CANX Momentum & basic candle patterns© CanxStixTrader
CANX Momentum & basic candle patterns
( Customizable )
An indicator that simply shows you the way the market is trending.
- This will make it very easy to see what direction you should be looking to take trades.
Also included are Basic candle patterns to help identify the correct timing to enter trades.
- Bearish Engulfing Candles
- Bullish Engulfing Candles
- Bullish 3 Candle Strike/CANX
- Bearish 3 Candle Strike/CANX
More candle patterns to follow in future updates
Triple EMA 50,100,200
X = Engulfing candles
3s - Bear & Bull = Potential Reversals
Cloud fill indicates the direction that you should be looking to trade. Red for sells and Green for Buys.
A simple concept that can be very effective if used correctly. Great to pair with fractals and multi time frame trading strategies.
Keep it simple
Análise Fundamentalista
CANX Multi-Timeframe Trend© CanxStixTrader
CANX Multi Trend Table indicator allows you to monitor the instruments you choose on the timeframes you want without the need to move between them.
Customizable time frames, pairs, colors and size.
1. Different methods of determining trend VIA super trend or EMAs
2. Monitor multiple instruments at the same time
3. Customizable ATR settings
COT NET SHG"This indicator evaluates market participants’ positioning through composite calculations based on the COT (Commitments of Traders) report from the CME. It aims to identify significant imbalances between buyers and sellers by highlighting moments when major market players concentrate unusually large volumes of contracts in either the long or short direction."
Indicador Opciones Mejorado con S/R y Alertasnueva version de mi primer script, ahora recibe indicaciones mas precisas
Rolling 4-Year CAGRCalculates rolling 4-year CAGR on day, week, or month chart.
Can change timeframe to any number of years.
-Jesse Myers
Swing Data - ADR% / RVol / PVol / Float % / Avg $ VolThis indicator provides a comprehensive table displaying essential swing trading metrics directly on your chart. Designed for traders who need a quick overview of stock volatility, liquidity, and volume dynamics at a glance.
Key Features:
✅ ADR% (Average Daily Range Percentage)
✅ Relative Volume (RVol)
✅ Projected Intraday Volume
✅ Average Daily $ Volume (AD NYSE:V )
✅ Float Percentage
✅ Market Capitalization
✅ LoD Distance (Low of Day distance in ATR%)
✅ Volume Buzz (current volume deviation from average)
✅ Sector & Industry classification
Customization Options:
➤ Table size (tiny to large)
➤ Adjustable position: Top-Left, Top-Right, Bottom-Left, Bottom-Right
➤ Dark Mode friendly colors
➤ Toggle each metric on/off
➤ Option to add a spacing row for clear visibility
Usage:
This script is ideal for intraday and swing traders who monitor volume surges, float dynamics, and volatility patterns to assess tradable setups. It combines key price and volume insights with fundamentals in one clean table — saving screen space while enhancing situational awareness.
Inspired by professional trading dashboards and adapted for TradingView charts.
Market sessionsMarket sessions on chart. I used some coding from a large code. I wanted to see the market sessions on chart once each session opens. i am going to look at adding in supply and demand zones. Hopefully this can be a nice add on to any chart.
Kenneth EMA Crossover StrategyKenneth EMA Crossover Strategy
The Kenneth EMA Crossover Strategy is a minimalist yet powerful trend-following tool designed for intraday and short-term trading on leveraged instruments. It focuses purely on EMA crossovers, utilizing a fast custom EMA (Kenneth EMA) and a slower EMA filter to generate clean, momentum-based entry signals.
This system is built with simplicity and execution speed in mind, making it well-suited for traders aiming to capture quick directional moves with high precision. By targeting modest profits such as +0.5% per trade and applying leverage wisely, the strategy aims to consistently realize gains while keeping exposure controlled.
🚀 Core Features:
EMA crossover logic for clear long/short entries
Visual signals and background highlights for instant readability
No noise, no overfitting — just price and trend
💡 Usage Tips:
Best used on trending assets with high volatility
Optimize timeframes and EMA lengths based on the asset's behavior
Ideal when paired with tight TP logic and disciplined risk management
This strategy is not about predicting tops or bottoms — it's about riding momentum efficiently and exiting with a profit. Perfect for fast-paced markets where every fraction of a percent counts.
Peak Trade V1.1This strategy is designed to generate buy and sell signals by examining market movements with technical analysis methods. It analyzes price movements through various technical indicators such as trend structure, volume and volatility. The strategy aims to detect both the continuation of the trend and possible turning points.
The strategy automatically gives buy or sell signals under appropriate conditions in line with the algorithms it determines. These signals are especially suitable for short and medium-term transactions, but users can also use them in different time frames according to their own preferences.
Users can personalize various parameters (e.g. indicator periods, entry/exit points, risk ratio, etc.) through the strategy's settings. Thus, they can optimize them according to their own trading style and market conditions.
Important Note: This strategy has been tested on historical data, but like every strategy, it does not guarantee future results. Please always do your own analysis and do not neglect risk management. Be careful when making your investment decisions.
WMA ATR With Zone + Donchian// 💡 WMA ATR With Zone + Donchian - Strategy Description (EN)
// 📈 A powerful system optimized for short-term trades.
// 🎯 Perfect for traders aiming for 0.5% to 1% profit per trade.
// ⚙️ Combines WMA crossovers, ATR zones, and Donchian filters for high-accuracy signals.
// 💥 Provides meaningful returns when used with leverage.
// 🔍 Filters out noise during sideways markets.
// 📊 Clear info panels and entry/exit zones for easy use.
// 🚀 Great for consistent scalping profits.
// 👉 If you like it, don’t forget to follow 💚
// #Scalping #Leverage #CryptoStrategy #TradingView
// ─────────────────────────────────────────────────────────────
// 💡 WMA ATR With Zone + Donchian - Strateji Açıklaması
// 📈 Kısa vadeli işlemler için optimize edilmiş güçlü bir stratejidir.
// 🎯 Özellikle %0.5 ila %1 kar hedefleyen yatırımcılar için idealdir.
// ⚙️ WMA kesişimleri, ATR bölgeleri ve Donchian kanal filtrelemesiyle yüksek doğruluk sağlar.
// 💥 Kaldıraçla birlikte anlamlı kazançlar sunabilir.
// 🔍 Yatay piyasa filtrelemesiyle yanıltıcı sinyalleri azaltır.
// 📊 Bilgi panelleri ve net giriş-çıkış sinyalleriyle kullanıcı dostudur.
// 🚀 Küçük ama istikrarlı kazançlar hedefleyenler için birebirdir.
// 👉 Beğendiyseniz takip etmeyi unutmayın 💚
// #Scalping #Kaldıraç #CryptoStrateji #TradingView
New York Open MarkerNEW YORK OPEN MARKER
This indicator highlights two key time points: the New York Open at 9:30 AM and the 10:00 AM NY time.
For many traders, the NY Open is a crucial session. Manually marking these candles every day can be repetitive and time-consuming — this tool automates that process.
When enabled, it will:
- Mark 9:30 AM NY Time with a Blue marker.
- Mark 10:00 AM NY Time with a Red marker.
You can easily toggle the indicator on or off, customize the labels, or even hide them entirely. The marker colors are also fully adjustable to match your chart style.
This tool is especially handy during backtesting, helping you quickly identify these critical candles without scanning the chart manually.
Beta -> The New SystemBeta → The New System 📊
Calculate and visualize your asset’s sensitivity to a benchmark over a rolling lookback period.
What is Beta? 🤔
Beta measures how much your asset moves in relation to a chosen benchmark. A Beta of 1 means it moves in perfect sync; above 1 means it’s more volatile (amplified moves), and below 1 means it’s less volatile (dampened moves). By tracking Beta you see if your asset is a risky rocket or a stable ship compared to the market. 🚀⚓️
Indicator Inputs ⚙️
Lookback Period ⏳
Number of bars (e.g. days) over which to compute rolling averages, covariance, and variance.
Benchmark Symbol 🏷️
The ticker of the market or index you want to compare against (e.g. BTCUSD, ETHUSD, an index).
How It Works 🧮
Fetch prices for both your asset and the benchmark at each bar.
Compute returns by calculating the percentage change from bar to bar.
Smooth returns with a simple moving average over the lookback period to get mean asset and benchmark returns.
Calculate covariance between asset and benchmark returns to see how they move together.
Calculate variance of the benchmark returns to measure its own volatility.
Divide covariance by variance (with a check to avoid division by zero)—that ratio is your Beta.
Plot & Interpretation 🎨
Line Color
Always blue for Beta, emphasizing volatility comparison.
Reference Line
A dashed gray line at Beta = 1 marks “market-level” sensitivity.
Reading Beta
β > 1 🟥
Asset tends to exaggerate benchmark moves—higher upside potential but larger downside risk.
β = 1 🟩
Asset moves in lockstep with your benchmark.
β < 1 🟦
Asset smooths out benchmark swings—less risk but also muted returns.
Pro Tips 💡
Combine Alpha + Beta: high Beta with positive Alpha can be great in up-markets but painful in drawdowns.
Monitor Beta shifts: a sudden jump could signal a regime change or new correlation dynamics.
Test different benchmarks: small-cap altcoins may track a broader crypto index differently than they track Bitcoin.
By keeping an eye on Beta in real time, you’ll understand not just how much you’re making, but how much market risk you’re taking on every trade.
Support & Resistance ZonesAdvanced Support & Resistance Detection Algorithm
This indicator identifies meaningful price levels by analyzing market structure using a proprietary statistical approach. Unlike traditional methods that rely on simple swing highs/lows or moving averages, this system dynamically detects zones where price has shown consistent interaction, revealing true areas of supply and demand.
Core Methodology
Price Data Aggregation
Collects highs and lows over a configurable lookback period.
Normalizes price data to account for volatility, ensuring levels remain relevant across different market conditions.
Statistical Significance Filtering
Rejection of random noise: Eliminates insignificant price fluctuations using adaptive thresholds.
Volume-weighted analysis (implied): Stronger reactions at certain price levels are given higher priority, even if volume data is unavailable.
Dynamic Level Extraction
Density-based S/R Zones: Instead of fixed swing points, the algorithm identifies zones where price has repeatedly consolidated.
Time decay adjustment: Recent price action has more influence, ensuring levels adapt to evolving market structure.
Strength Quantification
Each level is assigned a confidence score based on:
Touch frequency: How often price revisited the zone.
Reaction intensity: The magnitude of bounces/rejections.
Time relevance: Whether the level remains active or has been broken decisively.
Adaptive Level Merging & Pruning
Proximity-based merging: If two levels are too close (within a volatility-adjusted threshold), they combine into one stronger zone.
Decay mechanism: Old, untested levels fade away if price no longer respects them.
Why This Approach Works Better Than Traditional Methods
✅ No subjective drawing required – Levels are generated mathematically, removing human bias.
✅ Self-adjusting sensitivity – Works equally well on slow and fast-moving markets.
✅ Focuses on statistically meaningful zones – Avoids false signals from random noise.
✅ Non-repainting & real-time – Levels only update when new data confirms their validity.
How Traders Can Use These Levels
Support/Resistance Trading: Fade bounces off strong levels or trade breakouts with confirmation.
Confluence with Other Indicators: Combine with RSI, MACD, or volume profiles for higher-probability entries.
Stop Placement: Place stops just beyond key levels to avoid premature exits.
Technical Notes (For Advanced Users)
The algorithm avoids overfitting by dynamically adjusting zones sensitivity based on market conditions.
Unlike fixed pivot points, these levels adapt to trends, making them useful in both ranging and trending markets.
The strength percentage helps filter out weak levels—only trade those with a high score for better accuracy.
Note: Script takes some time to load.
QTA_LeGo_LibraryLibrary "QTA_LeGo_Library"
detectFVG(useStrongBody, useWeakSides, useDirectional, bodyStrengthRatio, weakBodyRatio)
Parameters:
useStrongBody (bool)
useWeakSides (bool)
useDirectional (bool)
bodyStrengthRatio (float)
weakBodyRatio (float)
Golden Footprint View Pro v1.0 – Confirmed
//@version=5
indicator("Golden Footprint View Pro v1.0 – Confirmed", overlay=true)
// === INPUTS ===
deltaMultiplier = input.float(1.0, title="Delta Strength Multiplier")
showDeltaColoring = input.bool(true, title="Color Candles by Delta Strength?")
threshold = input.float(0.2, title="Delta Coloring Threshold (0-1)")
rsiPeriod = input.int(14, title="RSI Period")
cciPeriod = input.int(20, title="CCI Period")
showSignals = input.bool(true, title="Show Confirmed Entry Signals?")
// === DELTA CALCULATION ===
delta = volume * (close - open)
normalizedDelta = volume != 0 ? (delta * deltaMultiplier / volume) : 0.0
// === INDICATORS ===
rsi = ta.rsi(close, rsiPeriod)
cci = ta.cci(close, cciPeriod)
// === PRICE ACTION: Rejection Candle
upperWick = high - math.max(close, open)
lowerWick = math.min(close, open) - low
bodySize = math.abs(close - open)
isRejection = lowerWick > bodySize * 1.5 or upperWick > bodySize * 1.5
// === STRUCTURE BREAK LOGIC
prevHigh = ta.highest(close , 5)
prevLow = ta.lowest(close , 5)
bosUp = close > prevHigh
bosDown = close < prevLow
// === SIGNAL LOGIC
buySignal = showSignals and normalizedDelta > threshold and rsi < 40 and cci < -100 and isRejection and bosUp
sellSignal = showSignals and normalizedDelta < -threshold and rsi > 60 and cci > 100 and isRejection and bosDown
// === CANDLE COLORING ===
barcolor(showDeltaColoring and normalizedDelta > threshold ? color.lime :showDeltaColoring and normalizedDelta < -threshold ? color.red :showDeltaColoring ? color.gray : na)
// === SIGNAL PLOTS ===
plotshape(buySignal, location=location.belowbar, color=color.green, style=shape.labelup, text="BUY", size=size.small)
plotshape(sellSignal, location=location.abovebar, color=color.red, style=shape.labeldown, text="SELL", size=size.small)
// === DEBUG (Optional)
plotchar(delta, title="Delta", location=location.bottom, color=color.white, size=size.tiny, offset=-1)
Bertozzi Mini Dollar
This echnical indicator uses an adaptive Gaussian filter to calculate dynamic bands around the price, based on the mean absolute error (MAE). It allows you to switch between two modes:
Repaint Mode (Live Preview) : Bands are adjusted in real time with greater smoothness, but with less historical accuracy.
Fixed Mode (No-Repaint) : Bands are calculated without repainting, ensuring reliability for automated testing and strategies.
Buy and sell signals are generated when price crosses above or below the dynamic bands and can be used to detect short-term reversals.
Ideal for high volatility assets such as the mini dollar (WDO), providing a powerful statistical and visual perspective for scalping or day trading.
Global M2 Money Supply (USD) (27 currencies)M2 for 27 currencies, converted into USD.
Does not constitute 100% of global M2, but ~90% accounted for.
Leverages Dylan LeClair's starting point, adds to it.
Bloomberg Financial Conditions Index (Proxy)The Bloomberg Financial Conditions Index (BFCI): A Proxy Implementation
Financial conditions indices (FCIs) have become essential tools for economists, policymakers, and market participants seeking to quantify and monitor the overall state of financial markets. Among these measures, the Bloomberg Financial Conditions Index (BFCI) has emerged as a particularly influential metric. Originally developed by Bloomberg L.P., the BFCI provides a comprehensive assessment of stress or ease in financial markets by aggregating various market-based indicators into a single, standardized value (Hatzius et al., 2010).
The original Bloomberg Financial Conditions Index synthesizes approximately 50 different financial market variables, including money market indicators, bond market spreads, equity market valuations, and volatility measures. These variables are normalized using a Z-score methodology, weighted according to their relative importance to overall financial conditions, and then aggregated to produce a composite index (Carlson et al., 2014). The resulting measure is centered around zero, with positive values indicating accommodative financial conditions and negative values representing tighter conditions relative to historical norms.
As Angelopoulou et al. (2014) note, financial conditions indices like the BFCI serve as forward-looking indicators that can signal potential economic developments before they manifest in traditional macroeconomic data. Research by Adrian et al. (2019) demonstrates that deteriorating financial conditions, as measured by indices such as the BFCI, often precede economic downturns by several months, making these indices valuable tools for predicting changes in economic activity.
Proxy Implementation Approach
The implementation presented in this Pine Script indicator represents a proxy of the original Bloomberg Financial Conditions Index, attempting to capture its essential features while acknowledging several significant constraints. Most critically, while the original BFCI incorporates approximately 50 financial variables, this proxy version utilizes only six key market components due to data accessibility limitations within the TradingView platform.
These components include:
Equity market performance (using SPY as a proxy for S&P 500)
Bond market yields (using TLT as a proxy for 20+ year Treasury yields)
Credit spreads (using the ratio between LQD and HYG as a proxy for investment-grade to high-yield spreads)
Market volatility (using VIX directly)
Short-term liquidity conditions (using SHY relative to equity prices as a proxy)
Each component is transformed into a Z-score based on log returns, weighted according to approximated importance (with weights derived from literature on financial conditions indices by Brave and Butters, 2011), and aggregated into a composite measure.
Differences from the Original BFCI
The methodology employed in this proxy differs from the original BFCI in several important ways. First, the variable selection is necessarily limited compared to Bloomberg's comprehensive approach. Second, the proxy relies on ETFs and publicly available indices rather than direct market rates and spreads used in the original. Third, the weighting scheme, while informed by academic literature, is simplified compared to Bloomberg's proprietary methodology, which may employ more sophisticated statistical techniques such as principal component analysis (Kliesen et al., 2012).
These differences mean that while the proxy BFCI captures the general direction and magnitude of financial conditions, it may not perfectly replicate the precision or sensitivity of the original index. As Aramonte et al. (2013) suggest, simplified proxies of financial conditions indices typically capture broad movements in financial conditions but may miss nuanced shifts in specific market segments that more comprehensive indices detect.
Practical Applications and Limitations
Despite these limitations, research by Arregui et al. (2018) indicates that even simplified financial conditions indices constructed from a limited set of variables can provide valuable signals about market stress and future economic activity. The proxy BFCI implemented here still offers significant insight into the relative ease or tightness of financial conditions, particularly during periods of market stress when correlations among financial variables tend to increase (Rey, 2015).
In practical applications, users should interpret this proxy BFCI as a directional indicator rather than an exact replication of Bloomberg's proprietary index. When the index moves substantially into negative territory, it suggests deteriorating financial conditions that may precede economic weakness. Conversely, strongly positive readings indicate unusually accommodative financial conditions that might support economic expansion but potentially also signal excessive risk-taking behavior in markets (López-Salido et al., 2017).
The visual implementation employs a color gradient system that enhances interpretation, with blue representing neutral conditions, green indicating accommodative conditions, and red signaling tightening conditions—a design choice informed by research on optimal data visualization in financial contexts (Few, 2009).
References
Adrian, T., Boyarchenko, N. and Giannone, D. (2019) 'Vulnerable Growth', American Economic Review, 109(4), pp. 1263-1289.
Angelopoulou, E., Balfoussia, H. and Gibson, H. (2014) 'Building a financial conditions index for the euro area and selected euro area countries: what does it tell us about the crisis?', Economic Modelling, 38, pp. 392-403.
Aramonte, S., Rosen, S. and Schindler, J. (2013) 'Assessing and Combining Financial Conditions Indexes', Finance and Economics Discussion Series, Federal Reserve Board, Washington, D.C.
Arregui, N., Elekdag, S., Gelos, G., Lafarguette, R. and Seneviratne, D. (2018) 'Can Countries Manage Their Financial Conditions Amid Globalization?', IMF Working Paper No. 18/15.
Brave, S. and Butters, R. (2011) 'Monitoring financial stability: A financial conditions index approach', Economic Perspectives, Federal Reserve Bank of Chicago, 35(1), pp. 22-43.
Carlson, M., Lewis, K. and Nelson, W. (2014) 'Using policy intervention to identify financial stress', International Journal of Finance & Economics, 19(1), pp. 59-72.
Few, S. (2009) Now You See It: Simple Visualization Techniques for Quantitative Analysis. Analytics Press, Oakland, CA.
Hatzius, J., Hooper, P., Mishkin, F., Schoenholtz, K. and Watson, M. (2010) 'Financial Conditions Indexes: A Fresh Look after the Financial Crisis', NBER Working Paper No. 16150.
Kliesen, K., Owyang, M. and Vermann, E. (2012) 'Disentangling Diverse Measures: A Survey of Financial Stress Indexes', Federal Reserve Bank of St. Louis Review, 94(5), pp. 369-397.
López-Salido, D., Stein, J. and Zakrajšek, E. (2017) 'Credit-Market Sentiment and the Business Cycle', The Quarterly Journal of Economics, 132(3), pp. 1373-1426.
Rey, H. (2015) 'Dilemma not Trilemma: The Global Financial Cycle and Monetary Policy Independence', NBER Working Paper No. 21162.
NeuroFlow Pro Strategy### Detailed Description: NeuroFlow Pro Strategy
The **NeuroFlow Pro Strategy** is a sophisticated, professional-grade trading system designed for the TradingView platform, crafted to empower traders with high-probability buy and sell signals across various markets, including cryptocurrencies, forex, and stocks. Developed by KoKalito under the MPL-2.0 license, this strategy integrates a diverse set of technical indicators into a unified framework, delivering a **Composite Score** (0–100) that distills complex market dynamics into a single, actionable metric. By blending trend-following, momentum, volatility, volume, and multi-timeframe (MTF) analysis. Without revealing proprietary details, the system leverages a carefully curated mix of classic and advanced techniques, enhanced by dynamic adjustments and robust confirmation mechanisms to filter out noise and focus on high-confidence trades.
**Core Features**:
- **Composite Score**: A normalized score aggregating signals from multiple indicators, where low scores (<30) suggest bullish opportunities and high scores (>70) indicate bearish conditions.
- **Intelligent Signal Generation**: Combines trend, momentum, and pattern-based signals with MTF confirmation, volume divergence, and price action validation to ensure precision.
- **Golden/Death Cross Detection**: Identifies major trend shifts with visual markers (🚀 for bullish EMA 50 crossing above EMA 200, 💀 for bearish crossing below).
- **Dynamic Adaptability**: Adjusts signal parameters based on market conditions (e.g., trending, ranging, volatile) to optimize performance.
- **Comprehensive Dashboard**: Provides real-time insights into market metrics, signal status, and confidence levels, customizable for user preferences.
- **Automated Trading**: Executes trades with precise position sizing, stop-loss, take-profit, and trailing stop logic, incorporating volatility-adjusted risk management.
- **Alert System**: Supports customizable alerts for key events (e.g., signals, crossovers, divergences), enabling timely notifications via TradingView.
The strategy is designed for versatility, performing well on various timeframes (e.g., 1H, 4H, daily) and assets, with a focus on reducing false positives through layered confirmation and adaptive filtering. Its secret sauce lies in the proprietary weighting and confirmation algorithms, which we’ll keep under wraps to maintain its edge. 😉
### User Guide: NeuroFlow Pro Strategy
#### 1. Installation
1. **Access TradingView**:
- Log into your TradingView account (web or app).
2. **Open Pine Editor**:
- Click the “Pine Editor” tab at the bottom of the TradingView interface.
3. **Add the Strategy**:
- Copy the **NeuroFlow Pro Strategy** script (ensure you have the latest version from KoKalito).
- Paste it into the Pine Editor.
- Save with a name like “NeuroFlow Pro Strategy.”
- Click “Add to Chart” to apply it to your active chart (e.g., BTC/USD, ETH/USDT).
4. **Verify Setup**:
- Confirm the strategy’s name appears in the chart’s indicator list (top-left).
- Check for the dashboard (default: right side), EMA plots (white for EMA 50, blue for EMA 200), and strategy metrics in the Strategy Tester tab.
#### 2. Understanding the Strategy
- **Dashboard**:
- Located on the chart (configurable to left or right), it displays real-time metrics:
- **Comp Score**: Composite Score (0–100); <30 is bullish, >70 is bearish, with confidence percentage.
- **Trend**: Bullish, Bearish, or Neutral based on moving averages, SuperTrend, and other trend indicators.
- **MTF Trend**: Trend from a higher timeframe (e.g., 60m, 240m).
- **Momentum**: Bullish, Bearish, or Neutral based on momentum indicators.
- **MFI**: Money Flow Index (Inflow, Outflow, Neutral) for capital flow.
- **Volatility**: High or Low based on market volatility.
- **Volume**: High, Low, or Neutral, colored green for buying pressure, red for selling.
- **Ichimoku**: Bullish, Bearish, or Neutral based on Ichimoku Cloud.
- **ADX Strength**: Strong or Weak trend strength.
- **Divergence**: Bullish, Bearish, or Neutral for price-indicator divergences.
- **Reversal**: Bullish or Bearish reversal potential with confidence percentage.
- **Signal Status**: Long (buy), Short (sell), or None.
- **Signal Confidence**: Confidence percentage for active signals.
- **Entry Price, Stop Level, Take-Profit, Position Size**: Trade-specific metrics for active positions.
- **Win Rates and Profits**: Long/Short win rates, profits, and total performance.
- **Chart Visuals**:
- **EMA 50 (White)**: Tracks short-term trends.
- **EMA 200 (Blue)**: Monitors long-term trends.
- **Golden Cross (🚀)**: Green rocket emoji for bullish EMA 50 crossing above EMA 200.
- **Death Cross (💀)**: Red skull emoji for bearish EMA 50 crossing below EMA 200.
- **Trading Logic**:
- Automatically enters long/short positions based on signals, with dynamic stop-loss, take-profit, and trailing stops.
- Uses volatility-adjusted position sizing to manage risk (configurable via inputs).
- **Alerts**:
- Configurable for buy/sell signals, Golden/Death Cross, divergences, and trade events (e.g., entry, exit).
#### 3. Configuring Settings
1. **Open Settings**:
- Right-click the strategy’s name on the chart and select “Settings,” or double-click it in the indicator list.
2. **Key Settings to Customize**:
- **Strategy Settings**:
- **Take-Profit Ratio (R:R)**: Choose risk-reward ratio (e.g., 2:1, default: 2:1).
- **Risk % per Trade**: Set equity risk per trade (default: 5%).
- **Max ATR Multiplier**: Cap volatility-based position sizing (default: 3.0).
- **Main Settings**:
- **Candlestick Pattern**: Select Hammer, Engulfing, Morning Star, or Custom (default: Hammer).
- **Multi-Timeframe Period**: Higher timeframe for trend analysis (e.g., 60m, default: 60m).
- **Higher Timeframe**: Secondary timeframe (e.g., 240m, default: 240m).
- **Cooldown Bars Preset**: Auto or preset (e.g., 1H: 3 bars, default: Auto).
- **Filters**: Enable/disable patterns, volume, ADX, or support/resistance filters (defaults: patterns off, volume/ADX on).
- **Trading Session**: Restrict trades to specific hours (default: off, 0800-1600 UTC).
- **Momentum Settings**:
- Adjust periods for RSI, Stochastic RSI, MFI, EMAs, ATR, ADX (defaults: RSI 14, EMAs 50/100/200, ATR/ADX 14).
- **Other Indicator Settings**:
- Configure SuperTrend (10/3.0), Bollinger Bands (20/2.0), Ichimoku (9/26/52), MACD (Auto preset).
- **Weights Settings**:
- Prioritize indicators (e.g., Trend 1.0, Momentum 0.3) for the Composite Score.
- **Threshold Settings**:
- Set bullish/bearish reversal thresholds (30/70), ADX threshold (20), signal thresholds (70/80).
- **Dashboard Settings**:
- Position (Left/Right, default: Right).
- Enable/disable metrics (all enabled by default except Volatility, Volume MA).
3. **Save Changes**:
- Click “OK” to apply. The dashboard, signals, and trades update instantly.
#### 4. Using the Strategy
1. **Interpreting Signals**:
- **Buy Signal (Long)**: Triggers when Composite Score is low (<30), with multiple confirmations (e.g., trend, momentum, MTF alignment). Shown as “Long” in Signal Status with confidence percentage.
- **Sell Signal (Short)**: Triggers when Composite Score is high (>70), with confirmations. Shown as “Short.”
- **Golden Cross (🚀)**: Signals a bullish trend shift (EMA 50 > EMA 200). Confirm with Composite Score and Signal Status.
- **Death Cross (💀)**: Signals a bearish trend shift (EMA 50 < EMA 200). Verify with dashboard metrics.
- **Reversal Signals**: Indicates potential reversals (Bullish/Bearish) with confidence percentages.
2. **Monitoring the Dashboard**:
- Use the dashboard for real-time market insights.
- Green (bullish), red (bearish), or gray (neutral) colors highlight conditions.
- Check “Signal Confidence” (>60% is ideal) and trade metrics (e.g., Stop Level, Take-Profit).
3. **Trading**:
- The strategy auto-executes trades based on signals, with dynamic position sizing and risk management.
- Monitor “Position Size,” “Entry Price,” “Stop Level,” and “Take-Profit” in the dashboard.
- Combine signals with external analysis (e.g., support/resistance, news) for added confidence.
4. **Setting Up Alerts**:
- Open the “Alerts” dialog (Alt+A or “Alerts” button).
- Select “NeuroFlow Pro Strategy” and “Any alert() function call” for all alerts (e.g., Long/Short Filled, Golden/Death Cross).
- Configure frequency (“Once Per Bar Close”) and notifications (email, webhook, SMS).
- Create alerts for specific events (e.g., “Golden Cross Detected on BTCUSD (4H)”).
- Test by scrolling to historical events or waiting for live triggers.
#### 5. Best Practices
- **Timeframe Selection**:
- Use 4H or daily for reliable signals, especially for Golden/Death Cross.
- Lower timeframes (e.g., 15m) may increase signals but add noise.
- **Signal Confirmation**:
- Cross-check signals with dashboard metrics (e.g., Trend, ADX, MFI).
- Use Golden/Death Cross as trend filters, not standalone signals.
- **Risk Management**:
- Stick to the default 5% risk per trade or adjust lower (e.g., 2–3%).
- Always review stop-loss and take-profit levels in the dashboard.
- **Backtesting**:
- Use TradingView’s Strategy Tester to evaluate performance (e.g., 6–12 months on BTC/USD).
- Adjust settings (e.g., MACD Preset, Weights) to optimize for your market/timeframe.
- **Market Conditions**:
- Avoid trading in high volatility (dashboard: “Volatility: High”) unless experienced.
- Monitor MTF trends for context (e.g., 60m, 240m alignment).
#### 6. Troubleshooting
- **No Trades**:
- Check if filters (Volume, ADX) are too strict; try disabling them.
- Ensure `mtfTimeframe`/`higherTimeframe` align with your chart (e.g., 60m/240m for 15m).
- **Dashboard Issues**:
- Verify “Dashboard Position” is set (Left/Right).
- Ensure metrics are enabled (e.g., Show Comp Score).
- **Alerts Not Triggering**:
- Confirm “Any alert() function call” is selected in the alert condition.
- Check TradingView’s “Alerts” panel for errors or expired alerts.
- **Crosses Not Visible**:
- Zoom in to see 🚀 (Golden Cross) or 💀 (Death Cross) symbols.
- Ensure EMA lengths (50/200) are distinct.
#### 7. Support
- **Author**: KoKalito (check TradingView profile for updates).
- **Community**: Engage with the TradingView Pine Script community for tips.
- **Documentation**: Refer to TradingView’s Pine Script v5 documentation for customization.
#### 8. Risk Warning
Trading carries significant risks. The **NeuroFlow Pro Strategy** is a tool, not a guarantee of profits. Always conduct your own analysis, use proper risk management, and test thoroughly before live trading.
Happy trading and let’s keep those wins flowing! 😄
Aggregated Perpetual Futures Open InterestPurpose
Aggregates perpetual futures open interest across Binance, Bybit, and OKX for the base currency of the asset loaded in your tradingview window.
How It Works
Symbol detection: The script grabs syminfo.basecurrency (e.g., “BTC”) from whatever market is on screen.
Ticker mapping: It constructs the three perp-OI feeds that TradingView publishes in the form EXCHANGE:USDT.P_OI
Data request: For each feed it fetches the full OHLC candle (request.security) on the chart’s timeframe. If a venue doesn’t list that perp, the request simply returns na.
Aggregation: The script adds the opens, highs, lows, and closes of all non-na feeds to produce a single aggregated OI candle.
General Notes
The status line shows each venue’s individual OI close.
AR Curve// Indicator: AR Curve (годовая доходность к ГО)
// Shows annual-return curve in its own pane (overlay=false)
// Optional session/date filter; value holds outside sessions; stops after LTD.
OpenIn SHG"This indicator is a key tool for understanding the internal dynamics of the market. It analyzes open interest and compares the volume of contracts traded within the futures and financial options markets. By observing this data, it becomes possible to more accurately identify areas where significant institutional activity is concentrated. Since large market participants—such as investment funds, banks, and professional traders—require specific conditions to engage in a market, this indicator becomes a strategic advantage for anticipating significant price movements, assessing the strength of a trend, and detecting potential accumulation or distribution zones."