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compute_portvals<\/code>(<\/span>orders_file=’.\/orders\/orders.csv’<\/em>, start_val=1000000<\/em>, commission=9.95<\/em>, impact=0.005<\/em>)<\/span><\/dt>\n- \n
Computes the portfolio values.<\/p>\n
\n- Parameters<\/dt>\n
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\n- orders_file<\/strong> (str<\/em> or <\/em>file object<\/em>) \u2013 Path of the order file or the file object<\/li>\n
- start_val<\/strong> (int<\/em>) \u2013 The starting value of the portfolio<\/li>\n
- commission<\/strong> (float<\/em>) \u2013 The fixed amount in dollars charged for each transaction (both entry and exit)<\/li>\n
- impact<\/strong> (float<\/em>) \u2013 The amount the price moves against the trader compared to the historical data at each transaction<\/li>\n<\/ul>\n<\/dd>\n
- Returns<\/dt>\n
- \n
the result (portvals) as a single-column dataframe, containing the value of the portfolio for each trading day in the first column from start_date to end_date, inclusive.<\/p>\n<\/dd>\n
- Return type<\/dt>\n
- \n
pandas.DataFrame<\/p>\n<\/dd>\n<\/dl>\n<\/dd>\n<\/dl>\n
\ntest_code<\/code>(<\/span>)<\/span><\/dt>\n- \n
Helper function to test code<\/p>\n<\/dd>\n<\/dl>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n
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