QMOM: Quantitative Momentum

This repository implements a long-only momentum strategy modeled on Alpha Architect's QMOM ETF. QMOM provides a couple of enhancements to traditional momentum strategies, including selecting stocks with the smoothest momentum and rebalancing the portfolio before quarter end to capture a window-dressing seasonality effect.

The rules of the QMOM strategy as outlined in the Alpha Architect white paper are:

  1. Universe selection
    1. Starting universe: all NYSE stocks
    2. Exclude financials, ADRs, REITs
    3. Liquidity screen: select top N percent of stocks by market cap (N=60)
  2. Apply momentum screen: calculate 12-month returns, excluding most recent month, and select N percent of stocks with best return (N=10)
  3. Filter by smoothness of momentum: of the momentum stocks, select the N percent with the smoothest momentum, as measured by the number of positive days in the last 12 months (N=50)
  4. Apply equal weights
  5. Rebalance portfolio before quarter-end to capture window-dressing seasonality effect

Prerequisites

QVAL and QMOM make up the value and momentum portions, respectively, of the Alpha Architect VMOT (Value/Momentum/Trend) strategy. QMOM can be run independently of QVAL or VMOT. However, because the QMOM universe is identical to the QVAL universe, this tutorial relies on the data collection and universe selection of the QVAL tutorial. Please see that tutorial for help collecting the data and creating the universes. Because this tutorial relies on the data collection from the QVAL tutorial, it utilizes Sharadar equity prices as the data source; however, IB historical data could also be used.

See also:

  • QVAL: quantrocket codeload clone 'qval'
  • VMOT: quantrocket codeload clone 'vmot'