def as_dict(self) -> Dict:
return {
"type": self.type,
"from": format_date(self.from_date),
"to": format_date(self.to_date),
"holdings": [holding._asdict() for holding in self.holdings],
"pctChange": self.pct_change
}
def as_dict(self) -> Dict:
return {
"statement": AccountStatement.from_account(self.result.account).as_dict(),
"returns": self.result.returns,
"maxDrawdown": self.result.max_drawdown,
"sharpeRatio": self.result.sharpe_ratio,
"startDate": format_date(self.result.start_date),
"endDate": format_date(self.result.end_date)
}
def calc(self, historic_prices: FundHistoricPrices) -> FundIndicator:
try:
drawdown_series = to_drawdown_series(historic_prices)
date = drawdown_series.idxmin()
return FundIndicator(drawdown_series[date],
metadata={"date": format_date(date)})
except:
return FundIndicator(np.nan)
def _reduce_returns(historic_prices_series: FundHistoricPrices, offset: pd.DateOffset,
agg_func: Callable[[FundHistoricPrices], datetime]) -> FundIndicator:
try:
shifted_series = drop_duplicate_index(
historic_prices_series.shift(freq=offset)) \
.reindex(index=historic_prices_series.index, method="ffill")
returns_series = (historic_prices_series - shifted_series) / shifted_series
date = agg_func(returns_series)
return FundIndicator(returns_series[date], metadata={"date": format_date(date)})
except:
return FundIndicator(np.nan)
def calc(self, historic_prices: FundHistoricPrices) -> FundIndicator:
try:
peaks = historic_prices.expanding().max()
peak_diffs = peaks.diff()
recovery_dates = peak_diffs.index[peak_diffs.gt(0)]
# add begin and last before comparison
recovery_dates = recovery_dates \
.insert(0, historic_prices.first_valid_index()) \
.append(DatetimeIndex([historic_prices.last_valid_index()]))
recovery_times = recovery_dates.to_series().diff()
date, mdt = recovery_times.idxmax(), recovery_times.max().days
return FundIndicator(mdt, metadata={"date": format_date(date)})
except:
return FundIndicator(np.nan)
def on_post_predict(self, req: falcon.Request, resp: falcon.Response):
params = SimulateRoutes.PredictParam.from_dict(req.media)
predict_date = BDAY.rollback(params.date) if params.date else None
simulator = self._build_simulator(params.simulate_param)
result = simulator.predict(predict_date)
resp.media = {
"date": format_date(result.date),
"funds": [
{
"isin": fund.isin,
"sedol": fund.sedol,
"name": fund.name
}
for fund in result.funds
]
}
def test_format_date():
d = datetime(2019, 1, 1, tzinfo=timezone.utc)
assert format_date(d) == "2019-01-01T00:00:00Z"
def as_dict(self) -> Dict:
return {
"date": format_date(self.date),
"price": self.price
}