def get_weights_html(self):
fmt_pct = tf.FmtPercent(1, apply_to_header_and_index=False)
fmt_align = tf.FmtAlignTable("left")
fmt_background = tf.FmtStripeBackground(
first_color=tf.colors.LIGHT_GREY,
second_color=tf.colors.WHITE,
header_color=tf.colors.BLACK)
targetweights = Block(self.InputList[3],
formatters=[fmt_pct, fmt_align, fmt_background],
use_default_formatters=False)._repr_html_()
targetweights = {'targetweights_table': targetweights}
effectiveweights = Block(
self.InputList[4],
formatters=[fmt_pct, fmt_align, fmt_background],
use_default_formatters=False)._repr_html_()
effectiveweights = {'effectiveweights_table': effectiveweights}
return targetweights, effectiveweights
def test_FmtPercent():
fmt = pbtf.FmtPercent(2)
assert fmt.fmt_string == '{:.2%}'
data = FormatterData(0.1234, None, None, None)
res = fmt._modify_cell_content(data)
assert res == '12.34%'
def get_performance_stats_html(self):
pct_rows = [('P&L', 'Total return'), ('P&L', 'Annual return'),
('P&L', 'Annual return (asset mode)'),
('Risk-adjusted return based on Drawdown',
'Max percentage drawdown')]
dec_rows = [
('P&L', 'Starting cash'),
('P&L', 'End value'),
('Risk-adjusted return based on Drawdown', 'Max money drawdown'),
# Distribution
('Distribution moments', 'Returns volatility'),
('Distribution moments', 'Returns skewness'),
('Distribution moments', 'Returns kurtosis'),
# Risk-adjusted return based on Volatility
('Risk-adjusted return based on Volatility', 'Treynor ratio'),
('Risk-adjusted return based on Volatility', 'Sharpe ratio'),
('Risk-adjusted return based on Volatility', 'Information ratio'),
# Risk-adjusted return based on Value at Risk
('Risk-adjusted return based on Value at Risk', 'VaR'),
('Risk-adjusted return based on Value at Risk',
'Expected Shortfall'),
('Risk-adjusted return based on Value at Risk', 'Excess var'),
('Risk-adjusted return based on Value at Risk',
'Conditional sharpe ratio'),
# Risk-adjusted return based on Lower Partial Moments
('Risk-adjusted return based on Lower Partial Moments',
'Omega ratio'),
('Risk-adjusted return based on Lower Partial Moments',
'Sortino ratio'),
('Risk-adjusted return based on Lower Partial Moments',
'Kappa three ratio'),
('Risk-adjusted return based on Lower Partial Moments',
'Gain loss ratio'),
('Risk-adjusted return based on Lower Partial Moments',
'Upside potential ratio'),
# Risk-adjusted return based on Drawdown
('Risk-adjusted return based on Drawdown', 'Calmar ratio')
]
fmt_pct = tf.FmtPercent(1,
rows=pct_rows,
apply_to_header_and_index=False)
fmt_dec = tf.FmtDecimals(2,
rows=dec_rows,
apply_to_header_and_index=False)
fmt_align = tf.FmtAlignTable("left")
fmt_background = tf.FmtStripeBackground(
first_color=tf.colors.LIGHT_GREY,
second_color=tf.colors.WHITE,
header_color=tf.colors.BLACK)
fmt_multiindex = tf.FmtExpandMultiIndex(operator=tf.OP_NONE)
perf_data = Block(self.InputList[2],
formatters=[
fmt_multiindex, fmt_pct, fmt_dec, fmt_align,
fmt_background
],
use_default_formatters=False)._repr_html_()
perf_data = {'performance_table': perf_data}
return perf_data