Recognizing　the　importance　of　incorporating　different　risk　measures　in　the　portfolio　management　model,　this　paper　examines　the　dynamic　mean-risk　portfolio　optimization　problem　using　both　variance　and　value　at　risk　(VaR)　as　risk　measures.　By　employing　the　martingale　approach　and　integrating　the　quantile　optimization　technique,　we　provide　a　solution　framework　for　this　problem.　We　demonstrate　that,　under　a　general　market　setting,　the　optimal　terminal　wealth　may　exhibit　different　patterns.　When　the　market　parameters　are　deterministic,　we　derive　the　closed-form　solution　for　this　problem.　Examples　are　provided　to　illustrate　the　solution　procedure　of　our　method　and　demonstrate　the　benefits　of　our　dynamic　portfolio　model　compared　to　its　static　counterpart.