Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Jump to bottom

MAIN: Update tauchen API according to new change in PR-664 (Quantecon.py) #289

Closed
wants to merge 1 commit into from
Closed

MAIN: Update tauchen API according to new change in PR-664 (Quantecon.py) #289

Changes from all commits
Commits
Show all changes
1 commit
Select commit
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
8 changes: 4 additions & 4 deletions lectures/markov_asset.md
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -53,7 +53,7 @@ An asset is a claim on one or more future payoffs.

The spot price of an asset depends primarily on

* the anticipated income stream
* the anticipated income stream
* attitudes about risk
* rates of time preference

Expand Down Expand Up @@ -313,7 +313,7 @@ The next figure shows a simulation, where
* $g_t = \exp(X_t)$, so that $\ln g_t = X_t$ is the growth rate.

```{code-cell} ipython
mc = qe.tauchen(0.96, 0.25, n=25)
mc = qe.tauchen(n, 0.96, 0.25)
sim_length = 80

x_series = mc.simulate(sim_length, init=np.median(mc.state_values))
Expand Down Expand Up @@ -404,7 +404,7 @@ Here's the code, including a test of the spectral radius condition
```{code-cell} python3
n = 25 # Size of state space
β = 0.9
mc = qe.tauchen(0.96, 0.02, n=n)
mc = qe.tauchen(n, 0.96, 0.02)

K = mc.P * np.exp(mc.state_values)

Expand Down Expand Up @@ -566,7 +566,7 @@ class AssetPriceModel:
if mc is None:
self.ρ = 0.9
self.σ = 0.02
self.mc = qe.tauchen(self.ρ, self.σ, n=25)
self.mc = qe.tauchen(n, self.ρ, self.σ)
else:
self.mc = mc

Expand Down