A MACD (Moving Average Convergence Divergence) chart displaying three components: the MACD line, signal line, and histogram. The MACD line represents the difference between 12-day and 26-day exponential moving averages, while the signal line is a 9-day EMA of the MACD. The histogram visualizes the difference between these two lines. This is an essential momentum oscillator for technical analysis, helping traders identify trend direction, momentum strength, and potential buy/sell signals through line crossovers.
""" anyplot.ai
indicator-macd: MACD Technical Indicator Chart
Library: matplotlib 3.10.9 | Python 3.13.13
Quality: 90/100 | Updated: 2026-05-16
"""
import os
import sys
sys.path.pop(0)
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
# Theme tokens
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"
# imprint palette
MACD_COLOR = "#4467A3" # blue — MACD line
SIGNAL_COLOR = "#BD8233" # ochre — signal line (categorical contrast with MACD blue)
POSITIVE_COLOR = "#009E73" # green — histogram bars above zero
NEGATIVE_COLOR = "#AE3030" # red — histogram bars below zero
# Generate synthetic stock price data and calculate MACD
np.random.seed(42)
# Create 150 trading days of price data (need 120 for display + 26 for EMA warmup)
n_days = 150
dates = pd.date_range("2024-06-01", periods=n_days, freq="B")
# Generate realistic price movement with trend and volatility
returns = np.random.normal(0.0005, 0.015, n_days)
price = 100 * np.cumprod(1 + returns)
# Calculate EMAs for MACD
def ema(data, span):
return pd.Series(data).ewm(span=span, adjust=False).mean().values
ema_12 = ema(price, 12)
ema_26 = ema(price, 26)
# Calculate MACD components
macd_line = ema_12 - ema_26
signal_line = ema(macd_line, 9)
histogram = macd_line - signal_line
# Use only the last 120 days (after EMAs have stabilized)
start_idx = 30
dates = dates[start_idx:]
macd_line = macd_line[start_idx:]
signal_line = signal_line[start_idx:]
histogram = histogram[start_idx:]
# Create figure with two subplots
fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(16, 9), facecolor=PAGE_BG, gridspec_kw={"height_ratios": [2, 1]})
# Upper subplot: MACD and Signal lines
ax1.set_facecolor(PAGE_BG)
ax1.plot(dates, macd_line, color=MACD_COLOR, linewidth=3, label="MACD (12, 26)")
ax1.plot(dates, signal_line, color=SIGNAL_COLOR, linewidth=3, label="Signal (9)")
ax1.axhline(y=0, color=INK_SOFT, linestyle="--", linewidth=1.5, alpha=0.5)
ax1.set_ylabel("MACD Value", fontsize=20, color=INK)
ax1.tick_params(axis="both", labelsize=16, colors=INK_SOFT)
ax1.spines["top"].set_visible(False)
ax1.spines["right"].set_visible(False)
for s in ("left", "bottom"):
ax1.spines[s].set_color(INK_SOFT)
ax1.yaxis.grid(True, alpha=0.10, linewidth=0.8, color=INK_SOFT)
# Legend for upper subplot
leg1 = ax1.legend(fontsize=16, loc="upper left")
if leg1:
leg1.get_frame().set_facecolor(ELEVATED_BG)
leg1.get_frame().set_edgecolor(INK_SOFT)
leg1.get_frame().set_alpha(0.95)
plt.setp(leg1.get_texts(), color=INK_SOFT)
# Lower subplot: Histogram
ax2.set_facecolor(PAGE_BG)
colors = [POSITIVE_COLOR if h >= 0 else NEGATIVE_COLOR for h in histogram]
ax2.bar(dates, histogram, color=colors, alpha=0.8, width=0.8, label="Histogram")
ax2.axhline(y=0, color=INK_SOFT, linestyle="-", linewidth=1.5, alpha=0.7)
ax2.set_xlabel("Date", fontsize=20, color=INK)
ax2.set_ylabel("Histogram", fontsize=20, color=INK)
ax2.tick_params(axis="both", labelsize=16, colors=INK_SOFT)
ax2.spines["top"].set_visible(False)
ax2.spines["right"].set_visible(False)
for s in ("left", "bottom"):
ax2.spines[s].set_color(INK_SOFT)
ax2.yaxis.grid(True, alpha=0.10, linewidth=0.8, color=INK_SOFT)
# Format x-axis dates
fig.autofmt_xdate(rotation=45, ha="right")
# Main title
fig.suptitle("indicator-macd · matplotlib · anyplot.ai", fontsize=24, fontweight="medium", color=INK, y=0.98)
plt.tight_layout(rect=[0, 0, 1, 0.96])
# Save to script directory
script_dir = os.path.dirname(os.path.abspath(__file__))
plt.savefig(os.path.join(script_dir, f"plot-{THEME}.png"), dpi=300, bbox_inches="tight", facecolor=PAGE_BG)
Part of MACD Technical Indicator Chart on anyplot.ai.