def get_stock_list(x_position):
stock_list = select(StockIO.get_stock('sha'), x_position=x_position, kline_type=StockConfig.kline_type_day)
stock_list += select(StockIO.get_stock('sza'), x_position=x_position, kline_type=StockConfig.kline_type_day)
stock_list = sorted(stock_list, key=lambda stock: stock.vb, reverse=True)
return stock_list[:40]
# 该选股方法 每天要过滤的形态：
for x in range(-1, 0):
position = x
date = position
# 过滤重复的
stock_code_list = []
with open('{}/{}'.format(StockConfig.path_track, 'zixuan.txt'),
'r',
encoding='utf-8') as f:
lines = f.readlines()
for line in lines:
if not line.startswith("#") and not '\n' == line:
data = line.strip('\n')
stock_code_list.append(data)
new_list = select(StockIO.get_stock('week_tendency'),
x_position=position,
kline_type=StockConfig.kline_type_day)
# 新结果
result_list = [
x.stock_code for x in new_list
if x.stock_code not in stock_code_list
]
with open('{}/{}.txt'.format(StockConfig.path_track, 'zixuan'),
mode='a',
encoding='utf-8') as f:
f.write('#{}\n'.format(date))
for stock_code in result_list:
f.write("{}\n".format(stock_code))
with open('{}/{}.txt'.format(StockConfig.path_track, 'today'),
def track():
"""
:param targets: 需要追踪的目标集合
@:param code:
@:param price:
:return:
"""
# 读取本地数据
track_data = get_track_data()
kline_map = StockIO.get_kline_map(track_data[:, 0],
StockConfig.kline_type_day)
page = 0
pageNum = 40
result = []
code_list = track_data[:, 0]
while page * pageNum < len(code_list):
from_position = page * pageNum
to_position = min((page + 1) * pageNum, len(code_list))
data = code_list[from_position:to_position]
cur_track_data = track_data[from_position:to_position]
page += 1
# 请求网络数据
codes = ''
for code in data:
if code.startswith('6'):
code = '0' + code
else:
code = '1' + code
codes = codes + code + ','
session = requests.Session()
session.trust_env = False
url = 'http://api.money.126.net/data/feed/{}'.format(codes)[:-1]
print(url)
r = session.get(url)
quote = json.loads(r.text[len('_ntes_quote_callback('):-2])
# 分析数据
for target in cur_track_data:
target_code = target[0]
target_sma_down = 0 if target[2].strip() == '' else int(target[2])
target_sma_up = 0 if target[3].strip() == '' else int(target[3])
target_price_down = 0 if target[4].strip() == '' else float(
target[4])
target_price_up = 0 if target[5].strip() == '' else float(
target[5])
target_chg_down = 0 if target[6].strip() == '' else float(
target[6])
target_chg_up = 0 if target[7].strip() == '' else float(target[7])
if target_code.startswith('6'):
target_code = '0' + target_code
else:
target_code = '1' + target_code
new_date = datetime.datetime.strptime(
quote[target_code]['time'],
'%Y/%m/%d %H:%M:%S').strftime('%Y-%m-%d')
kline = kline_map[target_code[1:]]
old_kline_item = kline[-1]
new_kline_item = np.array([
new_date, quote[target_code]['open'], old_kline_item[-3],
quote[target_code]['high'], quote[target_code]['low'],
quote[target_code]['volume']
])
if (new_kline_item[-1] == old_kline_item[-1]):
kline[-1] = new_kline_item
else:
kline = np.row_stack((kline, new_kline_item))
#print(kline[-1])
# 跌破目标均线
if target_sma_down != 0:
message = ''
sma, = StockIndicator.sma(kline, abs(target_sma_down))
price = quote[target_code]['price']
if (price < sma[-1]):
print(sma[-1], price)
print(r.text)
message = target_code[1:] + '跌破{}日线:'.format(
abs(target_sma_down))
if message != '':
show_dialog("tips", message)
# 突破目标均线
if target_sma_up != 0:
message = ''
sma, = StockIndicator.sma(kline, abs(target_sma_up))
price = quote[target_code]['low']
if (price > sma[-1]):
message = target_code[1:] + '突破{}日线:'.format(
abs(target_sma_up))
if message != '':
show_dialog("tips", message)
# 跌到目标价位
if target_price_down != 0:
message = ''
cur_price = float(quote[target_code]['price'])
message = ''
if cur_price <= abs(target_price_down):
message = target_code[1:] + '跌到目标价位:' + str(
abs(target_price_down))
if message != '':
show_dialog("tips", message)
# 涨到目标价位
if target_price_up != 0:
message = ''
cur_price = float(quote[target_code]['price'])
message = ''
if cur_price >= abs(target_price_up):
message = target_code[1:] + '涨到目标价位:' + str(
abs(target_price_up))
if message != '':
show_dialog("tips", message)
# 每日目标跌幅
if target_chg_down != 0:
p_close = float(quote[target_code]['yestclose'])
low = float(quote[target_code]['low'])
chg = np.round(((low - p_close) / p_close * 100), decimals=2)
if chg < target_chg_down:
message = target_code[1:] + '跌到目标跌幅:' + str(chg)
if message != '':
show_dialog("tips", message)
if target_chg_up != 0:
p_close = float(quote[target_code]['yestclose'])
high = float(quote[target_code]['high'])
chg = np.round(((high - p_close) / p_close * 100), decimals=2)
if chg > target_chg_up:
message = target_code[1:] + '涨到目标涨幅:' + str(chg)
if message != '':
show_dialog("tips", message)
# 每日目标涨幅
# 默认会跟踪自动筛选出来的 sma变化
# if target_sma_down == 0 and target_price_down == 0 and target_sma_up == 0 and target_price_up == 0:
# sma5, sma10, sma20, sma30 = StockIndicator.sma(kline, 5, 10, 20, 30)
# price = quote[target_code]['price']
# # # sma5 条件
# # if price < sma5[-1]:
# # message = target_code[1:] + '跌破{}日线:'.format(5)
# # sma10 条件
# if price < sma20[-1]:
# message = target_code[1:] + '跌破{}日线:'.format(20)
# # sma20 条件
# # elif price < sma20[-1]:
# # message = target_code[1:] + '跌破{}日线:'.format(20)
# else:
# message = ''
# if message != '':
# show_dialog("tips", message)
return result
# -*-coding:utf-8 -*-
import StockIO
import StockConfig
import StockFilter
import StockIndicator
import numpy as np
from StockDownloader import save_stock
# 每日分析
# 1. 分析每日仍然保持了趋势的个股（两点： 一是新高底部， 二是最近新高靠近日线， 三是均线金叉）
stock_list = StockIO.get_stock('week_tendency')
def avg_up_trend(stock):
kline = StockIO.get_kline(stock.stock_code, StockConfig.kline_type_day)
sma5, sma10, sma20, sma60 = StockIndicator.sma(kline, 5, 10, 20, 60)
if sma5[-1] > sma10[-1] > sma20[-1] and sma5[-1] > sma60[-1]:
return True
return False
StockIO.save_stock('today_trend.txt',
[stock for stock in stock_list if avg_up_trend(stock)])
to_position = None if to_position == -1 else to_position
close_b = kline[:, 2].astype(np.float)[from_position + 1:to_position]
close_p = kline[:,
2].astype(np.float)[from_position:to_position -
1 if to_position is not None else -1]
return close_b - close_p, (close_b - close_p) / close_p * 100
def position(date, stock_code, kline_type=StockConfig.kline_type_day):
kline = StockIO.get_kline(stock_code, kline_type)
dates = kline[:, 0]
length = dates.shape[0]
if date in dates:
index = np.argwhere(dates == date)[0][0] - length
return index
return None
if __name__ == '__main__':
sma5, sma10 = sma(
StockIO.get_kline('000001', kline_type=StockConfig.kline_type_day), 5,
10)
print(type(sma5))
print(sma5)
print(sma10)
#
# chg, chg_per = chg_per(get_kline('002040', kline_type_day), from_position=-4, to_position=-1)
# print(chg)
# print(chg_per)
#
def track():
"""
:param targets: 需要追踪的目标集合
@:param code:
@:param price:
:return:
"""
# 读取本地数据
track_data = get_track_data('2_sma_track.txt')
kline_map = StockIO.get_kline_map(track_data[:, 0],
StockConfig.kline_type_day)
page = 0
pageNum = 40
result = []
code_list = track_data[:, 0]
while page * pageNum < len(code_list):
from_position = page * pageNum
to_position = min((page + 1) * pageNum, len(code_list))
data = code_list[from_position:to_position]
cur_track_data = track_data[from_position:to_position]
page += 1
# 请求网络数据
codes = ''
for code in data:
if code.startswith('6'):
code = '0' + code
else:
code = '1' + code
codes = codes + code + ','
session = requests.Session()
session.trust_env = False
url = 'http://api.money.126.net/data/feed/{}'.format(codes)[:-1]
print(url)
r = session.get(url)
quote = json.loads(r.text[len('_ntes_quote_callback('):-2])
# 分析数据
for target in cur_track_data:
target_code = target[0]
target_sma = 0 if target[2].strip() == '' else int(target[2])
target_price = 0 if target[3].strip() == '' else float(target[3])
if target_code.startswith('6'):
target_code = '0' + target_code
else:
target_code = '1' + target_code
new_date = datetime.datetime.strptime(
quote[target_code]['time'],
'%Y/%m/%d %H:%M:%S').strftime('%Y-%m-%d')
kline = kline_map[target_code[1:]]
old_kline_item = kline[-1]
new_kline_item = np.array([
new_date, quote[target_code]['open'], old_kline_item[-3],
quote[target_code]['high'], quote[target_code]['low'],
quote[target_code]['volume']
])
if (new_kline_item[-1] == old_kline_item[-1]):
kline[-1] = new_kline_item
else:
kline = np.row_stack((kline, new_kline_item))
#print(kline[-1])
# sma track
if target_sma != 0:
sma, = StockIndicator.sma(kline, target_sma)
price = quote[target_code]['low']
if (price < sma[-1]):
message = target_code[1:] + '跌破{}日线:'.format(target_sma)
elif (price < sma[-1]):
message = target_code[1:] + '跌破{}日线:'.format(target_sma)
else:
message = ''
if message != '':
messagebox.showinfo("tips", message)
# price track
if target_price != 0:
cur_price = float(quote[target_code]['price'])
message = ''
if target_price < 0 and cur_price <= abs(target_price):
message = target_code[1:] + '跌到目标价位:' + str(
abs(target_price))
elif target_price > 0 and cur_price >= abs(target_price):
message = target_code[1:] + '涨到目标价位:' + str(
abs(target_price))
if message != '':
messagebox.showinfo("tips", message)
# 默认会跟踪自动筛选出来的 sma变化
if target_price == 0 and target_sma == 0:
sma5, sma10, sma20, sma30 = StockIndicator.sma(
kline, 5, 10, 20, 30)
price = quote[target_code]['low']
# sma5 条件
# if (price < sma5[-1] and sma5[-1] > sma10[-1] > sma20[-1] > sma30[-1]):
# message = target_code[1:] + '跌破{}日线:'.format(sma5[-1])
# sma10 条件
if (price < sma10[-1] and sma10[-1] > sma20[-1] > sma30[-1]):
message = target_code[1:] + '跌破{}日线:'.format(10)
# sma20 条件
elif (price < sma20[-1] and sma5[-1] > sma20[-1]
and sma10[-1] > sma20[-1]) and sma20[-1] > sma30[-1]:
message = target_code[1:] + '跌破{}日线:'.format(20)
else:
message = ''
if message != '':
messagebox.showinfo("tips", message)
# sma 自由追踪
# else:
# sma5, sma10, sma20 = StockIndicator.sma(kline, 5, 10, 20)
# price = quote[target_code]['low']
# if ((price < sma10[-1] or price < sma10[-2]) and sma10[-1] > sma20[-1]):
# message = target_code[1:] + '跌破10日线:'
# elif ((price < sma20[-1] or price < sma20[-2]) and sma20[-1] > sma10[-1]):
# message = target_code[1:] + '跌破20日线:'
# else:
# message = ''
# if message != '':
# messagebox.showinfo("tips", message)
# # analysis
# if cur_price >= price_uts or cur_price <= price_dtb:
# result.append([target[0], cur_price, price_uts, price_dtb, 's' if cur_price >= price_uts else 'b', datetime.datetime.now().strftime('%H:%m')])
return result
stock_list_2 = StockIO.get_stock('sza')
stock_list = stock_list_1 + stock_list_2
for stock in stock_list:
try:
kline = StockIO.get_kline(stock.stock_code,
kline_type=StockConfig.kline_type_week)
close = kline[:, 2].astype(np.float)
sma5, sma10, sma20, sma60 = StockIndicator.sma(
kline, 5, 10, 20, 60)
except Exception as e:
print(e)
continue
if kline.shape[0] < 41:
continue
if sma5[-2] > sma10[-2] and sma5[-2] > sma20[-2]:
stock_result.append(stock)
return stock_result
if __name__ == '__main__':
old_stock_list = StockIO.get_stock('week_tendency')
stock_list = week_tendency2()
# new_add_stock = [stock for stock in stock_list if stock not in old_stock_list]
# new_reduce_stock = [stock for stock in old_stock_list if stock not in stock_list]
# print('new_add_stock: ', new_add_stock)
# print('new_reduce_stock: ', new_reduce_stock)
#old_stock_list = StockIO.get_stock('')
write_stock_pool('week_tendency', stock_list)
if StockShape.is_lower_shadow(open_[x_position], close[x_position], high[x_position], low[x_position], min_vb=min_vb, ratio=ratio, red=False):
if not StockAlgrithm.sumOfSubArray(chg[-15:])[0] > 20:
print(stock)
result.append(stock)
# append to file
path = '{root}/{name}'.format(root=StockConfig.path_track, name=append_file)
with open(path, mode='a', encoding='utf-8') as f:
value = low[-1] + (high[-1] - low[-1]) * 0.3
f.write("{},{},{}\n".format(stock.stock_code, value, high[-1]))
return result
if __name__ == '__main__':
date = '2017-02-03'
position = StockIndicator.position(date, '000001')
result = {}
for x in range(-4, 0):
print('x = ', x)
stock_list = select(StockIO.get_stock('level_1'), x_position=x, kline_type=StockConfig.kline_type_day, min_vb=6, ratio=0.3)
print(stock_list)
for stock in stock_list:
result[stock] = result.get(stock, 0) + 1
print(sorted(result.items(), key=lambda d: d[1], reverse=True))
#print(down_to(StockIO.get_stock('sha'), duration=60))
stock_list = StockIO.get_stock('sha')
result = []
for stock in stock_list:
kline = StockIO.get_kline(stock.stock_code, StockConfig.kline_type_day)
from_position = x_position - 4
to_position = x_position + 1 if x_position != -1 else None
open = kline[:, 1].astype(np.float)[from_position:to_position + 1]
close = kline[:, 2].astype(np.float)[from_position:to_position]
sma5 = StockIndicator.sma(kline, 5)[0][from_position:to_position]
if kline.shape[0] > min_item:
chg, chg_per = StockIndicator.chg_per(kline, from_position,
to_position)
if chg[-4] > 0 and chg[-3] > 0 and chg[-2] < 0 and chg[-1] > 0:
if close[-1] > close[-4] and chg_per[-1] < 3 and sma5[
-2] < close[-2] and open[-1] < close[-1]:
result.append(stock)
return result
"""
todo: 观察不同position的后续变化， up down up or up up
"""
from_date = '2016-11-03'
to_date = '2016-11-04'
stock_list = select_7(from_date)
StockIO.save_stock('s7_1_20170110',
stock_list=stock_list,
message='down to jx')
print(stock_list)
StockStatistics.stat_chg(stock_list, from_date=from_date, to_date=to_date)
print(stock)
# # 连续三天10日线飘红上升
# if sma10_w[x_position] < open_week[x_position] < close_week[x_position]:
# if sma10_w[x_position - 1] < open_week[x_position] < close_week[x_position - 1]:
# if sma10_w[x_position - 2] < open_week[x_position - 2] < close_week[x_position - 2]:
# #if sma10_w[x_position - 2] > sma5_w[x_position - 2] and sma10_w[x_position] < sma5_w[x_position]:
# result.append(stock)
# print(stock)
return result
def xia_ying_xian(kline_item):
open = float(kline_item[1])
close = float(kline_item[2])
high = float(kline_item[3])
low = float(kline_item[4])
top = min(close, open)
bottom = low
if (top - bottom) / (top) * 100 > 6:
return True
if __name__ == '__main__':
# 均线处决胜负， 胜者向上，败者向下
date = '2017-02-03'
position = StockIndicator.position(date, '000001')
print(trend_up_2(StockIO.get_stock('sha'), x_position=-5))
#print(down_to(StockIO.get_stock('sha'), duration=60))
def trend_up_2(stock_list, x_position=-1, min_item=360):
"""
当股价到达均线附近时， 要么调整， 要么突破
:param stock_list:
:param kline_type:
:param avg:
:return:
"""
result = []
for stock in stock_list:
try:
kline_day = StockIO.get_kline(
stock.stock_code, kline_type=StockConfig.kline_type_day)
kline_week = StockIO.get_kline(
stock.stock_code, kline_type=StockConfig.kline_type_week)
except:
continue
if kline_day.shape[0] < min_item:
continue
open_day = kline_day[:, 1].astype(np.float)
open_week = kline_week[:, 1].astype(np.float)
close_day = kline_day[:, 2].astype(np.float)
close_week = kline_week[:, 2].astype(np.float)
sma5_d, sma10_d, sma20_d = StockIndicator.sma(kline_day, 5, 10, 20)
sma5_w, sma10_w, sma20_w = StockIndicator.sma(kline_week, 5, 10, 20)
# if sma5_d[x_position] > sma5_d[x_position - 1]:
# if sma10_d[x_position] > sma10_d[x_position - 1]:
# if sma20_d[x_position] > sma20_d[x_position - 1]:
# if sma20_d[x_position] > sma5_d[x_position]:
# if close_day[x_position] > sma5_d[x_position]:
# result.append(stock)
# print(stock)
# if sma5_w[x_position] > sma10_w[x_position] > sma20_w[x_position]:
# if close_week[x_position] > sma5_w[x_position]:
# result.append(stock)
# print(stock)
# if sma20_w[x_position - 1] > sma5_w[x_position - 1] and sma20_w[x_position] < sma5_w[x_position]:
# if sma5_w[x_position] > sma20_w[x_position] > sma10_w[x_position]:
# #if close_week[x_position] > sma10_w[x_position] > sma20_w[x_position]:
# result.append(stock)
# print(stock)
# # 后置判断
# if sma10_w[x_position - 1] > sma5_w[x_position - 1] and sma10_w[x_position] < sma5_w[x_position]:
# if sma20_w[x_position] > sma5_w[x_position] > sma10_w[x_position]:
# if sma10_w[x_position + 1] < open_week[x_position + 1] < close_week[x_position + 1]:
# result.append(stock)
# print(stock)
# # 5日线穿过10日线
if sma10_d[x_position - 1] > sma5_d[
x_position - 1] and sma10_d[x_position] < sma5_d[x_position]:
if sma5_d[x_position] > sma5_d[x_position - 1]:
#if sma5_w[x_position - 2] < open_week[x_position - 2] < close_week[x_position - 2]:
result.append(stock)
print(stock)
# # 连续三天10日线飘红上升
# if sma10_w[x_position] < open_week[x_position] < close_week[x_position]:
# if sma10_w[x_position - 1] < open_week[x_position] < close_week[x_position - 1]:
# if sma10_w[x_position - 2] < open_week[x_position - 2] < close_week[x_position - 2]:
# #if sma10_w[x_position - 2] > sma5_w[x_position - 2] and sma10_w[x_position] < sma5_w[x_position]:
# result.append(stock)
# print(stock)
return result
# for stock in stock_list:
# kline = StockIO.get_kline(stock.stock_code, StockConfig.kline_type_week)
# close = kline[:, 2].astype(np.float)
# sma5 = StockIndicator.sma(kline, 5)
# if close[-1] > sma5[0][-1]:
# stock_result.append(stock)
#
# print(stock_result)
# StockReporter.query_report(stock_result)
# first step : filter stock and select target stock
@find_sma_up(StockConfig.kline_type_day, x_position=-1)
@find_kdj_jx(StockConfig.kline_type_week, x_position=-1, k_max=60)
def filter_stock(stock_list):
"""
strategy:
:param stock_list: buy in Tuesday, Monday for confirm up trend, Friday must quits if profited.
:return:
"""
return stock_list
stock_list = filter_stock(StockIO.get_stock('sha'))
print(stock_list)
StockReporter.query_report(stock_list)
# second step: track stock and select buy point
# third step: track stock and select sell point
continue
if kline.shape[0] < min_item:
continue
open = kline[:, 1].astype(np.float)
close = kline[:, 2].astype(np.float)
high = kline[:, 3].astype(np.float)
low = kline[:, 4].astype(np.float)
chg = StockIndicator.chg(kline)
vb = StockIndicator.vibration(kline)
entity = StockIndicator.entity(kline)
sma5, sma10, sma20 = StockIndicator.sma(kline, 5, 10, 20)
if entity[x_position] / abs(chg[x_position]) > 1.5 and entity[x_position] > 3:
print(stock)
result.append(stock)
return result
if __name__ == '__main__':
date = '2017-02-03'
print(select(StockIO.get_stock('sha'), x_position=-4, kline_type=StockConfig.kline_type_day))
# result = {}
# for x in range(-5, 0):
# print('x = ', x)
# stock_list = select(StockIO.get_stock('sha'), x_position=x, kline_type=StockConfig.kline_type_day, min_vb=5, ratio=0.4)
# print(stock_list)
# for stock in stock_list:
# result[stock] = result.get(stock, 0) + 1
#
# print(sorted(result.items(), key=lambda d: d[1], reverse=True))
#print(down_to(StockIO.get_stock('sha'), duration=60))
sma5, sma10, sma20, sma30, sma60 = StockIndicator.sma(
kline, 5, 10, 20, 30, 60)
zf = StockIndicator.zf(kline)
if close[x_position] > sma5[x_position] > sma10[x_position] > open[
x_position] and sma10[x_position] > sma20[x_position]:
if zf[x_position] > 5:
print(stock)
result.append(stock)
return result
if __name__ == '__main__':
position = -7
date = '2018-03-20'
stock_list = select(StockIO.get_stock('sha'), x_position=position, kline_type=StockConfig.kline_type_day) + \
select(StockIO.get_stock('sza'), x_position=position, kline_type=StockConfig.kline_type_day)
print(stock_list)
stock_code_list = []
with open('data/track/2_sma_track.txt', mode='a', encoding='utf-8') as f:
f.write('\n#{}\n'.format(date))
for key in stock_list:
if key.stock_code not in stock_code_list:
f.write('{:>6},{: >5},{:>2},{:>2},{:>5},{:>5}, , ,\n'.format(
key.stock_code, key.stock_name, '', '', '00.00', '00.00'))
with open('data/track/s3_{}.txt'.format(date), mode='w',
encoding='utf-8') as f:
for key in stock_list:
if key.stock_code not in stock_code_list:
f.write("{}\n".format(key.stock_code))
def select(stock_list,
x_position=-1,
w_x_position=-1,
kline_type=StockConfig.kline_type_week,
min_item=80):
"""
均线选股法
:param stock_list:
:param kline_type:
:param avg:
:return:
"""
result = []
for stock in stock_list:
try:
kline = StockIO.get_kline(stock.stock_code, kline_type=kline_type)
except Exception as e:
print(e)
continue
if kline.shape[0] < min_item:
continue
open = kline[:, 1].astype(np.float)
close = kline[:, 2].astype(np.float)
low = kline[:, 4].astype(np.float)
sma5, sma10, sma20, sma30, sma60 = StockIndicator.sma(
kline, 5, 10, 20, 30, 60)
cjl = StockIndicator.cjl(kline)
add = False
if close[x_position] > sma5[x_position] > sma10[x_position] and close[
x_position] > sma20[x_position] and sma5[x_position] > sma20[
x_position]:
add = False
# 趋势
count = 0
while count < 5:
if StockFilter2.is_jx(sma5, sma10, x_position - count):
jx_value = StockFilter2.jx_value(sma5, sma10,
x_position - count)
if jx_value > sma20[x_position - count]:
add = True
if close[x_position] > np.max(
close[x_position - 10:x_position]):
add = True
break
count += 1
if add:
max_exceed = 5
while close[x_position] > np.max(
close[x_position - max_exceed:x_position]):
max_exceed += 1
if max_exceed > 200:
break
stock.max_exceed = max_exceed
if add:
print(stock)
result.append(stock)
return result
low = kline[:, 4].astype(np.float)
zf = abs((high - low) / low * 100)
zf = np.delete(zf, [np.argmax(zf), np.argmin(zf)]) # 去掉最大值和最小值
chg = (np.max(close) - np.min(close)) / np.min(close) * 100
print(close)
print(np.max(close), np.min(close))
avg_zf = np.average(zf)
#print(chg, avg_zf)
if limit_chg[0] < chg < limit_chg[1] and limit_avg_zf[
0] < avg_zf < limit_avg_zf[1]:
last_close = close[-1]
if (close[-1] - np.min(close)) / (
np.max(high) - np.min(close)) * 100 < limit_bottom:
result.append([stock, chg, avg_zf, close[-1]])
return result
if __name__ == '__main__':
position = StockIndicator.position('2017-01-16',
'601398',
kline_type=StockConfig.kline_type_day)
print(
filter_by_zf(StockIO.get_stock('sha'),
x_position=-2,
kline_type=StockConfig.kline_type_week,
min_item=120))
# for test single stock
#stock_list = [StockConfig.Stock('600072', '')]
#print(filter_by_zf(stock_list, x_position=position))
print(stock)
result.append(stock)
return result
if __name__ == '__main__':
date = '2017-02-03'
# result = {}
# for x in range(-5, 0):
# print('x = ', x)
# stock_list = select(StockIO.get_stock('level_1'), x_position=x, kline_type=StockConfig.kline_type_week, min_vb=14, ratio=0.5)
# print(stock_list)
# for stock in stock_list:
# result[stock] = result.get(stock, 0) + 1
#
# print(sorted(result.items(), key=lambda d: d[1], reverse=True))
result = {}
for x in range(-5, 0):
print('x = ', x)
stock_list = select(StockIO.get_stock('sha'),
x_position=x,
kline_type=StockConfig.kline_type_day,
min_vb=5,
ratio=0.4)
print(stock_list)
for stock in stock_list:
result[stock] = result.get(stock, 0) + 1
print(sorted(result.items(), key=lambda d: d[1], reverse=True))
#print(down_to(StockIO.get_stock('sha'), duration=60))
continue
if kline.shape[0] < min_item:
continue
sma30 = StockIndicator.sma(kline, 30)[0]
if close[x_position] > sma30[x_position]:
#print(stock)
result.append(stock)
return result
if __name__ == '__main__':
# date = '2017-02-03'
# position = StockIndicator.position(date, '000001')
#日线
result = {}
for x in range(-3, -1):
print('x = ', x)
stock_list = select(
StockIO.get_stock('sza'),
x_position=x,
kline_type=StockConfig.kline_type_week,
)
print(stock_list)
for stock in stock_list:
result[stock] = result.get(stock, 0) + 1
print(sorted(result.items(), key=lambda d: d[1], reverse=True))
def get_stock_list(x_position, zf=4, kline_type=StockConfig.kline_type_week):
stock_list = select(StockIO.get_stock('gzw'), x_position=x_position, zf= zf, kline_type=kline_type)
return stock_list
continue
chg = StockIndicator.chg(kline)
vb = StockIndicator.vibration(kline)
if max_chg > chg[x_position] > min_chg and max_vb > vb[
x_position] > min_vb:
print(stock)
result.append(stock)
return result
if __name__ == '__main__':
for x in range(-6, 0):
print('x = ', x)
# print(select(StockIO.get_stock('sza'), x_position=x))
# 按照跌幅来选
#print(select(StockIO.get_stock('sha'), '2017-07-03', x_position=-3, kline_type=StockConfig.kline_type_week, min_chg=-50, max_chg=0, min_vb=15, max_vb=100))
# 按照涨幅来选
print(
select(StockIO.get_stock('level_2'),
x_position=-2,
kline_type=StockConfig.kline_type_week,
min_chg=-100,
max_chg=0,
min_vb=10,
max_vb=100))
# =======
# for x in range(-3, 0):
# print('x = ', x)
# print(select(StockIO.get_stock('sha'), x_position=x, kline_type=StockConfig.kline_type_week))
result.append(stock)
return result
if __name__ == '__main__':
date = '2017-02-03'
position = StockIndicator.position(date, '000001')
# result = {}
# for x in range(-5, 0):
# print('x = ', x)
# stock_list = select(StockIO.get_stock('level_1'), x_position=x, kline_type=StockConfig.kline_type_week, min_vb=14, ratio=0.5)
# print(stock_list)
# for stock in stock_list:
# result[stock] = result.get(stock, 0) + 1
#
# print(sorted(result.items(), key=lambda d: d[1], reverse=True))
result = {}
for x in range(-5, 0):
print('x = ', x)
stock_list = select(StockIO.get_stock('level_1'),
x_position=x,
kline_type=StockConfig.kline_type_day,
min_vb=5,
ratio=0.01)
print(stock_list)
for stock in stock_list:
result[stock] = result.get(stock, 0) + 1
print(sorted(result.items(), key=lambda d: d[1], reverse=True))
#print(down_to(StockIO.get_stock('sha'), duration=60))
close = kline[:, 2].astype(np.float)
high = kline[:, 3].astype(np.float)
low = kline[:, 4].astype(np.float)
vb = StockIndicator.vibration(kline)
chg = StockIndicator.chg(kline)
sma5, sma10, sma20 = StockIndicator.sma(kline, 5, 10, 20)
if StockShape.is_lower_shadow(open[x_position], close[x_position], high[x_position], low[x_position], min_vb=min_vb, ratio=ratio, red=True):
print(stock)
result.append(stock)
# print(stock)
# result.append(stock)
# append to file
# path = '{root}/{name}'.format(root=StockConfig.path_track, name=append_file)
# with open(path, mode='a', encoding='utf-8') as f:
# value = low[-1] + (high[-1] - low[-1]) * 0.3
# f.write("{},{},{}\n".format(stock.stock_code, value, high[-1]))
return result
if __name__ == '__main__':
stock_list = []
for x in range(-1, 0):
stock_list += select(StockIO.get_stock('sha'), x_position=x, kline_type=StockConfig.kline_type_day, min_vb=5, ratio=0.6)
stock_list += select(StockIO.get_stock('sza'), x_position=x, kline_type=StockConfig.kline_type_day, min_vb=5,ratio=0.6)
print(stock_list)
with open('C:/Users/panha/Desktop/xgfx/1002.txt', mode='a', encoding='utf-8') as f:
for stock in stock_list:
f.write("{}\n".format(stock.stock_code))
def avg_up_trend(stock):
kline = StockIO.get_kline(stock.stock_code, StockConfig.kline_type_day)
sma5, sma10, sma20, sma60 = StockIndicator.sma(kline, 5, 10, 20, 60)
if sma5[-1] > sma10[-1] > sma20[-1] and sma5[-1] > sma60[-1]:
return True
return False
continue
if kline.shape[0] < min_item:
continue
chg = StockIndicator.chg(kline)
vb = StockIndicator.vibration(kline)
if max_chg > chg[x_position] > min_chg and max_vb > vb[x_position] > min_vb:
# 过滤掉单边上涨
if not StockAlgrithm.sumOfSubArray(chg[-period:])[0] > 14:
if np.max(vb[-period:]) > 14:
print(stock)
result.append(stock)
return result
if __name__ == '__main__':
date = '2017-02-03'
position = StockIndicator.position(date, '000001')
result = {}
for x in range(-6, 0):
print('x = ', x)
stock_list = select(StockIO.get_stock('level_1'), x_position=x, kline_type=StockConfig.kline_type_week,
min_chg=-100, max_chg=100, min_vb=10, max_vb=100)
print(stock_list)
for stock in stock_list:
result[stock.stock_code] = result.get(stock.stock_code, 0) + 1
print(sorted(result.items(), key=lambda d: d[1], reverse=True))
result.append(stock)
# print(stock)
# result.append(stock)
# append to file
# path = '{root}/{name}'.format(root=StockConfig.path_track, name=append_file)
# with open(path, mode='a', encoding='utf-8') as f:
# value = low[-1] + (high[-1] - low[-1]) * 0.3
# f.write("{},{},{}\n".format(stock.stock_code, value, high[-1]))
return result
if __name__ == '__main__':
stock_list = []
for x in range(-10, 0):
stock_list += select(StockIO.get_stock('sha'),
x_position=x,
kline_type=StockConfig.kline_type_day,
min_vb=5,
ratio=0.4)
stock_list += select(StockIO.get_stock('sza'),
x_position=x,
kline_type=StockConfig.kline_type_day,
min_vb=5,
ratio=0.4)
print(stock_list)
with open('C:/Users/panha/Desktop/xgfx/1002.txt',
mode='a',
encoding='utf-8') as f:
for stock in stock_list:
vbs.append(
(stock, float('%.2f' % vb_factor), float('%.2f' % buy_facotr)))
vbs.sort(key=lambda x: x[1])
return vbs
def stat_low(stock_list, peoriod=120, x_position=-2, min_item=360):
vbs = []
for stock in stock_list:
origin_kline = StockIO.get_kline(stock.stock_code,
kline_type=StockConfig.kline_type_day)
if origin_kline.shape[0] < min_item:
continue
from_position = x_position - peoriod + 1
to_position = None if x_position == -1 else x_position
kline = origin_kline[from_position:to_position]
open = kline[:, 1].astype(np.float)
close = kline[:, 2].astype(np.float)
high = kline[:, 3].astype(np.float)
low = kline[:, 4].astype(np.float)
if low[-1] <= np.min(low) and low[-1] != 0:
vbs.append(stock)
return vbs
if __name__ == '__main__':
stock_list = [StockConfig.Stock('601766', 'ZGZC')]
vbs = stat_low(StockIO.get_stock('sha'))
print(vbs)
# -*-coding:utf-8 -*-
"""
根据分红派息情况选股
以2016年的分红派息情况作为参考，根据当前的股票价格，算出预期分红点数，并做排名
"""
import StockIO
import StockConfig
import requests
import json
result = [] #[stock, price, profit, per, date]
stock_list = StockIO.get_stock('sha')
for stock in stock_list:
kline = StockIO.get_kline(stock.stock_code, StockConfig.kline_type_day)
result.append([stock, float(kline[:, 2][-1]), 0, 0, ''])
print(result)
for item in result:
stock_code = item[0].stock_code
stock_code = 'sh' + stock_code if stock_code.startswith(
'6') else 'sz' + stock_code
url = 'http://183.57.48.75/ifzqgtimg/stock/corp/cwbb/search?symbol={}&type=sum&jianjie=1'.format(
stock_code)
session = requests.Session()
session.trust_env = False
r = session.get(url)
json_obj = json.loads(r.text)
if json_obj['code'] == 0:
gegu = json_obj['data']['gegu']
if 'fenhong' in gegu:
fenhong = gegu['fenhong']
if len(fenhong) > 1:
for vb_value in vb[x_position - period:x_position]:
if StockFilter.between(vb_value, min_vb, max_vb):
count += 1
if count > count_limit:
print(stock)
result.append(stock)
return result
if __name__ == '__main__':
date = '2017-02-03'
position = StockIndicator.position(date, '000001')
for x in range(-20, 0):
print('x = ', x)
# print(select(StockIO.get_stock('sza'), x_position=x))
# 按照跌幅来选
#print(select(StockIO.get_stock('sha'), '2017-07-03', x_position=-3, kline_type=StockConfig.kline_type_week, min_chg=-50, max_chg=0, min_vb=15, max_vb=100))
# 按照涨幅来选
print(
select(StockIO.get_stock('sza'),
x_position=-1,
kline_type=StockConfig.kline_type_week,
period=5,
count_limit=3,
min_vb=10,
max_vb=100))
# =======
# for x in range(-3, 0):
# print('x = ', x)
# print(select(StockIO.get_stock('sha'), x_position=x, kline_type=StockConfig.kline_type_week))
def limit(stock_list, output_file='', high_limit_point=5, low_limit_point=4):
result = []
for stock in stock_list:
try:
kline = StockIO.get_kline(stock.stock_code,
kline_type=StockConfig.kline_type_day)
except Exception as e:
print(e)
continue
close = kline[:, 2].astype(np.float)
cur = close[-2]
# 获取最低价和最高价
up = cur * (1 + high_limit_point / 100)
down = cur * (1 - low_limit_point / 100)
result.append((stock.stock_code, down, up, stock.stock_name))
path = '{root}/{name}'.format(root=StockConfig.path_track,
name=output_file)
with open(path, mode='w', encoding='utf-8') as f:
for item in result:
print(item[0], item[1], item[2], item[3])
f.write("{}, {}, {}, {}, {}\n".format(item[0], '%05.2f' % item[1],
'%05.2f' % item[2], item[3],
'(* N)'))
if __name__ == '__main__':
limit(StockIO.get_stock('level_1'), 'level_1_track.txt')
if __name__ == '__main__':
result={}
# for x in range(-10, 0):
# print('x = ', x)
# stock_list = select(StockIO.get_stock('sha'), x_position=x, kline_type=StockConfig.kline_type_week)
# print(stock_list)
#
# for stock in stock_list:
# result[stock] = result.get(stock, 0) + 1
#
# with open('{}/{}'.format(StockConfig.path_stock, 'wsma10'), 'w', encoding='utf-8') as f:
# for key in result:
# if result[key] >= 7:
# f.write("{},{}\n".format(key.stock_code, key.stock_name))
#
# print(sorted(result.items(), key=lambda d: d[1], reverse=True))
date = '2017-10-09'
position = StockIndicator.position(date, '000001')
stock_list = select(StockIO.get_stock('sza'), x_position=-1)
stock_list2 = select(StockIO.get_stock('sha'), x_position=-1)
stock_list = stock_list + stock_list2
print(len(stock_list))
with open('C:/Users/panha/Desktop/xgfx/1002.txt', mode='w', encoding='utf-8') as f:
for key in stock_list:
f.write("{}\n".format(key.stock_code))