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If you are interested in finding out non correlated sequence/items in your time series , why don't u just apply ACF/PACT to find out lagged number (p). And then, I reckon, this p +1 would be your n, as there won't be much autocorrelation between these items.


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My answer is based on the fact that the above equations corresponds to the provided STATA code and output. Thus, I disregard my own questions in the comments below the post. Consider bounding your GJR-GARCH parameters: You need to bound your parameters in order to ensure positivity (positive estimates) and covariance stationarity. I will disregard the mean-...


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As far as I know we use Normalization in reviewing the Financial Statements(PnL,Balance Sheets,Cash Flow) of a Company. Now What is that exactly? If the company is seeking external funding, normalized financial statements provide the investor or lender with a clear picture of the actual expenses, revenues, earnings and cash flow of the company during a ...


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ADF tests for a unit root. Autocorrelation function of a unit root process does not make sense. For example let $$y_{t+1}=y_t+\epsilon_{t+1}$$ Here $\epsilon_t$ is i.i.d white noise. Then the one period autocovariance is $$Cov(y_{t+1},y_{t})=Cov(y_t+\epsilon_{t+1},y_{t})=Var(y_t)$$ For a unit root process $Var(y_t) \rightarrow \infty$ as $t\rightarrow \infty$...


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You will not be able to replicate positive decaying autocorrelations in current markets: Due to the increased popularity in high-frequency trading, there's been a likewise increased focus on studying the underlying empirical properties of high-frequency data. One of the stylized facts in high-frequency data is the significant first-order negative ...


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