Derivation of the Variance of Autocorrelation

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SUMMARY

The discussion centers on the derivation of the variance of autocorrelation, specifically for a given lag, represented by the formula $$Var(r_k) = \frac{n-k}{n(n+2)}$$. The variables involved include $$r_k$$, the autocorrelation at lag k, $$n$$, the number of data points, and $$a_t$$, the error term. Participants seek assistance in proving this variance formula, which is foundational in time series analysis.

PREREQUISITES
  • Understanding of autocorrelation in time series analysis
  • Familiarity with variance calculations in statistics
  • Knowledge of error terms in statistical models
  • Basic proficiency in mathematical notation and formulas
NEXT STEPS
  • Research the derivation of the autocorrelation function in time series
  • Study the properties of variance in statistical analysis
  • Explore the implications of the Ljung-Box test for autocorrelation
  • Learn about finite sample adjustments in statistical estimators
USEFUL FOR

Statisticians, data analysts, and researchers involved in time series analysis who require a deeper understanding of autocorrelation and its variance.

mertcan
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Hi everyone in this link (https://stats.stackexchange.com/questions/226334/ljung-box-finite-sample-adjustments) I see the variance of autocorrelation related to specific lag is demonstrated in the following: $$ Var(r_k) = \frac {\sum_{t=k+1}^n a_t*a_{t-k}} {\sum_{t=1}^n a_t^2}$$ where ##r_k## is autocorrelation at relevant lag, ##n## is the number of data set and ##a_t## is error. Could help me prove the formula I mentioned above?
 
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mertcan said:
Hi everyone in this link (https://stats.stackexchange.com/questions/226334/ljung-box-finite-sample-adjustments) I see the variance of autocorrelation related to specific lag is demonstrated in the following: $$ Var(r_k) = \frac {\sum_{t=k+1}^n a_t*a_{t-k}} {\sum_{t=1}^n a_t^2}$$ where ##r_k## is autocorrelation at relevant lag, ##n## is the number of data set and ##a_t## is error. Could help me prove the formula I mentioned above?

Guys sorry for wrong question. Please let me rectify it.
I have seen the following formula whereas $$ r_k = \frac {\sum_{t=k+1}^n a_t*a_{t-k}} {\sum_{t=1}^n a_t^2}$$ $$Var(r_k) = \frac {n-k}{n*(n+2)}$$ where $r_k$ is the autocorrelation at relevant lag, $n$ is the number of points in the data set, and $a_t$ is the error.

I have searched the internet for the proof for variance equation, but I haven't found it. Could anyone help me prove the formula I mentioned above?
 

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