Hi,
I coded a long short strategy. I am not getting any syntax error. But It is not taking any trades. Can you help me out?
Zipline
from zipline.api import( symbol, get_datetime,order_target_percent,schedule_function,
date_rules, time_rules, attach_pipeline, pipeline_output,
set_commission,set_slippage,get_open_orders,cancel_order,
order_target,order,get_order
)
from zipline.errors import HistoryWindowStartsBeforeData
from zipline.finance import commission,slippage
from zipline.finance.slippage import FixedBasisPointsSlippage
from zipline.pipeline import Pipeline, CustomFactor
from zipline.pipeline.data import EquityPricing
from zipline.pipeline.factors import SimpleMovingAverage
from zipline.errors import HistoryWindowStartsBeforeData
from zipline.pipeline import Pipeline, CustomFilter
from zipline.finance.slippage import FixedSlippage
from zipline.finance import commission
from zipline.finance.slippage import FixedBasisPointsSlippage
from zipline.pipeline.factors import DailyReturns
Data manipulation
import pandas as pd
import numpy as np
import talib as ta
import bisect
def initialize(context):
context.universe = [symbol('TITAN'),symbol('SUNPHARMA'), symbol('MARUTI'),
symbol('TATAMOTORS'),symbol('BPCL'),symbol('BAJFINANCE'),
symbol('HDFCBANK'),symbol('ASIANPAINT'),
symbol('TCS'),symbol('RELIANCE'),symbol('INFY'),symbol('KOTAKBANK'),
symbol('WIPRO'),symbol('HEROMOTOCO'),symbol('AXISBANK'),
symbol('POWERGRID'),symbol('UPL'),symbol('TITAN'),symbol('MARUTI'),
symbol('YESBANK'),symbol('INDUSINDBK'),symbol('ICICIBANK'),
symbol('GAIL'),symbol('TECHM'),symbol('BHARTIARTL'),symbol('VEDL'),symbol('NTPC'),
symbol('HCLTECH'),symbol('HINDUNILVR'),symbol('ONGC'),symbol('TATASTEEL'),
symbol('LT'),symbol('COALINDIA'),symbol('JSWSTEEL'),symbol('GRASIM'),symbol('SBIN'),
symbol('DRREDDY'),symbol('BRITANNIA'),symbol('M&M'),symbol('ZEEL'),symbol('BAJAJ-AUTO'),
symbol('ADANIPORTS'),symbol('CIPLA'),symbol('HDFC'),symbol('INFRATEL'),symbol('IBULHSGFIN'),
symbol('SIEMENS'),symbol('UBL'),
symbol('MOTHERSUMI'),symbol('ICICIPRULI'),symbol('AMBUJACEM'),
symbol('DABUR'),symbol('L&TFH'),
symbol('DLF'),symbol('OFSS'),symbol('INDIGO'),symbol('COLPAL'),
symbol('NMDC'),symbol('ACC'),symbol('NHPC'),symbol('LUPIN'),
symbol('BHEL'),symbol('CADILAHC'),symbol('PIDILITIND'),symbol('CONCOR'),symbol('MARICO'),
symbol('SAIL'),symbol('HINDPETRO'),symbol('PEL'),symbol('GODREJCP'),
symbol('DIVISLAB'),symbol('ASHOKLEY'),symbol('AUROPHARMA'),symbol('HINDZINC'),
symbol('HAVELLS'),symbol('PETRONET'),symbol('IDEA'),
symbol('MCDOWELL-N'),symbol('BIOCON'),symbol('BANKBARODA'),
symbol('SRTRANSFIN')
]
context.set_slippage(FixedBasisPointsSlippage(basis_points = 3))
schedule_function(strategy,
date_rules.every_day(),
time_rules.market_open(hours=0, minutes=30))
schedule_function(placetrade, date_rules.every_day(),
time_rules.market_close(hours=0, minutes=10))
attach_pipeline(make_pipeline(context), name='my_pipeline')
def filter_universe(universe):
class FilteredUniverse(CustomFilter):
inputs = ()
window_length = 1
def compute(self,today,assets,out):
in_universe = [asset in universe for asset in assets]
out[:] = in_universe
return FilteredUniverse()
def technical_factor(lookback, indicator_fn, indicator_lookback):
class TechnicalFactor(CustomFactor):
inputs = [EquityPricing.close]
def compute(self,today,assets,out,close_price):
signals = np.apply_along_axis(indicator_fn, 0, close_price, indicator_lookback)
out[:] = signals
return TechnicalFactor(window_length = lookback)
def up_days(px, lookback):
return np.sum(np.where(np.diff(px) > 0, 1, 0))
def make_pipeline(context):
Initialize the pipeline
pipe = Pipeline()
Construct Factors
plusdays = technical_factor(30, up_days, 0)
pipe.add(plusdays, 'plus')
nifty200 = filter_universe(context.universe)
pipe.set_screen(nifty200)
return pipe
def strategy(context,data):
Access results using the name passed to attach_pipeline.
n=5
pipeline_results = pipeline_output('my_pipeline')
context.longselected_stocks = pipeline_results.sort('plus', ascending=False).iloc[:n]
context.shortselected_stocks = pipeline_results.sort('plus', ascending=True).iloc[:n]
weight = 1/10
for security in context.longselected_stocks.index:
#print(context.longselected_stocks)
#print(context.shortselected_stocks)
order_target_percent(security, weight)
for security in context.shortselected_stocks.index:
order_target_percent(security, -weight)
def placetrade(context,data):
for security in context.portfolio.positions:
order_target(security,0)