Technical Indicators

📍 Table of Contents

1. 🎯 Trend Indicators
2. ⚡ Momentum Indicators
3. 📈 Volatility Indicators
4. 💰 Volume Indicators
5. 🔄 Oscillators & Special Indicators

📖 Quick Reference

Moving Averages

SMA(N) = SUM(Close, N) / N
EMA(N) = (Close × α) + (Previous EMA × (1-α)), α = 2/(N+1)
DEMA = (2 × EMA) - EMA(EMA)
TEMA = (3 × EMA1) - (3 × EMA2) + EMA3
VWMA(N) = SUM(Close × Volume, N) / SUM(Volume, N)

Momentum

RSI(14) = 100 - (100 / (1 + RS)), RS = Avg Gain / Avg Loss
MACD = EMA(12) - EMA(26), Signal = EMA(9, MACD)
APO = EMA(14) - EMA(30)
Stochastic %K = ((C - LOW14) / (HIGH14 - LOW14)) × 100
%D = SMA(%K, 3)

Volatility

ATR(14) = SMA(True Range, 14)
TR = MAX(H-L, |H-C_prev|, |L-C_prev|)
BB Upper = SMA(20) + (2 × STDEV)
BB Lower = SMA(20) - (2 × STDEV)
Keltner = EMA ± (2 × ATR)

Volume

OBV = Previous OBV ± Volume (+ if close > prev, - if close < prev)
CMF = SUM((CLR × Volume), 14) / SUM(Volume, 14)
AD = Previous AD + (CLR × Volume)
CLR = ((C-L) - (H-C)) / (H-L)
MFI = 100 - (100 / (1 + Money Ratio))

🎯 Trend Indicators

Trend indicators identify direction and persistence of price movement. [file:21]

📍 Moving Averages (MA)

🟢 SMA - Simple Moving Average

• What: Arithmetic average of last N price points equally weighted
• Why it matters: Identifies trend direction, reduces noise
• Good signal: Price above rising SMA (uptrend), SMA above price (downtrend)
• Bad signal: Price oscillating around SMA without clear direction
• Formula: SMA = Sum(Closing, period) / period
• Use case: Long-term trend confirmation, support/resistance levels

🟡 EMA - Exponential Moving Average

• What: Weighted average giving more weight to recent prices
• Why it matters: Responds faster to price changes than SMA
• Good signal: Price above rising EMA, faster reaction in strong trends
• Bad signal: Whipsaws in choppy markets, lag in reversals
• Formula: EMA = (Close × α) + (Previous EMA × (1 - α)), where α = 2/(period+1)
• Use case: Short-term trading, trend confirmation, scalping

🟣 DEMA - Double Exponential Moving Average

• What: Combination of two EMAs reducing lag further
• Why it matters: Tracks price action faster with less delay for quick decisions
• Good signal: Earlier crossovers than SMA/EMA, better trend following
• Bad signal: False signals in ranging markets
• Formula: DEMA = (2 × EMA) - EMA(EMA)
• Use case: Active trading, quick reversals, scalping with lower lag

🔵 TEMA - Triple Exponential Moving Average

• What: Three layers of exponential smoothing for even faster response
• Why it matters: Minimizes lag significantly while maintaining smoothness
• Good signal: First to identify trend changes, aggressive trend followers
• Bad signal: Prone to whipsaws in choppy conditions
• Formula: TEMA = (3 × EMA1) - (3 × EMA2) + EMA3
• Use case: Aggressive day trading, scalping, fast-moving markets

⚪ TRIMA - Triangular Moving Average

• What: Average of an average, giving center bars more weight
• Why it matters: Creates very smooth trend line, emphasizes middle prices
• Good signal: Smoothest trends with lag, good for breakouts
• Bad signal: Late entries and exits due to extreme smoothing
• Use case: Longer-term trends, institutional patterns

🟠 RMA - Rolling Moving Average

• What: Hybrid of SMA and recursive weighted average
• Why it matters: Balances responsiveness with smoothing
• Good signal: Smooth trends without excessive lag
• Bad signal: Still lags in sharp reversals
• Use case: Scalping, intraday trading, medium-term positioning

🟢 VWMA - Volume Weighted Moving Average

• What: Average price weighted by trading volume
• Why it matters: Institutions often pay attention to VWAP/VWMA as fair price
• Good signal: Price above VWMA with rising volume = strong uptrend
• Bad signal: Price far above VWMA with declining volume = overextension
• Formula: VWMA = Sum(Price × Volume, period) / Sum(Volume, period)
• Use case: Institutional trading, breakout validation, stop placement

📊 MACD Family (Momentum Convergence)

🟦 MACD - Moving Average Convergence Divergence

• What: Difference between 12-EMA and 26-EMA with 9-EMA signal line
• Why it matters: Most widely used momentum indicator, shows convergence/divergence
• Good signal: MACD > Signal (bullish), crosses above zero (strong buy), positive divergence
• Bad signal: MACD < Signal (bearish), crosses below zero (sell), negative divergence
• Formula: MACD = EMA(12) - EMA(26) | Signal = EMA(9, MACD) | Histogram = MACD - Signal
• Use case: Trend confirmation, momentum strength, entry/exit timing

🟦 APO - Absolute Price Oscillator

• What: MACD without signal line (just the difference between two EMAs)
• Why it matters: Simpler MACD alternative, better for divergence analysis
• Good signal: APO > 0 (uptrend), positive divergence, rising peaks
• Bad signal: APO < 0 (downtrend), negative divergence, lower lows
• Formula: APO = Fast EMA(14) - Slow EMA(30)
• Use case: Divergence trading, momentum pure plays

🟪 PPO - Percentage Price Oscillator

• What: APO expressed as percentage of 12-period EMA
• Why it matters: Normalized momentum, comparable across different price levels
• Good signal: PPO > 0% with rising signal, percentage magnitude increases
• Bad signal: PPO < 0% with declining signal, shrinking magnitude
• Use case: Multi-symbol comparisons, normalized momentum analysis

🔶 TRIX - Triple Exponential Moving Average Oscillator

• What: 1-day rate of change of a triple-smoothed EMA
• Why it matters: Extremely smooth momentum, filters out small price moves
• Good signal: TRIX > 0 (momentum up), crosses above zero from below
• Bad signal: TRIX < 0 (momentum down), prolonged negative without reversal
• Formula: TRIX = (EMA3 - Previous EMA3) / Previous EMA3 × 10000
• Use case: Noise filtering, smooth trend identification, lag tolerance

🎪 Aroon & Directional Movement

🎯 Aroon (Up/Down)

• What: Two lines measuring periods since highest high and lowest low
• Why it matters: Identifies trend strength and potential reversals
• Good signal: Aroon Up near 100, Aroon Down near 0 (strong uptrend), lines crossing
• Bad signal: Both near 50 (no clear direction), convergence suggests reversal
• Formula:
  • Aroon Up = ((Period - Periods Since High) / Period) × 100
  • Aroon Down = ((Period - Periods Since Low) / Period) × 100
• Use case: Trend strength assessment, crossover trading, reversal timing

📊 Aroon Oscillator

• What: Difference between Aroon Up and Aroon Down
• Why it matters: Single oscillator showing trend direction
• Good signal: Positive = uptrend favor, negative = downtrend favor
• Bad signal: Near zero = ranging/indecision
• Formula: Aroon Oscillator = Aroon Up - Aroon Down

🔷 ADX - Average Directional Index

• What: Measures trend strength 0–50 scale regardless of direction
• Why it matters: Values > 25 = strong trends, < 20 = ranging markets
• Good signal: ADX rising above 25 with +DI > -DI (strong uptrend)
• Bad signal: ADX < 20 (weak/range), conflicting DI signals
• Formula: ADX = SMA(14, DX) | DX = (|+DI - -DI| / |+DI + -DI|) × 100
• Use case: Trend qualification, strategy selection (trend vs range)

🔶 +DI / -DI (Plus/Minus Directional Indicator)

• What: Measures uptrend/downtrend strength respectively
• Why it matters: Shows when bulls (+DI) or bears (-DI) control price
• Good signal: +DI > -DI (bulls strong), +DI rising (improving uptrend)
• Bad signal: -DI > +DI (bears strong), lines converging (weakness)
• Use case: Directional confirmation, entry/exit with ADX filter

⚫ Vortex Indicator

• What: Two oscillators capturing positive and negative trend movement
• Why it matters: Identifies trend direction and strength via price swings
• Good signal: +VI > -VI (uptrend), +VI crossing above -VI
• Bad signal: -VI > +VI (downtrend), VI lines near equal (indecision)
• Formula:
  • +VI = SUM(|High - Low(prior)|, 14) / TR14
  • -VI = SUM(|Low - High(prior)|, 14) / TR14
• Use case: Swing trading, trend confirmation, momentum trades

🎪 Additional Trend Indicators

🟡 BOP - Balance of Power

• What: Ratio of buying to selling pressure
• Why it matters: Quick gauge of bull/bear dominance
• Good signal: BOP > 0.5 (strong buy pressure), rising trend
• Bad signal: BOP < -0.5 (strong sell pressure), declining trend
• Formula: BOP = (Close - Open) / (High - Low)
• Use case: Quick momentum gauge, scalping signals

🟢 Qstick

• What: Simple moving average of (Close - Open)
• Why it matters: Measures average body size, trend momentum
• Good signal: Qstick > 0 with rising (bullish bars), positive divergence
• Bad signal: Qstick < 0 with declining (bearish bars), negative divergence
• Formula: Qstick = SMA(Close - Open, period)

🔵 CCI - Commodity Channel Index

• What: Measures deviation of price from its simple moving average
• Why it matters: Identifies cyclical trends, overbought/oversold extremes
• Good signal: CCI > +100 (strong up-momentum), crossing above 100
• Bad signal: CCI < -100 (strong down-momentum), prolonged extremes
• Formula: CCI = (Typical Price - SMA) / (0.015 × Mean Deviation)
• Use case: Cycle trading, mean reversion, momentum extremes

🟣 KDJ - Random Index (Stochastic variant)

• What: Three-line indicator (K, D, J) comparing close to high-low range
• Why it matters: Identifies momentum reversals and overbought/oversold
• Good signal: K crosses above D with both < 20 (oversold bounce), J divergence
• Bad signal: K/D stuck above 80 without follow-through (exhaustion), false breakouts
• Formula: RSV = ((C - MIN) / (MAX - MIN)) × 100 | K = SMA(RSV, 3) | D = SMA(K, 3) | J = 3K - 2D
• Use case: Short-term timing, mean reversion, overbought/oversold fades

🎯 Parabolic SAR (PSAR)

• What: Trailing stop level that rises/falls with price trend acceleration
• Why it matters: Provides entry/exit signals and mechanical trailing stops
• Good signal: SAR flips from above to below price (uptrend start), dots rising
• Bad signal: SAR flips from below to above (downtrend start/exit), whipsaws in ranges
• Formula: SAR[i] = SAR[i-1] + AF × (EP - SAR[i-1])
• Use case: Trend trading, stop-loss placement, trend reversals

⚪ Mass Index (MI)

• What: Range expansion identification using high-low volatility
• Why it matters: Identifies trend reversals when range contracts then expands
• Good signal: MI crosses below 27 (potential reversal), bullish signal if followed by expansion
• Bad signal: MI stays high (strong trend continues), breakout false signals

🔷 Typical Price

• What: Average of high, low, and close: (H+L+C)/3
• Why it matters: Better price representative for moving averages
• Good signal: Used with moving averages above it (uptrend)
• Bad signal: Price below typical price MA (downtrend)
• Use case: Price filtering, equilibrium levels

📊 Since Change

• What: Number of periods since last value change
• Why it matters: Identifies stalled indicators or prolonged levels
• Good signal: Low "since change" = dynamic indicator, trend confirmation
• Bad signal: High "since change" = indicator stuck, reversal warning

📈 Moving Extremes (MMAX, MMIN, MSUM)

• What: Maximum/minimum/sum values within rolling period
• Why it matters: Identifies recent highs/lows for breakout and range trading
• Good signal: Price breaks MMAX (bullish), MMIN rising (support holding)
• Bad signal: Price breaks MMIN (bearish), MMAX falling (resistance breaking)
• Use case: Breakout trading, volatility analysis, range identification

⚡ Momentum Indicators

Momentum indicators focus on speed of price changes and overbought/oversold zones.

🟥 RSI - Relative Strength Index

• What: Oscillator measuring speed/magnitude of price changes (0–100 scale)
• Why it matters: Most widely used overbought/oversold indicator
• Good signal: RSI 40–60 in strong trend (healthy momentum), bounces from 30, exits at 70
• Bad signal: Prolonged > 70 (overbought against your position), divergence at 70, < 30 with strength
• Threshold values:
  • RSI > 70 = Overbought (potential reversal)
  • RSI < 30 = Oversold (potential bounce)
  • RSI 40–60 = Healthy momentum in trend
• Formula: RSI = 100 - (100 / (1 + RS)) | RS = Avg Gain / Avg Loss over 14 periods
• Use case: Mean reversion, overbought/oversold fades, divergence trading, trend confirmation

🟧 Stochastic Oscillator (STOCH)

• What: Compares closing price to recent high-low range with smoothing
• Why it matters: Identifies momentum reversals and overbought/oversold with dual lines
• Good signal: %K crosses above %D from below 20 (oversold bounce), slow stoch > fast
• Bad signal: %K stuck above 80 without follow-through (exhaustion), divergence at extremes
• Threshold values:
  • %K > 80 = Overbought
  • %K < 20 = Oversold
  • Golden cross: K > D = bullish
  • Death cross: K < D = bearish
• Formula: RSV = ((C - LOW14) / (HIGH14 - LOW14)) × 100 | %K = SMA(RSV, 3) | %D = SMA(%K, 3)
• Use case: Mean reversion, momentum confirmation, divergence signals

🟦 Williams %R (WILLR)

• What: Stochastic-like indicator on 0 to -100 scale
• Why it matters: Values near -100 show oversold, near 0 show overbought
• Good signal: %R near -100 (oversold, bounce setup), crosses up from oversold
• Bad signal: %R stuck near 0 without reversal (strong trend), doesn't reach oversold
• Threshold values:
  • %R > -20 = Overbought
  • %R < -80 = Oversold
  • %R between -20 and -80 = Neutral
• Formula: WILLR = (HIGHEST - CLOSE) / (HIGHEST - LOWEST) × -100
• Use case: Overbought/oversold trading, quick entry signals, mean reversion

🟩 MFI - Money Flow Index

• What: RSI-like oscillator using price AND volume (0–100)
• Why it matters: Shows strength of buying/selling pressure combined
• Good signal: MFI 50–80 in uptrend with rising (strong bull flow)
• Bad signal: MFI > 80 with price divergence (distribution), < 20 with strength (accumulation)
• Threshold values:
  • MFI > 80 = Overbought
  • MFI < 20 = Oversold
  • MFI rising = Buying pressure increasing
  • MFI falling = Selling pressure increasing
• Formula: MFI = 100 - (100 / (1 + Money Ratio)) | Money Ratio = Positive MF / Negative MF
• Use case: Volume confirmation, divergence trading, institutional flow detection

📊 ROC - Rate of Change

• What: Percentage change in price over N periods
• Why it matters: Normalized momentum measure showing acceleration/deceleration
• Good signal: ROC > 0 and rising (accelerating uptrend), positive divergence
• Bad signal: ROC < 0 and falling (accelerating downtrend), negative divergence
• Formula: ROC = ((Close - Close[N periods ago]) / Close[N periods ago]) × 100
• Use case: Momentum strength, divergence detection, trend exhaustion

⚫ Momentum (MOM)

• What: Simple difference between current and past price
• Why it matters: Raw momentum without normalization
• Good signal: MOM > 0 (upside), increasing (accelerating)
• Bad signal: MOM < 0 (downside), decreasing (decelerating)
• Formula: MOM = Close - Close[N periods ago]

🔶 CMO - Chande Momentum Oscillator

• What: Measures difference between up and down price movements (0–100)
• Why it matters: Identifies momentum strength with extremes
• Good signal: CMO > 50 with rising (strong up-momentum)
• Bad signal: CMO < -50 with falling (strong down-momentum)
• Formula: CMO = ((Up Sum - Down Sum) / (Up Sum + Down Sum)) × 100

🟡 CFO - Chande Forecast Oscillator

• What: Percentage difference between close and linear regression forecast
• Why it matters: Identifies when price deviates from trend (mean reversion setup)
• Good signal: CFO extreme then crosses back (mean reversion), price vs forecast divergence
• Bad signal: CFO flat (no momentum), stays extreme without reversal (trend strength)

🌊 Ichimoku Cloud

• What: Multi-line system encoding trend, support/resistance, and momentum
• Why it matters: Complete trading system in one indicator
• Good signal: Price > cloud with bullish line ordering (strong uptrend), cloud support hold
• Bad signal: Price < cloud with bearish ordering (downtrend), price inside cloud (indecision)
• Formula:
  • Tenkan = (9-high + 9-low) / 2
  • Kijun = (26-high + 26-low) / 2
  • Senkou A = (Tenkan + Kijun) / 2
  • Senkou B = (52-high + 52-low) / 2
• Use case: Trend system, support/resistance, lagging span confirmation

🎯 Awesome Oscillator (AO)

• What: Difference between 5-SMA and 34-SMA of median price (H+L)/2
• Why it matters: Captures short-term momentum vs longer trend
• Good signal: AO > 0 with green bars increasing (upside momentum)
• Bad signal: AO < 0 with red bars decreasing (downside momentum)
• Use case: Momentum divergence, continuation signals

📈 Volatility Indicators

Volatility indicators address "how much the price is moving" and risk/stop placement.

📊 ATR - Average True Range

• What: Average of true range (largest of: H-L, |H-C prev|, |L-C prev|) over N periods
• Why it matters: Measures volatility independent of direction, key for stop placement
• Good signal: ATR rising with breakout (increasing risk, trend strength)
• Bad signal: ATR spike after extended move (blow-off top), then collapse (reversal warning)
• Threshold:
  • Low ATR (< historical avg) = tighter stops, range potential
  • High ATR (> historical avg) = wider stops, trend potential
• Formula: ATR = SMA(True Range, 14) | TR = MAX(H-L, |H-C prev|, |L-C prev|)
• Use case: Stop-loss sizing, position sizing, volatility-adjusted entries

🟢 Bollinger Bands (BB)

• What: SMA with upper/lower bands set N standard deviations away
• Why it matters: One of top 3 most reliable indicators; identifies overbought/oversold
• Good signal: Price break band with volume + trend (continuation), touch with bounce (mean reversion)
• Bad signal: Repeated band touches without progress (range-bound), low volume tags (fakeout)
• Threshold:
  • Upper band tag with volume = Overbought if against you, continuation if with trend
  • Lower band tag with volume = Oversold if against you, support if with trend
  • Band squeeze (low BandWidth) = volatility contraction, breakout coming
• Formula: Upper Band = SMA + (2 × STDEV) | Lower Band = SMA - (2 × STDEV) | Middle = SMA(20)
• Use case: Breakout trading, mean reversion, volatility extremes, support/resistance

🔷 Keltner Channel (KC)

• What: EMA with bands based on ATR (more volatile than BB)
• Why it matters: ATR-based bands adjust for actual volatility
• Good signal: Price breaks KC with ATR rising (genuine breakout)
• Bad signal: KC bands widen (increasing volatility), breaks false
• Formula: Upper = EMA + (2 × ATR) | Lower = EMA - (2 × ATR)
• Use case: Volatility-adjusted breakouts, trend trading

📉 MSTD - Moving Standard Deviation

• What: Standard deviation of prices over N periods
• Why it matters: Raw volatility metric for custom band construction
• Good signal: MSTD increasing (volatility rising), supports trend strength
• Bad signal: MSTD at extremes without movement (dead market), excessive spikes
• Use case: Volatility quantification, custom indicator construction

🎪 Donchian Channel (DC)

• What: Highest high and lowest low over N periods (no smoothing)
• Why it matters: Pure price-based channels, good for breakouts
• Good signal: Price breaks above DC high with volume (bullish breakout)
• Bad signal: Price breaks DC low (bearish), false breakouts without follow-through
• Use case: Breakout trading, support/resistance, turtle strategy base

🟠 Acceleration Bands (AB)

• What: Dynamic bands based on high-low range acceleration
• Why it matters: Tighter bands during calm, wider during volatile
• Good signal: Price breaks bands with increasing acceleration (strong move)
• Bad signal: Bands converge (calm), breakout false if volume drops
• Use case: Volatility confirmation, breakout validation

🔶 Chandelier Exit (CE)

• What: Volatility-adjusted trailing stop using ATR
• Why it matters: Mechanical exit based on price action and volatility
• Good signal: Price respects Chandelier (orderly trend), stops protect gains
• Bad signal: Whipsawed by CE in choppy markets (volatility too high)
• Formula: CE Long = HIGH[N] - ATR × Multiple | CE Short = LOW[N] + ATR × Multiple
• Use case: Trailing stops, trend protection, exit timing

⚪ Projection Oscillator (PO)

• What: Linear regression-based oscillator of price projections
• Why it matters: Advanced volatility measure for prediction
• Good signal: PO at extremes then reverting (mean reversion), divergence signals
• Bad signal: PO flat (no volatility or trending), extremes without reversal
• Use case: Projection-based trading, advanced volatility analysis

🟡 NATR - Normalized Average True Range

• What: ATR expressed as percentage of current price
• Why it matters: Compares volatility across different price levels/symbols
• Good signal: NATR at historical highs (maximum volatility environment)
• Bad signal: NATR at historic lows (subdued volatility, range potential)
• Formula: NATR = (ATR / Close) × 100
• Use case: Cross-symbol volatility comparison, relative risk assessment

🔷 Ulcer Index (UI)

• What: Measures depth and duration of drawdowns
• Why it matters: Risk metric capturing pain of prolonged declines
• Good signal: UI low (shallow drawdowns, healthy trend)
• Bad signal: UI rising sharply (deep drawdown building), sustained high UI (downtrend)
• Use case: Risk management, drawdown tracking, strategy stress testing

💰 Volume Indicators

Volume indicators measure whether volume supports the price move.

📊 OBV - On-Balance Volume

• What: Cumulative volume added on up days, subtracted on down days
• Why it matters: Identifies volume strength behind moves, divergences predict reversals
• Good signal: OBV rising with price (bullish confirmation), new highs
• Bad signal: Price makes new high but OBV doesn't (divergence = weak), OBV declining
• Formula:
  • If Close > Previous Close: OBV = Previous OBV + Volume
  • If Close < Previous Close: OBV = Previous OBV - Volume
  • If Close = Previous Close: OBV = Previous OBV
• Use case: Volume confirmation, accumulation/distribution, divergence trading

💵 CMF - Chaikin Money Flow

• What: Combines price position in range with volume
• Why it matters: Shows if volume follows bulls or bears
• Good signal: CMF > 0 and rising (buying pressure), confirms uptrend
• Bad signal: CMF < 0 and falling (selling pressure), price divergence at CMF extremes
• Threshold:
  • CMF > 0.1 = Moderate buying pressure
  • CMF < -0.1 = Moderate selling pressure
  • CMF between ±0.1 = Neutral flow
• Formula: CMF = SUM((CLR × Volume), N) / SUM(Volume, N) | CLR = ((C-L) - (H-C)) / (H-L)

📈 AD - Accumulation/Distribution (Chaikin AD Line)

• What: Cumulative line combining price range with volume
• Why it matters: Measures money flow in/out, shows if volume confirms trends
• Good signal: AD rising with price (bullish), AD at new highs (distribution complete)
• Bad signal: AD declining while price rising (divergence = weak), AD new lows (dumping)
• Formula: AD = Previous AD + (CLR × Volume) | CLR = ((C-L) - (H-C)) / (H-L)

🔄 ADOSC - Chaikin A/D Oscillator

• What: Difference between fast and slow EMAs of AD line
• Why it matters: Identifies momentum shifts in money flow
• Good signal: ADOSC crosses above zero (buying momentum), positive divergence
• Bad signal: ADOSC crosses below zero (selling momentum), negative divergence
• Formula: ADOSC = EMA(3, AD) - EMA(10, AD)

🎯 MFI - Money Flow Index

Note: Listed under Momentum but is volume-aware

• What: RSI-like but using price range and volume
• Why it matters: Combines momentum with volume for stronger signals
• Good signal: MFI 50–80 in uptrend (strong buying)
• Bad signal: MFI > 80 with divergence (distribution), < 20 with strength (accumulation)
• Use case: Volume-weighted momentum, divergence trading

🟢 VWAP - Volume Weighted Average Price

• What: Average price weighted by intraday volume
• Why it matters: Institutional fair price, key reference level
• Good signal: Price above VWAP with rising volume (bullish), price bouncing off VWAP
• Bad signal: Price far above VWAP with declining volume (overextension), breaks below VWAP support
• Formula: VWAP = SUM(Price × Volume) / SUM(Volume) (intraday)
• Use case: Institutional entry/exit levels, intraday support/resistance

💪 Force Index (FI)

• What: Raw price movement × volume
• Why it matters: Raw volume-adjusted momentum
• Good signal: FI > 0 and rising (strong volume behind upside)
• Bad signal: FI < 0 and falling (strong volume behind downside)
• Formula: FI = (Close - Previous Close) × Volume

📍 Ease of Movement (EMV)

• What: Distance moved relative to range and volume
• Why it matters: Shows ease of price movement (low volume = harder to move)
• Good signal: EMV positive and rising (price moving up with ease)
• Bad signal: EMV negative or flat (difficulty moving in either direction)
• Formula: EMV = (Distance Moved / (High - Low)) / (Volume / Scale)

🔷 NVI - Negative Volume Index

• What: Cumulative index only advancing on down-volume days
• Why it matters: Shows "smart money" moves on declining volume
• Good signal: NVI rising (smart money buying accumulation)
• Bad signal: NVI declining (smart money distributing)
• Use case: Long-term accumulation/distribution, smart money tracking

📊 VPT - Volume Price Trend

• What: Volume adjusted by percentage price change
• Why it matters: Combines volume and momentum in single line
• Good signal: VPT rising (volume supporting uptrend)
• Bad signal: VPT declining despite rising price (weak volume)
• Formula: VPT = Previous VPT + (Volume × ROC) | ROC = (C - C prev) / C prev

🔄 Oscillators & Special Indicators

🟠 Hilbert Transform Indicators (Advanced)

🔶 HTTRENDLINE - Hilbert Transform Instantaneous Trendline

• What: Mathematical lag-free trendline using Hilbert transform
• Why it matters: Follows price closely while removing noise
• Good signal: Price above line (uptrend), crosses above from below
• Bad signal: Price below line (downtrend), whipsaws in choppy markets
• Use case: Advanced technical traders, lag-free analysis

🌊 HTSINE - Hilbert Transform Sine Wave

• What: Generates sine wave showing dominant cycle phase
• Why it matters: Identifies market cycles for timing entries/exits
• Good signal: Sine at trough (bottom of cycle, bounce), rising phase (uptrend probable)
• Bad signal: Sine at peak (top of cycle, pullback), declining phase (downtrend probable)
• Use case: Cycle-based trading, bottom/top picking

📊 HTDCPERIOD - Hilbert Transform Dominant Cycle Period

• What: Calculates dominant cycle length in current price data
• Why it matters: Shows market periodicity, helps choose indicator periods
• Good signal: Clear dominant period (cyclic market), use it for MA periods
• Bad signal: Shifting periods (choppy, ranging market)
• Use case: Parameter optimization, cycle strength assessment

🔄 HTDCPHASE - Hilbert Transform Dominant Cycle Phase

• What: Position within dominant cycle
• Why it matters: Timing indicator for cycle-based entries/exits
• Good signal: Phase at lows (bounce setup), rising phase (uptrend continuation)
• Bad signal: Phase at highs (pullback risk), phase unreliable in non-cyclic markets
• Use case: Precise entry/exit timing, cycle-based systems

🎯 HTTRENDMODE - Hilbert Transform Trend vs Cycle

• What: Binary indicator (trending vs cycling mode)
• Why it matters: Tells you which strategy to use (trend-following vs oscillator)
• Good signal: TRENDING mode = use trend-following strategies, Bollinger Bands, MACD
• Bad signal: CYCLING mode = avoid trend-following, use mean-reversion oscillators
• Use case: Strategy mode selection, adaptive trading systems

📍 Additional Oscillators

🟣 ROCR - Rate of Change Ratio

• What: Ratio form of ROC rather than percentage
• Why it matters: Alternative calculation method for ROC analysis
• Good signal: ROCR > 1 (price up), rising (acceleration)
• Bad signal: ROCR < 1 (price down), falling (deceleration)
• Use case: Ratio-based momentum, mathematical alternatives

📊 MIDPOINT / MIDPRICE

• What: Average of recent highs and lows (or close prices)
• Why it matters: Shows center price range for equilibrium levels
• Good signal: Price above midpoint (bullish bias), below midpoint (bearish bias)
• Bad signal: Price oscillating around midpoint (balanced, no edge)
• Use case: Center line identification, mean-reversion levels