def analysis_stock(stock_code, stock_name, trade_data):
base = BaseStock("base")
avg = Avg()
avg_result = avg.get_avg(stock_code, stock_name)
trade_data_avg = None
try:
trade_data_avg = avg_result[trade_data]
except:
pass
if trade_data_avg is None:
return None
current_stock_data = base.get_pre_stock_data(stock_code, trade_data, 0)
pre_stock_data = base.get_pre_stock_data(stock_code, trade_data, -1)
if pre_stock_data is None:
return None
pre_trade_data_avg = avg_result[pre_stock_data.get_trade_date()]
if pre_stock_data is not None \
and trade_data_avg["5"] > trade_data_avg["10"] \
and current_stock_data.get_close() > trade_data_avg["5"] \
and pre_trade_data_avg["5"] < pre_trade_data_avg["10"] \
and pre_stock_data.get_close() < pre_trade_data_avg["10"] \
and pre_stock_data.get_close() > pre_trade_data_avg["5"]:
return current_stock_data
return None
def __init__(self):
self.analysis_day = 20
self.base = BaseStock("base")
self.up_track = []
self.avg_line = []
self.down_track = []
self.trade_date = []
def analysis_stock(stock_code, stock_name, trade_data, boll_result):
base = BaseStock("base")
datas = base.get_stock_data(stock_code, stock_name,
timeUtil.day_after_day(trade_data, -30),
trade_data)
if datas is not None and len(datas) > 1:
if datas[0].get_trade_date() != trade_data:
return None
# 比较时间交易记录
trade_time_data = datas[0]
# 比较时间，前一天交易记录
trade_time_pre = datas[1]
if boll_result is None:
ball = Boll()
boll_result = ball.get_boll(stock_code, stock_name)
if boll_result[trade_data] is None:
return None
# 判断是否上穿Boll线中轨
if trade_time_data.get_close() >= boll_result[trade_time_data.get_trade_date()]["avg_line"] and trade_time_pre.get_close() <= \
boll_result[trade_time_pre.get_trade_date()]["avg_line"]:
# 获取在Boll线中轨下的天数
continue_down_count = 0
for tt in range(1, len(datas)):
if datas[tt].get_close() <= boll_result[
datas[tt].get_trade_date()]["avg_line"]:
continue_down_count += 1
trade_time_data.set_down_line_day_count(continue_down_count)
return trade_time_data
else:
return None
def __init__(self):
self.base = BaseStock("base")
self._ema_short = []
self._ema_lang = []
self._diff = []
self._eda = []
self._delta = []
self.trade_date = []
# 短时
self.short = 12
# 长时
self.long = 26
# DIF参数：9
self.dif = 9
class Boll(object):
def __init__(self):
self.analysis_day = 20
self.base = BaseStock("base")
self.up_track = []
self.avg_line = []
self.down_track = []
self.trade_date = []
# {
# '20190513': {
# 'up_track': 20.895620489161818,
# 'avg_line': 17.52700000000012,
# 'down_track': 14.158379510838419
# },
# '20190514': {
# 'up_track': 20.742542659338184,
# 'avg_line': 17.343500000000116,
# 'down_track': 13.94445734066205
# }
# }
def get_boll(self, stock_code, stock_name):
day_len = -20000
date = timeUtil.today()
stock_dates = self.base.get_stock_data(
stock_code, stock_name, timeUtil.day_after_day(date, day_len),
date)
if stock_dates is not None and len(stock_dates) > 1:
boll_result = {}
stock_dates.reverse()
# N天之内所有的开盘总和
day_count_sum = 0
for index in range(len(stock_dates)):
self.trade_date.append(stock_dates[index].get_trade_date())
day_count_sum += stock_dates[index].get_close()
if index < self.analysis_day:
boll_result[stock_dates[index].get_trade_date()] = {
"up_track": 0,
"avg_line": 0,
"down_track": 0,
}
else:
day_count_sum = day_count_sum - stock_dates[
index - self.analysis_day].get_close()
middle_value = day_count_sum / self.analysis_day
md = 0.0
for i in range(index - self.analysis_day + 1, index + 1):
md = md + math.pow(
middle_value - stock_dates[i].get_close(), 2)
md = md / self.analysis_day
md = math.sqrt(md)
boll_result[stock_dates[index].get_trade_date()] = {
"up_track": middle_value + 2 * md,
"avg_line": middle_value,
"down_track": middle_value - 2 * md,
}
return boll_result
else:
return None
class Macd(object):
def __init__(self):
self.base = BaseStock("base")
self._ema_short = []
self._ema_lang = []
self._diff = []
self._eda = []
self._delta = []
self.trade_date = []
# 短时
self.short = 12
# 长时
self.long = 26
# DIF参数：9
self.dif = 9
# {
# '20190513': {
# 'diff': 0.7732937859731557,
# 'eda': 0.9415498112527317,
# 'macd': -0.3365120505591521
# },
# '20190514': {
# 'diff': 0.6013899635176436,
# 'eda': 0.8735178417057141,
# 'macd': -0.544255756376141
# }
# }
def get_macd(self, stock_code, stock_name):
day_len = -20000
date = timeUtil.today()
stock_dates = self.base.get_stock_data(
stock_code, stock_name, timeUtil.day_after_day(date, day_len),
date)
if stock_dates is not None and len(stock_dates) > 1:
stock_dates.reverse()
macd_result = {}
# 计算EMA
EMA1 = []
EMA2 = []
for index in range(len(stock_dates)):
self.trade_date.append(stock_dates[index].get_trade_date())
if index == 0:
# 初始化短时EMA和长时EMA
EMA1.append(stock_dates[index].get_close())
EMA2.append(stock_dates[index].get_close())
else:
EMA1.append(
2 / (self.short + 1) *
(stock_dates[index].get_close() - EMA1[index - 1]) +
EMA1[index - 1])
EMA2.append(
2 / (self.long + 1) *
(stock_dates[index].get_close() - EMA2[index - 1]) +
EMA2[index - 1])
self._ema_short = EMA1
self._ema_lang = EMA2
self._diff = []
for index in range(len(EMA1)):
self._diff.append(EMA1[index] - EMA2[index])
for index in range(len(EMA1)):
if index == 0:
self._eda.append(self._diff[index])
else:
self._eda.append(
2 / (self.dif + 1) *
(self._diff[index] - self._eda[index - 1]) +
self._eda[index - 1])
# macd
self._delta = []
for index in range(len(self._diff)):
self._delta.append((self._diff[index] - self._eda[index]) * 2)
for ii in range(0, len(self.trade_date)):
macd_result[self.trade_date[ii]] = {
"diff": self._diff[ii],
"eda": self._eda[ii],
"macd": self._delta[ii]
}
return macd_result
else:
print("No Data Find! %s[%s] on %s " %
(stock_code, stock_name, date))
return None
# macd = Macd()
# result = macd.get_macd('000004.SZ', '国农科技')
# print(result)
from stock.BaseStock import BaseStock
import IndexConstants
import sys
from stock_mork_boll_line5_macd.StockMorkB5M import MorkB5N
base = BaseStock("base")
mork_ball = MorkB5N(20, -3, 9, 1, 1, -0.2, 99999)
stock = base.get_all_60_stock()
statistics_data = {
"winTime": 0,
"winMoney": 0,
"down5LineTime": 0,
"down5LineMoney": 0,
"lostTime": 0,
"lostMoney": 0,
"otherTime": 0,
"otherMoney": 0
}
savedStdout = sys.stdout # 保存标准输出流
with open(IndexConstants.date_file_path + "MorkB5N20_3_9_1_1_Z_60.txt",
'at') as file:
sys.stdout = file # 标准输出重定向至文件
for one in stock:
mork_ball.mork_b5m(one, stock[one], statistics_data)
sys.stdout = savedStdout # 恢复标准输出流
stock = base.get_all_30_stock()
statistics_data = {
pre_trade_data_avg = avg_result[pre_stock_data.get_trade_date()]
if pre_stock_data is not None \
and trade_data_avg["5"] > trade_data_avg["10"] \
and current_stock_data.get_close() > trade_data_avg["5"] \
and pre_trade_data_avg["5"] < pre_trade_data_avg["10"] \
and pre_stock_data.get_close() < pre_trade_data_avg["10"] \
and pre_stock_data.get_close() > pre_trade_data_avg["5"]:
return current_stock_data
return None
if __name__ == '__main__':
base = BaseStock("base")
stock = base.get_all_stock()
avg = Avg()
ball = Boll()
print("Save data in:" + constant.date_file_path)
for i in range(5):
analysis_date = "20190821"
trade_data = timeUtil.day_after_day(analysis_date, -1 * i)
print("Start---" + trade_data)
result_file_path = constant.date_file_path + "Line5Up10_" + trade_data + ".txt"
# result_file_path = constant.date_file_path + "Line5Up10.txt"
pt.p_file_no_format_add(result_file_path, [
"code,date,O,H,L,C,P,Diff,R,count,sum,avg5,avg10,avg20,up_track,avg_line,down_track"
.replace(",", " ")
])
def mork_bollBackDownLine(self, stock_code, stock_name, statistics_data):
base = BaseStock("base")
avg = Avg()
avg_result = avg.get_avg(stock_code, stock_name)
ball_class = Boll()
boll_result = ball_class.get_boll(stock_code, stock_name)
for i in range(0, 150):
catch_stock = boll.analysis_stock(
stock_code, stock_name,
timeUtil.day_after_day(timeUtil.today(), i * -1), boll_result)
if catch_stock is not None:
after_datas = base.get_stock_data(
stock_code, stock_name,
timeUtil.day_after_day(catch_stock.get_trade_date(), 1),
timeUtil.day_after_day(catch_stock.get_trade_date(), 20))
after_datas.reverse()
if len(after_datas) >= 1:
catch_down_line_day = catch_stock.get_down_line_day_count()
if catch_down_line_day >= self._minDownDay and catch_down_line_day <= self._maxDownDay:
print(stock_name + ":" + str(catch_stock))
print("%s 突破日股价 %.2f Boll下轨天数 %d" %
(stock_code, catch_stock.get_close(),
catch_down_line_day))
test_trade = {
"stockCode": stock_code,
"startBuy": 0,
"startBuyDate": "",
"endBuy": 0,
"endBuyDate": "",
# 止损率
"lostBuffRate": self._lostBuffRate,
# 止盈利率
"winBuffRate": self._winBuffRate,
"earn": 0,
"earnRate": 0,
"holdDay": 0,
"forceSell": False,
"forceSellType": ""
}
print("Line5[%.3f] - close[%.3f]" %
(avg_result[catch_stock.get_trade_date()]["5"],
catch_stock.get_close()))
self.cal_print_avg_line(catch_stock, avg_result,
after_datas, 0, test_trade)
for cal_day in range(2, self._calDay + 1):
if len(after_datas) >= cal_day:
self.cal_print_avg_line(
catch_stock, avg_result, after_datas,
cal_day - 1, test_trade)
if test_trade["startBuy"] > 0:
print(
"stockCode %s startBuy %.2f startBuyDate %s endBuy %.2f endBuyDate %s earn %.2f earnRate %.2f holdDay %d forceSell %s forceSellType %s"
%
(test_trade["stockCode"],
test_trade["startBuy"],
test_trade["startBuyDate"],
test_trade["endBuy"],
test_trade["endBuyDate"], test_trade["earn"],
test_trade["earnRate"], test_trade["holdDay"],
test_trade["forceSell"],
test_trade["forceSellType"]))
if test_trade["forceSellType"] == "down5Line":
statistics_data[
"down5LineTime"] = statistics_data[
"down5LineTime"] + 1
statistics_data[
"down5LineMoney"] = statistics_data[
"down5LineMoney"] + test_trade[
"earnRate"]
elif test_trade["forceSellType"] == "winBuffRate":
statistics_data[
"winTime"] = statistics_data["winTime"] + 1
statistics_data["winMoney"] = statistics_data[
"winMoney"] + test_trade["earnRate"]
elif test_trade["forceSellType"] == "lostBuffRate":
statistics_data["lostTime"] = statistics_data[
"lostTime"] + 1
statistics_data["lostMoney"] = statistics_data[
"lostMoney"] + test_trade["earnRate"]
else:
statistics_data["otherTime"] = statistics_data[
"otherTime"] + 1
statistics_data[
"otherMoney"] = statistics_data[
"otherMoney"] + test_trade["earnRate"]
print(
"code %s winTime %d winMoney %.3f down5LineTime %d down5LineMoney %.3f lostTime %d lostMoney %.3f otherTime %d otherMoney %.3f"
% (stock_code, statistics_data["winTime"],
statistics_data["winMoney"],
statistics_data["down5LineTime"],
statistics_data["down5LineMoney"],
statistics_data["lostTime"],
statistics_data["lostMoney"],
statistics_data["otherTime"],
statistics_data["otherMoney"]))
return statistics_data
if len(format_value) == 4:
format_value = " " + format_value
if len(format_value) == 5:
format_value = " " + format_value
return format_value
stocks = []
fileInfo = open("D:" + os.sep + "analysisStock.txt")
for line in fileInfo:
stocks.append(line)
avg = Avg()
avg_clos = {}
base = BaseStock("base")
pingan_datas = base.get_stock_data('601318.SH', 'PingAn', '20190701',
timeUtil.day_after(0))
lastest_trade_date = pingan_datas[0].get_trade_date()
print("lastest_trade_date:" + lastest_trade_date)
while True:
dateStr = ""
for oneStockInfo in stocks:
oneStockInfo = oneStockInfo.strip('\n')
oneStockInfo = oneStockInfo.strip(' ')
try:
if oneStockInfo[0] == '#':
continue
elif oneStockInfo == '000001':
stock_code = oneStockInfo + ".SZ"
oneStockInfo = 'sh' + oneStockInfo
def __init__(self):
self.analysis_day = 20
self.base = BaseStock("base")
class Avg(object):
def __init__(self):
self.analysis_day = 20
self.base = BaseStock("base")
def get_avg(self, stock_code, stock_name):
day_len = -20000
date = timeUtil.today()
stock_dates = self.base.get_stock_data(stock_code, stock_name, timeUtil.day_after_day(date, day_len), date)
if stock_dates is not None and len(stock_dates) > 1:
avg_result= {}
stock_dates.reverse()
day3_line = []
day4_line = []
day5_line = []
day6_line = []
day7_line = []
day8_line = []
day9_line = []
day10_line = []
day15_line = []
day20_line = []
day30_line = []
day60_line = []
day120_line = []
trade_date = []
day3 = 0
day4 = 0
day5 = 0
day6 = 0
day7 = 0
day8 = 0
day9 = 0
day10 = 0
day15 = 0
day20 = 0
day30 = 0
day60 = 0
day120 = 0
for index in range(len(stock_dates)):
trade_date.append(stock_dates[index].get_trade_date())
# Day 3
day3 += stock_dates[index].get_close()
if index < 3:
day3_line.append(day3 / (index + 1))
else:
day3 -= stock_dates[index - 3].get_close()
day3_line.append(day3 / 3)
# Day 4
day4 += stock_dates[index].get_close()
if index < 4:
day4_line.append(day4 / (index + 1))
else:
day4 -= stock_dates[index - 4].get_close()
day4_line.append(day4 / 4)
# Day 5
day5 += stock_dates[index].get_close()
if index < 5:
day5_line.append(day5 / (index + 1))
else:
day5 -= stock_dates[index - 5].get_close()
day5_line.append(day5 / 5)
# Day 6
day6 += stock_dates[index].get_close()
if index < 6:
day6_line.append(day6 / (index + 1))
else:
day6 -= stock_dates[index - 6].get_close()
day6_line.append(day6 / 6)
# Day 7
day7 += stock_dates[index].get_close()
if index < 7:
day7_line.append(day7 / (index + 1))
else:
day7 -= stock_dates[index - 7].get_close()
day7_line.append(day7 / 7)
# Day 8
day8 += stock_dates[index].get_close()
if index < 8:
day8_line.append(day8 / (index + 1))
else:
day8 -= stock_dates[index - 8].get_close()
day8_line.append(day8 / 8)
# Day 9
day9 += stock_dates[index].get_close()
if index < 9:
day9_line.append(day9 / (index + 1))
else:
day9 -= stock_dates[index - 9].get_close()
day9_line.append(day9 / 9)
# Day 10
day10 += stock_dates[index].get_close()
if index < 10:
day10_line.append(day10 / (index + 1))
else:
day10 -= stock_dates[index - 10].get_close()
day10_line.append(day10 / 10)
# Day 15
day15 += stock_dates[index].get_close()
if index < 15:
day15_line.append(day15 / (index + 1))
else:
day15 -= stock_dates[index - 15].get_close()
day15_line.append(day15 / 15)
# Day 20
day20 += stock_dates[index].get_close()
if index < 20:
day20_line.append(day20 / (index + 1))
else:
day20 -= stock_dates[index - 20].get_close()
day20_line.append(day20 / 20)
# Day 30
day30 += stock_dates[index].get_close()
if index < 30:
day30_line.append(day30 / (index + 1))
else:
day30 -= stock_dates[index - 30].get_close()
day30_line.append(day30 / 30)
# Day 60
day60 += stock_dates[index].get_close()
if index < 60:
day60_line.append(day60 / (index + 1))
else:
day60 -= stock_dates[index - 60].get_close()
day60_line.append(day60 / 60)
# Day 120
day120 += stock_dates[index].get_close()
if index < 120:
day120_line.append(day120 / (index + 1))
else:
day120 -= stock_dates[index - 120].get_close()
day120_line.append(day120 / 120)
# END LOOP-------------------------------
for ii in range(0,len(trade_date)):
avg_result[trade_date[ii]] = {
"3": day3_line[ii],
"4": day4_line[ii],
"5": day5_line[ii],
"6": day6_line[ii],
"7": day7_line[ii],
"8": day8_line[ii],
"9": day9_line[ii],
"10": day10_line[ii],
"15": day15_line[ii],
"20": day20_line[ii],
"30": day30_line[ii],
"60": day60_line[ii],
"120": day120_line[ii]
}
return avg_result
else:
return None
from stock.BaseStock import BaseStock
import tools.TimeUtil as timeUtil
import IndexConstants as constant
import time
from tools.PrintUtil import *
base = BaseStock("base")
stock = base.get_all_stock()
count = 1
index = 1
for one in stock:
count = count + 1
if count < 3509:
continue
else:
index = index + 1
index = index + 1
print(str(count) + "--" + one)
stock_datas = base.query_stock_data(one, stock[one], timeUtil.day_after(-20000), timeUtil.today())
if stock_datas is not None:
stock_file_path = constant.stock_file_path + one + '.txt'
p_file_list_with_no_format(stock_file_path, stock_datas)
# stock_datas_hfq = base.query_stock_data_hfq(one, stock[one], timeUtil.day_after(-20000), timeUtil.today())
# if stock_datas_hfq is not None:
# stock_file_path = constant.stock_file_path_hfq + one + '.txt'