鳄鱼法则交易系统源码(Python源码)
源码如下：[code]
import numpy as np
def initialize(context):
g.up_price = 0 #向上碎形最高价
g.low_price = 0 #向下碎形最低价
g.up_fractal_exists = False #判断有效向上碎形
g.down_fractal_exists = False #判断有效向下碎形
g.AO_index = [0] #存放连续的AO指标数据
g.cal_AC_index = [] #计算AC指标中转存储
g.AC_index = [0] #存放连续的AC指标数据
g.amount = 0 #满仓仓位
g.stock = ['160119.XSHE']
set_benchmark('160119.XSHE')
#判断 向上 或 向下 碎形
def is_fractal(stock,direction):
hist = history(5,'1d',direction,[stock],df = False)
if direction == 'high'\
and hist[stock][2] > hist[stock][0]\
and hist[stock][2] > hist[stock][1]\
and hist[stock][2] > hist[stock][3]\
and hist[stock][2] > hist[stock][4]:
g.up_price = hist[stock][2]
return True
elif direction == 'low'\
and hist[stock][2] < hist[stock][0]\
and hist[stock][2] < hist[stock][1]\
and hist[stock][2] < hist[stock][3]\
and hist[stock][2] < hist[stock][4]:
g.low_price = hist[stock][2]
return True
return False
#通过比较碎形与红线位置，判断碎形是否有效
def is_effective_fractal(stock, direction):
if is_fractal(stock,direction):
hist = history(13,'1d','close',[stock],df = False)
red_line = hist[stock][:-5].mean()
close_price = hist[stock][-1]
if direction == 'high':
if close_price > red_line:
g.up_fractal_exists = True
else:
g.up_fractal_exists = False
elif direction == 'low':
if close_price < red_line:
g.down_fractal_exists = True
else:
g.down_fractal_exists = False
#N日内最高价格的N日线
def nday_high_point(stock,n):
hist = history(2*n,'1d','high',[stock],df = False)[stock]
high_point = []
for i in range(n):
high_point.append(max(hist[-5-i:-1-i]))
return np.array(high_point).mean()
#N日内最低价格的N日线
def nday_low_point(stock,n):
hist = history(2*n,'1d','low',[stock],df = False)[stock]
low_point = []
for i in range(n):
low_point.append(max(hist[-5-i:-1-i]))
return np.array(low_point).mean()
#AO=5日内（最高-最低）/2的5日移动平均-34日内（最高-最低）/2的34日移动平均
def AO_index(stock):
g.AO_index.append(nday_high_point(stock,5)/2 + nday_low_point(stock,5)/2\
- nday_high_point(stock,34)/2 - nday_low_point(stock,34)/2)
return g.AO_index[-1]
#AO-AO的5日平均值的5日平均
def AC_index(stock):
AO_index(stock)
if len(g.AO_index) >= 5:
g.cal_AC_index.append(g.AO_index[-1] - np.array(g.AO_index[-5:]).mean())
if len(g.cal_AC_index) >=5:
g.AC_index.append(np.array(g.cal_AC_index[-5:]).mean())
#判断序列n日上行
def is_up_going(alist,n):
if len(alist) < n:
return False
for i in range(n-1):
if alist[-(1+i)] <= alist[-(2+i)]:
return False
return True
#判断序列n日下行
def is_down_going(alist,n):
if len(alist) < n:
return False
for i in range(n-1):
if alist[-(1+i)] >= alist[-(2+i)]:
return False
return True
#碎形被突破
def active_fractal(stock,direction):
close_price = history(1,'1d','close',[stock],df=False)[stock][0]
if direction == 'up' and close_price > g.up_price:
return True
elif direction == 'down' and close_price < g.low_price:
return True
#进场，初始仓位50%
def set_initial_position(stock,context):
close_price = history(1,'1d','close',[stock],df=False)[stock][0]
g.amount = context.portfolio.cash/close_price
order(stock, g.amount*0.8)
log.info("buying %s 股数为 %s"%(stock,g.amount*0.7))
g.down_fractal_exists = False
#卖出
def sell_all_stock(stock,context):
order_target(stock,0)
log.info("selling %s"%stock)
g.up_fractal_exists = False
#加仓
def adjust_position(stock,context,position):
order(stock,g.amount*position)
log.info("adjust position buying %s 股数为 %s"%(stock,g.amount*position))
def handle_data(context,data):
stock = g.stock[0]
#计算AO，AC指标
AC_index(stock)
#止损
#空仓时，寻找机会入场
if context.portfolio.positions[stock].amount == 0:
#计算向上碎形
is_effective_fractal(stock,'high')
#有效向上碎形存在，并被突破，买入
if g.up_fractal_exists and active_fractal(stock,'up'):
set_initial_position(stock,context)
#有持仓时，加仓或离场
else:
close_price = history(13,'1d','close',[stock],df=False)
red_line = close_price[stock][:-5].mean()
#计算向下碎形
is_effective_fractal(stock,'low')
#出场条件1：有效向下碎形存在，并被突破，卖出
if g.down_fractal_exists and active_fractal(stock,'down'):
sell_all_stock(stock,context)
return
#出场条件2：AC
#加仓10%：AO，AC同时5日上行，且收盘价走高
if is_up_going(g.AO_index,5)\
and is_up_going(g.AC_index,3)\
and is_up_going(close_price[stock],2):
adjust_position(stock,context,0.1)
#减仓10%：AO，AC同时3日下行，且收盘价走低
if is_down_going(g.AO_index,5)\
and is_down_going(g.AC_index,3)\
and is_down_going(close_price[stock],2):
adjust_position(stock,context,-0.1)
record(AOindex = g.AO_index[-1])
record(ACindex = g.AC_index[-1])
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