def main():
S = np.arange(80, 121)
Sl = 0
Su = 200
N = 128 * T
K = 8 * (Su - Sl)
Sk = K * (S - Sl) / (Su - Sl)
model1 = FDEModel(N, dS_total, payoff)
model2 = FDEModel(N, dS, payoff)
A.R = 1.0
plt.plot(S, model1.price(Sl, Su, K).V[0][Sk])
plt.plot(S, model2.price(Sl, Su, K).V[0][Sk])
A.R = 0.5
plt.plot(S, model1.price(Sl, Su, K).V[0][Sk])
A.R = 0.0
plt.plot(S, model1.price(Sl, Su, K).V[0][Sk])
plt.ylim(100, 150)
plt.xlabel("Stock Price")
plt.ylabel("Convertible Bond Price")
plt.legend([
"Total default (R=100%)", "No default", "Total default (R=50%)",
"Total default (R=0%)"
],
loc=2)
if __name__ == "__main__":
plotmain(main)
from convertible_bond import dS_total as dS, payoff, C, T
from model import FDEModel
from plot import plotmain
def main():
S = np.linspace(0, 200, 200 * 8 + 1)
Sl = 0
Su = 250
N = 128 * T
K = 8 * (Su - Sl)
Sk = (K * (S - Sl) / (Su - Sl)).astype(int)
legend = []
label = "$\\Omega^c = \\{%i\\}$"
model = FDEModel(N, dS, payoff)
fig = plt.figure()
ax = fig.add_subplot(111)
for i in range(1, 5):
C.times = [i]
ax.plot(S, model.price(Sl, Su, K).V[0][Sk])
legend.append(label % i)
plt.xlabel("Stock Price")
plt.ylabel("Convertible Bond Price")
plt.legend(legend)
if __name__ == "__main__":
plotmain(main)
