6 releases

0.1.5 Nov 16, 2024
0.1.4 Oct 7, 2024
0.1.2 Sep 28, 2024

#25 in Finance

Download history 258/week @ 2024-09-23 99/week @ 2024-09-30 313/week @ 2024-10-07 17/week @ 2024-10-14 97/week @ 2024-11-11 36/week @ 2024-11-18

133 downloads per month
Used in 3 crates

MIT/Apache

340KB
10K SLoC

Qust

Qust is a Rust libraries for building live-trading and back-test systems. It has the following features:

  • Fast: It's way to handle or to save the kline data, tick data and strategy makes the backtest and live trading fast.
  • Extensible: It provide many ways to build a strategy, and new ways can be implemented by needs, so that you can focus what you care. You can build a simple strategy or complicated one, then backtest it on kline data(for quick scruch) or tick data, on put it on live trading directly. For example, you can build a strategy by following ways:
    1. Accept kline flow, and return a target position.
    2. Accept tick data flow, and return a target position.
    3. Accept tick data flow, and return an order action.
    4. Accept kline and tick flow, return a target positon or an order action.
    5. Accept kline flow, and return a bool.(a least two of it make a strategy, one for open position, another for close)
    6. Add filter conditions to an existed strategy.
    7. Add algorithm method to an existed strategy.
    8. Add order matching methods when backtest a strategy.
    9. Add valitality manager to strategies.
    10. Add portoflio manager to a pool of strategies. and so on.

See this notebook Example for more detail.

Examples

Add this to Cargo.toml:

qust-derive = { version = ">=0.1" }
qust-ds = { version = ">=0.1" }
qust = { version = ">=0.1" }
qust-api = { version = ">=0.1"}
qust-io = {  version = ">=0.1"}
serde = "*"
serde_json = "*"
itertools = "*"
typetag = "*"
tokio = "*"
ta = { version = "0.5.0" }

You can build a strategy basing on kline data and backtest in on kline:

use qust_derive::*;
use qust_ds::prelude::*;
use qust::prelude::*;
use qust_api::prelude::*;
use qust_io::prelude::*;
use ta::{ Next, indicators::SimpleMovingAverage as SMA };

#[ta_derive2]
pub struct TwoMaStra {
    pub short_period: usize,
    pub long_period: usize,
}

#[typetag::serde]
impl Ktn for TwoMaStra {
    fn ktn(&self,_di: &Di) -> RetFnKtn {
        let mut last_norm_hold = NormHold::No;
        let mut short_ma = SMA::new(self.short_period).unwrap();
        let mut long_ma = SMA::new(self.long_period).unwrap();
        let mut last_short_value = 0f64;
        let mut last_long_value = 0f64;
        Box::new(move |di_kline| {
            let c = di_kline.di.c()[di_kline.i] as f64;
            let short_value = short_ma.next(c);
            let long_value = long_ma.next(c);
            match last_norm_hold {
                NormHold::No if di_kline.i != 0 => {
                    if last_short_value < last_long_value && short_value >= long_value {
                        last_norm_hold = NormHold::Lo(1.);
                    }
                }
                NormHold::Lo(_) if short_value < long_value => {
                    last_norm_hold = NormHold::No;
                }
                _ => {}
            }
            last_short_value = short_value;
            last_long_value = long_value;
            last_norm_hold.clone()
        })
    }
}

#[tokio::main]
async fn main() {
    let di = read_remote_kline_data().await;
    let two_ma_stra = TwoMaStra { short_period: 9, long_period: 20 };
    let two_ma_stra_ptm: Ptm = two_ma_stra.ktn_box().to_ktn().to_ptm();
    let pnl_res_dt: PnlRes<dt> = two_ma_stra_ptm.bt_kline((&di, cs1));
    pnl_res_dt.to_csv("pnl_res_dt.csv"); // save the pnl to local csv;
}

更新 version: 0.1.5

  1. 支持tick级别的横截面,目前不支持k线级别,可以在tick里面手动更新k线。需要指定各个ticker的到达时间,详见例子;
  2. 每个策略(ApiBridgeBox)都有自身的订单管理,api程序停止运行后,到下次重开程序,中间过程中如果没有手动开平仓,历史的订单会被读取

Dependencies

~8–11MB
~190K SLoC