porting algo to notebook

Back to Community

toan tran

posted

Hi guys, trying to move simple example algo attached to research platform and run a back test.

I'm having a lot trouble getting to work, can someone please help me?

Clone Algorithm

Backtest from to with initial capital

Cumulative performance:

Total Returns

Alpha

Beta

Sharpe

Sortino

Max Drawdown

Benchmark Returns

Volatility

Returns	1 Month	3 Month	6 Month	12 Month

Alpha	1 Month	3 Month	6 Month	12 Month

Beta	1 Month	3 Month	6 Month	12 Month

Sharpe	1 Month	3 Month	6 Month	12 Month

Sortino	1 Month	3 Month	6 Month	12 Month

Volatility	1 Month	3 Month	6 Month	12 Month

Max Drawdown	1 Month	3 Month	6 Month	12 Month

# Backtest ID: 57e303be43fae7102ca6a51d

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
 
def initialize(context):
    set_do_not_order_list(security_lists.leveraged_etf_list)
    # Rebalance every day, 1 hour after market open.
    schedule_function(my_rebalance, date_rules.every_day(), time_rules.market_open(hours=1))
    # Create our dynamic stock selector.
    attach_pipeline(make_pipeline(), 'my_pipeline')
         
def make_pipeline():
    
     
    # Create a dollar volume factor.
    dollar_volume = AverageDollarVolume(window_length=1)
 
    # Pick the top 1% of stocks ranked by dollar volume.
    high_dollar_volume = dollar_volume.percentile_between(99, 100)
     
    pipe = Pipeline(
        screen = high_dollar_volume,
        columns = {
            'dollar_volume': dollar_volume
        }
    )
    return pipe
 
def before_trading_start(context, data):
    """
    Called every day before market open.
    """
    context.output = pipeline_output('my_pipeline').sort('dollar_volume')
  
    # These are the securities that we are interested in trading each day.
    context.secs = context.output.index
     
def my_assign_weights(context, data):
    """
    Assign weights to securities that we want to order.
    """
    pass
 
def my_rebalance(context,data):
    cantrade = []
    for sec in context.secs[-20:]:
        if data.can_trade(sec) and (sec not in security_lists.leveraged_etf_list):
            cantrade.append(sec)
    for sec in context.portfolio.positions:
        if sec not in cantrade:
            order_target_percent(sec, 0)
    for sec in cantrade:
        order_target_percent(sec, 1.0/len(cantrade))
    print 1
    """
    Execute orders according to our schedule_function() timing. 
    """
    pass

Need Help? Contact Support

The material on this website is provided for informational purposes only and does not constitute an offer to sell, a solicitation to buy, or a recommendation or endorsement for any security or strategy, nor does it constitute an offer to provide investment advisory services by Quantopian.

In addition, the material offers no opinion with respect to the suitability of any security or specific investment. No information contained herein should be regarded as a suggestion to engage in or refrain from any investment-related course of action as none of Quantopian nor any of its affiliates is undertaking to provide investment advice, act as an adviser to any plan or entity subject to the Employee Retirement Income Security Act of 1974, as amended, individual retirement account or individual retirement annuity, or give advice in a fiduciary capacity with respect to the materials presented herein. If you are an individual retirement or other investor, contact your financial advisor or other fiduciary unrelated to Quantopian about whether any given investment idea, strategy, product or service described herein may be appropriate for your circumstances. All investments involve risk, including loss of principal. Quantopian makes no guarantees as to the accuracy or completeness of the views expressed in the website. The views are subject to change, and may have become unreliable for various reasons, including changes in market conditions or economic circumstances.

About Quantopian

Careers

Community

Events

Help

Status

Twitter

YouTube

Blog