A drawdown chart visualizes the percentage decline from peak value over time, showing how far an investment or asset has fallen from its highest point. This chart is essential for risk assessment and understanding the magnitude of losses during unfavorable market periods. The filled area below the zero line emphasizes the depth and duration of drawdowns, making it easy to identify maximum drawdown periods and recovery points.
""" anyplot.ai
drawdown-basic: Drawdown Chart
Library: altair 6.1.0 | Python 3.13.13
Quality: 91/100 | Updated: 2026-05-23
"""
import os
import altair as alt
import numpy as np
import pandas as pd
from PIL import Image
THEME = os.getenv("ANYPLOT_THEME", "light")
PAGE_BG = "#FAF8F1" if THEME == "light" else "#1A1A17"
ELEVATED_BG = "#FFFDF6" if THEME == "light" else "#242420"
INK = "#1A1A17" if THEME == "light" else "#F0EFE8"
INK_SOFT = "#4A4A44" if THEME == "light" else "#B8B7B0"
DD_COLOR = "#AE3030" # Imprint palette pos 3 — semantic: loss/drawdown
REC_COLOR = "#009E73" # Imprint palette pos 1 — semantic: recovery/new high
# Data — simulated asset price over ~2 years with drawdowns and recoveries
np.random.seed(42)
dates = pd.date_range("2022-01-01", periods=500, freq="D")
returns = np.random.normal(0.001, 0.01, 500)
returns[0:30] = np.random.normal(0.002, 0.008, 30) # initial rally
returns[30:50] = np.random.normal(-0.012, 0.012, 20) # correction ~20%
returns[50:90] = np.random.normal(0.008, 0.008, 40) # recovery to new highs
returns[100:130] = np.random.normal(-0.015, 0.015, 30) # deeper correction ~30%
returns[130:200] = np.random.normal(0.006, 0.009, 70) # recovery to new highs
returns[220:270] = np.random.normal(-0.01, 0.012, 50) # extended decline ~35%
returns[270:350] = np.random.normal(0.005, 0.008, 80) # gradual recovery
returns[380:410] = np.random.normal(-0.008, 0.01, 30) # late correction ~15%
returns[410:480] = np.random.normal(0.004, 0.007, 70) # final recovery
price = 100 * np.cumprod(1 + returns)
running_max = np.maximum.accumulate(price)
drawdown = (price - running_max) / running_max * 100
df = pd.DataFrame({"date": dates, "drawdown": drawdown})
# Max drawdown stats
max_dd_idx = df["drawdown"].idxmin()
max_dd_date = df.loc[max_dd_idx, "date"]
max_dd_value = df.loc[max_dd_idx, "drawdown"]
max_drawdown_pct = abs(max_dd_value)
# Drawdown duration (peak → trough)
dd_start_candidates = df.loc[:max_dd_idx][df.loc[:max_dd_idx, "drawdown"] == 0]
dd_start_date = dd_start_candidates.iloc[-1]["date"] if not dd_start_candidates.empty else dates[0]
dd_duration_days = (max_dd_date - dd_start_date).days
# Recovery (trough → next new high)
post_max = df[df.index > max_dd_idx]
recovery_row = post_max[post_max["drawdown"] >= 0]
recovery_days = int((recovery_row.iloc[0]["date"] - max_dd_date).days) if not recovery_row.empty else None
recovery_str = f"{recovery_days}d" if recovery_days else "ongoing"
# Recovery points: first new high after any drawdown deeper than -5%
df["prev_dd"] = df["drawdown"].shift(1)
df["is_new_high"] = (df["drawdown"] >= 0) & (df["prev_dd"] < 0)
rec_indices = []
last_low = 0.0
for idx, row in df.iterrows():
if row["drawdown"] < last_low:
last_low = row["drawdown"]
if row["is_new_high"] and last_low < -5:
rec_indices.append(idx)
last_low = 0.0
recovery_points = df.loc[rec_indices, ["date", "drawdown"]].copy().reset_index(drop=True)
recovery_points["series"] = "New High"
max_dd_df = pd.DataFrame(
{"date": [max_dd_date], "drawdown": [max_dd_value], "label": [f"Max DD: {max_drawdown_pct:.1f}%"]}
)
title_str = "drawdown-basic · python · altair · anyplot.ai"
subtitle_str = f"Max Drawdown: {max_drawdown_pct:.1f}% · Duration: {dd_duration_days}d · Recovery: {recovery_str}"
# Plot layers
area = (
alt.Chart(df)
.mark_area(opacity=0.45, color=DD_COLOR)
.encode(
x=alt.X("date:T", title="Date", axis=alt.Axis(format="%b %Y")),
y=alt.Y("drawdown:Q", title="Drawdown (%)", scale=alt.Scale(domain=[df["drawdown"].min() * 1.15, 5])),
)
)
dd_line = alt.Chart(df).mark_line(color=DD_COLOR, strokeWidth=2).encode(x="date:T", y="drawdown:Q")
zero_rule = (
alt.Chart(pd.DataFrame({"y": [0]}))
.mark_rule(strokeDash=[5, 4], strokeWidth=1.5)
.encode(y="y:Q", color=alt.value(INK_SOFT))
)
max_dd_point = (
alt.Chart(max_dd_df)
.mark_point(size=250, color="#C475FD", filled=True, stroke=INK, strokeWidth=1.5)
.encode(x="date:T", y="drawdown:Q")
)
max_dd_label = (
alt.Chart(max_dd_df)
.mark_text(align="left", dx=12, dy=-8, fontSize=11, fontWeight="bold")
.encode(x="date:T", y="drawdown:Q", text="label:N", color=alt.value(INK))
)
layers = [area, dd_line, zero_rule, max_dd_point, max_dd_label]
if len(recovery_points) > 0:
recovery_markers = (
alt.Chart(recovery_points)
.mark_point(shape="triangle-up", filled=True, size=150, stroke=PAGE_BG, strokeWidth=1)
.encode(
x="date:T",
y="drawdown:Q",
color=alt.Color(
"series:N", scale=alt.Scale(range=[REC_COLOR]), legend=alt.Legend(title="", orient="top-right")
),
tooltip=[alt.Tooltip("date:T", title="New High", format="%Y-%m-%d")],
)
)
layers.append(recovery_markers)
chart = (
alt.layer(*layers)
.properties(
width=620,
height=320,
background=PAGE_BG,
title=alt.Title(
title_str,
fontSize=16,
color=INK,
anchor="start",
subtitle=subtitle_str,
subtitleFontSize=12,
subtitleColor=INK_SOFT,
),
)
.configure_view(fill=PAGE_BG, stroke=None, continuousWidth=620, continuousHeight=320)
.configure_axis(
labelFontSize=10,
titleFontSize=12,
domainColor=INK_SOFT,
tickColor=INK_SOFT,
gridColor=INK,
gridOpacity=0.10,
labelColor=INK_SOFT,
titleColor=INK,
)
.configure_axisX(grid=False)
.configure_title(color=INK, fontSize=16, subtitleFontSize=12, subtitleColor=INK_SOFT)
.configure_legend(
fillColor=ELEVATED_BG,
strokeColor=INK_SOFT,
labelColor=INK_SOFT,
titleColor=INK,
labelFontSize=10,
titleFontSize=10,
)
)
# Save PNG and pad to exact canvas target
chart.save(f"plot-{THEME}.png", scale_factor=4.0)
TW, TH = 3200, 1800
_img = Image.open(f"plot-{THEME}.png").convert("RGB")
_w, _h = _img.size
if _w > TW or _h > TH:
raise SystemExit(
f"altair vl-convert produced {_w}×{_h}, exceeds target {TW}×{TH}. "
f"Shrink chart .properties(width=, height=) values and re-render."
)
if _w < TW or _h < TH:
_canvas = Image.new("RGB", (TW, TH), PAGE_BG)
_canvas.paste(_img, ((TW - _w) // 2, (TH - _h) // 2))
_canvas.save(f"plot-{THEME}.png")
chart.save(f"plot-{THEME}.html")
Part of Drawdown Chart on anyplot.ai.