Key takeaways
– The True Strength Index (TSI) is a momentum oscillator developed to measure the strength of price movement and help identify trends, reversals, overbought/oversold conditions, and divergence. (William Blau, 1991)
– Standard TSI settings are double-smoothed EMAs of price change: a 25-period EMA smoothed again with a 13-period EMA; the result is expressed as (double-smoothed PC ÷ double-smoothed |PC|) × 100.
– Common signals: signal-line crossovers (TSI crossing its signal EMA), centerline (zero) crossovers, divergence vs price, and breaks of trendlines drawn on the TSI.
– The TSI is similar in intent to MACD (momentum/confirmation) but is calculated differently (double-smoothed price-change ratio vs. separation of two EMAs). Use TSI with other analysis and risk management — false signals are common.
Source: Investopedia (TSI overview) —
1) What the TSI measures
– The TSI is an oscillator that measures momentum by smoothing price changes (PC = current close − prior close) twice using exponential moving averages (EMAs), and comparing the double-smoothed signed changes to the double-smoothed absolute changes. The ratio, expressed ×100, produces a bounded-like oscillator showing momentum direction and strength.
2) Who created the TSI
– William Blau introduced the True Strength Index in 1991. It is widely used in technical analysis to help identify momentum changes and potential turning points.
3) Formula and components (concise)
– PC = Current Close − Prior Close
– APC = |PC| (absolute price change)
– PCS = EMA(PC, length1) — typically length1 = 25
– PCDS = EMA(PCS, length2) — typically length2 = 13 (this is PC double-smoothed)
– APCS = EMA(APC, length1) — 25-period EMA of absolute PC
– APCDS = EMA(APCS, length2) — 13-period EMA of absolute PC smoothed twice
– TSI = (PCDS / APCDS) × 100
Signal line (optional): common is a 7-period EMA of the TSI (some traders use 9–12). Use whichever you prefer but be consistent.
4) How to calculate the TSI — step-by-step (practical / implementable)
A. Collect prices: assemble a time series of closing prices for your chosen timeframe.
B. Compute PC and APC columns:
• PC_t = Close_t − Close_{t−1}
• APC_t = ABS(PC_t)
C. Compute first smoothing (EMA length1, e.g., 25):
• PCS_t = EMA(PC_t, length1)
• APCS_t = EMA(APC_t, length1)
D. Compute second smoothing (EMA length2, e.g., 13):
• PCDS_t = EMA(PCS_t, length2)
• APCDS_t = EMA(APCS_t, length2)
E. Compute TSI:
• TSI_t = (PCDS_t / APCDS_t) * 100
F. (Optional) Compute signal line:
• Signal_t = EMA(TSI_t, signal_length) — commonly 7
Notes on computing EMA:
– EMA formula (recursive): EMA_t = α × Value_t + (1 − α) × EMA_{t−1}, where α = 2/(n+1).
– Seed the first EMA value with a simple average of the first n values or use the first value as EMA_0 (consistency matters).
Spreadsheet / coding hints:
– Use separate columns for PC, APC, PCS, PCDS, APCS, APCDS, TSI, Signal.
– Many charting packages and libraries (TradingView, TradingView Pine, Python ta-lib/pandas_ta, etc.) include TSI as a built-in indicator to avoid manual calculation.
5) How to interpret the TSI (signals and practical rules)
Signal-line crossovers
– Bullish: TSI crosses above its signal line (preferably while TSI > 0 or from oversold zone).
– Bearish: TSI crosses below its signal line (preferably while TSI 0 implies positive momentum; TSI 0 and only shorts when TSI 0 (positive momentum)
• TSI crosses above signal line
• Price above an uptrend or key support; volume confirms
– Aggressive/mean-reversion long:
• TSI in historically oversold region and begins to flatten or cross above signal line
• Look for bullish divergence between price and TSI
Exit rules
– Close on TSI crossing back below signal line (for long)
– Partial profit-taking at prior resistance or when TSI reaches historically extreme overbought level
– Use trailing stops: e.g., below price swing low or ATR-based trailing stop
Risk management
– Use position sizing such that any single trade loss is a small percentage of capital (1–2% is common).
– Place stop-loss based on structure (recent swing low/high) or volatility (e.g., 1.5–2 × ATR).
– Backtest your chosen entry and exit rules extensively before trading live.
Confirmation & filter ideas
– Use TSI with price structure (trendlines, support/resistance), volume, moving averages, or another momentum indicator (RSI or MACD) to reduce false signals.
– Favor trades that align with the higher-timeframe direction.
Backtesting and validation
– Test multiple parameter sets (25/13/7 vs. 13/7/5 etc.) and multiple timeframes.
– Measure win rate, expectancy, drawdown, Sharpe ratio. Validate on out-of-sample data and recent market regimes.
7) TSI vs MACD — quick comparison
– TSI: double-smoothed EMA of price changes ratio to absolute changes; emphasizes smoothed momentum and relative strength of directional moves.
– MACD: difference between two EMAs of price (typically 12 and 26) and a signal EMA (typically 9) — shows convergence/divergence of moving averages.
– Practical difference: TSI tends to be smoother and focused on net price-change momentum; MACD is based on EMA separation and can be more sensitive to moving-average relationships. Both produce centerline and signal-line crossover signals, and both can produce divergence—use whichever fits your approach, or use both for confirmation.
8) Limitations and cautions
– False signals: TSI crossovers and divergences often produce false signals in choppy markets.
– Lag: smoothing introduces lag—faster settings reduce lag but increase noise.
– No single indicator: TSI should be one element in a broader trading plan that includes price action, risk management, and possibly fundamental context.
– Parameter sensitivity: optimal thresholds (what’s “overbought/oversold”) vary by asset and timeframe — don’t rely on fixed ± values without calibration.
9) Example implementation checklist (practical)
– Choose timeframe (e.g., daily for swing trades).
– Set TSI(25,13) and Signal EMA(7).
– Plot TSI and zero line; mark historical extremes for the asset.
– Define entry/exit rules (see section 6).
– Define stop-loss and position sizing rules.
– Backtest rules across multiple market regimes.
– Trade with small size in a live demo before scaling.
10) Bottom line
The True Strength Index is a useful momentum oscillator that smooths price changes to highlight the strength and direction of momentum. Its common applications are signal-line and centerline crossovers, divergence detection, and detection of momentum breakouts. Like all indicators, TSI is not perfect: it gives frequent false signals in sideways markets and requires confirmation, prudent stops, and sound position sizing. Test and tune parameters to the asset and timeframe you trade and use TSI as part of a well-defined plan.
Primary reference
– Investopedia — True Strength Index (TSI)
Editor’s note: The following topics are reserved for upcoming updates and will be expanded with detailed examples and datasets.