feat: add KdCrossOver, MAGoldenDeathCrossOver, InstitutionalInvestors…

…OverBuy, ShortSaleMarginPurchaseRatio (#277)

* featL add KdCrossOver

* feat: add MAGoldenDeathCrossOver

* feat: add auto add _additional_dataset

* feat: add short_sale_margin_purchase_ratio

.github/workflows/python-package.yml

@@ -29,6 +29,7 @@ jobs:
         env:
           FINMIND_USER: ${{ secrets.FINMIND_USER }}
           FINMIND_PASSWORD: ${{ secrets.FINMIND_PASSWORD }}
+          FINMIND_API_TOKEN: ${{ secrets.FINMIND_TOKEN }}
         run: |
           python genenv.py
           pipenv sync

FinMind/data/finmind_api.py

@@ -120,7 +120,7 @@ def get_data(
         :param params: finmind api參數
         :return:
         """
-        logger.info(f"download {dataset}")
+        logger.info(f"download {dataset}, data_id: {data_id}")
         params = dict(
             dataset=dataset,
             data_id=data_id,

FinMind/indicators/__init__.py

@@ -1,13 +1,29 @@
-from FinMind.indicators.kd import add_kd_indicators
 from FinMind.indicators.bias import add_bias_indicators
 from FinMind.indicators.continue_holding import add_continue_holding_indicators
 from FinMind.indicators.institutional_investors_follower import (
     add_institutional_investors_follower,
 )
+from FinMind.indicators.institutional_investors_over_buy import (
+    add_institutional_investors_over_buy_indicators,
+)
+from FinMind.indicators.kd import add_kd_indicators
+from FinMind.indicators.kd_crossover import (
+    add_kd_golden_death_cross_over_indicators,
+)
+from FinMind.indicators.ma_cross_orver import (
+    add_ma_golden_death_cross_orver_indicators,
+)
+from FinMind.indicators.short_sale_margin_purchase_ratio import (
+    add_short_sale_margin_purchase_ratio_indicators,
+)
 
 INDICATORS_MAPPING = dict(
     KD=add_kd_indicators,
     BIAS=add_bias_indicators,
     ContinueHolding=add_continue_holding_indicators,
     InstitutionalInvestorsFollower=add_institutional_investors_follower,
+    KDGoldenDeathCrossOver=add_kd_golden_death_cross_over_indicators,
+    MAGoldenDeathCrossOver=add_ma_golden_death_cross_orver_indicators,
+    InstitutionalInvestorsOverBuy=add_institutional_investors_over_buy_indicators,
+    ShortSaleMarginPurchaseRatio=add_short_sale_margin_purchase_ratio_indicators,
 )

FinMind/indicators/institutional_investors_follower.py

@@ -37,7 +37,7 @@ def add_institutional_investors_follower(
         on=["stock_id", "date"],
         how="left",
     ).fillna(0)
-    stock_price["InstitutionalInvestorsOverBuy"] = __detect_Abnormal_Peak(
+    stock_price["InstitutionalInvestorsFollower"] = __detect_Abnormal_Peak(
         y=stock_price["diff"].values,
         lag=n_days,
         threshold=3,

FinMind/indicators/institutional_investors_over_buy.py

@@ -0,0 +1,56 @@
+import numpy as np
+import pandas as pd
+
+from FinMind.schema.data import Dataset
+
+
+def _taiwan_stock_institutional_investors_buy_sell_group_by(
+    taiwan_stock_institutional_investors_buy_sell: pd.DataFrame,
+) -> pd.DataFrame:
+    taiwan_stock_institutional_investors_buy_sell[["sell", "buy"]] = (
+        taiwan_stock_institutional_investors_buy_sell[["sell", "buy"]]
+        .fillna(0)
+        .astype(int)
+    )
+    taiwan_stock_institutional_investors_buy_sell = (
+        taiwan_stock_institutional_investors_buy_sell.groupby(
+            ["date", "stock_id"], as_index=False
+        ).agg({"buy": np.sum, "sell": np.sum})
+    )
+    taiwan_stock_institutional_investors_buy_sell[
+        "InstitutionalInvestorsOverBuy"
+    ] = (
+        taiwan_stock_institutional_investors_buy_sell["buy"]
+        - taiwan_stock_institutional_investors_buy_sell["sell"]
+    )
+    return taiwan_stock_institutional_investors_buy_sell
+
+
+def add_institutional_investors_over_buy_indicators(
+    stock_price: pd.DataFrame, additional_dataset_obj, **kwargs
+) -> pd.DataFrame:
+    """
+    url: "https://blog.above.tw/2018/08/15/%E7%B1%8C%E7%A2%BC%E9%9D%A2%E7%9A%84%E9%97%9C%E9%8D%B5%E6%8C%87%E6%A8%99%E6%9C%89%E5%93%AA%E4%BA%9B%EF%BC%9F/"
+    summary:
+        策略概念:法人買超股票會上漲, 反之亦然
+        策略規則: 法人買超, 買
+                法人賣超, 賣
+    """
+    stock_price = stock_price.sort_values("date")
+    taiwan_stock_institutional_investors_buy_sell = getattr(
+        additional_dataset_obj, Dataset.TaiwanStockInstitutionalInvestorsBuySell
+    )
+    taiwan_stock_institutional_investors_buy_sell = (
+        _taiwan_stock_institutional_investors_buy_sell_group_by(
+            taiwan_stock_institutional_investors_buy_sell
+        )
+    )
+    stock_price = pd.merge(
+        stock_price,
+        taiwan_stock_institutional_investors_buy_sell[
+            ["stock_id", "date", "InstitutionalInvestorsOverBuy"]
+        ],
+        on=["stock_id", "date"],
+        how="left",
+    ).fillna(0)
+    return stock_price

FinMind/indicators/kd_crossover.py

@@ -0,0 +1,62 @@
+import numpy as np
+import pandas as pd
+from ta.momentum import StochasticOscillator
+
+
+def add_kd_golden_death_cross_over_indicators(
+    stock_price: pd.DataFrame, k_days: int = 9, **kwargs
+) -> pd.DataFrame:
+    """
+    url: "http://smart.businessweekly.com.tw/Reading/WebArticle.aspx?id=68129&p=2"
+    summary: 日KD黃金交叉和死亡交叉
+            日K線 < 日D線，翻轉成，日K線 > 日D線 稱為黃金交叉
+            日K線 > 日D線，翻轉成，日K線 < 日D線 稱為死亡交叉
+            黃金交叉進場，死亡交叉出場
+    """
+    stock_price = stock_price.sort_values("date")
+    kd = StochasticOscillator(
+        high=stock_price["max"],
+        low=stock_price["min"],
+        close=stock_price["close"],
+        n=k_days,
+    )
+    rsv_ = kd.stoch().fillna(50)
+    _k = np.zeros(stock_price.shape[0])
+    _d = np.zeros(stock_price.shape[0])
+    for i, r in enumerate(rsv_):
+        if i == 0:
+            _k[i] = 50
+            _d[i] = 50
+        else:
+            _k[i] = _k[i - 1] * 2 / 3 + r / 3
+            _d[i] = _d[i - 1] * 2 / 3 + _k[i] / 3
+    stock_price["K"] = _k
+    stock_price["D"] = _d
+    stock_price.index = range(len(stock_price))
+    stock_price["diff"] = stock_price["K"] - stock_price["D"]
+    stock_price.loc[(stock_price.index < k_days), "diff"] = np.nan
+    stock_price["diff_sign"] = stock_price["diff"].map(
+        lambda x: 1 if x >= 0 else (-1 if x < 0 else 0)
+    )
+    stock_price["diff_sign_yesterday"] = (
+        stock_price["diff_sign"].shift(1).fillna(0).astype(int)
+    )
+    stock_price["KDGoldenDeathCrossOver"] = 0
+    stock_price.loc[
+        (
+            (stock_price["diff_sign"] > 0)
+            & (stock_price["diff_sign_yesterday"] < 0)
+        ),
+        "KDGoldenDeathCrossOver",
+    ] = 1
+    stock_price.loc[
+        (
+            (stock_price["diff_sign"] < 0)
+            & (stock_price["diff_sign_yesterday"] > 0)
+        ),
+        "KDGoldenDeathCrossOver",
+    ] = -1
+    stock_price = stock_price.drop(
+        ["diff", "diff_sign", "diff_sign_yesterday"], axis=1
+    )
+    return stock_price

FinMind/indicators/ma_cross_orver.py

@@ -0,0 +1,69 @@
+import pandas as pd
+from ta.trend import SMAIndicator
+
+
+def add_ma_golden_death_cross_orver_indicators(
+    stock_price: pd.DataFrame,
+    ma_short_term_days: int = 10,
+    ma_long_term_days: int = 30,
+    **kwargs,
+) -> pd.DataFrame:
+    """
+    url:
+    "https://www.cmoney.tw/learn/course/technicalanalysisfast/topic/1811"
+
+    summary:
+    均線黃金交叉
+    以短線操作來說，當 5日均線 向上突破 20日均線
+    也就是短期的平均買進成本大於長期平均成本
+    代表短期買方的力道較大，市場上大多數人獲利
+    市場易走出「多頭」的趨勢，進而帶動長期均線向上，讓股價上漲機率較大
+    短期線 突破 長期線(黃金交叉)，進場
+    長期線 突破 短期線(死亡交叉)，出場
+    """
+    stock_price = stock_price.sort_values("date")
+    stock_price[f"ma{ma_short_term_days}"] = SMAIndicator(
+        stock_price["close"], ma_short_term_days
+    ).sma_indicator()
+    stock_price[f"ma{ma_long_term_days}"] = SMAIndicator(
+        stock_price["close"], ma_long_term_days
+    ).sma_indicator()
+    stock_price["ma_diff"] = (
+        stock_price[f"ma{ma_short_term_days}"]
+        - stock_price[f"ma{ma_long_term_days}"]
+    )
+    stock_price["bool_signal"] = stock_price["ma_diff"].map(
+        lambda x: 1 if x > 0 else -1
+    )
+    stock_price["bool_signal_shift1"] = (
+        stock_price["bool_signal"].shift(1).fillna(0)
+    )
+    stock_price["bool_signal_shift1"] = stock_price[
+        "bool_signal_shift1"
+    ].astype(int)
+    stock_price["MAGoldenDeathCrossOver"] = 0
+    stock_price.loc[
+        (
+            (stock_price["bool_signal"] > 0)
+            & (stock_price["bool_signal_shift1"] < 0)
+        ),
+        "MAGoldenDeathCrossOver",
+    ] = 1
+    stock_price.loc[
+        (
+            (stock_price["bool_signal"] < 0)
+            & (stock_price["bool_signal_shift1"] > 0)
+        ),
+        "MAGoldenDeathCrossOver",
+    ] = -1
+    stock_price = stock_price.drop(
+        [
+            "ma_diff",
+            "bool_signal",
+            "bool_signal_shift1",
+            f"ma{ma_short_term_days}",
+            f"ma{ma_long_term_days}",
+        ],
+        axis=1,
+    )
+    return stock_price

FinMind/indicators/short_sale_margin_purchase_ratio.py

@@ -0,0 +1,51 @@
+import numpy as np
+import pandas as pd
+
+from FinMind.schema.data import Dataset
+
+
+def _create_short_sale_margin_purchase_today_ratio(
+    taiwan_stock_margin_purchase_shortSale: pd.DataFrame,
+) -> pd.DataFrame:
+    taiwan_stock_margin_purchase_shortSale[
+        ["ShortSaleTodayBalance", "MarginPurchaseTodayBalance"]
+    ] = taiwan_stock_margin_purchase_shortSale[
+        ["ShortSaleTodayBalance", "MarginPurchaseTodayBalance"]
+    ].astype(
+        int
+    )
+    taiwan_stock_margin_purchase_shortSale["ShortSaleMarginPurchaseRatio"] = (
+        taiwan_stock_margin_purchase_shortSale["ShortSaleTodayBalance"]
+        / taiwan_stock_margin_purchase_shortSale["MarginPurchaseTodayBalance"]
+    )
+    return taiwan_stock_margin_purchase_shortSale
+
+
+def add_short_sale_margin_purchase_ratio_indicators(
+    stock_price: pd.DataFrame, additional_dataset_obj, **kwargs
+) -> pd.DataFrame:
+    """
+    url: "https://blog.above.tw/2018/08/15/%E7%B1%8C%E7%A2%BC%E9%9D%A2%E7%9A%84%E9%97%9C%E9%8D%B5%E6%8C%87%E6%A8%99%E6%9C%89%E5%93%AA%E4%BA%9B%EF%BC%9F/"
+    summary:
+        策略概念: 券資比越高代表散戶看空，這時候賣可以跟大部分散戶進行相反的操作，反之亦然
+        策略規則: 券資比>=30%, 賣
+                券資比<30%, 買
+    """
+    stock_price = stock_price.sort_values("date")
+    taiwan_stock_margin_purchase_shortSale = getattr(
+        additional_dataset_obj, Dataset.TaiwanStockMarginPurchaseShortSale
+    )
+    taiwan_stock_margin_purchase_shortSale = (
+        _create_short_sale_margin_purchase_today_ratio(
+            taiwan_stock_margin_purchase_shortSale
+        )
+    )
+    stock_price = pd.merge(
+        stock_price,
+        taiwan_stock_margin_purchase_shortSale[
+            ["stock_id", "date", "ShortSaleMarginPurchaseRatio"]
+        ],
+        on=["stock_id", "date"],
+        how="left",
+    ).fillna(0)
+    return stock_price

FinMind/schema/indicators.py

@@ -3,6 +3,7 @@
 
 from pydantic import BaseModel
 
+from FinMind.schema.data import Dataset
 from FinMind.schema.rule import Rule
 
 
@@ -17,29 +18,77 @@ class Indicators(str, Enum):
         Regular fixed-amount buy-and-hold strategy, buy once every n days,
         defalt 30
     """
-    InstitutionalInvestorsFollower = "InstitutionalInvestorsOverBuy"
+    InstitutionalInvestorsFollower = "InstitutionalInvestorsFollower"
     """
         the formula of InstitutionalInvestorsFollower is n_days,
         if InstitutionalInvestors over buy n days,
         but the stock has not risen,
         so we will follow up and buy,
         defalt 10
     """
+    KDGoldenDeathCrossOver = "KDGoldenDeathCrossOver"
+    """
+        the formula of KD is k_days, defalt 9,
+
+        Indicators
+            1 means Golden Cross Over,
+            -1 means Death Cross Over
+    """
+    MAGoldenDeathCrossOver = "MAGoldenDeathCrossOver"
+    """
+        the formula of MA is [ma_short_term_days, ma_long_term_days]
+        
+        defalt [10, 30],
+
+        Indicators
+            1 means Golden Cross Over,
+            -1 means Death Cross Over
+    """
+    InstitutionalInvestorsOverBuy = "InstitutionalInvestorsOverBuy"
+    """
+        the formula is None, it just calculates ( Buy - Sell )
+
+        Indicators
+            > 0 means OverBuy,
+            < 0 means OverSell
+    """
+    ShortSaleMarginPurchaseRatio = "ShortSaleMarginPurchaseRatio"
+    """
+        the formula is None, it just calculates ( ShortSaleTodayBalance / MarginPurchaseTodayBalance )
+    """
 
 
 class IndicatorsParams(str, Enum):
     KD = "k_days"
     BIAS = "ma_days"
     ContinueHolding = "buy_freq_day"
     InstitutionalInvestorsFollower = "n_days"
+    KDGoldenDeathCrossOver = "k_days"
+    MAGoldenDeathCrossOver = ["ma_short_term_days", "ma_long_term_days"]
+    InstitutionalInvestorsOverBuy = None
+    ShortSaleMarginPurchaseRatio = None
 
 
 class IndicatorsInfo(BaseModel):
     name: Indicators
-    formula_value: typing.Union[int, float, str] = None
+    formula_value: typing.Union[
+        typing.List[typing.Union[int, float, str]], int, float, str
+    ] = None
 
 
 class AddBuySellRule(BaseModel):
     indicators: Indicators
     more_or_less_than: Rule
-    threshold: typing.Union[int, float, str]
+    threshold: typing.Union[float, int, str]
+
+
+class AdditionalDataset(str, Enum):
+    InstitutionalInvestorsFollower = (
+        Dataset.TaiwanStockInstitutionalInvestorsBuySell.value
+    )
+    InstitutionalInvestorsOverBuy = (
+        Dataset.TaiwanStockInstitutionalInvestorsBuySell.value
+    )
+    ShortSaleMarginPurchaseRatio = (
+        Dataset.TaiwanStockMarginPurchaseShortSale.value
+    )