我有以下年度现金流量:
w=np.array([ -56501, -14918073, -1745198, -20887403, -9960686, -31076934,
0, 0, 11367846, 26736802, -2341940, 20853917,
22166416, 19214094, 23056582, -11227178, 18867100, 24947517,
28733869, 24707603, -17030396, 7753089, 27526723, 31534327,
26726270, -24607953, 11532035, 29444013, 24350595, 30140678,
-33262793, 5640172, 32846900, 38165710, 31655489, -74343373,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, -8727068])
我使用np.irr计算IRR
np.irr(w)
Out[141]: -0.05393588064654964
当我在Excel中使用IRR函数获得相同的现金流量时,我得到了12%。 这两个函数通常会产生相同的结果。有谁知道为什么在这种情况下结果如此不同?谢谢!
答案 0 :(得分:1)
对于给定的现金流量,内部收益率不是唯一的;参见Multiple IRRs。 r
的numpy和Excel值都满足NPV(r) = 0
,其中NPV是净现值。
以下是w
中数据的NPV(r)图。红星标记IRR值(其中NPV(r)为零)。
以下是生成绘图的脚本:
import numpy as np
import matplotlib.pyplot as plt
w = np.array([ -56501, -14918073, -1745198, -20887403, -9960686, -31076934,
0, 0, 11367846, 26736802, -2341940, 20853917,
22166416, 19214094, 23056582, -11227178, 18867100, 24947517,
28733869, 24707603, -17030396, 7753089, 27526723, 31534327,
26726270, -24607953, 11532035, 29444013, 24350595, 30140678,
-33262793, 5640172, 32846900, 38165710, 31655489, -74343373,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0,
0, -8727068])
r_excel = 0.1200963665
r_numpy = np.irr(w)
rr = np.linspace(-0.055, 0.16, 500)
npvals = np.array([np.npv(r, w) for r in rr])
plt.plot(rr, npvals/1e6, alpha=0.8)
plt.plot(r_numpy, 0, 'r*')
plt.plot(r_excel, 0, 'r*')
plt.grid(True)
plt.xlabel('r')
plt.ylabel('NPV(r) [millions]')
plt.show()