def run_strategy_returns_stats(self, trading_model):
"""
run_strategy_returns_stats - Plots useful statistics for the trading strategy (using PyFolio)
Parameters
----------
trading_model : TradingModel
defining trading strategy
"""
pnl = trading_model.get_strategy_pnl()
tz = Timezone()
calculations = Calculations()
# PyFolio assumes UTC time based DataFrames (so force this localisation)
try:
pnl = tz.localise_index_as_UTC(pnl)
except:
pass
# set the matplotlib style sheet & defaults
# at present this only works in Matplotlib engine
try:
matplotlib.rcdefaults()
plt.style.use(
ChartConstants().chartfactory_style_sheet['chartpy-pyfolio'])
except:
pass
# TODO for intraday strategies, make daily
# convert DataFrame (assumed to have only one column) to Series
pnl = calculations.calculate_returns(pnl)
pnl = pnl.dropna()
pnl = pnl[pnl.columns[0]]
fig = pf.create_returns_tear_sheet(pnl, return_fig=True)
try:
plt.savefig(trading_model.DUMP_PATH + "stats.png")
except:
pass
plt.show()
def run_strategy_returns_stats(self,
trading_model,
index=None,
engine='finmarketpy'):
"""Plots useful statistics for the trading strategy using various backends
Parameters
----------
trading_model : TradingModel
defining trading strategy
engine : str
'pyfolio' - use PyFolio as a backend
'finmarketpy' - use finmarketpy as a backend
index: DataFrame
define strategy by a time series
"""
if index is None:
pnl = trading_model.strategy_pnl()
else:
pnl = index
tz = Timezone()
calculations = Calculations()
if engine == 'pyfolio':
# PyFolio assumes UTC time based DataFrames (so force this localisation)
try:
pnl = tz.localise_index_as_UTC(pnl)
except:
pass
# set the matplotlib style sheet & defaults
# at present this only works in Matplotlib engine
try:
matplotlib.rcdefaults()
plt.style.use(ChartConstants().
chartfactory_style_sheet['chartpy-pyfolio'])
except:
pass
# TODO for intraday strategies, make daily
# convert DataFrame (assumed to have only one column) to Series
pnl = calculations.calculate_returns(pnl)
pnl = pnl.dropna()
pnl = pnl[pnl.columns[0]]
fig = pf.create_returns_tear_sheet(pnl, return_fig=True)
try:
plt.savefig(trading_model.DUMP_PATH + "stats.png")
except:
pass
plt.show()
elif engine == 'finmarketpy':
# assume we have TradingModel
# to do to take in a time series
from chartpy import Canvas, Chart
# temporarily make scale factor smaller so fits the window
old_scale_factor = trading_model.SCALE_FACTOR
trading_model.SCALE_FACTOR = 0.75
pnl = trading_model.plot_strategy_pnl(
silent_plot=True) # plot the final strategy
individual = trading_model.plot_strategy_group_pnl_trades(
silent_plot=True) # plot the individual trade P&Ls
pnl_comp = trading_model.plot_strategy_group_benchmark_pnl(
silent_plot=True
) # plot all the cumulative P&Ls of each component
ir_comp = trading_model.plot_strategy_group_benchmark_pnl_ir(
silent_plot=True) # plot all the IR of each component
leverage = trading_model.plot_strategy_leverage(
silent_plot=True) # plot the leverage of the portfolio
ind_lev = trading_model.plot_strategy_group_leverage(
silent_plot=True) # plot all the individual leverages
canvas = Canvas([[pnl, individual], [pnl_comp, ir_comp],
[leverage, ind_lev]])
canvas.generate_canvas(
page_title=trading_model.FINAL_STRATEGY + ' Return Statistics',
silent_display=False,
canvas_plotter='plain',
output_filename=trading_model.FINAL_STRATEGY + ".html",
render_pdf=False)
trading_model.SCALE_FACTOR = old_scale_factor
def run_strategy_returns_stats(self, trading_model, index = None, engine = 'pyfolio'):
"""Plots useful statistics for the trading strategy (using PyFolio)
Parameters
----------
trading_model : TradingModel
defining trading strategy
index: DataFrame
define strategy by a time series
"""
if index is None:
pnl = trading_model.get_strategy_pnl()
else:
pnl = index
tz = Timezone()
calculations = Calculations()
if engine == 'pyfolio':
# PyFolio assumes UTC time based DataFrames (so force this localisation)
try:
pnl = tz.localise_index_as_UTC(pnl)
except: pass
# set the matplotlib style sheet & defaults
# at present this only works in Matplotlib engine
try:
matplotlib.rcdefaults()
plt.style.use(ChartConstants().chartfactory_style_sheet['chartpy-pyfolio'])
except: pass
# TODO for intraday strategies, make daily
# convert DataFrame (assumed to have only one column) to Series
pnl = calculations.calculate_returns(pnl)
pnl = pnl.dropna()
pnl = pnl[pnl.columns[0]]
fig = pf.create_returns_tear_sheet(pnl, return_fig=True)
try:
plt.savefig (trading_model.DUMP_PATH + "stats.png")
except: pass
plt.show()
elif engine == 'finmarketpy':
# assume we have TradingModel
# to do to take in a time series
from chartpy import Canvas, Chart
pnl = trading_model.plot_strategy_pnl(silent_plot=True) # plot the final strategy
individual = trading_model.plot_strategy_group_pnl_trades(silent_plot=True) # plot the individual trade P&Ls
pnl_comp = trading_model.plot_strategy_group_benchmark_pnl(silent_plot=True) # plot all the cumulative P&Ls of each component
ir_comp = trading_model.plot_strategy_group_benchmark_pnl_ir(silent_plot=True) # plot all the IR of each component
leverage = trading_model.plot_strategy_leverage(silent_plot=True) # plot the leverage of the portfolio
ind_lev = trading_model.plot_strategy_group_leverage(silent_plot=True) # plot all the individual leverages
canvas = Canvas([[pnl, individual],
[pnl_comp, ir_comp],
[leverage, ind_lev]]
)
canvas.generate_canvas(silent_display=False, canvas_plotter='plain')
