What is a worked example of Trix?

What is TRIX?

TRIX (often written as TRIX) is a technical indicator that starts with a price series (such as closing prices), smooths it multiple times, and then measures how the smoothed value changes over time.

A worked example typically focuses on the mechanics: the step-by-step calculations that turn an input time series into a sequence of TRIX values. Because TRIX depends on exact calculation choices (for example, the smoothing method and the averaging period), any numerical example must state those assumptions clearly.

How the worked example works (mechanics)

At a high level, TRIX can be understood as:

1. Take the input price series.
2. Apply smoothing three times (often called “triple smoothing”).
3. Compute the rate of change of the triple-smoothed series from one time step to the next.

Common calculation forms express the rate of change either as a simple difference or as a percentage change. To keep a worked example verifiable, we must pick one exact form and stick to it.

Numerical worked example with explicit assumptions

Assumptions for this example:

• Input series: use already-smoothed values to avoid needing to define the exact smoothing formula.
• Let the triple-smoothed values be for three time steps:
  • t0: S0 = 100
  • t1: S1 = 101
  • t2: S2 = 99
• Use TRIX as percentage rate of change:
  • TRIX(t) = (S(t) − S(t−1)) / S(t−1) × 100%

Now compute:

• TRIX(t1) = (101 − 100) / 100 × 100% = 1%
• TRIX(t2) = (99 − 101) / 101 × 100% = (−2/101) × 100% ≈ −1.9802%

If you plot TRIX, the sign indicates whether the triple-smoothed series is rising or falling relative to the previous time step, and the magnitude reflects how large that change is under the chosen formula.

Stable mechanics vs variable conditions

The mechanics above are stable given the assumptions. What changes across real use:

• The input price definition (close, typical price, etc.).
• The smoothing method and period.
• Whether the rate of change is computed as percent or difference.
• The data frequency (minutes, daily) and any preprocessing.

So the worked example is mainly useful as a “how the number is produced” reference, not as a guarantee about how TRIX will behave on future markets.

Limitations and risks (what can go wrong)

At least one material limitation is that TRIX is derived from smoothed data, which can lag behind turning points. In practice, that means:

• In fast-moving conditions, TRIX may react later than price changes.
• In choppy conditions, small fluctuations can still produce frequent sign changes.

Other failure modes come from calculation choices:

• If two platforms use different smoothing conventions or different period definitions, the same parameter name (like “TRIX 9”) may not yield identical values.
• If you compute rate of change differently (difference vs percent), the numeric TRIX values will differ even if the underlying direction is similar.

Finally, historical relationships do not ensure future outcomes. An indicator can be informative about past changes while still failing to predict future direction.

Verification and next question

To independently verify TRIX calculations for your setup:

• Take the triple-smoothed series values your platform shows (or that you compute).
• Apply the same explicit TRIX formula you choose (difference vs percent).
• Reproduce one or two TRIX values manually, like the worked example above.

If you want, specify which exact TRIX variant you are using (how smoothing is defined and how the rate of change is expressed), and you can then create a fully reproducible worked example using the same steps.