Since 2022 Sort Finance

Faber Timing Model

How this strategy trades, what it scored, and the measurements the score was read from — every symbol and timeframe, on real and resampled history.

  1. Compute a 10-month simple moving average of the close — 210 bars, treating every 21 bars as one month.
  2. Check the strategy only once a month, on every 21st bar; between reviews, nothing the market does matters. This monthly cadence is Faber's key idea — it ignores intra-month noise entirely and is what keeps the trade count tiny.
  3. At a review: if the close is above the 10-month average, be in the market; if below, be out. Buy or sell only when the answer changes from the previous review.
Score
Total Score Mean Of Real And Resampled 62 / 100
Real Data 57 / 100
Resampled Data 67 / 100
Overall Rank Top 4% 2 of 52
Rank In Trend Top 8% 2 of 28
Score By Metric
Beats Hold Real 53 · Resampled 81 67 / 100
Risk Adjusted Real 53 · Resampled 58 56 / 100
Profitability Real 63 · Resampled 74 68 / 100
Win Rate Real 32 · Resampled 26 29 / 100
Fee Efficiency Real 89 · Resampled 89 89 / 100

Scores

The six scores the total is made of, one dataset at a time: how each stood as the run went on, and where each of them ended.

Source Metrics

The numbers those scores are read from, one dataset at a time: every trade as it happened, and where the run ended.