herbert 
Die Kernidee des Volumatic VIDYA-Indikators besteht darin, ein dynamisches, adaptives Glättungstool bereitzustellen, das Trends erkennt und gleichzeitig den Volumendruck dahinter berechnet. Die VIDYA-Linie, die auf dem dynamischen Durchschnitt des variablen Index basiert, passt sich entsprechend der Stärke der Preisbewegungen an und bietet im Vergleich zu standardmäßigen gleitenden Durchschnitten eine adaptivere Reaktion auf den Markt.
Durch die Berechnung und Anzeige des Kauf- und Verkaufsvolumendrucks während jedes Trends bietet der Indikator Händlern wichtige Einblicke in die Marktbeteiligung. Die horizontalen Linien, die aus den Hochs und Tiefs der Marktstruktur-Pivotpunkte gezogen werden, geben zusätzliche Klarheit über die Unterstützungs- und Widerstandsniveaus, gestützt durch das durchschnittliche Volumen an diesen Punkten. Diese doppelte Analyse von Trend und Volumen ermöglicht es Händlern, die Stärke und das Potenzial von Marktbewegungen effektiver einzuschätzen.
HAUPTMERKMALE UND VERWENDUNG
VIDYA-Berechnung:
Der Variable Index Dynamic Average (VIDYA) ist eine spezielle Art des gleitenden Durchschnitts, der sich dynamisch an die Volatilität und Dynamik des Marktes anpasst. Im Gegensatz zu herkömmlichen gleitenden Durchschnitten, die feste Zeiträume verwenden, passt VIDYA seinen Glättungsfaktor basierend auf der relativen Stärke der Preisbewegungen an und nutzt den Chande Momentum Oscillator (CMO), um das Ausmaß der Preisänderungen zu erfassen. Wenn die Dynamik stark ist, passt sich VIDYA an und glättet Preisbewegungen schneller, sodass es besser auf schnelle Preisänderungen reagieren kann. Dies macht VIDYA im Vergleich zu herkömmlichen gleitenden Durchschnitten wie dem Simple Moving Average (SMA) oder dem Exponential Moving Average (EMA), die weniger flexibel sind, anpassungsfähiger an volatile Märkte.
Download Script
TradingView Code – Pine Script
// This work is licensed under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
// https://creativecommons.org/licenses/by-nc-sa/4.0/
// © BigBeluga
//@version=5
indicator("Volumatic Variable Index Dynamic Average [BigBeluga]", "Volumatic VIDYA [BigBeluga]",
overlay = true, max_lines_count = 500, max_labels_count = 500)
// ＩＮＰＵＴＳ ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――{
// Input parameters for length, momentum, and source data
int vidya_length = input.int(10, "VIDYA Length") // Length of the VIDYA calculation
int vidya_momentum = input.int(20, "VIDYA Momentum") // Momentum length for VIDYA
float band_distance = input.float(2, "Distance factor for upper/lower bands", step = 0.1) // Distance factor for upper/lower bands
// Define pivot parameters
int pivot_left_bars = 3 // Left side pivot bars
int pivot_right_bars = pivot_left_bars // Right side pivot bars
float source = input.source(close, "Source") // Source for VIDYA calculation
// Define colors for up and down trends
color up_trend_color = input(#17dfad, "+", group = "Color", inline = "c") // Color for uptrend
color down_trend_color = input(#dd326b, "-", group = "Color", inline = "c") // Color for downtrend
bool shadow = input.bool(true, "Shadow", group = "Color", inline = "c")
// Initialize variables for line, volume, and trend state
var line pivot_line = na // Variable for storing line references
var float volume_value = na // Variable for storing volume data
float smoothed_value = na // Smoothing variable for VIDYA trend levels
var bool is_trend_up = na // Boolean variable for tracking trend direction
// Initialize arrays for storing line and volume information
var array<line> liquidity_lines_low = array.new<line>(500) // Array for storing lines for lows
var array<line> liquidity_lines_high = array.new<line>(500) // Array for storing lines for highs
var float up_trend_volume = na // Volume accumulated during uptrend
var float down_trend_volume = na // Volume accumulated during downtrend
// }
// ＦＵＮＣＴＩＯＮＳ―――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――{
// Define VIDYA (Variable Index Dynamic Average) function
vidya_calc(src, vidya_length, vidya_momentum) =>
float momentum = ta.change(src)
float sum_pos_momentum = math.sum((momentum >= 0) ? momentum : 0.0, vidya_momentum)
float sum_neg_momentum = math.sum((momentum >= 0) ? 0.0 : -momentum, vidya_momentum)
float abs_cmo = math.abs(100 * (sum_pos_momentum - sum_neg_momentum) / (sum_pos_momentum + sum_neg_momentum))
float alpha = 2 / (vidya_length + 1)
var float vidya_value = 0.0
vidya_value := alpha * abs_cmo / 100 * src + (1 - alpha * abs_cmo / 100) * nz(vidya_value[1])
ta.sma(vidya_value, 15)
// Method to extend lines and add labels for liquidity levels
method extend_liquidity_lines(array<line> line_array, float price_level, bool is_cross, volume_val)=>
if line_array.size() > 0 and last_bar_index - bar_index < 5000
for i = 0 to line_array.size()-1
if i < line_array.size()
line liquidity_line = line_array.get(i)
float current_line_level = line.get_y2(liquidity_line)
bool price_cross = is_cross
? price_level < current_line_level and price_level[1] >= current_line_level
: price_level > current_line_level and price_level[1] <= current_line_level
bool is_short_line = bar_index - line.get_x1(liquidity_line) < 50
if price_cross and is_short_line
line.set_x2(liquidity_line, bar_index)
line_array.remove(i)
// Add volume label to the liquidity zone
label.new(bar_index-1, price_level[1],
str.tostring(volume_val, format.volume),
color = color.rgb(0, 0, 0, 99),
style = is_cross ? label.style_label_lower_left : label.style_label_upper_left,
textcolor = chart.fg_color,
size = size.small)
// Add a circle label to represent liquidity zone
label.new(bar_index-1, price_level[1],
text = "◉",
color = #00000003,
textcolor = is_cross ? down_trend_color : up_trend_color,
style = label.style_label_center,
size = size.normal)
// }
// ＣＡＬＣＵＬＡＴＩＯＮＳ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――{
// Calculate the Average True Range (ATR)
float atr_value = ta.atr(200) // ATR calculation with length of 200
// Calculate the VIDYA (Variable Index Dynamic Average)
vidya_value = vidya_calc(source, vidya_length, vidya_momentum)
// Calculate upper and lower bands based on VIDYA and ATR
float upper_band = vidya_value + atr_value * band_distance
float lower_band = vidya_value - atr_value * band_distance
// Detect trend direction using crossovers of source with bands
if ta.crossover(source, upper_band)
is_trend_up := true
if ta.crossunder(source, lower_band)
is_trend_up := false
// Set trend-based smoothing variable
if is_trend_up
smoothed_value := lower_band
if not is_trend_up
smoothed_value := upper_band
if ta.change(is_trend_up)
smoothed_value := na
// Calculate pivot highs and lows for price action
float pivot_high = ta.pivothigh(pivot_left_bars, pivot_right_bars)
float pivot_low = ta.pivotlow(close, pivot_left_bars, pivot_right_bars)
// Create and store lines for pivot lows (support zones)
if low[pivot_right_bars] > smoothed_value and pivot_low
pivot_line := line.new(
bar_index[pivot_right_bars],
low[pivot_right_bars],
bar_index[pivot_right_bars]+5,
low[pivot_right_bars],
color = color.new(up_trend_color, 50)
)
liquidity_lines_low.push(pivot_line)
volume_value := math.sum(volume, pivot_right_bars + pivot_left_bars) / (pivot_right_bars + pivot_left_bars)
// Create and store lines for pivot highs (resistance zones)
if high[pivot_right_bars] < smoothed_value and pivot_high
pivot_line := line.new(
bar_index[pivot_right_bars],
high[pivot_right_bars],
bar_index[pivot_right_bars]+5,
high[pivot_right_bars],
color = color.new(down_trend_color, 50)
)
liquidity_lines_high.push(pivot_line)
volume_value := math.sum(-volume, pivot_right_bars + pivot_left_bars) / (pivot_right_bars + pivot_left_bars)
// Extend lines to track price movements
liquidity_lines_high.extend_liquidity_lines(smoothed_value, true, volume_value)
liquidity_lines_low.extend_liquidity_lines(smoothed_value, false, volume_value)
// Detect changes in the trend direction
bool trend_cross_up = not is_trend_up[1] and is_trend_up
bool trend_cross_down = not is_trend_up and is_trend_up[1]
// Reset volume counters when trend changes
if ta.change(trend_cross_up) or ta.change(trend_cross_down)
up_trend_volume := 0
down_trend_volume := 0
// Accumulate volume during trends
if not(ta.change(trend_cross_up) or ta.change(trend_cross_down))
up_trend_volume += (close > open ? volume : 0)
down_trend_volume += (close < open ? volume : 0)
// Calculate average volume
float avg_volume_delta = (up_trend_volume + down_trend_volume) / 2
// Determine the color of the trend
color trend_color = is_trend_up ? up_trend_color
: not is_trend_up ? down_trend_color
: chart.fg_color
// Calculate delta volume percentage
string delta_volume =
str.tostring(((up_trend_volume - down_trend_volume) / avg_volume_delta) * 100, format.percent) == "NaN%"
? "0%"
: str.tostring(((up_trend_volume - down_trend_volume) / avg_volume_delta) * 100, format.percent)
// }
// ＰＬＯＴ ――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――――{
// Display labels for volume and trend statistics on the last bar
if barstate.islast
label.delete(
label.new(bar_index, smoothed_value,
"Buy: " + str.tostring(up_trend_volume, format.volume)
+ "\n Sell: " + str.tostring(down_trend_volume, format.volume)
+ "\nDelta Volume: " + delta_volume,
color = color.new(trend_color, 90),
style = is_trend_up ? label.style_label_upper_left : label.style_label_lower_left,
textcolor = chart.fg_color
)[1])
label.delete(label.new(bar_index, smoothed_value,
text = "✪",
color = #00000003,
textcolor = trend_color,
style = label.style_label_center,
size = size.large)[1])
// Plot the VIDYA trend line
p1 = plot(smoothed_value, color = trend_color, linewidth = 2, style = plot.style_linebr)
p2 = plot(hl2, display = display.none)
// Fill between the plot and the VIDYA line
fill(p1, p2, smoothed_value, hl2, color.new(trend_color, shadow ? 80 : 100), na)
// Plot trend change markers (up and down arrows)
plotshape(
series = trend_cross_up[1] ? smoothed_value[0] : na,
title = "Trend Up",
style = shape.labelup,
location = location.absolute,
color = color.new(up_trend_color, 50),
text = "▲",
textcolor = chart.fg_color
)
plotshape(
series = trend_cross_down[1] ? smoothed_value[0] : na,
title = "Trend Down",
style = shape.labeldown,
location = location.absolute,
color = color.new(down_trend_color, 50),
text = "▼",
textcolor = chart.fg_color
)
// }
