QQQ TLT 股债平衡策略

1.年回报

"""
This is a template algorithm on Quantopian for you to adapt and fill in.
"""
from quantopian.algorithm import attach_pipeline, pipeline_output
from quantopian.pipeline import Pipeline
from quantopian.pipeline.data.builtin import USEquityPricing
from quantopian.pipeline.factors import AverageDollarVolume
from quantopian.pipeline.filters.morningstar import Q1500US
 
def initialize(context):
    """
    Called once at the start of the algorithm.
    """
    set_benchmark(symbol('QQQ'))
    context.firstBuy = False
    context.firstYear = "%d"%(get_datetime("US/Eastern").date().year)
    context.leverage = 1.0
    # Rebalance every day, 1 hour after market open.
    schedule_function(my_rebalance, date_rules.every_day(), time_rules.market_open(hours=1))
     
    # Record tracking variables at the end of each day.
    schedule_function(my_record_vars, date_rules.every_day(), time_rules.market_close())
     

     
def my_assign_weights(context, data):
    """
    Assign weights to securities that we want to order.a
    """
    pass
 
def my_rebalance(context,data):
    """
    Execute orders according to our schedule_function() timing. 
    """
    currentYear = "%d"%(get_datetime("US/Eastern").date().year)
    if currentYear != context.firstYear or context.firstBuy == False:
        context.firstYear = currentYear
        context.firstBuy = True
        order_target_percent(symbol('QQQ'), 0.5 * context.leverage)
        order_target_percent(symbol('TLT'), 0.5 * context.leverage)
    pass
 
def my_record_vars(context, data):
    """
    Plot variables at the end of each day.
    """
    pass
 
def handle_data(context,data):
    """
    Called every minute.
    """
    pass