  We establish innovative liquidity premium measures, and construct
liquidity-adjusted return and volatility to model assets with extreme
liquidity, represented by a portfolio of selected crypto assets, and upon which
we develop a set of liquidity-adjusted ARMA-GARCH/EGARCH models. We demonstrate
that these models produce superior predictability at extreme liquidity to their
traditional counterparts. We provide empirical support by comparing the
performances of a series of Mean Variance portfolios.
