Correlated stocks should, in equilibrium, have correlated momenta, but in practice momenta do not always correlate. We use short-term inconsistencies between correlations and momenta to predict price corrections, produce more meaningful investment indicators, and improve upon accepted investing strategies. In particular, our approaches integrate inconsistencies within an entire security class rather than relying only on individual or pairwise security data. We use this theory to improve upon not only the standard momentum portfolio but also Pair Trading and Momentum Reversion methods. This results in three strategies for portfolio allocation that outperforms overlying indices and market benchmarks by 5%-10% in annual gain with an increase of CAPM alpha over the standard momentum portfolio from -0.1 to 5.4. We expand on these strategies by showing applications generalized to comparable investing indicators including volatility.