Build a Simple Moving‑Average Stock Strategy on Ricequant in Minutes

Overview

This article demonstrates implementing a single‑stock moving‑average strategy on the Ricequant quant platform, helping beginners get started and create their own strategy code.

Strategy Framework

The rule is simple: when the 5‑day moving average is above the 30‑day moving average, buy the stock with the full cash amount; otherwise, sell all holdings.

1. Initialization

Set the target stock to "300059.XSHE" (Dongfang Caifu on the Shenzhen exchange).

def init(context):
    context.stock = "300059.XSHE"  # target stock

Stock code suffixes: XSHE for Shenzhen, XSHG for Shanghai.

2. Retrieve Moving Averages

# fast = 5‑day average, slow = 30‑day average
fast = bar_dict[context.stock].mavg(5, frequency='day')
slow = bar_dict[context.stock].mavg(30, frequency='day')

3. Determine Cash

cash = context.portfolio.cash  # current cash amount

4. Buy / Sell Logic

if fast > slow:
    order_value(context.stock, cash)          # buy with all cash
elif fast < slow:
    order_target_percent(context.stock, 0)    # sell all holdings

5. Full Daily‑Frequency Code

def init(context):
    context.stock = "300059.XSHE"

def handle_bar(context, bar_dict):
    fast = bar_dict[context.stock].mavg(5, frequency='day')
    slow = bar_dict[context.stock].mavg(30, frequency='day')
    cash = context.portfolio.cash
    if fast > slow:
        order_value(context.stock, cash)
    elif fast < slow:
        order_target_percent(context.stock, 0)

6. Backtesting

Run a daily backtest from 2015‑01‑04 to 2016‑10‑04 with an initial capital of 100,000 CNY. The platform will display performance charts and risk‑return metrics.

7. Minute‑Level Backtesting

To switch to minute frequency, modify the handler and add a before_trading function that resets a flag each day, ensuring only one order per day.

def init(context):
    context.stock = "300059.XSHE"
    context.fired = 0

def before_trading(context):
    context.fired = 0

def handle_bar(context, bar_dict):
    if context.fired == 0:
        fast = bar_dict[context.stock].mavg(5, frequency='day')
        slow = bar_dict[context.stock].mavg(30, frequency='day')
        cash = context.portfolio.cash
        if fast > slow:
            order_value(context.stock, cash)
        elif fast < slow:
            order_target_percent(context.stock, 0)
        context.fired = 1

8. Simulation Trading

After a successful minute backtest, enable simulation trading in the platform to see real‑time order execution on minute‑level data.

9. WeChat Notifications

Activate the WeChat notification switch in the strategy settings, scan the QR code to bind your account, and receive trade signals instantly via WeChat.