class FuturesSpider:
def __init__(self):
self.dm = DBManager("Futures_d_table")
def init_table(self):
for item in symbol_list:
self.dm.add_one({
"code": item.split("/")[0],
"symbol": item.split("/")[1],
"details": []
})
def start_crawl(self):
for symbol in symbol_list:
url = "http://stock2.finance.sina.com.cn/futures/api/json.php/IndexService.getInnerFuturesDailyKLine?symbol=" + symbol.split(
"/")[0]
print(url)
max_try = 8
for tries in range(max_try):
try:
content = requests.get(url)
self.parse_pager(content.content, symbol.split("/")[0])
break
except Exception:
if tries < (max_try - 1):
sleep(2)
continue
else:
print(symbol, "fail")
def parse_pager(self, content, code):
timer_list = [
x["date"]
for x in self.dm.find_one_by_key({"code": code})["details"]
]
data = json.loads(content)
for item in data:
__dict = {
"date": item[0],
"open": item[1],
"high": item[2],
"low": item[3],
"close": item[4],
"count": item[5]
}
if __dict["date"] not in timer_list:
self.dm.add_futures_item(code, __dict)
print(code, "success")
def update_data(self):
print("-redis_start-")
dm = DBManager("wm_details")
code_list = dm.get_code_list()
for item in code_list:
try:
code = item["code"][:6]
_result = dm.find_by_id(item["code"])
sorted_result = sorted(_result["price_list"],
key=lambda x: cmp_datatime(x),
reverse=True)
self.set_data(code, sorted_result)
except Exception:
print("redis_error:501 " + str(item["code"]))
print("-redis_close-")
def update_data(self):
add_info_logs("redis_start", "-开始同步缓存-")
dm = DBManager("tk_details")
code_list = dm.get_code_list()
for item in code_list:
try:
code = item["code"][:6]
_result = dm.find_by_id(item["code"])
sorted_result = sorted(_result["price_list"],
key=lambda x: cmp_datatime_02(x),
reverse=True)
self.set_data(code, sorted_result)
except Exception:
add_error_logs("redis_error", "501", item["code"])
continue
add_info_logs("redis_close", "-结束同步缓存-")
def fun_02():
date_list = date_range("2017-05-04", "2018-05-21")
for date in date_list:
code = "000001.XSHE"
price_list = list()
tur_list = list()
highest_list = list()
open_list = list()
# 获取wmacd数据
db_manager_wm = DBManager("wm_details")
tk_details = db_manager_wm.find_by_key({"code": code})[0]
for tk_item in [
x for x in tk_details["price_list"] if x["close_price"] != 0
]:
if time_cmp(str(date), tk_item["date_list"][-2]):
price_list.append(tk_item["close_price"])
tur_list.append(tk_item["total_volume"])
highest_list.append(tk_item["max_price"])
open_list.append(tk_item["open_price"])
print(price_list, date)
class DataCrawl:
def __init__(self):
self.dm = DBManager("wm_details")
self.headers = {
"User-Agent":
":Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/59.0.3071.115 Safari/537.36"
}
def start_crawl(self):
print("-start up-")
_year, _season = get_cur_season()
self.get_url(_year, _season)
def end_crawl(self):
self.dm.close_db()
def get_url(self, year, season):
code_list = self.dm.get_code_list()
for item in code_list:
key = item["code"][:6]
url = "http://quotes.money.163.com/trade/lsjysj_" + key + ".html?year=" + year + "&season=" + season
print(url)
max_try = 8
for tries in range(max_try):
try:
content = requests.get(url)
self.parse_pager(content.content, item["code"])
break
except Exception:
if tries < (max_try - 1):
sleep(2)
continue
else:
print("ERROR TO DOWNLODE DATE")
code_list.close()
def parse_pager(self, content, key):
try:
_result = self.dm.find_by_id(key)
timer_list = [x["cur_timer"] for x in _result["price_list"]]
soup = bs4.BeautifulSoup(content, "lxml")
parse_list = soup.select("div.inner_box tr")
for item in parse_list[1:]:
data = [x.string for x in item.select("td")]
price = {
"cur_timer": data[0],
"cur_open_price": data[1],
"cur_max_price": data[2],
"cur_min_price": data[3],
"cur_close_price": data[4],
"cur_price_range": data[6],
"cur_total_volume": data[7],
"cur_total_money": data[8]
}
if price["cur_timer"] not in timer_list:
self.dm.add_tk_item(key, price)
print(key, "success")
except Exception:
print(key, "faild")
def __init__(self):
self.dm = DBManager("futures_d_table")
def parse_pager(content, ticker):
timer_list = [
x["date"] for x in dm.find_one_by_key({"ticker": ticker})["price_list"]
]
while content.next():
item_row = content.get_row_data()
__dict = {
"date": item_row[0],
"code": item_row[1],
"open": item_row[2],
"high": item_row[3],
"low": item_row[4],
"close": item_row[5],
"preclose": item_row[6],
"volume": item_row[7],
"amount": item_row[8],
"adjustflag": item_row[9],
"turn": item_row[10],
"tradestatus": item_row[11],
"pctChg": item_row[12]
}
if __dict["date"] not in timer_list:
dm.add_tk_item(ticker, __dict)
print(ticker, "success")
if __name__ == '__main__':
dm = DBManager("fcr_details")
init_table()
start_crawl()
class TsStrategyExpma:
def __init__(self):
self.db_manager_wm = DBManager("wm_details")
def get_result(self, ema_12_list, ema_26_list):
if len(ema_12_list) > 30 and ema_12_list[-1] > ema_26_list[
-1] and ema_12_list[-2] < ema_26_list[-2]:
return 1
return -1
def get_buy_list(self, date):
code_list = self.db_manager_wm.get_code_list()
buy_list = list()
for item in code_list:
try:
code = item["code"]
price_list = list()
expma_list = list()
# 获取ema数据
tk_details = self.db_manager_wm.find_by_key({"code": code})[0]
for tk_item in [
x for x in tk_details["price_list"]
if x["close_price"] != 0
]:
if time_cmp(str(date), tk_item["date_list"][-2]):
price_list.append(tk_item["close_price"])
ema_12_list, ema_26_list = self.get_w_expma_2(price_list[:])
if self.get_result(ema_12_list, ema_26_list) == 1:
buy_list.append(code)
except Exception as e:
continue
return buy_list
# 将策略结果同步到redis
def update_redis(self, date):
buy_list = self.get_buy_list(date)
rm = RedisManager()
rm.set_data("ema_" + str(date), buy_list)
# 计算当前时间段ema值
def get_w_expma(self, price_list):
ema_12_list = list()
for index in range(len(price_list)):
if index == 0:
ema_12_list.append(price_list[0])
else:
ema_12_list.append(
round(
ema_12_list[index - 1] * 11 / 13 +
price_list[index] * 2 / 13, 4))
ema_26_list = list()
for index in range(len(price_list)):
if index == 0:
ema_26_list.append(price_list[0])
else:
ema_26_list.append(
round(
ema_26_list[index - 1] * 25 / 27 +
price_list[index] * 2 / 27, 4))
return ema_12_list, ema_26_list
# 计算当前时间段ema值
def get_w_expma_2(self, price_list):
ema_12_list = list()
for index in range(len(price_list)):
if index == 0:
ema_12_list.append(price_list[0])
else:
ema_12_list.append(
round(
ema_12_list[index - 1] * 4 / 6 +
price_list[index] * 2 / 6, 4))
ema_26_list = list()
for index in range(len(price_list)):
if index == 0:
ema_26_list.append(price_list[0])
else:
ema_26_list.append(
round(
ema_26_list[index - 1] * 11 / 13 +
price_list[index] * 2 / 13, 4))
return ema_12_list, ema_26_list
class WmacdUtils:
def __init__(self):
self.db_manager_wm = DBManager("wm_details")
self.db_manager_tk = DBManager("tk_details")
# 初始化wmacd数据
def init_w_time(self):
# 初始化时间轴
date_list = date_range("2016-01-04", "2018-12-30")
# tk_details = self.dm.find_by_key({"code": code, "cur_timer": {"$in": cur_date_list}})
code_list = self.db_manager_wm.get_code_list()
for code_item in code_list:
code = code_item["code"]
print(code)
tk_result = self.db_manager_tk.find_by_key({"code": code})[0]
tk_details = sorted(tk_result["price_list"],
key=lambda x: cmp_datatime_02(x),
reverse=False)
for index in range(len(date_list)):
if datetime.datetime.strptime(date_list[index],
"%Y-%m-%d").weekday() == 0:
cur_date_list = date_list[index:index + 7]
# 从数据库中获取这个时间段内的数据
cur_tk_details = [
x for x in tk_details
if x["cur_timer"] in cur_date_list
]
try:
open_price_list = [
float(x["cur_open_price"]) for x in cur_tk_details
]
max_price_list = [
float(x["cur_max_price"]) for x in cur_tk_details
]
min_price_list = [
float(x["cur_min_price"]) for x in cur_tk_details
]
close_price_list = [
float(x["cur_close_price"]) for x in cur_tk_details
]
total_volume_list = [
int(x["cur_total_volume"].replace(",", ""))
for x in cur_tk_details
]
total_money_list = [
int(x["cur_total_money"].replace(",", ""))
for x in cur_tk_details
]
except Exception as e:
continue
if cur_tk_details:
wmacd_item = {
"frist_date": cur_date_list[0],
"date_list": cur_date_list,
"open_price": open_price_list[0],
"max_price": max(max_price_list),
"min_price": min(min_price_list),
"close_price": close_price_list[-1],
"total_volume": sum(total_volume_list),
"total_money": sum(total_money_list),
}
else:
wmacd_item = {
"frist_date": cur_date_list[0],
"date_list": cur_date_list,
"open_price": 0,
"max_price": 0,
"min_price": 0,
"close_price": 0,
"total_volume": 0,
"total_money": 0,
}
# 在数据库中添加一条记录
self.db_manager_wm.add_tk_item(code, wmacd_item)
def update_w_macd(self, cur_date=datetime.datetime.now().date()):
date_list = date_range("2016-01-04", "2018-12-30")
for index in range(len(date_list)):
# 匹配到当前时间所在的区间
if datetime.datetime.strptime(date_list[index],
"%Y-%m-%d").weekday() == 0:
cur_date_list = date_list[index:index + 7]
if str(cur_date) in cur_date_list:
ticker_list = self.db_manager_wm.get_code_list()
# 更新每支股票的数据
for tk_item in ticker_list:
code = tk_item["code"]
tk_result = self.db_manager_tk.find_by_key(
{"code": code})[0]
tk_details = sorted(tk_result["price_list"],
key=lambda x: cmp_datatime_02(x),
reverse=False)
# 从数据库中获取这个时间段内的数据
cur_tk_details = [
x for x in tk_details
if x["cur_timer"] in cur_date_list
]
open_price_list = [
float(x["cur_open_price"]) for x in cur_tk_details
]
max_price_list = [
float(x["cur_max_price"]) for x in cur_tk_details
]
min_price_list = [
float(x["cur_min_price"]) for x in cur_tk_details
]
close_price_list = [
float(x["cur_close_price"]) for x in cur_tk_details
]
total_volume_list = [
int(x["cur_total_volume"].replace(",", ""))
for x in cur_tk_details
]
total_money_list = [
int(x["cur_total_money"].replace(",", ""))
for x in cur_tk_details
]
if cur_tk_details:
wmacd_item = {
"frist_date": cur_date_list[0],
"date_list": cur_date_list,
"open_price": open_price_list[0],
"max_price": max(max_price_list),
"min_price": min(min_price_list),
"close_price": close_price_list[-1],
"total_volume": sum(total_volume_list),
"total_money": sum(total_money_list),
}
# 修改数据库中的数据
self.db_manager_wm.update_wm_price_list(
code, wmacd_item["frist_date"], wmacd_item)
class AccountBean(object):
def __init__(self, capital_base=1000000):
self.capital_base = capital_base # 起始资金
self.capital_available = capital_base # 可用资金
self.position_list = list() # 当前持仓
self.history_order_list = list() # 订单记录
self.db_manager_tk = DBManager("fcr_details")
def fun_buy(self, order):
if isinstance(order, OrderBean):
open_price = self.get_cur_values(order.ticker, order.date, "open")
if open_price <= 0 or open_price * order.amount > self.capital_available or self.get_cur_weekday(
order.date) >= 5:
return
if self.get_position_by_ticker(order.ticker): # 加仓
item_position = self.get_position_by_ticker(order.ticker)
surplus_value = ((item_position.price * item_position.amount) +
(open_price * order.amount)) / (
item_position.amount + order.amount)
item_position.price = surplus_value # 修改剩余价值
item_position.amount = order.amount + item_position.amount
self.capital_available -= open_price * order.amount
else: # 开仓
item_position = PositionBean(order.ticker, open_price,
order.amount, order.date)
self.position_list.append(item_position)
self.capital_available -= open_price * order.amount
self.history_order_list.append(order)
def fun_sell(self, order):
if isinstance(order, OrderBean):
item_position = self.get_position_by_ticker(order.ticker)
if self.get_cur_weekday(order.date) < 5 and item_position:
close_price = self.get_cur_values(order.ticker, order.date,
"close")
if self.get_date_diff(item_position.date,
order.date) > 0 and close_price > 0:
if order.amount < item_position.amount: # 减仓
surplus_value = (
(item_position.price * item_position.amount) -
(close_price * order.amount)) / (
item_position.amount - order.amount)
item_position.price = surplus_value # 修改剩余价值
item_position.amount = item_position.amount - order.amount # 修改剩余持仓
self.capital_available += close_price * order.amount
else: # 平仓
print(self.capital_available)
self.capital_available += close_price * item_position.amount
print(self.capital_available, close_price,
item_position.price)
self.position_list.remove(item_position)
def get_totla_capital(self):
totla_capital = self.capital_available
for position in self.position_list:
totla_capital += position.price * position.amount
return totla_capital
def get_position_by_ticker(self, ticker):
for item in self.position_list:
if isinstance(item, PositionBean) and item.ticker == ticker:
return item
return []
def get_cur_values(self, code, date, key):
result = [
x[key] for x in self.db_manager_tk.find_by_key({'code': code})[0]
["price_list"] if x["date"] == date
]
if result:
return round(float(result[0]), 2)
return 0
def get_cur_weekday(self, date):
return datetime.datetime.strptime(date, "%Y-%m-%d").weekday()
def get_date_diff(self, start, end, format="%Y-%m-%d"):
strptime, strftime = datetime.datetime.strptime, datetime.datetime.strftime
days = (strptime(end, format) - strptime(start, format)).days
return int(days)
@property
def capital_base(self):
return self._capital_base
@property
def capital_available(self):
return self._capital_available
@property
def position_list(self):
return self._position_list
@property
def history_order_list(self):
return self._history_order_list
@capital_base.setter
def capital_base(self, value):
self._capital_base = value
@capital_available.setter
def capital_available(self, value):
self._capital_available = value
@position_list.setter
def position_list(self, value):
self._position_list = value
@history_order_list.setter
def history_order_list(self, value):
self._history_order_list = value
def draw_profit_bar(list1, list2):
plt.subplot(111)
lable_x = np.arange(len(list1))
lable_y = [x * 0 for x in range(len(list1))]
plt.plot(lable_x, lable_y, color="#404040", linewidth=1.0, linestyle="-")
plt.bar(lable_x, list1, color="r", width=1.0)
plt.bar(lable_x, list2, color="g", width=1.0)
plt.xlim(lable_x.min(), lable_x.max() * 1.1)
plt.ylim(min(list2) * 1.1, max(list1) * 1.1)
plt.grid(True)
plt.show()
if __name__ == '__main__':
db_manager = DBManager("wm_details")
code_list = db_manager.get_code_list()
result_list = list()
for item in code_list:
code = item["code"]
print(code)
tk_data = db_manager.find_by_key({"code": code})[0]
close_list = [
float(x["cur_close_price"]) for x in tk_data["price_list"]
if x["cur_close_price"] != 0
]
len_list = len(close_list)
if close_list:
for index in range(expect, len(close_list)):
rate_1 = (close_list[index - period] -
close_list[index]) / close_list[index - period]
plt.subplot(111)
lable_x = np.arange(len(list1))
lable_y = [x * 0 for x in range(len(list1))]
# 绘制中轴线
plt.plot(lable_x, lable_y, color="#404040", linewidth=1.0, linestyle="-")
plt.bar(lable_x, list1, color="r", width=1.0)
plt.bar(lable_x, list2, color="g", width=1.0)
plt.xlim(lable_x.min(), lable_x.max() * 1.1)
plt.ylim(min(list2) * 1.1, max(list1) * 1.1)
plt.grid(True)
plt.show()
if __name__ == "__main__":
# 获取数据
db_manager_wm = DBManager("fcr_details")
code_list = db_manager_wm.get_code_list()
result_list = list()
for item in code_list:
code = item["code"]
print(code)
tk_data = db_manager_wm.find_by_key({"code": code})[0]
colse_list = [
float(x["close"]) for x in tk_data["price_list"] if x["close"] != 0
]
len_list = len(colse_list)
if colse_list:
# 执行判断逻辑
for index in range(expect, len(colse_list)):
rate_1 = (colse_list[index - period] - colse_list[index]
) / colse_list[index - period] # 下跌幅度
item_position[0],
str(round(profit_rate * 100, 2)) + "%", capital_base
]))
current_position.remove(item_position)
# 统计历史数据
history_capital.append(capital_base)
f_utils.insert_line("cash->" + str(get_all_capital()))
def start_bp():
st3 = TsStrategy3()
history_capital.append(capital_base)
# 初始化时间轴
date_list = date_range("2017-01-01", "2017-12-31")
for index in range(len(date_list)):
cur_date = date_list[index]
fun_sell(cur_date)
if datetime.datetime.strptime(cur_date, "%Y-%m-%d").weekday() == 0:
buy_list = st3.get_buy_list(cur_date)
if buy_list:
fun_buy(buy_list, cur_date)
net_rate = (history_capital[-1] -
history_capital[0]) / history_capital[0] # 计算回测结果
print(round(net_rate * 100, 2), "%")
if __name__ == "__main__":
f_utils = FileUtils("bp_result3_1.txt", "w")
db_manager_tk = DBManager("fcr_details")
start_bp()
class TsStrategy5f(object):
def __init__(self):
self.db_manager_wm = DBManager("fcr_w_details")
def get_result(self, ticker):
if isinstance(ticker,
tkWMacdBean) and len(ticker.get_wmacd_list()) > 30:
if ticker.get_wmacd_list()[-1] > 0 >= ticker.get_wmacd_list()[-2]:
if 0.1 > ticker.get_diff_list()[-1] > 0:
if np.mean(ticker.get_tur_list()
[-5:-1]) < ticker.get_tur_list()[-1]:
return 1
return -1
# 排除一些虚假信号
def get_result2(self, ticker):
if isinstance(ticker,
tkWMacdBean) and len(ticker.get_wmacd_list()) > 30:
if ticker.get_wmacd_list()[-1] > 0 >= ticker.get_wmacd_list()[-2]:
if 0.1 > ticker.get_diff_list()[-1] > 0:
if np.mean(ticker.get_tur_list()
[-5:-1]) < ticker.get_tur_list()[-1]:
if ticker.get_wmacd_list(
)[-3] < 0 and ticker.get_wmacd_list(
)[-4] < 0 and ticker.get_wmacd_list()[-5] < 0:
return 1
return -1
def get_result3(self, ticker):
if isinstance(ticker,
tkWMacdBean) and len(ticker.get_wmacd_list()) > 30:
if ticker.get_wmacd_list()[-1] > 0 >= ticker.get_wmacd_list()[-2]:
if 0.1 > ticker.get_diff_list()[-1] > 0:
if np.mean(ticker.get_tur_list()
[-5:-1]) < ticker.get_tur_list()[-1]:
if ticker.get_wmacd_list(
)[-3] < 0 and ticker.get_wmacd_list(
)[-4] < 0 and ticker.get_wmacd_list()[-5] < 0:
return 1
return -1
def get_buy_list(self, date):
code_list = self.db_manager_wm.get_code_list()
buy_list = list()
for item in code_list:
try:
code = item["code"]
price_list = list()
tur_list = list()
highest_list = list()
open_list = list()
date_list = list()
# 获取wmacd数据
tk_details = self.db_manager_wm.find_by_key({"code": code})[0]
for tk_item in [
x for x in tk_details["price_list"] if x["close"] != 0
]:
if time_cmp(str(date), tk_item["date"]):
date_list.append(tk_item["date"])
price_list.append(float(tk_item["close"]))
tur_list.append(float(tk_item["volume"]))
highest_list.append(float(tk_item["high"]))
open_list.append(float(tk_item["open"]))
wmacd_list, diff_list, dea_list = self.get_w_macd(
price_list[:])
# 创建wmacd实体
tk_bean = tkWMacdBean(code, price_list, wmacd_list, diff_list,
dea_list, tur_list, highest_list,
open_list)
if self.get_result2(tk_bean) == 1:
buy_list.append(code)
except Exception as e:
continue
return buy_list
# 计算当前时间段的wmacd值
def get_w_macd(self, price_list):
ema_12_list = list()
for index in range(len(price_list)):
if index == 0:
ema_12_list.append(price_list[0])
else:
ema_12_list.append(
round(
ema_12_list[index - 1] * 11 / 13 +
price_list[index] * 2 / 13, 4))
ema_26_list = list()
for index in range(len(price_list)):
if index == 0:
ema_26_list.append(price_list[0])
else:
ema_26_list.append(
round(
ema_26_list[index - 1] * 25 / 27 +
price_list[index] * 2 / 27, 4))
diff_list = list()
for index in range(len(ema_12_list)):
diff = ema_12_list[index] - ema_26_list[index]
diff_list.append(diff)
dea_list = list()
for index in range(len(diff_list)):
if index == 0:
dea_list.append(diff_list[0])
else:
dea_list.append(
round(dea_list[index - 1] * 0.8 + diff_list[index] * 0.2,
4))
wmacd_list = list()
for index in range(len(dea_list)):
bar = (diff_list[index] - dea_list[index]) * 3
wmacd_list.append(bar)
return wmacd_list, diff_list, dea_list
def __init__(self, capital_base=1000000):
self.capital_base = capital_base # 起始资金
self.capital_available = capital_base # 可用资金
self.position_list = list() # 当前持仓
self.history_order_list = list() # 订单记录
self.db_manager_tk = DBManager("fcr_details")
def __init__(self):
self.db_manager_wm = DBManager("fcr_w_details")
def __init__(self):
self.dm = DBManager("tk_details")
self.headers = {
"User-Agent": ":Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/59.0.3071.115 Safari/537.36"
}
]))
current_position.remove(item_position)
# 统计历史数据
history_capital.append(capital_base)
f_utils.insert_line("cash->" + str(capital_base))
def start_bp():
ste = TsStrategyExpma()
history_capital.append(capital_base)
# 初始化时间轴
date_list = date_range("2017-05-08", "2017-09-30")
for index in range(len(date_list)):
cur_date = date_list[index]
print(cur_date)
if datetime.datetime.strptime(cur_date, "%Y-%m-%d").weekday() == 0:
buy_list = ste.get_buy_list(cur_date)
if buy_list:
fun_buy(buy_list, cur_date)
else:
fun_sell(cur_date)
net_rate = (history_capital[-1] -
history_capital[0]) / history_capital[0] # 计算回测结果
print(round(net_rate * 100, 2), "%")
if __name__ == "__main__":
f_utils = FileUtils("bp_expma_result_1.txt", "a+")
db_manager_tk = DBManager("tk_details")
start_bp()
import os
import sys
sys.path.append('F:\\PYTHON\\TsSpiderServer\\')
from mongo_db.mongodb_manager import DBManager
base_path = os.path.abspath(os.path.join(os.getcwd(), "..")) + "/bean"
if __name__ == '__main__':
dm = DBManager("wm_details")
file_path = base_path + "/data_code.txt"
_file = open(file_path, 'r', encoding='utf_-8')
tk_list = list()
while True:
line = _file.readline()
if '' == line:
break
str_code = line.split()[0]
str_title = line.split()[1]
dm.add_one({"code": str_code, "title": str_title, "price_list": []})
def __init__(self):
self.db_manager_wm = DBManager("wm_details")
self.db_manager_tk = DBManager("tk_details")
class EmaManager:
def __init__(self):
self.db_manager_tk = DBManager("fcr_w_details")
def get_buy_list(self, date):
code_list = [x for x in self.db_manager_tk.get_code_list_02()]
buy_list = list()
for code_item in code_list:
ticker = code_item["ticker"]
# 获取数据
close_list = list()
tk_details = self.db_manager_tk.find_one_by_key({"ticker": ticker})
for tk_item in [x for x in tk_details["price_list"]]:
if time_cmp(str(date), tk_item["date"]):
close_list.append(float(tk_item["close"]))
# 执行判断条件
if len(close_list) > 20:
ema_20_1 = np.mean(close_list[-20:])
ema_20_2 = np.mean(close_list[-21:-1])
if close_list[-1] > ema_20_1 and close_list[-2] < ema_20_2:
buy_list.append(ticker)
return buy_list
def get_sell_list(self, date):
code_list = [x for x in self.db_manager_tk.get_code_list_02()]
sell_list = list()
for code_item in code_list:
ticker = code_item["ticker"]
# 获取数据
close_list = list()
tk_details = self.db_manager_tk.find_one_by_key({"ticker": ticker})
for tk_item in [x for x in tk_details["price_list"]]:
if time_cmp(str(date), tk_item["date"]):
close_list.append(float(tk_item["close"]))
# 执行判断条件
if len(close_list) > 20:
ema_10_1 = np.mean(close_list[-10:])
ema_10_2 = np.mean(close_list[-11:-1])
if close_list[-1] < ema_10_1 and close_list[-2] > ema_10_2:
sell_list.append(ticker)
return sell_list
def fun_01(self):
code_list = [x for x in self.db_manager_tk.get_code_list_02()]
result_list = list()
for code_item in code_list:
ticker = code_item["ticker"]
# 获取数据
tk_details = self.db_manager_tk.find_one_by_key({"ticker": ticker})
close_list = list()
open_list = list()
high_list = list()
low_list = list()
volume_list = list()
for x in tk_details["price_list"]:
if x["close"] != "":
close_list.append(float(x["close"]))
open_list.append(float(x["open"]))
high_list.append(float(x["high"]))
low_list.append(float(x["low"]))
volume_list.append(float(x["volume"]))
ema_list = list()
for i in range(len(close_list)):
if i >= 20:
ema_list.append(np.mean(close_list[i - 20:i]))
else:
ema_list.append(close_list[i])
# 执行判断条件
for date in range(len(close_list) - 1):
# 均线呈现向上趋势
if ema_list[date] > ema_list[date - 4]:
# K线上穿且连续8周位于均线之下
if close_list[date] > ema_list[date]:
if close_list[date - 1] < ema_list[
date - 1] and close_list[date - 2] < ema_list[
date -
2] and close_list[date - 3] < ema_list[
date - 3] and close_list[
date - 4] < ema_list[date - 4]:
profit_rate = (
close_list[date + 1] -
open_list[date + 1]) / open_list[date + 1]
result_list.append(profit_rate)
print(len(result_list))
result_list_up = [x for x in result_list if x > 0]
result_list_down = [x for x in result_list if x < 0]
print(len(result_list_up), max(result_list_up),
np.mean(result_list_up))
print(len(result_list_down), min(result_list_down),
np.mean(result_list_down))
# 绘图
plt.subplot(111)
lable_x = np.arange(len(result_list))
lable_y = [x * 0 for x in range(len(result_list))]
# 绘制中轴线
plt.plot(lable_x,
lable_y,
color="#404040",
linewidth=1.0,
linestyle="-")
plt.bar(lable_x, result_list, color="g", width=1.0)
plt.xlim(lable_x.min(), lable_x.max() * 1.1)
plt.ylim(min(result_list) * 1.1, max(result_list) * 1.1)
plt.grid(True)
plt.show()
def fun_get_strategy(self):
pass