Hi,

1. I want to estimate my risk measures using bi-variate diagonal GARCH (1,1) model (DVECH) for each of my 360 panels in the data(from a time period of 20 years). when I simply run my code, the error I get is that "sample may not include multiple panels". Could someone help me devise foreach code to extract coeffs, constants, t stat and p values.

Also, exactly what I need to do is as below:

"We begin by outlining a simple Gaussian framework under which risk measure(to be estimated) has a closed-form expression, and then present the estimation results. The Gaussian framework is a special case of the stylized financial system (X variable) with deterministic mean and covariance terms, and jointly normally distributed latent shock processes. In the Gaussian framework, risk measure is thus pinned down by three determinants: the correlation, the volatility of the financial system, and the Gaussian quantile"

2. My variables data is not normally distributed, what techniques I shall consider to normalize it for GARCH modelling? The assumption is that both the Y and X variable follow a bi-variate normal distribution.

1. I want to estimate my risk measures using bi-variate diagonal GARCH (1,1) model (DVECH) for each of my 360 panels in the data(from a time period of 20 years). when I simply run my code, the error I get is that "sample may not include multiple panels". Could someone help me devise foreach code to extract coeffs, constants, t stat and p values.

Also, exactly what I need to do is as below:

"We begin by outlining a simple Gaussian framework under which risk measure(to be estimated) has a closed-form expression, and then present the estimation results. The Gaussian framework is a special case of the stylized financial system (X variable) with deterministic mean and covariance terms, and jointly normally distributed latent shock processes. In the Gaussian framework, risk measure is thus pinned down by three determinants: the correlation, the volatility of the financial system, and the Gaussian quantile"

2. My variables data is not normally distributed, what techniques I shall consider to normalize it for GARCH modelling? The assumption is that both the Y and X variable follow a bi-variate normal distribution.

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