Positional Momentum and Liquidity Management; A Bivariate Rank ApproachTitle

This paper develops a new positional momentum management strategy and introduces a new positional liquidity management strategy. The approach relies on the expected ranks of asset returns and trade volume changes predicted from a bivariate Vector Autoregressive (VAR) model. The new methods are applied to a panel data of 1330 stocks traded on the NASDAQ between 1999 and 2016. The new prediction-based positional momentum strategy with bivariate ranks is shown to outperform the standard momentum strategy and the equally weighted portfolio. This suggests that volume ranks help improve the performance of a positional momentum portfolio. Moreover, the positional liquidity portfolios are shown to produce even higher average and cumulative returns over time than the positional momentum portfolios based on bivariate ranks