@@ -152,7 +152,6 @@ $$ (eq:apdb_sol)
152
152
153
153
Here is a small example, where the dividend stream is given by
154
154
155
- +++
156
155
157
156
```{code-cell} ipython3
158
157
T = 6
@@ -202,18 +201,80 @@ b = np.zeros(T+1)
202
201
b[-1] = δ * p_star
203
202
p = np.linalg.solve(A, d + b)
204
203
fig, ax = plt.subplots()
205
- ax.plot(p)
204
+ ax.plot(p, 'o', label='asset price')
205
+ ax.legend()
206
+ ax.set_xlabel('time')
206
207
plt.show()
207
208
```
208
209
209
- +++
210
210
211
+ We can also consider a cyclically growing dividend sequence, such as
212
+
213
+
214
+ ```{code-cell} ipython3
215
+ T = 100
216
+ current_d = 1.0
217
+ d = []
218
+ for t in range(T+1):
219
+ d.append(current_d)
220
+ current_d = current_d * 1.01 + 0.1 * np.sin(t)
221
+
222
+ fig, ax = plt.subplots()
223
+ ax.plot(d, 'o-', ms=4, alpha=0.8, label='dividends')
224
+ ax.legend()
225
+ ax.set_xlabel('time')
226
+ plt.show()
227
+ ```
228
+
229
+ ```{exercise-start}
230
+ :label: pv_ex_cyc
231
+ ```
232
+
233
+ Compute the corresponding asset price sequence when $p^*_{T+1} = 0$ and $\delta
234
+ = 0.98$.
235
+
236
+ ```{exercise-end}
237
+ ```
238
+
239
+ ```{solution-start} pv_ex_cyc
240
+ :class: dropdown
241
+ ```
242
+
243
+ We proceed as above after modifying parameters and $A$.
244
+
245
+ ```{code-cell} ipython3
246
+ δ = 0.98
247
+ p_star = 0.0
248
+ A = np.zeros((T+1, T+1))
249
+ for i in range(T+1):
250
+ for j in range(T+1):
251
+ if i == j:
252
+ A[i, j] = 1
253
+ if j < T:
254
+ A[i, j+1] = -δ
255
+
256
+ b = np.zeros(T+1)
257
+ b[-1] = δ * p_star
258
+ p = np.linalg.solve(A, d + b)
259
+ fig, ax = plt.subplots()
260
+ ax.plot(p, 'o-', ms=4, alpha=0.8, label='asset price')
261
+ ax.legend()
262
+ ax.set_xlabel('time')
263
+ plt.show()
264
+
265
+ ```
266
+
267
+ The weighted averaging associated with the present value calculation largely
268
+ eliminates the cycles.
269
+
270
+
271
+ ```{solution-end}
272
+ ```
211
273
212
274
## Analytical Expressions
213
275
214
276
It can be verified that the inverse of the matrix $A$ in {eq}`eq:pieq` is
215
277
216
- +++
217
278
218
279
$$ A^{-1} =
219
280
\begin{bmatrix}
323
384
p_t = c \delta^{-t}
324
385
$$ (eq:bubble)
325
386
326
- +++
327
387
328
388
## Gross rate of return
329
389
341
401
R_t = \delta^{-1} > 1 .
342
402
$$
343
403
344
- +++
345
404
346
- <!-- #endregion -->
405
+ ## Exercises
347
406
348
- ## Experiments
349
407
350
- We'll try various settings for $\vec d, p_{T+1}^*$:
408
+ ```{exercise-start}
409
+ :label: pv_ex_a
410
+ ```
351
411
352
- * $p_{T+1}^* = 0, d_t = g^t d_0$ to get a modified version of the Gordon growth formula
353
-
354
- * $p_{T+1}^* = g^{T+1} d_0, d_t = g^t d_0$ to get the plain vanilla Gordon growth formula
355
-
356
- * $p_{T+1}^* = 0, d_t = 0$ to get a worthless stock
357
-
358
- * $p_{T+1}^* = c \delta^{-(T+1)}, d_t = 0$ to get a bubble stock
412
+ Give analytical expressions for the asset price $p_t$ under the
413
+ following settings for $d$ and $p_{T+1}^*$:
414
+
415
+ 1. $p_{T+1}^* = 0, d_t = g^t d_0$ (a modified version of the Gordon growth formula)
416
+ 1. $p_{T+1}^* = g^{T+1} d_0, d_t = g^t d_0$ (the plain vanilla Gordon growth formula)
417
+ 1. $p_{T+1}^* = 0, d_t = 0$ (price of a worthless stock)
418
+ 1. $p_{T+1}^* = c \delta^{-(T+1)}, d_t = 0$ (price of a pure bubble stock)
419
+
420
+
421
+ ```{exercise-end}
422
+ ```
0 commit comments