breakoutlog完成,跳空高开止损价格不同完成,需继续止损按照价格阶梯卖出

This commit is contained in:
gyz 2025-05-16 20:20:58 +08:00
parent f35670ca53
commit 013bfe206c
2 changed files with 217 additions and 125 deletions

View File

@ -17,6 +17,7 @@ class BuyState:
buy_price: float # 买入价格
add_price: float # 加仓价格
stop_price: float # 止损价格
is_gap_up: bool # 是否跳空高开
shares: int # 买入股数
atr: int # ATR
available_cash: float # 可用资金
@ -35,6 +36,15 @@ class TradeLog:
Net_value: float # 净值
Net_return: float # 净收益
@dataclass
class BreakOutLog:
# 记录突破信息
data: str # 时间
breakout_price: float # 突破价格
lose_price: float # 亏损价格
valid_or_not: str # 是否有效
win_or_lose: bool # 是否盈利
def calc_sma_atr_pd(kdf,period):
"""计算TR与ATR
@ -74,7 +84,15 @@ class TurtleTrading(object):
self.TrigerTime = 0
self.BuyStates = list[BuyState]
self.tradeslog = list[TradeLog] # 交易记录
self.tradeslog = list[TradeLog]
self.BreakOutLog = list[BreakOutLog]
self.PriceNow = 0.0
self.Donchian_20_up = 0.0
self.Donchian_10_down = 0.0
self.Donchian_50_up = 0.0
self.is_gap_up = False # 是否跳空高开
self.prev_heigh = 0.0 # 前一天最高价
def GetRecentData(self):
"""获取某个标的的最近数据,从两年前到今天, 计算后的数据保存在self.CurrentData
@ -259,7 +277,7 @@ class TurtleTrading(object):
return True
elif PriceNow > TempDonchian20Upper:#todo !=0不会满足条件 先跳过
self.system1BreakoutValid(PriceNow)
if BreakOutLog[-1][5] == 'Lose': # TT!= 0且突破且上一次突破unseccessful
if BreakOutLog[-1].win_or_lose == None: # TT!= 0且突破且上一次突破unseccessful
return True
else:
return False
@ -277,10 +295,10 @@ class TurtleTrading(object):
def system1BreakoutValid(self, priceNow):
"""判断前一次突破是否成功是log[-1][5]写入“win”否则写入“Lose”
"""
if priceNow < self.BreakOutLog[-1][3]:
self.BreakOutLog[-1][5] = 'Lose'
if priceNow < self.BreakOutLog[-1].lose_price:
self.BreakOutLog[-1].win_or_lose = None
else:
self.BreakOutLog[-1][5] = 'None'
self.BreakOutLog[-1].win_or_lose = True
# 一天结束计算ATR计算唐奇安通道追加到已有的mysql数据库中
def system_1_Out(self, PriceNow, TempDonchian10Lower):
@ -294,7 +312,7 @@ class TurtleTrading(object):
def add(self, PriceNow):
"""加仓
"""
if self.TrigerTime < 4 and PriceNow > self.BuyStates[self.TrigerTime - 1][2]:#todo BuyStates是空的
if self.TrigerTime < 4 and PriceNow > self.BuyStates[self.TrigerTime - 1].add_price:#todo BuyStates是空的
# 买入
return True
else:
@ -303,7 +321,7 @@ class TurtleTrading(object):
def system_1_stop(self, PriceNow):
"""止损判断:如果当前价格<上一次买入后的止损价格则止损
"""
if PriceNow < self.BuyStates[self.TrigerTime - 1][3]:
if PriceNow < self.BuyStates[self.TrigerTime - 1].stop_price:
# 买入
return True
else:
@ -346,126 +364,176 @@ class TurtleTrading_OnTime(object):
def Buy_stock(self, price_now):
# 发送邮件 代码self.turtle.TradeCode, 建议买入价格price_now买入份额self.turtle.IntPositionSize
if self.turtle.TrigerTime == 0: # 第一次买入
subject = "买入"
body = f"{self.turtle.TradeCode},价格{price_now},份额{self.turtle.IntPositionSize} \n "
body += "回复:实际买入价格-买入份额-手续费"
send_email(subject, body, self.user_email)
send_email_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
subject = "买入"
body = f"{self.turtle.TradeCode},价格{price_now},份额{self.turtle.IntPositionSize} \n "
body += "回复:实际买入价格-买入份额-手续费"
send_email(subject, body, self.user_email)
send_email_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
#每隔1分钟检测回信解析邮件。
parsed_email_flag = False
while not parsed_email_flag:
time.sleep(60) # 每次尝试前等待 60 秒
parse_states, buy_price, buy_share, fee = parse_return_email(
self.user_email, send_email_time
)
#每隔1分钟检测回信解析邮件。
if parse_states:
parsed_email_flag = True
break
parsed_email_flag = False
while not parsed_email_flag:
time.sleep(60) # 每次尝试前等待 60 秒
parse_states, buy_price, buy_share, fee = parse_return_email(
self.user_email, send_email_time
)
if parse_states:
parsed_email_flag = True
break
# 成功买入
self.turtle.TrigerTime += 1
# 记录self.turtle.BuyStates
add_price = buy_price + 1/2 * self.turtle.N
stop_price = buy_price - 2 * self.turtle.N
cost = buy_price * buy_share - fee
available_cash = self.turtle.Capital - cost
buy_this_time = BuyState(self.turtle.TrigerTime,
buy_price,
add_price,
stop_price,
buy_share,
self.turtle.N,
available_cash)
# 成功买入
self.turtle.TrigerTime += 1
# 记录self.turtle.BuyStates
add_price = buy_price + 1/2 * self.turtle.N
stop_price = buy_price - 2 * self.turtle.N
cost = buy_price * buy_share - fee
available_cash = self.turtle.Capital - cost
buy_this_time = BuyState(self.turtle.TrigerTime,
buy_price,
add_price,
stop_price,
False,
buy_share,
self.turtle.N,
available_cash)
self.turtle.BuyStates.append(buy_this_time)
self.turtle.BuyStates.append(buy_this_time)
# 记录self.turtle.tradeslog
today = datetime.now().strftime("%Y-%m-%d")
log_this_time = TradeLog(today,
"买入",
buy_price,
buy_share,
cost,
self.turtle.N,
available_cash,
all_shares=buy_share,
all_cost=cost,
Net_value=buy_price * buy_share,
Net_return=0)
self.turtle.tradeslog.append(log_this_time)
today = datetime.now().strftime("%Y-%m-%d")
log_this_time = TradeLog(today,
"买入",
buy_price,
buy_share,
cost,
self.turtle.N,
available_cash,
all_shares=buy_share,
all_cost=cost,
Net_value=buy_price * buy_share,
Net_return=0)
self.turtle.tradeslog.append(log_this_time)
else:
# 加仓
subject = "加仓"
body = f"{self.turtle.TradeCode},价格{price_now},份额{self.turtle.IntPositionSize} \n "
body += "回复:实际买入价格-买入份额-手续费"
send_email(subject, body, self.user_email)
send_email_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
#每隔1分钟检测回信解析邮件。
parsed_email_flag = False
while not parsed_email_flag:
time.sleep(60) # 每次尝试前等待 60 秒
parse_states, buy_price, buy_share, fee = parse_return_email(
self.user_email, send_email_time
)
if parse_states:
parsed_email_flag = True
break
# 成功买入
self.turtle.TrigerTime += 1
# 记录self.turtle.BuyStates
add_price = buy_price + 1/2 * self.turtle.N
stop_price = buy_price - 2 * self.turtle.N
cost = buy_price * buy_share - fee
available_cash = self.turtle.BuyStates[-1].available_cash - cost
all_shares = buy_share + self.turtle.BuyStates[-1].all_shares
all_cost = cost + self.turtle.BuyStates[-1].all_cost
net_value = buy_price * all_shares
net_return = net_value - all_cost
buy_this_time = BuyState(self.turtle.TrigerTime,
buy_price,
add_price,
stop_price,
buy_share,
self.turtle.N,
available_cash)
self.turtle.BuyStates.append(buy_this_time)
today = datetime.now().strftime("%Y-%m-%d")
log_this_time = TradeLog(today,
"加仓",
buy_price,
buy_share,
cost,
self.turtle.N,
available_cash,
all_shares,
all_cost,
net_value,
net_return)
self.turtle.tradeslog.append(log_this_time)
pass
def add_stock(self, price_now):
"""加仓
Args:
price_now (_type_): 现价
"""
# 加仓
subject = "加仓"
body = f"{self.turtle.TradeCode},价格{price_now},份额{self.turtle.IntPositionSize} \n "
body += "回复:实际买入价格-买入份额-手续费"
send_email(subject, body, self.user_email)
send_email_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
#每隔1分钟检测回信解析邮件。
parsed_email_flag = False
while not parsed_email_flag:
time.sleep(60) # 每次尝试前等待 60 秒
parse_states, buy_price, buy_share, fee = parse_return_email(
self.user_email, send_email_time
)
if parse_states:
parsed_email_flag = True
break
# 成功买入
self.turtle.TrigerTime += 1
# 记录self.turtle.BuyStates
add_price = buy_price + 1/2 * self.turtle.N
stop_price = buy_price - 2 * self.turtle.N
cost = buy_price * buy_share - fee
available_cash = self.turtle.BuyStates[-1].available_cash - cost
all_shares = buy_share + self.turtle.BuyStates[-1].all_shares
all_cost = cost + self.turtle.BuyStates[-1].all_cost
net_value = buy_price * all_shares
net_return = net_value - all_cost
buy_this_time = BuyState(self.turtle.TrigerTime,
buy_price,
add_price,
stop_price,
self.turtle.is_gap_up,
buy_share,
self.turtle.N,
available_cash)
self.turtle.BuyStates.append(buy_this_time)
today = datetime.now().strftime("%Y-%m-%d")
log_this_time = TradeLog(today,
"加仓",
buy_price,
buy_share,
cost,
self.turtle.N,
available_cash,
all_shares,
all_cost,
net_value,
net_return)
self.turtle.tradeslog.append(log_this_time)
# 处理其他次买入的止损价格
# 检查BuyStates中有几个gap_up,返回个数和索引
gap_up_num = 0
gap_up_index = []
for i in range(len(self.turtle.BuyStates)):
if self.turtle.BuyStates[i].is_gap_up:
gap_up_num += 1
gap_up_index.append(i)
if gap_up_num == 0:
# 之前BuyStates中的stop_price = stop_price
for j in range(len(self.turtle.BuyStates)):
self.turtle.BuyStates[j].stop_price = stop_price
if not self.turtle.is_gap_up and gap_up_num == 1:
if gap_up_index[0] == 1:
number_tobe_change = self.turtle.TrigerTime -1 - gap_up_index[0]
for k in range(number_tobe_change):
self.turtle.BuyStates[k+1].stop_price = stop_price
elif gap_up_index[0] == 2:
self.turtle.BuyStates[2].stop_price = stop_price
elif not self.turtle.is_gap_up and gap_up_num == 2:
number_tobe_change = 2
for k in range(number_tobe_change):
self.turtle.BuyStates[k+1].stop_price = stop_price
def stop_sale_stock(self, price_now):
"""止损卖出
Args:
price_now (_type_): 现价
"""
# 判断需要卖出几份
sale_shares = 0
for i in range(len(self.turtle.BuyStates)):
if price_now <= self.turtle.BuyStates[i].stop_price:
sale_shares += 1
break
# 比较price_now与self.turtle.BuyStates[-1].stop_price
# 发送邮件 代码self.turtle.TradeCode, 建议卖出价格price_now卖出份额self.turtle.IntPositionSize
subject = "止损卖出"
body = f"{self.turtle.TradeCode},价格{price_now},份额{self.turtle.IntPositionSize} \n "
body = f"{self.turtle.TradeCode},价格{price_now},份额{self.turtle.IntPositionSize * sale_shares} \n "
body += "回复:实际卖出价格-卖出份额-手续费"
send_email(subject, body, self.user_email)
send_email_time = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
@ -564,6 +632,8 @@ class TurtleTrading_OnTime(object):
(now.hour == 15 and now.minute <= 0)
)
# if not is_trading_time:
# # 非交易时间,等待 1 分钟后继续循环
# time.sleep(60)
@ -580,6 +650,11 @@ class TurtleTrading_OnTime(object):
# self.turtle.PriceNow = float(etf_data.loc[etf_data['基金代码'] == self.turtle.TradeCode, '当前-单位净值'].values[0])
self.turtle.PriceNow = float(etf_data.loc[etf_data['代码'] == self.turtle.TradeCode, '最新价'].values[0])
# # 9点30 判断是否跳空高开
if now.hour == 9 and now.minute == 30 and self.turtle.PriceNow > self.turtle.prev_heigh:
self.turtle.is_gap_up = True
# 判断当前仓位状态并执行相应操作
if self.turtle.TrigerTime == 0:
# 空仓状态
@ -589,6 +664,16 @@ class TurtleTrading_OnTime(object):
self.turtle.BreakOutLog
):
self.Buy_stock(self.turtle.PriceNow)
# 突破 记录self.turtle.breakoutlog
today = datetime.now().strftime("%Y-%m-%d")
breakout_this_time = BreakOutLog(today,
self.turtle.Donchian_20_up,
self.turtle.Donchian_20_up - 2 * self.turtle.N,
'valid',
None)
self.turtle.BreakOutLog.append(breakout_this_time)
elif self.turtle.system1EnterSafe(
self.turtle.PriceNow,
self.turtle.Donchian_50_up
@ -596,22 +681,28 @@ class TurtleTrading_OnTime(object):
self.Buy_stock(self.turtle.PriceNow)
elif 1 <= self.turtle.TrigerTime <= 3:
# # 突破状态
# if self.turtle.system1EnterNormal(
# self.turtle.PriceNow,
# self.turtle.Donchian_20_up,
# self.turtle.BreakOutLog
# ):
# self.Buy_stock(self.turtle.PriceNow)
# elif self.turtle.system1EnterSafe(
# self.turtle.PriceNow,
# self.turtle.Donchian_50_up
# ):
# self.Buy_stock(self.turtle.PriceNow)
# 加仓状态
if self.turtle.system1EnterNormal(
self.turtle.PriceNow,
self.turtle.Donchian_20_up,
self.turtle.BreakOutLog
):
self.Buy_stock(self.turtle.PriceNow)
elif self.turtle.system1EnterSafe(
self.turtle.PriceNow,
self.turtle.Donchian_50_up
):
self.Buy_stock(self.turtle.PriceNow)
elif self.turtle.add(self.turtle.PriceNow):
self.Buy_stock(self.turtle.PriceNow)
if self.turtle.add(self.turtle.PriceNow):
self.add_stock(self.turtle.PriceNow)
# 止损状态
elif self.turtle.system_1_stop(self.turtle.PriceNow):
self.stop_sale_stock(self.turtle.PriceNow)
# 止盈
elif self.turtle.system_1_Out(
self.turtle.PriceNow,
self.turtle.Donchian_10_down
@ -619,7 +710,7 @@ class TurtleTrading_OnTime(object):
self.out_sale_stock(self.turtle.PriceNow)
elif self.turtle.TrigerTime == 4:
# 满仓状态
# 满仓 止损 止盈
if self.turtle.system_1_stop(self.turtle.PriceNow):
self.stop_sale_stock(self.turtle.PriceNow)
elif self.turtle.system_1_Out(
@ -639,6 +730,7 @@ class TurtleTrading_OnTime(object):
# 获取数据或读取数据 -- 计算ATR Donchian 20 50 up, 20 down
self.turtle.get_ready(100)
self.turtle.N = float(self.turtle.CurrentData['ATR'].iloc[-1])
self.turtle.prev_heigh = float(self.turtle.CurrentData['最高价'].iloc[-1])
self.turtle.Donchian_20_up = float(self.turtle.CurrentData['Donchian_20_upper'].iloc[-1])
self.turtle.Donchian_50_up = float(self.turtle.CurrentData['Donchian_50_upper'].iloc[-1])
self.turtle.Donchian_10_down = float(self.turtle.CurrentData['Donchian_10_lower'].iloc[-1])

View File

@ -419,7 +419,7 @@ class Trade(object):
return True
elif self.TrigerTime != 0 and PriceNow > TempDonchian20Upper[-1]:
self.system1BreakoutValid(PriceNow)
if BreakOutLog[-1][5] == 'Lose': # TT!= 0且突破且上一次突破unseccessful
if BreakOutLog[-1][5] == 'Lose': # TrigerTime != 0且突破且上一次突破unseccessful
return True
else:
return False