Files
QuanTAlib/lib/trends_IIR/kama/kama.pine
T
86fe32a682 SIMD Refactor: Merge simd-dev into dev (#55)
Co-authored-by: Claude Opus 4.5 <noreply@anthropic.com>
Co-authored-by: aider (openrouter/anthropic/claude-sonnet-4) <aider@aider.chat>
Co-authored-by: Warp <agent@warp.dev>
2026-01-18 19:02:03 -08:00

49 lines
2.1 KiB
Plaintext

// The MIT License (MIT)
// © mihakralj
//@version=6
indicator("Kaufman's Adaptive Moving Average (KAMA)", "KAMA", overlay=true)
//@function Calculates KAMA using adaptive smoothing based on market volatility
//@doc https://github.com/mihakralj/pinescript/blob/main/indicators/trends_IIR/kama.md
//@param source Series to calculate KAMA from
//@param period Length of the efficiency ratio lookback period
//@param fast_alpha Fastest EMA constant (2/(2+1))
//@param slow_alpha Slowest EMA constant (2/(30+1))
//@returns KAMA value with efficiency ratio-based adaptive smoothing
//@optimized Uses efficiency ratio calculation for O(n) complexity per bar due to lookback sum
kama(series float source, simple int period, simple float fast_alpha=0.666667, simple float slow_alpha=0.0645) =>
if period <= 0
runtime.error("Period must be greater than 0")
if fast_alpha <= 0 or slow_alpha <= 0
runtime.error("Alpha values must be greater than 0")
if fast_alpha <= slow_alpha
runtime.error("Fast alpha must be greater than slow alpha")
var float kama_state = na
float current_kama = na
if not na(source)
float change_val = math.abs(source - source[period])
float volatility_val = math.sum(math.abs(source - source[1]), period)
float er = 0.0
if not na(change_val) and not na(volatility_val) and volatility_val != 0.0
er := change_val / volatility_val
float sc = math.pow(er * (fast_alpha - slow_alpha) + slow_alpha, 2)
kama_state := na(kama_state) ? source : kama_state + sc * (source - kama_state)
current_kama := kama_state
current_kama
// ---------- Main loop ----------
// Inputs
i_period = input.int(10, "Period", minval=1)
i_source = input.source(close, "Source")
i_fast = input.int(2, "Fast EMA Period", minval=2)
i_slow = input.int(30, "Slow EMA Period", minval=2)
// Calculation
float fast_alpha = 2.0 / (float(i_fast) + 1.0)
float slow_alpha = 2.0 / (float(i_slow) + 1.0)
kama_value = kama(i_source, i_period, fast_alpha, slow_alpha)
// Plot
plot(kama_value, "KAMA", color=color.yellow, linewidth=2)