mirror of
https://github.com/freqtrade/freqtrade.git
synced 2024-09-20 01:21:11 +00:00
chore: ruff format notebook
This commit is contained in:
parent
d2c908b1ab
commit
ce66fbb595
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@ -18,13 +18,13 @@ from pathlib import Path
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# Modify this cell to insure that the output shows the correct path.
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# Define all paths relative to the project root shown in the cell output
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project_root = "somedir/freqtrade"
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i=0
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i = 0
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try:
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os.chdir(project_root)
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if not Path('LICENSE').is_file():
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if not Path("LICENSE").is_file():
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i = 0
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while i < 4 and (not Path('LICENSE').is_file()):
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os.chdir(Path(Path.cwd(), '../'))
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while i < 4 and (not Path("LICENSE").is_file()):
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os.chdir(Path(Path.cwd(), "../"))
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i += 1
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project_root = Path.cwd()
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except FileNotFoundError:
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@ -63,12 +63,13 @@ from freqtrade.data.history import load_pair_history
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from freqtrade.enums import CandleType
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candles = load_pair_history(datadir=data_location,
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timeframe=config["timeframe"],
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pair=pair,
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data_format = "json", # Make sure to update this to your data
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candle_type=CandleType.SPOT,
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)
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candles = load_pair_history(
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datadir=data_location,
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timeframe=config["timeframe"],
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pair=pair,
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data_format="json", # Make sure to update this to your data
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candle_type=CandleType.SPOT,
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)
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# Confirm success
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print(f"Loaded {len(candles)} rows of data for {pair} from {data_location}")
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@ -90,7 +91,7 @@ strategy.dp = DataProvider(config, None, None)
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strategy.ft_bot_start()
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# Generate buy/sell signals using strategy
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df = strategy.analyze_ticker(candles, {'pair': pair})
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df = strategy.analyze_ticker(candles, {"pair": pair})
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df.tail()
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```
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@ -109,7 +110,7 @@ df.tail()
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```python
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# Report results
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print(f"Generated {df['enter_long'].sum()} entry signals")
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data = df.set_index('date', drop=False)
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data = df.set_index("date", drop=False)
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data.tail()
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```
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@ -141,25 +142,24 @@ backtest_dir = config["user_data_dir"] / "backtest_results"
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# This contains all information used to generate the backtest result.
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stats = load_backtest_stats(backtest_dir)
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strategy = 'SampleStrategy'
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strategy = "SampleStrategy"
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# All statistics are available per strategy, so if `--strategy-list` was used during backtest,
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# this will be reflected here as well.
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# Example usages:
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print(stats['strategy'][strategy]['results_per_pair'])
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print(stats["strategy"][strategy]["results_per_pair"])
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# Get pairlist used for this backtest
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print(stats['strategy'][strategy]['pairlist'])
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print(stats["strategy"][strategy]["pairlist"])
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# Get market change (average change of all pairs from start to end of the backtest period)
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print(stats['strategy'][strategy]['market_change'])
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print(stats["strategy"][strategy]["market_change"])
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# Maximum drawdown ()
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print(stats['strategy'][strategy]['max_drawdown'])
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print(stats["strategy"][strategy]["max_drawdown"])
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# Maximum drawdown start and end
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print(stats['strategy'][strategy]['drawdown_start'])
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print(stats['strategy'][strategy]['drawdown_end'])
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print(stats["strategy"][strategy]["drawdown_start"])
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print(stats["strategy"][strategy]["drawdown_end"])
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# Get strategy comparison (only relevant if multiple strategies were compared)
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print(stats['strategy_comparison'])
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print(stats["strategy_comparison"])
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```
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@ -189,14 +189,13 @@ from freqtrade.data.btanalysis import load_backtest_stats
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# backtest_dir = config["user_data_dir"] / "backtest_results"
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stats = load_backtest_stats(backtest_dir)
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strategy_stats = stats['strategy'][strategy]
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strategy_stats = stats["strategy"][strategy]
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df = pd.DataFrame(columns=['dates','equity'], data=strategy_stats['daily_profit'])
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df['equity_daily'] = df['equity'].cumsum()
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df = pd.DataFrame(columns=["dates", "equity"], data=strategy_stats["daily_profit"])
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df["equity_daily"] = df["equity"].cumsum()
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fig = px.line(df, x="dates", y="equity_daily")
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fig.show()
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```
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### Load live trading results into a pandas dataframe
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@ -226,7 +225,7 @@ from freqtrade.data.btanalysis import analyze_trade_parallelism
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# Analyze the above
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parallel_trades = analyze_trade_parallelism(trades, '5m')
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parallel_trades = analyze_trade_parallelism(trades, "5m")
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parallel_trades.plot()
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```
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@ -243,19 +242,17 @@ from freqtrade.plot.plotting import generate_candlestick_graph
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# Limit graph period to keep plotly quick and reactive
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# Filter trades to one pair
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trades_red = trades.loc[trades['pair'] == pair]
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trades_red = trades.loc[trades["pair"] == pair]
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data_red = data['2019-06-01':'2019-06-10']
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data_red = data["2019-06-01":"2019-06-10"]
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# Generate candlestick graph
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graph = generate_candlestick_graph(pair=pair,
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data=data_red,
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trades=trades_red,
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indicators1=['sma20', 'ema50', 'ema55'],
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indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']
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)
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graph = generate_candlestick_graph(
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pair=pair,
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data=data_red,
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trades=trades_red,
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indicators1=["sma20", "ema50", "ema55"],
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indicators2=["rsi", "macd", "macdsignal", "macdhist"],
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)
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```
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@ -265,7 +262,6 @@ graph = generate_candlestick_graph(pair=pair,
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# Render graph in a separate window
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graph.show(renderer="browser")
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```
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## Plot average profit per trade as distribution graph
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@ -276,11 +272,10 @@ import plotly.figure_factory as ff
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hist_data = [trades.profit_ratio]
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group_labels = ['profit_ratio'] # name of the dataset
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group_labels = ["profit_ratio"] # name of the dataset
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fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)
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fig.show()
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```
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Feel free to submit an issue or Pull Request enhancing this document if you would like to share ideas on how to best analyze the data.
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@ -34,13 +34,13 @@
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"# Modify this cell to insure that the output shows the correct path.\n",
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"# Define all paths relative to the project root shown in the cell output\n",
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"project_root = \"somedir/freqtrade\"\n",
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"i=0\n",
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"i = 0\n",
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"try:\n",
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" os.chdir(project_root)\n",
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" if not Path('LICENSE').is_file():\n",
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" if not Path(\"LICENSE\").is_file():\n",
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" i = 0\n",
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" while i < 4 and (not Path('LICENSE').is_file()):\n",
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" os.chdir(Path(Path.cwd(), '../'))\n",
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" while i < 4 and (not Path(\"LICENSE\").is_file()):\n",
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" os.chdir(Path(Path.cwd(), \"../\"))\n",
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" i += 1\n",
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" project_root = Path.cwd()\n",
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"except FileNotFoundError:\n",
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@ -92,12 +92,13 @@
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"from freqtrade.enums import CandleType\n",
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"\n",
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"\n",
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"candles = load_pair_history(datadir=data_location,\n",
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" timeframe=config[\"timeframe\"],\n",
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" pair=pair,\n",
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" data_format = \"json\", # Make sure to update this to your data\n",
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" candle_type=CandleType.SPOT,\n",
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" )\n",
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"candles = load_pair_history(\n",
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" datadir=data_location,\n",
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" timeframe=config[\"timeframe\"],\n",
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" pair=pair,\n",
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" data_format=\"json\", # Make sure to update this to your data\n",
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" candle_type=CandleType.SPOT,\n",
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")\n",
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"\n",
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"# Confirm success\n",
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"print(f\"Loaded {len(candles)} rows of data for {pair} from {data_location}\")\n",
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@ -128,7 +129,7 @@
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"strategy.ft_bot_start()\n",
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"\n",
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"# Generate buy/sell signals using strategy\n",
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"df = strategy.analyze_ticker(candles, {'pair': pair})\n",
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"df = strategy.analyze_ticker(candles, {\"pair\": pair})\n",
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"df.tail()"
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]
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},
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@ -155,7 +156,7 @@
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"source": [
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"# Report results\n",
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"print(f\"Generated {df['enter_long'].sum()} entry signals\")\n",
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"data = df.set_index('date', drop=False)\n",
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"data = df.set_index(\"date\", drop=False)\n",
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"data.tail()"
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]
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},
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@ -205,24 +206,24 @@
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"# This contains all information used to generate the backtest result.\n",
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"stats = load_backtest_stats(backtest_dir)\n",
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"\n",
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"strategy = 'SampleStrategy'\n",
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"strategy = \"SampleStrategy\"\n",
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"# All statistics are available per strategy, so if `--strategy-list` was used during backtest,\n",
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"# this will be reflected here as well.\n",
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"# Example usages:\n",
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"print(stats['strategy'][strategy]['results_per_pair'])\n",
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"print(stats[\"strategy\"][strategy][\"results_per_pair\"])\n",
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"# Get pairlist used for this backtest\n",
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"print(stats['strategy'][strategy]['pairlist'])\n",
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"print(stats[\"strategy\"][strategy][\"pairlist\"])\n",
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"# Get market change (average change of all pairs from start to end of the backtest period)\n",
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"print(stats['strategy'][strategy]['market_change'])\n",
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"print(stats[\"strategy\"][strategy][\"market_change\"])\n",
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"# Maximum drawdown ()\n",
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"print(stats['strategy'][strategy]['max_drawdown'])\n",
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"print(stats[\"strategy\"][strategy][\"max_drawdown\"])\n",
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"# Maximum drawdown start and end\n",
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"print(stats['strategy'][strategy]['drawdown_start'])\n",
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"print(stats['strategy'][strategy]['drawdown_end'])\n",
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"print(stats[\"strategy\"][strategy][\"drawdown_start\"])\n",
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"print(stats[\"strategy\"][strategy][\"drawdown_end\"])\n",
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"\n",
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"\n",
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"# Get strategy comparison (only relevant if multiple strategies were compared)\n",
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"print(stats['strategy_comparison'])\n"
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"print(stats[\"strategy_comparison\"])"
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]
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},
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{
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@ -265,13 +266,13 @@
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"# backtest_dir = config[\"user_data_dir\"] / \"backtest_results\"\n",
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"\n",
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"stats = load_backtest_stats(backtest_dir)\n",
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"strategy_stats = stats['strategy'][strategy]\n",
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"strategy_stats = stats[\"strategy\"][strategy]\n",
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"\n",
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"df = pd.DataFrame(columns=['dates','equity'], data=strategy_stats['daily_profit'])\n",
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"df['equity_daily'] = df['equity'].cumsum()\n",
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"df = pd.DataFrame(columns=[\"dates\", \"equity\"], data=strategy_stats[\"daily_profit\"])\n",
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"df[\"equity_daily\"] = df[\"equity\"].cumsum()\n",
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"\n",
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"fig = px.line(df, x=\"dates\", y=\"equity_daily\")\n",
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"fig.show()\n"
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"fig.show()"
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]
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},
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{
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@ -319,7 +320,7 @@
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"\n",
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"\n",
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"# Analyze the above\n",
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"parallel_trades = analyze_trade_parallelism(trades, '5m')\n",
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"parallel_trades = analyze_trade_parallelism(trades, \"5m\")\n",
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"\n",
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"parallel_trades.plot()"
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]
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@ -345,18 +346,17 @@
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"# Limit graph period to keep plotly quick and reactive\n",
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"\n",
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"# Filter trades to one pair\n",
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"trades_red = trades.loc[trades['pair'] == pair]\n",
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"trades_red = trades.loc[trades[\"pair\"] == pair]\n",
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"\n",
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"data_red = data['2019-06-01':'2019-06-10']\n",
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"data_red = data[\"2019-06-01\":\"2019-06-10\"]\n",
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"# Generate candlestick graph\n",
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"graph = generate_candlestick_graph(pair=pair,\n",
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" data=data_red,\n",
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" trades=trades_red,\n",
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" indicators1=['sma20', 'ema50', 'ema55'],\n",
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" indicators2=['rsi', 'macd', 'macdsignal', 'macdhist']\n",
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" )\n",
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"\n",
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"\n"
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"graph = generate_candlestick_graph(\n",
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" pair=pair,\n",
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" data=data_red,\n",
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" trades=trades_red,\n",
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" indicators1=[\"sma20\", \"ema50\", \"ema55\"],\n",
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" indicators2=[\"rsi\", \"macd\", \"macdsignal\", \"macdhist\"],\n",
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")"
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]
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},
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{
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@ -369,7 +369,7 @@
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"# graph.show()\n",
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"\n",
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"# Render graph in a separate window\n",
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"graph.show(renderer=\"browser\")\n"
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"graph.show(renderer=\"browser\")"
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]
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},
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{
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@ -389,10 +389,10 @@
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"\n",
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"\n",
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"hist_data = [trades.profit_ratio]\n",
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"group_labels = ['profit_ratio'] # name of the dataset\n",
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"group_labels = [\"profit_ratio\"] # name of the dataset\n",
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"\n",
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"fig = ff.create_distplot(hist_data, group_labels, bin_size=0.01)\n",
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"fig.show()\n"
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"fig.show()"
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]
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},
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{
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