Hikyuu 1.1.5 has been released, which is a quantitative trading research framework. The version update is as follows:
1. Import tool repair weight information import
2. Support MySQL as storage engine (configured by import tool)
3. Rectify python api naming, class according to uppercase hump, methods and functions are unified to lowercase and underline
4. Add TimeDelta to facilitate date and time Calculation, such as: Datetime(202011090000) + TimeDelta(1). Datetime.timedelta can be used in python
4. Portfolio (asset portfolio algorithm), Allocatefunds (fund allocation algorithm), Selector (transaction object selection algorithm) are available
5. The number of transactions is changed from integer to float, which is convenient to support digital currency, foreign exchange, etc.
6 . Increase the strategy algorithm warehouse, welcome everyone to submit PR contribution public strategy: https://gitee.com/fasiondog/hikyuu_hub
Add local warehouse: add_local_hub('dev','/home/fasiondog/workspace/stockhouse')
Update reference: update_hub('default') to
get the strategy part of the specified warehouse: st = get_part('default.st.fixed_percent')
7. Other BUG fixes and optimizations
Hikyuu is a high-performance open source quantitative trading research framework based on C++/Python for strategy analysis and backtesting (currently used in the domestic stock market). Compared with other quantitative platforms or backtesting software, its uniqueness lies in: decomposing the complete strategy into different components, and by reusing different aspects of strategies, to maximize the reduction of the burden of writing strategies, such as common stop loss and money management Strategy, you only need to simply specify the existing stop loss or capital management strategy, you can complete different strategy combinations; at the same time, you can freely traverse all stocks and conduct comprehensive statistical analysis on the effect of the strategy. As the following example, simple and better different money management strategies. Getting started example: https://nbviewer.jupyter.org/github/fasiondog/hikyuu/blob/master/hikyuu/examples/notebook/000-Index.ipynb?flush_cache=True
For more information, see the project homepage: https://hikyuu.org