dumbmoney 0.3.1

Technical analysis and quantitative trading toolkit for retail investors taking on the market

dumbmoney

dumbmoney is a technical analysis and quantitative trading toolkit designed for retail investors. The current version provides a unified, transparent interface to fetch daily stock prices across A-shares, H-shares, and US markets by abstracting popular data packages like massive, tushare, and akshare, hiding their implementation complexity.

To use the massive or tushare providers, you must set the required environment variables MASSIVE_KEY or TUSHARE_TOKEN.

📦 Installation

Install only the core:

pip install dumbmoney

Install Tiger package:

pip install "dumbmoney[tiger]"

🚀 Quick Start

OHLCV Data & Charts

from dumbmoney import get_ohlcv, plot

os.environ["TUSHARE_TOKEN"] = "xxxxxx"
os.environ["MASSIVE_KEY"] = "yyyyyy"

ohlcv = get_ohlcv("AAPL.US")
print(ohlcv.tail())

from dumbmoney.indicators import MovingAverage, MACD, RSI

ma5 = MovingAverage(name="MA5", window=5, ma_type="SMA")
ma5.compute(ohlcv)

ma20 = MovingAverage(name="MA20", window=20, ma_type="SMA")
ma20.compute(ohlcv)

ma60 = MovingAverage(name="MA60", window=60, ma_type="SMA")
ma60.compute(ohlcv)

vol_ma20 = MovingAverage(name="Vol_MA20", window=20, ma_type="SMA", input_col="volume")
vol_ma20.compute(ohlcv)

macd = MACD()
macd.compute(ohlcv)

rsi = RSI()
rsi.compute(ohlcv)

plot(
  ohlcv,
  indicators=[ma5, ma20, ma60, vol_ma20, macd, rsi],
  panels=[0, 0, 0, 1, 2, 3],
  title="AAPL Stock Price with Indicators (mplfinance)",
  backend="mpl", # available backends: "mpl", "plotly"
)

Strategy, Policy & Backtest

from dumbmoney import get_ohlcv
from dumbmoney.strategies import MACrossParams, MACrossStrategy
from dumbmoney.policies import LongFlatAllInConfig, LongFlatAllInPolicy
from dumbmoney.backtests.single_asset import SingleAssetBacktester

ohlcv = get_ohlcv("AAPL.US")
strategy = MACrossStrategy(MACrossParams(fast_window=20, slow_window=60))
policy = LongFlatAllInPolicy(LongFlatAllInConfig(max_long_pct=1.0, min_strength=0.5))
backtester = SingleAssetBacktester(initial_cash=100_000.0)
result = backtester.run(symbol="AAPL", ohlcv=ohlcv, strategy=strategy, policy=policy)
print(result.metrics)

✨ Features

• 🔌 One function to fetch ohlcv data: get_ohlcv(symbol, start, end)
• 🌏 Multiple markets supported
  • A-shares (.SH, .SZ)
  • H-shares (.HK)
  • US stocks (.US)
• ⚙️ Automatic provider routing
  • A-shares → TuShare → AkShare
  • H-shares → TuShare → AkShare
  • US stocks → Massive → AkShare
• 📐 Unified normalized output
  • open, high, low, close, volume
• 🔁 Fallback logic
  • If one provider fails, the next takes over
• 🧩 Extensible architecture (plug in new providers)

Important Notice

• massive's free api key only supports retrieving data of US stocks from the most recent two years.
• tushare's free token only supports retrieving data of A-shares.
• akshare is free but depends on third-party data sources that may have variable reliability.

🏷️ Symbol Format

dumbmoney uses suffix-based symbol conventions:

Market	Example Symbol
SH	600519.SH or 600519
SZ	000001.SZ or 000001
KCB	688235.SH or 688235
ETF_SH	513090.SH or 513090, 562500.SH or 562500, 588080.SH or 588080
ETF_SZ	159652.SZ or 159652
HK	0700.HK
US	AAPL.US

Suffixes for H-shares and US stocks are required. A-share symbols may omit suffixes; however, if they are present, they must be valid and correct.

📘 API Reference

get_ohlcv(symbol, start, end, adjust="none")

Fetch normalized daily OHLCV prices.

• Parameters

Name	Type	Description
symbol	str	Stock symbol with suffix (600519.SH, 0700.HK, AAPL.US)
start	str	Start time, e.g. "2025-01-01"
end	str	End time, e.g. "2025-12-01"
adjust	str	Adjustment mode, "none" | "forward" | "backward"

• Returns

A pandas.DataFrame with:

Column	Description
open	Opening price
high	High
low	Low
close	Close
volume	Traded volume

Index is a DatetimeIndex named date.

plot(ohlcv, indicators=None, panels=None, title=None, backend="mpl", **kwargs)

Plot chart using the provided ohlcv data.

• Parameters

Name	Type	Description
ohlcv	pandas.DataFrame	DataFrame containing OHLCV columns (open, high, low, close, volume)
indicators	list or None	List of technical indicators to plot. Default is None.
panels	list or None	List of panel where the indicators will be plotted on. The ohlcv data will be plotted on the first two panels.
title	str or None	Chart title. Default is None.
backend	str	Plotting backend to use. Currently support "mpl" (mplfinance, default) and "plotly" (plotly).
**kwargs	-	Additional keyword arguments passed to the plotting backend.

• Returns

The plotter object which can be used to get the figure object by plotter.fig.