Browse the library
Finabase Learn
Technical indicators
Every indicator in the Finabase chart — what it measures, the formula, the default settings, how to read its signals and where it fails.
Trend and moving averages
- Simple moving average (SMA): formula, crossovers and limits How the simple moving average is calculated, how traders read the 50-day and 200-day lines and their crossovers, and why every SMA signal arrives late.
- Exponential moving average (EMA): formula and how to use it How the exponential moving average weights recent prices, how to compute it step by step, how it compares with the SMA, and how Finabase scans and scores it.
- Weighted moving average (WMA): linear weights, worked example How the linearly weighted moving average counts recent closes more heavily, a full worked calculation on Microsoft prices, and when it beats an SMA or EMA.
- Double exponential moving average (DEMA): reducing lag How Patrick Mulloy’s DEMA subtracts an EMA’s own lag, a worked example on AMD, why it overshoots at turns, and how Finabase computes it.
- Triple exponential moving average (TEMA): fast, with a catch How the TEMA combines three EMAs to cancel lag, what its overshoot looks like on a price jump and on Tesla’s 2026 slide, and how Finabase draws and scores it.
- Triangular moving average (TRIMA): the smoothest classic average How the triangular moving average double-smooths prices, a worked example on Coca-Cola closes, why it turns late, and when its smoothness is worth it.
- Kaufman Adaptive Moving Average (KAMA): efficiency ratio explained How KAMA speeds up in clean trends and slows down in noise using the efficiency ratio, a worked calculation on QQQ, and how Finabase computes and scores it.
- T3 moving average (Tillson T3): smooth with little lag How Tim Tillson’s T3 chains six EMAs with a volume factor to get a smooth, low-lag line, the coefficient arithmetic, a Meta example and Finabase’s settings.
- MESA Adaptive Moving Average (MAMA and FAMA) explained How John Ehlers’ MAMA adapts its speed to the market’s cycle phase, why it moves in steps, how MAMA/FAMA crossovers work on Amazon, and Finabase’s settings.
- Parabolic SAR: how stop-and-reverse works, step by step How Wilder’s Parabolic SAR trails price with an accelerating stop, a bar-by-bar calculation on Alphabet, its real win/loss record over a year, and Finabase’s settings.
- Average Directional Index (ADX): measuring trend strength What the ADX measures and what it does not, how Wilder built it from +DI and −DI, how to read 20, 25 and 40, a real Exxon Mobil example and Finabase’s ADX.
- Directional Movement Index (DX, +DI, −DI): a hand calculation How Wilder’s directional movement, true range, +DI, −DI and DX are calculated, worked bar by bar on JPMorgan Chase, and why raw DX is too noisy to use alone.
- ADXR (Average Directional Movement Rating): what it adds How Wilder’s ADXR averages today’s ADX with the ADX of 13 bars ago, a worked example on Chevron, what ADX–ADXR crossings mean, and how Finabase computes it.
- Aroon indicator (Aroon Up and Aroon Down): reading new highs How Tushar Chande’s Aroon measures time since the last high and low, a worked calculation on Costco, how to read crossovers and 100 readings, and Finabase’s settings.
- Aroon Oscillator: one line for trend direction and age How the Aroon Oscillator subtracts Aroon Down from Aroon Up, what readings of ±50 and ±100 mean, a worked example on Netflix’s 2026 downtrend, and Finabase’s settings.
- ZigZag indicator: filtering swings, and why the last leg repaints How the ZigZag connects swing highs and lows that differ by a set percentage, a worked example on IWM, why its last leg changes, and how Finabase draws it.
Momentum oscillators
- Relative Strength Index (RSI): how to read and use it What the RSI measures, how Wilder’s formula works step by step, how to read overbought, oversold, divergence and failure swings, and where it fails.
- MACD indicator: signal line, histogram and divergence How the MACD line, signal line and histogram are calculated, how to read crossovers, the zero line and divergence on Microsoft’s 2026 chart, and how Finabase scores it.
- Absolute Price Oscillator (APO): moving-average gap in dollars What the Absolute Price Oscillator measures, why Finabase’s APO uses simple averages unlike MACD, a worked example on Visa, its zero-line signals and their limits.
- Stochastic oscillator (slow %K and %D): how to read it How George Lane’s slow stochastic places the close within its recent range, a worked %K and %D on Johnson & Johnson, the 80/20 levels and Finabase’s 15/5 settings.
- Fast stochastic oscillator: raw %K, %D and its whipsaws How the fast stochastic differs from the slow one, a worked 5-bar %K on PepsiCo, why it swings from 82 to 0.6 in three days, and how Finabase computes and flags it.
- Stochastic RSI (StochRSI): an oscillator of an oscillator How StochRSI applies the stochastic formula to RSI values, a worked example on Broadcom, why Finabase’s 14/5/3 setting pins at 0 and 100, and how to read it.
- Williams %R: formula, −20/−80 levels and real signals How Larry Williams’ %R measures the close against the recent high, a worked calculation on Walmart, how its −20 and −80 signals fared over a year, and Finabase’s scoring.
- Commodity Channel Index (CCI): formula, ±100 and two readings How Donald Lambert’s CCI measures distance from the average typical price, a worked Caterpillar example, the two readings of ±100 and Finabase’s scoring.
- Chande Momentum Oscillator (CMO): formula and Finabase’s version How Tushar Chande’s CMO compares up-day and down-day totals, why Finabase’s TA-Lib CMO equals 2 × RSI − 100, a worked example on Home Depot, and how to read ±50.
- Momentum indicator (MOM): price change over n bars How the Momentum indicator subtracts the close n bars ago, a worked Oracle example of its echo effect, zero-line signals over a 46% decline, and how Finabase scores it.
- Rate of Change (ROC): percentage momentum and how to read it How the Rate of Change measures percentage price change over n bars, a worked example on the energy ETF XLE, reading its zero line and extremes, and Finabase’s ROC.
- ROCP (rate of change percentage): returns as fractions What ROCP is, how it differs from ROC, why adding or averaging returns misleads, a compounding example on Eli Lilly, and how to use ROCP in Finabase charts.
- ROCR (rate of change ratio): growth factors and relative strength What ROCR measures, why a ratio is the natural form for chaining returns and comparing a stock with the market, a Boeing versus SPY example, and Finabase’s ROCR.
- TRIX indicator: triple-smoothed momentum and its zero line How TRIX takes the one-bar percent change of a triple EMA, a worked calculation on Disney, why it filters noise but lags, and how Finabase scores its zero line.
- Ultimate Oscillator: three timeframes and Williams’ rules How Larry Williams’ Ultimate Oscillator blends 7-, 14- and 28-bar buying pressure, a worked Intel calculation, his divergence sell rule in action and Finabase’s settings.
Volume
- On-Balance Volume (OBV): reading volume flow and divergence How Joe Granville’s On-Balance Volume adds and subtracts each day’s volume, a worked Salesforce example, its 2026 divergences, and Finabase’s OBV.
- Chaikin Oscillator (ADOSC): accumulation/distribution momentum How Marc Chaikin’s oscillator turns the accumulation/distribution line into a 3/10-day momentum signal, a worked money-flow example on Pfizer, and Finabase’s ADOSC.
- Money Flow Index (MFI): the volume-weighted RSI How the Money Flow Index combines typical price and volume into a 0–100 oscillator, a worked calculation on Starbucks, how it differs from RSI, and Finabase’s MFI.
- VWAP (volume-weighted average price): session and anchored How VWAP weights typical price by volume, a minute-by-minute worked example on Palantir, session versus anchored VWAP, and exactly where Finabase’s VWAP is anchored.
Volatility
- Bollinger Bands: formula, the squeeze and walking the bands How Bollinger Bands set a two-standard-deviation envelope around a 20-day average, a worked IBM example, the squeeze and band walks, and how Finabase scores them.
- Average True Range (ATR): volatility, stops and position size How Wilder’s Average True Range measures volatility including gaps, a worked Micron example, using ATR for stops and position sizing, and how Finabase computes it.
- Normalized ATR (NATR): volatility as a percentage of price How NATR turns the Average True Range into a percentage of price, a worked Uber example, comparing volatility across stocks with Micron, and Finabase’s NATR.
Statistics
- Beta: market beta explained, and what Finabase’s BETA study shows What beta measures, how the regression slope is calculated, why McDonald’s market beta was near zero in 2026, and what Finabase’s 5-bar BETA chart study measures.
- Correlation coefficient (CORREL): how two series move together What Pearson correlation measures, a hand calculation on Treasury bond ETF prices, market correlation versus Finabase’s 5-bar CORREL study, and their pitfalls.
- Time Series Forecast (TSF): linear regression projected one bar How the Time Series Forecast fits a least-squares line to recent closes and extends it one bar, a worked Adobe example, how well its forecasts did, and Finabase’s TSF.
Educational content, not investment advice. Finabase Learn explains how markets and tools work. It does not recommend any security or strategy, and examples are for illustration only. Investing involves risk, including the loss of principal. Rules and figures are for the United States unless stated and can change — check the cited source before you act.