xtquant

name	xtquant
description	XtQuant QMT Python SDK — Integrates market data (xtdata) and trading interfaces (xttrade), supporting A-shares, futures, options, and other Chinese securities markets.
homepage	http://dict.thinktrader.net/nativeApi/start_now.html

XtQuant (QMT Python SDK by ThinkTrader)

XtQuant is the Python SDK for the QMT/miniQMT quantitative trading platform, developed by ThinkTrader (XunTou Technology). It contains two core modules:

• xtdata — Market Data Module: real-time quotes, historical K-lines, tick data, Level 2 data, financial data, sector management
• xttrade — Trading Module: order placement, position/order queries, account management, margin trading, futures/options, smart algorithms

⚠️ Requires miniQMT or QMT client running on Windows. XtQuant connects to the QMT process via local TCP. You need QMT/miniQMT access enabled by your broker.

Installation

pip install xtquant

You can also download from the official website: http://dict.thinktrader.net/nativeApi/download_xtquant.html

Architecture Overview

Your Python script (any IDE, any Python version)
    ↓ (xtquant SDK, pip install)
    ├── xtdata  → miniQMT (market data service, TCP connection)
    └── xttrade → miniQMT (trading service, TCP connection)
         ↓
    Broker trading system

Core Module Reference

Module	Import	Purpose
xtdata	from xtquant import xtdata	Market data: K-lines, tick, Level 2, financials, sectors
xttrader	from xtquant.xttrader import XtQuantTrader	Trading: order placement, queries, callbacks
xtconstant	from xtquant import xtconstant	Constants: order types, price types, market codes
xttype	from xtquant.xttype import StockAccount	Account types: STOCK, CREDIT, FUTURE

---

Quick Start — Market Data

from xtquant import xtdata

# Connect to local miniQMT (default: localhost)
xtdata.connect()

# Download historical K-line data (must download to local cache before first access)
xtdata.download_history_data('000001.SZ', '1d', start_time='20240101', end_time='20240630')

# Get local K-line data (returns a dict of DataFrames keyed by stock code)
data = xtdata.get_market_data_ex(
    [],                    # field_list, empty list means all fields
    ['000001.SZ'],         # stock_list, list of stock codes
    period='1d',
    start_time='20240101',
    end_time='20240630',
    dividend_type='front'  # Adjustment type: none (unadjusted), front (forward-adjusted), back (backward-adjusted), front_ratio (proportional forward), back_ratio (proportional backward)
)
print(data['000001.SZ'])

Real-Time Quote Subscription

def on_data(datas):
    """Quote data callback function, receives pushed real-time data"""
    for stock_code, data in datas.items():
        print(stock_code, data)

# Subscribe to tick data for a single stock
xtdata.subscribe_quote('000001.SZ', period='tick', callback=on_data)

# Subscribe to full-market quote push
xtdata.subscribe_whole_quote(['SH', 'SZ'], callback=on_data)

xtdata.run()  # Block the current thread, continuously receiving callback data

Financial Data

# First download financial data to local cache
xtdata.download_financial_data(['000001.SZ'])
# Then retrieve financial data from local cache
data = xtdata.get_financial_data(['000001.SZ'])
# Available financial reports: Balance (balance sheet), Income (income statement), CashFlow (cash flow statement),
# PershareIndex (per-share indicators), CapitalStructure (capital structure), TOP10HOLDER (top 10 shareholders),
# TOP10FLOWHOLDER (top 10 tradable shareholders), SHAREHOLDER (shareholder count)

Instrument Info & Sectors

# Get detailed instrument info (name, price limits, tick size, etc.)
info = xtdata.get_instrument_detail('000001.SZ')
# Get security type (stock/index/fund/bond, etc.)
itype = xtdata.get_instrument_type('000001.SZ')
# Get list of stocks in a sector
stocks = xtdata.get_stock_list_in_sector('沪深A股')
# Get list of trading dates
days = xtdata.get_trading_dates('SH', start_time='20240101', end_time='20240630')

---

Quick Start — Trading

from xtquant import xtconstant
from xtquant.xttrader import XtQuantTrader, XtQuantTraderCallback
from xtquant.xttype import StockAccount

# Create a trader instance (path points to miniQMT's userdata_mini directory)
path = r'D:\国金证券QMT交易端\userdata_mini'
session_id = 123456  # Each strategy must use a unique session_id
xt_trader = XtQuantTrader(path, session_id)

# Register a callback class to receive real-time push notifications
class MyCallback(XtQuantTraderCallback):
    def on_disconnected(self):
        print('Disconnected')
    def on_stock_order(self, order):
        print(f'Order update: {order.stock_code} status={order.order_status}')
    def on_stock_trade(self, trade):
        print(f'Trade update: {trade.stock_code} {trade.traded_volume}@{trade.traded_price}')
    def on_order_error(self, order_error):
        print(f'Order error: {order_error.error_msg}')
    def on_order_stock_async_response(self, response):
        print(f'Async order response: order_id={response.order_id}')

xt_trader.register_callback(MyCallback())
xt_trader.start()
connect_result = xt_trader.connect()  # Returns 0 on successful connection

# Create an account object and subscribe to push notifications
account = StockAccount('your_account_id')
xt_trader.subscribe(account)  # Enable push notifications for this account

# Place order: limit buy 600000.SH, 1000 shares at price 10.5
order_id = xt_trader.order_stock(
    account, '600000.SH', xtconstant.STOCK_BUY, 1000,
    xtconstant.FIX_PRICE, 10.5, 'strategy1', 'test_order'
)
# Returns order_id > 0 on success, -1 on failure

# Query positions
positions = xt_trader.query_stock_positions(account)
for pos in positions:
    print(pos.stock_code, pos.volume, pos.can_use_volume, pos.market_value)

# Query orders
orders = xt_trader.query_stock_orders(account)

# Query assets
asset = xt_trader.query_stock_asset(account)
print(f'Available cash: {asset.cash}, Total assets: {asset.total_asset}')

# Cancel order
xt_trader.cancel_order_stock(account, order_id)

# Block the main thread, waiting for callbacks
xt_trader.run_forever()

---

Stock Code Format

Market	Format	Example
Shanghai A-shares	XXXXXX.SH	600000.SH
Shenzhen A-shares	XXXXXX.SZ	000001.SZ
Beijing Stock Exchange	XXXXXX.BJ	430047.BJ
Shanghai Index	XXXXXX.SH	000001.SH (SSE Composite Index)
Shenzhen Index	XXXXXX.SZ	399001.SZ (SZSE Component Index)
CFFEX Futures	XXXX.IF	IF2401.IF (CSI 300 Futures)
SHFE Futures	XXXX.SF	ag2407.SF (Silver Futures)
DCE Futures	XXXX.DF	m2405.DF (Soybean Meal Futures)
ZCE Futures	XXXX.ZF	CF405.ZF (Cotton Futures)
INE Futures	XXXX.INE	sc2407.INE (Crude Oil Futures)
Shanghai Options	XXXXXXXX.SHO	10004358.SHO
Shenzhen Options	XXXXXXXX.SZO	90000001.SZO
ETF	XXXXXX.SH/SZ	510300.SH
Convertible Bonds	XXXXXX.SH/SZ	113050.SH

Data Periods

tick, 1m, 5m, 15m, 30m, 1h, 1d, 1w, 1mon

Supported Asset Types

Asset	Market Data (xtdata)	Trading (xttrade)
A-shares (Shanghai & Shenzhen)	✅ K-lines, tick, Level 2, financials	✅ Buy/Sell
ETF	✅ K-lines, tick, IOPV	✅ Buy/Sell, Subscribe/Redeem
Convertible Bonds	✅ K-lines, tick	✅ Buy/Sell
Futures	✅ K-lines, tick	✅ Open long/Close long/Open short/Close short
Options	✅ K-lines, tick	✅ Buy/Sell open/close, Exercise
Indices	✅ K-lines, tick	❌
Funds	✅ K-lines, tick	✅ Buy/Sell
Margin Trading	✅ Via credit account	✅ Full credit trading

Order Type Constants (xtconstant)

Category	Constants
Stock	STOCK_BUY (23, buy), STOCK_SELL (24, sell)
Credit	CREDIT_FIN_BUY (margin buy), CREDIT_SLO_SELL (short sell), CREDIT_BUY_SECU_REPAY (buy to repay securities), CREDIT_DIRECT_CASH_REPAY (direct cash repayment), etc.
Futures	FUTURE_BUY_OPEN (open long), FUTURE_SELL_CLOSE (close long), FUTURE_SELL_OPEN (open short), FUTURE_BUY_CLOSE (close short)
Options	STOCK_OPTION_BUY_OPEN (buy to open), STOCK_OPTION_SELL_CLOSE (sell to close), STOCK_OPTION_EXERCISE (exercise), etc.
Price Type	FIX_PRICE (11, limit), ANY_PRICE (12, market), LATEST_PRICE (5, latest price), MARKET_PEER_PRICE_FIRST (best counterparty price), etc.

Account Types

StockAccount('id')            # Regular stock account
StockAccount('id', 'CREDIT')  # Credit account (margin trading)
StockAccount('id', 'FUTURE')  # Futures account

xtdata Interface Pattern

The market data module follows a unified download → retrieve pattern:

1. Subscribe (subscribe): subscribe_quote, subscribe_whole_quote — real-time push
2. Download (download): download_history_data, download_financial_data — download from server to local cache (synchronous/blocking)
3. Retrieve (get): get_market_data_ex, get_financial_data — read from local cache (fast)

xttrade Callback System

Register an XtQuantTraderCallback subclass to receive real-time push notifications:

Callback	Data Type	Trigger Event
on_stock_order(order)	XtOrder	Order status change
on_stock_trade(trade)	XtTrade	Trade execution
on_stock_position(position)	XtPosition	Position change
on_stock_asset(asset)	XtAsset	Asset change
on_order_error(error)	XtOrderError	Order placement failure
on_cancel_error(error)	XtCancelError	Order cancellation failure
on_disconnected()	—	Connection lost
on_order_stock_async_response(resp)	XtOrderResponse	Async order response

Advanced Features

• Smart Algorithm Trading: Execute algorithmic orders such as VWAP via smart_algo_order_async
• Securities Lending: Query available securities, apply for lending, manage contracts
• Bank-Securities Transfer: Transfer funds between bank and securities accounts
• CTP Internal Transfer: Transfer funds between futures and options accounts
• Custom Sectors: Create, manage, and query custom stock groups
• Level 2 Data: l2quote, l2order, l2transaction, l2quoteaux, l2orderqueue, l2thousand (1000-level order book), limitupperformance (consecutive limit-up tracking), snapshotindex, hfiopv, fullspeedorderbook

Usage Tips

• miniQMT must be running on Windows — xtquant connects via local TCP.
• session_id must be unique per strategy — different strategies need different IDs.
• connect() is a one-time connection — it does not auto-reconnect after disconnection; you must call it again manually.
• Always call subscribe(account) to receive trading push callbacks.
• Data is cached locally after download — subsequent reads are extremely fast.
• Use dividend_type='front' to get forward-adjusted K-line data.
• In push callbacks, use async query methods to avoid deadlocks.
• Documentation: http://dict.thinktrader.net/nativeApi/start_now.html

---

Advanced Examples

Batch Download Full-Market Daily K-Line Data

from xtquant import xtdata

xtdata.connect()

# Get the full list of Shanghai & Shenzhen A-shares
stock_list = xtdata.get_stock_list_in_sector('沪深A股')
print(f"Total {len(stock_list)} A-shares")

# Batch download daily K-line data (recommended to download in batches to avoid timeout)
batch_size = 50
for i in range(0, len(stock_list), batch_size):
    batch = stock_list[i:i+batch_size]
    for stock in batch:
        try:
            xtdata.download_history_data(stock, '1d', start_time='20240101', end_time='20240630')
        except Exception as e:
            print(f"Failed to download {stock}: {e}")
    print(f"Downloaded {min(i+batch_size, len(stock_list))}/{len(stock_list)}")

# Batch retrieve data
data = xtdata.get_market_data_ex(
    [], stock_list[:10], period='1d',
    start_time='20240101', end_time='20240630',
    dividend_type='front'
)
for code, df in data.items():
    print(f"{code}: {len(df)} records, latest close={df['close'].iloc[-1]}")

Real-Time Quote Monitoring + Conditional Order Trigger

from xtquant import xtdata, xtconstant
from xtquant.xttrader import XtQuantTrader, XtQuantTraderCallback
from xtquant.xttype import StockAccount
import threading

# === Trading Callbacks ===
class MyCallback(XtQuantTraderCallback):
    def on_stock_order(self, order):
        print(f'Order: {order.stock_code} status={order.order_status} {order.status_msg}')
    def on_stock_trade(self, trade):
        print(f'Trade: {trade.stock_code} {trade.traded_volume}@{trade.traded_price}')
    def on_order_error(self, error):
        print(f'Error: {error.error_msg}')

# === Initialize Trading ===
path = r'D:\券商QMT\userdata_mini'
xt_trader = XtQuantTrader(path, 888888)
xt_trader.register_callback(MyCallback())
xt_trader.start()
xt_trader.connect()
account = StockAccount('your_account')
xt_trader.subscribe(account)

# === Quote Monitoring Parameters ===
target_stock = '000001.SZ'
buy_price = 10.50    # Target buy price
sell_price = 11.50   # Target sell price
bought = False

def on_tick(datas):
    """Real-time tick callback: automatically places orders when price hits target"""
    global bought
    for code, tick in datas.items():
        price = tick['lastPrice']
        print(f'{code}: latest price={price}')

        # Price drops to or below target buy price, buy
        if price <= buy_price and not bought:
            order_id = xt_trader.order_stock(
                account, code, xtconstant.STOCK_BUY, 100,
                xtconstant.FIX_PRICE, buy_price, 'auto_buy', '条件触发买入'
            )
            print(f'Buy triggered: order_id={order_id}')
            bought = True

        # Price rises to or above target sell price, sell
        elif price >= sell_price and bought:
            order_id = xt_trader.order_stock(
                account, code, xtconstant.STOCK_SELL, 100,
                xtconstant.FIX_PRICE, sell_price, 'auto_sell', '条件触发卖出'
            )
            print(f'Sell triggered: order_id={order_id}')
            bought = False

# === Start quote subscription (separate thread) ===
xtdata.connect()
def run_data():
    xtdata.subscribe_quote(target_stock, period='tick', callback=on_tick)
    xtdata.run()

t = threading.Thread(target=run_data, daemon=True)
t.start()

# Keep the main thread running
xt_trader.run_forever()

Multi-Stock Moving Average Strategy

from xtquant import xtdata, xtconstant
from xtquant.xttrader import XtQuantTrader, XtQuantTraderCallback
from xtquant.xttype import StockAccount
import pandas as pd

xtdata.connect()

# Define stock pool
stock_pool = ['000001.SZ', '600036.SH', '601318.SH', '000858.SZ', '300750.SZ']

# Download historical data
for stock in stock_pool:
    xtdata.download_history_data(stock, '1d', start_time='20240101', end_time='20241231')

# Retrieve data and compute signals
signals = {}
for stock in stock_pool:
    data = xtdata.get_market_data_ex([], [stock], period='1d',
        start_time='20240101', end_time='20241231', dividend_type='front')
    df = data[stock]

    # Calculate 5-day and 20-day moving averages
    df['ma5'] = df['close'].rolling(5).mean()
    df['ma20'] = df['close'].rolling(20).mean()

    # Determine the latest signal
    if len(df) >= 21:
        latest = df.iloc[-1]
        prev = df.iloc[-2]
        if prev['ma5'] <= prev['ma20'] and latest['ma5'] > latest['ma20']:
            signals[stock] = 'BUY'   # Golden cross
        elif prev['ma5'] >= prev['ma20'] and latest['ma5'] < latest['ma20']:
            signals[stock] = 'SELL'  # Death cross
        else:
            signals[stock] = 'HOLD'  # Hold

print("Trading signals:")
for stock, signal in signals.items():
    print(f"  {stock}: {signal}")

Retrieve Financial Data and Screen Stocks

from xtquant import xtdata

xtdata.connect()

# Get the list of Shanghai & Shenzhen A-shares
stock_list = xtdata.get_stock_list_in_sector('沪深A股')

# Download financial data
xtdata.download_financial_data(stock_list[:100])  # Download the first 100

# Retrieve financial data
for stock in stock_list[:10]:
    data = xtdata.get_financial_data([stock])
    if stock in data and 'PershareIndex' in data[stock]:
        psi = data[stock]['PershareIndex']
        if len(psi) > 0:
            latest = psi[-1]
            roe = latest.get('du_return_on_equity', 0)
            eps = latest.get('s_fa_eps_basic', 0)
            print(f"{stock}: ROE={roe}, EPS={eps}")

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