kquant API document (0.3.6)

handle_stock_merge

액면병합을 처리하는 함수

handle_stock_merge(
    ratio: 'int',
    df_position: 'pd.DataFrame',
) -> tuple[pd.DataFrame, float]

• ratio (int): 병합비율
• df_position (pd.DataFrame): 변환 전 포지션 정보 데이터프레임
• 반환값 (tuple[pd.DataFrame, float]): 변환 후 포지션 정보 데이터프레임과 병합되지 못한 잔여 주식수(병합비율로 나눈 값)

예제 코드

import kquant as kq

df_result1, df_position1 = kq.backtest_update_stock_daily(
    "111870",
    30,
    "2023-08-16",
    init_cash=100_000,
)

[2023-08-16] 종목: 111870, 주문전 보유수량:      0 주문수량:     30, 매매수량:     30, 주문후 보유수량:     30

df_result1

	DATE	SYMBOL	PRICE	ORDER	QTY	TRADE_PRICE	POSITION	AVG_PRICE	FEE	TRADE_TAX	SLIPPAGE	CASHFLOW	CASH	HIST_VALUE	STOCK_VALUE	TOTAL_VALUE	REAL_PROFIT	UNREAL_PROFIT	PROFIT	HIGHWATERMARK	DRAWDOWN
0	2023-08-16	111870	2,970	30	30	2,970	30	2,970.0000	0	0	0	-89,100	10,900	89,100	89,100	100,000	0	0	0	100,000	0

df_position1

	DATE	SYMBOL	QTY	TRADE_PRICE	HIST_VALUE	FEE	NOT_DELETE
0	2023-08-16	111870	30	2,970	89,100	0	True

df_position1_adj, remainder = kq.handle_stock_merge(15, df_position1)

df_position1_adj

	DATE	SYMBOL	QTY	TRADE_PRICE	HIST_VALUE	FEE	NOT_DELETE
0	2023-08-16	111870	2	44,550	89,100	0	True

remainder

0.0

df_result2, df_position2 = kq.backtest_update_stock_daily(
   "111870",
   0,
   "2023-08-17",
   df_result1,
   df_position1_adj,
)

[2023-08-17] 종목: 111870, 주문전 보유수량:      2 주문수량:      0, 매매수량:      0, 주문후 보유수량:      2

df_result2

	DATE	SYMBOL	PRICE	ORDER	QTY	TRADE_PRICE	POSITION	AVG_PRICE	FEE	TRADE_TAX	SLIPPAGE	CASHFLOW	CASH	HIST_VALUE	STOCK_VALUE	TOTAL_VALUE	REAL_PROFIT	UNREAL_PROFIT	PROFIT	HIGHWATERMARK	DRAWDOWN
0	2023-08-16	111870	2,970	30	30	2,970	30	2,970.0000	0	0	0	-89,100	10,900	89,100	89,100	100,000	0	0	0	100,000	0
1	2023-08-17	111870	2,970	0	0	0	2	44,550.0000	0	0	0	0	10,900	89,100	5,940	16,840	0	-83,160	-83,160	100,000	83,160

df_position2

	DATE	SYMBOL	QTY	TRADE_PRICE	HIST_VALUE	FEE	NOT_DELETE
0	2023-08-16	111870	2	44,550	89,100	0	True