Waves Decomposition with volume

//@version=5
indicator("Waves Decomposition", overlay=false)

wave_height = input(100)
wave_duration = input(162)
wave_duration_bigwave = input(216)

n = bar_index

f_cosine_wave(_wave_height, _wave_duration, _n) =>
    _pi = 3.14159265359
    _w = 2 * _pi / _wave_duration
    _cosine_wave = _wave_height * math.sin(_w * _n + _pi / 2)
    _cosine_wave

f_cosine_wave2(_wave_height, _wave_duration_bigwave, _n) =>
    _pi = 3.14159265359
    _w2 = 2 * _pi / _wave_duration_bigwave
    _cosine_wave2 = _wave_height * math.sin(_w2 * _n + _pi / 2)
    _cosine_wave2

wave = f_cosine_wave(wave_height, wave_duration, n)
big_wave = f_cosine_wave2(wave_height, wave_duration_bigwave, n)

wave_smoothed = ta.sma(wave, 20) // Apply moving average
big_wave_smoothed = ta.sma(big_wave, 50) // Apply moving average

plot(series=wave_smoothed, title='Normal Cycle', color=color.new(#FFFFFF, 0))
plot(series=big_wave_smoothed, title='Big Wave Cycle', color=color.new(#FFFFFF, 0))

// study(title="[RS]Compounded Risk Score", shorttitle="CRS")
// if you took a trade for every bars close for the duration of the length
// how would those trades fair atm?
// values closer to (100 | -100) are better for its (bull | bear), closer to 0 will be closer to break eaven.
// this indicator is optimal for trending markets.

length = input(100)
avg_length = input(25)

f_compound_risk(_source, _length) =>
    _total = 0.0
    _absolute = 0.0
    for _i = 1 to _length by 1
        _container0 = _total
        _container1 = _absolute
        _total := _container0 + _source[0] - _source[_i]
        _absolute := _container1 + math.abs(_source[0] - _source[_i])
    if _total > 0
        _container = _total
        _total := _total / _absolute
        _total
    else
        _container = _total
        _total := 0 - math.abs(_container) / _absolute
        _total

cr = f_compound_risk(wave_smoothed, length)
ma = ta.ema(cr, avg_length)

plot(series=cr, color=color.new(color.black, 0))
plot(series=ma, color=color.new(color.navy, 0))
hline(100)
hline(50)
hline(0)
hline(-50)
hline(-100)

//end of this part

// This source code is subject to the terms of the Mozilla Public License 2.0 at https://mozilla.org/MPL/2.0/
// © bit_ai_zine


//@version=5
//indicator(title="[Bit_Ai_zone]RSI columns", shorttitle="[Bit_Ai_zone]RSI columns", format=format.price, precision=2, timeframe="", timeframe_gaps=true)

ma(source, length, type) =>
    switch type
        "SMA" => ta.sma(source, length)
        "Bollinger Bands" => ta.sma(source, length)
        "EMA" => ta.ema(source, length)
        "SMMA (RMA)" => ta.rma(source, length)
        "WMA" => ta.wma(source, length)
        "VWMA" => ta.vwma(source, length)

rsiLengthInput = input.int(14, minval=1, title="RSI Length", group="RSI Settings") //
rsiSourceInput = input.source(close, "Source", group="RSI Settings")
maTypeInput = input.string("SMA", title="MA Type", options=["SMA", "Bollinger Bands", "EMA", "SMMA (RMA)", "WMA", "VWMA"], group="MA Settings")
maLengthInput = input.int(5, title="MA Length", group="MA Settings")

up = ta.rma(math.max(ta.change(rsiSourceInput), 0), rsiLengthInput)
down = ta.rma(-math.min(ta.change(rsiSourceInput), 0), rsiLengthInput)
rsi = down == 0 ? 100 : up == 0 ? 0 : 100 - (100 / (1 + up / down))
rsiMA = ma(rsi, maLengthInput, maTypeInput)

rsicolor = color.rgb(214, 212, 212)

if rsi < 30
    rsicolor := color.red
if rsi > 70
    rsicolor := color.green
if rsi < 20
    rsicolor := color.black

plot(rsi, "RSI", color=rsicolor , style =  plot.style_columns)
plot(rsiMA, "RSI-based MA", color=color.black)