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
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(),
}
# pipe_screen = (low_returns | high_returns)
pipe = Pipeline(columns=pipe_columns)
return pipe
