def __init__(self, t="19-04-2020", r=0.05, S_t=90.0, sigma=0.2):
print("Initializing the MarketEnvironment!")
self.__t = date_string_to_datetime_obj(t)
self.__r = r
self.__S = S_t
self.__sigma = sigma
def main():
# Calendar-Spread implementation example
# default market environment
market_env = MarketEnvironment()
print(market_env)
# options expirations
T_short = "31-05-2020"
T_long = "30-08-2020"
# current underlying level
S_t = market_env.get_S()
# calendar-spread portfolio initialized (as empty portfolio)
calendar_spread_ptf = Portfolio(name="Calendar Spread Strategy")
print(calendar_spread_ptf)
# T_long-call
Vanilla_Call_long = PlainVanillaOption(market_env, T=T_long, K=S_t)
print(Vanilla_Call_long)
# T_short-call
Vanilla_Call_short = PlainVanillaOption(market_env, T=T_short, K=S_t)
print(Vanilla_Call_short)
# creation of Calendar-Spread portfolio strategy
calendar_spread_ptf.add_instrument(Vanilla_Call_long, 1)
calendar_spread_ptf.add_instrument(Vanilla_Call_short, -1)
print(calendar_spread_ptf)
# portfolio plotter instance
calendar_spread_ptf_plotter = PortfolioPlotter(calendar_spread_ptf)
# valuation date of the portfolio
valuation_date = calendar_spread_ptf.get_t()
print(valuation_date)
# select dependency to plot as x-axis of the plot
for dependency_type in ["S", "K", "sigma", "r"]:
# keyboard parameter and corresponding range to test
x_axis_dict = options_x_axis_parameters_factory(calendar_spread_ptf, dependency_type)
# appropriate azimut angle for best viewing
azimut_angle = get_azimut_angle(dependency_type)
# select metrics to plot
for plot_metrics in ["price", "PnL", "delta", "theta", "gamma", "vega", "rho"]:
plot_details_flag = True if plot_metrics == "price" else False
# time-parameter as a date-range of 5 valuation dates between t and T_short
last_date = T_short if plot_metrics in ["price", "PnL"] else date_string_to_datetime_obj(T_short) - pd.Timedelta(days=1)
multiple_valuation_dates = pd.date_range(start=valuation_date,
end=last_date,
periods=5)
print(multiple_valuation_dates)
# Bull-Spread price plot
calendar_spread_ptf_plotter.plot(**x_axis_dict, t=last_date, plot_metrics=plot_metrics,
plot_details=plot_details_flag)
# Plot at multiple dates
calendar_spread_ptf_plotter.plot(**x_axis_dict, t=multiple_valuation_dates, plot_metrics=plot_metrics)
# Surface plot
calendar_spread_ptf_plotter.plot(**x_axis_dict, t=multiple_valuation_dates,
plot_metrics=plot_metrics, surf_plot=True)
# Surface plot (rotate) - Underlying value side
calendar_spread_ptf_plotter.plot(**x_axis_dict, t=multiple_valuation_dates,
plot_metrics=plot_metrics, surf_plot=True,
view=(0,azimut_angle["x-axis side"]))
# Price surface plot (rotate) - Date side
calendar_spread_ptf_plotter.plot(**x_axis_dict, t=multiple_valuation_dates,
plot_metrics=plot_metrics, surf_plot=True,
view=(0,azimut_angle["Date side"]))
def main():
# Calendar-Spread implementation example
# default market environment
market_env = MarketEnvironment()
print(market_env)
# options expirations
T_short = "31-05-2020"
T_long = "30-08-2020"
# current underlying level
S_t = market_env.get_S()
# calendar-spread portfolio initialized (as empty portfolio)
calendar_spread_ptf = Portfolio(name="Calendar Spread Strategy")
print(calendar_spread_ptf)
# T_long-call
Vanilla_Call_long = PlainVanillaOption(market_env, T=T_long, K=S_t)
print(Vanilla_Call_long)
# T_short-call
Vanilla_Call_short = PlainVanillaOption(market_env, T=T_short, K=S_t)
print(Vanilla_Call_short)
# creation of Calendar-Spread portfolio strategy
calendar_spread_ptf.add_instrument(Vanilla_Call_long, 1)
calendar_spread_ptf.add_instrument(Vanilla_Call_short, -1)
print(calendar_spread_ptf)
# portfolio plotter instance
calendar_spread_ptf_plotter = PortfolioPlotter(calendar_spread_ptf)
# valuation date of the portfolio
valuation_date = calendar_spread_ptf.get_t()
print(valuation_date)
# select metrics to plot
for plot_metrics in ["price", "PnL", "delta", "theta", "gamma", "vega", "rho"]:
plot_details_flag = True if plot_metrics == "price" else False
# time-parameter as a date-range of 5 valuation dates between t and T_short
# being the Calendar-Spread a multi-horizon portfolio, time-to-maturity
# time parameters are not allowed.
last_date = T_short if plot_metrics in ["price", "PnL"] else date_string_to_datetime_obj(T_short) - pd.Timedelta(days=1)
multiple_valuation_dates = pd.date_range(start=valuation_date,
end=last_date,
periods=5)
print(multiple_valuation_dates)
# Bull-Spread price plot
calendar_spread_ptf_plotter.plot(t=last_date, plot_metrics=plot_metrics,
plot_details=plot_details_flag)
# Plot at multiple dates
calendar_spread_ptf_plotter.plot(t=multiple_valuation_dates, plot_metrics=plot_metrics)
# Surface plot
calendar_spread_ptf_plotter.plot(t=multiple_valuation_dates, plot_metrics=plot_metrics,
surf_plot=True)
# Surface plot (rotate) - Underlying value side
calendar_spread_ptf_plotter.plot(t=multiple_valuation_dates, plot_metrics=plot_metrics,
surf_plot=True, view=(0,180))
# Price surface plot (rotate) - Date side
calendar_spread_ptf_plotter.plot(t=multiple_valuation_dates, plot_metrics=plot_metrics,
surf_plot=True, view=(0,-90))
def set_t(self, t):
self.__t = date_string_to_datetime_obj(t)