WonderTrader Demos for CTA, High-Frequency, and Arbitrage Workflows
Article WonderTrader
Summary
This overview catalogs Python examples for the WonderTrader framework, including CTA strategies, futures and stock backtests, futures arbitrage, optimization, reinforcement learning, and high-frequency trading. It names Dual Thrust as a sample strategy used for both stocks and futures. The demos also cover data components, contract loading, monitoring, execution modules, and strategy interfaces, giving readers a map of the framework’s research and live-trading capabilities.
The guide explains how to configure a data service and connect it to a live example, including market-data broadcast, storage, trading channels, execution settings, risk monitoring, and session or instrument rules. It mentions order-rate and cancellation limits, execution price offsets and expiry, and different close/open priorities based on fees. This is implementation documentation rather than evidence of strategy performance: it supplies no evaluated results, and the examples require the appropriate framework, Python environment, data feeds, and broker or simulation connections.
Key ideas
- The demo collection spans CTA, arbitrage, optimization, reinforcement learning, backtesting, and high-frequency workflows.
- Dual Thrust is presented as an example strategy for both stocks and futures.
- Live examples separate data collection and broadcasting from strategy and trading components.
- Configuration covers execution behavior, risk monitoring, order limits, fees, sessions, and instrument rules.
- The guide describes setup and examples but reports no strategy performance evidence.
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Full text
# Python Demos
# Python Demos
Python下的demo主要演示不同环境下不同组件的使用<br>
提供了一个示例策略，DualThrust，股票和期货都用这个策略
+ cta_arbitrage_bt 期货套利回测demo √
+ cta_fut 期货CTA实盘demo，配置的是SIMNOW通道 √
+ cta_fut_bt 期货回测demo √
+ cta_fut_rl 强化学习训练demo √
+ cta_optimizer CTA策略优化器demo √
+ cta_step_by_step CTA策略开箱即用demo，by安东尼Q不了
+ cta_stk 股票CTA实盘demo，配置的是XTP的仿真通道 √
+ cta_stk_bt 股票回测demo √
+ ctp_loader 合约加载器demo √
+ datakit_allday 全天候数据组件demo
+ datakit_fut 期货数据组件demo √
+ datakit_stk 股票数据组件demo √
+ hft_fut 期货高频实盘demo √
+ hft_fut_bt 期货高频回测demo √
+ hft_fut_mocker 期货高频本地仿真demo √
+ sel_fut_bt 期货SEL引擎回测demo √
+ test_dataexts 数据扩展模块demo √
+ test_datahelper 数据辅助模块demo √
+ test_extmodules python外接行情和执行模块demo √
+ test_hotpicker WtHotPicker的用法示例 √
+ test_monitor WtMonSvr的用法示例 √
+ cta_unit_test CTA策略接口的单元测试demo √
# 如何使用这些demo
+ 首先确认本地安装的是 *Python3.6* 以上的版本，32位、64位都可以，wtpy子框架会根据Python的版本自动选择对应的底层
+ 然后安装*WonderTrader*上的*Python*子框架[***wtpy***](https://pypi.org/project/wtpy/)(version >= v0.3.2)
+ 如何运行回测demo
> 直接运行目录下的 *run.py* 即可
+ 如何运行实盘demo
- 首先运行数据组件
> 修改配置文件dtcfg.json中的解析器配置<br>
以 *simnow* 通道为例，将********改成自己的simnow账号，然后修改*code*字段为自己要订阅的合约，合约代码规则为"市场代码.合约代码"
>```json
>"parsers":[
> {
> "active":true, //是否启用
> "module":"ParserCTP.dll", //模块文件名，linux下为libParserCTP.so
> "front":"tcp://180.168.146.187:10111", //行情前置
> "broker":"9999",
> "user":"********",
> "pass":"********",
> "code":"CFFEX.IF2005,SHFE.au2012"
> }
>]
>```
> 修改数据dtcfg.json中落地模块配置
>```json
>"writer":{
> "path":"E:/FUT_Data", //数据存储的路径
> "savelog":true, //是否同时输出csv格式的数据
> "async":true, //是否异步，异步会把数据提交到缓存队列，然后由独立线程进行处理
> "groupsize":100 //数据条数分组大小，每处理这么多条就会输出一条日志
>}
>```
> 修改dtcfg.json中的udp广播配置（目前只开放了内存块直接广播）
>```json
>"broadcaster":{
> "active":true, //是否启用
> "bport":3997, //udp监听端口
> "broadcast":[
> {
> "host":"255.255.255.255", //广播地址
> "port":9001, //广播端口
> "type":2 //广播类型,0-纯文本格式,1-json格式,2-内存块直接广播
> }
> ]
>}
>```
> 最后运行runDT.py
- 然后修改实盘demo的配置文件*config.json*, 再运行实盘demo下的 *run.py*
> 将数据读取配置中的路径修改为数据组件里配置的路径
>```json
>"data":{
> "store":{
> "path":"./STK_Data/" //这里改为数据组件的存储路径
> }
>}
>```
> 修改行情通道中的接收端口和接收地址
>```json
>"parsers":[
> {
> "active":true,
> "id":"parser1",
> "module":"ParserUDP.dll",
> "host":"127.0.0.1", //udp广播的地址
> "bport":9001, //udp广播的端口
> "sport":3997, //udp监听的端口
> "filter":"" //市场过滤器，根据需要配置，如CFFEX,SHFE，可针对不同的市场配置不同的行情通道
> }
>]
>```
> 修改交易通道的配置
>```json
>"traders":[
> {
> "active":true,
> "id":"simnow",
> "module":"TraderXTP.dll",
>
> "host":"120.27.164.69", //以下为交易模块专用配置
> "port":"6001",
> "user":"********",
> "pass":"********",
> "protocol":1,
> "clientid":1,
> "hbinterval":15,
> "buffsize":128,
> "quick":true,
>
> "riskmon": //交易通道风控配置
> {
> "active":true,
> "policy":
> {
> "default": //默认策略，可以针对品种进行专门设置，格式如CFFEX.IF
> {
> "order_times_boundary": 20, //单位时间最高下单次数，如10s内下单20次
> "order_stat_timespan": 10, //下单次数统计时间，单位秒
>
> "cancel_times_boundary": 20, //单位时间最高撤单次数，如10s内撤单20次
> "cancel_stat_timespan": 10, //撤单次数统计时间
> "cancel_total_limits": 470 //总的最大撤单次数
> }
> }
> }
> }
>]
>```
> 修改执行器的配置，可以根据需要配置多个执行器，执行器和交易通道一对一绑定
>```json
>"executers":[
> {
> "active":true, //是否启用
> "id":"exe0",
> "scale": 1, //放大倍数
> "policy": //执行策略
> {
> "default":{ //默认执行单元，也可以根据品种设置如CFFEX.IF
> "name":"WtExeFact.WtSimpExeUnit", //执行单元名（工厂名.执行单元名）
> "offset": 0, //下单价格与基准价的偏移量，买入+，卖出-
> "expire": 40, //未成交订单超时时间，单位秒
> "opposite": true //是否使用对手价作为基准价，false时为最新价
> }
> },
> "trader":"simnow" //绑定的交易通道id
> }
>]
>```
> 修改交易环境的的配置
>```json
>"env":{
> "name":"cta", //确定使用cta引擎，还是hft引擎
> "product":{ //生产环境的配置
> "session":"SD0930" //!!cta总调度的会话时间模板，可以在sessions.json里找到
> },
> "filters":"filters.json", //组合过滤器，用于临时控制某个策略或品种的信号
> "fees":"fees_stk.json", //佣金模板
> "riskmon":{ //组合风控设置
> "active":true,
> "module":"WtRiskMonFact.dll", //风控策略模板名
> "name":"SimpleRiskMon", //风控策略名，框架会根据这个策略名创建风控策略实例
> "calc_span":5, //以下是风控策略自己的参数
> "risk_span": 30,
> "risk_scale": 0.3,
> "basic_ratio": 101,
> "inner_day_fd":20.0,
> "inner_day_active":true,
> "multi_day_fd":60.0,
> "multi_day_active":false,
> "base_amount": 5000000
> }
>}
>```
> 修改自动开平策略的配置文件*actpolicy.json*<br>
>以股指为例，股指平今手续费很高，所以开平优先级顺序为：平昨>开仓>平今<br>
>如果是上期黄金和白银等品种，平今为0，则优先级顺序为：平今>平昨>开仓
>```json
>"stockindex":{ //开平策略名称，随意定，不要重复
> "order":[ //开平顺序设定
> {
> "action":"closeyestoday", //首先平昨，这样仓位不会一直增加，减少保证金占用
> "limit":0 //平昨手数限制，0为不限制
> },
> {
> "action":"open", //然后再开仓
> "limit":500 //开仓限制为500手
> },
> {
> "action":"closetoday", //最后平今
> "limit":0
> }
> ],
> "filters":["CFFEX.IF","CFFEX.IC","CFFEX.IH"] //适用品种为IF、IC、IH
>}
>```
> 交易所品种配置说明*commodities_stk.json*
>```json
>{
> "SSE": {
> "ETF": {
> "category": 0, //
> "covermode": 0, //
> "exchg": "SSE", //交易所代码
> "holiday": "CHINA", //中国节假日，详见holidays.json
> "name": "上证ETF", //名称
> "precision": 2, //
> "pricemode": 1, //
> "pricetick": 0.001, //价格变动单位
> "session": "SD0930", //交易时间，详见sessions.json
> "volscale": 1, //
> "trademode": 2 //0、多空 1、T0做多(可转债) 2、T1做多(股票/ETF)
> }
> }
>}
>```Shown in full with attribution under the source's licence. Licence: MIT
This summary was written by Stratmill's research agent from the original; it is not a copy of the source.