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Change iid to IID in heavy_tails.rst and kesten_processes.rst #788

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2 changes: 1 addition & 1 deletion source/rst/heavy_tails.rst
Original file line number Diff line number Diff line change
Expand Up @@ -172,7 +172,7 @@ One impact of heavy tails is that sample averages can be poor estimators of
the underlying mean of the distribution.

To understand this point better, recall :doc:`our earlier discussion
<lln_clt>` of the Law of Large Numbers, which considered iid :math:`X_1,
<lln_clt>` of the Law of Large Numbers, which considered IID :math:`X_1,
\ldots, X_n` with common distribution :math:`F`

If :math:`\mathbb E |X_i|` is finite, then
Expand Down
16 changes: 8 additions & 8 deletions source/rst/kesten_processes.rst
Original file line number Diff line number Diff line change
Expand Up @@ -63,7 +63,7 @@ A **Kesten process** is a stochastic process of the form
x_{t+1} = a_{t+1} x_t + \eta_{t+1}
\quad \text{with } x_0 \text{ given}

where :math:`\{a_t\}_{t \geq 1}` and :math:`\{\eta_t\}_{t \geq 1}` are iid
where :math:`\{a_t\}_{t \geq 1}` and :math:`\{\eta_t\}_{t \geq 1}` are IID
sequences.

We will focus on the nonnegative scalar case, where :math:`x_t` takes values
Expand All @@ -73,9 +73,9 @@ In particular, we will assume that

* the initial condition :math:`x_0` is nonnegative,

* :math:`\{a_t\}_{t \geq 1}` is a nonnegative iid stochastic process and
* :math:`\{a_t\}_{t \geq 1}` is a nonnegative IID stochastic process and

* :math:`\{\eta_t\}_{t \geq 1}` is another nonnegative iid stochastic process, independent of the first.
* :math:`\{\eta_t\}_{t \geq 1}` is another nonnegative IID stochastic process, independent of the first.



Expand Down Expand Up @@ -122,7 +122,7 @@ The GARCH(1, 1) volatility process takes the form

\sigma_{t+1}^2 = \alpha_0 + \sigma_t^2 (\alpha_1 \xi_{t+1}^2 + \beta)

where :math:`\{\xi_t\}` is iid with :math:`\mathbb E \xi_t^2 = 1` and all parameters are positive.
where :math:`\{\xi_t\}` is IID with :math:`\mathbb E \xi_t^2 = 1` and all parameters are positive.

Returns on a given asset are then modeled as

Expand All @@ -131,7 +131,7 @@ Returns on a given asset are then modeled as

r_t = \sigma_t \zeta_{t+1}

where :math:`\{\zeta_t\}` is again iid and independent of :math:`\{\xi_t\}`.
where :math:`\{\zeta_t\}` is again IID and independent of :math:`\{\xi_t\}`.

Notice that the volatility sequence :math:`\{\sigma_t\}`, which drives the dynamics, is a Kesten process.

Expand All @@ -152,7 +152,7 @@ Wealth then evolves according to

where :math:`\{R_t\}` is the gross rate of return on assets.

If :math:`\{R_t\}` and :math:`\{y_t\}` are both iid, then :eq:`wealth_dynam`
If :math:`\{R_t\}` and :math:`\{y_t\}` are both IID, then :eq:`wealth_dynam`
is a Kesten process.


Expand Down Expand Up @@ -386,7 +386,7 @@ We can express this idea by stating that a suitably defined measure

\frac{s_{t+1}}{s_t} = a_{t+1}

for some positive iid sequence :math:`\{a_t\}`.
for some positive IID sequence :math:`\{a_t\}`.

One implication of Gibrat's law is that the growth rate of individual firms
does not depend on their size.
Expand All @@ -413,7 +413,7 @@ to
s_{t+1} = a_{t+1} s_t + b_{t+1}


where :math:`\{a_t\}` and :math:`\{b_t\}` are both iid and independent of each
where :math:`\{a_t\}` and :math:`\{b_t\}` are both IID and independent of each
other.

In the exercises you are asked to show that :eq:`firm_dynam` is more
Expand Down