rename dual-ma to ma

Dual-MA/python/ma_stock.py.bak → MA/python/ma_multi_singals.py

@@ -3,15 +3,15 @@
 
 
 import time
-from talib.abstract import SMA
+from talib import SMA
 import numpy as np
 from collections import deque
 from gmsdk import *
 
 # 算法用到的一些常量，阀值，主要用于信号过滤
 eps = 1e-6
 threshold = 0.235
-tick_size = 1
+tick_size = 0.2
 half_tick_size = tick_size / 2
 significant_diff = tick_size * 2.6
 
@@ -29,12 +29,12 @@ def __init__(self, *args, **kwargs):
         self.sec_id = self.config.get('para', 'trade_symbol')
         self.symbol = ".".join([self.exchange, self.sec_id])
         self.last_price = 0.0
-        self.trade_unit = [1.0, 2.0, 4.0, 8.0, 5.0, 3.0,2.0,1.0,1.0, 0.0] ##  [8.0, 4.0, 2.0, 1.0]
+        self.trade_unit = [3, 1, 2, 0]
         self.trade_count = 0
         self.trade_limit = len(self.trade_unit)
-        self.window_size = self.config.getint('para', 'window_size') or 20
-        self.timeperiod = self.config.getint('para', 'timeperiod') or 20
-        self.bar_type = self.config.getint('para', 'bar_type') or 60
+        self.window_size = self.config.getint('para', 'window_size') or 60
+        self.timeperiod = self.config.getint('para', 'timeperiod') or 60
+        self.bar_type = self.config.getint('para', 'bar_type') or 15
         self.close_buffer = deque(maxlen=self.window_size)
         self.significant_diff = self.config.getfloat('para', 'significant_diff') or significant_diff
 
@@ -60,53 +60,67 @@ def on_tick(self, tick):
 
     def on_execution(self, execution):
         #打印订单成交回报信息
-        print "received execution: %s" % execution.exec_type
+        print("received execution: %s" % execution.exec_type)
 
     #策略的算法函数，策略的交易逻辑实现部分
     def algo_action(self):
         #数据转换，方便调用ta-lib函数进行技术指标的计算，这里用SMA指标
         close = np.asarray(self.close_buffer)
-        ma = SMA({'close':close}, timeperiod=self.timeperiod)
+        ma = SMA(close, timeperiod=self.timeperiod)
         delta = round(close[-1] - ma[-1],4)     # 最新数据点，bar的收盘价跟ma的差
+        cross = (close[-1] - ma[-1]) * (close[-3] - ma[-3]) < 0  ## 判断有否交叉
         last_ma = round(ma[-1], 4)  #  均线ma的最新值
         momentum = round(self.last_price - last_ma,4)  # 当前最新价格跟ma之间的差，成交价相对ma偏离
         #print 'close: ', close
-        print('close ma delta: {0}, last_ma: {1}, momentum: {2}'.format(delta, last_ma, momentum))
+        print(('close ma delta: {0}, last_ma: {1}, momentum: {2}'.format(delta, last_ma, momentum)))
 
+        a_p = self.get_position(self.exchange, self.sec_id, OrderSide_Ask)    #查询策略所持有的空仓
         b_p = self.get_position(self.exchange, self.sec_id, OrderSide_Bid)    #查询策略所持有的多仓
         # 打印持仓信息
-        print ('pos long: {0} vwap: {1:.2f}'.format(b_p.volume if b_p else 0.0, b_p.vwap if b_p else 0.0))
-        if delta > threshold and momentum >= significant_diff:        ## 收盘价上穿均线，且当前价格偏离满足门限过滤条件，多信号
-            # 没有超出下单次数限制
-            if self.trade_count < self.trade_limit:
+        print(('pos long: {0} vwap: {1}, pos short: {2}, vwap: {3}'.format(b_p.volume if b_p else 0.0,
+                round(b_p.vwap,2) if b_p else 0.0,
+                a_p.volume if a_p else 0.0,
+                round(a_p.vwap,2) if a_p else 0.0)))
+
+        if cross < 0 and delta > threshold and momentum >= significant_diff:        ## 收盘价上穿均线，且当前价格偏离满足门限过滤条件，多信号
+            # 没有空仓，开多，或者是有多仓且没有超出下单次数限制，继续加多
+            if (a_p is None or a_p.volume < eps) or (b_p and self.trade_count < self.trade_limit):
                 # 依次获取下单的交易量，下单量是配置的一个整数数列，用于仓位管理，可用配置文件中设置
                 vol = self.trade_unit[self.trade_count]
                 # 如果本次下单量大于0,  发出买入委托交易指令
                 if vol > eps:
                     self.open_long(self.exchange, self.sec_id, self.last_price, vol)
                 self.trade_count += 1    #增加计数
-        elif delta < -threshold and momentum <= - significant_diff:     ## bar 收盘价下穿ma均线，且偏离满足信号过滤条件
-            # 超出下单次数限制
-            if b_p and b_p.volume > eps and self.trade_count == self.trade_limit:
-                self.close_long(self.exchange, self.sec_id, self.last_price, b_p.volume)
-                self.trade_count = 0
             else:
-                # 已有多仓，且没有达到交易次数限制，继续加多
-                vol = self.trade_unit[self.trade_count] if self.trade_count < self.trade_limit else 0.0
+                #  如果有空仓，平掉空仓
+                if a_p and a_p.volume > eps:
+                    self.close_short(self.exchange, self.sec_id, self.last_price, a_p.volume)
+                    self.trade_count = 0
+        elif cross < 0 and delta < -threshold and momentum <= - significant_diff:     ## bar 收盘价下穿ma均线，且偏离满足信号过滤条件
+            # 没有多仓时，开空, 或者是有空仓时，且没超出交易次数限制，继续加空
+            if (b_p is None or b_p.volume < eps) or (a_p and self.trade_count < self.trade_limit):
+                vol = self.trade_unit[self.trade_count]
                 self.trade_count += 1
                 if vol > eps:
-                    self.open_long(self.exchange, self.sec_id, self.last_price, vol)
+                    self.open_short(self.exchange, self.sec_id, self.last_price, vol)
+            else:
+                # 已有多仓，平掉多仓
+                if b_p and b_p.volume > eps:
+                    self.close_long(self.exchange, self.sec_id, self.last_price, b_p.volume)
+                    self.trade_count = 0
         else:       ##  其他情况，忽略不处理
+            ## get positions and close if any
+            #self.trade_count = 0   ## reset trade count
             pass
 
 # 策略启动入口
 if __name__ == '__main__':
     #  初始化策略
-    ma = MA(config_file='ma_stock.ini')
+    ma = MA(config_file='ma.ini')
     #import pdb; pdb.set_trace()   # python调试开关
-    print 'strategy ready, waiting for market data ......'
+    print('strategy ready, waiting for market data ......')
     # 策略进入运行，等待数据事件
     ret = ma.run()
     # 打印策略退出状态
-    print "MA :", ma.get_strerror(ret)
+    print("MA :", ma.get_strerror(ret))
 

PositionManagement/python/dual_ma.py

@@ -208,11 +208,11 @@ def close_long_positions(self, b_p, ord_price=None):
         price = ord_price if ord_price else self.last_price - self.hops*self.tick_size
         self.logger.info("try to close long ... {0} @ {1}, today's position first".format(b_p.volume, price))
 
-        if b_p.exchange in (u'SHSE', u'SZSE'):  ## stocks
+        if b_p.exchange in ('SHSE', 'SZSE'):  ## stocks
             if b_p.available_yesterday:
                 self.close_long(b_p.exchange, b_p.sec_id, price, b_p.available_yesterday)
         else:
-            if self.exchange == u'SHFE':    ## special in SHFE
+            if self.exchange == 'SHFE':    ## special in SHFE
                 if b_p.available_today > 0:
                     self.close_long(b_p.exchange, b_p.sec_id, price, b_p.available_today)
                 if b_p.available_yesterday > 0:
@@ -226,10 +226,10 @@ def close_short_positions(self, a_p, ord_price=None):
         price = ord_price if ord_price else self.last_price + self.hops*self.tick_size
         self.logger.info("try to close short ... {0} @ {1}, today's position first".format(a_p.volume, price))
 
-        if a_p.exchange in (u'SHSE', u'SZSE'):  ## stocks, something must be wrong
+        if a_p.exchange in ('SHSE', 'SZSE'):  ## stocks, something must be wrong
             pass
         else:
-            if self.exchange == u'SHFE':   ## special in SHFE
+            if self.exchange == 'SHFE':   ## special in SHFE
                 if a_p.available_today > 0:
                     self.close_short(a_p.exchange, a_p.sec_id, price, a_p.available_today)
                 if a_p.available_yesterday > 0: