# How to estimate CAViaR (Engle and Manganelli 2004) using non linear quantile regression?

I am trying to replicate results from Engle and Manganelli (2004). The following is one of their specifications, $q_t(\theta)=\gamma_0+\gamma_1q_{t-1}(\theta)+\alpha|r_{t-1}|$, $q$ is the quantile of return distribution, $r$ is the return.

I do not know how to use quantile regression to estimate this process, since we have quantiles on both sides of equation. Any suggesions?

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