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

if current_time > '09:30:00' and current_time < '14:55:00':

data = context.history('RBM0', context.keys, time_range=15, freq='1m')['RBM0'] #转换为datatime类型的索引值

data.index = map(lambda x: datatime.strptime(x,'%Y-%m-%d %H:%M'), data.index) #转换为5分钟K线图

data['closePrice'] = data.closePrice.resample('5T', closed='left').last()

data['openPrice'] = data.openPrice.resample('5T', closed='left').first()

data['highPrice'] = data.highPrice.resample('5T', closed='left').max()

data['lowPrice'] = data.lowPrice.resample('5T', closed='left').min()

data['turnoverVol'] = data.turnoverVol.resample('5T', closed='left').sum()

data = data.dropna()

#print data

# data = data_pool.update(symbol)

before_2_close = data['closePrice'][-2]

before_2_high = data['highPrice'][-2]

before_1_close = data['closePrice'][-1]

before_1_high = data['highPrice'][-1]

before_1_low = data['lowPrice'][-1]

before_1_open = data['openPrice'][-1]

#观察卖出价

ssetup = context.high+0.35*(context.close-context.low)

#观察买入价

bsetup = context.low-0.35*(context.high-context.close)

#反转卖出价

senter = (1+0.07)/2*(context.high+context.low)-0.07*context.low

#反转买入价

benter = (1+0.07)/2*(context.high+context.low)-0.07*context.high

#突破买入价

bbreak = ssetup+0.25*(ssetup-bsetup)

#突破卖出价

sbreak = bsetup-0.25*(ssetup-bsetup)

##趋势

if before_2_close <= bbreak and before_1_close > bbreak:

if long_position == 0:

futures_account.order(symbol,amount,'open')

if short_position != 0:

futures_account.order(symbol,short_position,'close')

if before_2_close >= sbreak and before_1_close < sbreak:

if short_position == 0:

futures_account.order(symbol,-amount,'open')

if long_position != 0:

futures_account.order(symbol,-long_position,'close')

##反转

## 多单反转

if before_1_high > ssetup and before_1_close > senter:

context.count1 = 1

if context.count1 == 1 and before_1_close < senter:

if long_position > 0:

futures_account.order(symbol,-long_position, 'close')

futures_account.order(symbol,-amount, 'open')

##空单反转

if before_1_low < bsetup:

context.count2 = 1

if context.count2 == 1 and before_1_close > benter:

if short_position != 0:

futures_account.order(symbol,short_position, 'close')

futures_account.order(symbol,amount, 'open')

#收盘处理全部平仓

elif current_time >= '14:55:00':

if short_position > 0:

futures_account.order(symbol,short_position, 'close') if long_position > 0:

futures_account.order(symbol,-long_position, 'close')

#数据复位

context.high = np.NAN

context.low = np.NAN

context.close = np.NAN

context.count1 = 0

context.count2 = 0

华东政法大学（上海松江校区）法学学士学位

华东师范大学（上海闵行校区）金融学双学位

Stamford international university （东南亚曼谷）国际商务硕士

擅长：公司金融、财务报表分析、价值投资

金融学科毕业，在金融领域工作5年，对证券、外汇、现货有比较清晰成熟的认知与分析

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