Merge branch 'master' of https://github.com/kanghua309/strategy

# Conflicts:
#	campaign/deeplearn/training.py
#	me/helper/research_env.py

campaign/checkmode/factors.py

@@ -0,0 +1,85 @@
+# -*- coding: utf-8 -*-
+"""
+Created on Wed May 17 13:42:21 2017
+
+@author: kanghua
+"""
+import numpy as np
+import pandas as pd
+
+from zipline.pipeline.data import USEquityPricing
+from zipline.pipeline.factors import CustomFactor, Returns, Latest
+from me.pipeline.factors.tsfactor import Fundamental
+
+
+class ILLIQ(CustomFactor):
+    inputs = [USEquityPricing.close,USEquityPricing.volume]
+    window_length = int(252)
+    def compute(self, today, assets, out, close,volume):
+        _rets = pd.DataFrame(close, columns=assets).pct_change()[1:]
+        print(_rets.head(10))
+        _vols  = pd.DataFrame(volume, columns= assets)[1:]
+        print(_vols.head(10))
+        print(_rets/_vols)
+        print pd.rolling_mean(_rets/_vols, window=self.window_length)
+        #out[:] =
+
+
+import click
+import numpy as np
+import pandas as pd
+from zipline.pipeline import Pipeline
+from zipline.pipeline.data import USEquityPricing
+from zipline.pipeline.factors import Latest
+from zipline.pipeline.factors import Returns
+from zipline.utils.cli import Date
+
+from me.helper.research_env import Research
+from me.pipeline.factors.tsfactor import Fundamental
+from me.pipeline.filters.universe import make_china_equity_universe, default_china_equity_universe_mask, \
+    private_universe_mask
+from zipline.utils.cli import Date, Timestamp
+start = '2015-9-1'  # 必须在国内交易日
+end   = '2015-9-8'  # 必须在国内交易日
+
+def make_pipeline(asset_finder):
+    # h2o = USEquityPricing.high.latest / USEquityPricing.open.latest
+    # l2o = USEquityPricing.low.latest / USEquityPricing.open.latest
+    # c2o = USEquityPricing.close.latest / USEquityPricing.open.latest
+    # h2c = USEquityPricing.high.latest / USEquityPricing.close.latest
+    # l2c = USEquityPricing.low.latest / USEquityPricing.close.latest
+    # h2l = USEquityPricing.high.latest / USEquityPricing.low.latest
+    #
+    # vol = USEquityPricing.volume.latest
+    # outstanding = Fundamental(asset_finder).outstanding
+    # outstanding.window_safe = True
+    # turnover_rate = vol / Latest([outstanding])
+    # returns = Returns(inputs=[USEquityPricing.close], window_length=5)  # 预测一周数据
+    private_universe = private_universe_mask(['000001','000002','000003'],asset_finder=asset_finder)
+
+    illiq = ILLIQ(window_length=10,mask = private_universe)
+    pipe_columns = {
+        # 'h2o': h2o.log1p().zscore(),
+        # 'l2o': l2o.log1p().zscore(),
+        # 'c2o': c2o.log1p().zscore(),
+        # 'h2c': h2c.log1p().zscore(),
+        # 'l2c': l2c.log1p().zscore(),
+        # 'h2l': h2l.log1p().zscore(),
+        # 'vol': vol.zscore(),
+        # 'turnover_rate': turnover_rate.log1p().zscore(),
+        # 'return': returns.log1p(),
+        'ILLIQ':illiq,
+    }
+    # pipe_screen = (low_returns | high_returns)
+    pipe = Pipeline(columns=pipe_columns,screen=private_universe)
+    return pipe
+
+
+
+pd.set_option('display.width', 800)
+research = Research()
+print(research.get_engine()._finder)
+my_pipe = make_pipeline(research.get_engine()._finder)
+result = research.run_pipeline(my_pipe,
+                               Date(tz='utc', as_timestamp=True).parser(start),
+                               Date(tz='utc', as_timestamp=True).parser(end))

me/pipeline/filters/universe.py

@@ -202,14 +202,19 @@ def compute(self, today, asset_ids, out, *inputs):
             #print out
     return IsInDefaultChinaUniverse()
 
-def private_universe_mask(mask):
+def private_universe_mask(mask,asset_finder = None):
     mask = mask
+    def sid(sid):
+        return asset_finder.retrieve_asset(sid)
     class IsInPrivateUniverse(CustomFilter):
         inputs = [];
         window_length = 1
         def compute(self, today, asset_ids, out, *inputs):
-            #print asset_ids
             #print maskset
+            #print asset_ids
+            # for id in asset_ids:
+            #     print id
+            #     print type(sid(id))
             assets  = [sid(id).symbol for id in asset_ids]
             #print "--------------"
             #print pd.Series(assets)