富途量化程序-python

<div align="center"> <img alt="FutuAlgo Logo" src="https://raw.githubusercontent.com/billpwchan/futu_algo/master/images/logo.png" width="400px" /> **billpwchan/futu-algo API Reference Documentation** <a href="https://www.buymeacoffee.com/billpwchan98" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/default-orange.png" alt="Buy Me A Coffee" height="41" width="174"></a> [](https://app.codacy.com/gh/billpwchan/futu_algo?utm_source=github.com&utm_medium=referral&utm_content=billpwchan/futu_algo&utm_campaign=Badge_Grade_Settings) [](https://github.com/billpwchan/futu_algo/issues) [](https://github.com/billpwchan/futu_algo/blob/master/LICENSE) [](https://github.com/billpwchan/futu_algo/blob/master/LICENSE) [](https://github.com/billpwchan/futu_algo/commits/master) [](https://github.com/billpwchan/futu_algo/commits/master) [](https://github.com/billpwchan/futu_algo) [](https://github.com/billpwchan/futu_algo) </div> ## Highlights - **Supported Platforms and Markets** Futu_algo is a algorithmic trading solution developed based on FutuOpenD and FutuOpenAPI. Fully support FutuNiuNiu and FutuMooMoo users in Hong Kong stock market. *(More market support is coming soon)* - **Historical K-Line Data** Allow users to automatically downloading historical data for your interested stocks into CSV and storing to SQLite database for backtesting. *(up to 1M level for max. 2 years, or 1D level for max. 10 years)* - **Backtesting Trading Strategies (BETA)** Backtest your own trading strategies on historical data with a summarized reports and visualizations using Pyfolio. For more demanding users, feel free to other commercial solutions such as Amibroker for backtesting. - **Algorithmic Trading** Real-time low-latency trading features that allows applying your own basket of trading strategies on your stock pool. User can specify the trading strategy to be used for each stock based on their preference. ***EXAMPLE: 0.01s/STOCK TO DECIDE BUY/SELL ORDER WITH A 3-TECHNICAL INDICATORS STRATEGY (MACD, KDJ AND CLOSE PRICE)*** - **Advanced Stock Screener** Screens high-quality stocks using your own stock screening strategies, and notify your friends using the email subscription feature. **Feel free to subscribe by submitting this Google Form! https://forms.gle/C9y4kyYUArKmFzu86** - **Trading Strategy Editor** Write your own trading strategy following a simple template (buy, sell, calculate technical indicators). Common strategies such as MACD and KDJ-based trading rules are provided as guidelines. - **GUI Support (Upcoming)** Easy-to-use GUI for users to adjust their configurations, trading, downloading data and filtering stocks within one application. No longer need to type any command for trading! ## Version Guidance | FutuAlgo Release | Futu OpenAPI Specification | |:-----------------|:---------------------------| | 1.0 | 6.1 | ## 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 [TradePreference] LotSizeMultiplier = <# of Stocks to Buy per Signal> MaxPercPerAsset = <Maximum % of Capital Allocated per Asset> StockList = <Subscribed Stocks in List Format> [Backtesting.Commission.HK] FixedCharge = <Fixed Transaction Fee and Tax in HKD - 15.5> PercCharge = <Percentage Transaction Fee in % - 0.1097> [Email] Port = <Server SMTP Setting> SmtpServer = <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"] [TuShare.Credential] token = 2134342ABC2D03780772038A7816 ``` **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/): ```bash conda env create -f environment.yml ``` To export current environment, use the following command ```bash conda env export > environment.yml ``` To update current environment with the latest dependencies, use the following command ```bash conda env update --name futu_trade --file environment.yml --prune ``` For GitHub Actions - with pip dependencies, use the following command ```bash pip list --format=freeze > requirements.txt ``` ### 2. Install FutuOpenD For **Windows/MacOS/CentOS/Ubuntu**: https://www.futunn.com/download/OpenAPI Please do make sure that you have at least a LV1 subscription level on your interested quotes. For details, please refer to https://openapi.futunn.com/futu-api-doc/qa/quote.html **MAKE SURE YOU LOGIN TO FUTU OPEND FIRST BEFORE STARTING FUTU_ALGO!** ### 4. Download Data (e.g. 1M Data for max. 2 Years) For **Windows**: python main_backend.py --force_update For **MacOS/Linux**: python3 main_backend.py --force_update ### 4. Enjoy :smile: ## Command-line Interface Usages ### Historical Data Download & Processing Update all `K_1M` and `K_DAY` interval historical K-line data python main_backend.py -u / python main_backend.py --update **IMPORTANT NOTE:** This will not override existing historical data if the file exists. It will automatically detect the latest stock data you have downloaded in the folder and resume from there. If you want to refresh all data, use the following command instead (WITH CAUTION!) python main_backend.py -fu / python main_backend.py --force_update ### Algorithmic Trading Execute Algorithmic Trading with a Pre-defined Strategy (By default use **1M data**) python main_backend.py -s MACD_Cross / python main_backend.py --strategy MACD_Cross If you would like to use another time interval based date (e.g., Day data), use the following command python main_backend.py -s MACD_Cross --time_interval K_DAY If you do not have a pre-defined stock list in `config.ini`, then you can just trade the Top 30 HSI stocks python main_backend.py -s MACD_Cross --include_hsi --time_interval K_DAY **IMPORTANT NOTE:** The supported time intervals are: K_1M, K_30M, K_5M, K_15M, K_30M, K_60M, K_DAY, K_WEEK, K_MON, K_YEAR. ### Stock Filtering and Email Subscription Execute Stock Filtering with Pre-defined Filtering Strategies with Email Title "MACD_Cross_Technique" in HK and China (Shanghai and Shenzhen) Stock Market python main_backend.py -f Volume_Threshold Price_Threshold -en MACD_Cross_Technique -m HK CHINA ## GUI Usages Start the GUI with `main.py` (**NOT FINISHED YET**) python main.py ## Future Plans - [ ] [NEED A GREAT NAME FOR THIS ALGO TRADE!!](https://github.com/billpwchan/futu_algo/issues/23) - [x] [Custom Backtesting Time Interval]() - [x] [Dynamic Instantiation](https://github.com/billpwchan