请问我在miniQMT中把K线数据和复权数据下载下来保存在外部数据库中后，怎么计算前复权

*******3497 · 发表于 2023-12-25 20:57:54

请问我在miniQMT中把K线数据和复权数据下载下来保存在外部数据库中后，怎么计算前复权和后复权

rzp · 发表于 2023-12-26 09:23:11

使用xtdata的接口时可以指定复权方式获取k线

*******3497 · 发表于 2023-12-26 09:47:35

rzp 发表于 2023-12-26 09:23
使用xtdata的接口时可以指定复权方式获取k线

我现在是把数据存到外部的数据库里面，没有在QMT里面，调xtdata的接口没用，需要自己算，想知道这个计算公式是怎么样的

张三 · 发表于 2023-12-26 11:58:45

本帖最后由张三于 2023-12-26 12:04 编辑

#coding:utf-8
import numpy as np
import pandas as pd
from xtquant import xtdata
#def gen_divid_ratio(quote_datas, divid_datas):
# drl = []
# for qi in range(len(quote_datas)):
# q = quote_datas.iloc[qi]
# dr = 1.0
# for di in range(len(divid_datas)):
# d = divid_datas.iloc[di]
# if d.name <= q.name:
# dr *= d['dr']
# drl.append(dr)
# return pd.DataFrame(drl, index = quote_datas.index, columns = quote_datas.columns)
def gen_divid_ratio(quote_datas, divid_datas):
drl = []
dr = 1.0
qi = 0
qdl = len(quote_datas)
di = 0
ddl = len(divid_datas)
while qi < qdl and di < ddl:
qd = quote_datas.iloc[qi]
dd = divid_datas.iloc[di]
if qd.name >= dd.name:
dr *= dd['dr']
di += 1
if qd.name <= dd.name:
drl.append(dr)
qi += 1
while qi < qdl:
drl.append(dr)
qi += 1
return pd.DataFrame(drl, index = quote_datas.index, columns = quote_datas.columns)
def process_forward_ratio(quote_datas, divid_datas):
drl = gen_divid_ratio(quote_datas, divid_datas)
drlf = drl / drl.iloc[-1]
result = (quote_datas * drlf).apply(lambda x: round(x, 2))
return result
def process_backward_ratio(quote_datas, divid_datas):
drl = gen_divid_ratio(quote_datas, divid_datas)
result = (quote_datas * drl).apply(lambda x: round(x, 2))
return result
def process_forward(quote_datas1, divid_datas):
quote_datas = quote_datas1.copy()
def calc_front(v, d):
return round(
(v - d['interest'] + d['allotPrice'] * d['allotNum'])
/ (1 + d['allotNum'] + d['stockBonus'] + d['stockGift'])
, 2
)
for qi in range(len(quote_datas)):
q = quote_datas.iloc[qi]
for di in range(len(divid_datas)):
d = divid_datas.iloc[di]
if d.name <= q.name:
continue
q.iloc[0] = calc_front(q.iloc[0], d)
return quote_datas
def process_backward(quote_datas1, divid_datas):
quote_datas = quote_datas1.copy()
def calc_front(v, d):
return round(
(v * (1 + d['stockGift'] + d['stockBonus'] + d['allotNum'])
+ d['interest'] - d['allotNum'] * d['allotPrice'])
, 2
)
for qi in range(len(quote_datas)):
q = quote_datas.iloc[qi]
for di in range(len(divid_datas)):
d = divid_datas.iloc[di]
if d.name > q.name:
continue
q.iloc[0] = calc_front(q.iloc[0], d)
return quote_datas
#--------------------------------
s = '002594.SZ'
#xtdata.download_history_data(s, '1d', '20100101', '')
dd = xtdata.get_divid_factors(s)
print(dd)
#复权计算用于处理价格字段
field_list = ['open', 'high', 'low', 'close']
datas_ori = xtdata.get_market_data(field_list, [s], '1d', dividend_type = 'none')['close'].T
#print(datas_ori)
#等比前复权
datas_forward_ratio = process_forward_ratio(datas_ori, dd)
print('datas_forward_ratio', datas_forward_ratio)
#等比后复权
datas_backward_ratio = process_backward_ratio(datas_ori, dd)
print('datas_backward_ratio', datas_backward_ratio)
#前复权
datas_forward = process_forward(datas_ori, dd)
print('datas_forward', datas_forward)
#后复权
datas_backward = process_backward(datas_ori, dd)
print('datas_backward', datas_backward)