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Fix price-repair-currency, logic was inverted #2036

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Aug 24, 2024
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98 changes: 56 additions & 42 deletions yfinance/scrapers/history.py
Original file line number Diff line number Diff line change
Expand Up @@ -368,48 +368,7 @@ def history(self, period="1mo", interval="1d",
# Must fix bad 'Adj Close' & dividends before 100x/split errors.
# First make currency consistent. On some exchanges, dividends often in different currency
# to prices, e.g. £ vs pence.
if currency in ["GBp", "ZAc", "ILA"]:
if currency == 'GBp':
# UK £/pence
currency = 'GBP'
m = 0.01
elif currency == 'ZAc':
# South Africa Rand/cents
currency = 'ZAR'
m = 0.01
elif currency == 'ILA':
# Israel Shekels/Agora
currency = 'ILS'
m = 0.01

prices_in_subunits = True # usually is true
if df.index[-1] > (pd.Timestamp.utcnow() - _datetime.timedelta(days=30)):
try:
ratio = self._history_metadata['regularMarketPrice'] / self._history_metadata['chartPreviousClose']
if abs((ratio*m)-1) < 0.1:
# within 10% of 100x
prices_in_subunits = True
except Exception:
pass
if prices_in_subunits:
for c in _PRICE_COLNAMES_:
df[c] *= m
self._history_metadata["currency"] = currency

f_div = df['Dividends']!=0.0
if f_div.any():
# But sometimes the dividend was in pence.
# Heuristic is: if dividend yield is ridiculous high vs converted prices, then
# assume dividend was also in pence and convert to GBP.
# Threshold for "ridiculous" based on largest yield I've seen anywhere - 63.4%
# If this simple heuritsic generates a false positive, then _fix_bad_div_adjust()
# will detect and repair.
divs = df[['Close','Dividends']].copy()
divs['Close'] = divs['Close'].ffill().shift(1, fill_value=divs['Close'].iloc[0])
divs = divs[f_div]
div_pcts = (divs['Dividends'] / divs['Close']).to_numpy()
if len(div_pcts) > 0 and np.average(div_pcts) > 1:
df['Dividends'] *= m
df, currency = self._standardise_currency(df, currency)

df = self._fix_bad_div_adjust(df, interval, currency)

Expand Down Expand Up @@ -933,6 +892,61 @@ def _reconstruct_intervals_batch(self, df, interval, prepost, tag=-1):

return df_v2

def _standardise_currency(self, df, currency):
if currency not in ["GBp", "ZAc", "ILA"]:
return df, currency
currency2 = currency
if currency == 'GBp':
# UK £/pence
currency2 = 'GBP'
m = 0.01
elif currency == 'ZAc':
# South Africa Rand/cents
currency2 = 'ZAR'
m = 0.01
elif currency == 'ILA':
# Israel Shekels/Agora
currency2 = 'ILS'
m = 0.01

# Use latest row with actual volume, because volume=0 rows can be 0.01x the other rows.
# _fix_unit_switch() will ensure all rows are on same scale.
f_volume = df['Volume']>0
if not f_volume.any():
return df, currency
last_row = df.iloc[np.where(f_volume)[0][-1]]
prices_in_subunits = True # usually is true
if last_row.name > (pd.Timestamp.utcnow() - _datetime.timedelta(days=30)):
try:
ratio = self._history_metadata['regularMarketPrice'] / last_row['Close']
if abs((ratio*m)-1) < 0.1:
# within 10% of 100x
prices_in_subunits = False
except Exception:
# Should never happen but just-in-case
pass
if prices_in_subunits:
for c in _PRICE_COLNAMES_:
df[c] *= m
self._history_metadata["currency"] = currency

f_div = df['Dividends']!=0.0
if f_div.any():
# But sometimes the dividend was in pence.
# Heuristic is: if dividend yield is ridiculous high vs converted prices, then
# assume dividend was also in pence and convert to GBP.
# Threshold for "ridiculous" based on largest yield I've seen anywhere - 63.4%
# If this simple heuristic generates a false positive, then _fix_bad_div_adjust()
# will detect and repair.
divs = df[['Close','Dividends']].copy()
divs['Close'] = divs['Close'].ffill().shift(1, fill_value=divs['Close'].iloc[0])
divs = divs[f_div]
div_pcts = (divs['Dividends'] / divs['Close']).to_numpy()
if len(div_pcts) > 0 and np.average(div_pcts) > 1:
df['Dividends'] *= m

return df, currency2

@utils.log_indent_decorator
def _fix_unit_mixups(self, df, interval, tz_exchange, prepost):
if df.empty:
Expand Down
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