Esempi in Python per LSS

Esempio n. 1

File: solution_lss_ex2.py Progetto: 1simon/quant-econ

import numpy as np
import matplotlib.pyplot as plt
from lss import LSS

phi_1, phi_2, phi_3, phi_4 = 0.5, -0.2, 0, 0.5
sigma = 0.2

A = [[phi_1, phi_2, phi_3, phi_4],
     [1,     0,     0,     0],
     [0,     1,     0,     0],
     [0,     0,     1,     0]]
C = [sigma, 0, 0, 0]
G = [1, 0, 0, 0]

ar = LSS(A, C, G, mu_0=np.ones(4))
x, y = ar.simulate(ts_length=200)

fig, ax = plt.subplots(figsize=(8, 4.6))
y = y.flatten()
ax.plot(y, 'b-', lw=2, alpha=0.7)
ax.grid()
ax.set_xlabel('time')
ax.set_ylabel(r'$y_t$', fontsize=16)
plt.show()

Esempio n. 2

File: paths_and_stationarity.py Progetto: LechPi/quant-econ

phi_1, phi_2, phi_3, phi_4 = 0.5, -0.2, 0, 0.5
sigma = 0.1

A = [[phi_1, phi_2, phi_3, phi_4],
     [1,     0,     0,     0],
     [0,     1,     0,     0],
     [0,     0,     1,     0]]
C = [sigma, 0, 0, 0]
G = [1, 0, 0, 0]

T0 = 10
T1 = 50
T2 = 75
T4 = 100

ar = LSS(A, C, G, mu_0=np.ones(4))
ymin, ymax = -0.8, 1.25

fig, ax = plt.subplots(figsize=(8, 5))

ax.grid(alpha=0.4)
ax.set_ylim(ymin, ymax)
ax.set_ylabel(r'$y_t$', fontsize=16)
ax.vlines((T0, T1, T2), -1.5, 1.5)

ax.set_xticks((T0, T1, T2))
ax.set_xticklabels((r"$T$", r"$T'$", r"$T''$"), fontsize=14)

sample = []
for i in range(80):
    rcolor = random.choice(('c', 'g', 'b'))

Esempio n. 3

File: solution_lss_ex2.py Progetto: dschippers/quant-econ-1

import numpy as np
import matplotlib.pyplot as plt
from lss import LSS

phi_1, phi_2, phi_3, phi_4 = 0.5, -0.2, 0, 0.5
sigma = 0.2

A = [[phi_1, phi_2, phi_3, phi_4], [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]]
C = [[sigma], [0], [0], [0]]
G = [1, 0, 0, 0]

ar = LSS(A, C, G, mu_0=np.ones(4))
x, y = ar.simulate(ts_length=200)

fig, ax = plt.subplots(figsize=(8, 4.6))
y = y.flatten()
ax.plot(y, 'b-', lw=2, alpha=0.7)
ax.grid()
ax.set_xlabel('time')
ax.set_ylabel(r'$y_t$', fontsize=16)
plt.show()

Esempio n. 4

import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm
from lss import LSS
import random

phi_1, phi_2, phi_3, phi_4 = 0.5, -0.2, 0, 0.5
sigma = 0.1

A = [[phi_1, phi_2, phi_3, phi_4], [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]]
C = [[sigma], [0], [0], [0]]
G = [1, 0, 0, 0]

I = 20
T = 50
ar = LSS(A, C, G, mu_0=np.ones(4))
ymin, ymax = -0.5, 1.15

fig, ax = plt.subplots()

ax.set_ylim(ymin, ymax)
ax.set_xlabel(r'time', fontsize=16)
ax.set_ylabel(r'$y_t$', fontsize=16)

ensemble_mean = np.zeros(T)
for i in range(I):
    x, y = ar.simulate(ts_length=T)
    y = y.flatten()
    ax.plot(y, 'c-', lw=0.8, alpha=0.5)
    ensemble_mean = ensemble_mean + y

Esempio n. 5

File: solution_lss_ex4.py Progetto: 1simon/quant-econ

phi_1, phi_2, phi_3, phi_4 = 0.5, -0.2, 0, 0.5
sigma = 0.1

A = [[phi_1, phi_2, phi_3, phi_4],
     [1,     0,     0,     0],
     [0,     1,     0,     0],
     [0,     0,     1,     0]]
C = [sigma, 0, 0, 0]
G = [1, 0, 0, 0]

T0 = 10
T1 = 50
T2 = 75
T4 = 100

ar = LSS(A, C, G, mu_0=np.ones(4))
ymin, ymax = -0.8, 1.0

fig, ax = plt.subplots(figsize=(8, 5))

ax.grid(alpha=0.4)
ax.set_ylim(ymin, ymax)
ax.set_ylabel(r'$y_t$', fontsize=16)
ax.vlines((T0, T1, T2), -1.5, 1.5)

ax.set_xticks((T0, T1, T2))
ax.set_xticklabels((r"$T$", r"$T'$", r"$T''$"), fontsize=14)

mu_x, mu_y, Sigma_x, Sigma_y = ar.stationary_distributions()
ar.mu_0 = mu_x
ar.Sigma_0 = Sigma_x

Esempio n. 6

File: tsh_hg.py Progetto: equihuam/quant-econ

from scipy.stats import norm
from lss import LSS
import random

phi_1, phi_2, phi_3, phi_4 = 0.5, -0.2, 0, 0.5
sigma = 0.1

A = [[phi_1, phi_2, phi_3, phi_4],
     [1,     0,     0,     0],
     [0,     1,     0,     0],
     [0,     0,     1,     0]]
C = [sigma, 0, 0, 0]
G = [1, 0, 0, 0]

T = 30
ar = LSS(A, C, G)

ymin, ymax = -0.8, 1.25

fig, ax = plt.subplots(figsize=(8,4))

ax.set_xlim(ymin, ymax)
ax.set_xlabel(r'$y_t$', fontsize=16)

x, y = ar.replicate(T=T, num_reps=500000, mu_0=np.ones(4))
mu_x, mu_y, Sigma_x, Sigma_y = ar.moments(T=T, mu_0=np.ones(4))
f_y = norm(loc=float(mu_y), scale=float(np.sqrt(Sigma_y)))

y = y.flatten()
ax.hist(y, bins=50, normed=True, alpha=0.4)

Esempio n. 7

File: solution_lss_ex3.py Progetto: 1simon/quant-econ

from lss import LSS
import random

phi_1, phi_2, phi_3, phi_4 = 0.5, -0.2, 0, 0.5
sigma = 0.1

A = [[phi_1, phi_2, phi_3, phi_4],
     [1,     0,     0,     0],
     [0,     1,     0,     0],
     [0,     0,     1,     0]]
C = [sigma, 0, 0, 0]
G = [1, 0, 0, 0]

I = 20
T = 50
ar = LSS(A, C, G, mu_0=np.ones(4))
ymin, ymax = -0.5, 1.15

fig, ax = plt.subplots()

ax.set_ylim(ymin, ymax)
ax.set_xlabel(r'time', fontsize=16)
ax.set_ylabel(r'$y_t$', fontsize=16)

ensemble_mean = np.zeros(T)
for i in range(I):
    x, y = ar.simulate(ts_length=T)
    y = y.flatten()
    ax.plot(y, 'c-', lw=0.8, alpha=0.5)
    ensemble_mean = ensemble_mean + y

Esempio n. 8

File: solution_lss_ex4.py Progetto: xiaohr/quant-econ

from lss import LSS
import random

phi_1, phi_2, phi_3, phi_4 = 0.5, -0.2, 0, 0.5
sigma = 0.1

A = [[phi_1, phi_2, phi_3, phi_4], [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]]
C = [sigma, 0, 0, 0]
G = [1, 0, 0, 0]

T0 = 10
T1 = 50
T2 = 75
T4 = 100

ar = LSS(A, C, G, mu_0=np.ones(4))
ymin, ymax = -0.8, 1.0

fig, ax = plt.subplots(figsize=(8, 5))

ax.grid(alpha=0.4)
ax.set_ylim(ymin, ymax)
ax.set_ylabel(r'$y_t$', fontsize=16)
ax.vlines((T0, T1, T2), -1.5, 1.5)

ax.set_xticks((T0, T1, T2))
ax.set_xticklabels((r"$T$", r"$T'$", r"$T''$"), fontsize=14)

mu_x, mu_y, Sigma_x, Sigma_y = ar.stationary_distributions()
ar.mu_0 = mu_x
ar.Sigma_0 = Sigma_x

Esempio n. 9

File: tsh_hg.py Progetto: koustuv26/quant-econ

import numpy as np
import matplotlib.pyplot as plt
from scipy.stats import norm
from lss import LSS
import random

phi_1, phi_2, phi_3, phi_4 = 0.5, -0.2, 0, 0.5
sigma = 0.1

A = [[phi_1, phi_2, phi_3, phi_4], [1, 0, 0, 0], [0, 1, 0, 0], [0, 0, 1, 0]]
C = [sigma, 0, 0, 0]
G = [1, 0, 0, 0]

T = 30
ar = LSS(A, C, G)

ymin, ymax = -0.8, 1.25

fig, ax = plt.subplots(figsize=(8, 4))

ax.set_xlim(ymin, ymax)
ax.set_xlabel(r"$y_t$", fontsize=16)

x, y = ar.replicate(T=T, num_reps=500000, mu_0=np.ones(4))
mu_x, mu_y, Sigma_x, Sigma_y = ar.moments(T=T, mu_0=np.ones(4))
f_y = norm(loc=float(mu_y), scale=float(np.sqrt(Sigma_y)))

y = y.flatten()
ax.hist(y, bins=50, normed=True, alpha=0.4)

ygrid = np.linspace(ymin, ymax, 150)

Esempio n. 10

import numpy as np
import matplotlib.pyplot as plt
from lss import LSS

phi_0, phi_1, phi_2 = 1.1, 0.8, -0.8

A = [[1, 0, 0], [phi_0, phi_1, phi_2], [0, 1, 0]]
C = np.zeros((3, 1))
G = [0, 1, 0]

ar = LSS(A, C, G, mu_0=np.ones(3))
x, y = ar.simulate(ts_length=50)

fig, ax = plt.subplots(figsize=(8, 4.6))
y = y.flatten()
ax.plot(y, 'b-', lw=2, alpha=0.7)
ax.grid()
ax.set_xlabel('time')
ax.set_ylabel(r'$y_t$', fontsize=16)
plt.show()