Grid Bot Moving Avarage StDev [p…: Free TradingView Indicator (Pine Script)

Add It to Your TradingView Chart

1Copy the scriptPress Copy script above, or the copy button on the code below.
2Open the Pine EditorOpen a TradingView chart and choose Pine Editor at the bottom of the screen.
3Paste over the templateCreate a new indicator, select all of the template text and paste. Press Save and give it a name.
4Add it to the chartPress Add to chart, then adjust the settings with the gear icon next to its name.

Source Code

123 lines of Pine Script v6 from plugins/Grid Bot [Grid range plugin] Moving Avarage StDev [psyll].pine, published under MIT. Keep the author's credit and licence lines when you reuse it.

Grid Bot [Grid range plugin] Moving Avarage StDev [psyll].pine

//@version=6
// Author: Psyll.com
// Email: info@psyll.com
// Website: https://psyll.com
// Copyright: Copyright © 2025 psyll.com. All rights reserved.

indicator('Grid Bot [Grid range plugin] Moving Avarage StDev [psyll]', overlay = false)
group_ma = 'MA'
ma_type = input.string(defval = 'EMA - Exponential Moving Average', title = 'Type', group = group_ma, display = display.none, options = ['EMA - Exponential Moving Average', 'SMA - Simple Moving Average', 'RMA - Relative Moving Average', 'HMA - Hull Moving Average', 'WMA - Weighted Moving Average', 'VWMA - Volume-Weighted Moving Average', 'DEMA - Double Exponential Moving Average', 'TEMA - Triple Exponential Moving Average', 'ZLEMA - Zero-Lag Exponential Moving Average', 'TMA - Triangular Moving Average', 'XEMA - Exponential Moving Average Optimized', 'KAMA - Kaufmans Adaptive Moving Average', 'FRAMA - Fractal Reactive Moving Average', 'DONCHIAN - Donchian', 'DONCHIAN2 - Donchian V2', 'FIBMA - Fibonacci Moving Average', 'GMMA - Guppy Multiple Moving Average'])
ma_length = input.int(500, 'Length', minval = 1, group = group_ma, display = display.none)
ma_source = input.source(defval = close, title = 'Source', group = group_ma, display = display.none)
deviations = input(2.0, title = 'Number of Deviations', group = group_ma)
offset = input.float(1, 'Offset', group = group_ma, display = display.none)
ma_tf_confirmation_wait = input.bool(defval = true, title = 'Wait for confirm', group = group_ma, inline = group_ma, display = display.none)
ma_tf_no_repaint_security = input.bool(defval = true, title = 'No repaint', group = group_ma, inline = group_ma, display = display.none)
ma_tf_barmerge_lookahead = input.bool(defval = false, title = 'Lookahead', group = group_ma, inline = group_ma, display = display.none)
ma_tf_barmerge_gaps = input.bool(defval = false, title = 'Gaps', group = group_ma, inline = group_ma, display = display.none)
ma_tf_type = input.string(title = 'Type', options = ['Static', 'Custom'], defval = 'Static', group = group_ma, display = display.none)
ma_tf_static = input.timeframe(defval = '', title = 'Static', group = group_ma, display = display.none)
ma_tf_custom = str.tostring(input.int(1, 'Custom', group = group_ma, display = display.none))
ma_tf_type_value = switch ma_tf_type
    'Static' => ma_tf_static
    'Custom' => ma_tf_custom
ma_tf_security(source) =>
    request.security(syminfo.tickerid, ma_tf_type_value, ma_tf_no_repaint_security ? source[barstate.isrealtime ? 1 : 0] : source, gaps = ma_tf_barmerge_gaps ? barmerge.gaps_on : barmerge.gaps_off, lookahead = ma_tf_barmerge_lookahead ? barmerge.lookahead_on : barmerge.lookahead_off)[ma_tf_no_repaint_security ? barstate.isrealtime ? 0 : 1 : 0]
ma() =>
    float result = 0
    if ma_type == 'EMA - Exponential Moving Average'
        result := ta.ema(ma_source, ma_length)
        result
    if ma_type == 'SMA - Simple Moving Average'
        result := ta.sma(ma_source, ma_length)
        result
    if ma_type == 'RMA - Relative Moving Average'
        result := ta.rma(ma_source, ma_length)
        result
    if ma_type == 'HMA - Hull Moving Average'
        result := ta.hma(ma_source, ma_length)
        result
    if ma_type == 'WMA - Weighted Moving Average'
        result := ta.wma(ma_source, ma_length)
        result
    if ma_type == 'VWMA - Volume-Weighted Moving Average'
        result := ta.vwma(ma_source, ma_length)
        result
    if ma_type == 'DEMA - Double Exponential Moving Average'
        result := 2 * ta.ema(ma_source, ma_length) - ta.ema(ta.ema(ma_source, ma_length), ma_length)
        result
    if ma_type == 'TEMA - Triple Exponential Moving Average'
        result := 3 * (ta.ema(ma_source, ma_length) - ta.ema(ta.ema(ma_source, ma_length), ma_length)) + ta.ema(ta.ema(ta.ema(ma_source, ma_length), ma_length), ma_length)
        result
    if ma_type == 'ZLEMA - Zero-Lag Exponential Moving Average'
        result := ta.ema(ma_source + ma_source - ma_source[(ma_length - 1) / 2], ma_length)
        result
    if ma_type == 'TMA - Triangular Moving Average'
        result := ta.sma(ta.sma(ma_source, math.ceil(ma_length / 2)), math.floor(ma_length / 2) + 1)
        result
    if ma_type == 'XEMA - Exponential Moving Average Optimized'
        mult = 2.0 / (ma_length + 1.0)
        result := mult * ma_source + (1.0 - mult) * nz(result[1], ma_source)
        result
    if ma_type == 'KAMA - Kaufmans Adaptive Moving Average'
        dist = math.abs(ma_source[0] - ma_source[1])
        signal = math.abs(ma_source - ma_source[ma_length])
        noise = math.sum(dist, ma_length)
        effr = noise != 0 ? signal / noise : 1
        sc = math.pow(effr * (0.666 - 0.0645) + 0.0645, 2)
        kama = ma_source
        result := nz(result[1]) + sc * (ma_source - nz(result[1]))
        result
    if ma_type == 'FRAMA - Fractal Reactive Moving Average'
        result := ta.ema(ma_source, ma_length)
        n3_l = (ta.highest(high, ma_length) - ta.lowest(low, ma_length)) / ma_length
        hd2_l = ta.highest(high, ma_length / 2)
        ld2_l = ta.lowest(low, ma_length / 2)
        n2_l = (hd2_l - ld2_l) / (ma_length / 2)
        n1_l = (hd2_l[ma_length / 2] - ld2_l[ma_length / 2]) / (ma_length / 2)
        dim_l = n1_l > 0 and n2_l > 0 and n3_l > 0 ? (math.log(n1_l + n2_l) - math.log(n3_l)) / math.log(2) : 0
        alpha_l = math.exp(-4.6 * (dim_l - 1))
        sc_l = alpha_l < 0.01 ? 0.01 : alpha_l > 1 ? 1 : alpha_l
        frama_l = ma_source
        result := ta.cum(1) <= 2 * ma_length ? ma_source : ma_source * sc_l + nz(frama_l[1]) * (1 - sc_l)
        result
    if ma_type == 'DONCHIAN - Donchian'
        result := math.avg(ta.lowest(ma_length), ta.highest(ma_length))
        result
    if ma_type == 'DONCHIAN2 - Donchian V2'
        kijun = math.avg(ta.lowest(ma_length), ta.highest(ma_length)) //, (open + close)/2)
        conversionLine = math.avg(ta.lowest(ma_length / 2), ta.highest(ma_length / 2))
        result := (kijun + conversionLine) / 2
        result
    if ma_type == 'FIBMA - Fibonacci Moving Average'
        fibLength = math.round(ma_length * 0.618)
        result := ta.sma(ma_source, fibLength)
        result
    if ma_type == 'GMMA - Guppy Multiple Moving Average'
        shortMa = ta.sma(ma_source, math.round(ma_length * 0.5))
        longMa = ta.sma(ma_source, ma_length)
        result := (shortMa + longMa) / 2
        result
    ma_tf_security(result)
width_min = input.float(0, 'Min width', group = group_ma, display = display.none)
width_max = input.float(99999, 'Max width', group = group_ma, display = display.none)
width_min_half = width_min / 2
width_max_half = width_max / 2
display_group = 'Display ##################################################'
price_color = input.color(color.black, 'Candles color', display = display.none, group = display_group)
plotcandle(open, high, low, close, color = price_color, bordercolor = price_color, wickcolor = price_color, display = display.pane)
ma = ma()
grid_high = ma * (1 + deviations)
grid_low = ma * (1 - deviations)
grid_middle = (grid_high + grid_low) / 2
if grid_high - grid_low < width_min
    grid_high := grid_middle + width_min_half
    grid_low := grid_middle - width_min_half
    grid_low
if grid_high - grid_low > width_max
    grid_high := grid_middle - width_max_half
    grid_low := grid_middle + width_max_half
    grid_low
plot(grid_high, 'High', color.green, display = display.all)
plot(grid_middle, 'Middle', color.silver, display = display.pane)
plot(grid_low, 'Low', color.red, display = display.all)

Overview

Grid Bot Moving Avarage StDev [psyll] supports 17 different moving average algorithms, including EMA, SMA, Hull, VWMA, and KAMA, along with custom timeframe security requests and boundary width constraints. Intended to run in a separate pane, it outputs range data to coordinate grid spacing.

17 selectable moving average types
Standard deviation volatility range calculations
Multi-timeframe security fetching with non-repainting toggle
Configurable minimum and maximum range width boundaries

Details

Published by

cullyk on GitHub

Code credit

Copyright, as written in the script's header

Type

Indicator, Pine Script v6

Draws

Separate pane below the chart

Markets

Any symbol

Timeframes

Any timeframe

Risk Notes

Reads higher-timeframe data with lookahead on, so the history can show signals that were not there in real time

File

plugins/Grid Bot [Grid range plugin] Moving Avarage StDev [psyll].pine

Repository

github.com/cullyk/Grid-Bot. See its other scripts in the library

Settings

The inputs you can change from the gear icon on the chart. Defaults are the author's.

Setting	Type	Default	Variable
Type	`string`	`EMA - Exponential Moving Average`	`ma_type`
Length	`int`	`500`	`ma_length`
Source	`source`	`close`	`ma_source`
Number of Deviations	`float`	`2.0`	`deviations`
Offset	`float`	`1`	`offset`
Wait for confirm	`bool`	`true`	`ma_tf_confirmation_wait`
No repaint	`bool`	`true`	`ma_tf_no_repaint_security`
Lookahead	`bool`	`false`	`ma_tf_barmerge_lookahead`
Gaps	`bool`	`false`	`ma_tf_barmerge_gaps`
Type	`string`	`Static`	`ma_tf_type`
Static	`timeframe`		`ma_tf_static`
Custom	`int`	`1`	`Custom`

Show all 15 settings

Setting	Type	Default	Variable
Min width	`float`	`0`	`width_min`
Max width	`float`	`99999`	`width_max`
Candles color	`color`	`color.black`	`price_color`

Third-party code. ForexR did not write, test or endorse this script, and the summary above was generated automatically from its code and README. Indicators describe the past, and a strategy's backtest can look better than live trading, especially when a script repaints. Check it in the Strategy Tester and on a demo account before you rely on it.

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