Merge remote-tracking branch 'origin/tmp/calcprofit' into pr/mkavinkumar1/6545

freqtrade/commands/__init__.py

@@ -6,6 +6,7 @@ Contains all start-commands, subcommands and CLI Interface creation.
 Note: Be careful with file-scoped imports in these subfiles.
     as they are parsed on startup, nothing containing optional modules should be loaded.
 """
+from freqtrade.commands.analyze_commands import start_analysis_entries_exits
 from freqtrade.commands.arguments import Arguments
 from freqtrade.commands.build_config_commands import start_new_config
 from freqtrade.commands.data_commands import (start_convert_data, start_convert_trades,

freqtrade/commands/analyze_commands.py

@@ -0,0 +1,69 @@
+import logging
+from pathlib import Path
+from typing import Any, Dict
+
+from freqtrade.configuration import setup_utils_configuration
+from freqtrade.enums import RunMode
+from freqtrade.exceptions import OperationalException
+
+
+logger = logging.getLogger(__name__)
+
+
+def setup_analyze_configuration(args: Dict[str, Any], method: RunMode) -> Dict[str, Any]:
+    """
+    Prepare the configuration for the entry/exit reason analysis module
+    :param args: Cli args from Arguments()
+    :param method: Bot running mode
+    :return: Configuration
+    """
+    config = setup_utils_configuration(args, method)
+
+    no_unlimited_runmodes = {
+        RunMode.BACKTEST: 'backtesting',
+    }
+    if method in no_unlimited_runmodes.keys():
+        from freqtrade.data.btanalysis import get_latest_backtest_filename
+
+        if 'exportfilename' in config:
+            if config['exportfilename'].is_dir():
+                btfile = Path(get_latest_backtest_filename(config['exportfilename']))
+                signals_file = f"{config['exportfilename']}/{btfile.stem}_signals.pkl"
+            else:
+                if config['exportfilename'].exists():
+                    btfile = Path(config['exportfilename'])
+                    signals_file = f"{btfile.parent}/{btfile.stem}_signals.pkl"
+                else:
+                    raise OperationalException(f"{config['exportfilename']} does not exist.")
+        else:
+            raise OperationalException('exportfilename not in config.')
+
+        if (not Path(signals_file).exists()):
+            raise OperationalException(
+                (f"Cannot find latest backtest signals file: {signals_file}."
+                  "Run backtesting with `--export signals`.")
+            )
+
+    return config
+
+
+def start_analysis_entries_exits(args: Dict[str, Any]) -> None:
+    """
+    Start analysis script
+    :param args: Cli args from Arguments()
+    :return: None
+    """
+    from freqtrade.data.entryexitanalysis import process_entry_exit_reasons
+
+    # Initialize configuration
+    config = setup_analyze_configuration(args, RunMode.BACKTEST)
+
+    logger.info('Starting freqtrade in analysis mode')
+
+    process_entry_exit_reasons(config['exportfilename'],
+                               config['exchange']['pair_whitelist'],
+                               config['analysis_groups'],
+                               config['enter_reason_list'],
+                               config['exit_reason_list'],
+                               config['indicator_list']
+                               )

freqtrade/commands/arguments.py

@@ -101,6 +101,9 @@ ARGS_HYPEROPT_SHOW = ["hyperopt_list_best", "hyperopt_list_profitable", "hyperop
                       "print_json", "hyperoptexportfilename", "hyperopt_show_no_header",
                       "disableparamexport", "backtest_breakdown"]
 
+ARGS_ANALYZE_ENTRIES_EXITS = ["exportfilename", "analysis_groups", "enter_reason_list",
+                              "exit_reason_list", "indicator_list"]
+
 NO_CONF_REQURIED = ["convert-data", "convert-trade-data", "download-data", "list-timeframes",
                     "list-markets", "list-pairs", "list-strategies", "list-data",
                     "hyperopt-list", "hyperopt-show", "backtest-filter",
@@ -182,8 +185,9 @@ class Arguments:
         self.parser = argparse.ArgumentParser(description='Free, open source crypto trading bot')
         self._build_args(optionlist=['version'], parser=self.parser)
 
-        from freqtrade.commands import (start_backtesting, start_backtesting_show,
-                                        start_convert_data, start_convert_db, start_convert_trades,
+        from freqtrade.commands import (start_analysis_entries_exits, start_backtesting,
+                                        start_backtesting_show, start_convert_data,
+                                        start_convert_db, start_convert_trades,
                                         start_create_userdir, start_download_data, start_edge,
                                         start_hyperopt, start_hyperopt_list, start_hyperopt_show,
                                         start_install_ui, start_list_data, start_list_exchanges,
@@ -283,6 +287,13 @@ class Arguments:
         backtesting_show_cmd.set_defaults(func=start_backtesting_show)
         self._build_args(optionlist=ARGS_BACKTEST_SHOW, parser=backtesting_show_cmd)
 
+        # Add backtesting analysis subcommand
+        analysis_cmd = subparsers.add_parser('backtesting-analysis',
+                                             help='Backtest Analysis module.',
+                                             parents=[_common_parser])
+        analysis_cmd.set_defaults(func=start_analysis_entries_exits)
+        self._build_args(optionlist=ARGS_ANALYZE_ENTRIES_EXITS, parser=analysis_cmd)
+
         # Add edge subcommand
         edge_cmd = subparsers.add_parser('edge', help='Edge module.',
                                          parents=[_common_parser, _strategy_parser])

freqtrade/commands/cli_options.py

@@ -614,4 +614,37 @@ AVAILABLE_CLI_OPTIONS = {
               "that do not contain any parameters."),
         action="store_true",
     ),
+    "analysis_groups": Arg(
+        "--analysis-groups",
+        help=("grouping output - "
+              "0: simple wins/losses by enter tag, "
+              "1: by enter_tag, "
+              "2: by enter_tag and exit_tag, "
+              "3: by pair and enter_tag, "
+              "4: by pair, enter_ and exit_tag (this can get quite large)"),
+        nargs='+',
+        default=['0', '1', '2'],
+        choices=['0', '1', '2', '3', '4'],
+    ),
+    "enter_reason_list": Arg(
+        "--enter-reason-list",
+        help=("Comma separated list of entry signals to analyse. Default: all. "
+              "e.g. 'entry_tag_a,entry_tag_b'"),
+        nargs='+',
+        default=['all'],
+    ),
+    "exit_reason_list": Arg(
+        "--exit-reason-list",
+        help=("Comma separated list of exit signals to analyse. Default: all. "
+              "e.g. 'exit_tag_a,roi,stop_loss,trailing_stop_loss'"),
+        nargs='+',
+        default=['all'],
+    ),
+    "indicator_list": Arg(
+        "--indicator-list",
+        help=("Comma separated list of indicators to analyse. "
+              "e.g. 'close,rsi,bb_lowerband,profit_abs'"),
+        nargs='+',
+        default=[],
+    ),
 }

freqtrade/configuration/configuration.py

@@ -95,6 +95,8 @@ class Configuration:
 
         self._process_data_options(config)
 
+        self._process_analyze_options(config)
+
         # Check if the exchange set by the user is supported
         check_exchange(config, config.get('experimental', {}).get('block_bad_exchanges', True))
 
@@ -433,6 +435,19 @@ class Configuration:
         self._args_to_config(config, argname='candle_types',
                              logstring='Detected --candle-types: {}')
 
+    def _process_analyze_options(self, config: Dict[str, Any]) -> None:
+        self._args_to_config(config, argname='analysis_groups',
+                             logstring='Analysis reason groups: {}')
+
+        self._args_to_config(config, argname='enter_reason_list',
+                             logstring='Analysis enter tag list: {}')
+
+        self._args_to_config(config, argname='exit_reason_list',
+                             logstring='Analysis exit tag list: {}')
+
+        self._args_to_config(config, argname='indicator_list',
+                             logstring='Analysis indicator list: {}')
+
     def _process_runmode(self, config: Dict[str, Any]) -> None:
 
         self._args_to_config(config, argname='dry_run',

freqtrade/data/entryexitanalysis.py

@@ -0,0 +1,227 @@
+import logging
+from pathlib import Path
+from typing import List, Optional
+
+import joblib
+import pandas as pd
+from tabulate import tabulate
+
+from freqtrade.data.btanalysis import (get_latest_backtest_filename, load_backtest_data,
+                                       load_backtest_stats)
+from freqtrade.exceptions import OperationalException
+
+
+logger = logging.getLogger(__name__)
+
+
+def _load_signal_candles(backtest_dir: Path):
+    if backtest_dir.is_dir():
+        scpf = Path(backtest_dir,
+                    Path(get_latest_backtest_filename(backtest_dir)).stem + "_signals.pkl"
+                    )
+    else:
+        scpf = Path(backtest_dir.parent / f"{backtest_dir.stem}_signals.pkl")
+
+    try:
+        scp = open(scpf, "rb")
+        signal_candles = joblib.load(scp)
+        logger.info(f"Loaded signal candles: {str(scpf)}")
+    except Exception as e:
+        logger.error("Cannot load signal candles from pickled results: ", e)
+
+    return signal_candles
+
+
+def _process_candles_and_indicators(pairlist, strategy_name, trades, signal_candles):
+    analysed_trades_dict = {}
+    analysed_trades_dict[strategy_name] = {}
+
+    try:
+        logger.info(f"Processing {strategy_name} : {len(pairlist)} pairs")
+
+        for pair in pairlist:
+            if pair in signal_candles[strategy_name]:
+                analysed_trades_dict[strategy_name][pair] = _analyze_candles_and_indicators(
+                                                              pair,
+                                                              trades,
+                                                              signal_candles[strategy_name][pair])
+    except Exception as e:
+        print(f"Cannot process entry/exit reasons for {strategy_name}: ", e)
+
+    return analysed_trades_dict
+
+
+def _analyze_candles_and_indicators(pair, trades, signal_candles):
+    buyf = signal_candles
+
+    if len(buyf) > 0:
+        buyf = buyf.set_index('date', drop=False)
+        trades_red = trades.loc[trades['pair'] == pair].copy()
+
+        trades_inds = pd.DataFrame()
+
+        if trades_red.shape[0] > 0 and buyf.shape[0] > 0:
+            for t, v in trades_red.open_date.items():
+                allinds = buyf.loc[(buyf['date'] < v)]
+                if allinds.shape[0] > 0:
+                    tmp_inds = allinds.iloc[[-1]]
+
+                    trades_red.loc[t, 'signal_date'] = tmp_inds['date'].values[0]
+                    trades_red.loc[t, 'enter_reason'] = trades_red.loc[t, 'enter_tag']
+                    tmp_inds.index.rename('signal_date', inplace=True)
+                    trades_inds = pd.concat([trades_inds, tmp_inds])
+
+            if 'signal_date' in trades_red:
+                trades_red['signal_date'] = pd.to_datetime(trades_red['signal_date'], utc=True)
+                trades_red.set_index('signal_date', inplace=True)
+
+                try:
+                    trades_red = pd.merge(trades_red, trades_inds, on='signal_date', how='outer')
+                except Exception as e:
+                    raise e
+        return trades_red
+    else:
+        return pd.DataFrame()
+
+
+def _do_group_table_output(bigdf, glist):
+    for g in glist:
+        # 0: summary wins/losses grouped by enter tag
+        if g == "0":
+            group_mask = ['enter_reason']
+            wins = bigdf.loc[bigdf['profit_abs'] >= 0] \
+                        .groupby(group_mask) \
+                        .agg({'profit_abs': ['sum']})
+
+            wins.columns = ['profit_abs_wins']
+            loss = bigdf.loc[bigdf['profit_abs'] < 0] \
+                        .groupby(group_mask) \
+                        .agg({'profit_abs': ['sum']})
+            loss.columns = ['profit_abs_loss']
+
+            new = bigdf.groupby(group_mask).agg({'profit_abs': [
+                                                    'count',
+                                                    lambda x: sum(x > 0),
+                                                    lambda x: sum(x <= 0)]})
+            new = pd.concat([new, wins, loss], axis=1).fillna(0)
+
+            new['profit_tot'] = new['profit_abs_wins'] - abs(new['profit_abs_loss'])
+            new['wl_ratio_pct'] = (new.iloc[:, 1] / new.iloc[:, 0] * 100).fillna(0)
+            new['avg_win'] = (new['profit_abs_wins'] / new.iloc[:, 1]).fillna(0)
+            new['avg_loss'] = (new['profit_abs_loss'] / new.iloc[:, 2]).fillna(0)
+
+            new.columns = ['total_num_buys', 'wins', 'losses', 'profit_abs_wins', 'profit_abs_loss',
+                           'profit_tot', 'wl_ratio_pct', 'avg_win', 'avg_loss']
+
+            sortcols = ['total_num_buys']
+
+            _print_table(new, sortcols, show_index=True)
+
+        else:
+            agg_mask = {'profit_abs': ['count', 'sum', 'median', 'mean'],
+                        'profit_ratio': ['sum', 'median', 'mean']}
+            agg_cols = ['num_buys', 'profit_abs_sum', 'profit_abs_median',
+                        'profit_abs_mean', 'median_profit_pct', 'mean_profit_pct',
+                        'total_profit_pct']
+            sortcols = ['profit_abs_sum', 'enter_reason']
+
+            # 1: profit summaries grouped by enter_tag
+            if g == "1":
+                group_mask = ['enter_reason']
+
+            # 2: profit summaries grouped by enter_tag and exit_tag
+            if g == "2":
+                group_mask = ['enter_reason', 'exit_reason']
+
+            # 3: profit summaries grouped by pair and enter_tag
+            if g == "3":
+                group_mask = ['pair', 'enter_reason']
+
+            # 4: profit summaries grouped by pair, enter_ and exit_tag (this can get quite large)
+            if g == "4":
+                group_mask = ['pair', 'enter_reason', 'exit_reason']
+            if group_mask:
+                new = bigdf.groupby(group_mask).agg(agg_mask).reset_index()
+                new.columns = group_mask + agg_cols
+                new['median_profit_pct'] = new['median_profit_pct'] * 100
+                new['mean_profit_pct'] = new['mean_profit_pct'] * 100
+                new['total_profit_pct'] = new['total_profit_pct'] * 100
+
+                _print_table(new, sortcols)
+            else:
+                logger.warning("Invalid group mask specified.")
+
+
+def _print_results(analysed_trades, stratname, analysis_groups,
+                   enter_reason_list, exit_reason_list,
+                   indicator_list, columns=None):
+    if columns is None:
+        columns = ['pair', 'open_date', 'close_date', 'profit_abs', 'enter_reason', 'exit_reason']
+
+    bigdf = pd.DataFrame()
+    for pair, trades in analysed_trades[stratname].items():
+        bigdf = pd.concat([bigdf, trades], ignore_index=True)
+
+    if bigdf.shape[0] > 0 and ('enter_reason' in bigdf.columns):
+        if analysis_groups:
+            _do_group_table_output(bigdf, analysis_groups)
+
+        if enter_reason_list and "all" not in enter_reason_list:
+            bigdf = bigdf.loc[(bigdf['enter_reason'].isin(enter_reason_list))]
+
+        if exit_reason_list and "all" not in exit_reason_list:
+            bigdf = bigdf.loc[(bigdf['exit_reason'].isin(exit_reason_list))]
+
+        if "all" in indicator_list:
+            print(bigdf)
+        elif indicator_list is not None:
+            available_inds = []
+            for ind in indicator_list:
+                if ind in bigdf:
+                    available_inds.append(ind)
+            ilist = ["pair", "enter_reason", "exit_reason"] + available_inds
+            _print_table(bigdf[ilist], sortcols=['exit_reason'], show_index=False)
+    else:
+        print("\\_ No trades to show")
+
+
+def _print_table(df, sortcols=None, show_index=False):
+    if (sortcols is not None):
+        data = df.sort_values(sortcols)
+    else:
+        data = df
+
+    print(
+        tabulate(
+            data,
+            headers='keys',
+            tablefmt='psql',
+            showindex=show_index
+        )
+    )
+
+
+def process_entry_exit_reasons(backtest_dir: Path,
+                               pairlist: List[str],
+                               analysis_groups: Optional[List[str]] = ["0", "1", "2"],
+                               enter_reason_list: Optional[List[str]] = ["all"],
+                               exit_reason_list: Optional[List[str]] = ["all"],
+                               indicator_list: Optional[List[str]] = []):
+    try:
+        backtest_stats = load_backtest_stats(backtest_dir)
+        for strategy_name, results in backtest_stats['strategy'].items():
+            trades = load_backtest_data(backtest_dir, strategy_name)
+
+            if not trades.empty:
+                signal_candles = _load_signal_candles(backtest_dir)
+                analysed_trades_dict = _process_candles_and_indicators(pairlist, strategy_name,
+                                                                       trades, signal_candles)
+                _print_results(analysed_trades_dict,
+                               strategy_name,
+                               analysis_groups,
+                               enter_reason_list,
+                               exit_reason_list,
+                               indicator_list)
+
+    except ValueError as e:
+        raise OperationalException(e) from e

freqtrade/exchange/exchange.py

@@ -93,7 +93,7 @@ class Exchange:
         :return: None
         """
         self._api: ccxt.Exchange
-        self._api_async: ccxt_async.Exchange
+        self._api_async: ccxt_async.Exchange = None
         self._markets: Dict = {}
         self._trading_fees: Dict[str, Any] = {}
         self._leverage_tiers: Dict[str, List[Dict]] = {}

freqtrade/optimize/backtesting.py

@@ -1297,13 +1297,14 @@ class Backtesting:
                 self.results['strategy_comparison'].extend(results['strategy_comparison'])
             else:
                 self.results = results
-
+            dt_appendix = datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
             if self.config.get('export', 'none') in ('trades', 'signals'):
-                store_backtest_stats(self.config['exportfilename'], self.results)
+                store_backtest_stats(self.config['exportfilename'], self.results, dt_appendix)
 
             if (self.config.get('export', 'none') == 'signals' and
                     self.dataprovider.runmode == RunMode.BACKTEST):
-                store_backtest_signal_candles(self.config['exportfilename'], self.processed_dfs)
+                store_backtest_signal_candles(
+                    self.config['exportfilename'], self.processed_dfs, dt_appendix)
 
         # Results may be mixed up now. Sort them so they follow --strategy-list order.
         if 'strategy_list' in self.config and len(self.results) > 0:

freqtrade/optimize/optimize_reports.py

@@ -17,21 +17,21 @@ from freqtrade.optimize.backtest_caching import get_backtest_metadata_filename
 logger = logging.getLogger(__name__)
 
 
-def store_backtest_stats(recordfilename: Path, stats: Dict[str, DataFrame]) -> None:
+def store_backtest_stats(
+        recordfilename: Path, stats: Dict[str, DataFrame], dtappendix: str) -> None:
     """
     Stores backtest results
     :param recordfilename: Path object, which can either be a filename or a directory.
         Filenames will be appended with a timestamp right before the suffix
         while for directories, <directory>/backtest-result-<datetime>.json will be used as filename
     :param stats: Dataframe containing the backtesting statistics
+    :param dtappendix: Datetime to use for the filename
     """
     if recordfilename.is_dir():
-        filename = (recordfilename /
-                    f'backtest-result-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}.json')
+        filename = (recordfilename / f'backtest-result-{dtappendix}.json')
     else:
         filename = Path.joinpath(
-            recordfilename.parent,
-            f'{recordfilename.stem}-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}'
+            recordfilename.parent, f'{recordfilename.stem}-{dtappendix}'
         ).with_suffix(recordfilename.suffix)
 
     # Store metadata separately.
@@ -44,7 +44,8 @@ def store_backtest_stats(recordfilename: Path, stats: Dict[str, DataFrame]) -> N
     file_dump_json(latest_filename, {'latest_backtest': str(filename.name)})
 
 
-def store_backtest_signal_candles(recordfilename: Path, candles: Dict[str, Dict]) -> Path:
+def store_backtest_signal_candles(
+        recordfilename: Path, candles: Dict[str, Dict], dtappendix: str) -> Path:
     """
     Stores backtest trade signal candles
     :param recordfilename: Path object, which can either be a filename or a directory.
@@ -52,14 +53,13 @@ def store_backtest_signal_candles(recordfilename: Path, candles: Dict[str, Dict]
         while for directories, <directory>/backtest-result-<datetime>_signals.pkl will be used
         as filename
     :param stats: Dict containing the backtesting signal candles
+    :param dtappendix: Datetime to use for the filename
     """
     if recordfilename.is_dir():
-        filename = (recordfilename /
-                    f'backtest-result-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}_signals.pkl')
+        filename = (recordfilename / f'backtest-result-{dtappendix}_signals.pkl')
     else:
         filename = Path.joinpath(
-            recordfilename.parent,
-            f'{recordfilename.stem}-{datetime.now().strftime("%Y-%m-%d_%H-%M-%S")}_signals.pkl'
+            recordfilename.parent, f'{recordfilename.stem}-{dtappendix}_signals.pkl'
         )
 
     file_dump_joblib(filename, candles)

freqtrade/persistence/trade_model.py

@@ -666,8 +666,8 @@ class LocalTrade():
         """
         self.close_rate = rate
         self.close_date = self.close_date or datetime.utcnow()
-        self.close_profit = self.calc_profit_ratio()
-        self.close_profit_abs = self.calc_profit() + self.realized_profit
+        self.close_profit = self.calc_profit_ratio(rate)
+        self.close_profit_abs = self.calc_profit(rate) + self.realized_profit
         self.is_open = False
         self.exit_order_status = 'closed'
         self.open_order_id = None
@@ -716,12 +716,12 @@ class LocalTrade():
         """
         return len([o for o in self.orders if o.ft_order_side == self.exit_side])
 
-    def _calc_open_trade_value(self) -> float:
+    def _calc_open_trade_value(self, amount: float, open_rate: float) -> float:
         """
         Calculate the open_rate including open_fee.
         :return: Price in of the open trade incl. Fees
         """
-        open_trade = Decimal(self.amount) * Decimal(self.open_rate)
+        open_trade = Decimal(amount) * Decimal(open_rate)
         fees = open_trade * Decimal(self.fee_open)
         if self.is_short:
             return float(open_trade - fees)
@@ -733,12 +733,11 @@ class LocalTrade():
         Recalculate open_trade_value.
         Must be called whenever open_rate, fee_open is changed.
         """
-        self.open_trade_value = self._calc_open_trade_value()
+        self.open_trade_value = self._calc_open_trade_value(self.amount, self.open_rate)
 
-    def calculate_interest(self, interest_rate: Optional[float] = None) -> Decimal:
+    def calculate_interest(self) -> Decimal:
         """
-        :param interest_rate: interest_charge for borrowing this coin(optional).
-        If interest_rate is not set self.interest_rate will be used
+        Calculate interest for this trade. Only applicable for Margin trading.
         """
         zero = Decimal(0.0)
         # If nothing was borrowed
@@ -751,90 +750,77 @@ class LocalTrade():
         total_seconds = Decimal((now - open_date).total_seconds())
         hours = total_seconds / sec_per_hour or zero
 
-        rate = Decimal(interest_rate or self.interest_rate)
+        rate = Decimal(self.interest_rate)
         borrowed = Decimal(self.borrowed)
 
         return interest(exchange_name=self.exchange, borrowed=borrowed, rate=rate, hours=hours)
 
-    def _calc_base_close(self, amount: Decimal, rate: Optional[float] = None,
-                         fee: Optional[float] = None) -> Decimal:
+    def _calc_base_close(self, amount: Decimal, rate: float, fee: float) -> Decimal:
 
-        close_trade = Decimal(amount) * Decimal(rate or self.close_rate)  # type: ignore
-        fees = close_trade * Decimal(fee or self.fee_close)
+        close_trade = amount * Decimal(rate)
+        fees = close_trade * Decimal(fee)
 
         if self.is_short:
             return close_trade + fees
         else:
             return close_trade - fees
 
-    def calc_close_trade_value(self, rate: Optional[float] = None,
-                               fee: Optional[float] = None,
-                               interest_rate: Optional[float] = None) -> float:
+    def calc_close_trade_value(self, rate: float, amount: float = None) -> float:
         """
-        Calculate the close_rate including fee
-        :param fee: fee to use on the close rate (optional).
-            If rate is not set self.fee will be used
-        :param rate: rate to compare with (optional).
-            If rate is not set self.close_rate will be used
-        :param interest_rate: interest_charge for borrowing this coin (optional).
-            If interest_rate is not set self.interest_rate will be used
-        :return: Price in BTC of the open trade
+        Calculate the Trade's close value including fees
+        :param rate: rate to compare with.
+        :return: value in stake currency of the open trade
         """
         if rate is None and not self.close_rate:
             return 0.0
 
-        amount = Decimal(self.amount)
+        amount = Decimal(amount or self.amount)
         trading_mode = self.trading_mode or TradingMode.SPOT
 
         if trading_mode == TradingMode.SPOT:
-            return float(self._calc_base_close(amount, rate, fee))
+            return float(self._calc_base_close(amount, rate, self.fee_close))
 
         elif (trading_mode == TradingMode.MARGIN):
 
-            total_interest = self.calculate_interest(interest_rate)
+            total_interest = self.calculate_interest()
 
             if self.is_short:
                 amount = amount + total_interest
-                return float(self._calc_base_close(amount, rate, fee))
+                return float(self._calc_base_close(amount, rate, self.fee_close))
             else:
                 # Currency already owned for longs, no need to purchase
-                return float(self._calc_base_close(amount, rate, fee) - total_interest)
+                return float(self._calc_base_close(amount, rate, self.fee_close) - total_interest)
 
         elif (trading_mode == TradingMode.FUTURES):
             funding_fees = self.funding_fees or 0.0
             # Positive funding_fees -> Trade has gained from fees.
             # Negative funding_fees -> Trade had to pay the fees.
             if self.is_short:
-                return float(self._calc_base_close(amount, rate, fee)) - funding_fees
+                return float(self._calc_base_close(amount, rate, self.fee_close)) - funding_fees
             else:
-                return float(self._calc_base_close(amount, rate, fee)) + funding_fees
+                return float(self._calc_base_close(amount, rate, self.fee_close)) + funding_fees
         else:
             raise OperationalException(
                 f"{self.trading_mode.value} trading is not yet available using freqtrade")
 
-    def calc_profit(self, rate: Optional[float] = None,
-                    fee: Optional[float] = None,
-                    interest_rate: Optional[float] = None) -> float:
+    def calc_profit(self, rate: float, amount: float = None, open_rate: float = None) -> float:
         """
         Calculate the absolute profit in stake currency between Close and Open trade
-        :param fee: fee to use on the close rate (optional).
-            If fee is not set self.fee will be used
-        :param rate: close rate to compare with (optional).
-            If rate is not set self.close_rate will be used
-        :param interest_rate: interest_charge for borrowing this coin (optional).
-            If interest_rate is not set self.interest_rate will be used
-        :return:  profit in stake currency as float
+        :param rate: close rate to compare with.
+        :param amount: Amount to use for the calculation. Falls back to trade.amount if not set.
+        :param open_rate: open_rate to use. Defaults to self.open_rate if not provided.
+        :return: profit in stake currency as float
         """
-        close_trade_value = self.calc_close_trade_value(
-            rate=(rate or self.close_rate),
-            fee=(fee or self.fee_close),
-            interest_rate=(interest_rate or self.interest_rate)
-        )
+        close_trade_value = self.calc_close_trade_value(rate, amount)
+        if amount is None or open_rate is None:
+            open_trade_value = self.open_trade_value
+        else:
+            open_trade_value = self._calc_open_trade_value(amount, open_rate)
 
         if self.is_short:
-            profit = self.open_trade_value - close_trade_value
+            profit = open_trade_value - close_trade_value
         else:
-            profit = close_trade_value - self.open_trade_value
+            profit = close_trade_value - open_trade_value
         return float(f"{profit:.8f}")
 
     def calc_profit2(self, open_rate: float, close_rate: float,
@@ -845,35 +831,33 @@ class LocalTrade():
                      * (Decimal(1 - self.fee_close) * Decimal(close_rate)
                         - Decimal(1 + self.fee_open) * Decimal(open_rate)))
 
-    def calc_profit_ratio(self, rate: Optional[float] = None,
-                          fee: Optional[float] = None,
-                          interest_rate: Optional[float] = None) -> float:
+    def calc_profit_ratio(
+            self, rate: float, amount: float = None, open_rate: float = None) -> float:
         """
         Calculates the profit as ratio (including fee).
-        :param rate: rate to compare with (optional).
-            If rate is not set self.close_rate will be used
-        :param fee: fee to use on the close rate (optional).
-        :param interest_rate: interest_charge for borrowing this coin (optional).
-            If interest_rate is not set self.interest_rate will be used
+        :param rate: rate to compare with.
+        :param amount: Amount to use for the calculation. Falls back to trade.amount if not set.
+        :param open_rate: open_rate to use. Defaults to self.open_rate if not provided.
         :return: profit ratio as float
         """
-        close_trade_value = self.calc_close_trade_value(
-            rate=(rate or self.close_rate),
-            fee=(fee or self.fee_close),
-            interest_rate=(interest_rate or self.interest_rate)
-        )
+        close_trade_value = self.calc_close_trade_value(rate, amount)
+
+        if amount is None or open_rate is None:
+            open_trade_value = self.open_trade_value
+        else:
+            open_trade_value = self._calc_open_trade_value(amount, open_rate)
 
         short_close_zero = (self.is_short and close_trade_value == 0.0)
-        long_close_zero = (not self.is_short and self.open_trade_value == 0.0)
+        long_close_zero = (not self.is_short and open_trade_value == 0.0)
         leverage = self.leverage or 1.0
 
         if (short_close_zero or long_close_zero):
             return 0.0
         else:
             if self.is_short:
-                profit_ratio = (1 - (close_trade_value / self.open_trade_value)) * leverage
+                profit_ratio = (1 - (close_trade_value / open_trade_value)) * leverage
             else:
-                profit_ratio = ((close_trade_value / self.open_trade_value) - 1) * leverage
+                profit_ratio = ((close_trade_value / open_trade_value) - 1) * leverage
 
         return float(f"{profit_ratio:.8f}")
 

freqtrade/rpc/api_server/api_backtest.py

@@ -1,6 +1,7 @@
 import asyncio
 import logging
 from copy import deepcopy
+from datetime import datetime
 from typing import Any, Dict, List
 
 from fastapi import APIRouter, BackgroundTasks, Depends
@@ -102,7 +103,10 @@ async def api_start_backtest(bt_settings: BacktestRequest, background_tasks: Bac
                     min_date=min_date, max_date=max_date)
 
             if btconfig.get('export', 'none') == 'trades':
-                store_backtest_stats(btconfig['exportfilename'], ApiServer._bt.results)
+                store_backtest_stats(
+                    btconfig['exportfilename'], ApiServer._bt.results,
+                    datetime.now().strftime("%Y-%m-%d_%H-%M-%S")
+                    )
 
             logger.info("Backtest finished.")
 

freqtrade/rpc/rpc.py

@@ -512,7 +512,7 @@ class RPC:
 
     def _rpc_balance(self, stake_currency: str, fiat_display_currency: str) -> Dict:
         """ Returns current account balance per crypto """
-        currencies = []
+        currencies: List[Dict] = []
         total = 0.0
         try:
             tickers = self._freqtrade.exchange.get_tickers(cached=True)
@@ -547,13 +547,12 @@ class RPC:
                 except (ExchangeError):
                     logger.warning(f" Could not get rate for pair {coin}.")
                     continue
-            total = total + (est_stake or 0)
+            total = total + est_stake
             currencies.append({
                 'currency': coin,
-                # TODO: The below can be simplified if we don't assign None to values.
-                'free': balance.free if balance.free is not None else 0,
-                'balance': balance.total if balance.total is not None else 0,
-                'used': balance.used if balance.used is not None else 0,
+                'free': balance.free,
+                'balance': balance.total,
+                'used': balance.used,
                 'est_stake': est_stake or 0,
                 'stake': stake_currency,
                 'side': 'long',
@@ -583,7 +582,6 @@ class RPC:
             total, stake_currency, fiat_display_currency) if self._fiat_converter else 0
 
         trade_count = len(Trade.get_trades_proxy())
-        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
 
@@ -871,7 +869,7 @@ class RPC:
             else:
                 errors[pair] = {
                     'error_msg': f"Pair {pair} is not in the current blacklist."
-                    }
+                }
         resp = self._rpc_blacklist()
         resp['errors'] = errors
         return resp