In the previous post we introduced the momentum score as a measure of the potential for momentum profits for a given investment universe. Before proceeding to part 2 of the series, I thought it would be interesting for readers to see a pairwise matrix of momentum scores to get a better feel for how they work in practice. Note that higher scores indicate higher potential for momentum profits. Below are the pairwise momentum score matrices for both sectors and asset classes:
Notice that sectors with similar macro-factor exposure have lower scores: for example materials and energy which tend to thrive in cyclical upturns in the economy (XLE/XLB), or health care and consumer staples (XLP/XLV) which thrive in recessions or cyclical downturns. The highest scores accrue to sectors that are likely to do well at different times in the economic cycle such as energy and utilities (XLE/XLU). This makes logical sense– momentum strategies require the ability to rotate to assets that are doing well at different times.
Notice that pairings of equity, real estate or commodity assets classes (e.g. SPY,EEM, IEV, DBC, RWX) with TLT and GLD tend to have the highest momentum scores. The combination of near substitute assets such as intermediate bonds (IEF) and long-term bonds (TLT), or say S&P500 (SPY) and European stocks (IEV) tend to have very low scores by comparison. In general most pairwise scores for asset classes are substantially higher than those contained within the sector momentum score matrix.