def plot_returns(self, contract_group: ContractGroup = None) -> Optional[Tuple[mpl.figure.Figure, mpl.axes.Axes]]:
'''Display plots of equity, drawdowns and returns for the given contract group or for all contract groups if contract_group
is None (default)'''
if contract_group is None:
returns = self.df_returns()
else:
returns = self.df_returns(contract_group)
ev = compute_return_metrics(returns.timestamp.values, returns.ret.values, self.account.starting_equity)
return plot_return_metrics(ev.metrics())
def plot(self, sampling_frequency = 'D', strategy_names = None):
'''Display plots of equity, drawdowns and returns
Args:
sampling_frequency: Date frequency. Default 'D' for daily so we downsample to daily returns before computing metrics
strategy_names: A list of strategy names. By default this is set to None and we use all strategies.
'''
returns = self.df_returns(sampling_frequency, strategy_names)
ev = compute_return_metrics(returns.index.values, returns.ret.values, returns.equity.values[0])
plot_return_metrics(ev.metrics())
def plot_returns(self, contract_group=None):
'''Display plots of equity, drawdowns and returns for the given contract group or for all contract groups if contract_group
is None (default)'''
if contract_group is None:
returns = self.df_returns()
else:
returns = self.df_returns(contract_group)
ev = compute_return_metrics(returns.timestamp.values,
returns.ret.values,
self.account.starting_equity)
fig, ax = plot_return_metrics(ev.metrics())
return fig, ax
def evaluate_returns(self, symbol=None, plot=True, float_precision=4):
'''Returns a dictionary of common return metrics.
Args:
symbol (str): Date frequency. Default 'D' for daily so we downsample to daily returns before computing metrics
plot (bool): If set to True, display plots of equity, drawdowns and returns. Default False
float_precision (float, optional): Number of significant figures to show in returns. Default 4
'''
returns = self.df_returns(symbol)
ev = compute_return_metrics(returns.index.values, returns.ret.values,
self.account.starting_equity)
display_return_metrics(ev.metrics(), float_precision=float_precision)
if plot: plot_return_metrics(ev.metrics())
return ev.metrics()
def evaluate_returns(self, sampling_frequency = 'D', strategy_names = None, plot = True, float_precision = 4):
'''Returns a dictionary of common return metrics.
Args:
sampling_frequency: Date frequency. Default 'D' for daily so we downsample to daily returns before computing metrics
strategy_names: A list of strategy names. By default this is set to None and we use all strategies.
plot: If set to True, display plots of equity, drawdowns and returns. Default False
float_precision: Number of significant figures to show in returns. Default 4
'''
returns = self.df_returns(sampling_freq, strategy_names)
ev = compute_return_metrics(returns.timestamp.values, returns.ret.values, returns.equity.values[0])
display_return_metrics(ev.metrics(), float_precision = float_precision)
if plot: plot_return_metrics(ev.metrics())
return ev.metrics()
def evaluate_returns(self, contract_group = None, plot = True, display_summary = True, float_precision = 4):
'''Returns a dictionary of common return metrics.
Args:
contract_group (:obj:`ContractGroup`, optional): Contract group to evaluate or None (default) for all contract groups
plot (bool): If set to True, display plots of equity, drawdowns and returns. Default False
float_precision (float, optional): Number of significant figures to show in returns. Default 4
'''
returns = self.df_returns(contract_group)
ev = compute_return_metrics(returns.timestamp.values, returns.ret.values, self.account.starting_equity)
if display_summary:
display_return_metrics(ev.metrics(), float_precision = float_precision)
if plot: plot_return_metrics(ev.metrics())
return ev.metrics()
def plot_returns(self, symbol=None):
'''Display plots of equity, drawdowns and returns for the given symbol or for all symbols if symbol is None (default)'''
if symbol is None:
symbols = self.symbols()
else:
symbols = [symbol]
df_list = []
for symbol in symbols:
df_list.append(self.df_returns(symbol))
df = pd.concat(df_list, axis=1)
ev = compute_return_metrics(returns.index.values, returns.ret.values,
self.account.starting_equity)
plot_return_metrics(ev.metrics())
def plot_returns(self, contract_group = None):
'''Display plots of equity, drawdowns and returns for the given contract group or for all contract groups if contract_group
is None (default)'''
if contract_group is None:
contract_groups = self.contract_groups()
else:
contract_groups = [contract_groups]
df_list = []
for contract_group in contract_groups:
df_list.append(self.df_returns(contract_group))
df = pd.concat(df_list, axis = 1)
ev = compute_return_metrics(returns.timestamp.values, returns.ret.values, self.account.starting_equity)
plot_return_metrics(ev.metrics())
