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1991issue C051-4

Audit indicator forecasts with chi-square hit rates

When weekly indicators disagree, confirmation bias favors the calls that already match a prior stance. A forecast log, five horizon scores, and a chi-square test of right versus wrong counts give each indicator a scored record instead of an informal reading.

  • A mixed indicator panel invites confirmation bias, because analysts tend to overweight the signals that already match their own stance.
  • A weekly forecast log records each indicator as bullish, bearish, or undecided, and accuracy is scored only on later index direction, not on the size of the move.
  • The same forecast week receives five horizon scores, so an indicator can post a higher batting average on short horizons than on long ones, or the reverse.
  • Undecided weeks drop out of the batting average, and a one-degree-of-freedom chi-square test with a Yates correction asks whether the right-wrong split is distinguishable from chance.
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Mixed signals and confirmation bias

An indicator panel is typically mixed at any one moment. Some calls read bullish, others bearish, and some sit in the middle as undecided.

Analysts tend to overweight the signals that already match their own stance. That habit is confirmation bias: the tendency to trust whichever indicators already match a prior bullish or bearish stance.

Build a weekly forecast log

One evaluation design keeps a forecast log for each indicator. Every week for 10 years, the call is recorded as bullish, bearish, or undecided.

Accuracy is scored only on the later direction of a benchmark equity index, not on the size of the move. The log tracks whether later direction agreed with a resolved call, not how far the index traveled.

Score the same week at five horizons

The same forecast week is paired with five later directional outcomes. Those horizon scores are one week, four weeks, 13 weeks, 26 weeks, and one year.

The procedure produces five separate batting averages. An indicator can score better on short horizons than on long ones, or the reverse.

Count only resolved weeks

A batting average uses only resolved weeks. An undecided week is a forecast that is neither bullish nor bearish and is dropped from the batting-average denominator.

Successful and unsuccessful cases then sum to 100 percent. The batting average is the share of correct directional forecasts among weeks that were not logged as undecided.

Test the right-wrong split

Right and wrong counts are tested with a chi-square statistic that has one degree of freedom and a Yates correction. The chi-square test is that one-degree-of-freedom significance check applied to an indicator's right versus wrong directional counts.

The Yates correction is a continuity adjustment used when the chi-square statistic is computed from those counts. Hypothesis testing asks whether an observed batting average is distinguishable from chance rather than a product of sampling noise.

The chi-square result is read as a range that indicates whether the observed right-wrong split can be treated as significant.

Chi-square gates for one degree of freedom

After right and wrong counts are tallied, Merrill reads the Yates-corrected chi-square against three printed cutoffs. Clearing 3.84 is only a one-in-twenty hint that the split is not chance; 6.64 and 10.83 are the firmer gates before an indicator should get extra weight. These are the critical values from his Figure 3 table, not a scored series for any single market or signal.
After right and wrong counts are tallied, Merrill reads the Yates-corrected chi-square against three printed cutoffs. Clearing 3.84 is only a one-in-twenty hint that the split is not chance; 6.64 and 10.83 are the firmer gates before an indicator should get extra weight. These are the critical values from his Figure 3 table, not a scored series for any single market or signal.

The companion formula uses one degree of freedom and the Yates correction of subtracting 1 from the absolute right-minus-wrong gap before squaring.

Educational research material, not investment advice. Historical source context does not establish present-day performance.
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All readings on this track · 20 readings
  1. 1988Serial dependence, trade excursions, and belief revision
  2. 1989Score an indicator before anyone writes a buy or sell rule
  3. 1990Evaluating safety labels in a crash window
  4. 1991Keep a decade-year only when it differs from the overall-mean
  5. 1991Audit indicator forecasts with chi-square hit rates
  6. 1992A lag-regression audit of stochastic forecast skill
  7. 1992Constructing detrended tests for calendar seasonality
  8. 1992Building a shared workbook for calendar seasonality tests
  9. 1995T-test evaluation of simulated trade returns
  10. 1995Constructing a two-proportion Z-test for hit rates
  11. 1996Treat a volume-price surge as a contingency table
  12. 1997Testing bond and stock seasonality before you trade
  13. 1997Walk-forward tests after system optimization
  14. 1997Testing breakout rate versus rally speed
  15. 2000Score the misses before a pattern is a system
  16. 2002Leave a moving-average crossover unfinished until chance cannot explain the ranges
  17. 2013Keep or drop an RSI threshold with a complementary-sample test
  18. 2013Constructing a null and a t-test for sample returns
  19. 2017Partial correlation and the market-adjusted stock trend
  20. 2017Constructing market-adjusted stock trend scores
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