Create your own proprietary multi-user quantitative trading platform at zero cost and fast

Create your own proprietary multi-user quantitative trading platform at zero cost and fast

Anyone can build a quantitative trading platform using the Inventor Quantitative Extension API, and this example project shows how to build a powerful quantitative trading platform using Python and the Inventor Quantitative Extension API.

• Embed into existing systems

  According to this DEMO project, it is possible to write server-side code, add front-end pages to embed existing systems such as forums, blogs, communities, etc.; In order to achieve flexible access to existing user groups, and where existing user groups do not fully experience the underlying technical support quantified by the inventors, user use is more concise and easy to operate.

• Supporting the market

  • CTP Commodity Futures (expired, department store, department store, and exchange)
  • EOS (main foreign futures exchanges such as CME, CBOT)
  • More than 30 blockchain asset trading platforms worldwide

• Build your own quantification platform

  • Strategic design for high freedom

    Writing quantitative trading strategies using Python, JavaScript, C++ and freely customizing them to implement your trading ideas in a world of quantitative trading.

  • Powerful and efficient feedback systems

    From now on, it will no longer be necessary to collect data, and the local retrieval system engine can be easily configured with just one command, link:https://github.com/fmzquant/backtest_python

  • Simple architecture

    An HTTP server side program can be easily built with just a few front-end pages written.

• The DEMO project

  • Name: Inventors Quantify demonstrates how to build your own Asset Management Quantification platform using the Inventors Quantified Extension API

  • This DEMO project is installed

    • The first thing to do is to clone this demo project.

      git clone https://github.com/fmzquant/fmz_extend_api_demo.git
      

      

    • Switch to this directory, run pip, install

      

      pip install -r requirements.txt 
      

      

      Note: If Permission denied is prompted, sudo pip install -r requirements.txt is required to execute pip, and enter the operating system password as requested.

    • Once installed, configure the server program to be used, inventor quantification, account API KEY

      Inventor Quantification Expanded API KEY for use See the Inventor Quantification API documentation for more detailshttps://www.fmz.com/api

      Created by Inventor Quantified API KEY

      

      Write the API KEY, and the demo will be executed.app.pyThe server-side program.

      

  • This DEMO project runs commands on the server side

    python app.py
    

    • Running shows:

      

      After running the server side program, open the local page in the browser:http://127.0.0.1:5000

      

    • Test the registration page

      

      The project DEMO Quantitative Platform is up and running, register with the account of this testing platform (which stores local data), log in and configure the API KEY of the exchange as a user of this platform.

      

      

      It is now configured as follows:

      

      The three strategies shown on the page are just UI displays, which also require the administrator of the Asset Management Quantitative Platform to specifically design the implementation, here for demonstration purposes only.

    • Configure a test policy In this DEMO project, the server detects that pressing the Start button triggers a search for a policy that contains the keyword "main" in the inventor's quantified account, and uses this policy to bind the bot to run. So we created a strategy called the main test profit.

      The main Test profit strategy code is as follows:

      function main() {
          while(true) {
          LogProfit(Math.random()*100);
              Sleep(1000);
          }
      }
      

      

      After editing the code, click Save.

      Please note: It is necessary to ensure that there is an online host before running.https://www.fmz.com/bbs-topic/463 ）

    • Clicking on the Start button automatically creates a bot that binds a demonstration policy that will only randomly output a value as a yield value.

      A newly created robot can be seen in the inventor's quantized control center:

      The DEMO web page also shows the corresponding random number.

    • A robot running on inventor quantized by appId identifies the current user logged on to the DEMO platform

      

      def robot_run(robotId, appId, exchanges):
          strategyId = -1
          # 从策略库里选出一个包含main字符串的策略运行, 也可以预定义
          for ele in api("GetStrategyList")['data']['result']['strategies']:
              if 'main' in ele['name']:
                  strategyId = ele['id']
          if strategyId < 0:
              raise u"not found strategy"
          settings = {
                  "name":"robot for %s" % (appId, ),
                  "args": [], # our custom arguments for this strategey
                  "appid": appId, # 为该机器人设置标签,关联到本用户
                  "period": 60,
                  "strategy": strategyId,
                  "exchanges": [],
                  }
          for e in exchanges:
              settings["exchanges"].append({"eid": e.eid, "pair": get_default_stock(e.eid), "meta" :{"AccessKey": e.accessKey, "SecretKey": e.secretKey}})
          if robotId > 0:
              return api('RestartRobot', robotId, settings)
          else:
              return api('NewRobot', settings)
      

      As you can see, the settings in the code are the creation of the bot's configuration information and the appid is used to tag the user.

• Updated by

  # Github 地址更新：  https://github.com/fmzquant/fmz_extend_api_demo