Beispiel #1
0
 else:
     f1 = plt.figure(1)
     pf.plot_rolling_returns(strat_ret, factor_returns=bm_ret)
     f1.show()
     f2 = plt.figure(2)
     pf.plot_rolling_volatility(strat_ret, factor_returns=bm_ret)
     f2.show()
     f3 = plt.figure(3)
     pf.plot_rolling_sharpe(strat_ret)
     f3.show()
     f4 = plt.figure(4)
     pf.plot_drawdown_periods(strat_ret)
     f4.show()
     f5 = plt.figure(5)
     pf.plot_monthly_returns_heatmap(strat_ret)
     f5.show()
     f6 = plt.figure(6)
     pf.plot_annual_returns(strat_ret)
     f6.show()
     f7 = plt.figure(7)
     pf.plot_monthly_returns_dist(strat_ret)
     plt.show()
     f8 = plt.figure(8)
     pf.create_position_tear_sheet(strat_ret, df_positions)
     plt.show()
     f9 = plt.figure(9)
     pf.create_txn_tear_sheet(strat_ret, df_positions, df_trades)
     plt.show()
     f10 = plt.figure(10)
     pf.create_round_trip_tear_sheet(strat_ret, df_positions, df_trades)
     plt.show()
def create_report(perf,
                  filename,
                  now,
                  doc=None,
                  duration=None,
                  param=None,
                  info=None,
                  show_image=True):
    if not hasattr(perf, 'returns'):
        perf['returns'] = perf['pnl'] / (perf['portfolio_value'] - perf['pnl'])
        perf['returns'] = perf['returns'].replace([np.nan, np.inf, -np.inf],
                                                  0.0)

    tot_positions = sum([len(x) for x in perf.positions])
    if tot_positions == 0:
        log.warn("No positions available")
        return

    rets, positions, transactions = pf.utils.extract_rets_pos_txn_from_zipline(
        perf)
    date_rows = OrderedDict()
    if len(rets.index) > 0:
        date_rows['Start date'] = rets.index[0].strftime('%Y-%m-%d')
        date_rows['End date'] = rets.index[-1].strftime('%Y-%m-%d')
        date_rows['Total months'] = int(len(rets) / 21)

    perf_stats_series = pf.timeseries.perf_stats(rets,
                                                 positions=positions,
                                                 transactions=transactions)

    benchmark_rets = returns(symbol('SPY'), rets.index[0], rets.index[-1])
    benchmark_perf_stats = pf.timeseries.perf_stats(benchmark_rets)

    perf_stats_df = pd.DataFrame(perf_stats_series, columns=['Backtest'])
    perf_stats_df['Benchmark'] = benchmark_perf_stats
    perf_stats_df[
        'Spread'] = perf_stats_df['Backtest'] - perf_stats_df['Benchmark']
    format_perf_stats(perf_stats_df)

    drawdown_df = pf.timeseries.gen_drawdown_table(rets, top=5)
    rets_interesting = pf.timeseries.extract_interesting_date_ranges(rets)
    positions = utils.check_intraday('infer', rets, positions, transactions)
    transactions_closed = rt.add_closing_transactions(positions, transactions)
    trades = rt.extract_round_trips(
        transactions_closed,
        portfolio_value=positions.sum(axis='columns') / (1 + rets))

    if show_image:
        fig0 = None
        fig1 = None
        fig2 = None
        fig3 = None
        fig4 = None
        fig5 = None
        try:
            fig0 = create_log_returns_chart(rets, benchmark_rets)
        except Exception as e:
            log.warn(e)

        try:
            fig1 = pf.create_returns_tear_sheet(rets,
                                                positions,
                                                transactions,
                                                benchmark_rets=benchmark_rets,
                                                return_fig=True)
        except Exception as e:
            log.warn(e)

        try:
            fig2 = pf.create_position_tear_sheet(rets,
                                                 positions,
                                                 return_fig=True)
        except Exception as e:
            log.warn(e)

        try:
            fig3 = pf.create_txn_tear_sheet(rets,
                                            positions,
                                            transactions,
                                            return_fig=True)
        except Exception as e:
            log.warn(e)

        try:
            fig4 = pf.create_interesting_times_tear_sheet(rets,
                                                          return_fig=True)
        except Exception as e:
            log.warn(e)

        try:
            fig5 = pf.create_round_trip_tear_sheet(rets,
                                                   positions,
                                                   transactions,
                                                   return_fig=True)
        except Exception as e:
            log.warn(e)

    report_suffix = "_%s_%.2f_report.htm" % (
        now.strftime(DATETIME_FMT), 100. * perf_stats_series['Annual return'])
    reportfile = change_extension(filename, report_suffix)
    with open(reportfile, 'w') as f:
        print("""<!DOCTYPE html>
<html>
   <head>
      <title>Performance Report</title>
      <style >
         body {
         font-family: Arial, Helvetica, sans-serif;
         }
         table {
         border-collapse: collapse;
         }
         tbody tr:nth-child(odd) {
         background-color: lightgrey;
         }
         tbody tr:nth-child(even) {
         background-color: white;
         }
         tr th {
         border: none;
         text-align: right;
         padding: 2px 5px 2px;
         }
         tr td {
         border: none;
         text-align: right;
         padding: 2px 5px 2px;
         }
      </style>
      
      <script type="text/javascript">
        function showElement() {
            element = document.getElementById('code'); 
            element.style.visibility = 'visible'; 
        } 
      
        function hideElement() { 
            element = document.getElementById('code'); 
            element.style.visibility = 'hidden'; 
        } 
      </script> 
   </head>
   <body>""",
              file=f)
        print("<h1>Performance report for " + os.path.basename(filename) +
              "</h1>",
              file=f)
        print("<p>Created on %s</p>" % (now), file=f)
        if duration is not None:
            print("<p>Backtest executed in %s</p>" %
                  (time.strftime("%H:%M:%S", time.gmtime(duration))),
                  file=f)
        if doc is not None:
            print('<h3>Description</h3>', file=f)
            print('<p style="white-space: pre">%s</p>' % doc.strip(), file=f)
        if param is not None and len(param) > 0:
            print('<h3>Parameters</h3>', file=f)
            print('<pre>%s</pre><br/>' % str(param), file=f)
        if info is not None and len(info) > 0:
            print('<h3>Info</h3>', file=f)
            print('<pre>%s</pre><br/>' % str(info), file=f)
        print(to_html_table(perf_stats_df,
                            float_format='{0:.2f}'.format,
                            header_rows=date_rows),
              file=f)
        print("<br/>", file=f)
        if show_image:
            if fig0 is not None:
                print("<h3>Log Returns</h3>", file=f)
                print(_to_img(fig0), file=f)
                print("<br/>", file=f)
        print(to_html_table(
            drawdown_df.sort_values('Net drawdown in %', ascending=False),
            name='Worst drawdown periods',
            float_format='{0:.2f}'.format,
        ),
              file=f)
        print("<br/>", file=f)
        print(to_html_table(pd.DataFrame(rets_interesting).describe().
                            transpose().loc[:, ['mean', 'min', 'max']] * 100,
                            name='Stress Events',
                            float_format='{0:.2f}%'.format),
              file=f)
        print("<br/>", file=f)
        if len(trades) >= 5:
            stats = rt.gen_round_trip_stats(trades)
            print(to_html_table(stats['summary'],
                                float_format='{:.2f}'.format,
                                name='Summary stats'),
                  file=f)
            print("<br/>", file=f)
            print(to_html_table(stats['pnl'],
                                float_format='${:.2f}'.format,
                                name='PnL stats'),
                  file=f)
            print("<br/>", file=f)
            print(to_html_table(stats['duration'],
                                float_format='{:.2f}'.format,
                                name='Duration stats'),
                  file=f)
            print("<br/>", file=f)
            print(to_html_table(stats['returns'] * 100,
                                float_format='{:.2f}%'.format,
                                name='Return stats'),
                  file=f)
            print("<br/>", file=f)
            stats['symbols'].columns = stats['symbols'].columns.map(
                format_asset)
            print(to_html_table(stats['symbols'] * 100,
                                float_format='{:.2f}%'.format,
                                name='Symbol stats'),
                  file=f)

        if show_image:
            if fig1 is not None:
                print("<h3>Returns</h3>", file=f)
                print(_to_img(fig1), file=f)

            if fig2 is not None:
                print("<h3>Positions</h3>", file=f)
                print(_to_img(fig2), file=f)

            if fig3 is not None:
                print("<h3>Transactions</h3>", file=f)
                print(_to_img(fig3), file=f)

            if fig4 is not None:
                print("<h3>Interesting Times</h3>", file=f)
                print(_to_img(fig4), file=f)

            if fig5 is not None:
                print("<h3>Trades</h3>", file=f)
                print(_to_img(fig5), file=f)

        print('<br/>', file=f)
        print(
            '<button onclick="showElement()">Show Code</button> <button onclick="hideElement()">Hide Code</button>',
            file=f)
        print('<pre id="code" style="visibility: hidden">', file=f)
        print(open(filename, "r").read(), file=f)
        print('</pre>', file=f)

        print("</body>\n</html>", file=f)