Sigmoid Alpha Bands | NAL1. Overview
Sigmoid Alpha Bands | NAL is an adaptive trend and volatility framework built around a sigmoid-weighted EMA baseline and dynamically adjusted volatility bands.
Instead of smoothing price with a fixed alpha, the indicator modifies its responsiveness using a selected market feed. Momentum, volatility, volume, or price disparity can control how quickly the baseline adapts to changing conditions.
The surrounding bands can also respond asymmetrically to bullish and bearish return shocks. This allows the upper and lower boundaries to develop independently rather than remaining equally spaced around the baseline.
2. Calculation
The indicator begins by selecting the market variable used to control the baseline’s adaptive smoothing weight.
Momentum measures changes in RSI, volatility measures changes in ATR, volume measures changes in smoothed volume, and disparity measures changes in price relative to its EMA.
sigmoidFeed = switch sigFeed
"Momentum" => ta.change(ta.rsi(src, modLen), changeL)
"Volatility" => ta.change(ta.atr(modLen), changeL)
"Volume" => ta.change(ta.ema(volume, modLen), changeL)
"Disparity" => ta.change(src / ta.ema(src, modLen), changeL)
The selected feed is passed through a sigmoid function, converting it into a bounded adaptive weight.
That weight modifies the standard EMA alpha. When the sigmoid weight increases, the baseline can respond more quickly. When it decreases, the baseline becomes more stable.
sigmoidWeight = sigmoid_function(sigmoidFeed)
baseAlpha = 2.0 / (emaLen + 1.0)
adaptiveAlpha = f_clamp(baseAlpha * (0.5 + sigmoidWeight), 0.01, 1.0)
The final adaptive baseline is calculated recursively using the changing alpha.
sigmoid_ema = f_sigmoid_ema(src, sigmoidFeed, sigLen)
The indicator then calculates its base volatility using one of four methods: standard deviation, ATR, mean absolute deviation, or median absolute deviation.
volatilityRaw = switch volFeed
"SD" => ta.stdev(src, volLen)
"ATR" => ta.atr(volLen)
"MeanAD" => ta.dev(src, volLen)
"MedianAD" => f_median_ad(src, volLen)
This raw volatility value is also processed through a sigmoid-adaptive smoothing layer. The result becomes the symmetric volatility foundation used by the bands.
volatilityFeed = ta.change(volatilityRaw / nz(ta.ema(volatilityRaw, volLen), volatilityRaw), changeL)
volatility = f_sigmoid_ema(volatilityRaw, volatilityFeed, volLen)
When asymmetric bands are enabled, positive and negative log-return shocks are separated into bullish and bearish variance components.
bullShock = math.pow(math.max(ret, 0.0), 2.0)
bearShock = math.pow(math.max(-ret, 0.0), 2.0)
totalShock = bullShock + bearShock
Each shock component is adaptively smoothed and compared with total variance. This produces separate upper and lower volatility multipliers.
The multipliers are constrained around their longer-term average so the bands can adapt without becoming unstable.
upperVol = math.max(nz(symmetricVol, syminfo.mintick) * upperMultAdj, syminfo.mintick)
lowerVol = math.max(nz(symmetricVol, syminfo.mintick) * lowerMultAdj, syminfo.mintick)
The final bands are positioned around the sigmoid-adaptive baseline.
upperBand = sigmoid_ema + finalUpper * volMul
lowerBand = sigmoid_ema - finalLower * volMul
A bullish state is established when price closes above the upper band. A bearish state is established when price closes below the lower band. While price remains between the boundaries, the existing state is preserved.
if close > upperBand
NAL := 1
if close < lowerBand
NAL := -1
3. Key Features
Sigmoid-weighted adaptive EMA baseline.
Selectable momentum, volatility, volume, or disparity adaptation feed.
Multiple volatility calculation methods.
Optional asymmetric bullish and bearish volatility bands.
Independent modeling of positive and negative return shocks.
Controlled asymmetry through long-term multiplier normalization.
State-based candle coloring, layered volatility hulls, glow effects, and directional fills.
4. Use
Sigmoid Alpha Bands is designed to identify when price expands beyond an adaptively smoothed volatility structure.
A close above the upper boundary reflects bullish expansion beyond the current baseline and volatility regime. A close below the lower boundary reflects bearish expansion beneath that structure.
The asymmetric mode allows the indicator to recognize that bullish and bearish volatility do not always develop with equal intensity. As market pressure changes, each side of the channel can adjust independently while remaining anchored to the same adaptive baseline.
This indicator is designed as a specialized component within a complete strategy architecture. Its role is to isolate the interaction between adaptive trend, changing volatility, and directional return pressure. Its full value emerges through the way this information is integrated into a broader decision framework.
Indicator
Quantile Cloud [MiesOnCharts]Quantile Cloud
This indicator draws the recent value zone using order statistics instead of a moving average and standard deviation. Over a rolling window, it collects every close and finds the upper and lower quantile of that sample, plus the median as a centerline. The cloud sits between the two quantiles.
Why quantiles instead of mean and sigma bands?
A single outlier bar can only shift a percentile rank by one spot, so the cloud stays put after a shock instead of ballooning the way Bollinger style bands do. What you get is a picture of where price has actually spent its time during the window, not a statistical estimate that a spike can distort.
How to read it:
While price stays inside the cloud, it's behaving normally relative to its recent range, and the prior regime holds. No new signal fires just from wandering around inside the value zone. A close above the upper quantile or below the lower quantile means price is doing something it has rarely done recently, and that flips the regime. The median line changes color with the regime (green for up, red for down, gray when neutral), and triangles mark the actual flip bars.
Settings:
Window (bars): how many recent closes make up the sample. Longer windows give a slower, more stable value zone; shorter windows react faster but flip more often.
Upper Quantile % / Lower Quantile %: how wide the cloud is. Pushing these toward the extremes (e.g. 99/1) makes the cloud wider and signals rarer; pulling them toward the middle makes it tighter and more sensitive.
Includes alerts for both upside and downside breaks of the value zone, so you can get notified without watching the chart.
Disclaimer
The indicator provided is not financial advice. Always conduct your own research and consider multiple factors before making trading decisions. Trade at your own risk. Indicator
Funding Rate & OI Radar [StrixEDGE]What It Does
Funding Rate & OI Radar is a multi-symbol derivatives dashboard that consolidates funding rate intensity, open interest momentum across three timeframes, and price-OI divergence signals into a single on-chart table. It is designed for perpetual futures traders who need to read market positioning at a glance — without switching tabs or charts.
The indicator tracks up to 5 perpetual contract symbols simultaneously, surfaces extreme funding conditions as they develop, and flags structurally weak rallies or drops where price and open interest are moving in opposite directions.
Core Features
Funding Rate with Color Intensity
Funding rate values are color-graded by severity — from dim neutral tones near zero, through elevated orange, to extreme red (longs paying) or bright green (shorts paying). Extreme readings trigger a highlighted cell background so they stand out immediately during fast-moving markets.
Open Interest Change — 1H / 4H / 24H
Three separate OI delta columns show how positioning is shifting across intraday, swing, and daily windows. Each cell includes a directional arrow (▲ ▼ ►) and percentage change, color-coded against your configured alert threshold. This gives you a layered read: is OI building across all timeframes, or only spiking on the short window?
Price-OI Divergence Detection
The SIGNAL column cross-references 24H price change against 24H OI change and classifies the move:
- WEAK▲ — Price rising but OI declining. Rally lacks new capital commitment. Potential short squeeze or exhaustion move.
- WEAK▼ — Price falling but OI rising. New positions opening into the drop. Potential capitulation trap or forced selling.
- STRONG▲ — Price and OI both rising. New money entering on the long side. Structurally supported move.
- STRONG▼ — Price and OI both falling. Positions closing out. Orderly deleveraging.
- NEUTRAL — No meaningful divergence.
Weak signals receive a highlighted background row to ensure they are not missed.
Multi-Symbol Table
Monitor BTC, ETH, SOL, and two custom perpetual contracts of your choice — all rendered in a single dashboard. The table includes configurable column visibility, so you can strip it down to just FR + divergence, or run the full 8-column view.
Aggregate Sentiment Footer
The bottom row averages funding rates across all active symbols and classifies the overall market into one of seven sentiment tiers — from 🟢 EXTREME FEAR through ⚪ NEUTRAL to 🔴 EXTREME GREED. A fast, blunt read on whether the derivatives market is skewing overleveraged in either direction.
Alerts
Four built-in alert conditions, all routed through PulseWire's native alert system:
- Extreme Funding Rate — Any tracked symbol's absolute FR exceeds your configured threshold (default: 0.05%/8h).
- OI Surge — Any symbol's 1H OI change exceeds your OI alert threshold (default: 5%).
- OI-Price Divergence — A WEAK▲ or WEAK▼ signal fires on any tracked symbol.
- Sentiment Extreme — Aggregate average FR across all symbols reaches the extreme zone.
Data Sources & Configuration
The indicator supports two modes for funding rate data:
- Ticker Mode (default) — Pulls funding rate from your exchange's dedicated FR data feed using a configurable ticker suffix (default: `_FR`). Requires the exchange to publish FR data through PulseWire.
- Basis Proxy Mode — Estimates the implied 8-hour funding rate from the perpetual-spot price spread: `(Perp − Spot) / Spot / 3`. Useful when direct FR tickers are unavailable. Note: this is an approximation, not the actual settlement rate.
Open interest data is fetched via configurable OI ticker suffix (default: `_OI`).
Important: Ticker formats vary across exchanges and PulseWire data providers. If columns display "N/A", adjust the OI/FR suffix inputs under 🔌 Data Sources to match your exchange's naming convention. Consult your exchange's PulseWire symbol search for the correct format.
Settings Overview
📊 Symbols — Exchange selector, 3 default symbols (BTC/ETH/SOL perpetuals), 2 optional custom slots.
🔌 Data Sources — OI suffix, FR suffix, FR method toggle, spot suffix override for basis proxy.
🚨 Thresholds — Extreme FR level, elevated FR level, OI alert percentage. These control both color intensity breakpoints and alert trigger levels.
🎨 Display — Table position (8 positions), text size (Tiny / Small / Normal / Large).
📋 Columns — Individual toggles for Price, Price Δ24H, Funding Rate, OI Δ1H, OI Δ4H, OI Δ24H, Divergence Signal, and Sentiment Footer. Disable any column you don't need to keep the table compact.
Technical Notes
- Uses 25 `request.security()` calls across 5 symbols (well within Pine Script's 40-call limit).
- OI changes are calculated from actual multi-timeframe requests (60min, 240min, Daily) — not bar-count estimates — so they remain accurate regardless of your chart's timeframe.
- Table renders only on the last bar (`barstate.islast`) for performance.
- Inactive custom symbol slots (left blank) fall back to the primary ticker internally and are hidden from the table.
How to Read It
Open the indicator on any chart. The table appears as an overlay (default: top-right corner). Scan left to right:
1. Symbol — Which asset.
2. Price — Current perpetual price.
3. Δ24H — Daily price change. Green = up, red = down.
4. FR /8h — Current funding rate per 8-hour interval. Bright color = elevated. Highlighted background = extreme.
5. OI Δ1H / 4H / 24H — Open interest change with directional arrows. Look for alignment across timeframes (all rising = strong conviction) or divergence (1H spiking, 24H flat = short-term noise).
6. SIGNAL — Divergence classification. WEAK▲ and WEAK▼ are the actionable signals — they indicate structural fragility in the current move.
7. Sentiment — Aggregate market tilt from combined funding rates.
Use Cases
- Scalpers & intraday traders — Monitor 1H OI spikes alongside funding rate to detect short-squeeze or long-squeeze setups forming in real time.
- Swing traders — Use the divergence signal column to filter entries. Avoid longing into WEAK▲ conditions; avoid shorting into WEAK▼.
- Portfolio monitors — Track funding costs across multiple positions simultaneously. Elevated aggregate sentiment warns of crowded positioning before liquidation cascades.
Complementary Tools
Designed to pair with liquidity heatmaps and liquidation level estimators. Funding rate tells you who is paying whom. OI tells you how much is at stake. Liquidity maps tell you where the pressure points are. Together, they give a full derivatives positioning read. Indicator
Zero-Lag GARCH Bands | NAL1. Overview
Zero-Lag GARCH Bands | NAL is an adaptive volatility band indicator built from a Zero-Lag EMA baseline and an optimized GARCH-style volatility engine.
The indicator does not use a standard fixed-width channel. Instead, it estimates market variance through a recursive GARCH framework, smooths that volatility with a Zero-Lag EMA, and uses the result to create dynamic upper and lower bands around price structure.
The purpose of the indicator is to identify when price escapes a volatility-adjusted regime boundary, while allowing the band width to adapt to the underlying variance environment.
2. Calculation
The indicator starts by estimating volatility from lagged log returns. These returns are squared to create a variance component, which becomes the foundation of the GARCH model.
GARCH_LogReturn = math.log(close / close )
GARCH_SquaredLogReturn = math.pow(GARCH_LogReturn, 2.0)
GARCH_RealizedVariance = ta.sma(GARCH_SquaredLogReturn, GARCH_Lookback)
The script then searches through possible coefficient weights to find a beta/lambda value that better fits recent realized variance behavior. A second optimization loop is used to estimate gamma, which controls the long-run variance contribution.
These optimized coefficients are combined into a GARCH-style variance model using three components: long-run variance, recent shock variance, and lagged variance.
GARCH_Variance =
GARCH_Gamma * GARCH_LongRunVariance +
GARCH_Alpha * GARCH_SquaredLogReturn +
GARCH_Beta * GARCH_LaggedVariance
After the variance estimate is created, it is smoothed using a Zero-Lag EMA. This gives the volatility engine a faster response while still reducing noise.
GARCH_ProjectedVariance = f_zlema(GARCH_Variance, GARCH_SmoothLen)
GARCH_Volatility = math.sqrt(math.max(GARCH_ProjectedVariance, 0.0))
The baseline is also built with a Zero-Lag EMA, applied after a light EMA pre-smoothing step. This creates the central reference line for the band structure.
The final bands are created by scaling the Zero-Lag GARCH volatility against the selected source and band pressure setting. Higher band pressure creates a tighter band, while lower pressure allows the band structure to expand.
upperBand = baseline + (baseline_src / band_pressure) * GARCH_VolatilityMultiplier
lowerBand = baseline - (baseline_src / band_pressure) * GARCH_VolatilityMultiplier
A bullish state triggers when price closes above the upper band. A bearish state triggers when price closes below the lower band. When price remains inside the bands, the previous regime is held.
3. Key Features
Zero-Lag EMA baseline for reduced-lag price structure.
Optimized GARCH-style volatility engine.
Adaptive variance model using shock, lagged, and long-run components.
Zero-Lag smoothing applied to projected volatility.
Dynamic upper and lower volatility bands.
Band pressure control for adjusting channel tightness.
State-based candle coloring, band coloring, glow effect, and directional fills.
4. Use
Zero-Lag GARCH Bands is designed to identify when price begins escaping its volatility-adjusted structure. A close above the upper band reflects bullish expansion, while a close below the lower band reflects bearish expansion.
The GARCH engine gives the indicator a deeper volatility layer than a standard ATR or deviation channel. Instead of only measuring recent range, it models variance behavior and projects that into the band structure.
This indicator is best used as a specialized module within a complete strategy framework. Its role is to isolate volatility-adjusted regime expansion, where price is evaluated against a dynamic variance boundary rather than a static channel. The full value comes from how this volatility regime signal is integrated into a broader process for timing, structure, and execution.
Indicator
Adpative Dual Cloud | NAL1. Overview
Adaptive Dual Cloud | NAL is a dual-baseline trend cloud built from two separate smoothing structures: a Kijun-style midpoint baseline and an ALMA baseline. Instead of relying on a single moving average or one volatility model, the indicator builds an adaptive cloud around both baselines and only confirms direction when price escapes the full combined structure.
The purpose of the indicator is to create a stricter trend envelope. The Kijun side captures broader structural balance, while the ALMA side adds a smoother adaptive layer. The final upper and lower cloud boundaries are selected from both systems, forcing price to clear the stronger side of the cloud before a bullish or bearish state is confirmed.
2. Calculation
The indicator starts by creating two independent baselines. The first baseline is a Kijun-style midpoint calculated from the highest and lowest values over the selected lookback. This represents a structural equilibrium zone.
kijun_sen = math.avg(ta.lowest(cloudLen1), ta.highest(cloudLen1))
The second baseline uses ALMA, giving the cloud a smoother weighted-average component with adjustable sigma and offset. This adds a more refined smoothing layer beside the Kijun structure.
alma_base = ta.alma(srcSeries, cloudLen2, cloud2Off, cloud2Sig)
The indicator then calculates volatility using a selectable deviation engine. The volatility source can be price, the residual between price and the cloud average, or the cloud structure itself. This allows the band width to be built from different layers of market behavior.
VolSrc = switch devSrc
"Price" => srcSeries
"Residuals" => srcSeries - math.avg(alma_base, kijun_sen)
"Cloud" => math.avg(alma_base, kijun_sen)
The volatility engine supports multiple deviation types, including standard deviation, mean absolute deviation, median absolute deviation, exponential deviation, ATR, linear regression deviation, Hull deviation, FRAMA deviation, Kauffman adaptive deviation, Gaussian deviation, and quantile deviation.
After volatility is calculated, adaptive upper and lower bands are created around both baselines.
upper_kijun = kijun_sen + vol * multi_u
lower_kijun = kijun_sen - vol * multi_l
upper_alma = alma_base + vol * multi_u
lower_alma = alma_base - vol * multi_l
The final cloud uses the highest upper boundary and the lowest lower boundary. This makes the signal more selective because price must break beyond the combined cloud, not just one individual baseline.
upper = math.max(upper_kijun, upper_alma)
lower = math.min(lower_kijun, lower_alma)
A bullish state triggers when price closes above the final upper cloud. A bearish state triggers when price closes below the final lower cloud. When price remains inside the cloud, the previous state is held.
3. Key Features
Dual-baseline cloud using Kijun structure and ALMA smoothing.
Adaptive upper and lower bands built from selectable volatility models.
Multiple deviation engines for different volatility interpretations.
Selectable volatility source: price, residuals, or cloud structure.
Final cloud requires price to clear the combined upper or lower boundary.
State-based candle coloring, cloud coloring, glow effect, and directional fills.
4. Use
Adaptive Dual Cloud is designed to identify when price escapes a combined structural and smoothed volatility envelope. A close above the upper cloud reflects bullish expansion beyond both baseline systems, while a close below the lower cloud reflects bearish expansion below the combined structure.
The indicator is intentionally stricter than a single-baseline channel. By combining a Kijun-style midpoint with an ALMA baseline, it creates a cloud that filters more of the internal noise before confirming a directional regime.
This indicator is best used as a specialized module within a complete strategy framework. Its role is to isolate a cloud-based volatility and structure layer, where price must prove strength or weakness against more than one adaptive baseline. The full value comes from how this regime signal is integrated into a broader process for timing, structure, and execution.
Indicator
Volatility Halo | NAL1. Overview
Volatility Halo | NAL is an adaptive volatility band indicator built from a Zero-Lag EMA baseline, ATR band structure, and a recursive GARCH-style volatility regime multiplier.
The indicator does not use fixed-width bands. Instead, it starts with ATR-based bands and then adjusts their width using a projected volatility regime model. This allows the bands to respond differently when market volatility is expanding, contracting, or stabilizing.
2. Calculation
The indicator starts by calculating a Zero-Lag EMA baseline from the selected source. This baseline acts as the central trend reference, helping reduce lag compared to a standard EMA while still keeping the structure smooth.
float baseline = f_zlema(src, baseline_len)
float ATR_Value = ta.atr(ATR_Len)
The ATR value is then multiplied by the user-defined ATR multiple. This forms the base volatility distance used for the upper and lower bands.
The more advanced part of the indicator is the recursive GARCH-style regime multiplier. It begins by calculating log returns and converting them into shock variance. A long-run variance estimate is then built from recent shock variance.
GARCH_LogReturn = close > 0.0 and close > 0.0 ? math.log(close / close ) : 0.0
GARCH_ShockVariance = math.pow(GARCH_LogReturn, 2.0)
GARCH_LongRunVariance = ta.ema(GARCH_ShockVariance, GARCH_LongRunLen)
The model recursively updates conditional variance using three components: recent shock variance, long-run variance, and previous conditional variance. When adaptive coefficients are enabled, the script searches for coefficient weights that better fit recent variance behavior.
GARCH_ConditionalVariance :=
GARCH_Gamma * GARCH_LongRunVariance +
GARCH_Alpha * GARCH_ShockVariance +
GARCH_Beta * GARCH_PreviousConditionalVariance
The conditional variance is then projected and converted into a volatility estimate. This volatility is compared against its own regime baseline to create a volatility regime multiplier. The multiplier is clamped between a minimum and maximum value, preventing the bands from becoming too narrow or too wide.
GARCH_Volatility = math.sqrt(math.max(GARCH_ProjectedVariance, 0.0))
GARCH_RegimeMultiplierRaw = GARCH_Volatility / GARCH_RegimeBase
GARCH_RegimeMultiplier = f_clamp(GARCH_RegimeMultiplierSmooth, GARCH_MinMult, GARCH_MaxMult)
The final band width is created by combining ATR with the GARCH regime multiplier. The upper and lower bands are placed around the Zero-Lag EMA baseline.
hybridBandWidth = ATR_Value * ATR_Mult * GARCH_RegimeMultiplier
upperBand = baseline + hybridBandWidth
lowerBand = baseline - hybridBandWidth
A bullish state triggers when price closes above the upper band. A bearish state triggers when price closes below the lower band. When price remains inside the bands, the previous state is held.
3. Key Features
Zero-Lag EMA baseline for reduced-lag trend structure.
ATR-based volatility bands.
Recursive GARCH-style conditional variance model.
Adaptive volatility regime multiplier.
Bands expand or contract based on projected volatility conditions.
State-based candle coloring, band coloring, glow effect, and regime fills.
4. Use
Volatility Halo is designed to identify moments where price begins escaping its volatility-adjusted structure. A close above the upper band reflects bullish expansion, while a close below the lower band reflects bearish expansion.
The adaptive volatility engine allows the bands to shift with the underlying market environment, making the signal more responsive to changes in pressure and regime.
This indicator is best used as a specialized module within a complete strategy framework. Its real strength appears when it is combined with a broader process for reading market behavior, timing, and risk. The full edge comes from how the signal is integrated, not from the signal existing in isolation.
Indicator
Perpetual Basis Drift Map [AGPro Series]Perpetual Basis Drift Map
🧠 Core Idea
Is the perpetual market quietly drifting away from spot, or is the basis relationship compressing back toward neutral?
📌 Overview / What it does
Perpetual Basis Drift Map is a crypto derivatives context tool designed to monitor how the active perpetual or futures market behaves against a matching spot reference.
The script compares the active chart price with an automatically selected spot reference, measures basis percentage, basis drift, normalized basis z-score, drift velocity, persistence, and trend context. It converts that relationship into an open three-rail basis drift meter, state labels, right-side tags, alerts, and an AG Pro dashboard.
It does not read official funding payments, automate trades, predict future price direction, or promise that basis must mean-revert. It is a structured visual map for interpreting perpetual premium, perpetual discount, basis expansion, basis compression, reset, and spot-reference mismatch conditions.
🎯 Purpose & Design Philosophy
This script was built to separate basis drift from generic funding or premium talk.
Funding pressure can be noisy, and a raw premium number is often not enough. Traders need to know whether the relationship between perp/futures and spot is widening, compressing, persisting, or simply resetting.
The design goal is to make basis behavior visible as a chart story, not just a number in a panel.
⚡ Why This Script Is Different
Most tools show a spread or premium value and leave the interpretation to the user.
This script does NOT treat basis as a simple buy or sell signal, does NOT claim that premium must reverse, and does NOT hide reference mismatch risk.
Instead, it maps the basis relationship into states: Positive Drift, Negative Drift, Basis Expansion, Basis Compression, Reset, and Check Spot Ref, while the chart labels use Premium Drift, Discount Drift, Spread Expansion, and Basis Compression for faster visual reading. It uses spot-reference comparison, baseline drift, z-score, velocity, persistence, and trend context together.
⚙️ Methodology
1. Context Detection
The script builds a spot reference from the active chart base currency, selected exchange, and selected quote.
2. Reference Mapping
It compares the active market against the spot reference and calculates basis percentage.
3. Reaction Evaluation
The model evaluates basis drift from baseline, normalized basis z-score, drift velocity, persistence, and trend context.
4. Visual Output
The result is shown as a compact open basis drift meter, centered meter label, right-side tags, event labels, and dashboard panel.
🗺️ How to Read the Chart
The basis drift meter separates the current read into three visible layers: state rail, basis value rail, and pressure score rail. It is intentionally open-ended rather than a closed corridor, so the visual story feels different from zone-first tools.
Labels mark state changes such as Premium Drift, Discount Drift, Spread Expansion, and Basis Compression. Optional compact pulse markers add additional context when premium, discount, expansion, or compression pressure appears without turning the script into a signal engine.
Colors communicate context:
• Teal = positive/perp-premium drift pressure
• Pink = negative/perp-discount drift pressure
• Yellow = spread expansion or reference warning
• Indigo = compression/reset regime
The panel summarizes state, score, basis, basis z-score, velocity, persistence, direction, quality, spot reference, trend, and meter values.
🚦 Signals & States
• Positive Drift → perpetual/futures market is drifting above the spot reference
• Negative Drift → perpetual/futures market is drifting below the spot reference
• Basis Expansion → basis deviation and drift velocity are widening
• Basis Compression → basis deviation is compressing back toward neutral
• Reset → no active drift state is strong enough to dominate the read
• Check Spot Ref → selected spot reference appears mismatched or unavailable
🔔 Alerts Logic
Alerts trigger when the script transitions into selected basis states.
Positive Basis Drift alerts mark meaningful upward perp-versus-spot drift.
Negative Basis Drift alerts mark meaningful downward perp-versus-spot drift.
Basis Expansion alerts mark widening basis deviation and drift velocity.
Basis Compression alerts mark movement back toward a neutral basis relationship.
Alerts are attention markers, not trade instructions.
🧩 Confluence Logic
The strongest context appears when multiple components align:
Basis percentage + normalized basis z-score + drift velocity + persistence + trend context.
When basis widens and persists, the relationship may deserve closer attention. When basis compresses, the market may be returning toward a more neutral perp-versus-spot condition.
📊 When to Use
• Crypto perpetual and futures charts
• Markets where spot reference comparison is meaningful
• Perp/spot monitoring on BTC, ETH, and liquid crypto pairs
• Basis expansion, basis compression, and drift-context analysis
• Sessions where derivatives premium or discount behavior matters
⚠️ When NOT to Use
• Symbols with poor spot-reference alignment
• Illiquid markets with unreliable pricing
• Spot-only charts if the user expects a derivatives basis story
• Extreme news events where spread behavior can become unstable
• Markets where the active symbol and selected reference are not comparable
🎛️ Key Inputs
• Auto Spot Reference → automatically builds a matching spot reference
• Basis Baseline Length → controls how quickly the normal basis relationship adapts
• Basis Normalization Lookback → controls how unusual basis drift must be
• Drift Velocity Lookback → measures whether basis is widening or tightening
• Persistence Window → measures whether basis behavior continues across bars
• Reference Mismatch Guard % → prevents mismatched references from being interpreted as real basis drift
• Visual Settings → control meter projection, labels, right-side tags, and font sizes
🖥️ Interface & Visual Design
The interface is designed around a premium chart-first story.
The basis drift meter provides the main visual anchor. Centered meter text explains the state without relying on weak transparent labels or a large corridor box. Right-side tags keep the current state, basis, and score visible near the active price area.
The panel follows the AG Pro standard with a merged blue header row, adjustable location, adjustable theme, and adjustable font size.
🧪 Practical Usage Workflow
1. Apply the script to a crypto perpetual or futures chart.
2. Keep Auto Spot Reference enabled for the first pass.
3. Confirm the Spot Ref row matches the active market base currency.
4. Read State, Score, Basis, Basis Z, and Velocity.
5. Inspect whether basis is drifting, expanding, compressing, or resetting.
6. Confirm the read with broader market structure, liquidity, volatility, and risk management.
🔍 Interpretation Guidelines
Positive basis drift can show perp premium building, but it does not automatically mean price must fall.
Negative basis drift can show perp discount building, but it does not automatically mean price must rise.
Basis expansion is a context marker, not a trade instruction.
Basis compression can indicate normalization, but normalization does not guarantee direction.
🚫 What This Script Is NOT
This script is not a prediction engine.
This script is not financial advice.
This script is not an auto trading system.
This script is not a guaranteed signal engine.
This script does not read official funding payments directly.
This script does not claim that basis drift must immediately reverse.
⚠️ Limitations & Transparency
The script estimates basis from active-symbol versus spot-reference price behavior.
Reference quality matters. If the selected reference is wrong or unavailable, the script shows Check Spot Ref rather than presenting the spread as valid basis drift.
Different exchanges, contract types, liquidity conditions, and timeframes can produce different basis behavior.
Very low basis values can be visually clean but may not produce a dramatic story.
🧠 Market Context Notes
Perpetual basis can help traders understand whether derivatives pricing is leaning above or below spot.
The value of this tool is strongest when combined with structure, volatility, liquidity, open interest, and disciplined risk management.
Basis tells context. It does not create certainty.
🧾 Use Case Examples
When a perpetual chart trades persistently above spot and basis velocity expands, the script may classify Positive Drift or Basis Expansion.
When a perpetual chart trades persistently below spot and basis velocity expands downward, the script may classify Negative Drift.
When basis returns toward its baseline, Basis Compression can help show normalization.
🧱 System Philosophy
Perpetual Basis Drift Map follows the AGProLabs principle of building decision-support maps rather than prediction tools.
The script is designed to make hidden derivatives context easier to see, not to replace judgment.
🔐 Non-Promise Statement
No basis model can guarantee future price direction.
No drift score removes uncertainty.
This tool helps organize context; it does not create certainty.
📉 Risk Disclosure
Trading involves risk.
Crypto derivatives can be highly volatile and may involve leverage, liquidation risk, exchange risk, funding-cost changes, and rapid market movement.
This script is for educational and analytical purposes only.
It does not provide financial advice or guaranteed trading outcomes.
Users remain responsible for their own decisions.
📚 Educational Note
Use the script as a learning layer for understanding how perpetual premium, perpetual discount, basis drift, basis velocity, and spot-reference behavior can combine into a cleaner derivatives-context read.
Indicator
Indicator
Funding Carry Stress Map [AGPro Series]Funding Carry Stress Map
🧠 Core Idea
Is the market carrying a hidden derivatives premium or discount that is becoming crowded enough to matter?
📌 Overview / What it does
Funding Carry Stress Map is a crypto derivatives context tool designed to estimate when perpetual-style premium, carry pressure, basis drift, and volatility-adjusted crowding are becoming structurally relevant on the chart.
The script compares the active chart symbol against a user-selected spot reference, builds a smoothed carry baseline, measures premium/discount deviation, evaluates persistence, and converts the result into a visual carry stress framework. It produces a projected carry stress corridor, state labels, right-side tags, alerts, and a compact AG Pro dashboard.
It does not read official exchange funding payments, automate trades, predict future price direction, or promise that elevated carry stress must reverse. It is a structured analytical layer for reading derivatives pressure, premium imbalance, discount imbalance, carry squeeze risk, and cooling behavior.
🎯 Purpose & Design Philosophy
This script was built to fill a gap in the public AGProLabs lineup: most chart tools focus on trend, volume, support/resistance, momentum, or volatility. Crypto traders also need a clean way to think about derivatives-side pressure without turning the chart into a noisy data terminal.
The design goal is to make carry stress visible as a chart story. Instead of showing only a raw spread number, the script asks whether premium/discount is large, unusual, persistent, and supported by enough volatility context to deserve attention.
It is built for traders who want to monitor crowded long carry, crowded short carry, squeeze risk, and stress cooling while still making their own decisions from broader market context.
⚡ Why This Script Is Different
Most tools either show generic premium/basis values or treat funding-related pressure as a simple bullish/bearish signal.
This script does NOT claim to know the next candle, does NOT treat carry pressure as an automatic reversal signal, and does NOT depend on official funding-rate feeds that may not be available on every chart.
Instead, it converts spot-vs-active-symbol premium behavior into a structured carry stress map: premium size, normalized basis deviation, persistence, volatility rank, price reaction, and cooling behavior are combined into one visual decision-support framework.
⚙️ Methodology
1. Context Detection
The script reads the active chart price and a spot reference. By default, it automatically builds that reference from the chart base currency, selected exchange, and selected quote.
2. Reference Mapping
The premium series is smoothed into a carry baseline. The script then measures how far current premium/discount has moved away from that baseline.
3. Reaction Evaluation
The model evaluates basis z-score, absolute premium percentage, persistence across a recent window, volatility rank, and whether price is starting to reject the crowded side.
4. Visual Output
The result is displayed as a carry stress corridor, event labels, right-side tags, and a dashboard panel showing state, stress score, premium, basis z-score, persistence, volatility rank, and current interpretation.
🗺️ How to Read the Chart
The carry stress corridor represents the active price area where derivatives-side pressure is being monitored.
Labels mark important state transitions such as premium stress, discount stress, carry squeeze risk, and carry cooling.
Colors communicate state:
• Pink = positive carry / long-crowding stress
• Teal = negative carry / short-crowding stress
• Yellow = squeeze-risk reaction
• Indigo = cooling or neutralization
The panel summarizes the current condition so the user can quickly read whether carry pressure is low, watch-level, elevated, or extreme.
🚦 Signals & States
• Premium Stress → positive premium/carry pressure is active and persistent enough to monitor
• Discount Stress → negative premium/discount pressure is active and persistent enough to monitor
• Carry Squeeze Risk → elevated carry pressure is present while price begins reacting against the crowded side
• Carry Cooling → previously meaningful carry stress has faded below the model’s cooling zone
• Reset → no active carry imbalance is strong enough to dominate the current read
🔔 Alerts Logic
Alerts trigger when the internal state changes into one of the selected alert conditions.
Premium Stress alerts mark a transition into meaningful positive carry pressure.
Discount Stress alerts mark a transition into meaningful negative carry pressure.
Carry Squeeze Risk alerts mark a transition where crowded carry pressure and adverse price reaction align.
Carry Cooling alerts mark a transition where carry stress has materially faded.
Alerts are attention markers, not trade instructions.
🧩 Confluence Logic
The strongest context appears when multiple components align:
When premium size + basis z-score + persistence + volatility rank align, the carry stress score becomes more meaningful.
When that elevated score also appears with price rejection against the crowded side, the context shifts from simple premium/discount monitoring into potential squeeze-risk awareness.
📊 When to Use
• Crypto perpetual and futures markets where a spot reference can be selected
• Perpetual charts compared against their closest spot market
• High-interest crypto pairs where basis and carry pressure can influence behavior
• Volatile sessions where crowded positioning may matter more than usual
• Market regimes where traders want to monitor long-crowd or short-crowd pressure
⚠️ When NOT to Use
• Illiquid symbols with unreliable spot or futures pricing
• Charts where the selected spot reference is not comparable to the active symbol
• Markets with very noisy or fragmented data
• Extreme news events where spread behavior can become unstable
• Non-crypto symbols unless the user deliberately selects a meaningful reference
🎛️ Key Inputs
• Auto Spot Reference → automatically builds the spot reference from the chart base currency, selected exchange, and selected quote
• Carry Baseline Length → controls how quickly the premium baseline adapts
• Stress Normalization Lookback → controls how far back the script looks to judge unusual basis behavior
• Persistence Window → measures whether carry pressure persists across several bars
• Premium Stress Threshold % → defines the minimum premium/discount level required for active stress
• Reference Mismatch Guard % → prevents mismatched symbols from being interpreted as real carry stress
• Basis Z-Score Threshold → defines how unusual the spread must be before stress can activate
• Visual Settings → control corridor projection, labels, right-side tags, bar colors, and font sizes
🖥️ Interface & Visual Design
The interface is designed around a premium first-glance chart story.
The corridor gives the chart an active visual anchor. The centered label explains the current stress read without forcing the user to inspect every panel row. Right-side tags keep the current state visible near the active price area.
The panel uses the AG Pro layout standard with a blue merged header row, adjustable location, adjustable theme, and adjustable font size.
🧪 Practical Usage Workflow
1. Apply the script to a perpetual or futures chart.
2. Keep Auto Spot Reference enabled, or manually select the closest matching spot market.
3. Read the panel state and stress score.
4. Check whether the corridor is neutral, premium-stressed, discount-stressed, or showing squeeze risk.
5. Evaluate price reaction around the corridor together with broader market structure, volatility, and risk rules.
🔍 Interpretation Guidelines
Treat carry stress as a context layer.
Premium stress can mean long-side carry is becoming crowded, but it does not automatically mean price must fall.
Discount stress can mean short-side carry is becoming crowded, but it does not automatically mean price must rise.
Carry squeeze risk is stronger when elevated stress and adverse price reaction appear together, but it still requires confirmation from broader market context.
🚫 What This Script Is NOT
This script is not a prediction engine.
This script is not financial advice.
This script is not an auto trading system.
This script is not a guaranteed signal engine.
This script does not read official funding payment data directly.
This script does not claim that premium or discount must immediately mean-revert.
⚠️ Limitations & Transparency
The script estimates carry stress from active-symbol versus spot-reference behavior. It is a proxy framework, not an official exchange funding-rate feed.
Results can vary by exchange, symbol mapping, liquidity, timeframe, and data quality.
The selected reference must match the active market. Auto Spot Reference is enabled by default to help keep ETH charts on an ETH reference, BTC charts on a BTC reference, and similar mappings aligned.
Fast market moves, low liquidity, stale references, or mismatched symbol selections can affect the accuracy of the stress interpretation.
Market conditions change, and the same stress score may behave differently across different volatility regimes.
🧠 Market Context Notes
In crypto markets, derivatives pressure can matter because perpetual traders may become crowded on one side when premium, basis, and volatility remain elevated.
This does not create certainty. It creates context.
The value of the script is strongest when the user combines carry stress with structure, liquidity, trend quality, volatility, and disciplined risk management.
🧾 Use Case Examples
When price trades above the spot reference with persistent premium and the panel shifts into Premium Stress, the user may monitor whether long-side carry is becoming crowded.
When price trades below the spot reference with persistent discount and the panel shifts into Discount Stress, the user may monitor whether short-side pressure is becoming crowded.
When elevated carry stress appears and price starts rejecting the crowded side, the Carry Squeeze Risk state can help highlight a context worth closer attention.
🧱 System Philosophy
Funding Carry Stress Map follows the AGProLabs principle of building decision-support maps rather than prediction tools.
The script is designed to make hidden context easier to see, not to replace judgment.
Its purpose is to organize information into a cleaner visual workflow: read the state, inspect the corridor, evaluate reaction, and confirm with broader context.
🔐 Non-Promise Statement
No script can guarantee market direction.
No carry stress model can remove uncertainty.
This tool helps organize context; it does not create certainty.
📉 Risk Disclosure
Trading involves risk.
Crypto derivatives can be highly volatile and may involve leverage, liquidation risk, exchange risk, funding-cost changes, and rapid market movement.
This script is for educational and analytical purposes only.
It does not provide financial advice or guaranteed trading outcomes.
Users remain responsible for their own decisions.
📚 Educational Note
Use the script as a learning layer for understanding how premium, discount, persistence, volatility, and price reaction can combine into a more complete derivatives-pressure read.
Indicator
Indicator
Spot-Futures SpreadSpot-Futures Spread Indicator
A comprehensive indicator that automatically calculates and visualizes the percentage spread between spot and perpetual futures prices across multiple exchanges.
Key Features:
Automatic Exchange Detection - Automatically detects your current exchange and finds the corresponding spot/futures pair
Smart Fallback System - If the counterpart isn't available on your exchange, it automatically searches across 7+ major exchanges (Binance, Bybit, OKX, Gate.io, MEXC, KuCoin, HTX) and uses the first valid match
Multi-Exchange Support - Works with 14 exchanges including Binance, Bybit, OKX, MEXC, BitGet, Gate.io, KuCoin, and more
Clear Exchange Attribution - Shows exactly which exchanges are providing spot and futures data in the statistics table
Configurable Moving Average - Track the average spread with customizable period
Standard Deviation Bands - Identify unusual spread conditions with Bollinger-style bands
Built-in Alerts - Get notified when spread crosses bands or zero (parity)
Statistics Table - Real-time stats showing current spread, MA, std dev, and bands
Manual Override Options - Advanced users can manually specify exchanges and symbols
How It Works:
The indicator calculates the spread as: (Futures Price - Spot Price) / Spot Price × 100
Positive spread = Futures trading at a premium (contango)
Negative spread = Futures trading at a discount (backwardation)
Zero = Parity between spot and futures
Use Cases:
Funding Rate Analysis - Correlates with perpetual funding rates
Arbitrage Opportunities - Identify significant spot-futures divergences
Market Sentiment - Premium/discount indicates bullish/bearish positioning
Cross-Exchange Analysis - Compare spreads when spot and futures are on different exchanges
Smart Features:
Works whether you're viewing a spot or futures chart
Automatically handles exchange-specific perpetual contract naming (.P, PERP, SWAP, etc.)
Color-coded visualization (green for premium, red for discount)
Customizable colors and display options
Background shading based on spread direction
Perfect For:
Crypto traders monitoring funding rates, arbitrage traders, market makers, and anyone interested in spot-futures dynamics across multiple exchanges.
Getting Started:
Simply add the indicator to any spot or perpetual futures chart. It will automatically detect the exchange and find the corresponding pair. The statistics table shows which exchanges are being used for maximum transparency.
Note: The indicator automatically ignores invalid symbols, so you'll never see errors even if a specific pair doesn't exist on a particular exchange.
Kudos to @AlekMel that made the "Spot - Fut Spread v2" indicator that I enhance the Automatic detection feature which was not working in some case. Indicator
Qullamagi EMA Breakout Autotrade (Crypto Futures L+S)Title: Qullamagi EMA Breakout – Crypto Autotrade
Overview
A crypto-focused, Qullamagi-style EMA breakout strategy built for autotrading on futures and perpetual swaps.
It combines a 5-MA trend stack (EMA 10/20, SMA 50/100/200), volatility contraction boxes, volume spikes and an optional higher-timeframe 200-MA filter. The script supports both long and short trades, partial take profit, trailing MA exits and percent-of-equity position sizing for automated crypto futures trading.
Key Features (Crypto)
Qullamagi MA Breakout Engine – trades only when price is aligned with a strong EMA/SMA trend and breaks out of a tight consolidation range. Longs use: Close > EMA10 > EMA20 > SMA50 > SMA100 > SMA200. Shorts are the mirror condition with all MAs sloping in the trend direction.
Strict vs Loose Modes – Strict (Daily) is designed for cleaner swing trades on 1H–4H (full MA stack, box+ATR and volume filters, optional HTF filter). Loose (Intraday) focuses on 10/20/50 alignment with relaxed filters for more frequent 15m–30m signals.
Volatility & Volume Filters for Crypto – ATR-based box height limit to detect volatility contraction, wide-candle filter to avoid chasing exhausted breakouts, and a volume spike condition requiring current volume to exceed an SMA of volume.
Higher-Timeframe Trend Filter (Optional) – uses a 200-period SMA on a higher timeframe (default: 1D). Longs only when HTF close is above the HTF 200-SMA, shorts only when it is below, helping avoid trading against dominant crypto trends.
Autotrade-Oriented Trade Management – position size as % of equity, initial stop anchored to a chosen MA (EMA10 / EMA20 / SMA50) with optional buffer, partial take profit at a configurable R-multiple, trailing MA exit for the remainder, and an optional cooldown after a full exit.
Markets & Timeframes
Best suited for BTC, ETH and major altcoin futures/perpetuals (Binance, Bybit, OKX, etc.).
Strict preset: 1H–4H charts for classic Qullamagi-style trend structure and fewer fake breakouts.
Loose preset: 15m–30m charts for higher trade frequency and more active intraday trading.
Always retune ATR length, box length, volume multiplier and position size for each symbol and exchange.
Strategy Logic (Quick Summary)
Long (Strict): MA stack in bullish alignment with all MAs sloping up → tight volatility box (ATR-based) → volume spike above SMA(volume) × multiplier → breakout above box high (close or intrabar) → optional HTF close above 200-SMA.
Short: Mirror logic: bearish MA stack, tight box, volume spike and breakdown below box low with optional HTF downtrend.
Best Practices for Crypto
Backtest on each symbol and timeframe you plan to autotrade, including commissions and slippage.
Start on higher timeframes (1H/4H) to learn the behavior, then move to 15m–30m if you want more signals.
Use the higher-timeframe filter when markets are strongly trending to reduce counter-trend trades.
Keep position-size percentage conservative until you fully understand the drawdowns.
Forward-test / paper trade before connecting to live futures accounts.
Webhook / Autotrade Integration
Designed to work with PulseWire webhooks and external crypto trading bots.
Alert messages include structured fields such as: EVENT=ENTRY / SCALE_OUT / EXIT, SIDE=LONG / SHORT, STRATEGY=Qullamagi_MA.
Map each EVENT + SIDE combination to your bot logic (open long/short, partial close, full close, etc.) on your preferred exchange.
Important Notes & Disclaimer
Crypto markets are highly volatile and can change regime quickly. Backtest and forward-test thoroughly before using real capital. Higher timeframes generally produce cleaner MA structures and fewer fake breakouts.
This strategy is for educational and informational purposes only and does not constitute financial advice. Trading leveraged crypto products involves substantial risk of loss. Always do your own research, manage risk carefully, and never trade with money you cannot afford to lose.
Strategy
Crypto Perp Calc v1Advanced Perpetual Position Calculator for PulseWire
Description
A comprehensive position sizing and risk management tool designed specifically for perpetual futures trading. This indicator eliminates the confusion of calculating leveraged positions by providing real-time position metrics directly on your chart.
Key Features:
Interactive Price Selection: Click directly on chart to set entry, stop loss, and take profit levels
Accurate Lot Size Calculation: Instantly calculates the exact position size needed for your margin and leverage
Multiple Entry Support: DCA into positions with up to 3 entry points with customizable allocation
Multiple Take Profit Levels: Scale out of positions with up to 3 TP targets
Comprehensive Risk Metrics: Shows dollar P&L, account risk percentage, and liquidation price
Visual Risk/Reward: Color-coded boxes and lines display your trade setup clearly
Real-time Info Table: All critical position data in one organized panel
Perfect for traders using perpetual futures who need precise position sizing with leverage.
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How to Use
Quick Start (3 Clicks)
1. Add the indicator to your chart
2. Click three times when prompted:
First click: Set your entry price
Second click: Set your stop loss
Third click: Set your take profit
3. Read the TOTAL LOTS value from the info table (highlighted in yellow)
4. Use this lot size in your exchange when placing the trade
Detailed Setup
Step 1: Configure Your Account
Enter your account balance (total USDT in account)
Set your margin amount (how much USDT to risk on this trade)
Choose your leverage (1x to 125x)
Select Long or Short position
Step 2: Set Price Levels
Main levels use interactive clicking (Entry, SL, TP)
For multiple entries or TPs, use the settings panel to manually input prices and percentages
Step 3: Read the Results
The info table shows:
TOTAL LOTS - The position size to enter on your exchange
Margin Used - Your actual capital at risk
Notional - Total position value (margin × leverage)
Max Risk - Dollar amount you'll lose at stop loss
Total Profit - Dollar amount you'll gain at take profit
R:R Ratio - Risk to reward ratio
Account Risk - Percentage of account at risk
Liquidation - Price where position gets liquidated
Step 4: Advanced Features (Optional)
Multiple Entries (DCA):
Enable "Use Multiple Entries"
Set up to 3 entry prices
Allocate percentage for each (must total 100%)
See individual lot sizes for each entry
Multiple Take Profits:
Enable "Use Multiple TPs"
Set up to 3 TP levels
Allocate percentage to close at each level (must total 100%)
View profit at each target
Visual Elements
Blue lines/labels: Entry points
Red lines/labels: Stop loss
Green lines/labels: Take profit targets
Colored boxes: Visual risk (red) and reward (green) zones
Info table: Can be positioned anywhere on screen
Alerts
Set price alerts for:
Entry zones reached
Stop loss approached
Take profit levels hit
Works with PulseWire's alert system
Tips for Best Results
Always verify the lot size matches your intended risk
Check the liquidation price stays far from your stop loss
Monitor the account risk percentage (recommended: keep under 2-3%)
Use the warning indicators if risk exceeds margin
For quick trades, use single entry/TP; for complex strategies, use multiple levels
Example Workflow
Find your trade setup using your analysis
Add this indicator and click to set levels
Check risk metrics in the table
Copy the TOTAL LOTS value
Enter this exact position size on your exchange
Set alerts for key levels if desired
This tool bridges the gap between PulseWire charting and exchange execution, ensuring your position sizing is always accurate when trading with leverage.
Disclaimer, this was coded with help of AI, double check calculations if they are off. Indicator
BINANCE-BYBIT Cross Chart: Spot-Perpetual CorrelationName: "Binance-Bybit Cross Chart: Spot-Perpetual Correlation"
Category: Scalping, Trend Analysis
Timeframe: 1M, 5M, 30M, 1D (depending on the specific technique)
Technical analysis: This indicator facilitates a comparison between the price movements shown on the Binance spot chart and the Bybit perpetual chart, with the aim of discerning the correlation between the two charts and identifying the dominant market trends. It automatically generates the corresponding chart based on the ticker selected in the primary chart. When a Binance pair is selected in the main chart, the indicator replicates the Bybit perpetual chart for the same pair and timeframe, and vice versa, selecting the Bybit perpetual chart as the primary chart generates the Binance spot chart.
Suggested use: You can utilize this tool to conduct altcoin trading on Binance or Bybit, facilitating the comparison of price actions and real-time monitoring of trigger point sensitivity across both exchanges. We recommend prioritizing the Binance Spot chart in the main panel due to its typically longer historical data availability compared to Bybit.
The primary objective is to efficiently and automatically manage the following three aspects:
- Data history analysis for higher timeframes, leveraging the extensive historical data of the Binance spot market. Variations in indicators such as slow moving averages may arise due to differences in historical data between exchanges.
- Assessment of coin liquidity on both exchanges by observing candlestick consistency on smaller timeframes or the absence of gaps. In the crypto market, clean charts devoid of gaps indicate dominance and offer enhanced reliability.
- Identification of precise trigger point levels, including daily, previous day, or previous week highs and lows, which serve as sensitive areas for breakout or reversal operations.
All-Time High (ATH) and All-Time Low (ATL) levels may vary significantly across exchanges due to disparities in historical data series.
This tool empowers traders to make informed decisions by leveraging historical data, liquidity insights, and precise trigger point identification across Binance Spot and Bybit Perpetual market.
Configuration:
EMA length:
- EMA 1: Default 5, user configurable
- EMA 2: Default 10, user configurable
- EMA 3: Default 60, user configurable
- EMA 4: Default 223, user configurable
- Additional Average: Optional display of an additional average, such as a 20-period average.
Chart Elements:
- Session separator: Indicates the beginning of the current session (in blue)
- Background: Indicates an uptrend (60 > 223) with a green background and a downtrend (60 < 223) with a red background.
Instruments:
- EMA Daily: Shows daily averages on an intraday timeframe.
- EMA levels 1h - 30m: Shows the levels of the 1g-30m EMAs.
- EMA Levels Highest TF: Provides the option to select additional EMA levels from the major timeframes, customizable via the drop-down menu.
- "Hammer Detector: Marks hammers with a green triangle and inverted hammers with a red triangle on the chart
- "Azzeramento" signal on TF > 30m: Indicates a small candlestick on the EMA after a dump.
- "No Fomo" signal on TF < 30m: Indicates a hyperextended movement.
Trigger Points:
- Today's highs and lows: Shows the opening price of the day's candlestick, along with the day's highs and lows (high in purple, low in red, open in green).
- Yesterday's highs and lows: Displays the opening price of the daily candlestick, along with the previous day's highs and lows (high in yellow, low in red).
You can customize the colors in "Settings" > "Style".
It is best used with the Scalping The Bull indicator on the main panel.
Credits:
@tumiza999: for tests and suggestions.
Thanks for your attention, happy to support the PulseWire community.
Indicator
Lines and Table for risk managementABOUT THIS INDICATOR
This is a simple indicator that can help you manage the risk when you are trading, and especially if you are leverage trading. The indicator can also be used to help visualize and to find trades within a suitable or predefined trading range.
This script calculates and draws six “profit and risk lines” (levels) that show the change in percentage from the current price. The values are also shown in a table, to help you get a quick overview of risk before you trade.
ABOUT THE LINES/VALUES
This indicator draws seven percentage-lines, where the dotted line in the middle represents the current price. The other three lines on top of and below the middle line shows the different levels of change in percentage from current price (dotted line). The values are also shown in a table.
DEFAULT VALUES AND SETTINGS
By default the indicator draw lines 0.5%, 1.0%, and 1.5% from current price (step size = 0.5).
The default setting for leverage in this indicator = 1 (i.e. no leverage).
The line closest to dotted line (current price) is calculated by step size (%) * leverage (x) = % from price.
Pay attention to the %-values in the table, they represent the distance from the current price (dotted line) to where the lines are drawn.
* Be aware! If you change the leverage, the distance from the closest lines to the dotted line showing the current price increase.
SETTINGS
1. Leverage: set the leverage for what you are planning to trade on (1 = no leverage, 2 = 2 x leverage, 5 = 5 x leverage...).
2. Stepsize is used to set the distance between the lines and price.
EXAMPLES WITH DIFFERENT SETTINGS
1) Leverage = 1 (no leverage, default setting) and step size 0.5 (%). Lines plotted at (0.5%, 1%, 1.5%, and –0.5%, –1%, –1,5%) from the current price.
2) Leverage = 3 and stepsize 0.5(%). Lines plotted at (1.5%, 3.0%, 4.5%, and –1.5%, –3.0%, –4.5%) from the current price.
3) Leverage = 3 and stepsize 1(%). Lines plotted at (3%, 6%, 9%, and –3%, –6%, –9%) from the current price.
The distance to the nearest line from the current price is always calculated by the formula: Leverage * step size (%) = % to the nearest line from the current price.
Indicator
Perpetual American Options [Loxx]Perpetual American Options is Perpetual American Options pricing model. This indicator also includes numerical greeks.
American Perpetual Options
While there in general is no closed-form solution for American options (except for non-dividend-paying stock call options) it is possible to find a closed-form solution for options with an infinite time to expiration. The reason is that the time to expiration will always be the same: infinite. The time to maturity, therefore, does not depend on at what point in time we look at the valuation problem, which makes the valuation problem independent of time McKean (1965) and Merton (1973) gives closed-form solutions for American perpetual options. For a call option we have
c = (X / (y1 - 1)) * ((y1 - 1)/y1 * S/X)^y1
where
y1 = 1/2 - b/v^2 + ((b/v^2 - 1/2)^2 + 2*r/v^2)^0.5
If b >= r, then there is never optimal to exercise a call option. In the case of an American perpetual put, we have
p = X/(1-y2) * (((y2 - 1) / y2) * S/X)^y2
where
y2 = 1/2 - b/v^2 - ((b/v^2 - 1/2)^2 + 2*r/v^2)^0.5
In practice, one can naturally discuss if there is such a thing as infinite time to maturity. For instance, credit risk could play an important role: Even when you are buying an option from an AAA bank, there is no guarantee the bank will be around forever.
b=r options on non-dividend paying stock
b=r-q options on stock or index paying a dividend yield of q
b=0 options on futures
b=r-rf currency options (where rf is the rate in the second currency)
Inputs
S = Stock price.
K = Strike price of option.
T = Time to expiration in years.
r = Risk-free rate
c = Cost of Carry
V = Variance of the underlying asset price
cnd1(x) = Cumulative Normal Distribution
cbnd3(x) = Cumulative Bivariate Normal Distribution
nd(x) = Standard Normal Density Function
convertingToCCRate(r, cmp ) = Rate compounder
Numerical Greeks or Greeks by Finite Difference
Analytical Greeks are the standard approach to estimating Delta, Gamma etc... That is what we typically use when we can derive from closed form solutions. Normally, these are well-defined and available in text books. Previously, we relied on closed form solutions for the call or put formulae differentiated with respect to the Black Scholes parameters. When Greeks formulae are difficult to develop or tease out, we can alternatively employ numerical Greeks - sometimes referred to finite difference approximations. A key advantage of numerical Greeks relates to their estimation independent of deriving mathematical Greeks. This could be important when we examine American options where there may not technically exist an exact closed form solution that is straightforward to work with. (via VinegarHill FinanceLabs)
Things to know
Only works on the daily timeframe and for the current source price.
You can adjust the text size to fit the screen
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Bitmex BTC Perpetual PremiumThis script tracks the premium of the Bitcoin Perpetual futures at Bimex exchange relative to 3 different reference prices.
The difference between this script and already published scripts is that it tracks the premium relative to 3 different reference prices. This tends to produce slightly different results.
This script is also open source, so you can verify the calculations, or use it as a basis for your own script.
The 3 plots uses the following reference prices:
Blue Area:
Bitmex Index price, ticker: BITMEX:XBT
Red line:
Bitmex Perpetual Premium, ticker XBTUSDPI
(This one is not used as reference, but simply plots the ticker*100)
Orange line:
The reference here is a price calculated by the tickers in trading view based on the Bitmex indices with weighing as follows:
Bitstamp:28,81%
Bittrex:5,5%
Coinbase: 38,07%
Gemini: 7,34%
Kraken: 20,28
Please note that Bitmex changes the bases of its indices regularly. Bitmex might also "rule out" on of these exchanges if there is a short term problem. Indicator
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