futu_algo:Futu算法交易框架（Python）基于富途OpenApi所开发的量化交易框架

<div align="center"> <img alt="Billerikay Logo" src="https://raw.githubusercontent.com/billpwchan/futu_algo/master/docs/img/author-logo.png" width="400px" /> **billpwchan/futu-algo API Reference Documentation** [](https://github.com/billpwchan/futu_algo/issues) [](https://github.com/billpwchan/futu_algo/blob/master/LICENSE) [](https://github.com/billpwchan/futu_algo) [](https://github.com/billpwchan/futu_algo/commits/master) [](https://github.com/billpwchan/futu_algo) [](https://github.com/billpwchan/futu_algo) </div> ## Features - Developed based on FutoOpenD and FutuOpenAPI - Low-latency Trading Support (up to 1M level) - Daily Stock Filtering and Email Notification - Strategy Backtesting and Reporting ## Issues - [x] ~~[ADX & RSI Trading Strategy Support](https://github.com/billpwchan/futu_algo/issues/1)~~ ## Releases **Important:** Program still in Alpha Phase now. ## Version Guidance | FutuAlgo Release | Futu OpenAPI Specification | |:-----------------|:---------------------------| | 0.0.2-alpha.x | 4.0 | ## Deployment ### Pre-Requisite: Configuration File (Config.ini) ```ini [FutuOpenD.Config] Host = <OpenD Host> Port = <OpenD Port> WebSocketPort = <OpenD WebSocketPort> WebSocketKey = <OpenD WebSocketKey> TrdEnv = <SIMULATE or REAL> [FutuOpenD.Credential] Username = <Futu Login Username> Password_md5 = <Futu Login Password Md5 Value> [FutuOpenD.DataFormat] HistoryDataFormat = ["code","time_key","open","close","high","low","pe_ratio","turnover_rate","volume","turnover","change_rate","last_close"] SubscribedDataFormat = None [Database] Database_path = <Your SQLite Database File Path> [TradePreference] Lot_size_multiplier = <# of Stocks to Buy per Signal> StockList = <Subscribed Stocks in List Format> [Backtesting.Commission.HK] Fixed_Charge = <Fixed Transaction Fee and Tax in HKD - 15.5> Perc_Charge = <Percentage Transaction Fee in % - 0.1097> [Email] Port = <Server SMTP Setting> Smtp_server = <Server SMTP Setting> Sender = <Sender Email Address - account1@example.com> Login = <Sender Email Address - account1@example.com> Password = <Sender Email Password> SubscriptionList = ["account1@example.com", "account2@example.com"] ``` **IMPORTANT NOTE:** The format may be changed in later commits. Please refer to this README if exception is raised. ### 1. Install Dependencies Install using [conda](https://docs.conda.io/en/latest/): conda create --name <env> --file requirements.txt ### 2. Install FutuOpenD For **Windows/MacOS/CentOS/Ubuntu**: https://www.futunn.com/download/OpenAPI ### 3. Initialize SQLite Database Go to [SQLite official website](https://www.sqlite.org/quickstart.html) and follow the QuickStart instruction to install SQLite tools in the device. Create a folder named 'database' in the root folder, and execute the SQLite DDL file stored in *./util/database_ddl.sql* . ``` ./ ├── database │ └── stock_data.sqlite ``` ### 4. Download Data (e.g. 1M Data for max. 2 Years) For **Windows**: python main.py -u For **MacOS/Linux**: python3 main.py -u ### 4. Enjoy :smile: ## Usages Update all `K_1M` and `K_DAY` interval historical K-line data python main.py -u / python main.py --update **IMPORTANT NOTE:** This will not override existing historical data if the file exists. If you want to refresh all data, use the following command instead (WITH CAUTION!) python main.py -fu / python main.py --force_update Store all data from CSV to SQLite Database python main.py -d / python main.py --database Execute High-Frequency Trading (HFT) with a Pre-defined Strategy python main.py -s MACD_Cross / python main.py --strategy MACD_Cross Execute Stock Filtering with Pre-defined Filtering Strategies python main.py -f Volume_Threshold Price_Threshold / python main.py --filter Volume_Threshold Price_Threshold ----------- ## Contributor [Bill Chan -- Main Developer](https://github.com/billpwchan/)