Bank Nifty Crossover Strategy Error "Invalid Visual Code"

Blueshift
1 
# This is an auto-generated code <5e6a9a9446b068a534fe5a9542db6e58>
# uses generator version 1.1.0
# please use dataset nse



from blueshift.api import set_max_order_size, order, date_rules
from blueshift.api import set_max_order_count, set_slippage, schedule_function
from blueshift.api import set_commission, time_rules, symbol
from blueshift.finance import slippage, commission
from blueshift.library.library import handle_stop_loss, alpha_function, finish_prune_tracking
from blueshift.library.library import enter_short, squareoff, get_portfolio_assets
from blueshift.library.library import init_prune_tracking, handle_take_profit, get_history
from blueshift.library.library import enter_long


def initialize(context):
    set_max_order_count(20)
    set_max_order_size(max_quantity=1)
    set_slippage(slippage.FixedSlippage(0.05))
    set_commission(commission.PerShare(0.0))
    context.universe = [symbol('nifty bank')]
    context.short_signal = {}
    context.long_signal = {}
    context.my_10_ema = {}
    context.my_13_ema = {}
    schedule_function(scheduled_func_5924, date_rules.every_day(),
        time_rules.market_open(hours=0, minutes=15))


def stop_loss_func(context, data):
    assets = get_portfolio_assets(context)
    if not assets:
        return
    handle_stop_loss(context, data, None, 'PERCENT', 3)


def handle_data(context, data):
    take_profit_func(context, data)
    stop_loss_func(context, data)


def take_profit_func(context, data):
    assets = get_portfolio_assets(context)
    if not assets:
        return
    handle_take_profit(context, data, None, 'PERCENT', 6)


def rule_func_5942(context, data):
    for asset in context.universe:
        if context.short_signal[asset]:
            enter_short(context, asset, order, -1, None, 'SCHEDULE')
            squareoff(context, symbol('nifty bank'))


def rule_func_5936(context, data):
    for asset in context.universe:
        if context.long_signal[asset]:
            squareoff(context, symbol('nifty bank'))


def rule_func_5928(context, data):
    for asset in context.universe:
        if context.long_signal[asset]:
            enter_long(context, asset, order, 1, None, 'SCHEDULE')


def scheduled_func_5924(context, data):
    init_prune_tracking(context, 'SCHEDULE')
    context.history_1d = get_history(data, context.universe, ['close'], 20,
        '1d')
    for asset in context.universe:
        context.my_10_ema[asset] = alpha_function(context.history_1d, asset,
            func='exponential_moving_average', kwargs={'lookback': 10})
        context.my_13_ema[asset] = alpha_function(context.history_1d, asset,
            func='exponential_moving_average', kwargs={'lookback': 13})
        context.short_signal[asset] = context.my_10_ema[asset
            ] < context.my_13_ema[asset]
        context.long_signal[asset] = context.my_10_ema[asset
            ] > context.my_13_ema[asset]
    rule_func_5928(context, data)
    rule_func_5936(context, data)
    rule_func_5942(context, data)
    finish_prune_tracking(context, 'SCHEDULE')

 

2

Hi Deepak,



We are closing this query here as these have been responded to by blueshift-support. If you have any further questions regarding Blueshift, please feel free to reach out to the Blueshift team at blueshift-support@quantinsti.com.



Thanks,

Akshay