Analyzing stock has never been easier.
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安裝
在任意平台上,皆可安裝 FinLab Package,我們支援 Windows、MacOS、Linux,並且甚至是 Pyodide! 以新手來說,推薦的使用方式是直接在 Google Colab,來使用。 Google Colab 可以線上產生一個執行 Python 的環境,使用者不需額外在本機安裝任何程式,即可開始使用。
=== ":octicons-code-16: FinLab 實驗室"
打開選股策略頁面 https://ai.finlab.tw/strategies 並點選「建立策略」即可開始使用。
=== ":octicons-code-16: Google Colab" ``` py # 打開 Colab: https://colab.research.google.com/ 新增筆記本 # 在 Colab 中任意 Cell 中執行
!pip install finlab > log.txt
# 即可
```
=== ":octicons-code-16: 本機 Python" ``` py # 在 anacnoda prompt 中執行
pip install finlab
```
!!! tip annotate "可能存在相容性問題"
用「pip install finlab」方法安裝,可能會造成 Package 不相容的問題,假如您希望得到更穩定的版本,請參考「Docker」安裝。
=== ":octicons-code-16: Docker 安裝"
* 前往 Docker 官方網站:https://www.docker.com/products/docker-desktop。
* 在下載頁面中,按一下「Download Docker Desktop」按鈕。
* 完成下載後,執行安裝程式並按照提示進行安裝。
### 2. 下載 FinLab 的 Jupyter 映像檔
在安裝 Docker 完成後,請按照以下步驟從 Docker Hub 下載 FinLab 的 Jupyter 映像檔:
開啟終端機或命令提示字元。
輸入以下命令以下載 FinLab 的 Jupyter 映像檔:
```bash
docker pull finlab/jupyter-finlab
```
此命令將會從 Docker Hub 下載映像檔,請耐心等待下載完成。
### 3. 執行映像檔並連接到 8888:8888 的 IP 位址
下載完成後,您可以使用以下命令執行映像檔:
```bash
docker run -p 8888:8888 finlab/jupyter-finlab
```
此命令將會啟動一個容器並將容器內部的 8888 埠口映射到您的本機 8888 埠口。請耐心等待容器啟動完成,終端機中將會顯示一個 URL,例如:
```bash
http://127.0.0.1:8888/?token=xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx
```
請複製該 URL,稍後您將使用它來連接到 JupyterLab。
### 4. 使用 JupyterLab 和 FinLab 套件
現在您已經成功啟動了 JupyterLab,請按照以下步驟進一步使用 JupyterLab 和 FinLab 套件:
在瀏覽器中打開剛剛複製的 URL。這將會顯示 JupyterLab 的介面。
在 JupyterLab 的介面中,您可以創建新的 Jupyter Notebook 。
在 Notebook 中,您可以使用 FinLab 提供的功能和套件。FinLab 是一個針對金融數據分析和策略回測的 Python 套件,詳細的使用方法請參考 FinLab 的官方文件。
</div>
下載資料
輸入以下程式碼,即可下載資料。可以查詢有哪些歷史資料可以下載。
from finlab import data
data.get('price:收盤價')
| date | 0015 | 0050 | 0051 | 0052 | 0053 |
|---|---|---|---|---|---|
| 2007-04-23 | 9.54 | 57.85 | 32.83 | 38.4 | nan |
| 2007-04-24 | 9.54 | 58.1 | 32.99 | 38.65 | nan |
| 2007-04-25 | 9.52 | 57.6 | 32.8 | 38.59 | nan |
| 2007-04-26 | 9.59 | 57.7 | 32.8 | 38.6 | nan |
| 2007-04-27 | 9.55 | 57.5 | 32.72 | 38.4 | nan |
撰寫策略
可以用非常簡單的 Pandas 語法來撰寫策略邏輯,以創新高的策略來說,可以用以下的寫法:
from finlab import data
close = data.get('price:收盤價')
# 創三百個交易日新高
position = close >= close.rolling(300).max()
position
| date | 0015 | 0050 | 0051 | 0052 | 0053 |
|---|---|---|---|---|---|
| 2007-04-23 00:00:00 | False | False | False | False | False |
| 2007-04-24 00:00:00 | False | False | False | False | False |
| 2007-04-25 00:00:00 | False | False | False | False | False |
| 2007-04-26 00:00:00 | False | False | False | True | False |
| 2007-04-27 00:00:00 | False | False | False | False | False |
這邊的 position 是一個 False/True 的查詢表,當數值為 True ,代表該股票在當天有創新高,而數字 False 則代表沒有創新高。由於創新高的股票很少,上面的範例中,只有少數股票的數值會是 True。
假設我們希望每個月底,搜尋上表中數值為 True 的股票並且買入持有一個月,可以用以下的語法:
回測績效
from finlab import backtest
report = backtest.sim(position, resample='M')
report.display()
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