merged with feat/short

2021-09-19 17:02:09 -06:00
parent ddc203ca69
commit 60a678fea7
52 changed files with 3356 additions and 663 deletions
--- a/freqtrade/commands/hyperopt_commands.py
+++ b/freqtrade/commands/hyperopt_commands.py
@@ -53,7 +53,7 @@ def start_hyperopt_list(args: Dict[str, Any]) -> None:

    if epochs and export_csv:
        HyperoptTools.export_csv_file(
-            config, epochs, total_epochs, not config.get('hyperopt_list_best', False), export_csv
+            config, epochs, export_csv
        )


--- a/freqtrade/configuration/PeriodicCache.py
+++ b/freqtrade/configuration/PeriodicCache.py
@@ -0,0 +1,19 @@
+from datetime import datetime, timezone
+
+from cachetools.ttl import TTLCache
+
+
+class PeriodicCache(TTLCache):
+    """
+    Special cache that expires at "straight" times
+    A timer with ttl of 3600 (1h) will expire at every full hour (:00).
+    """
+
+    def __init__(self, maxsize, ttl, getsizeof=None):
+        def local_timer():
+            ts = datetime.now(timezone.utc).timestamp()
+            offset = (ts % ttl)
+            return ts - offset
+
+        # Init with smlight offset
+        super().__init__(maxsize=maxsize, ttl=ttl-1e-5, timer=local_timer, getsizeof=getsizeof)
--- a/freqtrade/configuration/init.py
+++ b/freqtrade/configuration/init.py
@@ -4,4 +4,5 @@ from freqtrade.configuration.check_exchange import check_exchange
 from freqtrade.configuration.config_setup import setup_utils_configuration
 from freqtrade.configuration.config_validation import validate_config_consistency
 from freqtrade.configuration.configuration import Configuration
+from freqtrade.configuration.PeriodicCache import PeriodicCache
 from freqtrade.configuration.timerange import TimeRange
--- a/freqtrade/edge/edge_positioning.py
+++ b/freqtrade/edge/edge_positioning.py
@@ -119,7 +119,7 @@ class Edge:
            )
            # Download informative pairs too
            res = defaultdict(list)
-            for p, t in self.strategy.informative_pairs():
+            for p, t in self.strategy.gather_informative_pairs():
                res[t].append(p)
            for timeframe, inf_pairs in res.items():
                timerange_startup = deepcopy(self._timerange)
--- a/freqtrade/exchange/bibox.py
+++ b/freqtrade/exchange/bibox.py
@@ -20,4 +20,7 @@ class Bibox(Exchange):

    # fetchCurrencies API point requires authentication for Bibox,
    # so switch it off for Freqtrade load_markets()
-    _ccxt_config: Dict = {"has": {"fetchCurrencies": False}}
+    @property
+    def _ccxt_config(self) -> Dict:
+        # Parameters to add directly to ccxt sync/async initialization.
+        return {"has": {"fetchCurrencies": False}}
--- a/freqtrade/exchange/binance.py
+++ b/freqtrade/exchange/binance.py
@@ -1,10 +1,13 @@
 """ Binance exchange subclass """
+import json
 import logging
-from typing import Dict, List
+from pathlib import Path
+from typing import Dict, List, Optional, Tuple

 import arrow
 import ccxt

+from freqtrade.enums import Collateral, TradingMode
 from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
                                  OperationalException, TemporaryError)
 from freqtrade.exchange import Exchange
@@ -27,36 +30,74 @@ class Binance(Exchange):
    }
    funding_fee_times: List[int] = [0, 8, 16]  # hours of the day

-    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
+    _supported_trading_mode_collateral_pairs: List[Tuple[TradingMode, Collateral]] = [
+        # TradingMode.SPOT always supported and not required in this list
+        # (TradingMode.MARGIN, Collateral.CROSS),  # TODO-lev: Uncomment once supported
+        # (TradingMode.FUTURES, Collateral.CROSS),  # TODO-lev: Uncomment once supported
+        # (TradingMode.FUTURES, Collateral.ISOLATED) # TODO-lev: Uncomment once supported
+    ]
+
+    @property
+    def _ccxt_config(self) -> Dict:
+        # Parameters to add directly to ccxt sync/async initialization.
+        if self.trading_mode == TradingMode.MARGIN:
+            return {
+                "options": {
+                    "defaultType": "margin"
+                }
+            }
+        elif self.trading_mode == TradingMode.FUTURES:
+            return {
+                "options": {
+                    "defaultType": "future"
+                }
+            }
+        else:
+            return {}
+
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
        """
        Verify stop_loss against stoploss-order value (limit or price)
        Returns True if adjustment is necessary.
+        :param side: "buy" or "sell"
        """
-        return order['type'] == 'stop_loss_limit' and stop_loss > float(order['info']['stopPrice'])
+
+        return order['type'] == 'stop_loss_limit' and (
+            (side == "sell" and stop_loss > float(order['info']['stopPrice'])) or
+            (side == "buy" and stop_loss < float(order['info']['stopPrice']))
+        )

    @retrier(retries=0)
-    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+    def stoploss(self, pair: str, amount: float, stop_price: float,
+                 order_types: Dict, side: str, leverage: float) -> Dict:
        """
        creates a stoploss limit order.
        this stoploss-limit is binance-specific.
        It may work with a limited number of other exchanges, but this has not been tested yet.
+        :param side: "buy" or "sell"
        """
        # Limit price threshold: As limit price should always be below stop-price
        limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
-        rate = stop_price * limit_price_pct
+        if side == "sell":
+            # TODO: Name limit_rate in other exchange subclasses
+            rate = stop_price * limit_price_pct
+        else:
+            rate = stop_price * (2 - limit_price_pct)

        ordertype = "stop_loss_limit"

        stop_price = self.price_to_precision(pair, stop_price)

+        bad_stop_price = (stop_price <= rate) if side == "sell" else (stop_price >= rate)
+
        # Ensure rate is less than stop price
-        if stop_price <= rate:
+        if bad_stop_price:
            raise OperationalException(
-                'In stoploss limit order, stop price should be more than limit price')
+                'In stoploss limit order, stop price should be better than limit price')

        if self._config['dry_run']:
            dry_order = self.create_dry_run_order(
-                pair, ordertype, "sell", amount, stop_price)
+                pair, ordertype, side, amount, stop_price, leverage)
            return dry_order

        try:
@@ -67,7 +108,8 @@ class Binance(Exchange):

            rate = self.price_to_precision(pair, rate)

-            order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
+            self._lev_prep(pair, leverage)
+            order = self._api.create_order(symbol=pair, type=ordertype, side=side,
                                           amount=amount, price=rate, params=params)
            logger.info('stoploss limit order added for %s. '
                        'stop price: %s. limit: %s', pair, stop_price, rate)
@@ -75,21 +117,96 @@ class Binance(Exchange):
            return order
        except ccxt.InsufficientFunds as e:
            raise InsufficientFundsError(
-                f'Insufficient funds to create {ordertype} sell order on market {pair}. '
-                f'Tried to sell amount {amount} at rate {rate}. '
+                f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
+                f'Tried to {side} amount {amount} at rate {rate}. '
                f'Message: {e}') from e
        except ccxt.InvalidOrder as e:
            # Errors:
            # `binance Order would trigger immediately.`
            raise InvalidOrderException(
-                f'Could not create {ordertype} sell order on market {pair}. '
-                f'Tried to sell amount {amount} at rate {rate}. '
+                f'Could not create {ordertype} {side} order on market {pair}. '
+                f'Tried to {side} amount {amount} at rate {rate}. '
                f'Message: {e}') from e
        except ccxt.DDoSProtection as e:
            raise DDosProtection(e) from e
        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
            raise TemporaryError(
-                f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
+                f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    @retrier
+    def fill_leverage_brackets(self):
+        """
+            Assigns property _leverage_brackets to a dictionary of information about the leverage
+            allowed on each pair
+        """
+        if self.trading_mode == TradingMode.FUTURES:
+            try:
+                if self._config['dry_run']:
+                    leverage_brackets_path = (
+                        Path(__file__).parent / 'binance_leverage_brackets.json'
+                    )
+                    with open(leverage_brackets_path) as json_file:
+                        leverage_brackets = json.load(json_file)
+                else:
+                    leverage_brackets = self._api.load_leverage_brackets()
+
+                for pair, brackets in leverage_brackets.items():
+                    self._leverage_brackets[pair] = [
+                        [
+                            min_amount,
+                            float(margin_req)
+                        ] for [
+                            min_amount,
+                            margin_req
+                        ] in brackets
+                    ]
+
+            except ccxt.DDoSProtection as e:
+                raise DDosProtection(e) from e
+            except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+                raise TemporaryError(f'Could not fetch leverage amounts due to'
+                                     f'{e.__class__.__name__}. Message: {e}') from e
+            except ccxt.BaseError as e:
+                raise OperationalException(e) from e
+
+    def get_max_leverage(self, pair: Optional[str], nominal_value: Optional[float]) -> float:
+        """
+            Returns the maximum leverage that a pair can be traded at
+            :param pair: The base/quote currency pair being traded
+            :nominal_value: The total value of the trade in quote currency (collateral + debt)
+        """
+        pair_brackets = self._leverage_brackets[pair]
+        max_lev = 1.0
+        for [min_amount, margin_req] in pair_brackets:
+            if nominal_value >= min_amount:
+                max_lev = 1/margin_req
+        return max_lev
+
+    @ retrier
+    def _set_leverage(
+        self,
+        leverage: float,
+        pair: Optional[str] = None,
+        trading_mode: Optional[TradingMode] = None
+    ):
+        """
+            Set's the leverage before making a trade, in order to not
+            have the same leverage on every trade
+        """
+        trading_mode = trading_mode or self.trading_mode
+
+        if self._config['dry_run'] or trading_mode != TradingMode.FUTURES:
+            return
+
+        try:
+            self._api.set_leverage(symbol=pair, leverage=leverage)
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
        except ccxt.BaseError as e:
            raise OperationalException(e) from e

--- a/freqtrade/exchange/binance_leverage_brackets.json
+++ b/freqtrade/exchange/binance_leverage_brackets.json
--- a/freqtrade/exchange/exchange.py
+++ b/freqtrade/exchange/exchange.py
@@ -7,7 +7,7 @@ import http
 import inspect
 import logging
 from copy import deepcopy
-from datetime import datetime, timedelta, timezone
+from datetime import datetime, timezone
 from math import ceil
 from typing import Any, Dict, List, Optional, Tuple, Union

@@ -22,6 +22,7 @@ from pandas import DataFrame
 from freqtrade.constants import (DEFAULT_AMOUNT_RESERVE_PERCENT, NON_OPEN_EXCHANGE_STATES,
                                 ListPairsWithTimeframes)
 from freqtrade.data.converter import ohlcv_to_dataframe, trades_dict_to_list
+from freqtrade.enums import Collateral, TradingMode
 from freqtrade.exceptions import (DDosProtection, ExchangeError, InsufficientFundsError,
                                  InvalidOrderException, OperationalException, PricingError,
                                  RetryableOrderError, TemporaryError)
@@ -48,9 +49,6 @@ class Exchange:

    _config: Dict = {}

-    # Parameters to add directly to ccxt sync/async initialization.
-    _ccxt_config: Dict = {}
-
    # Parameters to add directly to buy/sell calls (like agreeing to trading agreement)
    _params: Dict = {}

@@ -75,6 +73,10 @@ class Exchange:
    _ft_has: Dict = {}
    funding_fee_times: List[int] = []  # hours of the day

+    _supported_trading_mode_collateral_pairs: List[Tuple[TradingMode, Collateral]] = [
+        # TradingMode.SPOT always supported and not required in this list
+    ]
+
    def __init__(self, config: Dict[str, Any], validate: bool = True) -> None:
        """
        Initializes this module with the given config,
@@ -84,6 +86,7 @@ class Exchange:
        self._api: ccxt.Exchange = None
        self._api_async: ccxt_async.Exchange = None
        self._markets: Dict = {}
+        self._leverage_brackets: Dict = {}

        self._config.update(config)

@@ -126,14 +129,25 @@ class Exchange:
        self._trades_pagination = self._ft_has['trades_pagination']
        self._trades_pagination_arg = self._ft_has['trades_pagination_arg']

+        self.trading_mode: TradingMode = (
+            TradingMode(config.get('trading_mode'))
+            if config.get('trading_mode')
+            else TradingMode.SPOT
+        )
+        self.collateral: Optional[Collateral] = (
+            Collateral(config.get('collateral'))
+            if config.get('collateral')
+            else None
+        )
+
        # Initialize ccxt objects
-        ccxt_config = self._ccxt_config.copy()
+        ccxt_config = self._ccxt_config
        ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}), ccxt_config)
        ccxt_config = deep_merge_dicts(exchange_config.get('ccxt_sync_config', {}), ccxt_config)

        self._api = self._init_ccxt(exchange_config, ccxt_kwargs=ccxt_config)

-        ccxt_async_config = self._ccxt_config.copy()
+        ccxt_async_config = self._ccxt_config
        ccxt_async_config = deep_merge_dicts(exchange_config.get('ccxt_config', {}),
                                             ccxt_async_config)
        ccxt_async_config = deep_merge_dicts(exchange_config.get('ccxt_async_config', {}),
@@ -141,6 +155,9 @@ class Exchange:
        self._api_async = self._init_ccxt(
            exchange_config, ccxt_async, ccxt_kwargs=ccxt_async_config)

+        if self.trading_mode != TradingMode.SPOT:
+            self.fill_leverage_brackets()
+
        logger.info('Using Exchange "%s"', self.name)

        if validate:
@@ -158,7 +175,7 @@ class Exchange:
            self.validate_order_time_in_force(config.get('order_time_in_force', {}))
            self.validate_required_startup_candles(config.get('startup_candle_count', 0),
                                                   config.get('timeframe', ''))
-
+            self.validate_trading_mode_and_collateral(self.trading_mode, self.collateral)
        # Converts the interval provided in minutes in config to seconds
        self.markets_refresh_interval: int = exchange_config.get(
            "markets_refresh_interval", 60) * 60
@@ -211,6 +228,11 @@ class Exchange:

        return api

+    @property
+    def _ccxt_config(self) -> Dict:
+        # Parameters to add directly to ccxt sync/async initialization.
+        return {}
+
    @property
    def name(self) -> str:
        """exchange Name (from ccxt)"""
@@ -356,6 +378,7 @@ class Exchange:
            # Also reload async markets to avoid issues with newly listed pairs
            self._load_async_markets(reload=True)
            self._last_markets_refresh = arrow.utcnow().int_timestamp
+            self.fill_leverage_brackets()
        except ccxt.BaseError:
            logger.exception("Could not reload markets.")

@@ -483,6 +506,25 @@ class Exchange:
                f"This strategy requires {startup_candles} candles to start. "
                f"{self.name} only provides {candle_limit} for {timeframe}.")

+    def validate_trading_mode_and_collateral(
+        self,
+        trading_mode: TradingMode,
+        collateral: Optional[Collateral]  # Only None when trading_mode = TradingMode.SPOT
+    ):
+        """
+            Checks if freqtrade can perform trades using the configured
+            trading mode(Margin, Futures) and Collateral(Cross, Isolated)
+            Throws OperationalException:
+                If the trading_mode/collateral type are not supported by freqtrade on this exchange
+        """
+        if trading_mode != TradingMode.SPOT and (
+            (trading_mode, collateral) not in self._supported_trading_mode_collateral_pairs
+        ):
+            collateral_value = collateral and collateral.value
+            raise OperationalException(
+                f"Freqtrade does not support {collateral_value} {trading_mode.value} on {self.name}"
+            )
+
    def exchange_has(self, endpoint: str) -> bool:
        """
        Checks if exchange implements a specific API endpoint.
@@ -542,8 +584,8 @@ class Exchange:
        else:
            return 1 / pow(10, precision)

-    def get_min_pair_stake_amount(self, pair: str, price: float,
-                                  stoploss: float) -> Optional[float]:
+    def get_min_pair_stake_amount(self, pair: str, price: float, stoploss: float,
+                                  leverage: Optional[float] = 1.0) -> Optional[float]:
        try:
            market = self.markets[pair]
        except KeyError:
@@ -577,12 +619,24 @@ class Exchange:
        # The value returned should satisfy both limits: for amount (base currency) and
        # for cost (quote, stake currency), so max() is used here.
        # See also #2575 at github.
-        return max(min_stake_amounts) * amount_reserve_percent
+        return self._get_stake_amount_considering_leverage(
+            max(min_stake_amounts) * amount_reserve_percent,
+            leverage or 1.0
+        )
+
+    def _get_stake_amount_considering_leverage(self, stake_amount: float, leverage: float):
+        """
+        Takes the minimum stake amount for a pair with no leverage and returns the minimum
+        stake amount when leverage is considered
+        :param stake_amount: The stake amount for a pair before leverage is considered
+        :param leverage: The amount of leverage being used on the current trade
+        """
+        return stake_amount / leverage

    # Dry-run methods

    def create_dry_run_order(self, pair: str, ordertype: str, side: str, amount: float,
-                             rate: float, params: Dict = {}) -> Dict[str, Any]:
+                             rate: float, leverage: float, params: Dict = {}) -> Dict[str, Any]:
        order_id = f'dry_run_{side}_{datetime.now().timestamp()}'
        _amount = self.amount_to_precision(pair, amount)
        dry_order: Dict[str, Any] = {
@@ -599,7 +653,8 @@ class Exchange:
            'timestamp': arrow.utcnow().int_timestamp * 1000,
            'status': "closed" if ordertype == "market" else "open",
            'fee': None,
-            'info': {}
+            'info': {},
+            'leverage': leverage
        }
        if dry_order["type"] in ["stop_loss_limit", "stop-loss-limit"]:
            dry_order["info"] = {"stopPrice": dry_order["price"]}
@@ -609,7 +664,7 @@ class Exchange:
            average = self.get_dry_market_fill_price(pair, side, amount, rate)
            dry_order.update({
                'average': average,
-                'cost': dry_order['amount'] * average,
+                'cost': (dry_order['amount'] * average) / leverage
            })
            dry_order = self.add_dry_order_fee(pair, dry_order)

@@ -717,17 +772,26 @@ class Exchange:

    # Order handling

-    def create_order(self, pair: str, ordertype: str, side: str, amount: float,
-                     rate: float, time_in_force: str = 'gtc') -> Dict:
-
-        if self._config['dry_run']:
-            dry_order = self.create_dry_run_order(pair, ordertype, side, amount, rate)
-            return dry_order
+    def _lev_prep(self, pair: str, leverage: float):
+        if self.trading_mode != TradingMode.SPOT:
+            self.set_margin_mode(pair, self.collateral)
+            self._set_leverage(leverage, pair)

+    def _get_params(self, ordertype: str, leverage: float, time_in_force: str = 'gtc') -> Dict:
        params = self._params.copy()
        if time_in_force != 'gtc' and ordertype != 'market':
            param = self._ft_has.get('time_in_force_parameter', '')
            params.update({param: time_in_force})
+        return params
+
+    def create_order(self, pair: str, ordertype: str, side: str, amount: float,
+                     rate: float, leverage: float = 1.0, time_in_force: str = 'gtc') -> Dict:
+        # TODO-lev: remove default for leverage
+        if self._config['dry_run']:
+            dry_order = self.create_dry_run_order(pair, ordertype, side, amount, rate, leverage)
+            return dry_order
+
+        params = self._get_params(ordertype, leverage, time_in_force)

        try:
            # Set the precision for amount and price(rate) as accepted by the exchange
@@ -736,6 +800,7 @@ class Exchange:
                           or self._api.options.get("createMarketBuyOrderRequiresPrice", False))
            rate_for_order = self.price_to_precision(pair, rate) if needs_price else None

+            self._lev_prep(pair, leverage)
            order = self._api.create_order(pair, ordertype, side,
                                           amount, rate_for_order, params)
            self._log_exchange_response('create_order', order)
@@ -759,14 +824,15 @@ class Exchange:
        except ccxt.BaseError as e:
            raise OperationalException(e) from e

-    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
        """
        Verify stop_loss against stoploss-order value (limit or price)
        Returns True if adjustment is necessary.
        """
        raise OperationalException(f"stoploss is not implemented for {self.name}.")

-    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+    def stoploss(self, pair: str, amount: float, stop_price: float,
+                 order_types: Dict, side: str, leverage: float) -> Dict:
        """
        creates a stoploss order.
        The precise ordertype is determined by the order_types dict or exchange default.
@@ -1559,21 +1625,66 @@ class Exchange:
        except ccxt.BaseError as e:
            raise OperationalException(e) from e

-    def _get_funding_fee_dates(self, open_date: datetime, close_date: datetime):
+    def fill_leverage_brackets(self):
        """
-            Get's the date and time of every funding fee that happened between two datetimes
+            # TODO-lev: Should maybe be renamed, leverage_brackets might not be accurate for kraken
+            Assigns property _leverage_brackets to a dictionary of information about the leverage
+            allowed on each pair
        """
-        open_date = datetime(open_date.year, open_date.month, open_date.day, open_date.hour)
-        close_date = datetime(close_date.year, close_date.month, close_date.day, close_date.hour)
+        return

-        results = []
-        date_iterator = open_date
-        while date_iterator < close_date:
-            date_iterator += timedelta(hours=1)
-            if date_iterator.hour in self.funding_fee_times:
-                results.append(date_iterator)
+    def get_max_leverage(self, pair: Optional[str], nominal_value: Optional[float]) -> float:
+        """
+            Returns the maximum leverage that a pair can be traded at
+            :param pair: The base/quote currency pair being traded
+            :nominal_value: The total value of the trade in quote currency (collateral + debt)
+        """
+        return 1.0

-        return results
+    @retrier
+    def _set_leverage(
+        self,
+        leverage: float,
+        pair: Optional[str] = None,
+        trading_mode: Optional[TradingMode] = None
+    ):
+        """
+            Set's the leverage before making a trade, in order to not
+            have the same leverage on every trade
+        """
+        if self._config['dry_run'] or not self.exchange_has("setLeverage"):
+            # Some exchanges only support one collateral type
+            return
+
+        try:
+            self._api.set_leverage(symbol=pair, leverage=leverage)
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not set leverage due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e
+
+    @retrier
+    def set_margin_mode(self, pair: str, collateral: Collateral, params: dict = {}):
+        '''
+            Set's the margin mode on the exchange to cross or isolated for a specific pair
+            :param symbol: base/quote currency pair (e.g. "ADA/USDT")
+        '''
+        if self._config['dry_run'] or not self.exchange_has("setMarginMode"):
+            # Some exchanges only support one collateral type
+            return
+
+        try:
+            self._api.set_margin_mode(pair, collateral.value, params)
+        except ccxt.DDoSProtection as e:
+            raise DDosProtection(e) from e
+        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
+            raise TemporaryError(
+                f'Could not set margin mode due to {e.__class__.__name__}. Message: {e}') from e
+        except ccxt.BaseError as e:
+            raise OperationalException(e) from e


 def is_exchange_known_ccxt(exchange_name: str, ccxt_module: CcxtModuleType = None) -> bool:
--- a/freqtrade/exchange/ftx.py
+++ b/freqtrade/exchange/ftx.py
@@ -1,9 +1,10 @@
 """ FTX exchange subclass """
 import logging
-from typing import Any, Dict, List
+from typing import Any, Dict, List, Optional, Tuple

 import ccxt

+from freqtrade.enums import Collateral, TradingMode
 from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
                                  OperationalException, TemporaryError)
 from freqtrade.exchange import Exchange
@@ -22,6 +23,12 @@ class Ftx(Exchange):
    }
    funding_fee_times: List[int] = list(range(0, 23))

+    _supported_trading_mode_collateral_pairs: List[Tuple[TradingMode, Collateral]] = [
+        # TradingMode.SPOT always supported and not required in this list
+        # (TradingMode.MARGIN, Collateral.CROSS),  # TODO-lev: Uncomment once supported
+        # (TradingMode.FUTURES, Collateral.CROSS)  # TODO-lev: Uncomment once supported
+    ]
+
    def market_is_tradable(self, market: Dict[str, Any]) -> bool:
        """
        Check if the market symbol is tradable by Freqtrade.
@@ -32,15 +39,19 @@ class Ftx(Exchange):
        return (parent_check and
                market.get('spot', False) is True)

-    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
        """
        Verify stop_loss against stoploss-order value (limit or price)
        Returns True if adjustment is necessary.
        """
-        return order['type'] == 'stop' and stop_loss > float(order['price'])
+        return order['type'] == 'stop' and (
+            side == "sell" and stop_loss > float(order['price']) or
+            side == "buy" and stop_loss < float(order['price'])
+        )

    @retrier(retries=0)
-    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+    def stoploss(self, pair: str, amount: float, stop_price: float,
+                 order_types: Dict, side: str, leverage: float) -> Dict:
        """
        Creates a stoploss order.
        depending on order_types.stoploss configuration, uses 'market' or limit order.
@@ -48,7 +59,10 @@ class Ftx(Exchange):
        Limit orders are defined by having orderPrice set, otherwise a market order is used.
        """
        limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
-        limit_rate = stop_price * limit_price_pct
+        if side == "sell":
+            limit_rate = stop_price * limit_price_pct
+        else:
+            limit_rate = stop_price * (2 - limit_price_pct)

        ordertype = "stop"

@@ -56,7 +70,7 @@ class Ftx(Exchange):

        if self._config['dry_run']:
            dry_order = self.create_dry_run_order(
-                pair, ordertype, "sell", amount, stop_price)
+                pair, ordertype, side, amount, stop_price, leverage)
            return dry_order

        try:
@@ -68,7 +82,8 @@ class Ftx(Exchange):
            params['stopPrice'] = stop_price
            amount = self.amount_to_precision(pair, amount)

-            order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
+            self._lev_prep(pair, leverage)
+            order = self._api.create_order(symbol=pair, type=ordertype, side=side,
                                           amount=amount, params=params)
            self._log_exchange_response('create_stoploss_order', order)
            logger.info('stoploss order added for %s. '
@@ -76,19 +91,19 @@ class Ftx(Exchange):
            return order
        except ccxt.InsufficientFunds as e:
            raise InsufficientFundsError(
-                f'Insufficient funds to create {ordertype} sell order on market {pair}. '
+                f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
                f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
                f'Message: {e}') from e
        except ccxt.InvalidOrder as e:
            raise InvalidOrderException(
-                f'Could not create {ordertype} sell order on market {pair}. '
+                f'Could not create {ordertype} {side} order on market {pair}. '
                f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
                f'Message: {e}') from e
        except ccxt.DDoSProtection as e:
            raise DDosProtection(e) from e
        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
            raise TemporaryError(
-                f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
+                f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
        except ccxt.BaseError as e:
            raise OperationalException(e) from e

@@ -153,3 +168,18 @@ class Ftx(Exchange):
        if order['type'] == 'stop':
            return safe_value_fallback2(order, order, 'id_stop', 'id')
        return order['id']
+
+    def fill_leverage_brackets(self):
+        """
+            FTX leverage is static across the account, and doesn't change from pair to pair,
+            so _leverage_brackets doesn't need to be set
+        """
+        return
+
+    def get_max_leverage(self, pair: Optional[str], nominal_value: Optional[float]) -> float:
+        """
+            Returns the maximum leverage that a pair can be traded at, which is always 20 on ftx
+            :param pair: Here for super method, not used on FTX
+            :nominal_value: Here for super method, not used on FTX
+        """
+        return 20.0
--- a/freqtrade/exchange/kraken.py
+++ b/freqtrade/exchange/kraken.py
@@ -1,9 +1,10 @@
 """ Kraken exchange subclass """
 import logging
-from typing import Any, Dict, List
+from typing import Any, Dict, List, Optional, Tuple

 import ccxt

+from freqtrade.enums import Collateral, TradingMode
 from freqtrade.exceptions import (DDosProtection, InsufficientFundsError, InvalidOrderException,
                                  OperationalException, TemporaryError)
 from freqtrade.exchange import Exchange
@@ -24,6 +25,12 @@ class Kraken(Exchange):
    }
    funding_fee_times: List[int] = [0, 4, 8, 12, 16, 20]  # hours of the day

+    _supported_trading_mode_collateral_pairs: List[Tuple[TradingMode, Collateral]] = [
+        # TradingMode.SPOT always supported and not required in this list
+        # (TradingMode.MARGIN, Collateral.CROSS),  # TODO-lev: Uncomment once supported
+        # (TradingMode.FUTURES, Collateral.CROSS)  # TODO-lev: No CCXT support
+    ]
+
    def market_is_tradable(self, market: Dict[str, Any]) -> bool:
        """
        Check if the market symbol is tradable by Freqtrade.
@@ -68,16 +75,19 @@ class Kraken(Exchange):
        except ccxt.BaseError as e:
            raise OperationalException(e) from e

-    def stoploss_adjust(self, stop_loss: float, order: Dict) -> bool:
+    def stoploss_adjust(self, stop_loss: float, order: Dict, side: str) -> bool:
        """
        Verify stop_loss against stoploss-order value (limit or price)
        Returns True if adjustment is necessary.
        """
-        return (order['type'] in ('stop-loss', 'stop-loss-limit')
-                and stop_loss > float(order['price']))
+        return (order['type'] in ('stop-loss', 'stop-loss-limit') and (
+                (side == "sell" and stop_loss > float(order['price'])) or
+                (side == "buy" and stop_loss < float(order['price']))
+                ))

    @retrier(retries=0)
-    def stoploss(self, pair: str, amount: float, stop_price: float, order_types: Dict) -> Dict:
+    def stoploss(self, pair: str, amount: float, stop_price: float,
+                 order_types: Dict, side: str, leverage: float) -> Dict:
        """
        Creates a stoploss market order.
        Stoploss market orders is the only stoploss type supported by kraken.
@@ -87,7 +97,10 @@ class Kraken(Exchange):
        if order_types.get('stoploss', 'market') == 'limit':
            ordertype = "stop-loss-limit"
            limit_price_pct = order_types.get('stoploss_on_exchange_limit_ratio', 0.99)
-            limit_rate = stop_price * limit_price_pct
+            if side == "sell":
+                limit_rate = stop_price * limit_price_pct
+            else:
+                limit_rate = stop_price * (2 - limit_price_pct)
            params['price2'] = self.price_to_precision(pair, limit_rate)
        else:
            ordertype = "stop-loss"
@@ -96,13 +109,13 @@ class Kraken(Exchange):

        if self._config['dry_run']:
            dry_order = self.create_dry_run_order(
-                pair, ordertype, "sell", amount, stop_price)
+                pair, ordertype, side, amount, stop_price, leverage)
            return dry_order

        try:
            amount = self.amount_to_precision(pair, amount)

-            order = self._api.create_order(symbol=pair, type=ordertype, side='sell',
+            order = self._api.create_order(symbol=pair, type=ordertype, side=side,
                                           amount=amount, price=stop_price, params=params)
            self._log_exchange_response('create_stoploss_order', order)
            logger.info('stoploss order added for %s. '
@@ -110,18 +123,70 @@ class Kraken(Exchange):
            return order
        except ccxt.InsufficientFunds as e:
            raise InsufficientFundsError(
-                f'Insufficient funds to create {ordertype} sell order on market {pair}. '
+                f'Insufficient funds to create {ordertype} {side} order on market {pair}. '
                f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
                f'Message: {e}') from e
        except ccxt.InvalidOrder as e:
            raise InvalidOrderException(
-                f'Could not create {ordertype} sell order on market {pair}. '
+                f'Could not create {ordertype} {side} order on market {pair}. '
                f'Tried to create stoploss with amount {amount} at stoploss {stop_price}. '
                f'Message: {e}') from e
        except ccxt.DDoSProtection as e:
            raise DDosProtection(e) from e
        except (ccxt.NetworkError, ccxt.ExchangeError) as e:
            raise TemporaryError(
-                f'Could not place sell order due to {e.__class__.__name__}. Message: {e}') from e
+                f'Could not place {side} order due to {e.__class__.__name__}. Message: {e}') from e
        except ccxt.BaseError as e:
            raise OperationalException(e) from e
+
+    def fill_leverage_brackets(self):
+        """
+            Assigns property _leverage_brackets to a dictionary of information about the leverage
+            allowed on each pair
+        """
+        leverages = {}
+
+        for pair, market in self.markets.items():
+            leverages[pair] = [1]
+            info = market['info']
+            leverage_buy = info.get('leverage_buy', [])
+            leverage_sell = info.get('leverage_sell', [])
+            if len(leverage_buy) > 0 or len(leverage_sell) > 0:
+                if leverage_buy != leverage_sell:
+                    logger.warning(
+                        f"The buy({leverage_buy}) and sell({leverage_sell}) leverage are not equal"
+                        "for {pair}. Please notify freqtrade because this has never happened before"
+                    )
+                    if max(leverage_buy) <= max(leverage_sell):
+                        leverages[pair] += [int(lev) for lev in leverage_buy]
+                    else:
+                        leverages[pair] += [int(lev) for lev in leverage_sell]
+                else:
+                    leverages[pair] += [int(lev) for lev in leverage_buy]
+        self._leverage_brackets = leverages
+
+    def get_max_leverage(self, pair: Optional[str], nominal_value: Optional[float]) -> float:
+        """
+            Returns the maximum leverage that a pair can be traded at
+            :param pair: The base/quote currency pair being traded
+            :nominal_value: Here for super class, not needed on Kraken
+        """
+        return float(max(self._leverage_brackets[pair]))
+
+    def _set_leverage(
+        self,
+        leverage: float,
+        pair: Optional[str] = None,
+        trading_mode: Optional[TradingMode] = None
+    ):
+        """
+            Kraken set's the leverage as an option in the order object, so we need to
+            add it to params
+        """
+        return
+
+    def _get_params(self, ordertype: str, leverage: float, time_in_force: str = 'gtc') -> Dict:
+        params = super()._get_params(ordertype, leverage, time_in_force)
+        if leverage > 1.0:
+            params['leverage'] = leverage
+        return params
--- a/freqtrade/freqtradebot.py
+++ b/freqtrade/freqtradebot.py
@@ -86,10 +86,10 @@ class FreqtradeBot(LoggingMixin):

        self.dataprovider = DataProvider(self.config, self.exchange, self.pairlists)

-        # Attach Dataprovider to Strategy baseclass
-        IStrategy.dp = self.dataprovider
-        # Attach Wallets to Strategy baseclass
-        IStrategy.wallets = self.wallets
+        # Attach Dataprovider to strategy instance
+        self.strategy.dp = self.dataprovider
+        # Attach Wallets to strategy instance
+        self.strategy.wallets = self.wallets

        # Initializing Edge only if enabled
        self.edge = Edge(self.config, self.exchange, self.strategy) if \
@@ -173,7 +173,7 @@ class FreqtradeBot(LoggingMixin):

        # Refreshing candles
        self.dataprovider.refresh(self.pairlists.create_pair_list(self.active_pair_whitelist),
-                                  self.strategy.informative_pairs())
+                                  self.strategy.gather_informative_pairs())

        strategy_safe_wrapper(self.strategy.bot_loop_start, supress_error=True)()

@@ -763,9 +763,14 @@ class FreqtradeBot(LoggingMixin):
        :return: True if the order succeeded, and False in case of problems.
        """
        try:
-            stoploss_order = self.exchange.stoploss(pair=trade.pair, amount=trade.amount,
-                                                    stop_price=stop_price,
-                                                    order_types=self.strategy.order_types)
+            stoploss_order = self.exchange.stoploss(
+                pair=trade.pair,
+                amount=trade.amount,
+                stop_price=stop_price,
+                order_types=self.strategy.order_types,
+                side=trade.exit_side,
+                leverage=trade.leverage
+            )

            order_obj = Order.parse_from_ccxt_object(stoploss_order, trade.pair, 'stoploss')
            trade.orders.append(order_obj)
@@ -857,11 +862,11 @@ class FreqtradeBot(LoggingMixin):
            # if trailing stoploss is enabled we check if stoploss value has changed
            # in which case we cancel stoploss order and put another one with new
            # value immediately
-            self.handle_trailing_stoploss_on_exchange(trade, stoploss_order)
+            self.handle_trailing_stoploss_on_exchange(trade, stoploss_order, side=trade.exit_side)

        return False

-    def handle_trailing_stoploss_on_exchange(self, trade: Trade, order: dict) -> None:
+    def handle_trailing_stoploss_on_exchange(self, trade: Trade, order: dict, side: str) -> None:
        """
        Check to see if stoploss on exchange should be updated
        in case of trailing stoploss on exchange
@@ -869,7 +874,7 @@ class FreqtradeBot(LoggingMixin):
        :param order: Current on exchange stoploss order
        :return: None
        """
-        if self.exchange.stoploss_adjust(trade.stop_loss, order):
+        if self.exchange.stoploss_adjust(trade.stop_loss, order, side):
            # we check if the update is necessary
            update_beat = self.strategy.order_types.get('stoploss_on_exchange_interval', 60)
            if (datetime.utcnow() - trade.stoploss_last_update).total_seconds() >= update_beat:
--- a/freqtrade/leverage/interest.py
+++ b/freqtrade/leverage/interest.py
@@ -20,7 +20,7 @@ def interest(

        :param exchange_name: The exchanged being trading on
        :param borrowed: The amount of currency being borrowed
-        :param rate: The rate of interest
+        :param rate: The rate of interest (i.e daily interest rate)
        :param hours: The time in hours that the currency has been borrowed for

        Raises:
@@ -36,7 +36,8 @@ def interest(
        # Rounded based on https://kraken-fees-calculator.github.io/
        return borrowed * rate * (one+ceil(hours/four))
    elif exchange_name == "ftx":
-        # TODO-lev: Add FTX interest formula
-        raise OperationalException(f"Leverage not available on {exchange_name} with freqtrade")
+        # As Explained under #Interest rates section in
+        # https://help.ftx.com/hc/en-us/articles/360053007671-Spot-Margin-Trading-Explainer
+        return borrowed * rate * ceil(hours)/twenty_four
    else:
        raise OperationalException(f"Leverage not available on {exchange_name} with freqtrade")
--- a/freqtrade/optimize/backtesting.py
+++ b/freqtrade/optimize/backtesting.py
@@ -154,7 +154,7 @@ class Backtesting:
        self.strategy: IStrategy = strategy
        strategy.dp = self.dataprovider
        # Attach Wallets to Strategy baseclass
-        IStrategy.wallets = self.wallets
+        strategy.wallets = self.wallets
        # Set stoploss_on_exchange to false for backtesting,
        # since a "perfect" stoploss-sell is assumed anyway
        # And the regular "stoploss" function would not apply to that case
--- a/freqtrade/optimize/edge_cli.py
+++ b/freqtrade/optimize/edge_cli.py
@@ -8,6 +8,7 @@ from typing import Any, Dict

 from freqtrade import constants
 from freqtrade.configuration import TimeRange, validate_config_consistency
+from freqtrade.data.dataprovider import DataProvider
 from freqtrade.edge import Edge
 from freqtrade.optimize.optimize_reports import generate_edge_table
 from freqtrade.resolvers import ExchangeResolver, StrategyResolver
@@ -33,6 +34,7 @@ class EdgeCli:
        self.config['stake_amount'] = constants.UNLIMITED_STAKE_AMOUNT
        self.exchange = ExchangeResolver.load_exchange(self.config['exchange']['name'], self.config)
        self.strategy = StrategyResolver.load_strategy(self.config)
+        self.strategy.dp = DataProvider(config, None)

        validate_config_consistency(self.config)

--- a/freqtrade/optimize/hyperopt.py
+++ b/freqtrade/optimize/hyperopt.py
@@ -45,7 +45,7 @@ progressbar.streams.wrap_stdout()
 logger = logging.getLogger(__name__)


-INITIAL_POINTS = 30
+INITIAL_POINTS = 5

 # Keep no more than SKOPT_MODEL_QUEUE_SIZE models
 # in the skopt model queue, to optimize memory consumption
@@ -241,7 +241,7 @@ class Hyperopt:

        if HyperoptTools.has_space(self.config, 'buy'):
            logger.debug("Hyperopt has 'buy' space")
-            self.buy_space = self.custom_hyperopt.indicator_space()
+            self.buy_space = self.custom_hyperopt.buy_indicator_space()

        if HyperoptTools.has_space(self.config, 'sell'):
            logger.debug("Hyperopt has 'sell' space")
@@ -365,10 +365,20 @@ class Hyperopt:
        }

    def get_optimizer(self, dimensions: List[Dimension], cpu_count) -> Optimizer:
+        estimator = self.custom_hyperopt.generate_estimator()
+
+        acq_optimizer = "sampling"
+        if isinstance(estimator, str):
+            if estimator not in ("GP", "RF", "ET", "GBRT"):
+                raise OperationalException(f"Estimator {estimator} not supported.")
+            else:
+                acq_optimizer = "auto"
+
+        logger.info(f"Using estimator {estimator}.")
        return Optimizer(
            dimensions,
-            base_estimator="ET",
-            acq_optimizer="auto",
+            base_estimator=estimator,
+            acq_optimizer=acq_optimizer,
            n_initial_points=INITIAL_POINTS,
            acq_optimizer_kwargs={'n_jobs': cpu_count},
            random_state=self.random_state,
--- a/freqtrade/optimize/hyperopt_auto.py
+++ b/freqtrade/optimize/hyperopt_auto.py
@@ -12,7 +12,7 @@ from freqtrade.exceptions import OperationalException
 with suppress(ImportError):
    from skopt.space import Dimension

-from freqtrade.optimize.hyperopt_interface import IHyperOpt
+from freqtrade.optimize.hyperopt_interface import EstimatorType, IHyperOpt


 def _format_exception_message(space: str) -> str:
@@ -56,7 +56,7 @@ class HyperOptAuto(IHyperOpt):
        else:
            _format_exception_message(category)

-    def indicator_space(self) -> List['Dimension']:
+    def buy_indicator_space(self) -> List['Dimension']:
        return self._get_indicator_space('buy')

    def sell_indicator_space(self) -> List['Dimension']:
@@ -79,3 +79,6 @@ class HyperOptAuto(IHyperOpt):

    def trailing_space(self) -> List['Dimension']:
        return self._get_func('trailing_space')()
+
+    def generate_estimator(self) -> EstimatorType:
+        return self._get_func('generate_estimator')()
--- a/freqtrade/optimize/hyperopt_interface.py
+++ b/freqtrade/optimize/hyperopt_interface.py
@@ -5,8 +5,9 @@ This module defines the interface to apply for hyperopt
 import logging
 import math
 from abc import ABC
-from typing import Dict, List
+from typing import Dict, List, Union

+from sklearn.base import RegressorMixin
 from skopt.space import Categorical, Dimension, Integer

 from freqtrade.exchange import timeframe_to_minutes
@@ -17,6 +18,8 @@ from freqtrade.strategy import IStrategy

 logger = logging.getLogger(__name__)

+EstimatorType = Union[RegressorMixin, str]
+

 class IHyperOpt(ABC):
    """
@@ -37,6 +40,14 @@ class IHyperOpt(ABC):
        IHyperOpt.ticker_interval = str(config['timeframe'])  # DEPRECATED
        IHyperOpt.timeframe = str(config['timeframe'])

+    def generate_estimator(self) -> EstimatorType:
+        """
+        Return base_estimator.
+        Can be any of "GP", "RF", "ET", "GBRT" or an instance of a class
+        inheriting from RegressorMixin (from sklearn).
+        """
+        return 'ET'
+
    def generate_roi_table(self, params: Dict) -> Dict[int, float]:
        """
        Create a ROI table.
--- a/freqtrade/optimize/hyperopt_tools.py
+++ b/freqtrade/optimize/hyperopt_tools.py
@@ -7,6 +7,7 @@ from pathlib import Path
 from typing import Any, Dict, Iterator, List, Optional, Tuple

 import numpy as np
+import pandas as pd
 import rapidjson
 import tabulate
 from colorama import Fore, Style
@@ -298,8 +299,8 @@ class HyperoptTools():
                f"Objective: {results['loss']:.5f}")

    @staticmethod
-    def prepare_trials_columns(trials, legacy_mode: bool, has_drawdown: bool) -> str:
-
+    def prepare_trials_columns(trials: pd.DataFrame, legacy_mode: bool,
+                               has_drawdown: bool) -> pd.DataFrame:
        trials['Best'] = ''

        if 'results_metrics.winsdrawslosses' not in trials.columns:
@@ -435,8 +436,7 @@ class HyperoptTools():
        return table

    @staticmethod
-    def export_csv_file(config: dict, results: list, total_epochs: int, highlight_best: bool,
-                        csv_file: str) -> None:
+    def export_csv_file(config: dict, results: list, csv_file: str) -> None:
        """
        Log result to csv-file
        """
--- a/freqtrade/persistence/models.py
+++ b/freqtrade/persistence/models.py
@@ -2,7 +2,7 @@
 This module contains the class to persist trades into SQLite
 """
 import logging
-from datetime import datetime, timezone
+from datetime import datetime, timedelta, timezone
 from decimal import Decimal
 from typing import Any, Dict, List, Optional

@@ -1057,17 +1057,21 @@ class Trade(_DECL_BASE, LocalTrade):
        return total_open_stake_amount or 0

    @staticmethod
-    def get_overall_performance() -> List[Dict[str, Any]]:
+    def get_overall_performance(minutes=None) -> List[Dict[str, Any]]:
        """
        Returns List of dicts containing all Trades, including profit and trade count
        NOTE: Not supported in Backtesting.
        """
+        filters = [Trade.is_open.is_(False)]
+        if minutes:
+            start_date = datetime.now(timezone.utc) - timedelta(minutes=minutes)
+            filters.append(Trade.close_date >= start_date)
        pair_rates = Trade.query.with_entities(
            Trade.pair,
            func.sum(Trade.close_profit).label('profit_sum'),
            func.sum(Trade.close_profit_abs).label('profit_sum_abs'),
            func.count(Trade.pair).label('count')
-        ).filter(Trade.is_open.is_(False))\
+        ).filter(*filters)\
            .group_by(Trade.pair) \
            .order_by(desc('profit_sum_abs')) \
            .all()
--- a/freqtrade/plugins/pairlist/AgeFilter.py
+++ b/freqtrade/plugins/pairlist/AgeFilter.py
@@ -8,6 +8,7 @@ from typing import Any, Dict, List, Optional
 import arrow
 from pandas import DataFrame

+from freqtrade.configuration import PeriodicCache
 from freqtrade.exceptions import OperationalException
 from freqtrade.misc import plural
 from freqtrade.plugins.pairlist.IPairList import IPairList
@@ -18,14 +19,15 @@ logger = logging.getLogger(__name__)

 class AgeFilter(IPairList):

-    # Checked symbols cache (dictionary of ticker symbol => timestamp)
-    _symbolsChecked: Dict[str, int] = {}
-
    def __init__(self, exchange, pairlistmanager,
                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
                 pairlist_pos: int) -> None:
        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)

+        # Checked symbols cache (dictionary of ticker symbol => timestamp)
+        self._symbolsChecked: Dict[str, int] = {}
+        self._symbolsCheckFailed = PeriodicCache(maxsize=1000, ttl=86_400)
+
        self._min_days_listed = pairlistconfig.get('min_days_listed', 10)
        self._max_days_listed = pairlistconfig.get('max_days_listed', None)

@@ -69,9 +71,12 @@ class AgeFilter(IPairList):
        :param tickers: Tickers (from exchange.get_tickers()). May be cached.
        :return: new allowlist
        """
-        needed_pairs = [(p, '1d') for p in pairlist if p not in self._symbolsChecked]
+        needed_pairs = [
+            (p, '1d') for p in pairlist
+            if p not in self._symbolsChecked and p not in self._symbolsCheckFailed]
        if not needed_pairs:
-            return pairlist
+            # Remove pairs that have been removed before
+            return [p for p in pairlist if p not in self._symbolsCheckFailed]

        since_days = -(
            self._max_days_listed if self._max_days_listed else self._min_days_listed
@@ -118,5 +123,6 @@ class AgeFilter(IPairList):
                    " or more than "
                    f"{self._max_days_listed} {plural(self._max_days_listed, 'day')}"
                ) if self._max_days_listed else ''), logger.info)
+                self._symbolsCheckFailed[pair] = arrow.utcnow().int_timestamp * 1000
                return False
        return False
--- a/freqtrade/plugins/pairlist/PerformanceFilter.py
+++ b/freqtrade/plugins/pairlist/PerformanceFilter.py
@@ -2,7 +2,7 @@
 Performance pair list filter
 """
 import logging
-from typing import Dict, List
+from typing import Any, Dict, List

 import pandas as pd

@@ -15,6 +15,13 @@ logger = logging.getLogger(__name__)

 class PerformanceFilter(IPairList):

+    def __init__(self, exchange, pairlistmanager,
+                 config: Dict[str, Any], pairlistconfig: Dict[str, Any],
+                 pairlist_pos: int) -> None:
+        super().__init__(exchange, pairlistmanager, config, pairlistconfig, pairlist_pos)
+
+        self._minutes = pairlistconfig.get('minutes', 0)
+
    @property
    def needstickers(self) -> bool:
        """
@@ -40,7 +47,7 @@ class PerformanceFilter(IPairList):
        """
        # Get the trading performance for pairs from database
        try:
-            performance = pd.DataFrame(Trade.get_overall_performance())
+            performance = pd.DataFrame(Trade.get_overall_performance(self._minutes))
        except AttributeError:
            # Performancefilter does not work in backtesting.
            self.log_once("PerformanceFilter is not available in this mode.", logger.warning)
--- a/freqtrade/rpc/api_server/api_schemas.py
+++ b/freqtrade/rpc/api_server/api_schemas.py
@@ -46,6 +46,12 @@ class Balances(BaseModel):
    value: float
    stake: str
    note: str
+    starting_capital: float
+    starting_capital_ratio: float
+    starting_capital_pct: float
+    starting_capital_fiat: float
+    starting_capital_fiat_ratio: float
+    starting_capital_fiat_pct: float


 class Count(BaseModel):
--- a/freqtrade/rpc/rpc.py
+++ b/freqtrade/rpc/rpc.py
@@ -459,6 +459,9 @@ class RPC:
            raise RPCException('Error getting current tickers.')

        self._freqtrade.wallets.update(require_update=False)
+        starting_capital = self._freqtrade.wallets.get_starting_balance()
+        starting_cap_fiat = self._fiat_converter.convert_amount(
+            starting_capital, stake_currency, fiat_display_currency) if self._fiat_converter else 0

        for coin, balance in self._freqtrade.wallets.get_all_balances().items():
            if not balance.total:
@@ -494,15 +497,25 @@ class RPC:
            else:
                raise RPCException('All balances are zero.')

-        symbol = fiat_display_currency
-        value = self._fiat_converter.convert_amount(total, stake_currency,
-                                                    symbol) if self._fiat_converter else 0
+        value = self._fiat_converter.convert_amount(
+            total, stake_currency, fiat_display_currency) if self._fiat_converter else 0
+
+        starting_capital_ratio = 0.0
+        starting_capital_ratio = (total / starting_capital) - 1 if starting_capital else 0.0
+        starting_cap_fiat_ratio = (value / starting_cap_fiat) - 1 if starting_cap_fiat else 0.0
+
        return {
            'currencies': output,
            'total': total,
-            'symbol': symbol,
+            'symbol': fiat_display_currency,
            'value': value,
            'stake': stake_currency,
+            'starting_capital': starting_capital,
+            'starting_capital_ratio': starting_capital_ratio,
+            'starting_capital_pct': round(starting_capital_ratio * 100, 2),
+            'starting_capital_fiat': starting_cap_fiat,
+            'starting_capital_fiat_ratio': starting_cap_fiat_ratio,
+            'starting_capital_fiat_pct': round(starting_cap_fiat_ratio * 100, 2),
            'note': 'Simulated balances' if self._freqtrade.config['dry_run'] else ''
        }

--- a/freqtrade/rpc/telegram.py
+++ b/freqtrade/rpc/telegram.py
@@ -603,12 +603,15 @@ class Telegram(RPCHandler):

            output = ''
            if self._config['dry_run']:
-                output += (
-                    f"*Warning:* Simulated balances in Dry Mode.\n"
-                    "This mode is still experimental!\n"
-                    "Starting capital: "
-                    f"`{self._config['dry_run_wallet']}` {self._config['stake_currency']}.\n"
-                )
+                output += "*Warning:* Simulated balances in Dry Mode.\n"
+
+            output += ("Starting capital: "
+                       f"`{result['starting_capital']}` {self._config['stake_currency']}"
+                       )
+            output += (f" `{result['starting_capital_fiat']}` "
+                       f"{self._config['fiat_display_currency']}.\n"
+                       ) if result['starting_capital_fiat'] > 0 else '.\n'
+
            total_dust_balance = 0
            total_dust_currencies = 0
            for curr in result['currencies']:
@@ -641,9 +644,12 @@ class Telegram(RPCHandler):
                    f"{round_coin_value(total_dust_balance, result['stake'], False)}`\n")

            output += ("\n*Estimated Value*:\n"
-                       f"\t`{result['stake']}: {result['total']: .8f}`\n"
+                       f"\t`{result['stake']}: "
+                       f"{round_coin_value(result['total'], result['stake'], False)}`"
+                       f" `({result['starting_capital_pct']}%)`\n"
                       f"\t`{result['symbol']}: "
-                       f"{round_coin_value(result['value'], result['symbol'], False)}`\n")
+                       f"{round_coin_value(result['value'], result['symbol'], False)}`"
+                       f" `({result['starting_capital_fiat_pct']}%)`\n")
            self._send_msg(output, reload_able=True, callback_path="update_balance",
                           query=update.callback_query)
        except RPCException as e:
--- a/freqtrade/strategy/init.py
+++ b/freqtrade/strategy/init.py
@@ -3,5 +3,7 @@ from freqtrade.exchange import (timeframe_to_minutes, timeframe_to_msecs, timefr
                                timeframe_to_prev_date, timeframe_to_seconds)
 from freqtrade.strategy.hyper import (BooleanParameter, CategoricalParameter, DecimalParameter,
                                      IntParameter, RealParameter)
+from freqtrade.strategy.informative_decorator import informative
 from freqtrade.strategy.interface import IStrategy
-from freqtrade.strategy.strategy_helper import merge_informative_pair, stoploss_from_open
+from freqtrade.strategy.strategy_helper import (merge_informative_pair, stoploss_from_absolute,
+                                                stoploss_from_open)
--- a/freqtrade/strategy/informative_decorator.py
+++ b/freqtrade/strategy/informative_decorator.py
@@ -0,0 +1,128 @@
+from typing import Any, Callable, NamedTuple, Optional, Union
+
+from pandas import DataFrame
+
+from freqtrade.exceptions import OperationalException
+from freqtrade.strategy.strategy_helper import merge_informative_pair
+
+
+PopulateIndicators = Callable[[Any, DataFrame, dict], DataFrame]
+
+
+class InformativeData(NamedTuple):
+    asset: Optional[str]
+    timeframe: str
+    fmt: Union[str, Callable[[Any], str], None]
+    ffill: bool
+
+
+def informative(timeframe: str, asset: str = '',
+                fmt: Optional[Union[str, Callable[[Any], str]]] = None,
+                ffill: bool = True) -> Callable[[PopulateIndicators], PopulateIndicators]:
+    """
+    A decorator for populate_indicators_Nn(self, dataframe, metadata), allowing these functions to
+    define informative indicators.
+
+    Example usage:
+
+        @informative('1h')
+        def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
+            dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
+            return dataframe
+
+    :param timeframe: Informative timeframe. Must always be equal or higher than strategy timeframe.
+    :param asset: Informative asset, for example BTC, BTC/USDT, ETH/BTC. Do not specify to use
+    current pair.
+    :param fmt: Column format (str) or column formatter (callable(name, asset, timeframe)). When not
+    specified, defaults to:
+    * {base}_{quote}_{column}_{timeframe} if asset is specified.
+    * {column}_{timeframe} if asset is not specified.
+    Format string supports these format variables:
+    * {asset} - full name of the asset, for example 'BTC/USDT'.
+    * {base} - base currency in lower case, for example 'eth'.
+    * {BASE} - same as {base}, except in upper case.
+    * {quote} - quote currency in lower case, for example 'usdt'.
+    * {QUOTE} - same as {quote}, except in upper case.
+    * {column} - name of dataframe column.
+    * {timeframe} - timeframe of informative dataframe.
+    :param ffill: ffill dataframe after merging informative pair.
+    """
+    _asset = asset
+    _timeframe = timeframe
+    _fmt = fmt
+    _ffill = ffill
+
+    def decorator(fn: PopulateIndicators):
+        informative_pairs = getattr(fn, '_ft_informative', [])
+        informative_pairs.append(InformativeData(_asset, _timeframe, _fmt, _ffill))
+        setattr(fn, '_ft_informative', informative_pairs)
+        return fn
+    return decorator
+
+
+def _format_pair_name(config, pair: str) -> str:
+    return pair.format(stake_currency=config['stake_currency'],
+                       stake=config['stake_currency']).upper()
+
+
+def _create_and_merge_informative_pair(strategy, dataframe: DataFrame, metadata: dict,
+                                       inf_data: InformativeData,
+                                       populate_indicators: PopulateIndicators):
+    asset = inf_data.asset or ''
+    timeframe = inf_data.timeframe
+    fmt = inf_data.fmt
+    config = strategy.config
+
+    if asset:
+        # Insert stake currency if needed.
+        asset = _format_pair_name(config, asset)
+    else:
+        # Not specifying an asset will define informative dataframe for current pair.
+        asset = metadata['pair']
+
+    if '/' in asset:
+        base, quote = asset.split('/')
+    else:
+        # When futures are supported this may need reevaluation.
+        # base, quote = asset, ''
+        raise OperationalException('Not implemented.')
+
+    # Default format. This optimizes for the common case: informative pairs using same stake
+    # currency. When quote currency matches stake currency, column name will omit base currency.
+    # This allows easily reconfiguring strategy to use different base currency. In a rare case
+    # where it is desired to keep quote currency in column name at all times user should specify
+    # fmt='{base}_{quote}_{column}_{timeframe}' format or similar.
+    if not fmt:
+        fmt = '{column}_{timeframe}'                # Informatives of current pair
+        if inf_data.asset:
+            fmt = '{base}_{quote}_' + fmt           # Informatives of other pairs
+
+    inf_metadata = {'pair': asset, 'timeframe': timeframe}
+    inf_dataframe = strategy.dp.get_pair_dataframe(asset, timeframe)
+    inf_dataframe = populate_indicators(strategy, inf_dataframe, inf_metadata)
+
+    formatter: Any = None
+    if callable(fmt):
+        formatter = fmt             # A custom user-specified formatter function.
+    else:
+        formatter = fmt.format      # A default string formatter.
+
+    fmt_args = {
+        'BASE': base.upper(),
+        'QUOTE': quote.upper(),
+        'base': base.lower(),
+        'quote': quote.lower(),
+        'asset': asset,
+        'timeframe': timeframe,
+    }
+    inf_dataframe.rename(columns=lambda column: formatter(column=column, **fmt_args),
+                         inplace=True)
+
+    date_column = formatter(column='date', **fmt_args)
+    if date_column in dataframe.columns:
+        raise OperationalException(f'Duplicate column name {date_column} exists in '
+                                   f'dataframe! Ensure column names are unique!')
+    dataframe = merge_informative_pair(dataframe, inf_dataframe, strategy.timeframe, timeframe,
+                                       ffill=inf_data.ffill, append_timeframe=False,
+                                       date_column=date_column)
+    return dataframe
--- a/freqtrade/strategy/interface.py
+++ b/freqtrade/strategy/interface.py
@@ -19,6 +19,9 @@ from freqtrade.exchange import timeframe_to_minutes, timeframe_to_seconds
 from freqtrade.exchange.exchange import timeframe_to_next_date
 from freqtrade.persistence import PairLocks, Trade
 from freqtrade.strategy.hyper import HyperStrategyMixin
+from freqtrade.strategy.informative_decorator import (InformativeData, PopulateIndicators,
+                                                      _create_and_merge_informative_pair,
+                                                      _format_pair_name)
 from freqtrade.strategy.strategy_wrapper import strategy_safe_wrapper
 from freqtrade.wallets import Wallets

@@ -118,7 +121,7 @@ class IStrategy(ABC, HyperStrategyMixin):
    # Class level variables (intentional) containing
    # the dataprovider (dp) (access to other candles, historic data, ...)
    # and wallets - access to the current balance.
-    dp: Optional[DataProvider] = None
+    dp: Optional[DataProvider]
    wallets: Optional[Wallets] = None
    # Filled from configuration
    stake_currency: str
@@ -134,6 +137,24 @@ class IStrategy(ABC, HyperStrategyMixin):
        self._last_candle_seen_per_pair: Dict[str, datetime] = {}
        super().__init__(config)

+        # Gather informative pairs from @informative-decorated methods.
+        self._ft_informative: List[Tuple[InformativeData, PopulateIndicators]] = []
+        for attr_name in dir(self.__class__):
+            cls_method = getattr(self.__class__, attr_name)
+            if not callable(cls_method):
+                continue
+            informative_data_list = getattr(cls_method, '_ft_informative', None)
+            if not isinstance(informative_data_list, list):
+                # Type check is required because mocker would return a mock object that evaluates to
+                # True, confusing this code.
+                continue
+            strategy_timeframe_minutes = timeframe_to_minutes(self.timeframe)
+            for informative_data in informative_data_list:
+                if timeframe_to_minutes(informative_data.timeframe) < strategy_timeframe_minutes:
+                    raise OperationalException('Informative timeframe must be equal or higher than '
+                                               'strategy timeframe!')
+                self._ft_informative.append((informative_data, cls_method))
+
    @abstractmethod
    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
@@ -377,6 +398,23 @@ class IStrategy(ABC, HyperStrategyMixin):
 # END - Intended to be overridden by strategy
 ###

+    def gather_informative_pairs(self) -> ListPairsWithTimeframes:
+        """
+        Internal method which gathers all informative pairs (user or automatically defined).
+        """
+        informative_pairs = self.informative_pairs()
+        for inf_data, _ in self._ft_informative:
+            if inf_data.asset:
+                pair_tf = (_format_pair_name(self.config, inf_data.asset), inf_data.timeframe)
+                informative_pairs.append(pair_tf)
+            else:
+                if not self.dp:
+                    raise OperationalException('@informative decorator with unspecified asset '
+                                               'requires DataProvider instance.')
+                for pair in self.dp.current_whitelist():
+                    informative_pairs.append((pair, inf_data.timeframe))
+        return list(set(informative_pairs))
+
    def get_strategy_name(self) -> str:
        """
        Returns strategy class name
@@ -786,10 +824,11 @@ class IStrategy(ABC, HyperStrategyMixin):
        Does not run advise_buy or advise_sell!
        Used by optimize operations only, not during dry / live runs.
        Using .copy() to get a fresh copy of the dataframe for every strategy run.
+        Also copy on output to avoid PerformanceWarnings pandas 1.3.0 started to show.
        Has positive effects on memory usage for whatever reason - also when
        using only one strategy.
        """
-        return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair})
+        return {pair: self.advise_indicators(pair_data.copy(), {'pair': pair}).copy()
                for pair, pair_data in data.items()}

    def advise_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
@@ -801,6 +840,12 @@ class IStrategy(ABC, HyperStrategyMixin):
        :return: a Dataframe with all mandatory indicators for the strategies
        """
        logger.debug(f"Populating indicators for pair {metadata.get('pair')}.")
+
+        # call populate_indicators_Nm() which were tagged with @informative decorator.
+        for inf_data, populate_fn in self._ft_informative:
+            dataframe = _create_and_merge_informative_pair(
+                self, dataframe, metadata, inf_data, populate_fn)
+
        if self._populate_fun_len == 2:
            warnings.warn("deprecated - check out the Sample strategy to see "
                          "the current function headers!", DeprecationWarning)
--- a/freqtrade/strategy/strategy_helper.py
+++ b/freqtrade/strategy/strategy_helper.py
@@ -4,7 +4,9 @@ from freqtrade.exchange import timeframe_to_minutes


 def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
-                           timeframe: str, timeframe_inf: str, ffill: bool = True) -> pd.DataFrame:
+                           timeframe: str, timeframe_inf: str, ffill: bool = True,
+                           append_timeframe: bool = True,
+                           date_column: str = 'date') -> pd.DataFrame:
    """
    Correctly merge informative samples to the original dataframe, avoiding lookahead bias.

@@ -24,6 +26,8 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
    :param timeframe: Timeframe of the original pair sample.
    :param timeframe_inf: Timeframe of the informative pair sample.
    :param ffill: Forwardfill missing values - optional but usually required
+    :param append_timeframe: Rename columns by appending timeframe.
+    :param date_column: A custom date column name.
    :return: Merged dataframe
    :raise: ValueError if the secondary timeframe is shorter than the dataframe timeframe
    """
@@ -32,25 +36,29 @@ def merge_informative_pair(dataframe: pd.DataFrame, informative: pd.DataFrame,
    minutes = timeframe_to_minutes(timeframe)
    if minutes == minutes_inf:
        # No need to forwardshift if the timeframes are identical
-        informative['date_merge'] = informative["date"]
+        informative['date_merge'] = informative[date_column]
    elif minutes < minutes_inf:
        # Subtract "small" timeframe so merging is not delayed by 1 small candle
        # Detailed explanation in https://github.com/freqtrade/freqtrade/issues/4073
        informative['date_merge'] = (
-            informative["date"] + pd.to_timedelta(minutes_inf, 'm') - pd.to_timedelta(minutes, 'm')
+            informative[date_column] + pd.to_timedelta(minutes_inf, 'm') -
+            pd.to_timedelta(minutes, 'm')
        )
    else:
        raise ValueError("Tried to merge a faster timeframe to a slower timeframe."
                         "This would create new rows, and can throw off your regular indicators.")

    # Rename columns to be unique
-    informative.columns = [f"{col}_{timeframe_inf}" for col in informative.columns]
+    date_merge = 'date_merge'
+    if append_timeframe:
+        date_merge = f'date_merge_{timeframe_inf}'
+        informative.columns = [f"{col}_{timeframe_inf}" for col in informative.columns]

    # Combine the 2 dataframes
    # all indicators on the informative sample MUST be calculated before this point
    dataframe = pd.merge(dataframe, informative, left_on='date',
-                         right_on=f'date_merge_{timeframe_inf}', how='left')
-    dataframe = dataframe.drop(f'date_merge_{timeframe_inf}', axis=1)
+                         right_on=date_merge, how='left')
+    dataframe = dataframe.drop(date_merge, axis=1)

    if ffill:
        dataframe = dataframe.ffill()
@@ -83,3 +91,28 @@ def stoploss_from_open(open_relative_stop: float, current_profit: float) -> floa

    # negative stoploss values indicate the requested stop price is higher than the current price
    return max(stoploss, 0.0)
+
+
+def stoploss_from_absolute(stop_rate: float, current_rate: float) -> float:
+    """
+    Given current price and desired stop price, return a stop loss value that is relative to current
+    price.
+
+    The requested stop can be positive for a stop above the open price, or negative for
+    a stop below the open price. The return value is always >= 0.
+
+    Returns 0 if the resulting stop price would be above the current price.
+
+    :param stop_rate: Stop loss price.
+    :param current_rate: Current asset price.
+    :return: Positive stop loss value relative to current price
+    """
+
+    # formula is undefined for current_rate 0, return maximum value
+    if current_rate == 0:
+        return 1
+
+    stoploss = 1 - (stop_rate / current_rate)
+
+    # negative stoploss values indicate the requested stop price is higher than the current price
+    return max(stoploss, 0.0)