def basic(returns,
benchmark=None,
rf=0.,
grayscale=False,
figsize=(8, 5),
display=True):
if _utils._in_notebook():
iDisplay(iHTML('<h4>Performance Metrics</h4>'))
metrics(returns=returns,
benchmark=benchmark,
rf=rf,
display=display,
mode='basic')
iDisplay(iHTML('<h4>Strategy Visualization</h4>'))
else:
print('[Performance Metrics]\n')
metrics(returns=returns,
benchmark=benchmark,
rf=rf,
display=display,
mode='basic')
print('\n\n')
print('[Strategy Visualization]\nvia Matplotlib')
plots(returns=returns,
benchmark=benchmark,
grayscale=grayscale,
figsize=figsize,
mode='basic')
def _open_html(html):
jscode = _regex.sub(' +', ' ', """<script>
var win=window.open();win.document.body.innerHTML='{{html}}';
</script>""".replace('\n', ''))
jscode = jscode.replace('{{html}}', _regex.sub(
' +', ' ', html.replace('\n', '')))
if _utils._in_notebook():
iDisplay(iHTML(jscode))
def _download_html(html, filename="quantstats-tearsheet.html"):
jscode = _regex.sub(' +', ' ', """<script>
var bl=new Blob(['{{html}}'],{type:"text/html"});
var a=document.createElement("a");
a.href=URL.createObjectURL(bl);
a.download="{{filename}}";
a.hidden=true;document.body.appendChild(a);
a.innerHTML="download report";
a.click();</script>""".replace('\n', ''))
jscode = jscode.replace('{{html}}', _regex.sub(
' +', ' ', html.replace('\n', '')))
if _utils._in_notebook():
iDisplay(iHTML(jscode.replace('{{filename}}', filename)))
def full(returns,
benchmark=None,
rf=0.,
grayscale=False,
figsize=(8, 5),
display=True,
compounded=True):
dd = _stats.to_drawdown_series(returns)
dd_info = _stats.drawdown_details(dd).sort_values(by='max drawdown',
ascending=True)[:5]
dd_info.index = range(1, 6)
dd_info.columns = map(lambda x: str(x).title(), dd_info.columns)
if _utils._in_notebook():
iDisplay(iHTML('<h4>Performance Metrics</h4>'))
iDisplay(
metrics(returns=returns,
benchmark=benchmark,
rf=rf,
display=display,
mode='full',
compounded=compounded))
iDisplay(iHTML('<h4>5 Worst Drawdowns</h4>'))
iDisplay(dd_info)
iDisplay(iHTML('<h4>Strategy Visualization</h4>'))
else:
print('[Performance Metrics]\n')
metrics(returns=returns,
benchmark=benchmark,
rf=rf,
display=display,
mode='full',
compounded=compounded)
print('\n\n')
print('[5 Worst Drawdowns]\n')
print(
_tabulate(dd_info,
headers="keys",
tablefmt='simple',
floatfmt=".2f"))
print('\n\n')
print('[Strategy Visualization]\nvia Matplotlib')
plots(returns=returns,
benchmark=benchmark,
grayscale=grayscale,
figsize=figsize,
mode='full')
def basic(returns,
benchmark=None,
rf=0.,
grayscale=False,
figsize=(8, 5),
display=True,
compounded=True,
periods_per_year=252,
match_dates=False):
# prepare timeseries
returns = _utils._prepare_returns(returns)
if benchmark is not None:
benchmark = _utils._prepare_benchmark(benchmark, returns.index, rf)
if match_dates is True:
returns, benchmark = _match_dates(returns, benchmark)
if _utils._in_notebook():
iDisplay(iHTML('<h4>Performance Metrics</h4>'))
metrics(returns=returns,
benchmark=benchmark,
rf=rf,
display=display,
mode='basic',
compounded=compounded,
periods_per_year=periods_per_year,
prepare_returns=False)
iDisplay(iHTML('<h4>Strategy Visualization</h4>'))
else:
print('[Performance Metrics]\n')
metrics(returns=returns,
benchmark=benchmark,
rf=rf,
display=display,
mode='basic',
compounded=compounded,
periods_per_year=periods_per_year,
prepare_returns=False)
print('\n\n')
print('[Strategy Visualization]\nvia Matplotlib')
plots(returns=returns,
benchmark=benchmark,
grayscale=grayscale,
figsize=figsize,
mode='basic',
periods_per_year=periods_per_year,
prepare_returns=False)
def full(returns,
benchmark=None,
rf=0.,
grayscale=False,
figsize=(8, 5),
display=True,
compounded=True,
periods_per_year=252,
match_dates=False):
# prepare timeseries
returns = _utils._prepare_returns(returns)
if benchmark is not None:
benchmark = _utils._prepare_benchmark(benchmark, returns.index, rf)
if match_dates is True:
returns, benchmark = _match_dates(returns, benchmark)
dd = _stats.to_drawdown_series(returns)
dd_info = _stats.drawdown_details(dd).sort_values(by='max drawdown',
ascending=True)[:5]
if not dd_info.empty:
dd_info.index = range(1, min(6, len(dd_info) + 1))
dd_info.columns = map(lambda x: str(x).title(), dd_info.columns)
if _utils._in_notebook():
iDisplay(iHTML('<h4>Performance Metrics</h4>'))
iDisplay(
metrics(returns=returns,
benchmark=benchmark,
rf=rf,
display=display,
mode='full',
compounded=compounded,
periods_per_year=periods_per_year,
prepare_returns=False))
iDisplay(iHTML('<h4>5 Worst Drawdowns</h4>'))
if dd_info.empty:
iDisplay(iHTML("<p>(no drawdowns)</p>"))
else:
iDisplay(dd_info)
iDisplay(iHTML('<h4>Strategy Visualization</h4>'))
else:
print('[Performance Metrics]\n')
metrics(returns=returns,
benchmark=benchmark,
rf=rf,
display=display,
mode='full',
compounded=compounded,
periods_per_year=periods_per_year,
prepare_returns=False)
print('\n\n')
print('[5 Worst Drawdowns]\n')
if dd_info.empty:
print("(no drawdowns)")
else:
print(
_tabulate(dd_info,
headers="keys",
tablefmt='simple',
floatfmt=".2f"))
print('\n\n')
print('[Strategy Visualization]\nvia Matplotlib')
plots(returns=returns,
benchmark=benchmark,
grayscale=grayscale,
figsize=figsize,
mode='full',
periods_per_year=periods_per_year,
prepare_returns=False)