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Newbie question: What did I just do?

Hello!

First I would like to say you guys have built a great product and I'm having lots of fun playing with it.

Anyway, my question is that shouldn't there be some sort of warnings notifying users of situations such as this? It looks like I'm just selling a stock that I never even ordered over and over again and seeing crazy returns?

Clone Algorithm
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Backtest from to with initial capital
Total Returns
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Alpha
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Beta
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Sharpe
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Sortino
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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):
    context.stocks = [sid(24)]
    context.max_notional = 1000000.1
    context.min_notional = -1000000.0
def handle_data(context, data):
    for stock in context.stocks:
        order(stock,-500)        
This backtest was created using an older version of the backtester. Please re-run this backtest to see results using the latest backtester. Learn more about the recent changes.
There was a runtime error.
1 response

Hello Bob,

Your analysis is right - your algo just sells Apple short, indiscriminately, over and over. Since Apple has been going down for the last few months, you made a lot of (fictional) money.

As it is today, Quantopian sets very few rules.

  • Commissions are included by default, but you can turn them off.
  • Slippage is included by default, but you can turn that off too.
  • You can't artificially increase your cash, or magically create new stock, or other deus ex machina
  • You can't get around look-ahead bias - there's no real way for you to include future data in your algorithm.

With such a short set of rules, the rest of the algorithm writing is left to best practice. If you clone the sample agorithm you'll see some of those best practices implemented. The sample algorithm includes a max- and min-notional. If you take the code from your sample and apply some notional limits, you'll get a more reasonable-looking result.

I agree that we need to make it easier to avoid crazy situations like this. Cash management, notional limits, margin limits, borrowing limits, etc. are all ripe for improvements. I'm not sure when we'll get to it, but they are on the list.

Dan

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