INSTRUCTION stringlengths 1 46.3k | RESPONSE stringlengths 75 80.2k |
|---|---|
返回start_day到end_day中间有多少个交易天 算首尾 | def QA_util_get_trade_gap(start, end):
'返回start_day到end_day中间有多少个交易天 算首尾'
start, end = QA_util_get_real_datelist(start, end)
if start is not None:
return trade_date_sse.index(end) + 1 - trade_date_sse.index(start)
else:
return 0 |
:param date: 字符串起始日 类型 str eg: 2018-11-11
:param gap: 整数 间隔多数个交易日
:param methods: gt大于 ，gte 大于等于， 小于lt ，小于等于lte ， 等于===
:return: 字符串 eg：2000-01-01 | def QA_util_date_gap(date, gap, methods):
'''
:param date: 字符串起始日 类型 str eg: 2018-11-11
:param gap: 整数 间隔多数个交易日
:param methods: gt大于 ，gte 大于等于， 小于lt ，小于等于lte ， 等于===
:return: 字符串 eg：2000-01-01
'''
try:
if methods in ['>', 'gt']:
return trade_date_sse[trade_date_sse.index... |
交易的真实日期
Returns:
[type] -- [description] | def QA_util_get_trade_datetime(dt=datetime.datetime.now()):
"""交易的真实日期
Returns:
[type] -- [description]
"""
#dt= datetime.datetime.now()
if QA_util_if_trade(str(dt.date())) and dt.time() < datetime.time(15, 0, 0):
return str(dt.date())
else:
return QA_util_get_real_dat... |
委托的真实日期
Returns:
[type] -- [description] | def QA_util_get_order_datetime(dt):
"""委托的真实日期
Returns:
[type] -- [description]
"""
#dt= datetime.datetime.now()
dt = datetime.datetime.strptime(str(dt)[0:19], '%Y-%m-%d %H:%M:%S')
if QA_util_if_trade(str(dt.date())) and dt.time() < datetime.time(15, 0, 0):
return str(dt)
... |
输入是真实交易时间,返回按期货交易所规定的时间* 适用于tb/文华/博弈的转换
Arguments:
real_datetime {[type]} -- [description]
Returns:
[type] -- [description] | def QA_util_future_to_tradedatetime(real_datetime):
"""输入是真实交易时间,返回按期货交易所规定的时间* 适用于tb/文华/博弈的转换
Arguments:
real_datetime {[type]} -- [description]
Returns:
[type] -- [description]
"""
if len(str(real_datetime)) >= 19:
dt = datetime.datetime.strptime(
str(real_dat... |
输入是交易所规定的时间,返回真实时间*适用于通达信的时间转换
Arguments:
trade_datetime {[type]} -- [description]
Returns:
[type] -- [description] | def QA_util_future_to_realdatetime(trade_datetime):
"""输入是交易所规定的时间,返回真实时间*适用于通达信的时间转换
Arguments:
trade_datetime {[type]} -- [description]
Returns:
[type] -- [description]
"""
if len(str(trade_datetime)) == 19:
dt = datetime.datetime.strptime(
str(trade_datetime)... |
创建股票的小时线的index
Arguments:
day {[type]} -- [description]
Returns:
[type] -- [description] | def QA_util_make_hour_index(day, type_='1h'):
"""创建股票的小时线的index
Arguments:
day {[type]} -- [description]
Returns:
[type] -- [description]
"""
if QA_util_if_trade(day) is True:
return pd.date_range(
str(day) + ' 09:30:00',
str(day) + ' 11:30:00',
... |
分钟线回测的时候的gap | def QA_util_time_gap(time, gap, methods, type_):
'分钟线回测的时候的gap'
min_len = int(240 / int(str(type_).split('min')[0]))
day_gap = math.ceil(gap / min_len)
if methods in ['>', 'gt']:
data = pd.concat(
[
pd.DataFrame(QA_util_make_min_index(day,
... |
QA_util_save_csv(data,name,column,location)
将list保存成csv
第一个参数是list
第二个参数是要保存的名字
第三个参数是行的名称(可选)
第四个是保存位置(可选)
@yutiansut | def QA_util_save_csv(data, name, column=None, location=None):
# 重写了一下保存的模式
# 增加了对于可迭代对象的判断 2017/8/10
"""
QA_util_save_csv(data,name,column,location)
将list保存成csv
第一个参数是list
第二个参数是要保存的名字
第三个参数是行的名称(可选)
第四个是保存位置(可选)
@yutiansut
"""
assert isinstance(data, list)
if locat... |
查询现金和持仓
Arguments:
accounts {[type]} -- [description]
Returns:
dict-- {'cash_available':xxx,'hold_available':xxx} | def query_positions(self, accounts):
"""查询现金和持仓
Arguments:
accounts {[type]} -- [description]
Returns:
dict-- {'cash_available':xxx,'hold_available':xxx}
"""
try:
data = self.call("positions", {'client': accounts})
if data is not ... |
查询clients
Returns:
[type] -- [description] | def query_clients(self):
"""查询clients
Returns:
[type] -- [description]
"""
try:
data = self.call("clients", {'client': 'None'})
if len(data) > 0:
return pd.DataFrame(data).drop(
['commandLine',
... |
查询订单
Arguments:
accounts {[type]} -- [description]
Keyword Arguments:
status {str} -- 'open' 待成交 'filled' 成交 (default: {'filled'})
Returns:
[type] -- [description] | def query_orders(self, accounts, status='filled'):
"""查询订单
Arguments:
accounts {[type]} -- [description]
Keyword Arguments:
status {str} -- 'open' 待成交 'filled' 成交 (default: {'filled'})
Returns:
[type] -- [description]
"""
try:
... |
[summary]
Arguments:
accounts {[type]} -- [description]
code {[type]} -- [description]
price {[type]} -- [description]
amount {[type]} -- [description]
Keyword Arguments:
order_direction {[type]} -- [description] (default: {ORDER_DIRECTION.BU... | def send_order(
self,
accounts,
code='000001',
price=9,
amount=100,
order_direction=ORDER_DIRECTION.BUY,
order_model=ORDER_MODEL.LIMIT
):
"""[summary]
Arguments:
accounts {[type]} -- [description]
... |
获取某一时间的某一只股票的指标 | def get_indicator(self, time, code, indicator_name=None):
"""
获取某一时间的某一只股票的指标
"""
try:
return self.data.loc[(pd.Timestamp(time), code), indicator_name]
except:
raise ValueError('CANNOT FOUND THIS DATE&CODE') |
获取某一段时间的某一只股票的指标 | def get_timerange(self, start, end, code=None):
"""
获取某一段时间的某一只股票的指标
"""
try:
return self.data.loc[(slice(pd.Timestamp(start), pd.Timestamp(end)), slice(code)), :]
except:
return ValueError('CANNOT FOUND THIS TIME RANGE') |
获取已经被终止上市的股票列表，数据从上交所获取，目前只有在上海证券交易所交易被终止的股票。
collection：
code：股票代码 name：股票名称 oDate:上市日期 tDate:终止上市日期
:param client:
:return: None | def QA_SU_save_stock_terminated(client=DATABASE):
'''
获取已经被终止上市的股票列表，数据从上交所获取，目前只有在上海证券交易所交易被终止的股票。
collection：
code：股票代码 name：股票名称 oDate:上市日期 tDate:终止上市日期
:param client:
:return: None
'''
# 🛠todo 已经失效从wind 资讯里获取
# 这个函数已经失效
print("！！！ tushare 这个函数已经失效！！！")
df = QATs.get... |
获取 股票的 基本信息，包含股票的如下信息
code,代码
name,名称
industry,所属行业
area,地区
pe,市盈率
outstanding,流通股本(亿)
totals,总股本(亿)
totalAssets,总资产(万)
liquidAssets,流动资产
fixedAssets,固定资产
reserved,公积金
reservedPerShare,每股公积金
esp,每股收益
bvps,每股... | def QA_SU_save_stock_info_tushare(client=DATABASE):
'''
获取 股票的 基本信息，包含股票的如下信息
code,代码
name,名称
industry,所属行业
area,地区
pe,市盈率
outstanding,流通股本(亿)
totals,总股本(亿)
totalAssets,总资产(万)
liquidAssets,流动资产
fixedAssets,固定资产
reserved... |
save stock_day
保存日线数据
:param client:
:param ui_log: 给GUI qt 界面使用
:param ui_progress: 给GUI qt 界面使用
:param ui_progress_int_value: 给GUI qt 界面使用 | def QA_SU_save_stock_day(client=DATABASE, ui_log=None, ui_progress=None):
'''
save stock_day
保存日线数据
:param client:
:param ui_log: 给GUI qt 界面使用
:param ui_progress: 给GUI qt 界面使用
:param ui_progress_int_value: 给GUI qt 界面使用
'''
stock_list = QA_fetch_get_stock_list()
# TODO: 重命名stock... |
输入一个dict 返回删除后的 | def QA_util_dict_remove_key(dicts, key):
"""
输入一个dict 返回删除后的
"""
if isinstance(key, list):
for item in key:
try:
dicts.pop(item)
except:
pass
else:
try:
dicts.pop(key)
except:
pass
return dic... |
异步mongo示例
Keyword Arguments:
uri {str} -- [description] (default: {'mongodb://localhost:27017/quantaxis'})
Returns:
[type] -- [description] | def QA_util_sql_async_mongo_setting(uri='mongodb://localhost:27017/quantaxis'):
"""异步mongo示例
Keyword Arguments:
uri {str} -- [description] (default: {'mongodb://localhost:27017/quantaxis'})
Returns:
[type] -- [description]
"""
# loop = asyncio.new_event_loop()
# asyncio.set_eve... |
portfolio add a account/stratetgy | def add_account(self, account):
'portfolio add a account/stratetgy'
if account.account_cookie not in self.account_list:
if self.cash_available > account.init_cash:
account.portfolio_cookie = self.portfolio_cookie
account.user_cookie = self.user_cookie
... |
删除一个account
Arguments:
account_cookie {[type]} -- [description]
Raises:
RuntimeError -- [description] | def drop_account(self, account_cookie):
"""删除一个account
Arguments:
account_cookie {[type]} -- [description]
Raises:
RuntimeError -- [description]
"""
if account_cookie in self.account_list:
res = self.account_list.remove(account_cookie)
... |
创建一个新的Account
Keyword Arguments:
account_cookie {[type]} -- [description] (default: {None})
Returns:
[type] -- [description] | def new_account(
self,
account_cookie=None,
init_cash=1000000,
market_type=MARKET_TYPE.STOCK_CN,
*args,
**kwargs
):
"""创建一个新的Account
Keyword Arguments:
account_cookie {[type]} -- [description] (default: {None})
... |
'give the account_cookie and return the account/strategy back'
:param cookie:
:return: QA_Account with cookie if in dict
None not in list | def get_account_by_cookie(self, cookie):
'''
'give the account_cookie and return the account/strategy back'
:param cookie:
:return: QA_Account with cookie if in dict
None not in list
'''
try:
return QA_Account(
account_cookie=c... |
check the account whether in the protfolio dict or not
:param account: QA_Account
:return: QA_Account if in dict
None not in list | def get_account(self, account):
'''
check the account whether in the protfolio dict or not
:param account: QA_Account
:return: QA_Account if in dict
None not in list
'''
try:
return self.get_account_by_cookie(account.account_cookie)
e... |
portfolio 的cookie | def message(self):
"""portfolio 的cookie
"""
return {
'user_cookie': self.user_cookie,
'portfolio_cookie': self.portfolio_cookie,
'account_list': list(self.account_list),
'init_cash': self.init_cash,
'cash': self.cash,
'histo... |
基于portfolio对子账户下单
Arguments:
account_cookie {str} -- [description]
Keyword Arguments:
code {[type]} -- [description] (default: {None})
amount {[type]} -- [description] (default: {None})
time {[type]} -- [description] (default: {None})
towards... | def send_order(
self,
account_cookie: str,
code=None,
amount=None,
time=None,
towards=None,
price=None,
money=None,
order_model=None,
amount_model=None,
*args,
**kwargs
):
... |
每日每个股票持仓市值表
Returns:
pd.DataFrame -- 市值表 | def market_value(self):
"""每日每个股票持仓市值表
Returns:
pd.DataFrame -- 市值表
"""
if self.account.daily_hold is not None:
if self.if_fq:
return (
self.market_data.to_qfq().pivot('close').fillna(
method='ffill'
... |
存储过程 | def save(self):
"""存储过程
"""
self.client.update(
{
'portfolio_cookie': self.portfolio_cookie,
'user_cookie': self.user_cookie
},
{'$set': self.message},
upsert=True
) |
最大回撤 | def max_dropback(self):
"""最大回撤
"""
return round(
float(
max(
[
(self.assets.iloc[idx] - self.assets.iloc[idx::].min())
/ self.assets.iloc[idx]
for idx in range(len(self.assets... |
总手续费 | def total_commission(self):
"""总手续费
"""
return float(
-abs(round(self.account.history_table.commission.sum(),
2))
) |
总印花税 | def total_tax(self):
"""总印花税
"""
return float(-abs(round(self.account.history_table.tax.sum(), 2))) |
利润构成
Returns:
dict -- 利润构成表 | def profit_construct(self):
"""利润构成
Returns:
dict -- 利润构成表
"""
return {
'total_buyandsell':
round(
self.profit_money - self.total_commission - self.total_tax,
2
),
'total_tax':
self.... |
盈利额
Returns:
[type] -- [description] | def profit_money(self):
"""盈利额
Returns:
[type] -- [description]
"""
return float(round(self.assets.iloc[-1] - self.assets.iloc[0], 2)) |
年化收益
Returns:
[type] -- [description] | def annualize_return(self):
"""年化收益
Returns:
[type] -- [description]
"""
return round(
float(self.calc_annualize_return(self.assets,
self.time_gap)),
2
) |
基准组合的行情数据(一般是组合,可以调整) | def benchmark_data(self):
"""
基准组合的行情数据(一般是组合,可以调整)
"""
return self.fetch[self.benchmark_type](
self.benchmark_code,
self.account.start_date,
self.account.end_date
) |
基准组合的账户资产队列 | def benchmark_assets(self):
"""
基准组合的账户资产队列
"""
return (
self.benchmark_data.close /
float(self.benchmark_data.close.iloc[0])
* float(self.assets[0])
) |
基准组合的年化收益
Returns:
[type] -- [description] | def benchmark_annualize_return(self):
"""基准组合的年化收益
Returns:
[type] -- [description]
"""
return round(
float(
self.calc_annualize_return(
self.benchmark_assets,
self.time_gap
)
),... |
beta比率 组合的系统性风险 | def beta(self):
"""
beta比率 组合的系统性风险
"""
try:
res = round(
float(
self.calc_beta(
self.profit_pct.dropna(),
self.benchmark_profitpct.dropna()
)
),
... |
alpha比率 与市场基准收益无关的超额收益率 | def alpha(self):
"""
alpha比率 与市场基准收益无关的超额收益率
"""
return round(
float(
self.calc_alpha(
self.annualize_return,
self.benchmark_annualize_return,
self.beta,
0.05
)
... |
夏普比率 | def sharpe(self):
"""
夏普比率
"""
return round(
float(
self.calc_sharpe(self.annualize_return,
self.volatility,
0.05)
),
2
) |
资金曲线叠加图
@Roy T.Burns 2018/05/29 修改百分比显示错误 | def plot_assets_curve(self, length=14, height=12):
"""
资金曲线叠加图
@Roy T.Burns 2018/05/29 修改百分比显示错误
"""
plt.style.use('ggplot')
plt.figure(figsize=(length, height))
plt.subplot(211)
plt.title('BASIC INFO', fontsize=12)
plt.axis([0, length, 0, 0.6])
... |
使用热力图画出买卖信号 | def plot_signal(self, start=None, end=None):
"""
使用热力图画出买卖信号
"""
start = self.account.start_date if start is None else start
end = self.account.end_date if end is None else end
_, ax = plt.subplots(figsize=(20, 18))
sns.heatmap(
self.account.trade.rese... |
使用后进先出法配对成交记录 | def pnl_lifo(self):
"""
使用后进先出法配对成交记录
"""
X = dict(
zip(
self.target.code,
[LifoQueue() for i in range(len(self.target.code))]
)
)
pair_table = []
for _, data in self.target.history_table_min.iterrows():
... |
画出pnl比率散点图 | def plot_pnlratio(self):
"""
画出pnl比率散点图
"""
plt.scatter(x=self.pnl.sell_date.apply(str), y=self.pnl.pnl_ratio)
plt.gcf().autofmt_xdate()
return plt |
画出pnl盈亏额散点图 | def plot_pnlmoney(self):
"""
画出pnl盈亏额散点图
"""
plt.scatter(x=self.pnl.sell_date.apply(str), y=self.pnl.pnl_money)
plt.gcf().autofmt_xdate()
return plt |
胜率
胜率
盈利次数/总次数 | def win_rate(self):
"""胜率
胜率
盈利次数/总次数
"""
data = self.pnl
try:
return round(len(data.query('pnl_money>0')) / len(data), 2)
except ZeroDivisionError:
return 0 |
Get the local time of the next schedule time this job will run.
:param bool asc: Format the result with ``time.asctime()``
:returns: The epoch time or string representation of the epoch time that
the job should be run next | def next_time(self, asc=False):
"""Get the local time of the next schedule time this job will run.
:param bool asc: Format the result with ``time.asctime()``
:returns: The epoch time or string representation of the epoch time that
the job should be run next
"""
_time ... |
期货实时tick | def QA_fetch_get_future_transaction_realtime(package, code):
"""
期货实时tick
"""
Engine = use(package)
if package in ['tdx', 'pytdx']:
return Engine.QA_fetch_get_future_transaction_realtime(code)
else:
return 'Unsupport packages' |
MA
Arguments:
DataFrame {[type]} -- [description]
Returns:
[type] -- [description] | def QA_indicator_MA(DataFrame,*args,**kwargs):
"""MA
Arguments:
DataFrame {[type]} -- [description]
Returns:
[type] -- [description]
"""
CLOSE = DataFrame['close']
return pd.DataFrame({'MA{}'.format(N): MA(CLOSE, N) for N in list(args)}) |
MACD CALC | def QA_indicator_MACD(DataFrame, short=12, long=26, mid=9):
"""
MACD CALC
"""
CLOSE = DataFrame['close']
DIF = EMA(CLOSE, short)-EMA(CLOSE, long)
DEA = EMA(DIF, mid)
MACD = (DIF-DEA)*2
return pd.DataFrame({'DIF': DIF, 'DEA': DEA, 'MACD': MACD}) |
趋向指标 DMI | def QA_indicator_DMI(DataFrame, M1=14, M2=6):
"""
趋向指标 DMI
"""
HIGH = DataFrame.high
LOW = DataFrame.low
CLOSE = DataFrame.close
OPEN = DataFrame.open
TR = SUM(MAX(MAX(HIGH-LOW, ABS(HIGH-REF(CLOSE, 1))),
ABS(LOW-REF(CLOSE, 1))), M1)
HD = HIGH-REF(HIGH, 1)
LD = R... |
瀑布线 | def QA_indicator_PBX(DataFrame, N1=3, N2=5, N3=8, N4=13, N5=18, N6=24):
'瀑布线'
C = DataFrame['close']
PBX1 = (EMA(C, N1) + EMA(C, 2 * N1) + EMA(C, 4 * N1)) / 3
PBX2 = (EMA(C, N2) + EMA(C, 2 * N2) + EMA(C, 4 * N2)) / 3
PBX3 = (EMA(C, N3) + EMA(C, 2 * N3) + EMA(C, 4 * N3)) / 3
PBX4 = (EMA(C, N4) + ... |
平均线差 DMA | def QA_indicator_DMA(DataFrame, M1=10, M2=50, M3=10):
"""
平均线差 DMA
"""
CLOSE = DataFrame.close
DDD = MA(CLOSE, M1) - MA(CLOSE, M2)
AMA = MA(DDD, M3)
return pd.DataFrame({
'DDD': DDD, 'AMA': AMA
}) |
动量线 | def QA_indicator_MTM(DataFrame, N=12, M=6):
'动量线'
C = DataFrame.close
mtm = C - REF(C, N)
MTMMA = MA(mtm, M)
DICT = {'MTM': mtm, 'MTMMA': MTMMA}
return pd.DataFrame(DICT) |
指数平均线 EXPMA | def QA_indicator_EXPMA(DataFrame, P1=5, P2=10, P3=20, P4=60):
""" 指数平均线 EXPMA"""
CLOSE = DataFrame.close
MA1 = EMA(CLOSE, P1)
MA2 = EMA(CLOSE, P2)
MA3 = EMA(CLOSE, P3)
MA4 = EMA(CLOSE, P4)
return pd.DataFrame({
'MA1': MA1, 'MA2': MA2, 'MA3': MA3, 'MA4': MA4
}) |
佳庆指标 CHO | def QA_indicator_CHO(DataFrame, N1=10, N2=20, M=6):
"""
佳庆指标 CHO
"""
HIGH = DataFrame.high
LOW = DataFrame.low
CLOSE = DataFrame.close
VOL = DataFrame.volume
MID = SUM(VOL*(2*CLOSE-HIGH-LOW)/(HIGH+LOW), 0)
CHO = MA(MID, N1)-MA(MID, N2)
MACHO = MA(CHO, M)
return pd.DataFrame({... |
乖离率 | def QA_indicator_BIAS(DataFrame, N1, N2, N3):
'乖离率'
CLOSE = DataFrame['close']
BIAS1 = (CLOSE - MA(CLOSE, N1)) / MA(CLOSE, N1) * 100
BIAS2 = (CLOSE - MA(CLOSE, N2)) / MA(CLOSE, N2) * 100
BIAS3 = (CLOSE - MA(CLOSE, N3)) / MA(CLOSE, N3) * 100
DICT = {'BIAS1': BIAS1, 'BIAS2': BIAS2, 'BIAS3': BIAS3}... |
变动率指标 | def QA_indicator_ROC(DataFrame, N=12, M=6):
'变动率指标'
C = DataFrame['close']
roc = 100 * (C - REF(C, N)) / REF(C, N)
ROCMA = MA(roc, M)
DICT = {'ROC': roc, 'ROCMA': ROCMA}
return pd.DataFrame(DICT) |
TYP:=(HIGH+LOW+CLOSE)/3;
CCI:(TYP-MA(TYP,N))/(0.015*AVEDEV(TYP,N)); | def QA_indicator_CCI(DataFrame, N=14):
"""
TYP:=(HIGH+LOW+CLOSE)/3;
CCI:(TYP-MA(TYP,N))/(0.015*AVEDEV(TYP,N));
"""
typ = (DataFrame['high'] + DataFrame['low'] + DataFrame['close']) / 3
cci = ((typ - MA(typ, N)) / (0.015 * AVEDEV(typ, N)))
a = 100
b = -100
return pd.DataFrame({
... |
威廉指标 | def QA_indicator_WR(DataFrame, N, N1):
'威廉指标'
HIGH = DataFrame['high']
LOW = DataFrame['low']
CLOSE = DataFrame['close']
WR1 = 100 * (HHV(HIGH, N) - CLOSE) / (HHV(HIGH, N) - LLV(LOW, N))
WR2 = 100 * (HHV(HIGH, N1) - CLOSE) / (HHV(HIGH, N1) - LLV(LOW, N1))
DICT = {'WR1': WR1, 'WR2': WR2}
... |
变动速率线
震荡量指标OSC，也叫变动速率线。属于超买超卖类指标,是从移动平均线原理派生出来的一种分析指标。
它反应当日收盘价与一段时间内平均收盘价的差离值,从而测出股价的震荡幅度。
按照移动平均线原理，根据OSC的值可推断价格的趋势，如果远离平均线，就很可能向平均线回归。 | def QA_indicator_OSC(DataFrame, N=20, M=6):
"""变动速率线
震荡量指标OSC，也叫变动速率线。属于超买超卖类指标,是从移动平均线原理派生出来的一种分析指标。
它反应当日收盘价与一段时间内平均收盘价的差离值,从而测出股价的震荡幅度。
按照移动平均线原理，根据OSC的值可推断价格的趋势，如果远离平均线，就很可能向平均线回归。
"""
C = DataFrame['close']
OS = (C - MA(C, N)) * 100
MAOSC = EMA(OS, M)
DICT = {'OSC': OS, 'MAOS... |
相对强弱指标RSI1:SMA(MAX(CLOSE-LC,0),N1,1)/SMA(ABS(CLOSE-LC),N1,1)*100; | def QA_indicator_RSI(DataFrame, N1=12, N2=26, N3=9):
'相对强弱指标RSI1:SMA(MAX(CLOSE-LC,0),N1,1)/SMA(ABS(CLOSE-LC),N1,1)*100;'
CLOSE = DataFrame['close']
LC = REF(CLOSE, 1)
RSI1 = SMA(MAX(CLOSE - LC, 0), N1) / SMA(ABS(CLOSE - LC), N1) * 100
RSI2 = SMA(MAX(CLOSE - LC, 0), N2) / SMA(ABS(CLOSE - LC), N2) * 1... |
动态买卖气指标 | def QA_indicator_ADTM(DataFrame, N=23, M=8):
'动态买卖气指标'
HIGH = DataFrame.high
LOW = DataFrame.low
OPEN = DataFrame.open
DTM = IF(OPEN > REF(OPEN, 1), MAX((HIGH - OPEN), (OPEN - REF(OPEN, 1))), 0)
DBM = IF(OPEN < REF(OPEN, 1), MAX((OPEN - LOW), (OPEN - REF(OPEN, 1))), 0)
STM = SUM(DTM, N)
... |
LC=REF(CLOSE,1);
AA=ABS(HIGH-LC);
BB=ABS(LOW-LC);
CC=ABS(HIGH-REF(LOW,1));
DD=ABS(LC-REF(OPEN,1));
R=IF(AA>BB AND AA>CC,AA+BB/2+DD/4,IF(BB>CC AND BB>AA,BB+AA/2+DD/4,CC+DD/4));
X=(CLOSE-LC+(CLOSE-OPEN)/2+LC-REF(OPEN,1));
SI=16*X/R*MAX(AA,BB);
ASI:SUM(SI,M1);
ASIT:MA(ASI,M2); | def QA_indicator_ASI(DataFrame, M1=26, M2=10):
"""
LC=REF(CLOSE,1);
AA=ABS(HIGH-LC);
BB=ABS(LOW-LC);
CC=ABS(HIGH-REF(LOW,1));
DD=ABS(LC-REF(OPEN,1));
R=IF(AA>BB AND AA>CC,AA+BB/2+DD/4,IF(BB>CC AND BB>AA,BB+AA/2+DD/4,CC+DD/4));
X=(CLOSE-LC+(CLOSE-OPEN)/2+LC-REF(OPEN,1));
SI=16*X/R*MAX... |
能量潮 | def QA_indicator_OBV(DataFrame):
"""能量潮"""
VOL = DataFrame.volume
CLOSE = DataFrame.close
return pd.DataFrame({
'OBV': np.cumsum(IF(CLOSE > REF(CLOSE, 1), VOL, IF(CLOSE < REF(CLOSE, 1), -VOL, 0)))/10000
}) |
布林线 | def QA_indicator_BOLL(DataFrame, N=20, P=2):
'布林线'
C = DataFrame['close']
boll = MA(C, N)
UB = boll + P * STD(C, N)
LB = boll - P * STD(C, N)
DICT = {'BOLL': boll, 'UB': UB, 'LB': LB}
return pd.DataFrame(DICT) |
MIKE指标
指标说明
MIKE是另外一种形式的路径指标。
买卖原则
1 WEAK-S，MEDIUM-S，STRONG-S三条线代表初级、中级、强力支撑。
2 WEAK-R，MEDIUM-R，STRONG-R三条线代表初级、中级、强力压力。 | def QA_indicator_MIKE(DataFrame, N=12):
"""
MIKE指标
指标说明
MIKE是另外一种形式的路径指标。
买卖原则
1 WEAK-S，MEDIUM-S，STRONG-S三条线代表初级、中级、强力支撑。
2 WEAK-R，MEDIUM-R，STRONG-R三条线代表初级、中级、强力压力。
"""
HIGH = DataFrame.high
LOW = DataFrame.low
CLOSE = DataFrame.close
TYP = (HIGH+LOW+CLOSE)/3
LL = ... |
多空指标 | def QA_indicator_BBI(DataFrame, N1=3, N2=6, N3=12, N4=24):
'多空指标'
C = DataFrame['close']
bbi = (MA(C, N1) + MA(C, N2) + MA(C, N3) + MA(C, N4)) / 4
DICT = {'BBI': bbi}
return pd.DataFrame(DICT) |
资金指标
TYP := (HIGH + LOW + CLOSE)/3;
V1:=SUM(IF(TYP>REF(TYP,1),TYP*VOL,0),N)/SUM(IF(TYP<REF(TYP,1),TYP*VOL,0),N);
MFI:100-(100/(1+V1));
赋值: (最高价 + 最低价 + 收盘价)/3
V1赋值:如果TYP>1日前的TYP,返回TYP*成交量(手),否则返回0的N日累和/如果TYP<1日前的TYP,返回TYP*成交量(手),否则返回0的N日累和
输出资金流量指标:100-(100/(1+V1)) | def QA_indicator_MFI(DataFrame, N=14):
"""
资金指标
TYP := (HIGH + LOW + CLOSE)/3;
V1:=SUM(IF(TYP>REF(TYP,1),TYP*VOL,0),N)/SUM(IF(TYP<REF(TYP,1),TYP*VOL,0),N);
MFI:100-(100/(1+V1));
赋值: (最高价 + 最低价 + 收盘价)/3
V1赋值:如果TYP>1日前的TYP,返回TYP*成交量(手),否则返回0的N日累和/如果TYP<1日前的TYP,返回TYP*成交量(手),否则返回0的N日累和
输出资金流... |
输出TR:(最高价-最低价)和昨收-最高价的绝对值的较大值和昨收-最低价的绝对值的较大值
输出真实波幅:TR的N日简单移动平均
算法：今日振幅、今日最高与昨收差价、今日最低与昨收差价中的最大值，为真实波幅，求真实波幅的N日移动平均
参数：N 天数，一般取14 | def QA_indicator_ATR(DataFrame, N=14):
"""
输出TR:(最高价-最低价)和昨收-最高价的绝对值的较大值和昨收-最低价的绝对值的较大值
输出真实波幅:TR的N日简单移动平均
算法：今日振幅、今日最高与昨收差价、今日最低与昨收差价中的最大值，为真实波幅，求真实波幅的N日移动平均
参数：N 天数，一般取14
"""
C = DataFrame['close']
H = DataFrame['high']
L = DataFrame['low']
TR = MAX(MAX((H - L), ABS(REF(C, 1)... |
1.指标>80 时，回档机率大；指标<20 时，反弹机率大；
2.K在20左右向上交叉D时，视为买进信号参考；
3.K在80左右向下交叉D时，视为卖出信号参考；
4.SKDJ波动于50左右的任何讯号，其作用不大。 | def QA_indicator_SKDJ(DataFrame, N=9, M=3):
"""
1.指标>80 时，回档机率大；指标<20 时，反弹机率大；
2.K在20左右向上交叉D时，视为买进信号参考；
3.K在80左右向下交叉D时，视为卖出信号参考；
4.SKDJ波动于50左右的任何讯号，其作用不大。
"""
CLOSE = DataFrame['close']
LOWV = LLV(DataFrame['low'], N)
HIGHV = HHV(DataFrame['high'], N)
RSV = EMA((CLOSE - LOWV) /... |
'方向标准离差指数'
分析DDI柱状线，由红变绿(正变负)，卖出信号参考；由绿变红，买入信号参考。 | def QA_indicator_DDI(DataFrame, N=13, N1=26, M=1, M1=5):
"""
'方向标准离差指数'
分析DDI柱状线，由红变绿(正变负)，卖出信号参考；由绿变红，买入信号参考。
"""
H = DataFrame['high']
L = DataFrame['low']
DMZ = IF((H + L) > (REF(H, 1) + REF(L, 1)),
MAX(ABS(H - REF(H, 1)), ABS(L - REF(L, 1))), 0)
DMF = IF((H + L) < (REF... |
上下影线指标 | def QA_indicator_shadow(DataFrame):
"""
上下影线指标
"""
return {
'LOW': lower_shadow(DataFrame), 'UP': upper_shadow(DataFrame),
'BODY': body(DataFrame), 'BODY_ABS': body_abs(DataFrame), 'PRICE_PCG': price_pcg(DataFrame)
} |
:type series: List
:type exponent: int
:rtype: float | def run(self, series, exponent=None):
'''
:type series: List
:type exponent: int
:rtype: float
'''
try:
return self.calculateHurst(series, exponent)
except Exception as e:
print(" Error: %s" % e) |
:type seriesLenght: int
:rtype: int | def bestExponent(self, seriesLenght):
'''
:type seriesLenght: int
:rtype: int
'''
i = 0
cont = True
while(cont):
if(int(seriesLenght/int(math.pow(2, i))) <= 1):
cont = False
else:
i += 1
return int(i-... |
:type start: int
:type limit: int
:rtype: float | def mean(self, series, start, limit):
'''
:type start: int
:type limit: int
:rtype: float
'''
return float(np.mean(series[start:limit])) |
:type start: int
:type limit: int
:type mean: int
:rtype: list() | def deviation(self, series, start, limit, mean):
'''
:type start: int
:type limit: int
:type mean: int
:rtype: list()
'''
d = []
for x in range(start, limit):
d.append(float(series[x] - mean))
return d |
:type start: int
:type limit: int
:rtype: float | def standartDeviation(self, series, start, limit):
'''
:type start: int
:type limit: int
:rtype: float
'''
return float(np.std(series[start:limit])) |
:type series: List
:type exponent: int
:rtype: float | def calculateHurst(self, series, exponent=None):
'''
:type series: List
:type exponent: int
:rtype: float
'''
rescaledRange = list()
sizeRange = list()
rescaledRangeMean = list()
if(exponent is None):
exponent = self.bestExponent(len(s... |
邮件发送
Arguments:
msg {[type]} -- [description]
title {[type]} -- [description]
from_user {[type]} -- [description]
from_password {[type]} -- [description]
to_addr {[type]} -- [description]
smtp {[type]} -- [description] | def QA_util_send_mail(msg, title, from_user, from_password, to_addr, smtp):
"""邮件发送
Arguments:
msg {[type]} -- [description]
title {[type]} -- [description]
from_user {[type]} -- [description]
from_password {[type]} -- [description]
to_addr {[type]} -- [description]
... |
'zyfw', 主营范围 'jyps'#经营评述 'zygcfx' 主营构成分析
date 主营构成 主营收入(元) 收入比例cbbl 主营成本(元) 成本比例 主营利润(元) 利润比例 毛利率(%)
行业 /产品/ 区域 hq cp qy | def QA_fetch_get_stock_analysis(code):
"""
'zyfw', 主营范围 'jyps'#经营评述 'zygcfx' 主营构成分析
date 主营构成 主营收入(元) 收入比例cbbl 主营成本(元) 成本比例 主营利润(元) 利润比例 毛利率(%)
行业 /产品/ 区域 hq cp qy
"""
market = 'sh' if _select_market_code(code) == 1 else 'sz'
null = 'none'
data = eval(requests.get(BusinessAnalysis_url.f... |
下单
Arguments:
code {[type]} -- [description]
price {[type]} -- [description]
amount {[type]} -- [description]
towards {[type]} -- [description]
order_model {[type]} -- [description]
market:市场，SZ 深交所，SH 上交所
Returns:
[ty... | def send_order(self, code, price, amount, towards, order_model, market=None):
"""下单
Arguments:
code {[type]} -- [description]
price {[type]} -- [description]
amount {[type]} -- [description]
towards {[type]} -- [description]
order_model {[typ... |
#返回所有月份，以及每月的起始日期、结束日期，字典格式 | def QA_util_getBetweenMonth(from_date, to_date):
"""
#返回所有月份，以及每月的起始日期、结束日期，字典格式
"""
date_list = {}
begin_date = datetime.datetime.strptime(from_date, "%Y-%m-%d")
end_date = datetime.datetime.strptime(to_date, "%Y-%m-%d")
while begin_date <= end_date:
date_str = begin_date.strftime("... |
#返回dt隔months个月后的日期，months相当于步长 | def QA_util_add_months(dt, months):
"""
#返回dt隔months个月后的日期，months相当于步长
"""
dt = datetime.datetime.strptime(
dt, "%Y-%m-%d") + relativedelta(months=months)
return(dt) |
获取下个月第一天的日期
:return: 返回日期 | def QA_util_get_1st_of_next_month(dt):
"""
获取下个月第一天的日期
:return: 返回日期
"""
year = dt.year
month = dt.month
if month == 12:
month = 1
year += 1
else:
month += 1
res = datetime.datetime(year, month, 1)
return res |
#加上每季度的起始日期、结束日期 | def QA_util_getBetweenQuarter(begin_date, end_date):
"""
#加上每季度的起始日期、结束日期
"""
quarter_list = {}
month_list = QA_util_getBetweenMonth(begin_date, end_date)
for value in month_list:
tempvalue = value.split("-")
year = tempvalue[0]
if tempvalue[1] in ['01', '02', '03']:
... |
save account
Arguments:
message {[type]} -- [description]
Keyword Arguments:
collection {[type]} -- [description] (default: {DATABASE}) | def save_account(message, collection=DATABASE.account):
"""save account
Arguments:
message {[type]} -- [description]
Keyword Arguments:
collection {[type]} -- [description] (default: {DATABASE})
"""
try:
collection.create_index(
[("account_cookie", ASCENDING), (... |
本地存储financialdata | def QA_SU_save_financial_files():
"""本地存储financialdata
"""
download_financialzip()
coll = DATABASE.financial
coll.create_index(
[("code", ASCENDING), ("report_date", ASCENDING)], unique=True)
for item in os.listdir(download_path):
if item[0:4] != 'gpcw':
print(
... |
QUANTAXIS Log Module
@yutiansut
QA_util_log_x is under [QAStandard#0.0.2@602-x] Protocol | def QA_util_log_info(
logs,
ui_log=None,
ui_progress=None,
ui_progress_int_value=None,
):
"""
QUANTAXIS Log Module
@yutiansut
QA_util_log_x is under [QAStandard#0.0.2@602-x] Protocol
"""
logging.warning(logs)
# 给GUI使用，更新当前任务到日志和进度
if ui_log is not None:
... |
save file
Arguments:
file_dir {str:direction} -- 文件的地址
Keyword Arguments:
client {Mongodb:Connection} -- Mongo Connection (default: {DATABASE}) | def QA_save_tdx_to_mongo(file_dir, client=DATABASE):
"""save file
Arguments:
file_dir {str:direction} -- 文件的地址
Keyword Arguments:
client {Mongodb:Connection} -- Mongo Connection (default: {DATABASE})
"""
reader = TdxMinBarReader()
__coll = client.stock_min_five
for... |
从stock_ip_list删除列表exclude_ip_list中的ip
从stock_ip_list删除列表future_ip_list中的ip
:param exclude_ip_list: 需要删除的ip_list
:return: None | def exclude_from_stock_ip_list(exclude_ip_list):
""" 从stock_ip_list删除列表exclude_ip_list中的ip
从stock_ip_list删除列表future_ip_list中的ip
:param exclude_ip_list: 需要删除的ip_list
:return: None
"""
for exc in exclude_ip_list:
if exc in stock_ip_list:
stock_ip_list.remove(exc)
# 扩展市场
... |
[summary]
Keyword Arguments:
section {str} -- [description] (default: {'MONGODB'})
option {str} -- [description] (default: {'uri'})
default_value {[type]} -- [description] (default: {DEFAULT_DB_URI})
Returns:
[type] -- [description] | def get_config(
self,
section='MONGODB',
option='uri',
default_value=DEFAULT_DB_URI
):
"""[summary]
Keyword Arguments:
section {str} -- [description] (default: {'MONGODB'})
option {str} -- [description] (default: {'uri'})
... |
[summary]
Keyword Arguments:
section {str} -- [description] (default: {'MONGODB'})
option {str} -- [description] (default: {'uri'})
default_value {[type]} -- [description] (default: {DEFAULT_DB_URI})
Returns:
[type] -- [description] | def set_config(
self,
section='MONGODB',
option='uri',
default_value=DEFAULT_DB_URI
):
"""[summary]
Keyword Arguments:
section {str} -- [description] (default: {'MONGODB'})
option {str} -- [description] (default: {'uri'})
... |
[summary]
Arguments:
config {[type]} -- [description]
section {[type]} -- [description]
option {[type]} -- [description]
DEFAULT_VALUE {[type]} -- [description]
Keyword Arguments:
method {str} -- [description] (default: {'get'})
Retu... | def get_or_set_section(
self,
config,
section,
option,
DEFAULT_VALUE,
method='get'
):
"""[summary]
Arguments:
config {[type]} -- [description]
section {[type]} -- [description]
option {[type]... |
日期字符串 '2011-09-11' 变换成 整数 20110911
日期字符串 '2018-12-01' 变换成 整数 20181201
:param date: str日期字符串
:return: 类型int | def QA_util_date_str2int(date):
"""
日期字符串 '2011-09-11' 变换成 整数 20110911
日期字符串 '2018-12-01' 变换成 整数 20181201
:param date: str日期字符串
:return: 类型int
"""
# return int(str(date)[0:4] + str(date)[5:7] + str(date)[8:10])
if isinstance(date, str):
return int(str().join(date.split('-')))
... |
类型datetime.datatime
:param date: int 8位整数
:return: 类型str | def QA_util_date_int2str(int_date):
"""
类型datetime.datatime
:param date: int 8位整数
:return: 类型str
"""
date = str(int_date)
if len(date) == 8:
return str(date[0:4] + '-' + date[4:6] + '-' + date[6:8])
elif len(date) == 10:
return date |
字符串 '2018-01-01' 转变成 datatime 类型
:param time: 字符串str -- 格式必须是 2018-01-01 ，长度10
:return: 类型datetime.datatime | def QA_util_to_datetime(time):
"""
字符串 '2018-01-01' 转变成 datatime 类型
:param time: 字符串str -- 格式必须是 2018-01-01 ，长度10
:return: 类型datetime.datatime
"""
if len(str(time)) == 10:
_time = '{} 00:00:00'.format(time)
elif len(str(time)) == 19:
_time = str(time)
else:
QA_ut... |
:param dt: pythone datetime.datetime
:return: 1999-02-01 string type | def QA_util_datetime_to_strdate(dt):
"""
:param dt: pythone datetime.datetime
:return: 1999-02-01 string type
"""
strdate = "%04d-%02d-%02d" % (dt.year, dt.month, dt.day)
return strdate |
:param dt: pythone datetime.datetime
:return: 1999-02-01 09:30:91 string type | def QA_util_datetime_to_strdatetime(dt):
"""
:param dt: pythone datetime.datetime
:return: 1999-02-01 09:30:91 string type
"""
strdatetime = "%04d-%02d-%02d %02d:%02d:%02d" % (
dt.year,
dt.month,
dt.day,
dt.hour,
dt.minute,
dt.second
)
return... |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.