How to create pyfolio round trip tearsheet?

[kian hong Tan]

@run-out I realized there was a html copy being saved into local directory. So I guess it's deemed successful? Initially I thought a new browser will automatically pop up to show the results.

[kian hong Tan]

@balibou That's positive. I use the below code and now I'm able to see the html tearsheet saved in my local drive. But not sure why you have the html error.

qs.reports.html(df_values, "SPY",output="qs.html")

[run-out]

You are really into a quantstats problem at this point.

[kian hong Tan]

@run-out ok, I will check with ranaroussi then. Thank you.

[kian hong Tan]

@run-out I came out with a workaround, by just opening the file since it's already saved. : )

webbrowser.open('qs.html')

[Jonny8]

@kian-hong-Tan

Hi,

I have issues getting the code to work. Can you post your working code ?

Best!

[kunalp]

@Arun-Lama

With the second alternative,

pf.create_round_trip_tear_sheet(returns, positions=positions, transactions=transactions)

, you do get the error that you have mentioned.

You will need to go to the pyfolio files and make certain changes. At this point I am not sure whether I should go to pyfolio github repository and do a pull request because my changes work for what I need in the context of backtrader. I am in no way certain that making these changes will not break something else in pyfolio.

In round_trips.py, I made the following changes
Original

grouped_price = (t.groupby(('block_dir', 'block_time')).apply(vwap))

Modified to:

grouped_price = (t.groupby(['block_dir', 'block_time']).apply(vwap)) 

After you solve this error, as the pyfolio code is able to run further you will get a few more errors. As I understood, it is because pandas moved ahead and deprecated certain functionality. Link below:
https://pandas.pydata.org/pandas-docs/stable/whatsnew/v0.20.0.html#whatsnew-0200-api-breaking-deprecate-group-agg-dict

This functionality was used to pass dicts to

agg_all_long_short

Earlier code was:

PNL_STATS = OrderedDict([
    ('Total profit', lambda x: x.sum()),
     ('Gross profit', lambda x: x[x > 0].sum()),
     ('Gross loss', lambda x: x[x < 0].sum()),
     ('Profit factor', lambda x: x[x > 0].sum() / x[x < 0].abs().sum()
      if x[x < 0].abs().sum() != 0 else np.nan),
     ('Avg. trade net profit', 'mean'),
     ('Avg. winning trade', lambda x: x[x > 0].mean()),
     ('Avg. losing trade', lambda x: x[x < 0].mean()),
     ('Ratio Avg. Win:Avg. Loss', lambda x: x[x > 0].mean() /
      x[x < 0].abs().mean() if x[x < 0].abs().mean() != 0 else np.nan),
     ('Largest winning trade', 'max'),
     ('Largest losing trade', 'min'),])

Change this to:

PNL_STATS = (
     (lambda x: x.sum()),
     ( lambda x: x[x > 0].sum()),
     (lambda x: x[x < 0].sum()),
     ( lambda x: x[x > 0].sum() / x[x < 0].abs().sum()
      if x[x < 0].abs().sum() != 0 else np.nan),
     ('mean'),
     (lambda x: x[x > 0].mean()),
     ( lambda x: x[x < 0].mean()),
     ( lambda x: x[x > 0].mean() / x[x < 0].abs().mean() if x[x < 0].abs().mean() != 0 else np.nan),
     ('max'),
     ('min'),
)

Please make similar changes for the other dicts:
Original code

SUMMARY_STATS = OrderedDict([('Total number of round_trips', 'count'),
    ('Percent profitable', lambda x: len(x[x > 0]) / float(len(x))),
     ('Winning round_trips', lambda x: len(x[x > 0])),
     ('Losing round_trips', lambda x: len(x[x < 0])),
     ('Even round_trips', lambda x: len(x[x == 0])),
     ])

Modified code

SUMMARY_STATS = (
     ('count'),
     (lambda x: len(x[x > 0]) / float(len(x))),
     (lambda x: len(x[x > 0])),
     (lambda x: len(x[x < 0])),
     (lambda x: len(x[x == 0])),
)

And so on for even the other dicts:

RETURN_STATS

DURATION_STATS

Essentially, you now cannot pass rename logic in the dicts themselves. This also means that for you will need to create a list of the column names and pass it yourself.

In

def gen_round_trip_stats(round_trips):

this is the updated code Main changes are that we are creating a list of column names col_list before each function call to pass to the agg_all_long_short function (for reasons explained above - pandas deprecating nested renaming)

col_list = ['Total profit', 'Gross profit', 'Gross loss', 'Profit factor', 'Avg. trade net profit', 'Avg. winning trade', 'Avg. losing trade', 'Ratio Avg. Win:Avg. Loss', 'Largest winning trade', 'Largest losing trade']
stats['pnl'] = agg_all_long_short(round_trips, 'pnl', PNL_STATS, col_list)

col_list = ['Total number of round_trips','Percent profitable', 'Winning round_trips', 'Losing round_trips', 'Even round_trips']
stats['summary'] = agg_all_long_short(round_trips, 'pnl', SUMMARY_STATS, col_list)

col_list = ['Average duration', 'Median duration','Longest duration', 'Shortest duration']
stats['duration'] = agg_all_long_short(round_trips, 'duration',
                                           DURATION_STATS, col_list)

col_list = ['Avg returns all round_trips','Avg returns winning','Avg returns losing', 'Median returns all round_trips', 'Median returns winning','Median returns losing', 'Largest winning trade', 'Largest losing trade' ]
stats['returns'] = agg_all_long_short(round_trips, 'rt_returns',
                                          RETURN_STATS, col_list)

In function definition:
original

def agg_all_long_short(round_trips, col, stats_dict):

modified (adding col_list argument)

def agg_all_long_short(round_trips, col, stats_dict, col_list):

A few more changes in tears.py
Original code:

 sns.distplot(trades.rt_returns.dropna() * 100, kde=False,
                 ax=ax_pnl_per_round_trip_pct)

Modified code:

 sns.distplot(trades.returns.dropna() * 100, kde=False,
                 ax=ax_pnl_per_round_trip_pct)

With these changes the round_trip functionality should work. If any problems are faced please reply here. It will be helpful for the community.

Thanks.