def get_row(pair, command):
ps = process_pair_string(pair)
ticker1 = ps.ticker1
ticker2 = ps.ticker2
fixed_stdev_ratio = ps.stdev_ratio
back_days = core.safe_execute(gcnv.PAIR_BACK_DAYS, ValueError,
lambda x: int(x) * 30, command[2])
bring_if_connected(ticker1)
bring_if_connected(ticker2)
try:
pair = Pair(ticker1, ticker2, fixed_stdev_ratio)
max_stored_date = gcnv.data_handler.get_max_stored_date(
"stock", ticker1)
date = '-' if max_stored_date is None \
else util.date_in_string(max_stored_date) # Need to change this
row = [
ticker1 + '-' + ticker2,
date,
'-',
pair.get_last_close(
back_days), # GettingInfoError raised here if not stored data
pair.min(back_days),
pair.max(back_days),
pair.current_rank(back_days),
pair.ma(back_days),
'-',
pair.stdev_ratio(back_days),
pair.correlation(back_days),
pair.hv_to_10_ratio(back_days),
'-'
]
closes = pair.closes(back_days)[-gcnv.PAIR_PAST_RESULTS:]
closes.reverse()
row += closes
return row
except (GettingInfoError, ZeroDivisionError,
statistics.StatisticsError) as e:
print(e)
return []
def get_row(ticker, command):
try:
bring_if_connected(ticker)
date = gcnv.data_handler.get_max_stored_date("stock", ticker)
if date is None:
return []
date = util.date_in_string(date)
back_days = core.safe_execute(gcnv.BACK_DAYS, ValueError,
lambda x: int(x) * 30, command[2])
iv = IV(ticker)
hv = HV(ticker)
mixed_vs = MixedVs(iv, hv)
stock = Stock(ticker)
spy_pair = Pair(ticker, "SPY")
spy_iv = IV("SPY")
earnings_data = load_earnings()
row = [ticker, date]
# Price related data
row += [
stock.get_close_at(
date), # GettingInfoError raised here if not stored data
f"{stock.min(back_days)} - {stock.max(back_days)}",
round(stock.min_max_rank(date, back_days)),
stock.range(28) / spy_pair.stdev_ratio(back_days),
stock.range(14) / spy_pair.stdev_ratio(back_days),
stock.move(7) / spy_pair.stdev_ratio(back_days),
stock.get_last_percentage_change(),
up_down_closes_str(stock, 14),
core.safe_execute('-', GettingInfoError, spy_pair.correlation,
back_days),
spy_pair.stdev_ratio(back_days),
stock.hv_to_10_ratio(back_days),
round(
notional.directional_stock_number(
stock.get_close_at(date),
spy_pair.stdev_ratio(back_days))),
round(
notional.neutral_options_number(
stock.get_close_at(date), spy_pair.stdev_ratio(back_days)),
1),
round(
notional.directional_options_number(
stock.get_close_at(date), spy_pair.stdev_ratio(back_days)),
1),
earnings_data[ticker][0],
earnings_data[ticker][1],
chart_link(ticker)
]
# Volatility related data
try:
row += [
iv.current_to_average_ratio(date, back_days),
mixed_vs.iv_current_to_hv_average(date, back_days),
mixed_vs.positive_difference_ratio(back_days),
mixed_vs.difference_average(back_days),
iv.current_percentile_iv_rank(back_days)
]
row += iv.period_iv_ranks(back_days, max_results=gcnv.IVR_RESULTS)
except (GettingInfoError, ZeroDivisionError,
statistics.StatisticsError) as e:
result_row_len = 5 # Number of rows above
row += ['-'] * (result_row_len + gcnv.IVR_RESULTS)
return row
except (GettingInfoError, InputError, ZeroDivisionError,
statistics.StatisticsError) as e:
print(e)
return []
