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update docs
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@albertandking
albertandking committed Sep 16, 2023
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217 changes: 208 additions & 9 deletions docs/quickstart.md
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```python
import pybroker as pb
from pybroker import Strategy, StrategyConfig
from pybroker import Strategy, StrategyConfig, ExecContext
from pybroker.ext.data import AKShare

print(pb.__version__)
```

1. 将 pybroker 模块导入为 `pb`，这是一个约定俗成的做法，方便后续使用。
1. 将 `pybroker` 模块导入为 `pb`，这是一个约定俗成的做法，方便后续使用。
2. 从 `pybroker` 中导入 `Strategy` 和 `StrategyConfig` 类，以及 `AKShare` 数据源。
3. `Strategy` 类是 pybroker 中的策略基类，所有的策略都需要继承该类。
4. `StrategyConfig` 类是 pybroker 中的策略配置基类，所有的策略配置都需要继承该类。
5. `AKShare` 类是 pybroker 中的数据源类，用于获取数据。
6. `pb.__version__` 属性用于获取 pybroker 的版本。

## 配置策略

Expand All @@ -25,25 +28,221 @@ config = StrategyConfig(initial_cash=500_000)
1. 创建一个策略配置对象，该对象用于配置策略的一些参数。
2. `initial_cash` 参数用于配置策略的初始资金，默认为 10 万。

```python
strategy = Strategy(data_source=AKShare(), start_date='20220101', end_date='20230916', config=config)
```

1. 创建一个策略对象，该对象用于运行策略。
2. `AKShare()` 参数用于配置策略的数据源，该数据源为 akshare。
3. `20220101` 参数用于配置策略的开始日期。
4. `20230916` 参数用于配置策略的结束日期。
5. `config` 参数用于配置策略的配置对象。
6. `strategy` 对象用于运行策略。
7. `strategy` 对象的 `config` 属性用于获取策略的配置对象。

## 定义规则

```python
def buy_low(ctx):
# If shares were already purchased and are currently being held, then return.
def buy_low(ctx: ExecContext):
# 如果当前已经持有仓位，则不再买入。
if ctx.long_pos():
return
# If the latest close price is less than the previous day's low price,
# then place a buy order.
# 如果当前的收盘价小于前一天的最低价，则下单买入。
if ctx.bars >= 2 and ctx.close[-1] < ctx.low[-2]:
# Buy a number of shares that is equal to 25% the portfolio.
# 计算买入的股票数量，该数量为当前资金的 25%。
ctx.buy_shares = ctx.calc_target_shares(0.25)
# Set the limit price of the order.
# 设置买入的限价，该限价为当前收盘价减去 0.01。
ctx.buy_limit_price = ctx.close[-1] - 0.01
# Hold the position for 3 bars before liquidating (in this case, 3 days).
# 设置持有仓位的时间，该时间为 3 个交易日。
ctx.hold_bars = 3
```

1. 定义一个名为 `buy_low` 的函数，该函数用于判断是否需要买入。
2. `ctx` 参数是一个上下文对象，该对象包含了策略运行时的一些数据。
3. `ctx.long_pos()` 方法用于判断是否已经持有仓位。
4. `ctx.bars` 属性用于获取当前的交易日。

## 运行策略

可以通过调用 `strategy.backtest()` 方法来进行策略回测：

```python
strategy.add_execution(fn=buy_low, symbols=['000001', '600000'])
result = strategy.backtest()
```

## 产看结果

### 查看订单

```python
print(result.orders)
```

```shell
type symbol date shares limit_price fill_price fees
id
1 buy 000001 2022-01-17 44 2822.91 2818.04 0.0
2 sell 000001 2022-01-20 44 NaN 2922.06 0.0
3 buy 000001 2022-01-25 42 2964.31 2922.88 0.0
4 buy 600000 2022-01-25 1497 84.20 83.74 0.0
5 sell 000001 2022-01-28 42 NaN 2791.23 0.0
.. ... ... ... ... ... ... ...
116 sell 000001 2023-08-29 57 NaN 2090.42 0.0
117 buy 000001 2023-08-30 57 2090.40 2072.54 0.0
118 buy 600000 2023-08-30 1525 78.33 78.24 0.0
119 sell 000001 2023-09-04 57 NaN 2114.79 0.0
120 sell 600000 2023-09-04 1525 NaN 78.44 0.0
[120 rows x 7 columns]
```

### 查看持仓

```python
print(result.positions)
```

```shell
long_shares short_shares ... margin unrealized_pnl
symbol date ...
000001 2022-01-17 44 0 ... 0.0 -572.00
2022-01-18 44 0 ... 0.0 1573.44
2022-01-19 44 0 ... 0.0 1430.44
600000 2022-01-25 1497 0 ... 0.0 -583.83
000001 2022-01-25 42 0 ... 0.0 -648.48
... ... ... ... ...
2023-08-30 57 0 ... 0.0 -648.66
600000 2023-08-31 1525 0 ... 0.0 -762.50
000001 2023-08-31 57 0 ... 0.0 -648.66
600000 2023-09-01 1525 0 ... 0.0 -457.50
000001 2023-09-01 57 0 ... 0.0 1111.50
[180 rows x 7 columns]
```

### 查看投资组合

```python
print(result.portfolio)
```

```shell

cash equity margin ... pnl unrealized_pnl fees
date ...
2022-01-04 500000.00 500000.00 0.0 ... 0.00 0.0 0.0
2022-01-05 500000.00 500000.00 0.0 ... 0.00 0.0 0.0
2022-01-06 500000.00 500000.00 0.0 ... 0.00 0.0 0.0
2022-01-07 500000.00 500000.00 0.0 ... 0.00 0.0 0.0
2022-01-10 500000.00 500000.00 0.0 ... 0.00 0.0 0.0
... ... ... ... ... ... ...
2023-09-11 480740.77 480740.77 0.0 ... -19259.23 0.0 0.0
2023-09-12 480740.77 480740.77 0.0 ... -19259.23 0.0 0.0
2023-09-13 480740.77 480740.77 0.0 ... -19259.23 0.0 0.0
2023-09-14 480740.77 480740.77 0.0 ... -19259.23 0.0 0.0
2023-09-15 480740.77 480740.77 0.0 ... -19259.23 0.0 0.0
[415 rows x 7 columns]
```

## 查看交易

```python
print(result.trades)
```

```shell
type symbol entry_date exit_date ... agg_pnl bars pnl_per_bar stop
id ...
1 long 000001 2022-01-17 2022-01-20 ... 4576.88 3 1525.63 bar
2 long 000001 2022-01-25 2022-01-28 ... -952.42 3 -1843.10 bar
3 long 600000 2022-01-25 2022-01-28 ... -2524.27 3 -523.95 bar
4 long 000001 2022-02-15 2022-02-18 ... -1441.10 3 361.06 bar
5 long 600000 2022-02-15 2022-02-18 ... -1188.31 3 84.26 bar
6 long 000001 2022-02-23 2022-02-28 ... -4084.39 3 -965.36 bar
7 long 000001 2022-03-07 2022-03-10 ... -7784.63 3 -1233.41 bar
8 long 600000 2022-03-07 2022-03-10 ... -11308.67 3 -1174.68 bar
9 long 000001 2022-04-12 2022-04-15 ... -9666.50 3 547.39 bar
10 long 600000 2022-04-22 2022-04-27 ... -11531.88 3 -621.79 bar
11 long 000001 2022-04-26 2022-04-29 ... -6642.94 3 1629.65 bar
12 long 000001 2022-05-05 2022-05-10 ... -13708.08 3 -2355.05 bar
13 long 600000 2022-05-09 2022-05-12 ... -13302.74 3 135.11 bar
14 long 000001 2022-05-25 2022-05-30 ... -15136.34 3 -611.20 bar
15 long 000001 2022-06-06 2022-06-09 ... -12149.79 3 995.52 bar
16 long 600000 2022-07-04 2022-07-07 ... -12961.75 3 -270.65 bar
17 long 000001 2022-07-07 2022-07-12 ... -12649.75 3 104.00 bar
18 long 000001 2022-07-14 2022-07-19 ... -13804.68 3 -384.98 bar
19 long 600000 2022-07-14 2022-07-19 ... -13897.56 3 -30.96 bar
20 long 000001 2022-07-22 2022-07-27 ... -13638.92 3 86.21 bar
21 long 000001 2022-08-01 2022-08-04 ... -17386.55 3 -1249.21 bar
22 long 600000 2022-08-01 2022-08-04 ... -19096.76 3 -570.07 bar
23 long 000001 2022-08-30 2022-09-02 ... -17780.24 3 438.84 bar
24 long 000001 2022-09-05 2022-09-08 ... -18770.81 3 -330.19 bar
25 long 000001 2022-09-27 2022-09-30 ... -19576.01 3 -268.40 bar
26 long 600000 2022-09-27 2022-09-30 ... -19844.44 3 -89.48 bar
27 long 000001 2022-10-20 2022-10-25 ... -24840.56 3 -1665.37 bar
28 long 600000 2022-10-24 2022-10-27 ... -25142.66 3 -100.70 bar
29 long 000001 2022-10-31 2022-11-03 ... -23732.16 3 470.17 bar
30 long 600000 2022-10-31 2022-11-03 ... -23891.56 3 -53.13 bar
31 long 000001 2022-11-17 2022-11-22 ... -24114.86 3 -74.43 bar
32 long 600000 2022-11-18 2022-11-23 ... -23060.95 3 351.30 bar
33 long 600000 2022-12-26 2022-12-29 ... -22132.15 3 309.60 bar
34 long 000001 2023-02-02 2023-02-07 ... -24748.17 3 -872.01 bar
35 long 600000 2023-02-02 2023-02-07 ... -25848.33 3 -366.72 bar
36 long 000001 2023-02-17 2023-02-22 ... -22225.27 3 1207.69 bar
37 long 600000 2023-02-24 2023-03-01 ... -22225.27 3 0.00 bar
38 long 000001 2023-02-27 2023-03-02 ... -18559.03 3 1222.08 bar
39 long 000001 2023-03-08 2023-03-13 ... -21546.07 3 -995.68 bar
40 long 600000 2023-03-13 2023-03-16 ... -21031.93 3 171.38 bar
41 long 000001 2023-03-20 2023-03-23 ... -20482.29 3 183.21 bar
42 long 000001 2023-04-12 2023-04-17 ... -18328.90 3 717.80 bar
43 long 000001 2023-04-20 2023-04-25 ... -22681.82 3 -1450.97 bar
44 long 600000 2023-05-15 2023-05-18 ... -21994.58 3 229.08 bar
45 long 000001 2023-05-24 2023-05-29 ... -22608.56 3 -204.66 bar
46 long 600000 2023-05-24 2023-05-29 ... -22411.35 3 65.74 bar
47 long 000001 2023-05-31 2023-06-05 ... -20623.85 3 595.83 bar
48 long 000001 2023-06-13 2023-06-16 ... -19349.29 3 424.85 bar
49 long 000001 2023-06-20 2023-06-27 ... -20805.29 3 -485.33 bar
50 long 600000 2023-06-20 2023-06-27 ... -22283.69 3 -492.80 bar
51 long 000001 2023-07-07 2023-07-12 ... -21681.77 3 200.64 bar
52 long 000001 2023-07-18 2023-07-21 ... -21079.85 3 200.64 bar
53 long 000001 2023-08-02 2023-08-07 ... -20218.60 3 287.08 bar
54 long 000001 2023-08-08 2023-08-11 ... -20433.78 3 -71.73 bar
55 long 600000 2023-08-08 2023-08-11 ... -21923.53 3 -496.58 bar
56 long 000001 2023-08-14 2023-08-17 ... -22844.77 3 -307.08 bar
57 long 600000 2023-08-14 2023-08-17 ... -23130.72 3 -95.32 bar
58 long 000001 2023-08-24 2023-08-29 ... -21972.48 3 386.08 bar
59 long 000001 2023-08-30 2023-09-04 ... -19564.23 3 802.75 bar
60 long 600000 2023-08-30 2023-09-04 ... -19259.23 3 101.67 bar
[60 rows x 13 columns]
```

## 策略代码

```python
import pybroker as pb
from pybroker import Strategy, StrategyConfig, ExecContext
from pybroker.ext.data import AKShare

print(pb.__version__)

config = StrategyConfig(initial_cash=500_000)
strategy = Strategy(data_source=AKShare(), start_date='20220101', end_date='20230916', config=config)


def buy_low(ctx: ExecContext):
# 如果当前已经持有仓位，则不再买入。
if ctx.long_pos():
return
# 如果当前的收盘价小于前一天的最低价，则下单买入。
if ctx.bars >= 2 and ctx.close[-1] < ctx.low[-2]:
# 计算买入的股票数量，该数量为当前资金的 25%。
ctx.buy_shares = ctx.calc_target_shares(0.25)
# 设置买入的限价，该限价为当前收盘价减去 0.01。
ctx.buy_limit_price = ctx.close[-1] - 0.01
# 设置持有仓位的时间，该时间为 3 个交易日。
ctx.hold_bars = 3


strategy.add_execution(fn=buy_low, symbols=['000001', '600000'])
result = strategy.backtest()
print(result.orders)
```
26 changes: 25 additions & 1 deletion main.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,27 @@
import pybroker as pb
from pybroker import Strategy, StrategyConfig, ExecContext
from pybroker.ext.data import AKShare

print(pb.__version__)
print(pb.__version__)

config = StrategyConfig(initial_cash=500_000)
strategy = Strategy(data_source=AKShare(), start_date='20220101', end_date='20230916', config=config)


def buy_low(ctx: ExecContext):
# 如果当前已经持有仓位，则不再买入。
if ctx.long_pos():
return
# 如果当前的收盘价小于前一天的最低价，则下单买入。
if ctx.bars >= 2 and ctx.close[-1] < ctx.low[-2]:
# 计算买入的股票数量，该数量为当前资金的 25%。
ctx.buy_shares = ctx.calc_target_shares(0.25)
# 设置买入的限价，该限价为当前收盘价减去 0.01。
ctx.buy_limit_price = ctx.close[-1] - 0.01
# 设置持有仓位的时间，该时间为 3 个交易日。
ctx.hold_bars = 3


strategy.add_execution(fn=buy_low, symbols=['000001', '600000'])
result = strategy.backtest()
print(result.orders)

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