def _add_volume_traded(self):
transactions = self.backtest_result.transactions
transactions_series = QFSeries(data=transactions,
index=(t.time for t in transactions))
if transactions_series.empty:
raise ValueError("Transactions series is empty")
# Add the chart containing the volume traded in terms of quantity
quantities = [abs(t.quantity) for t in transactions_series]
quantities_series = QFSeries(data=quantities,
index=transactions_series.index)
# Aggregate the quantities for each day
quantities_series = quantities_series.resample(
Frequency.DAILY.to_pandas_freq()).sum()
# Generate chart and add it to the document
self._add_line_chart_element(quantities_series,
"Volume traded per day [in contracts]")
# Add the chart containing the exposure of the traded assets
total_exposures = [
abs(t.quantity) * t.price * t.contract.contract_size
for t in transactions_series
]
total_exposures_series = QFSeries(data=total_exposures,
index=transactions_series.index)
total_exposures_series = total_exposures_series.resample(
Frequency.DAILY.to_pandas_freq()).sum()
# Generate chart and add it to the document
self._add_line_chart_element(
total_exposures_series,
"Volume traded per day [notional in currency units]")
def _add_number_of_transactions_chart(self, pandas_freq: str, title: str):
transactions = self.backtest_result.transactions
transactions_series = QFSeries(data=transactions,
index=(t.time for t in transactions))
if transactions_series.empty:
raise ValueError("Transactions series is empty")
# Compute the number of transactions per day
transactions_series = transactions_series.resample(
Frequency.DAILY.to_pandas_freq()).count()
# Aggregate the transactions using the given frequency
if to_offset(pandas_freq) > to_offset('D'):
transactions_series = transactions_series.rolling(
pandas_freq).sum()
# Cut the non complete beginning of the outputs (e.g. in case of 30 days window, cut the first 30 days)
start_date = transactions_series.index[0]
transactions_series = transactions_series.loc[start_date +
Timedelta(pandas_freq
):]
if transactions_series.empty:
# The available time period is too short to compute the statistics with the provided frequency
return
elif to_offset(pandas_freq) < to_offset('D'):
raise ValueError(
"The provided pandas frequency can not be higher than the daily frequency"
)
self._add_line_chart_element(transactions_series, title)
