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Why did the returns could go below -100%?

I'm new to quantopain, and I have a very simple algorithms to test, I'm surprised that the returns went below -100% at some period. Why did it happen?

Clone Algorithm
3
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Total Returns
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Alpha
--
Beta
--
Sharpe
--
Sortino
--
Max Drawdown
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Benchmark Returns
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Volatility
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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
def initialize(context):
    # Reference to AAPL
    context.xiv = symbol('xiv')
    set_benchmark(context.xiv)

def handle_data(context, data):
    # Position 100% of our portfolio to be long in AAPL
    order_target_percent(context.xiv, 0.5)
    print 
There was a runtime error.
5 responses

Welcome!

Leverage. Your strategy borrowed to trade more capital.

There are lots of forum posts and content devoted to controlling your leverage.

Happy learning!

Josh

Disclaimer

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.

Try using the schedule_function, the cumulative performance for the algo now follows the benchmark.

Clone Algorithm
0
Loading...
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
def initialize(context):
    context.xiv = symbol('xiv')
    set_benchmark(context.xiv)
    #set_commission(commission.PerShare(cost=0, min_trade_cost=0))
    #set_slippage(slippage.FixedSlippage(spread=0.0))    
    schedule_function(
        rebalance,
        date_rules.every_day(),
        time_rules.market_open(minutes=5)
    )
def handle_data(context, data):
    pass
def rebalance(context, data):
    order_target_percent(context.xiv,1.0)
There was a runtime error.

Thank you Josh and Ted!
I got it, I will try to learn how to control leverage.

Hi Aaron,

I'd recommend checking out Lesson 10 of the Getting Started Tutorial. It discusses managing your orders to control leverage.

Disclaimer

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.

Thank you Jamie! I'll check it out.

I have a question, why doesn't it have a option to set max leverage?
you know people like me don't want to use leverage, so I could simply set "context.account.max_leverage=0", thus I could make sure no leverage would be used in my algo.