
"initialLeverage": "1", "initialLeverage": "1",
"notionalCap": "30000000", "notionalCap": "5000000",
"notionalFloor": "1000000", "notionalFloor": "1000000",
"maintMarginRatio": "0.5", "maintMarginRatio": "0.5",
"cum": "386950.0" "cum": "386950.0"
@ -15487,6 +15945,104 @@
} }
} }
], ],
"SPELL/USDT": [
{
"tier": 1.0,
"currency": "USDT",
"minNotional": 0.0,
"maxNotional": 5000.0,
"maintenanceMarginRate": 0.01,
"maxLeverage": 25.0,
"info": {
"bracket": "1",
"initialLeverage": "25",
"notionalCap": "5000",
"notionalFloor": "0",
"maintMarginRatio": "0.01",
"cum": "0.0"
}
},
{
"tier": 2.0,
"currency": "USDT",
"minNotional": 5000.0,
"maxNotional": 25000.0,
"maintenanceMarginRate": 0.025,
"maxLeverage": 20.0,
"info": {
"bracket": "2",
"initialLeverage": "20",
"notionalCap": "25000",
"notionalFloor": "5000",
"maintMarginRatio": "0.025",
"cum": "75.0"
}
},
{
"tier": 3.0,
"currency": "USDT",
"minNotional": 25000.0,
"maxNotional": 100000.0,
"maintenanceMarginRate": 0.05,
"maxLeverage": 10.0,
"info": {
"bracket": "3",
"initialLeverage": "10",
"notionalCap": "100000",
"notionalFloor": "25000",
"maintMarginRatio": "0.05",
"cum": "700.0"
}
},
{
"tier": 4.0,
"currency": "USDT",
"minNotional": 100000.0,
"maxNotional": 250000.0,
"maintenanceMarginRate": 0.1,
"maxLeverage": 5.0,
"info": {
"bracket": "4",
"initialLeverage": "5",
"notionalCap": "250000",
"notionalFloor": "100000",
"maintMarginRatio": "0.1",
"cum": "5700.0"
}
},
{
"tier": 5.0,
"currency": "USDT",
"minNotional": 250000.0,
"maxNotional": 1000000.0,
"maintenanceMarginRate": 0.125,
"maxLeverage": 2.0,
"info": {
"bracket": "5",
"initialLeverage": "2",
"notionalCap": "1000000",
"notionalFloor": "250000",
"maintMarginRatio": "0.125",
"cum": "11950.0"
}
},
{
"tier": 6.0,
"currency": "USDT",
"minNotional": 1000000.0,
"maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5,
"maxLeverage": 1.0,
"info": {
"bracket": "6",
"initialLeverage": "1",
"notionalCap": "5000000",
"notionalFloor": "1000000",
"maintMarginRatio": "0.5",
"cum": "386950.0"
}
}
],
"SRM/USDT": [ "SRM/USDT": [
{ {
"tier": 1.0, "tier": 1.0,
@ -15585,6 +16141,104 @@
} }
} }
], ],
"STG/USDT": [
{
"tier": 1.0,
"currency": "USDT",
"minNotional": 0.0,
"maxNotional": 5000.0,
"maintenanceMarginRate": 0.01,
"maxLeverage": 25.0,
"info": {
"bracket": "1",
"initialLeverage": "25",
"notionalCap": "5000",
"notionalFloor": "0",
"maintMarginRatio": "0.01",
"cum": "0.0"
}
},
{
"tier": 2.0,
"currency": "USDT",
"minNotional": 5000.0,
"maxNotional": 25000.0,
"maintenanceMarginRate": 0.025,
"maxLeverage": 20.0,
"info": {
"bracket": "2",
"initialLeverage": "20",
"notionalCap": "25000",
"notionalFloor": "5000",
"maintMarginRatio": "0.025",
"cum": "75.0"
}
},
{
"tier": 3.0,
"currency": "USDT",
"minNotional": 25000.0,
"maxNotional": 100000.0,
"maintenanceMarginRate": 0.05,
"maxLeverage": 10.0,
"info": {
"bracket": "3",
"initialLeverage": "10",
"notionalCap": "100000",
"notionalFloor": "25000",
"maintMarginRatio": "0.05",
"cum": "700.0"
}
},
{
"tier": 4.0,
"currency": "USDT",
"minNotional": 100000.0,
"maxNotional": 250000.0,
"maintenanceMarginRate": 0.1,
"maxLeverage": 5.0,
"info": {
"bracket": "4",
"initialLeverage": "5",
"notionalCap": "250000",
"notionalFloor": "100000",
"maintMarginRatio": "0.1",
"cum": "5700.0"
}
},
{
"tier": 5.0,
"currency": "USDT",
"minNotional": 250000.0,
"maxNotional": 1000000.0,
"maintenanceMarginRate": 0.125,
"maxLeverage": 2.0,
"info": {
"bracket": "5",
"initialLeverage": "2",
"notionalCap": "1000000",
"notionalFloor": "250000",
"maintMarginRatio": "0.125",
"cum": "11950.0"
}
},
{
"tier": 6.0,
"currency": "USDT",
"minNotional": 1000000.0,
"maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5,
"maxLeverage": 1.0,
"info": {
"bracket": "6",
"initialLeverage": "1",
"notionalCap": "5000000",
"notionalFloor": "1000000",
"maintMarginRatio": "0.5",
"cum": "386950.0"
}
}
],
"STMX/USDT": [ "STMX/USDT": [
{ {
"tier": 1.0, "tier": 1.0,
@ -16176,13 +16830,13 @@
"tier": 5.0, "tier": 5.0,
"currency": "BUSD", "currency": "BUSD",
"minNotional": 1000000.0, "minNotional": 1000000.0,
"maxNotional": 30000000.0, "maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5, "maintenanceMarginRate": 0.5,
"maxLeverage": 1.0, "maxLeverage": 1.0,
"info": { "info": {
"bracket": "5", "bracket": "5",
"initialLeverage": "1", "initialLeverage": "1",
"notionalCap": "30000000", "notionalCap": "5000000",
"notionalFloor": "1000000", "notionalFloor": "1000000",
"maintMarginRatio": "0.5", "maintMarginRatio": "0.5",
"cum": "386875.0" "cum": "386875.0"
@ -16470,13 +17124,13 @@
"tier": 6.0, "tier": 6.0,
"currency": "USDT", "currency": "USDT",
"minNotional": 1000000.0, "minNotional": 1000000.0,
"maxNotional": 30000000.0, "maxNotional": 5000000.0,
"maintenanceMarginRate": 0.5, "maintenanceMarginRate": 0.5,
"maxLeverage": 1.0, "maxLeverage": 1.0,
"info": { "info": {
"bracket": "6", "bracket": "6",
"initialLeverage": "1", "initialLeverage": "1",
"notionalCap": "30000000", "notionalCap": "5000000",
"notionalFloor": "1000000", "notionalFloor": "1000000",
"maintMarginRatio": "0.5", "maintMarginRatio": "0.5",
"cum": "386950.0" "cum": "386950.0"

2
freqtrade/exchange/exchange.py
View File

@ -2304,7 +2304,7 @@ class Exchange:
updated = tiers.get('updated') updated = tiers.get('updated')
if updated: if updated:
updated_dt = parser.parse(updated) updated_dt = parser.parse(updated)
if updated_dt < datetime.now(timezone.utc) - timedelta(days=1): if updated_dt < datetime.now(timezone.utc) - timedelta(weeks=4):
logger.info("Cached leverage tiers are outdated. Will update.") logger.info("Cached leverage tiers are outdated. Will update.")
return None return None
return tiers['data'] return tiers['data']

7
freqtrade/freqtradebot.py
View File

@ -1072,6 +1072,7 @@ class FreqtradeBot(LoggingMixin):
order_obj = Order.parse_from_ccxt_object(stoploss_order, trade.pair, 'stoploss') order_obj = Order.parse_from_ccxt_object(stoploss_order, trade.pair, 'stoploss')
trade.orders.append(order_obj) trade.orders.append(order_obj)
trade.stoploss_order_id = str(stoploss_order['id']) trade.stoploss_order_id = str(stoploss_order['id'])
trade.stoploss_last_update = datetime.now(timezone.utc)
return True return True
except InsufficientFundsError as e: except InsufficientFundsError as e:
logger.warning(f"Unable to place stoploss order {e}.") logger.warning(f"Unable to place stoploss order {e}.")
@ -1145,10 +1146,9 @@ class FreqtradeBot(LoggingMixin):
if self.create_stoploss_order(trade=trade, stop_price=stop_price): if self.create_stoploss_order(trade=trade, stop_price=stop_price):
# The above will return False if the placement failed and the trade was force-sold. # The above will return False if the placement failed and the trade was force-sold.
# in which case the trade will be closed - which we must check below. # in which case the trade will be closed - which we must check below.
trade.stoploss_last_update = datetime.utcnow()
return False return False
# If stoploss order is canceled for some reason we add it # If stoploss order is canceled for some reason we add it again
if (trade.is_open if (trade.is_open
and stoploss_order and stoploss_order
and stoploss_order['status'] in ('canceled', 'cancelled')): and stoploss_order['status'] in ('canceled', 'cancelled')):
@ -1186,7 +1186,8 @@ class FreqtradeBot(LoggingMixin):
if self.exchange.stoploss_adjust(stoploss_norm, order, side=trade.exit_side): if self.exchange.stoploss_adjust(stoploss_norm, order, side=trade.exit_side):
# we check if the update is necessary # we check if the update is necessary
update_beat = self.strategy.order_types.get('stoploss_on_exchange_interval', 60) update_beat = self.strategy.order_types.get('stoploss_on_exchange_interval', 60)
if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() >= update_beat: upd_req = datetime.now(timezone.utc) - timedelta(seconds=update_beat)
if trade.stoploss_last_update_utc and upd_req >= trade.stoploss_last_update_utc:
# cancelling the current stoploss on exchange first # cancelling the current stoploss on exchange first
logger.info(f"Cancelling current stoploss on exchange for pair {trade.pair} " logger.info(f"Cancelling current stoploss on exchange for pair {trade.pair} "
f"(orderid:{order['id']}) in order to add another one ...") f"(orderid:{order['id']}) in order to add another one ...")

17
freqtrade/optimize/backtesting.py
View File

@ -812,14 +812,6 @@ class Backtesting:
return trade return trade
time_in_force = self.strategy.order_time_in_force['entry'] time_in_force = self.strategy.order_time_in_force['entry']
if not pos_adjust:
# Confirm trade entry:
if not strategy_safe_wrapper(self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair, order_type=order_type, amount=stake_amount, rate=propose_rate,
time_in_force=time_in_force, current_time=current_time,
entry_tag=entry_tag, side=direction):
return trade
if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount): if stake_amount and (not min_stake_amount or stake_amount > min_stake_amount):
self.order_id_counter += 1 self.order_id_counter += 1
base_currency = self.exchange.get_pair_base_currency(pair) base_currency = self.exchange.get_pair_base_currency(pair)
@ -834,6 +826,15 @@ class Backtesting:
# Backcalculate actual stake amount. # Backcalculate actual stake amount.
stake_amount = amount * propose_rate / leverage stake_amount = amount * propose_rate / leverage
if not pos_adjust:
# Confirm trade entry:
if not strategy_safe_wrapper(
self.strategy.confirm_trade_entry, default_retval=True)(
pair=pair, order_type=order_type, amount=amount, rate=propose_rate,
time_in_force=time_in_force, current_time=current_time,
entry_tag=entry_tag, side=direction):
return trade
is_short = (direction == 'short') is_short = (direction == 'short')
# Necessary for Margin trading. Disabled until support is enabled. # Necessary for Margin trading. Disabled until support is enabled.
# interest_rate = self.exchange.get_interest_rate() # interest_rate = self.exchange.get_interest_rate()

9
freqtrade/persistence/trade_model.py
View File

@ -83,7 +83,7 @@ class Order(_DECL_BASE):
@property @property
def safe_price(self) -> float: def safe_price(self) -> float:
return self.average or self.price return self.average or self.price or self.stop_price
@property @property
def safe_filled(self) -> float: def safe_filled(self) -> float:
@ -376,6 +376,12 @@ class LocalTrade():
def open_date_utc(self): def open_date_utc(self):
return self.open_date.replace(tzinfo=timezone.utc) return self.open_date.replace(tzinfo=timezone.utc)
@property
def stoploss_last_update_utc(self):
if self.stoploss_last_update:
return self.stoploss_last_update.replace(tzinfo=timezone.utc)
return None
@property @property
def close_date_utc(self): def close_date_utc(self):
return self.close_date.replace(tzinfo=timezone.utc) return self.close_date.replace(tzinfo=timezone.utc)
@ -560,7 +566,6 @@ class LocalTrade():
self.stop_loss = stop_loss_norm self.stop_loss = stop_loss_norm
self.stop_loss_pct = -1 * abs(percent) self.stop_loss_pct = -1 * abs(percent)
self.stoploss_last_update = datetime.utcnow()
def adjust_stop_loss(self, current_price: float, stoploss: float, def adjust_stop_loss(self, current_price: float, stoploss: float,
initial: bool = False, refresh: bool = False) -> None: initial: bool = False, refresh: bool = False) -> None:

17
freqtrade/strategy/interface.py
View File

@ -613,6 +613,22 @@ class IStrategy(ABC, HyperStrategyMixin):
# END - Intended to be overridden by strategy # END - Intended to be overridden by strategy
### ###
def __informative_pairs_freqai(self) -> ListPairsWithTimeframes:
"""
Create informative-pairs needed for FreqAI
"""
if self.config.get('freqai', {}).get('enabled', False):
whitelist_pairs = self.dp.current_whitelist()
candle_type = self.config.get('candle_type_def', CandleType.SPOT)
corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
informative_pairs = []
for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
for pair in set(whitelist_pairs + corr_pairs):
informative_pairs.append((pair, tf, candle_type))
return informative_pairs
return []
def gather_informative_pairs(self) -> ListPairsWithTimeframes: def gather_informative_pairs(self) -> ListPairsWithTimeframes:
""" """
Internal method which gathers all informative pairs (user or automatically defined). Internal method which gathers all informative pairs (user or automatically defined).
@ -637,6 +653,7 @@ class IStrategy(ABC, HyperStrategyMixin):
else: else:
for pair in self.dp.current_whitelist(): for pair in self.dp.current_whitelist():
informative_pairs.append((pair, inf_data.timeframe, candle_type)) informative_pairs.append((pair, inf_data.timeframe, candle_type))
informative_pairs.extend(self.__informative_pairs_freqai())
return list(set(informative_pairs)) return list(set(informative_pairs))
def get_strategy_name(self) -> str: def get_strategy_name(self) -> str:

13
freqtrade/templates/FreqaiExampleStrategy.py
View File

@ -47,19 +47,6 @@ class FreqaiExampleStrategy(IStrategy):
std_dev_multiplier_sell = CategoricalParameter( std_dev_multiplier_sell = CategoricalParameter(
[0.1, 0.25, 0.4], space="sell", default=0.2, optimize=True) [0.1, 0.25, 0.4], space="sell", default=0.2, optimize=True)
def informative_pairs(self):
whitelist_pairs = self.dp.current_whitelist()
corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
informative_pairs = []
for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
for pair in whitelist_pairs:
informative_pairs.append((pair, tf))
for pair in corr_pairs:
if pair in whitelist_pairs:
continue # avoid duplication
informative_pairs.append((pair, tf))
return informative_pairs
def populate_any_indicators( def populate_any_indicators(
self, pair, df, tf, informative=None, set_generalized_indicators=False self, pair, df, tf, informative=None, set_generalized_indicators=False
): ):

14
freqtrade/templates/FreqaiHybridExampleStrategy.py
View File

@ -95,20 +95,6 @@ class FreqaiExampleHybridStrategy(IStrategy):
short_rsi = IntParameter(low=51, high=100, default=70, space='sell', optimize=True, load=True) short_rsi = IntParameter(low=51, high=100, default=70, space='sell', optimize=True, load=True)
exit_short_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True) exit_short_rsi = IntParameter(low=1, high=50, default=30, space='buy', optimize=True, load=True)
# FreqAI required function, leave as is or add additional informatives to existing structure.
def informative_pairs(self):
whitelist_pairs = self.dp.current_whitelist()
corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
informative_pairs = []
for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
for pair in whitelist_pairs:
informative_pairs.append((pair, tf))
for pair in corr_pairs:
if pair in whitelist_pairs:
continue # avoid duplication
informative_pairs.append((pair, tf))
return informative_pairs
# FreqAI required function, user can add or remove indicators, but general structure # FreqAI required function, user can add or remove indicators, but general structure
# must stay the same. # must stay the same.
def populate_any_indicators( def populate_any_indicators(

9
tests/exchange/test_binance.py
View File

@ -23,7 +23,7 @@ from tests.exchange.test_exchange import ccxt_exceptionhandlers
def test_stoploss_order_binance(default_conf, mocker, limitratio, expected, side, trademode): def test_stoploss_order_binance(default_conf, mocker, limitratio, expected, side, trademode):
api_mock = MagicMock() api_mock = MagicMock()
order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6)) order_id = 'test_prod_buy_{}'.format(randint(0, 10 ** 6))
order_type = 'stop_loss_limit' if trademode == TradingMode.SPOT else 'stop' order_type = 'stop_loss_limit' if trademode == TradingMode.SPOT else 'limit'
api_mock.create_order = MagicMock(return_value={ api_mock.create_order = MagicMock(return_value={
'id': order_id, 'id': order_id,
@ -45,12 +45,15 @@ def test_stoploss_order_binance(default_conf, mocker, limitratio, expected, side
amount=1, amount=1,
stop_price=190, stop_price=190,
side=side, side=side,
order_types={'stoploss_on_exchange_limit_ratio': 1.05}, order_types={'stoploss': 'limit', 'stoploss_on_exchange_limit_ratio': 1.05},
leverage=1.0 leverage=1.0
) )
api_mock.create_order.reset_mock() api_mock.create_order.reset_mock()
order_types = {} if limitratio is None else {'stoploss_on_exchange_limit_ratio': limitratio} order_types = {'stoploss': 'limit'}
if limitratio is not None:
order_types.update({'stoploss_on_exchange_limit_ratio': limitratio})
order = exchange.stoploss( order = exchange.stoploss(
pair='ETH/BTC', pair='ETH/BTC',
amount=1, amount=1,

2
tests/exchange/test_okx.py
View File

@ -472,7 +472,7 @@ def test_load_leverage_tiers_okx(default_conf, mocker, markets, tmpdir, caplog,
api_mock.fetch_market_leverage_tiers.call_count == 0 api_mock.fetch_market_leverage_tiers.call_count == 0
# 2 day passes ... # 2 day passes ...
time_machine.move_to(datetime.now() + timedelta(days=2)) time_machine.move_to(datetime.now() + timedelta(weeks=5))
exchange.load_leverage_tiers() exchange.load_leverage_tiers()
assert log_has(logmsg, caplog) assert log_has(logmsg, caplog)

25
tests/freqai/test_freqai_interface.py
View File

@ -8,6 +8,7 @@ import pytest
from freqtrade.configuration import TimeRange from freqtrade.configuration import TimeRange
from freqtrade.data.dataprovider import DataProvider from freqtrade.data.dataprovider import DataProvider
from freqtrade.freqai.data_kitchen import FreqaiDataKitchen from freqtrade.freqai.data_kitchen import FreqaiDataKitchen
from freqtrade.plugins.pairlistmanager import PairListManager
from tests.conftest import get_patched_exchange, log_has_re from tests.conftest import get_patched_exchange, log_has_re
from tests.freqai.conftest import get_patched_freqai_strategy from tests.freqai.conftest import get_patched_freqai_strategy
@ -350,3 +351,27 @@ def test_plot_feature_importance(mocker, freqai_conf):
assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}.html") assert Path(freqai.dk.data_path / f"{freqai.dk.model_filename}.html")
shutil.rmtree(Path(freqai.dk.full_path)) shutil.rmtree(Path(freqai.dk.full_path))
@pytest.mark.parametrize('timeframes,corr_pairs', [
(['5m'], ['ADA/BTC', 'DASH/BTC']),
(['5m'], ['ADA/BTC', 'DASH/BTC', 'ETH/USDT']),
(['5m', '15m'], ['ADA/BTC', 'DASH/BTC', 'ETH/USDT']),
])
def test_freqai_informative_pairs(mocker, freqai_conf, timeframes, corr_pairs):
freqai_conf['freqai']['feature_parameters'].update({
'include_timeframes': timeframes,
'include_corr_pairlist': corr_pairs,
})
strategy = get_patched_freqai_strategy(mocker, freqai_conf)
exchange = get_patched_exchange(mocker, freqai_conf)
pairlists = PairListManager(exchange, freqai_conf)
strategy.dp = DataProvider(freqai_conf, exchange, pairlists)
pairlist = strategy.dp.current_whitelist()
pairs_a = strategy.informative_pairs()
assert len(pairs_a) == 0
pairs_b = strategy.gather_informative_pairs()
# we expect unique pairs * timeframes
assert len(pairs_b) == len(set(pairlist + corr_pairs)) * len(timeframes)

13
tests/strategy/strats/freqai_test_multimodel_strat.py
View File

@ -43,19 +43,6 @@ class freqai_test_multimodel_strat(IStrategy):
) )
max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True) max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
def informative_pairs(self):
whitelist_pairs = self.dp.current_whitelist()
corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
informative_pairs = []
for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
for pair in whitelist_pairs:
informative_pairs.append((pair, tf))
for pair in corr_pairs:
if pair in whitelist_pairs:
continue # avoid duplication
informative_pairs.append((pair, tf))
return informative_pairs
def populate_any_indicators( def populate_any_indicators(
self, pair, df, tf, informative=None, set_generalized_indicators=False self, pair, df, tf, informative=None, set_generalized_indicators=False
): ):

13
tests/strategy/strats/freqai_test_strat.py
View File

@ -43,19 +43,6 @@ class freqai_test_strat(IStrategy):
) )
max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True) max_roi_time_long = IntParameter(0, 800, default=400, space="sell", optimize=False, load=True)
def informative_pairs(self):
whitelist_pairs = self.dp.current_whitelist()
corr_pairs = self.config["freqai"]["feature_parameters"]["include_corr_pairlist"]
informative_pairs = []
for tf in self.config["freqai"]["feature_parameters"]["include_timeframes"]:
for pair in whitelist_pairs:
informative_pairs.append((pair, tf))
for pair in corr_pairs:
if pair in whitelist_pairs:
continue # avoid duplication
informative_pairs.append((pair, tf))
return informative_pairs
def populate_any_indicators( def populate_any_indicators(
self, pair, df, tf, informative=None, set_generalized_indicators=False self, pair, df, tf, informative=None, set_generalized_indicators=False
): ):

11
tests/test_freqtradebot.py
View File

@ -1427,6 +1427,7 @@ def test_handle_stoploss_on_exchange_trailing(
trade.is_open = True trade.is_open = True
trade.open_order_id = None trade.open_order_id = None
trade.stoploss_order_id = 100 trade.stoploss_order_id = 100
trade.stoploss_last_update = arrow.utcnow().shift(minutes=-20).datetime
stoploss_order_hanging = MagicMock(return_value={ stoploss_order_hanging = MagicMock(return_value={
'id': 100, 'id': 100,
@ -1456,7 +1457,7 @@ def test_handle_stoploss_on_exchange_trailing(
) )
cancel_order_mock = MagicMock() cancel_order_mock = MagicMock()
stoploss_order_mock = MagicMock(return_value={'id': 13434334}) stoploss_order_mock = MagicMock(return_value={'id': 'so1'})
mocker.patch('freqtrade.exchange.Binance.cancel_stoploss_order', cancel_order_mock) mocker.patch('freqtrade.exchange.Binance.cancel_stoploss_order', cancel_order_mock)
mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss_order_mock) mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss_order_mock)
@ -1569,6 +1570,7 @@ def test_handle_stoploss_on_exchange_trailing_error(
assert stoploss.call_count == 1 assert stoploss.call_count == 1
# Fail creating stoploss order # Fail creating stoploss order
trade.stoploss_last_update = arrow.utcnow().shift(minutes=-601).datetime
caplog.clear() caplog.clear()
cancel_mock = mocker.patch("freqtrade.exchange.Binance.cancel_stoploss_order", MagicMock()) cancel_mock = mocker.patch("freqtrade.exchange.Binance.cancel_stoploss_order", MagicMock())
mocker.patch("freqtrade.exchange.Binance.stoploss", side_effect=ExchangeError()) mocker.patch("freqtrade.exchange.Binance.stoploss", side_effect=ExchangeError())
@ -1657,6 +1659,7 @@ def test_handle_stoploss_on_exchange_custom_stop(
trade.is_open = True trade.is_open = True
trade.open_order_id = None trade.open_order_id = None
trade.stoploss_order_id = 100 trade.stoploss_order_id = 100
trade.stoploss_last_update = arrow.utcnow().shift(minutes=-601).datetime
stoploss_order_hanging = MagicMock(return_value={ stoploss_order_hanging = MagicMock(return_value={
'id': 100, 'id': 100,
@ -1685,7 +1688,7 @@ def test_handle_stoploss_on_exchange_custom_stop(
) )
cancel_order_mock = MagicMock() cancel_order_mock = MagicMock()
stoploss_order_mock = MagicMock(return_value={'id': 13434334}) stoploss_order_mock = MagicMock(return_value={'id': 'so1'})
mocker.patch('freqtrade.exchange.Binance.cancel_stoploss_order', cancel_order_mock) mocker.patch('freqtrade.exchange.Binance.cancel_stoploss_order', cancel_order_mock)
mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss_order_mock) mocker.patch('freqtrade.exchange.Binance.stoploss', stoploss_order_mock)
@ -1727,8 +1730,7 @@ def test_handle_stoploss_on_exchange_custom_stop(
assert freqtrade.handle_trade(trade) is True assert freqtrade.handle_trade(trade) is True
def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog, def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, limit_order) -> None:
limit_order) -> None:
enter_order = limit_order['buy'] enter_order = limit_order['buy']
exit_order = limit_order['sell'] exit_order = limit_order['sell']
@ -1784,6 +1786,7 @@ def test_tsl_on_exchange_compatible_with_edge(mocker, edge_conf, fee, caplog,
trade.is_open = True trade.is_open = True
trade.open_order_id = None trade.open_order_id = None
trade.stoploss_order_id = 100 trade.stoploss_order_id = 100
trade.stoploss_last_update = arrow.utcnow()
stoploss_order_hanging = MagicMock(return_value={ stoploss_order_hanging = MagicMock(return_value={
'id': 100, 'id': 100,