价值投资与量化交易

量化投资多因子选股策略：

import numpy as np #导入python 计算模块

start = '2014-08-01'

end = '2016-08-01'

benchmark = 'HS300'

capital_base = 1000000

freq = 'd'

refresh_rate = 1

universe = StockScreener( Factor.LFLO.nsmall(30)) #用选股器选择流通市值最小的30只股票作为股票池

def initialize(account):

pass

def handle_data(account):

#生成买入列表

last_date = account.previous_date.strftime("%Y-%m-%d") #获取上一个交易日

last_screener = universe.preview(last_date) #获取上一个交易日市值最小的30只股票

buylist = [sec for sec in last_screener if sec in account.universe]

v = account.referencePortfolioValue

d = len(buylist)

#卖出不在买入列表中的股票，估计持仓价值

for stock in account.valid_secpos:

if stock not in buylist:

if stock in account.universe:

order_to(stock,0)

else:

v -= account.valid_secpos[stock] * account.referencePrice[stock] #获得调仓数量

change = {}

for stock in buylist:

p = account.referencePrice[stock]

if p and not np.isnan(p):

change[stock] = int(v / d / p) - account.valid_secpos.get(stock,0)

#按先卖后买的顺序发出指令

for stock in sorted(change,key=change.get):

if change[stock] <= -100 or change[stock] >= 100:

order(stock,change[stock])

量化投资：期货日内策略

from datetime import datetime

import numpy as np

###策略初始化函数

universe = ['RBM0'] #策略交易的期货合约

start = "2015-11-01"

end = "2016-12-28"

capital_base = 1e6

refresh_rate = 5

freq = 'm'

comission = {'RB':(0.000025, 'perValue')}

slippage = Slippage(0, 'perValue')

amount =20

accounts ={'fantasy_account': AccountConfig(account_type='futures', capital_base=100000,commission=commission,slippage=slippage)}

def initialize(context):

context.high = np.NAN

context.low = np.NAN

context.close = np.NAN

context.count1 = 0

context.count2 = 0

context.keys = [u'openPrice', u'highPrice', u'lowPrice', u'closePrice', u'tradeDate', u'turnoverVol']

def handle_data(context):

futures_account = context.get_account('fantasy_account')

symbol = context.get_symbol(universe[0])

current_position = futures_account.get_position(symbol)

if current_position:

long_position = current_position.long_amount

short_position = current_position.short_amount

else:

long_position = 0

short_position = 0

current_time = context.now.strftime('%H:%M:%S')

#记录当日开盘的高开低收数据

if current_time =='09:30:00':

yester_data = DataAPI.MktFutdGet(tradeDate=context.previous_date, ticker=symbol, field=[u'closePrice',u'highestPrice',u'lowestPrice'],pandas= "1")

context.high = yester_data['highestPrice'].iat[0]

context.low = yester_data['lowestPrice'].iat[0]

context.close = yester_data['closePrice'].iat[0]

#盘中逻辑