3 - Intro to Stochastic Processes

Question 1

What is the statistical answer to quantify uncertainty?

Answer 1

The statistical answer to quantify uncertainty around estimates and forecasts is probability.

Question 2

How do we define a discrete time stochastic process?

Answer 2

Question 3

What is a stochastic process? How does it become a time series? How can the time series be?

Answer 3

Question 4

Differenza tra Yt e yt

Answer 4

Question 5

What does it mean to assume a statistical model for a time series Yt?

Answer 5

Question 6

But what if the events refere to the entire path? Meaning that it’s not for example from time 1 to time 10, but from -∞ to +∞. How do we assign the probabilities in this case?

Answer 6

Question 7

How is the joint distribution in the basic setting (random sampling)? And wy this is not good in time series?

Answer 7

Question 8

What models will we use for taking into account the temporal dependece?

Answer 8

Question 9

What is a White noise? And why may it be interesting? And a Gaussian white noise?

Answer 9

Question 10

Summaries for time series?

Answer 10

Question 11

Definizione di Strict stationarity

Answer 11

Question 12

Definizione Second order stationarity

Answer 12

Question 13

Gaussian process

Answer 13

Question 14

Gaussian white noise

Answer 14