Documentation

🔹 QuantumFlow

Deep Explanation:

QuantumFlow is inspired by the idea that markets are not random but driven by institutionalplayers—big funds, banks, and hedge funds. These institutions leave footprints—order blocks,liquidity gaps, and zones of premium or discount—that retail traders often overlook.

Market Microstructure Theory:

Market microstructure studies how trades and order book dynamics influence price movements.QuantumFlow leverages this by identifying where the big players are likely to act, providing amap of potential support and resistance zones rooted in actual flow.

Core Components:

• Order Blocks: Zones where large orders have accumulated, often leading to reversals orbreakouts.
• Fair Value Gaps: Price zones where trading was imbalanced, indicating potential areas ofreversion.
• Liquidity Sweeps: Rapid price movements that clear liquidity, often preceding big institutionalmoves.
• Premium/Discount Zones: Areas where price is overextended relative to recentvalue—potential reversal points.

Application in Trading:

• Add QuantumFlow to your chart to visualize these zones.
• Use overlays to see where institutional footprints align with other signals like TrendScore orEdgeFlow.
• When price approaches a significant order block or liquidity zone, consider it a probabilitycluster—the market may reverse or accelerate.

Advanced Application:

Combine QuantumFlow with other tools to filter false signals. For example, only take entrieswhen QuantumFlow zones align with high EdgeFlow momentum or a strong TrendScore.

Historical Insight:

The concept of order flow has been a staple in professional trading rooms for decades. Moderntechnology allows retail traders to access similar insights, leveling the playing field.

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🔹 TrendScore

In-Depth Mechanics:

TrendScore distills the complex idea of trend strength into a single, easy-to-understand metric. Itconsiders multiple factors:

• Slope: The steepness of recent price moves.
• Momentum Efficiency: How smoothly prices are moving in one direction without excessivevolatility or reversals.
• Fractal Persistence: How consistently a trend has been maintained across multipletimeframes.

Quantitative Foundations:

• Uses linear regression to assess slope.
• Applies momentum indicators like RSI or MACD in a normalized way.
• Incorporates fractal analysis to measure how often a pattern repeats across scales.

Why It Matters:

By simplifying trend strength into a single score, traders can avoid false signals from choppymarkets. It’s a trend filter that ensures you only trade when the odds are in your favor.

Practical Use Cases:

• Enter long when TrendScore > +0.03 and aligned with your other signals.
• Short when below –0.03.
• Stay out or wait when in the neutral zone, especially during sideways or choppy markets.

Historical Note:

The idea of quantifying trend strength has roots in the development of momentum models usedby fund managers—here, it’s simplified for retail use but retains the core principles.

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🔹 Deepwave Oscillator

Technical Deep Dive:

Deepwave is inspired by the idea that volatility is not just random noise but a structuredphenomenon—markets tend to cycle through phases of calm and chaos. It models these cycles,measuring the strength and likelihood of breakouts or reversals.

Mathematical Model:

• Combines volatility clustering models (like GARCH) with cycle detection algorithms.
• Outputs a score from 0–100 indicating current volatility strength.

Market Scenarios:

• During low scores (0–30), the market is in a quiet phase—less trading, less opportunity forquick profits.
• During moderate (30–70), volatility is active—suitable for intraday trading.
• During high (70–100), markets are more likely to breakout or reverse—ideal for breakoutstrategies.

Usage Tips:

• Use Deepwave to decide when to stand aside or when to prepare for big moves.
• Combine with QuantumFlow to pinpoint where big moves may originate.
• Adjust your position sizes based on the volatility level—smaller during calm, larger duringactive phases.

Historical Context:

Volatility modeling is a cornerstone of risk management in hedge funds. Our implementationdemocratizes this insight for retail traders, enabling better timing and risk controls.

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🔹 EdgeFlow Oscillator

Technical Deep Dive:

Deepwave is inspired by the idea that volatility is not just random noise but a structuredphenomenon—markets tend to cycle through phases of calm and chaos. It models these cycles,measuring the strength and likelihood of breakouts or reversals.

Mathematical Model:

• Combines volatility clustering models (like GARCH) with cycle detection algorithms.
• Outputs a score from 0–100 indicating current volatility strength.

Market Scenarios:

• During low scores (0–30), the market is in a quiet phase—less trading, less opportunity forquick profits.
• During moderate (30–70), volatility is active—suitable for intraday trading.
• During high (70–100), markets are more likely to breakout or reverse—ideal for breakoutstrategies.

Usage Tips:

• Use Deepwave to decide when to stand aside or when to prepare for big moves.
• Combine with QuantumFlow to pinpoint where big moves may originate.
• Adjust your position sizes based on the volatility level—smaller during calm, larger duringactive phases.

Historical Context:

Volatility modeling is a cornerstone of risk management in hedge funds. Our implementationdemocratizes this insight for retail traders, enabling better timing and risk controls.

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🔹 SignalWave

Technical Deep Dive:

SignalWave employs advanced pattern recognition algorithms combined with trend analysis toidentify potential trade setups across multiple timeframes. It filters out noise and emphasizessignals with the highest probability of success.

Underlying Technology:

• Uses machine learning models trained on decades of market data.
• Recognizes complex patterns like breakouts, pullbacks, and reversals.

Practical Scenarios:

• During trending markets, SignalWave highlights pullbacks that offer high-probability entries.
• In ranging markets, it signals potential breakouts or reversals.

Usage Tips:

• Always confirm SignalWave signals with other indicators like TrendScore or QuantumFlow.
• Use it as an initial scan tool to prioritize setups.

Historical Analogy:

It mimics how institutional traders use pattern recognition software to scan for high-probabilitysetups quickly.

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🔹 Nova AI Trader

In-Depth Functionality:

Nova AI leverages machine learning and adaptive algorithms that process real-time marketdata—volatility, flow, structure—and adjust trading parameters dynamically. It mimics thedecision-making process of top quant funds, learning from ongoing market behavior.

How It Works:

• It monitors live data feeds, including order book flow, volatility, and price action.
• Adjusts risk, targets, and entries on the fly based on evolving conditions.
• Provides alerts, recommendations, or automatic execution options.

Ideal Usage:

• Use during volatile periods to adapt quickly
• Combine with manual signals for hybrid trading.
• Use for backtesting adaptive strategies over historical data.

Historical Context:

Adaptive AI systems are the cutting edge of modern finance implemented by top hedge fundsfor portfolio rebalancing and trade timing.

Still stuck? Use the contact form on our site/Discord to open a support ticket. Providescreenshots where possible for faster help.

• If you lose access, confirm your subscription is active. Payment failures will automaticallypause access.
• For billing questions, reach out directly via our support form

Problem:

Heiken Ashi candles, Deepwave oscillator, or other overlays do not display correctly

Solution:

• Go to Chart Settings → Symbol tab and disable Body, Borders, and Wick if using HeikenAshi-based indicators.
• Ensure Regular candles are selected in chart settings.
• Refresh or reapply the indicator if overlays appear misaligned.

Pro Tip:

Some indicators like Deepwave or QuantumFlow rely on color-coded outputs; ensure chartbackground and theme don’t obscure signals.

Problem:

Webhook alerts fail or return HTTP errors.

Solution:

• Ensure the webhook URL starts with https:// (TradingView requires secure endpoints).
• Verify your server/bot can accept POST requests in JSON format.
• Check for firewall or security rules that may block TradingView requests.

Pro Tip:

Use tools like RequestBin or Webhook.site to test payload reception before connecting to livesystems.

Problem:

Webhook or chart alerts trigger too frequently or repeat for the same candle.

Solution:

• Set the alert frequency to “Once per bar close” instead of “Every time.”
• Enable primary + secondary filters in Paradox Algo settings to reduce noise.
• Avoid using low-timeframe charts with multiple timeframe confirmations — this can createoverlapping alerts.

Pro Tip:

Combine with TrendScore or EdgeFlow Oscillator filters to reduce false signals.

Problem:

Entry/exit signals do not appear in real-time or seem delayed.

Solution:

• Ensure your chart timeframe matches your selected primary timeframe in Paradox Algosettings.
• Confirm your TradingView connection is stable (alerts require an active internet connection).
• Verify non-repainting mode is enabled if you want only confirmed closed-candle signals.

Pro Tip:

Using multiple timeframe filters (secondary/tertiary) may delay signals slightly — this is normaland increases accuracy.

Problem:

Users cannot see the indicator in TradingView under “Invite-Only Scripts.”

Solution:

• Confirm your TradingView username was correctly submitted during signup.
• Check your subscription plan to verify the indicator is included.
• Refresh TradingView, and search exactly by script name in Invite-Only Scripts.

Pro Tip:

Log out and back into TradingView after gaining access — sometimes refresh is required.

Problem: Users may struggle to set up webhook alerts for automated signals from the ParadoxAlgo indicator on TradingView.

Solution:

1. Open TradingView and go to your chart with Paradox Algo applied.
2. Click the “Alerts” button (bell icon) in the top toolbar.
3. In the Condition dropdown, select Paradox Algo – Entry/Exit Signals.
4. Choose “Webhook URL” and paste your server/bot URL where you want alerts sent.
5. In the Message box, use the default signal placeholders or customize them to include:
   
   • {{ticker}} – Symbol
   • {{strategy.order.action}} – Buy/Sell
   • {{close}} – Price at signal
6. Set alert expiration and frequency (only once or every bar).
7. Click Create. Alerts will now trigger automatically to your webhook whenever the indicatorfires a signal.

Pro Tip:

Test your webhook with a manual alert first to ensure the URL is reachable and properlyformatted. Ensure your bot/server can process JSON payloads from TradingView.

⚠️ Each third-party service is different (e.g., brokers, Discord bots, trade copiers). They willprovide their own instructions and message templates. Follow these carefully.

If alerts aren’t firing, double-check your alert conditions and ensure the webhook URL iscorrect.

1. Scalper (5m) — Manual
   
   • TrendScore (15m) = bias
   • Deepwave on 5m = filter (only trade when 30–70)
   • EdgeFlow on 5m = entry/exit
   • SignalWave = confirmation
2. Swing (4H / Daily) — Manual
   
   • TrendScore (Daily) = bias
   • QuantumFlow = structure (order blocks)
   • EdgeFlow (4H) = entry timing
   • Deepwave = volatility sizing
3. Futures Day Trade
   
   • TrendScore 1H for bias
   • QuantumFlow for session order blocks
   • EdgeFlow for intraday entries
   • Deepwave to avoid low-volatility traps

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• Does this trade fit within my daily risk cap?
• Will my stop loss keep my per-trade risk acceptable?
• Am I using structural or tactical indicators to justify my stop?
• Have I tracked cumulative risk for the day?

If any answer is “No,” do not take the trade. Discipline is non-negotiable in prop trading.

Stops protect your capital. Proper stop placement is not arbitrary—it should be logical,structural, and consistent with your risk rules.

Important Note: Paradox tools do not automatically place stops for you. You must set stopsmanually, using indicator context and your risk management rules.

1. Use indicator context for tactical stops:
   
   • SignalWave line or EdgeFlow inflection points can guide short-term stop placement
   • QuantumFlow order block invalidation can serve as a structural stop
2. Stop distance matters:
   
   • Too tight → frequent stop-outs (micro-noise)
   • Too wide → violates your position sizing rules
   • Goal: tight enough to respect your daily risk, wide enough to avoid random noise
3. Scaling and skipping trades:
   
   • If a proper stop would require risking more than your allowed per-trade allocation, do not takethe trade or reduce the number of contracts
4. Consistency is key:
   
   • Follow the same logic for every trade
   • Never move stops farther just to avoid a loss
   • Discipline in stops = survival in prop trading

Position sizing ensures that each trade fits your daily risk rules. Here’s a concrete example withfutures contracts:

1. Suppose your stop loss is 20 ticks, and each tick is worth $5. Risk per contract = 20 × $5 = $100
2. Daily risk limit = $400. Maximum contracts allowed = $400 ÷ $100 = 4 contracts
3. If you want to open a second trade: Check combined risk: Trade 1 risk + Trade 2 risk ≤ $400. If not, reduce the number of contracts or skip the second trade

Always calculate the worst-case scenario before placing any trade.

1. Check your max drawdown limit in the prop firm contract. Example: $4,000
2. Calculate your daily risk limit by multiplying max drawdown × 10%. Example: $4,000 × 10% = $400
3. Determine per-trade risk before entering a trade. Ask: If my stop loss is hit, how much will I lose in dollars per contract or lot?
4. Track cumulative risk for the day. Formula: total_loss_today = current_day_losses + sum(all_open_trade_risks). Ensure total ≤ daily cap. If adding a new trade exceeds the cap, reduce your position size or skip the trade entirely.
5. Stop trading when the cap is reached. No exceptions, no “just one more trade.” Protects your account and builds discipline,a key traitprop firms look for.

The golden rule:

• Only risk 10% of your maximum drawdown per trading day/session.
• This ensures that one bad day does not ruin your account or violate the prop firm’s rules.

Example:

• Prop account max drawdown: $4,000
• Daily risk limit: 10% × $4,000 = $400
• This $400 is the total allowable loss for the entire day, regardless of how many trades youtake.

If your trades hit this cap, stop trading immediately—no exceptions. This is critical to preserveyour capital and your prop account.

Risk management is the most important skill in prop trading. No indicator, system, or strategycan save you from blowing an account if you ignore risk limits. The following guide breakseverything down step by step, using concrete examples, so it’s easy to follow—even if you’renew to prop trading.

Paradox Algo is built to give traders flexible tools,not rigid systems. While our automatedstrategy is available, it’s designed for automation. For manual trading, focus on the indicators tobuild your own setups.

Scalping

• Look for fast intraday moves
• Use EdgeFlow Oscillator for precise entries/exits.
• Apply SignalWave or TrendScore on higher timeframes (15m–1h) to stay aligned with trendbias.
• Avoid trading during unstable volatility spikes with Deepwave.

Swing Trading

• Focus on broader moves across 4H–Daily charts.
• Use TrendScore/SignalWave to establish long-term trend bias.
• Verify market structure with QuantumFlow(order blocks, liquidity sweeps, premium/discountzones).
• Use EdgeFlow for timing entries within your larger bias.

Key Point:

Each trader should combine these tools in a way that fits their style. There’s no single bestsetup.The indicators are designed to adapt to you, not the other way around.

• Scalping: 1m–5m
• Day Trading: 15m–1h
• Swing: 4h–1D

A.I Fibonacci [Paradox]

Description:

The A.I fibonacci is a tool designed to assist traders in identifying potential price levels followinga retracement. Unlike many other Fibonacci indicators available, this script is tailored to highlightthe most crucial levels for entries, take profits, and stop losses.

Key Features:

• Automatic Calculation: The script automatically calculates and plots Fibonacci extension levelsbased on the price movement and the highs and the lows on the chart.
• Optimal Levels: It emphasizes the most relevant levels for making informed trading decisions,ensuring traders focus on what specific levels.
• Versatility: Suitable for all markets, making it a versatile tool for traders across different assetclasses.
• User-Friendly: Designed with both novice and experienced traders in mind, the script is easy touse and interpret.

How It Stands Out:

While there are numerous Fibonacci tools available, the A.I Fibonacci is distinct in its approach.It not only calculates potential price reversal areas but also pinpoints possible price levels aftera retracement is completed. This dual functionality ensures traders have a comprehensive viewof the market.

How to Use:

Apply the script to your desired chart.

Observe the plotted Fibonacci levels.

Use these levels to determine potential entry, exit, and stop-loss points.

Green - Entry levels

Red - Stop Loss Levels

Yellow - Take Profit Levels

Applicability:

A.I Fibonacci is designed for all markets, making it a versatile tool for forex, stocks,commodities, and more.

Conditions for Use:

The script performs optimally under various market conditions. However, as with all technicaltools, it's recommended to use it in conjunction with other indicators and analysis methods forbest results.

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Support & Resistance AI LevelScope

Support & Resistance AI LevelScope is an advanced, AI-driven tool that automatically detectsand highlights key support and resistance levels on your chart. This indicator leverages smartalgorithms to pinpoint the most impactful levels, providing traders with a precise, real-time viewof critical price boundaries. Save time and enhance your trading edge with effortless, intelligentsupport and resistance identification.

Key Features:

• AI-Powered Level Detection: The LevelScope algorithm continuously analyzes price action,dynamically plotting support and resistance levels based on recent highs and lows across yourchosen timeframe.
• Sensitivity Control: Customize the sensitivity to display either major levels for a macro view ormore frequent levels for detailed intraday analysis. Easily adjust to suit any trading style ormarket condition.
• Level Strength Differentiation: Instantly recognize the strength of each level with visual cuesbased on how often price has touched each one. Stronger levels are emphasized, highlightingareas with higher significance, while weaker levels are marked subtly.
• Customizable Visuals: Tailor the look of your chart with customizable color schemes and linethickness options for strong and weak levels, ensuring clear visibility without clutter.
• Proximity Alerts: Receive alerts when price approaches key support or resistance, giving you aheads-up for potential market reactions and trading opportunities.

Who It’s For:

Whether you're a day trader, swing trader, or just want a quick, AI-driven way to identifyhigh-probability levels on your chart, Support & Resistance AI LevelScope is designed to keepyou focused and informed. This indicator is the perfect addition to any trader’s toolkit,empowering you to make more confident, data-backed trading decisions with ease.

Upgrade your analysis with AI-powered support and resistance—no more manual lines, onlysmart levels!

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Flow Optimized Moving Average

Overview:

The Flow Optimized Moving Average (Flow OMA) [ParadoxAlgo] is an advanced adaptivemoving average designed to dynamically adjust smoothing factors based on market efficiencyand volatility. By integrating the Efficiency Ratio (ER) with an Adaptive Moving Average (AMA)and leveraging ATR-based bands, this indicator provides traders with a refined tool foridentifying trend direction, strength, and potential reversal zones.

Key Features:

• Adaptive Moving Average (AMA) - Adjusts to price action based on the Efficiency Ratio (ER), reducing lag in trending marketswhile smoothing noise in ranging conditions.
• Efficiency Ratio (ER) - Measures the effectiveness of price movement over a defined lookback period.Helps in dynamically adjusting the smoothing constant of the AMA.
• ATR-Based Volatility Bands - Creates upper and lower dynamic bands based on the Average True Range (ATR).Expands in high volatility and contracts in low volatility, providing traders with a contextualunderstanding of price action.
• Slope-Based Trend Strength - Normalizes the moving average slope relative to ATR.Generates a trend strength score, which influences band opacity, making strong trends visuallydistinguishable.

Dynamic Color Coding

Bullish Trends: Cyan/Turquoise (#00e2ff)

Bearish Trends: Blue (#003ff5)

Neutral Trends: Gray

The transparency of the bands dynamically adjusts based on trend strength.

Fill Zone Effect

The area between the ATR bands is filled with a gradient-like effect, giving a clear visualrepresentation of trend strength and transitions.

Indicator Components:

Inputs (User Settings)

ER Lookback Period: Defines how many bars are used in the Efficiency Ratio calculation(default: 10).

Fast & Slow Periods: Control the sensitivity of the Adaptive Moving Average (default: 2 & 30).

ATR Period: Defines the lookback for Average True Range (default: 14).

Band Multiplier: Determines the width of ATR-based bands (default: 1.5).

Slope Average Period: Smooths trend slope for more stable trend assessment (default: 5).

Efficiency Ratio Calculation

Measures how effectively price moves in a straight line compared to its total movement.

A higher ER value suggests strong trend momentum, while a lower value implies consolidation.

Adaptive Moving Average (AMA)

Dynamically adjusts its smoothing factor based on ER.

Uses a smoothing constant that ranges between the fastest and slowest specified values.

Volatility-Based Bands

Constructed using the ATR multiplier.

Expand and contract dynamically in response to market volatility.

Trend Strength & Direction

Computed using the normalized slope of AMA against ATR

Positive slope = Bullish trend, Negative slope = Bearish trend.

Visual Enhancements

Colored Adaptive MA Line: Changes based on trend direction.

ATR Bands with Gradient Fill: Visual representation of market conditions.

Dynamic Opacity: Highlights trend strength through transparency.

How to Use the Flow OMA Indicator

Trend Identification:

When the Adaptive MA is rising and colored cyan, a bullish trend is in play.

When the Adaptive MA is falling and colored blue, a bearish trend is present.

Trend Strength Assessment

A stronger trend results in more opaque band fills, indicating a clear directional bias.

Weaker trends or consolidations result in fainter fills, signaling a loss of momentum.

Reversal Signals

If price touches the upper band in a bullish move and starts reversing, it can indicate potentialprofit-taking areas.

If price approaches the lower band in a bearish move and rebounds, a short-term reversal maybe imminent.

Volatility Insights

Narrow bands indicate low volatility and possible breakout conditions.

Wider bands suggest increased volatility, warning traders of potential price swings.

Best Practices:

✅ Combine with Other Indicators

Use RSI, MACD, or Volume Profile for confirmation before executing trades.

✅ Apply to Multiple Timeframes

Works effectively in higher timeframes (1H, 4H, Daily) for trend trading.

Can be utilized in lower timeframes (5m, 15m) for scalping setups.

✅ Adjust Parameters Based on Asset Volatility

Increase ATR Period for stocks with high volatility.

Reduce ATR Multiplier for forex pairs to avoid excessive band width.

The Flow Optimized Moving Average (Flow OMA) [ParadoxAlgo] is a powerful trend-followingtool designed for both swing and intraday traders. Its adaptive nature allows it to efficiently tracktrends while minimizing false signals. By incorporating dynamic volatility bands andtrend-sensitive color coding, this indicator enhances traders' ability to read price actioneffectively. Whether used standalone or in combination with other indicators, Flow OMAprovides a significant edge in trend analysis

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Adaptable Relative Momentum Index [ParadoxAlgo]

The Adaptable Relative Momentum Index (RMI) by ParadoxAlgo is an advancedmomentum-based indicator that builds upon the well-known RSI (Relative Strength Index)concept by introducing a customizable momentum length. This indicator measures pricemomentum over a specified number of periods and applies a Rolling Moving Average (RMA) toboth the positive and negative price changes. The result is a versatile tool that can help tradersgauge the strength of a trend, pinpoint overbought/oversold levels, and potentially identifybreakout opportunities.

Smart Configuration Feature:

What sets this version of the RMI apart is ParadoxAlgo’s exclusive “Smart Configuration”functionality. Instead of manually adjusting parameters, traders can simply select their AssetClass (e.g., Stocks, Forex, Futures/Indices, Crypto, Commodities) and Trading Style (e.g.,Scalping, Day Trading, Swing Trading, Short-Term Investing, Long-Term Investing). Based onthese selections, the indicator automatically optimizes its core parameters:

• Length – The period over which the price changes are smoothed.
• Momentum Length – The number of bars used to calculate the price change.

By automating this process, users save time on tedious trial-and-error adjustments, ensuringthat the RMI’s settings are tailored to the characteristics of specific markets and personal tradinghorizons.

Key Features & Benefits:

1. Momentum-Based Insights
   
   • Uses RMA to smooth price movements, helping identify shifts in market momentum moreclearly than a basic RSI.
   • Enhanced adaptability for a wide range of asset classes and time horizons.
2. Simple Yet Powerful Configuration
   
   • Smart Configuration automatically sets optimal parameter values for each combination ofasset class and trading style.
   • Eliminates guesswork and manual recalibration when switching between markets ortimeframes.
3. Overbought & Oversold Visualization
   
   • Integrated highlight zones mark potential overbought and oversold extremes (default at 80 and 20).
   • Optional breakout highlighting draws attention to times when the indicator crosses these keythresholds, helping spot possible entry or exit signals.
4. Intuitive Design & Ease of Use
   
   • Clean plotting and color-coded signal lines make it easy to interpret bullish or bearish shifts inmomentum.
   • Straightforward dropdown menus keep the interface user-friendly, even for novice traders.

Practical Applications:

• Early Trend Detection: Spot emerging trends when the RMI transitions from oversold to higherlevels or vice versa.
• Breakout Confirmation: Confirm potential breakout trades by tracking overbought/oversoldbreakouts alongside other technical signals.
• Support/Resistance Confluence: Combine RMI signals with horizontal support/resistancelevels to reinforce trade decisions.
• Trade Timing: Quickly gauge when momentum could be shifting, helping you time entries andexits more effectively.

Disclaimer:

As with any technical indicator, the Adaptable Relative Momentum Index should be used as partof a broader trading strategy that includes risk management, fundamental analysis, and otherforms of technical confirmation. Past performance does not guarantee future results.

Enjoy using the Adaptable RMI [ParadoxAlgo] and experience a more streamlined, flexibleapproach to momentum analysis. Feel free to explore different asset classes and trading stylesto discover which configurations resonate best with your unique trading preferences.

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Chaikin Money Flow (CMF) [ParadoxAlgo]

OVERVIEW

This indicator implements the Chaikin Money Flow oscillator as an overlay on the price chart,designed to help traders identify institutional money flow patterns. The Chaikin Money Flowcombines price and volume data to measure the flow of money into and out of a security,making it particularly useful for detecting accumulation and distribution phases.

WHAT IS CHAIKIN MONEY FLOW?

Chaikin Money Flow was developed by Marc Chaikin and measures the amount of Money FlowVolume over a specific period. The indicator oscillates between +1 and -1, where:

Positive values indicate money flowing into the security (accumulation)

Negative values indicate money flowing out of the security (distribution)

Values near zero suggest equilibrium between buying and selling pressure

CALCULATION METHOD

Big Money Detection:

• Identifies significant institutional activity when CMF exceeds user-defined thresholds.
• Requires volume confirmation (volume above average) to validate signals.
• Uses battery icon (🔋) for institutional buying and lightning icon (⚡) for institutional selling.

Visual Elements:

• Background coloring based on money flow direction.
• Support and resistance levels calculated using Average True Range.
• Real-time dashboard showing current CMF value, volume strength, and signal status.

Customizable Parameters:

• CMF Period: Calculation period for the money flow (default: 20)
• Signal Smoothing: EMA smoothing applied to reduce noise (default: 5)
• Big Money Threshold: CMF level required to trigger institutional signals (default: 0.15)
• Volume Threshold: Volume multiplier required for signal confirmation (default: 1.5x)

INTERPRETATION

Signal Types:

🔋 (Battery): Indicates strong institutional buying when CMF > threshold with high volume

⚡ (Lightning): Indicates strong institutional selling when CMF < -threshold with high volume

Background color: Green tint for positive money flow, red tint for negative money flow

Dashboard Information:

• CMF Value: Current Chaikin Money Flow reading
• Volume: Current volume as a multiple of 20-period average
• Big Money: Status of institutional activity (BUYING/SELLING/QUIET)
• Signal: Strength assessment (STRONG/MEDIUM/WEAK)

TRADING APPLICATIONS

• Trend Confirmation: Use CMF direction to confirm price trends
• Divergence Analysis: Look for divergences between price and money flow
• Volume Validation: Confirm breakouts with corresponding money flow
• Accumulation/Distribution: Identify phases of institutional activity

PARAMETER RECOMMENDATIONS

Day Trading: CMF Period 14-21, higher sensitivity settings

Swing Trading: CMF Period 20-30, moderate sensitivity

Position Trading: CMF Period 30-50, lower sensitivity for major trends

ALERTS

Optional alert system notifies users when:

Big money buying is detected (CMF above threshold with volume confirmation)

Big money selling is detected (CMF below negative threshold with volume confirmation)

LIMITATIONS

May generate false signals in low-volume conditions

Best used in conjunction with other technical analysis tools

Effectiveness varies across different market conditions and timeframes

EDUCATIONAL PURPOSE

This open-source indicator is provided for educational purposes to help traders understandmoney flow analysis. It demonstrates the practical application of the Chaikin Money Flowconcept with visual enhancements for easier interpretation.

TECHNICAL SPECIFICATIONS

• Overlay indicator (displays on price chart)
• No repainting - all calculations are based on closed bar data.
• Suitable for all timeframes and asset classes.
• Minimal resource usage for optimal performance

DISCLAIMER

This indicator is for educational and informational purposes only. Past performance does notguarantee future results. Always conduct your own analysis and consider risk managementbefore making trading decisions.

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QFisher-R™ [ParadoxAlgo]

QFISHER-R™ (Regime-Aware Fisher Transform)

A research/education tool that helps visualize potential momentum exhaustion and probableinflection zones using a quantitative, non-repainting Fisher framework with regime filters andmulti-timeframe (MTF) confirmation.

What it does:

• Converts normalized price movement into a stabilized Fisher domain to highlight potentialturning points.
• Uses adaptive smoothing, robust (MAD/quantile) thresholds, and optional MTF alignment tocontextualize extremes.
• Provides a Reversal Probability Score (0–100) to summarize signal confluence (extreme,slope, cross, divergence, regime, and MTF checks).

Key features:

• Non-repainting logic (bar-close confirmation; security() with no lookahead).
• Dynamic exhaustion bands (data-driven thresholds vs fixed ±2).
• Adaptive smoothing (efficiency-ratio based).
• Optional divergence tags on structurally valid pivots.
• MTF confirmation (same logic computed on a higher timeframe).
• Compact visuals with subtle plotting to reduce chart clutter.

Inputs (high level):

• Source (e.g., HLC3 / Close / HA).
• Core lookback, fast/slow range blend, and ER length.
• Band sensitivity (robust thresholding).
• MTF timeframe(s) and agreement requirement.
• Toggle divergence & intrabar previews (default off).

Signals & Alerts:

• Turn Candidate (Up/Down) when multiple conditions align.
• Trade-Grade Turn when score ≥ threshold and MTF agrees.
• Divergence Confirmed when structural criteria are met.
• Alerts are generated on the confirmed bar close by default. Optional “preview” mode isavailable for experimentation.
• Toggle divergence & intrabar previews (default off).

How to use:

• Start on your preferred timeframe; optionally enable an HTF (e.g., 4×) for confirmation.
• Look for RPS clusters near the exhaustion bands, slope inflections, and (optionally)divergences.
• Combine with your own risk management, liquidity, and trend context.
• Paper test first and calibrate thresholds to your instrument and timeframe.

Notes & limitations:

• This is not a buy/sell signal generator and does not predict future returns.
• Readings can remain extreme during strong trends; use HTF context and your own filters.
• Parameters are intentionally conservative by default; adjust carefully.

Compliance / Disclaimer:

• Educational & research tool only. Not financial advice. No recommendation to buy/sell anysecurity or derivative.
• Past performance, backtests, or examples (if any) are not indicative of future results.
• Trading involves risk; you are responsible for your own decisions and risk management.
• Built upon the Fisher Transform concept (Ehlers); all modifications, smoothing, regime logic,scoring, and visualization are original work by Paradox Algo.

🔹 Paradox Algo Automated Strategy (Main)

Deep Dive:

This is the backbone of our system. It encapsulates a set of rules derived from statistical analysis of market data. Think of it as a financial engine that interprets market signals based onmultiple layers of information—trend, volatility, momentum, and market structure.

Historical Foundations:

The development of automated trading engines draws from concepts like the Black-Scholes model for option pricing, mean reversion theories, and trend-following algorithms. These modelshave been refined over decades, leveraging massive datasets and computational power toidentify subtle patterns.

Mathematical Principles:

• Statistical Significance: Signals are validated through hypothesis testing—ensuring they are not random artifacts.
• Trend Timeframe Analysis: Used to determine the strength and direction of trends.
• Volatility Modeling: Employs our DeepWave model or similar to adapt to changing market regimes.
• Pattern Recognition: Machine learning techniques are incorporated to detect complex patterns, such as regime shifts or liquidity accumulation.

Operational Mechanics:

• The system evaluates price action in real-time, comparing it against historical models.
• It assesses whether market conditions are favorable for a move—considering volatility, trend strength, and liquidity.
• When conditions align, it issues a high-confidence signal—either to enter, exit, or stay out.

Practical Application:

• Use the engine for automated trading, but always monitor and review signals.
• Run backtests across different assets and timeframes to understand its behavior.
• Adjust parameters cautiously—markets evolve, and models need recalibration.

Limitations & Considerations:

• No model can predict 100% of market moves; always manage risk.
• Use in conjunction with manual analysis for confirmation.
• Be aware of market gaps, news events, or black-swan scenarios that models might not capture.

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🔹 Quantum Edge Automated Strategy

In-Depth Functionality:

This strategy focuses on futures markets, especially those using Renko bricks—a charting method that filters out minor price noise to highlight significant moves. It is optimized for capturing big, institutional-style entries.

Mathematical Underpinning:

• Renko Chart Logic: Based on fixed or ATR-based brick sizes, which adapt to market volatility.
• Precision Entry Algorithms: Use pattern recognition and flow analysis to pinpoint optimal entry points.
• Adaptive Stop-Loss / Take-Profit: Based on volatility and recent market structure; avoids static targets that become irrelevant in changing regimes.

Practical Scenarios:

• During trending markets, Quantum Edge can identify high-probability entries with tight stops.
• In choppy markets, it reduces trade frequency, avoiding false signals.
• When volatility spikes, it dynamically adjusts position sizes and targets.

Advanced Tips:

• Combine with TrendScore to ensure trades align with the broader trend.
• Use session filters to avoid false signals during low-liquidity periods.
• Regularly review the model’s parameters as market conditions evolve.

Historical Fact:

Futures markets, especially commodities and indices, are heavily influenced by liquidity andmacroeconomic factors. Quant models that incorporate liquidity footprints and volatility regimescan outperform traditional trend-following or breakout systems.

Time needed: 5 minutes

Steps:

• Subscribe on paradoxalgo.com.
• Send your TradingView username.
• Log into TradingView, open any chart.
• Add the core indicator (we recommend starting with Paradox Algo Strategy).
• Observe signals, entries, and exits appearing in real-time.
• Begin paper trading or small live trades to familiarize yourself.

Step 1: Log into TradingView with your account.

Step 2: Open your preferred asset chart—be it a forex pair, futures contract, or stock.

Step 3: Navigate to Indicators → Invite-Only Scripts.

Step 4: Select your Paradox Algo indicators.

Step 5: Customize parameters,these are designed to be flexible for different assets and styles.

Tip: Use multiple indicators in tandem to confirm signals.This reduces false positives andincreases confidence.

1. Subscription: Choose the plan that fits your trading style and asset focus on paradoxalgo.com.
2. User Information: Post-subscription, provide your TradingView username to us for access.
3. Invitation: You will receive an invite link—usually within 24 hours—allowing you to unlock premiumscripts.
4. Activation: Open TradingView, head to Indicators → Invite-Only Scripts. Your tools will be listed there,ready to deploy.
5. Setup:Adjust the indicator parameters to suit your chosen timeframe, asset class, and trading style.

Experiment with different settings to understand how each impacts the signals.

Understanding the nature of these tools is essential. Think of them as marketmicroscopes—they reveal hidden structures and flow that are invisible to the naked eye ortraditional indicators. They do not rely on lagging signals but instead interpret the market’scurrent state and likely future.

Scenario:

Suppose the market is in a ranging phase with low volatility. Traditional indicators might givemixed signals. Our models, however, recognize the low-volatility regime using volatilityclustering models and suggest waiting until the market shifts into a trending phase—indicating ahigher probability for profitable trades.

In contrast, during high-volatility periods, our models adjust their sensitivity, reducing falsesignals and filtering noise, much like a seasoned trader who knows when to tighten stops orreduce position sizes.

• Predictive Power: Our Quantitative models are designed to forecast market moves before they fully materialize, giving you an edge.
• Neural Testing: All tools are backtested across multiple years, assets, and market conditions using Quantitative neural models to ensure reliability & accuracy.
• Ease of Use: While based on complex models, our tools are plug-and-play, allowing traders to focus on execution rather than complex analysis.

Our tools are designed for traders who want to trade with the precision and consistency of large institutions. We recognize that retail traders often operate with limited information and rely heavily on visual indicators that can be deceptive. Paradox Algo’s goal is to bridge that gap with models that interpret the underlying market microstructure, flow, and macro trends.

What Makes Our System Different:

• Unlike simple moving average crossovers, our models analyze the context of a move, considering volatility regimes, order book imbalances, and liquidity zones.
• Our indicators adapt to different timeframes, recognizing that the same model can serve scalpers, day traders, or swing traders with appropriate parameter adjustments.
• We incorporate the concept of anticipation—predicting where the market is likely to go next—rather than just confirming what has already happened.

Paradox Algo represents a new frontier in the world of trading tools. At its core, it is asophisticated, data-driven, and mathematically grounded trading system rooted in principlesfrom quantitative finance—an area that has revolutionized asset management and hedge fundsover the past few decades. Unlike retail trading indicators, which are often based on simplifiedheuristics or heuristic overlays that can produce false signals, Paradox Algo leveragesadvanced algorithms, statistical models, and institutional techniques to generate high-probabilitytrading signals.

Historical Context and Evolution:

Quantitative finance emerged in the late 20th century as a response to the limitations ofdiscretionary trading. Hedge funds and institutional investors started employing mathematicians,statisticians, and computer scientists to analyze markets at scale—using vast datasets toidentify patterns, inefficiencies, and arbitrage opportunities. These models often rely onconcepts like mean reversion, momentum, volatility clustering, and liquidity flows—concepts thatform the backbone of Paradox Algo’s design.

Why Quantitative Models Matter:

Traditional retail indicators—like RSI, MACD, or Fibonacci retracements—are often lagging oroversimplified. They do not incorporate the multitude of factors influencing price movements,such as order book dynamics, macroeconomic news, or institutional footprints. Paradox Algo, bycontrast, employs a multi-layered approach, combining price action with underlying marketstructure, flow, and volatility to produce signals that anticipate moves

Core Principles of Paradox Algo:

• Data-Driven: All signals are generated through rigorous testing and validation against historicalmarket data, ensuring robustness.
• Rule-Based: Instead of discretionary judgment, signals follow explicit mathematical rules,reducing emotional bias.
• Adaptive: Indicators adjust to changing market regimes—whether trending, ranging, orvolatile—mimicking how institutions manage risk.
• Multi-Asset Compatibility: Designed to work seamlessly across futures, forex, stocks, andcrypto, recognizing that different markets have unique characteristics but share underlyingfinancial principles.