Define RSI and MACD in terms of required inputs
RSI (Relative Strength Index) and MACD (Moving Average Convergence Divergence) are indicator calculations that transform a price series into values shown over time. To assess them, you need to know exactly what price series is being used and how the calculations are parameterized.
For both indicators, “data needed” is not just market prices. It includes the data source, the sampling (timeframe), and the calculation settings (the periods and smoothing rules). Without these, two people can compute different RSI/MACD lines from the same chart-looking instrument and still be mathematically correct relative to their own inputs.
Data inputs you should gather before calculating or comparing
- Historical price series with consistent definitions
- For RSI, you need a sequence of closing prices (or the specific price field your RSI implementation uses).
- For MACD, you need the price series used for moving averages (commonly closes), including enough history to cover the longest lookback and initial smoothing.
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Timeframe and bar construction RSI and MACD values change with the timeframe (for example, minutes versus hours) because each bar aggregates prices differently. To assess the indicators, record the timeframe and how bars are formed (open/high/low/close aggregation, and whether the data is “new bar” at the close).
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Calculation parameters (indicator settings)
- RSI: at minimum, the RSI period (often described as the lookback length used to compute average gains and losses).
- MACD: at minimum, the fast and slow moving-average periods, plus the signal smoothing period.
If a provider uses alternative conventions (such as different price fields, different smoothing types, or an adjusted versus unadjusted series), you need those settings too so your computed values can match.
Provenance: where the data came from and what it represents
To independently verify RSI and MACD, capture provenance details:
- Data source: which platform, feed, or export produced the candles/prices.
- Instrument identity: symbol name alone can be ambiguous; you need what the symbol actually refers to (contract specs, whether it is spot or a derivative), at least at the level the provider documents.
- Time zone and session rules: candle timestamps must be interpreted consistently. A mismatch can shift the series alignment and therefore the resulting indicator path.
These provenance items are part of the “inputs” because the same nominal indicator settings applied to misaligned or differently constructed bars will produce different outputs.
Timeliness and reproducibility checks
Even without real-time decision-making, timeliness still matters for assessment and verification:
- Use the same historical snapshot when comparing results (for example, “prices downloaded on date X” rather than a rolling download).
- Confirm whether the data is subject to revisions or backfills.
- Store indicator settings alongside the data export so another run produces the same RSI and MACD values.
A practical quality check is to recompute RSI/MACD using your recorded settings and confirm that the results match the values displayed by the source (within any documented rounding or computational conventions).
Evidence or example: what can be independently verified
You can verify the indicator computations without predicting outcomes:
- Confirm that RSI uses the specified lookback period and the chosen gains/losses method.
- Confirm that MACD uses the specified fast/slow moving averages and the specified signal line smoothing.
- Verify alignment: the indicator’s plotted value at a given bar corresponds to calculations that only use data up to that bar (not future bars).
Assumption to state explicitly in any example: assume a particular timeframe and candle data set, and assume the indicator settings exactly match the documented parameters of the implementation you are testing. Without these assumptions, “the same indicators” may not be comparable.
Limitations and failure modes (material risks)
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Input choice sensitivity RSI and MACD depend on the input series and settings. Changing the timeframe, the price field used (close versus other), or the RSI/MACD periods can materially change the indicator values. This can look like “pattern changes,” even when nothing about the underlying computation is wrong.
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Data quality problems Common failure modes include missing candles, duplicated bars, incorrect timestamps, or broken continuity in the price series. These issues can distort moving averages and RSI’s gain/loss averages.