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Multi-strategy reports
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@ranaroussi
ranaroussi committed Jun 22, 2023
1 parent 3b9ad16 commit 52fcc4e
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Showing 4 changed files with 222 additions and 123 deletions.
171 changes: 109 additions & 62 deletions quantstats/_plotting/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -50,9 50,10 @@
'ytick.color': '#666666'
})

_FLATUI_COLORS = ["#fedd78", "#348dc1", "#af4b64",
"#4fa487", "#9b59b6", "#808080"]
_GRAYSCALE_COLORS = ['silver', '#222222', 'gray'] * 3
_FLATUI_COLORS = ['#FEDD78', '#348DC1', '#BA516B', '#4FA487', '#9B59B6',
'#613F66', '#84B082', '#DC136C', '#559CAD', '#4A5899']
_GRAYSCALE_COLORS = ['#000000', '#222222', '#555555', '#888888', '#AAAAAA',
'#CCCCCC', '#EEEEEE', '#333333', '#666666', '#999999']


def _get_colors(grayscale):
Expand Down Expand Up @@ -108,11 109,11 @@ def plot_returns_bars(returns, benchmark=None,
ax.spines['left'].set_visible(False)

# use a more precise date string for the x axis locations in the toolbar
fig.suptitle(title "\n", y=.99, fontweight="bold", fontname=fontname,
fig.suptitle(title, y=.94, fontweight="bold", fontname=fontname,
fontsize=14, color="black")

if subtitle:
ax.set_title("\n%s - %s " % (
ax.set_title("%s - %s \n" % (
df.index.date[:1][0].strftime('%Y'),
df.index.date[-1:][0].strftime('%Y')
), fontsize=12, color='gray')
Expand Down Expand Up @@ -151,7 152,7 @@ def plot_returns_bars(returns, benchmark=None,
ax.axhline(0, ls="--", lw=1, color="#000000", zorder=2)

# if isinstance(benchmark, _pd.Series) or hline:
ax.legend(fontsize=12)
ax.legend(fontsize=11)

_plt.yscale("symlog" if log_scale else "linear")

Expand All @@ -163,6 164,9 @@ def plot_returns_bars(returns, benchmark=None,

ax.yaxis.set_major_formatter(_FuncFormatter(format_pct_axis))

if benchmark is None and len(_pd.DataFrame(returns).columns) == 1:
ax.get_legend().remove()

try:
_plt.subplots_adjust(hspace=0, bottom=0, top=1)
except Exception:
Expand Down Expand Up @@ -238,11 242,11 @@ def plot_timeseries(returns, benchmark=None,
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)

fig.suptitle(title "\n", y=.99, fontweight="bold", fontname=fontname,
fig.suptitle(title, y=.94, fontweight="bold", fontname=fontname,
fontsize=14, color="black")

if subtitle:
ax.set_title("\n%s - %s " % (
ax.set_title("%s - %s \n" % (
returns.index.date[:1][0].strftime('%e %b \'%y'),
returns.index.date[-1:][0].strftime('%e %b \'%y')
), fontsize=12, color='gray')
Expand All @@ -258,8 262,8 @@ def plot_timeseries(returns, benchmark=None,
ax.plot(returns, lw=lw, label=returns.name, color=colors[1], alpha=alpha)
elif isinstance(returns, _pd.DataFrame):
# color_dict = {col: colors[i 1] for i, col in enumerate(returns.columns)}
for col in returns.columns:
ax.plot(returns[col], lw=lw, label=col, alpha=alpha)
for i, col in enumerate(returns.columns):
ax.plot(returns[col], lw=lw, label=col, alpha=alpha, color=colors[i 1])

if fill:
if isinstance(returns, _pd.Series):
Expand Down Expand Up @@ -287,8 291,7 @@ def plot_timeseries(returns, benchmark=None,
color='white' if grayscale else 'black', zorder=2)

# if isinstance(benchmark, _pd.Series) or hline is not None:
# ax.legend(fontsize=12)
ax.legend(fontsize=12)
ax.legend(fontsize=11)

_plt.yscale("symlog" if log_scale else "linear")

Expand All @@ -303,6 306,9 @@ def plot_timeseries(returns, benchmark=None,
fontweight='bold', fontsize=12, color="black")
ax.yaxis.set_label_coords(-.1, .5)

if benchmark is None and len(_pd.DataFrame(returns).columns) == 1:
ax.get_legend().remove()

try:
_plt.subplots_adjust(hspace=0, bottom=0, top=1)
except Exception:
Expand Down Expand Up @@ -336,9 342,11 @@ def plot_histogram(returns, benchmark, resample="M", bins=20,
ylabel=True, subtitle=True, compounded=True,
savefig=None, show=True):

colors = ['#348dc1', '#003366', 'red']
if grayscale:
colors = ['silver', 'gray', 'black']
# colors = ['#348dc1', '#003366', 'red']
# if grayscale:
# colors = ['silver', 'gray', 'black']

colors, _, _ = _get_colors(grayscale)

apply_fnc = _stats.comp if compounded else _np.sum
if benchmark is not None:
Expand All @@ -348,58 356,80 @@ def plot_histogram(returns, benchmark, resample="M", bins=20,
returns = returns.fillna(0).resample(resample).apply(
apply_fnc).resample(resample).last()

figsize = (0.995 * figsize[0], figsize[1])
fig, ax = _plt.subplots(figsize=figsize)

ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)

fig.suptitle(title "\n", y=.99, fontweight="bold", fontname=fontname,
fig.suptitle(title, y=.94, fontweight="bold", fontname=fontname,
fontsize=14, color="black")

if subtitle:
ax.set_title("\n%s - %s " % (
ax.set_title("%s - %s \n" % (
returns.index.date[:1][0].strftime('%Y'),
returns.index.date[-1:][0].strftime('%Y')
), fontsize=12, color='gray')

fig.set_facecolor('white')
ax.set_facecolor('white')

# Why do we need average?
# ax.axvline(returns.mean(), ls="--", lw=1.5,
# zorder=2, label="Average")
if isinstance(returns, _pd.DataFrame) and len(returns.columns) == 1:
returns = returns[returns.columns[0]]

pallete = colors[1:2] if benchmark is None else colors[:2]
alpha = 0.7
if isinstance(returns, _pd.DataFrame):
pallete = colors[1:len(returns.columns) 1] if benchmark is None else colors[:len(returns.columns) 1]
if len(returns.columns) > 1:
alpha = 0.5

if benchmark is not None:
if isinstance(returns, _pd.Series):
combined_returns = benchmark.to_frame().join(returns.to_frame()) \
.stack().reset_index() \
.rename(columns={'level_1': 'Portfolio', 0: 'Returns'})
.rename(columns={'level_1': '', 0: 'Returns'})
elif isinstance(returns, _pd.DataFrame):
combined_returns = benchmark.to_frame().join(returns) \
.stack().reset_index() \
.rename(columns={'level_1': 'Portfolio', 0: 'Returns'})
.rename(columns={'level_1': '', 0: 'Returns'})
x = _sns.histplot(data=combined_returns, x='Returns',
bins=bins, alpha=alpha, kde=kde,
stat="density", hue='',
palette=pallete,
ax=ax)

_sns.histplot(data=combined_returns, x='Returns',
bins=bins, alpha=0.4, kde=kde,
stat="density", hue='Portfolio',
ax=ax)
else:
if isinstance(returns, _pd.Series):
combined_returns = returns.copy()
_sns.histplot(data=combined_returns, bins=bins,
alpha=0.4, kde=kde,
stat="density",
ax=ax)
ax.legend(fontsize=12)
if kde:
_sns.kdeplot(data=combined_returns, color='black', ax=ax)
x = _sns.histplot(data=combined_returns, bins=bins,
alpha=alpha,
kde=False,
stat="density",
color=colors[1],
ax=ax)

elif isinstance(returns, _pd.DataFrame):
combined_returns = returns.stack().reset_index() \
.rename(columns={'level_1': 'Portfolio', 0: 'Returns'})
_sns.histplot(data=combined_returns, x='Returns',
bins=bins, alpha=0.4, kde=kde,
stat="density", hue='Portfolio',
ax=ax)
.rename(columns={'level_1': '', 0: 'Returns'})
# _sns.kdeplot(data=combined_returns, color='black', ax=ax)
x = _sns.histplot(data=combined_returns, x='Returns',
bins=bins, alpha=alpha, kde=kde,
stat="density", hue='',
palette=pallete,
ax=ax)

# Why do we need average?
if isinstance(combined_returns, _pd.Series) or len(combined_returns.columns) == 1:
ax.axvline(combined_returns.mean(), ls="--", lw=1.5,
zorder=2, label="Average", color="red")


# _plt.setp(x.get_legend().get_texts(), fontsize=11)
ax.xaxis.set_major_formatter(_plt.FuncFormatter(
lambda x, loc: "{:,}%".format(int(x*100))))

Expand All @@ -408,10 438,9 @@ def plot_histogram(returns, benchmark, resample="M", bins=20,
# ax.axvline(0, lw=1, color="#000000", zorder=2)

ax.set_xlabel('')
if ylabel:
ax.set_ylabel("Occurrences", fontname=fontname,
fontweight='bold', fontsize=12, color="black")
ax.yaxis.set_label_coords(-.1, .5)
ax.set_ylabel("Occurrences", fontname=fontname,
fontweight='bold', fontsize=12, color="black")
ax.yaxis.set_label_coords(-.1, .5)

# fig.autofmt_xdate()

Expand Down Expand Up @@ -473,9 502,8 @@ def plot_rolling_stats(returns, benchmark=None, title="",
elif isinstance(returns, _pd.DataFrame):
col_names = ['Benchmark', returns_label]
df = df[list(_pd.core.common.flatten(col_names))].dropna()
for col in returns_label:
ax.plot(df[col], lw=lw,
label=col)
for i, col in enumerate(returns_label):
ax.plot(df[col], lw=lw, label=col, color=colors[i 1])
ax.plot(df['Benchmark'], lw=lw, label=benchmark.name,
color=colors[0], alpha=.8)
else:
Expand All @@ -485,20 513,19 @@ def plot_rolling_stats(returns, benchmark=None, title="",
label=returns.name, color=colors[1])
elif isinstance(returns, _pd.DataFrame):
df = df[returns_label].dropna()
for col in returns_label:
ax.plot(df[col], lw=lw,
label=col)
for i, col in enumerate(returns_label):
ax.plot(df[col], lw=lw, label=col, color=colors[i 1])

# rotate and align the tick labels so they look better
fig.autofmt_xdate()

# use a more precise date string for the x axis locations in the toolbar
# ax.fmt_xdata = _mdates.DateFormatter('%Y-%m-%d')\
fig.suptitle(title "\n", y=.99, fontweight="bold", fontname=fontname,
fig.suptitle(title, y=.94, fontweight="bold", fontname=fontname,
fontsize=14, color="black")

if subtitle:
ax.set_title("\n%s - %s " % (
ax.set_title("%s - %s \n" % (
df.index.date[:1][0].strftime('%e %b \'%y'),
df.index.date[-1:][0].strftime('%e %b \'%y')
), fontsize=12, color='gray')
Expand All @@ -519,7 546,10 @@ def plot_rolling_stats(returns, benchmark=None, title="",

ax.yaxis.set_major_formatter(_FormatStrFormatter('%.2f'))

ax.legend(fontsize=12)
ax.legend(fontsize=11)

if benchmark is None and len(_pd.DataFrame(returns).columns) == 1:
ax.get_legend().remove()

try:
_plt.subplots_adjust(hspace=0, bottom=0, top=1)
Expand Down Expand Up @@ -562,35 592,38 @@ def plot_rolling_beta(returns, benchmark,
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)

fig.suptitle(title "\n", y=.99, fontweight="bold", fontname=fontname,
fig.suptitle(title, y=.94, fontweight="bold", fontname=fontname,
fontsize=14, color="black")

if subtitle:
ax.set_title("\n%s - %s " % (
ax.set_title("%s - %s \n" % (
returns.index.date[:1][0].strftime('%e %b \'%y'),
returns.index.date[-1:][0].strftime('%e %b \'%y')
), fontsize=12, color='gray')

i = 1
if isinstance(returns, _pd.Series):
beta = _stats.rolling_greeks(returns, benchmark, window1)['beta'].fillna(0)
ax.plot(beta, lw=lw, label=window1_label, color=colors[1])
elif isinstance(returns, _pd.DataFrame):
beta = ({col: _stats.rolling_greeks(returns[col], benchmark, window1)['beta'].fillna(0)
for col in returns.columns})
for name, b in beta.items():
ax.plot(b, lw=lw, label=name " " f"({window1_label})")
ax.plot(b, lw=lw, label=name " " f"({window1_label})", color=colors[i])
i = 1

i = 1
if window2:
lw = lw - 0.5
if isinstance(returns, _pd.Series):
ax.plot(_stats.rolling_greeks(returns, benchmark, window2)['beta'],
lw=lw, label=window2_label, color="gray", alpha=0.8)
elif isinstance(returns, _pd.DataFrame):
betas_w2 = ({col: _stats.rolling_greeks(returns[col], benchmark, window2)['beta']
for col in returns.columns})
for name, beta_w2 in betas_w2.items():
ax.plot(beta_w2, lw=lw, ls='--', label=name " " f"({window2_label})", alpha=0.8)
# ax.plot(_stats.rolling_greeks(returns, benchmark, window2)['beta'],
# lw=lw, label=window2_label, color="gray", alpha=0.8)
ax.plot(beta_w2, lw=lw, ls='--', label=name " " f"({window2_label})", alpha=0.5, color=colors[i])
i = 1

beta_min = beta.min() if isinstance(returns, _pd.Series) else min([b.min() for b in beta.values()])
beta_max = beta.max() if isinstance(returns, _pd.Series) else max([b.max() for b in beta.values()])
Expand All @@ -616,7 649,10 @@ def plot_rolling_beta(returns, benchmark,
fontweight='bold', fontsize=12, color="black")
ax.yaxis.set_label_coords(-.1, .5)

ax.legend(fontsize=12)
ax.legend(fontsize=11)
if benchmark is None and len(_pd.DataFrame(returns).columns) == 1:
ax.get_legend().remove()

try:
_plt.subplots_adjust(hspace=0, bottom=0, top=1)
except Exception:
Expand Down Expand Up @@ -665,11 701,11 @@ def plot_longest_drawdowns(returns, periods=5, lw=1.5,
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)

fig.suptitle(f"{title} - Worst %.0f Drawdown Periods\n" %
periods, y=.99, fontweight="bold", fontname=fontname,
fig.suptitle(f"{title} - Worst %.0f Drawdown Periods" %
periods, y=.94, fontweight="bold", fontname=fontname,
fontsize=14, color="black")
if subtitle:
ax.set_title("\n%s - %s " % (
ax.set_title("%s - %s \n" % (
returns.index.date[:1][0].strftime('%e %b \'%y'),
returns.index.date[-1:][0].strftime('%e %b \'%y')
), fontsize=12, color='gray')
Expand Down Expand Up @@ -767,20 803,31 @@ def plot_distribution(returns, figsize=(10, 6),
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)

fig.suptitle(f"{title} - Return Quantiles\n", y=.99,
if title:
title = f"{title} - Return Quantiles"
else:
title = "Return Quantiles"
fig.suptitle(title, y=.94,
fontweight="bold", fontname=fontname,
fontsize=14, color="black")

if subtitle:
ax.set_title("\n%s - %s " % (
ax.set_title("%s - %s \n" % (
returns.index.date[:1][0].strftime('%e %b \'%y'),
returns.index.date[-1:][0].strftime('%e %b \'%y')
), fontsize=12, color='gray')

fig.set_facecolor('white')
ax.set_facecolor('white')

port.boxplot(ax=ax)#, colo=tuple(colors[:5]))
_sns.boxplot(data=port, ax=ax,
palette={
'Daily': colors[0],
'Weekly': colors[1],
'Monthly': colors[2],
'Quarterly': colors[3],
'Yearly': colors[4]
})

ax.yaxis.set_major_formatter(_plt.FuncFormatter(
lambda x, loc: "{:,}%".format(int(x*100))))
Expand Down
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