sell-signal -> exit_signal

docs/backtesting.md

@@ -477,7 +477,7 @@ Since backtesting lacks some detailed information about what happens within a ca
 - Buys happen at open-price
 - All orders are filled at the requested price (no slippage, no unfilled orders)
 - Sell-signal sells happen at open-price of the consecutive candle
-- Sell-signal is favored over Stoploss, because sell-signals are assumed to trigger on candle's open
+- Sell-signal is favored over Stoploss, because exit-signals are assumed to trigger on candle's open
 - ROI
   - sells are compared to high - but the ROI value is used (e.g. ROI = 2%, high=5% - so the sell will be at 2%)
   - sells are never "below the candle", so a ROI of 2% may result in a sell at 2.4% if low was at 2.4% profit

docs/bot-basics.md

@@ -35,7 +35,7 @@ By default, loop runs every few seconds (`internals.process_throttle_secs`) and
   * Calls `check_buy_timeout()` strategy callback for open buy orders.
   * Calls `check_sell_timeout()` strategy callback for open sell orders.
 * Verifies existing positions and eventually places sell orders.
-  * Considers stoploss, ROI and sell-signal, `custom_exit()` and `custom_stoploss()`.
+  * Considers stoploss, ROI and exit-signal, `custom_exit()` and `custom_stoploss()`.
   * Determine sell-price based on `ask_strategy` configuration setting or by using the `custom_exit_price()` callback.
   * Before a sell order is placed, `confirm_trade_exit()` strategy callback is called.
 * Check if trade-slots are still available (if `max_open_trades` is reached).
@@ -60,7 +60,7 @@ This loop will be repeated again and again until the bot is stopped.
   * Call `custom_entry_price()` (if implemented in the strategy) to determine entry price (Prices are moved to be within the opening candle).
   * Determine stake size by calling the `custom_stake_amount()` callback.
   * Call `custom_stoploss()` and `custom_exit()` to find custom exit points.
-  * For sells based on sell-signal and custom-sell: Call `custom_exit_price()` to determine exit price (Prices are moved to be within the closing candle).
+  * For sells based on exit-signal and custom-sell: Call `custom_exit_price()` to determine exit price (Prices are moved to be within the closing candle).
 
 * Generate backtest report output
 

docs/configuration.md

@@ -333,7 +333,7 @@ If it is not set in either Strategy or Configuration, a default of 1000% `{"0":
 
 The `forcebuy_enable` configuration parameter enables the usage of forcebuy commands via Telegram and REST API.
 For security reasons, it's disabled by default, and freqtrade will show a warning message on startup if enabled.
-For example, you can send `/forcebuy ETH/BTC` to the bot, which will result in freqtrade buying the pair and holds it until a regular sell-signal (ROI, stoploss, /forcesell) appears.
+For example, you can send `/forcebuy ETH/BTC` to the bot, which will result in freqtrade buying the pair and holds it until a regular exit-signal (ROI, stoploss, /forcesell) appears.
 
 This can be dangerous with some strategies, so use with care.
 

docs/hyperopt.md

@@ -206,7 +206,7 @@ Hyper-optimization will, for each epoch round, pick one trigger and possibly mul
 
 #### Sell optimization
 
-Similar to the buy-signal above, sell-signals can also be optimized.
+Similar to the buy-signal above, exit-signals can also be optimized.
 Place the corresponding settings into the following methods
 
 * Define the parameters at the class level hyperopt shall be optimizing, either naming them `sell_*`, or by explicitly defining `space='sell'`.

docs/strategy-callbacks.md

@@ -9,7 +9,7 @@ Currently available callbacks:
 
 * [`bot_loop_start()`](#bot-loop-start)
 * [`custom_stake_amount()`](#custom-stake-size)
-* [`custom_exit()`](#custom-sell-signal)
+* [`custom_exit()`](#custom-exit-signal)
 * [`custom_stoploss()`](#custom-stoploss)
 * [`custom_entry_price()` and `custom_exit_price()`](#custom-order-price-rules)
 * [`check_buy_timeout()` and `check_sell_timeout()](#custom-order-timeout-rules)

docs/strategy-customization.md

@@ -235,7 +235,7 @@ def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
 ### Sell signal rules
 
 Edit the method `populate_sell_trend()` into your strategy file to update your sell strategy.
-Please note that the sell-signal is only used if `use_exit_signal` is set to true in the configuration.
+Please note that the exit-signal is only used if `use_exit_signal` is set to true in the configuration.
 
 It's important to always return the dataframe without removing/modifying the columns `"open", "high", "low", "close", "volume"`, otherwise these fields would contain something unexpected.
 

freqtrade/optimize/backtesting.py

@@ -396,7 +396,7 @@ class Backtesting:
             # call the custom exit price,with default value as previous closerate
             current_profit = trade.calc_profit_ratio(closerate)
             if sell.exit_type in (ExitType.EXIT_SIGNAL, ExitType.CUSTOM_EXIT):
-                # Custom exit pricing only for sell-signals
+                # Custom exit pricing only for exit-signals
                 closerate = strategy_safe_wrapper(self.strategy.custom_exit_price,
                                                   default_retval=closerate)(
                     pair=trade.pair, trade=trade,

freqtrade/plot/plotting.py

@@ -466,7 +466,7 @@ def generate_candlestick_graph(pair: str, data: pd.DataFrame, trades: pd.DataFra
             )
             fig.add_trace(sells, 1, 1)
         else:
-            logger.warning("No sell-signals found.")
+            logger.warning("No exit-signals found.")
     # Add Bollinger Bands
     fig = plot_area(fig, 1, data, 'bb_lowerband', 'bb_upperband',
                     label="Bollinger Band")

tests/optimize/test_backtest_detail.py

@@ -381,7 +381,7 @@ tc23 = BTContainer(data=[
 
 # Test 24: Sell with signal sell in candle 3 (stoploss also triggers on this candle)
 # Stoploss at 1%.
-# Stoploss wins over Sell-signal (because sell-signal is acted on in the next candle)
+# Stoploss wins over Sell-signal (because exit-signal is acted on in the next candle)
 tc24 = BTContainer(data=[
     # D  O     H     L     C     V    B  S
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
@@ -417,7 +417,7 @@ tc26 = BTContainer(data=[
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
     [2, 4987, 5012, 4986, 4986, 6172, 0, 0],
-    [3, 5010, 5251, 4986, 5010, 6172, 0, 1],  # Triggers ROI, sell-signal
+    [3, 5010, 5251, 4986, 5010, 6172, 0, 1],  # Triggers ROI, exit-signal
     [4, 5010, 5010, 4855, 4995, 6172, 0, 0],
     [5, 4995, 4995, 4950, 4950, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.05}, profit_perc=0.05, use_exit_signal=True,
@@ -431,8 +431,8 @@ tc27 = BTContainer(data=[
     [0, 5000, 5025, 4975, 4987, 6172, 1, 0],
     [1, 5000, 5025, 4975, 4987, 6172, 0, 0],  # enter trade (signal on last candle)
     [2, 4987, 5012, 4986, 4986, 6172, 0, 0],
-    [3, 5010, 5012, 4986, 5010, 6172, 0, 1],  # sell-signal
-    [4, 5010, 5251, 4855, 4995, 6172, 0, 0],  # Triggers ROI, sell-signal acted on
+    [3, 5010, 5012, 4986, 5010, 6172, 0, 1],  # exit-signal
+    [4, 5010, 5251, 4855, 4995, 6172, 0, 0],  # Triggers ROI, exit-signal acted on
     [5, 4995, 4995, 4950, 4950, 6172, 0, 0]],
     stop_loss=-0.10, roi={"0": 0.05}, profit_perc=0.002, use_exit_signal=True,
     trades=[BTrade(exit_reason=ExitType.EXIT_SIGNAL, open_tick=1, close_tick=4)]

tests/test_integration.py

@@ -16,7 +16,7 @@ def test_may_execute_exit_stoploss_on_exchange_multi(default_conf, ticker, fee,
     Sells
     * first trade as stoploss
     * 2nd trade is kept
-    * 3rd trade is sold via sell-signal
+    * 3rd trade is sold via exit-signal
     """
     default_conf['max_open_trades'] = 3
     default_conf['exchange']['name'] = 'binance'

tests/test_plotting.py

@@ -223,7 +223,7 @@ def test_generate_candlestick_graph_no_signals_no_trades(default_conf, mocker, t
     assert trades_mock.call_count == 1
 
     assert log_has("No buy-signals found.", caplog)
-    assert log_has("No sell-signals found.", caplog)
+    assert log_has("No exit-signals found.", caplog)
 
 
 def test_generate_candlestick_graph_no_trades(default_conf, mocker, testdatadir):