diff --git a/quantstats_lumi/_plotting/core.py b/quantstats_lumi/_plotting/core.py
index 1dee056..5f52a14 100644
--- a/quantstats_lumi/_plotting/core.py
+++ b/quantstats_lumi/_plotting/core.py
@@ -354,6 +354,14 @@ def plot_timeseries(
_plt.yscale("symlog" if log_scale else "linear")
+ # Set y-axis limits to avoid blank space at the bottom and top
+ min_val = returns.min()
+ max_val = returns.max()
+ if benchmark is not None:
+ min_val = min(min_val, benchmark.min())
+ max_val = max(max_val, benchmark.max())
+ ax.set_ylim(bottom=min_val, top=max_val)
+
if percent:
ax.yaxis.set_major_formatter(_FuncFormatter(format_pct_axis))
# ax.yaxis.set_major_formatter(_plt.FuncFormatter(
@@ -940,6 +948,10 @@ def plot_longest_drawdowns(
ax.axhline(0, ls="--", lw=1, color="#000000", zorder=2)
_plt.yscale("symlog" if log_scale else "linear")
+
+ # Set y-axis limits to avoid blank space at the bottom and top
+ ax.set_ylim(bottom=series.min(), top=series.max())
+
if ylabel:
ax.set_ylabel(
"Cumulative Returns",
@@ -994,6 +1006,7 @@ def plot_distribution(
title=None,
savefig=None,
show=True,
+ log_scale=False,
):
colors = _FLATUI_COLORS
if grayscale:
@@ -1057,6 +1070,7 @@ def plot_distribution(
},
)
+ _plt.yscale("symlog" if log_scale else "linear")
ax.yaxis.set_major_formatter(
_plt.FuncFormatter(lambda x, loc: "{:,}%".format(int(x * 100)))
)
diff --git a/quantstats_lumi/_plotting/wrappers.py b/quantstats_lumi/_plotting/wrappers.py
index 3f85f7d..c8108b2 100644
--- a/quantstats_lumi/_plotting/wrappers.py
+++ b/quantstats_lumi/_plotting/wrappers.py
@@ -589,6 +589,7 @@ def distribution(
show=True,
title=None,
prepare_returns=True,
+ log_scale=True,
):
if prepare_returns:
returns = _utils._prepare_returns(returns)
@@ -604,6 +605,7 @@ def distribution(
compounded=compounded,
savefig=savefig,
show=show,
+ log_scale=log_scale,
)
if not show:
return fig
diff --git a/quantstats_lumi/reports.py b/quantstats_lumi/reports.py
index ce072c6..93bca3b 100644
--- a/quantstats_lumi/reports.py
+++ b/quantstats_lumi/reports.py
@@ -190,7 +190,7 @@ def html(
tpl = tpl.replace("{{metrics}}", _html_table(mtrx))
# Add all of the summary metrics
-
+
# CAGR #
# Get the value of the "Strategy" column where the "Metric" column is "CAGR% (Annual Return)"
cagr = mtrx.loc["CAGR% (Annual Return)", strategy_title]
@@ -209,7 +209,7 @@ def html(
max_drawdown = mtrx.loc["Max Drawdown", strategy_title]
# Add the max drawdown to the template
tpl = tpl.replace("{{max_drawdown}}", max_drawdown)
-
+
# RoMaD #
# Get the value of the "Strategy" column where the "Mteric" column is "RoMaD"
romad = mtrx.loc["RoMaD", strategy_title]
@@ -331,7 +331,7 @@ def html(
if benchmark is not None:
figfile = _utils._file_stream()
- _plots.returns(
+ _plots.log_returns(
returns,
benchmark,
match_volatility=True,
@@ -464,6 +464,7 @@ def html(
ylabel=False,
compounded=compounded,
prepare_returns=False,
+ log_scale=True,
)
tpl = tpl.replace("{{dd_periods}}", _embed_figure(figfile, figfmt))
elif isinstance(returns, _pd.DataFrame):
@@ -831,7 +832,7 @@ def parameters_section(parameters):
# Make sure that the value is something that can be displayed
if not isinstance(value, (int, float, str)):
value = str(value)
-
+
tpl += f"| {key} | {value} |
"
tpl += """
@@ -960,7 +961,7 @@ def metrics(
metrics["Sharpe"] = _stats.sharpe(df, rf, win_year, True)
metrics["RoMaD"] = _stats.romad(df, win_year, True)
-
+
if benchmark is not None:
metrics["Corr to Benchmark "] = _stats.benchmark_correlation(df, benchmark, True)
metrics["Prob. Sharpe Ratio %"] = (
diff --git a/report.html b/report.html
index cbfba46..6a64013 100644
--- a/report.html
+++ b/report.html
@@ -281,7 +281,7 @@
Strategy Tearsheet 31 Jan, 2022 - 31 May, 2022
-