mirror of
https://github.com/mihakralj/QuanTAlib.git
synced 2026-08-13 16:18:05 +00:00
Miha Kralj
24e86d762a
- Updated BBWN, BBWP, CCV, CV, CVI, EWMA, GKV, HLV, HV, Jvolty, JVOLTYN, MASSI, NATR, RSV, RV, RVI, TR, UI, VOV, VR, YZV indicators with documentation links. - Added documentation links for Aberration, Acceleration Bands, Andrews' Pitchfork, Adaptive Price Zone, ATR Bands, Bollinger Bands, Center of Gravity, Donchian Channels, Decay Min-Max Channel, Detrended Synthetic Price, EACP, EBSW, HOMOD, Jurik Volatility Bands, Keltner Channel, MA Envelope, Min-Max Channel, Price Channel, Regression Channels, Standard Deviation Channel, Stoller Average Range Channel, Super Trend Bands, Ultimate Bands, Ultimate Channel, VWAP Bands, and VWAP with Standard Deviation Bands.
86 lines
3.2 KiB
Plaintext
86 lines
3.2 KiB
Plaintext
// The MIT License (MIT)
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// © mihakralj
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//@version=6
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indicator("Percentage Price Oscillator (PPO)", "PPO", overlay=false)
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//@function Calculates Percentage Price Oscillator using compensated EMAs
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//@param src Source series to calculate PPO for
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//@param fast_len Fast EMA period
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//@param slow_len Slow EMA period
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//@param signal_len Signal line period
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//@returns Tuple containing PPO line and signal line values
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ppo(series float src, simple int fast_len, simple int slow_len, simple int signal_len)=>
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if fast_len<=0 or slow_len<=0 or signal_len<=0
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runtime.error("Lengths must be greater than 0")
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if fast_len>=slow_len
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runtime.error("Fast length must be less than slow length")
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float alpha_fast = 2.0/math.max(fast_len,1)
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var float fast_ema = na, var float fast_result = na
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var float fast_e = 1.0, var bool fast_warmup = true
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float alpha_slow = 2.0/math.max(slow_len,1)
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var float slow_ema = na, var float slow_result = na
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var float slow_e = 1.0, var bool slow_warmup = true
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float alpha_signal = 2.0/math.max(signal_len,1)
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var float signal_ema = na, var float signal_result = na
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var float signal_e = 1.0, var bool signal_warmup = true
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if not na(src)
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if na(fast_ema)
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fast_ema := 0.0
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fast_result := src
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else
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fast_ema := alpha_fast*(src-fast_ema)+fast_ema
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if fast_warmup
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fast_e *= (1-alpha_fast)
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float fast_c = 1.0/(1.0-fast_e)
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fast_result := fast_c*fast_ema
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if fast_e<=1e-10
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fast_warmup := false
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else
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fast_result := fast_ema
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if na(slow_ema)
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slow_ema := 0.0
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slow_result := src
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else
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slow_ema := alpha_slow*(src-slow_ema)+slow_ema
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if slow_warmup
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slow_e *= (1-alpha_slow)
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float slow_c = 1.0/(1.0-slow_e)
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slow_result := slow_c*slow_ema
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if slow_e<=1e-10
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slow_warmup := false
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else
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slow_result := slow_ema
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float ppo_line = 100 * (fast_result - slow_result) / slow_result
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if not na(ppo_line)
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if na(signal_ema)
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signal_ema := 0.0
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signal_result := ppo_line
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else
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signal_ema := alpha_signal*(ppo_line-signal_ema)+signal_ema
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if signal_warmup
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signal_e *= (1-alpha_signal)
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float signal_c = 1.0/(1.0-signal_e)
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signal_result := signal_c*signal_ema
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if signal_e<=1e-10
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signal_warmup := false
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else
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signal_result := signal_ema
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float hist = ppo_line - signal_result
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[ppo_line, signal_result, hist]
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// ---------- Main loop ----------
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// Inputs
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i_source = input.source(close, "Source")
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i_fast_len = input.int(12, "Fast Length", minval=1)
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i_slow_len = input.int(26, "Slow Length", minval=1)
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i_signal_len = input.int(9, "Signal Length", minval=1)
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// Calculation
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[ppo_line, signal_line, hist] = ppo(i_source, i_fast_len, i_slow_len, i_signal_len)
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// Plot
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plot(ppo_line, "PPO", color=color.blue, linewidth=2)
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plot(signal_line, "Signal", color=color.red, linewidth=2)
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plot(hist, "Histogram", color.gray, style=plot.style_histogram)
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