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DOC: Adding the no-benchmark setting for the initial run in the readme so that the first run by end users doesn't fail
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3 changed files with 4 additions and 3 deletions
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@ -99,7 +99,7 @@ Once you have your key, run the following from the command line:
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.. code:: bash
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$ QUANDL_API_KEY=<yourkey> zipline ingest -b quandl
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$ zipline run -f dual_moving_average.py --start 2014-1-1 --end 2018-1-1 -o dma.pickle
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$ zipline run -f dual_moving_average.py --start 2014-1-1 --end 2018-1-1 -o dma.pickle --no-benchmark
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This will download asset pricing data data from `quandl`, and stream it through the algorithm
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over the specified time range. Then, the resulting performance DataFrame is saved in `dma.pickle`, which you
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@ -162,6 +162,9 @@ on OSX):
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--benchmark-symbol The instrument's symbol to be used as
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a benchmark.
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(should exist in the ingested bundle)
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--benchmark-sid The sid of the instrument to be used as a
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benchmark.
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(should exist in the ingested bundle)
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--no-benchmark This flag is used to set the benchmark to
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zero. Alpha, beta and benchmark metrics
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are not calculated
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@ -536,8 +536,6 @@ class TradingAlgorithm(object):
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raise ValueError("Must specify either benchmark_sid "
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"or benchmark_returns.")
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benchmark_asset = None
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# get benchmark info from trading environment, which defaults to
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# downloading data from IEX Trading.
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benchmark_returns = self.benchmark_returns
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return BenchmarkSource(
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benchmark_asset=benchmark_asset,
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