def contractMap_mod_domain_utc():
rq.init()
# 为contractMap文件增加life_utc列
cm = pd.read_csv(
'D:\\002 MakeLive\DataCollection\public data\\contractMap.csv')
domain_start_utc_list = []
domain_end_utc_list = []
cm['domain_start_date'] = cm['domain_start_date'].str.replace('\\', '-')
cm['domain_end_date'] = cm['domain_end_date'].str.replace('\\', '-')
cm['listed_date'] = cm['listed_date'].str.replace('\\', '-')
cm['maturity_date'] = cm['maturity_date'].str.replace('\\', '-')
for n, rows in cm.iterrows():
first_date = rows['domain_start_date']
predate = get_previous_trading_date(first_date, country='cn')
domain_start_utc = int(
time.mktime(
time.strptime(
predate.strftime("%Y-%m-%d") + ' 21:00:00',
'%Y-%m-%d %H:%M:%S')))
domain_end_utc = int(
time.mktime(
time.strptime(rows['domain_end_date'] + ' 16:00:00',
'%Y-%m-%d %H:%M:%S')))
domain_start_utc_list.append(domain_start_utc)
domain_end_utc_list.append(domain_end_utc)
cm['domain_start_utc'] = domain_start_utc_list
cm['domain_end_utc'] = domain_end_utc_list
#cm.drop('Unnamed: 0.1', axis=1, inplace=True)
#cm['Unnamed: 0']=range(cm.shape[0])
cm.to_csv('contractMap2.csv', index=False)
pass
def auth(self, **kwargs):
if self.isAuthed:
return
rq.init(**kwargs)
self.isAuthed = True
print("Rqdata has been authorized.")
def prep_download(self):
# self.start = datetime(2011, 1, 1)
self.end = datetime.now().date()
# read csv commodities futures list
with open('cf_list.csv', 'r') as f:
reader = csv.reader(f)
cf_list = list(reader)
rq.init()
today = rq.get_latest_trading_date()
prev_trading_day = rq.get_previous_trading_date(today, 1, market='cn')
for instrument in cf_list:
# check if changed the dominant contract for the latest trading day
today_dominant = rq.futures.get_dominant(instrument[1], today)
prev_day_dominant = rq.futures.get_dominant(
instrument[1], prev_trading_day)
if today_dominant[today] == prev_day_dominant[prev_trading_day]:
self.start = prev_trading_day
elif today_dominant[today] != prev_day_dominant[prev_trading_day]:
self.start = datetime(2011, 1, 1)
print(
f"品种 {instrument[1]} 的主力合约即日起从 {prev_day_dominant[prev_trading_day]} 换到 {today_dominant[today]}"
)
else:
print("####### 检查主力合约过程中出错，请手动debug！")
if self.download_full == True:
self.start = datetime(2011, 1, 1)
self.rq_download(instrument[0], '1m', self.start, self.end)
self.rq_download(instrument[0], 'd', self.start, self.end)
def before_trading(context, bar_dict):
rqd.init(
'license',
'BZPntqmgrLH4lKAOjx671eO91m87PaKGRLpXoldWGCf-3Skw8oZ_VnjVSA-M4fRtcuye-HfX8velChxb0iLxDtpzt9DeTCVJsdSYOKQ4'
'grrpqge2IYBUMKmrpFqMiuI6ZXw5d9eje7Qtu28Z-wgDKeWpoI4K0MNYf2aPt_ejSsM=MABNzwICqZ_LX_sk549IAzaYHdtWgAJwSkyRAe'
'DQUq992HgGBL1nC_WicztRvUqa-WiwR-_cGj8-vfFakdVXqtNx9tapTpSuM5PKhfTfDJqOD7HH3jr2KpgI_IX4gNDbKT0a4W9mCKz6qka7'
'KDTj_TlCpdV5_lIfAd7UaIgm9pc=', ('115.159.129.195', 443),
proxy_info=('http', '172.20.0.2', 8086, 'yuxiaoqi', '0814xqYu'))
trade_date = context.now.strftime('%Y-%m-%d')
# print(trade_date)
context.stock_lst = index_components('000300.XSHG', trade_date)
# print(context.stock_lst)
# factor_ret = rqd.get_factor_exposure(id_or_symbols=context.stock_lst, start_date=trade_date,
# end_date=trade_date,
# factors=['momentum'])
# indexes = list(factor_ret.index)
# values = list(factor_ret['momentum'])
#
# context.cached = defaultdict(list)
# for idx, val in enumerate(indexes):
# book_id, date = val
# factor = values[idx]
# context.cached[date.strftime('%Y%m%d')].append((book_id, factor))
query_fundamental(context)
context.b_price = get_price('000300.XSHG',
start_date=trade_date,
end_date=trade_date,
fields='close').values[0]
context.mtm = context.b_price * 300
def update_bundle(data_bundle_path, rqdatac_uri, compression, concurrency):
try:
import rqdatac
except ImportError:
click.echo(
_('rqdatac is required to update bundle. '
'you can visit https://www.ricequant.com/welcome/rqdata to get rqdatac, '
'or use "rqalpha download-bundle" to download monthly updated bundle.'
))
return 1
try:
init_rqdatac_env(rqdatac_uri)
rqdatac.init()
except ValueError as e:
click.echo(_('rqdatac init failed with error: {}').format(e))
return 1
if not os.path.exists(os.path.join(data_bundle_path, 'bundle')):
click.echo(
_('bundle not exist, use "rqalpha create-bundle" command instead'))
return 1
from rqalpha.data.bundle import update_bundle as update_bundle_
update_bundle_(os.path.join(data_bundle_path, 'bundle'), False,
compression, concurrency)
def __init__(self, isSub=False):
if not isSub:
rq.init()
else:
rq.reset()
self.columns = ["close", "open", "high", "low", "volume"]
self.tickColumns = [
"last", "open", "high", "low", "volume", "asks", "ask_vols",
"bids", "bid_vols"
]
self.HisKline = None
self.HisKlineTime = None
self.currentKline = {}
self.preKline = None
self.validDate = None
self.kPeriod = 1
self.TimeArea = []
self.TimeDiffArea = []
self.indexCodeList, self.indexMcodes = [], [] # 指数期货对应的行情代码
self.indexMap = {}
self.HisKlineTime = {}
self.HisKline = {}
# tick 触发持续状态，进程结束时返回false，用于终止ctp窗口
self.tickStatus = True
def for_test(mongo_url, db, _days, implied):
rqdatac.init(uri='tcp://*****:*****@dev:16010')
test = 'test'
'''find n trading days before today'''
my_mongo = CustomizedMongo(mongo_url, db, test)
trading_days = list(get_previous_trading_days_customized(int(_days)))
try:
print('data_processing')
data_processing(my_mongo, trading_days, implied, upsert=True)
except ValueError:
print('today\'s data is not reachable yet')
def init_rqdatac(rqdatac_uri):
try:
import rqdatac
except ImportError:
return
try:
init_rqdatac_env(rqdatac_uri)
rqdatac.init()
except Exception as e:
system_log.warn(_('rqdatac init failed, some apis will not function properly: {}').format(str(e)))
def get_barra_exposure(stock_list, date):
rqdatac.init('rice', 'rice', ('192.168.10.64', 16008))
style_factors = [
'CNE5S_BETA', 'CNE5S_MOMENTUM', 'CNE5S_SIZE', 'CNE5S_EARNYILD',
'CNE5S_RESVOL', 'CNE5S_GROWTH', 'CNE5S_BTOP', 'CNE5S_LEVERAGE',
'CNE5S_LIQUIDTY', 'CNE5S_SIZENL'
]
style_exposure = rqdatac.barra.get_factor_exposure(stock_list, date, date,
style_factors)
style_exposure.index = style_exposure.index.droplevel('date')
return style_exposure
def init_rqdatac(rqdatac_uri):
try:
import rqdatac
except ImportError:
return
import warnings
try:
init_rqdatac_env(rqdatac_uri)
with warnings.catch_warnings(record=True):
rqdatac.init()
except Exception as e:
system_log.warn(
_('rqdatac init failed, some apis will not function properly: {}').
format(str(e)))
def init_rqdatac(rqdatac_uri):
try:
import rqdatac
except ImportError:
system_log.info(
_('rqdatac is not available, some apis will not function properly')
)
return
try:
init_rqdatac_env(rqdatac_uri)
rqdatac.init()
except ValueError as e:
system_log.warn(
_('rqdatac init failed, some apis will not function properly: {}').
format(str(e)))
def get_gics_exposure(stock_list, date):
rqdatac.init('rice', 'rice', ('192.168.10.64', 16008))
industry_factors = [
'CNE5S_ENERGY', 'CNE5S_CHEM', 'CNE5S_CONMAT', 'CNE5S_MTLMIN',
'CNE5S_MATERIAL', 'CNE5S_AERODEF', 'CNE5S_BLDPROD', 'CNE5S_CNSTENG',
'CNE5S_ELECEQP', 'CNE5S_INDCONG', 'CNE5S_MACH', 'CNE5S_TRDDIST',
'CNE5S_COMSERV', 'CNE5S_AIRLINE', 'CNE5S_MARINE', 'CNE5S_RDRLTRAN',
'CNE5S_AUTO', 'CNE5S_HOUSEDUR', 'CNE5S_LEISLUX', 'CNE5S_CONSSERV',
'CNE5S_MEDIA', 'CNE5S_RETAIL', 'CNE5S_PERSPRD', 'CNE5S_BEV',
'CNE5S_FOODPROD', 'CNE5S_HEALTH', 'CNE5S_BANKS', 'CNE5S_DVFININS',
'CNE5S_REALEST', 'CNE5S_SOFTWARE', 'CNE5S_HDWRSEMI', 'CNE5S_UTILITIE'
]
industry_exposure = rqdatac.barra.get_factor_exposure(
stock_list, date, date, industry_factors)
industry_exposure.index = industry_exposure.index.droplevel('date')
return industry_exposure
def get_data(start, end, symbol, exchange, level):
""" using rqdatac to make an example """
import rqdatac as rq
from rqdatac import get_price, id_convert
username = "******"
password = "******" \
"t7AbdBZEBqRK74fIJH5vsaAfFQgl-tuB8l03axrW8cyN6-nBUho_6Y5VCRI63Mx_PN54nsQOpc1psIGEz" \
"gND8c6Y=bqMVlABkpSlrDNk4DgG-1QXNknJtk0Kkw2axvFDa0E_XPMqOcBxifuRa_DFI2svseXU-8A" \
"eLjchnTkeuvQkKh6nrfehVDiXjoMeq5sXgqpbgFAd4A5j2B1a0gpE3cb5kXb42n13fGwFaGris" \
"8-eKzz_jncvuAamkJEQQV0aLdiw="
host = "rqdatad-pro.ricequant.com"
port = 16011
rq.init(username, password, (host, port))
symbol_rq = id_convert(symbol)
data = get_price(symbol_rq,
start_date=start,
end_date=end,
frequency=level,
fields=None,
adjust_type='pre',
skip_suspended=False,
market='cn',
expect_df=False)
origin = data.to_dict(orient='records')
result = []
for x in origin:
do = {}
do['open_price'] = x['open']
do['low_price'] = x['low']
do['high_price'] = x['high']
do['close_price'] = x['close']
do['datetime'] = datetime.strptime(str(x['trading_date']),
"%Y-%m-%d %H:%M:%S")
do['symbol'] = symbol
do['local_symbol'] = symbol + "." + exchange
do['exchange'] = exchange
result.append(do)
return result
def create_bundle(data_bundle_path, rqdatac_uri, compression, concurrency):
"""create bundle using rqdatac"""
try:
import rqdatac
except ImportError:
click.echo(
_('rqdatac is required to create bundle. '
'you can visit https://www.ricequant.com/welcome/rqdata to get rqdatac, '
'or use "rqalpha download-bundle" to download monthly updated bundle.'
))
return 1
try:
init_rqdatac_env(rqdatac_uri)
rqdatac.init()
except ValueError as e:
click.echo(_('rqdatac init failed with error: {}').format(e))
return 1
os.makedirs(os.path.join(data_bundle_path, 'bundle'), exist_ok=True)
from rqalpha.data.bundle import update_bundle as update_bundle_
update_bundle_(os.path.join(data_bundle_path, 'bundle'), True, compression,
concurrency)
def start_up(self, env, mod_config):
if os.environ.get("RQDATAC2_CONF") or os.environ.get("RQDATAC_CONF"):
system_log.info('rqdatac use RQDATAC2_CONF or RQDATAC_CONF')
rqdatac.init()
else:
addr = (mod_config.rqdata_client_addr, mod_config.rqdata_client_port)
env.system_log.info('rqdatac use address {}', addr)
rqdatac.init(
username=mod_config.rqdata_client_username,
password=mod_config.rqdata_client_password,
addr=addr,
lazy=True
)
# noinspection PyUnresolvedReferences
from rqdatac import fundamentals, Fundamentals, financials, Financials, fenji, query
from rqalpha.api.api_base import register_api
register_api("fundamentals", fundamentals)
register_api("Fundamentals", Fundamentals)
register_api("financials", financials)
register_api("Financials", Financials)
register_api("fenji", fenji)
register_api("query", query)
(data_filter['spread_on'] < 0) &
(data_filter['spread_pre'] > 0.001 * order)).sum()
if (data_filter['spread_pre'] > 0.001 * order).sum():
statistical_details.loc[order, 'ratio_inverse'] = statistical_details.loc[order, 'count_inverse'] \
/ statistical_details.loc[order, 'count_all']
statistical_details.loc[
order, 'return_avg'] = data_filter['spread_on'][
data_filter['spread_pre'] > 0.001 * order].mean()
statistical_details.drop(index=[0], inplace=True)
statistical_dict[time_on] = statistical_details
return statistical_dict
if __name__ == '__main__':
rq.init("ricequant", "8ricequant8", ('10.29.135.119', 16010))
# 参数 回测区间及合约代码
startDate = '20170101'
endDate = '20200531'
underlyingList = ('IF', 'IH')
timeYes = "14:59:00"
timeList = [
"09:31:00", "09:35:00", "09:40:00", "09:45:00", "09:50:00", "09:55:00",
"10:00:00"
]
underlying_list = underlyingList
start_date = startDate
end_date = endDate
time_list = timeList
from time import time
import rqdatac as rq
from vnpy.trader.database import DbBarData, DB
USERNAME = ""
PASSWORD = ""
FIELDS = ["open", "high", "low", "close", "volume"]
rq.init(USERNAME, PASSWORD, ("rqdatad-pro.ricequant.com", 16011))
def generate_bar_from_row(row, symbol, exchange):
""""""
bar = DbBarData()
bar.symbol = symbol
bar.exchange = exchange
bar.interval = "1m"
bar.open_price = row["open"]
bar.high_price = row["high"]
bar.low_price = row["low"]
bar.close_price = row["close"]
bar.volume = row["volume"]
bar.datetime = row.name.to_pydatetime()
bar.gateway_name = "DB"
bar.vt_symbol = f"{symbol}.{exchange}"
return bar
import numpy as np
import pandas as pd
import scipy.optimize as sc_opt
from datetime import datetime
from datetime import timedelta
import rqdatac
rqdatac.init('rice', 'rice', ('192.168.10.64', 16030))
def get_shenwan_industry_exposure(stock_list, date):
industry_classification = rqdatac.shenwan_instrument_industry(
stock_list, date)
if date > '2014-01-01':
shenwan_industry_name = ['农林牧渔', '采掘', '化工', '钢铁', '有色金属', '电子', '家用电器', '食品饮料', '纺织服装', '轻工制造',\
'医药生物', '公用事业', '交通运输', '房地产', '商业贸易', '休闲服务','综合', '建筑材料', '建筑装饰', '电气设备',\
'国防军工', '计算机', '传媒', '通信', '银行', '非银金融', '汽车', '机械设备']
else:
shenwan_industry_name = [
'金融服务', '房地产', '医药生物', '有色金属', '餐饮旅游', '综合', '建筑建材', '家用电器',
'交运设备', '食品饮料', '电子', '信息设备', '交通运输', '轻工制造', '公用事业', '机械设备',
'纺织服装', '农林牧渔', '商业贸易', '化工', '信息服务', '采掘', '黑色金属'
]
industry_exposure_df = pd.DataFrame(0,
index=industry_classification.index,
# encoding: UTF-8
import rqdatac as rq
from rqdatac import *
import pandas as pd
import sys
import datetime
import os
DATA_PATH = "E:\\future_data\\all_data\\"
NO_MAKER_DATA_PATH = "other_table\\"
SAVE_PATH = DATA_PATH + NO_MAKER_DATA_PATH
reload(sys)
loop_count = 0
sys.setdefaultencoding('utf8')
rq.init()
need_to_monitor_future_list = [
'RB', 'TA', 'CF', 'L', 'PP', 'M', 'Y', 'AG', 'MA', 'SR'
]
margin_rate_list = []
contract_multiplier_list = []
symbol_list = []
time_of_today = datetime.datetime.now().strftime("%Y%m%d")
def get_current_domain_future_info():
for temp_future in need_to_monitor_future_list:
temp_future_name = rq.get_dominant_future(temp_future,
time_of_today)[-1]
temp_info = rq.instruments(temp_future_name)
margin_rate = temp_info.margin_rate # 保证金率
contract_multiplier = temp_info.contract_multiplier # 合约乘数
from intermediate_variables import *
from operators import *
import numpy as np
import pandas as pd
from datetime import datetime
from datetime import timedelta
import rqdatac
rqdatac.init("ricequant", "Ricequant123", ('rqdatad-pro.ricequant.com', 16004))
def get_market_portfolio_beta(stock_excess_return, market_portfolio_excess_return, market_cap_on_current_day):
exp_weight = get_exponential_weight(half_life=63, length=252)
weighted_stock_excess_return = stock_excess_return.T.multiply(exp_weight).T
weighted_market_portfolio_excess_return = market_portfolio_excess_return.multiply(exp_weight).T
weighted_market_portfolio_variance = weighted_market_portfolio_excess_return.var()
beta = [weighted_market_portfolio_excess_return.cov(
weighted_stock_excess_return[stock]) / weighted_market_portfolio_variance for stock in
stock_excess_return.columns]
market_portfolio_beta = pd.Series(beta, index=stock_excess_return.columns)
market_portfolio_beta_exposure = winsorization_and_market_cap_weighed_standardization(market_portfolio_beta,
import rqdatac
from rqdatac import *
rqdatac.init("ricequant", "8ricequant8")
import datetime as dt
import itertools
import matplotlib.pyplot as plt
import numpy as np
from math import *
import pandas as pd
from optimizer_tests.stock_test.ptfopt_cov_shrink import *
def get_stock_test_suite(start_t='2013-01-01', end_t='2017-07-05'):
"""
get alive stock test suite between dates (for test use between 20140101 to 2017)
make sure it has IPO for at least one year and is never ST between dates
:param start_t:
:param end_t:
:return: dic
return a dic, key is 0-99.
0 is the biggest 100
1 is the second 101 ~ 200 stocks
2 is the smallest -200 ~ -101 stocks
3 is the smallest -100 ~ -1 stocks
4 is the biggest 50 + smallest 50
5 ~ 99 is the 28*3 combo (28: shenwan_industry category, 3: we split each cate by market cap)
"""
# get all stocks
all_stocks0 = list(all_instruments(type='CS').order_book_id)
# 加载配置
config = open('config.json')
setting = json.load(config)
MONGO_HOST = setting['MONGO_HOST']
MONGO_PORT = setting['MONGO_PORT']
SYMBOLS = setting['SYMBOLS']
mc = MongoClient(MONGO_HOST, MONGO_PORT) # Mongo连接
db = mc[MINUTE_DB_NAME] # 数据库
db2 = mc[DAILY_DB_NAME]
USERNAME = setting['USERNAME']
PASSWORD = setting['PASSWORD']
rq.init(USERNAME, PASSWORD)
FIELDS = ['open', 'high', 'low', 'close', 'volume']
#----------------------------------------------------------------------
def generateVtBar(row, symbol):
"""生成K线"""
bar = VtBarData()
bar.symbol = symbol
bar.vtSymbol = symbol
bar.open = row['open']
bar.high = row['high']
bar.low = row['low']
bar.close = row['close']
from time import time
import rqdatac as rq
from fcs_trade.trader.object import BarData
from fcs_trade.trader.constant import Exchange, Interval
from fcs_trade.trader.database import database_manager
USERNAME = ""
PASSWORD = ""
FIELDS = ["open", "high", "low", "close", "volume"]
rq.init(USERNAME, PASSWORD, ("rqdatad-pro.ricequant.com", 16011))
def generate_bar_from_row(row, symbol, exchange):
""""""
bar = BarData(symbol=symbol,
exchange=Exchange(exchange),
interval=Interval.MINUTE,
open_price=row["open"],
high_price=row["high"],
low_price=row["low"],
close_price=row["close"],
volume=row["volume"],
datetime=row.name.to_pydatetime(),
gateway_name="DB")
return bar
def download_minute_bar(vt_symbol):
def main():
rq.init()
update_minute_lib()
update_daily_lib()
# -*- coding:utf-8 -*-
from factor.base_factor import BaseFactor
from data.data_module import DataModule
import rqdatac as rqd
rqd.init()
"""
PE因子
"""
class PEFactor(BaseFactor):
def __init__(self):
BaseFactor.__init__(self, 'pe_ratio_ttm')
def compute_one_day(self, date):
# 用不到,只是为了练习,实际取米筐数据存
# dm = DataModule()
# 某天所有股票数据
# df_daily = dm.get_all_price_one_day(date)
stocklist = rqd.all_instruments('CS', date)['order_book_id'].tolist()
pe = rqd.get_factor(stocklist, self.name, date, date)
factors = []
for code in pe.index:
factors.append({
'date': date,
'code': code,
self.name: round(pe[code], 2)
})
return factors
#coding=utf-8
import rqdatac
from rqdatac import *
rqdatac.init()
from rqalpha.api import *
import numpy as np
import pandas as pd
import lightgbm
import talib
from sklearn import metrics
def init(context):
# 在context中保存全局变量
context.symbols = list(get_all_ins(context).index.values)
context.train_days = 40 #用45-5日前的数据做训练
context.test_days = 5 #预测五日收益
scheduler.run_weekly(rebalance, 1)
# 实时打印日志
logger.info("there are : {}".format(len(context.symbols)))
def rebalance(context, bar_dict):
''' 换仓 '''
#训练预测
train_x, train_y, test_x = get_data(context)
test_y_pred = fit_transform(context, train_x, train_y, test_x)
#%%
import rqdatac as rq
from rqdatac import *
rq.init('13581903798','hun829248')
import talib
import pandas as pd
import numpy as np
#%%
data = get_price("RB2010", start_date="2020-01-02", end_date="2020-01-03", frequency="tick")
#%%
# rb888_excel = pd.ExcelWriter('D:\\期货自动化交易\\8-CTA_Development\\1-常用模板\\1-rqdata\\螺纹钢期货tick数据.xlsx') # 定义一个向Excel写入数据的对象
# data.to_excel(rb888_excel, "RB888tick数据") # 向该Excel中写入df1到Data1这个sheet
# rb888_excel.save() # 保存Excel表格
# rb888_excel.close() # 关闭Excel表格
#%%
print(data)
#%%
data['cci'] = talib.CCI(data['high'], data['low'], data['close'], timeperiod=14)
print("cci值为:", data['cci'])
data1 = np.array(data['cci'])
print("data1：", data1)
print("data1[-1]:", data1[-1])
print("data1[-2]:", data1[-2])
print("data1[-3]:", data1[-3])
a = data1[-1]
b = data1[-2]
c = data1[-3]
print(data1[-1] < 100)
# %%
from rqdatac import *
import talib
import datetime
import pandas as pd
import numpy as np
from pandas.tseries.offsets import *
import plotly.plotly as py
import plotly.graph_objs as go
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
############################## Initialize rqdatac and plotly environments ################################
# initialize rqdatac to enable online functions such as get_price() and get_next_trading_date()
rqdatac.init('xinjin', '123456', ('172.19.182.162', 16003))
# initialize plotly to enable offline mode
init_notebook_mode(connected=True)
############################## Initialize rqdatac and plotly environments ################################
## helper functions
# keep only year and moth(year-month) as string of datetime object
# return example: 2017-01-01
def date2ym_str(date):
y = date.year
m = date.month
ym = '{}-{}'.format(y, m)
return ym
def date2ymd_str(date):
TICK_DB_NAME)
import rqdatac as rq
# 加载配置
config = open('config.json')
setting = json.load(config)
mc = MongoClient() # Mongo连接
dbMinute = mc[MINUTE_DB_NAME] # 数据库
dbDaily = mc[DAILY_DB_NAME]
dbTick = mc[TICK_DB_NAME]
USERNAME = setting['rqUsername']
PASSWORD = setting['rqPassword']
rq.init(USERNAME, PASSWORD)
FIELDS = ['open', 'high', 'low', 'close', 'volume']
#----------------------------------------------------------------------
def generateVtBar(row, symbol):
"""生成K线"""
bar = VtBarData()
bar.symbol = symbol
bar.vtSymbol = symbol
bar.open = row['open']
bar.high = row['high']
bar.low = row['low']
bar.close = row['close']
bar.volume = row['volume']
import rqdatac as rd
from keras.models import Sequential
from keras.layers import Dense
from sklearn.model_selection import train_test_split
import numpy as np
import keras
import matplotlib.pyplot as plt
import pandas as pd
rd.init()
spot_input_data = rd.get_price('510050.XSHG',
start_date='2015-06-01',
end_date='2019-01-23',
frequency='10m')
future_data = rd.get_price('IH88',
start_date='2015-06-01',
end_date='2019-01-23',
frequency='10m')
future_data.drop(columns=['trading_date', 'limit_up', 'limit_down'],
inplace=True)
spot_output_data = rd.get_price('510050.XSHG',
start_date='2015-06-02',
end_date='2019-01-24',
frequency='1d',
fields=['open', 'close'])
spot_output_data = spot_output_data['close'] > spot_output_data['open']
def combine_spot_future(spot, future, direction):
spot1 = spot.copy()
import numpy as np
import pandas as pd
import rqdatac
from rqdatac import *
rqdatac.init('ricequant', '8ricequant8')
def get_risk_indicators(previous_weight, current_weight, cov_matrix, asset_type):
"""
Calculate the risk indicators
:param previous_weight: list or array
:param current_weight: list or array
:param cov_matrix: data_frame
:param asset_type: str
'fund' or 'stock'
:return: list
HRCs, HRCGs, Herfindahl, turnover_rate
"""
# change list to array for later process
# previous_weight_array = np.array(previous_weight)
current_weight_array = np.array(current_weight)
# refer to paper formula 2.19 2.20
production_i = current_weight_array * (cov_matrix.dot(current_weight_array))
productions = current_weight_array.dot(cov_matrix).dot(current_weight_array)
# calculate individual's risk contributions
# encoding: UTF-8
# 在python3下运行
import rqdatac
from rqdatac import *
rqdatac.init('Dajia','------')
# 获取螺纹钢的指数数据，15分钟周期
df = get_price('RB99', start_date='2009-01-01', end_date='2017-03-12', frequency='15m')
# 导出到文件
df.to_csv('RB99_20090101_20170312_M15.csv')
