diff --git a/docs/plotting.md b/docs/plotting.md
index ecd5e1603..3eef8f8e7 100644
--- a/docs/plotting.md
+++ b/docs/plotting.md
@@ -196,6 +196,7 @@ The first graph is good to get a grip of how the overall market progresses.
 
 The second graph will show if your algorithm works or doesn't.
 Perhaps you want an algorithm that steadily makes small profits, or one that acts less often, but makes big swings.
+This graph will also highlight the start (and end) of the Max drawdown period.
 
 The third graph can be useful to spot outliers, events in pairs that cause profit spikes.
 
diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py
index 394c40112..7972c6333 100644
--- a/freqtrade/data/btanalysis.py
+++ b/freqtrade/data/btanalysis.py
@@ -190,7 +190,7 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str,
     return df
 
 
-def calculate_max_drawdown(trades: pd.DataFrame, date_col: str = 'close_time',
+def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_time',
                            value_col: str = 'profitperc'
                            ) -> Tuple[float, pd.Timestamp, pd.Timestamp]:
     """
diff --git a/freqtrade/plot/plotting.py b/freqtrade/plot/plotting.py
index 2ce4f1501..d979a40e0 100644
--- a/freqtrade/plot/plotting.py
+++ b/freqtrade/plot/plotting.py
@@ -126,8 +126,8 @@ def add_max_drawdown(fig, row, trades: pd.DataFrame, df_comb: pd.DataFrame) -> m
                 df_comb.loc[lowdate, 'cum_profit'],
             ],
             mode='markers',
-            name='Max Drawdown',
-            text=f"Max drawdown {max_drawdown}",
+            name=f"Max drawdown {max_drawdown:.2f}%",
+            text=f"Max drawdown {max_drawdown:.2f}%",
             marker=dict(
                 symbol='square-open',
                 size=9,
diff --git a/tests/test_plotting.py b/tests/test_plotting.py
index 34d1f2b0c..dd04035b7 100644
--- a/tests/test_plotting.py
+++ b/tests/test_plotting.py
@@ -3,15 +3,16 @@ from copy import deepcopy
 from pathlib import Path
 from unittest.mock import MagicMock
 
+import pandas as pd
 import plotly.graph_objects as go
 import pytest
 from plotly.subplots import make_subplots
 
+from freqtrade.commands import start_plot_dataframe, start_plot_profit
 from freqtrade.configuration import TimeRange
 from freqtrade.data import history
 from freqtrade.data.btanalysis import create_cum_profit, load_backtest_data
 from freqtrade.exceptions import OperationalException
-from freqtrade.commands import start_plot_dataframe, start_plot_profit
 from freqtrade.plot.plotting import (add_indicators, add_profit,
                                      create_plotconfig,
                                      generate_candlestick_graph,
@@ -266,6 +267,7 @@ def test_generate_profit_graph(testdatadir):
     trades = load_backtest_data(filename)
     timerange = TimeRange.parse_timerange("20180110-20180112")
     pairs = ["TRX/BTC", "ADA/BTC"]
+    trades = trades[trades['close_time'] < pd.Timestamp('2018-01-12', tz='UTC')]
 
     tickers = history.load_data(datadir=testdatadir,
                                 pairs=pairs,
@@ -283,13 +285,15 @@ def test_generate_profit_graph(testdatadir):
     assert fig.layout.yaxis3.title.text == "Profit"
 
     figure = fig.layout.figure
-    assert len(figure.data) == 4
+    assert len(figure.data) == 5
 
     avgclose = find_trace_in_fig_data(figure.data, "Avg close price")
     assert isinstance(avgclose, go.Scatter)
 
     profit = find_trace_in_fig_data(figure.data, "Profit")
     assert isinstance(profit, go.Scatter)
+    profit = find_trace_in_fig_data(figure.data, "Max drawdown 0.00%")
+    assert isinstance(profit, go.Scatter)
 
     for pair in pairs:
         profit_pair = find_trace_in_fig_data(figure.data, f"Profit {pair}")