Linear Regression Relative Strength[image/x/iZvwDWEY/
Relative Strength indicator comparing the current symbol to SPY (or any other benchmark). It may help to pick the right assets to complement the portfolio build around core ETFs such as SPY.
The general idea is to show if the current symbol outperforms or underperforms the benchmark (SPY by default) when bought some certain time ago. Relative performance is displayed as percent and is calculated for three different time ranges - short (1 mo by default), mid (1 quarter), and long (half a year). To smooth the volatility, the script uses linear regression to estimate the trend and takes the start and the end points of the linear regression line to compute the relative strength.
It is important to remember that the script shows the gain relative to SPY (or other selected benchmark), not the asset's gain. Therefore, it may indicate that the asset is profitable, but it still may lose value if SPY is in downtrend.
Therefore, it is crucial to check other indicators before making a decision. In the example above, standard linear regression for one quarter is used to indicate the direction of the trend.
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Drawdown RangeHello death eaters, presenting a unique script which can be used for fundamental analysis or mean reversion based trades.
Process of deriving this table is as below:
Find out ATH for given day
Calculate the drawdown from ATH for the day and drawdown percentage
Based on the drawdown percentage, increment the count of basket which is based on input iNumber of ranges . For example, if number of ranges is 5, then there will be 5 baskets. First basket will fit drawdown percentage 0-20% and each subsequent ones will accommodate next 20% range.
Repeat the process from start to last bar. Once done, table will plot how much percentage of days belong to which basket.
For example, from the below chart of NASDAQ:AAPL
We can deduce following,
Historically stock has traded within 1% drawdown from ATH for 6.59% of time. This is the max amount of time stock has stayed in specific range of drawdown from ATH.
Stock has traded at the drawdown range of 82-83% from ATH for 0.17% of time. This is the least amount of time the stock has stayed in specific range of drawdown from ATH.
At present, stock is trading 2-3% below ATH and this has happened for about 2.46% of total days in trade
Maximum drawdown the stock has suffered is 83%
Lets take another example of NASDAQ:TSLA
Stock is trading at 21-22% below ATH. But, historically the max drawdown range where stock has traded is within 0-1%. Now, if we make this range to show 20 divisions instead of 100, it will look something like this:
Table suggests that stock is trading about 20-25% below ATH - which is right. But, table also suggests that stock has spent most number of days within this drawdown range when we divide it by 20 baskets instad of 100. I would probably wait for price to break out of this range before going long or short. At present, it seems a stage ranging stage. I might think about selling PUTs or covered CALLs outside this range.
Similarly, if you look at AMEX:SPY , 36% of the time, price has stayed within 5% from ATH - makes it a compelling bull case!!
NYSE:BABA is trading at 50-55% below ATH - which is the most it has retraced so far. In general, it is used to be within 15-20% from ATH
NOW, Bit of explanation on input options.
Number of Ranges : Says how many baskets the drawdown map needs to be divided into.
Reference : You can take ATH as reference or chose a time window between which the highest need to be considered for drawdown. This can be useful for megacaps which has gone beyond initial phase of uncertainity. There is no point looking at 80% drawdown AAPL had during 1990s. More approriate to look at it post 2000s where it started making higher impact and growth.
Cumulative Percentage : When this is unchecked, percentage division shows 0-nth percentage instad of percentage ranges. For example this is how it looks on SPY:
We can see that SPY has remained within 6% from ATH for more than 50% of the time.
Hope this is helpful. Happy trading :)
PS: this can be used in conjunction with Drawdown-Price-vs-Fundamentals to pick value stocks at discounted price while also keeping an eye on range tendencies of it.
Thanks to @mattX5 for the ideas and discussion today :)
Altered True Strength Indicator (TSI) Reupload-
Altered TSI provides a slightly more volatile signal that demonstrates extremities in price action with greater success than standard TSI. In addition, I added bull/bear cross indicators (green/red) to make it easier to notice the crosses to save time when the market is moving fast (I couldn't find a regular TSI script with this addition). Finally, the signal also has overextension parameters (red and green lines)
I think this is best used on Intraday time frames as the signals respond to volatility very well and using Heikin Ashi candles, trend is more visual. In this particular example, I am showing SPY on the 3m time chart (my favorite short time frame) and the signal alone provided many opportunities for trades when using simple divergences and countering overextension direction when short term (blue) signal crosses either
In the first example (purple lines), SPY ramps but it was a dull signal given the signal strength flatlining- we would be looking for a short entry. When the signal fires, it provides a clean $1.50 move down in spy.
In the second example (orange), the blue signal provides a nice V shape (rebound signal) in which we are looking for a long entry. 390.50 is a strong SPY support in confluence with 2nd std dev VWAP extension, but disregarding that bull signal fires resulting in a 2 dollar move upwards. Exit is provided when blue line crosses green overextension.
In the third example (white), we are searching for a short entry at 392.5 resistance in confluence with divergently higher highs. Bear cross signal when fired and a significant cross is visible provides a $2.50 move to the downside with a potential exit provided when blue line crosses red overextension line in confluence with previous LOD area.
In the fourth example (green), we watch as the blue line provides a V pattern, we are searching for a long entry. If you didn't take a riskier long at 2nd std dev VWAP overextension with V recovery on blue line at red overextension for a ride to vwap, then you are looking for a secondary entry long as you wouldn't take the trade at resistance (vwap). Bullishly divergent lows provide this entry and the signal does not bear cross at all (but looking for significant crosses is more important even if the signal were to make a minor bear cross). Bullishly divergent double bottom provides a long entry to end of day with a nice clean signal for a $5.00 move until eod or when signal crosses overextension range.
Ideally, close to the money options or SPY/SPXS/SPXL are best used in the intraday time frame.
Again, this is not a standalone indicator but it's best used in conjunction with other indicators/trading strategies
Any questions feel free to comment
Candlestick RSThis is a candlestick charted Relative Strength indicator. It compares the chosen stock's progress compared to that of the SPY ETF ... ( SPY is used so it should hopefully update intraday). I use this indicator to see which stocks are outperforming the market.
Input Variable Descriptions:
Ratio: this variable is a float (0 to 1) that is basically how close the Candlestick RS is to the actual price action of the chart. (1.0 being right on top of it, 0.0 being as far away as possible from it)
Ballpark SPY price: this variable has to be constant, and due to the way pinescript works, you have to manually put in a ballpark of what SPY is at.
Neither of these variables influences the actual data of the indicator, but rather how it is shown on screen. It's difficult to describe, so I recommend you messing around with the variables and see what changes.
Hope this helps, I find this useful, so I figured I'd publish this... This is my first pine script so forgive me for any errors, just want to help :)
Opening Range IndicatorComplete Trading Guide: Opening Range Breakout Strategy
What Are Opening Ranges?
Opening ranges capture the high and low prices during the first few minutes of market open. These levels often act as key support and resistance throughout the trading day because:
Heavy volume occurs at market open as overnight orders execute
Institutional activity is concentrated during opening minutes
Price discovery happens as market participants react to overnight news
Psychological levels are established that traders watch all day
Understanding the Three Timeframes
OR5 (5-Minute Range: 9:30-9:35 AM)
Most sensitive - captures immediate market reaction
Quick signals but higher false breakout rate
Best for scalping and momentum trading
Use for early entry when conviction is high
OR15 (15-Minute Range: 9:30-9:45 AM)
Balanced approach - most popular among day traders
Moderate sensitivity with better reliability
Good for swing trades lasting several hours
Primary timeframe for most strategies
OR30 (30-Minute Range: 9:30-10:00 AM)
Most reliable but slower signals
Lower false breakout rate
Best for position trades and trend following
Use when looking for major moves
Core Trading Strategies
Strategy 1: Basic Breakout
Setup:
Wait for price to break above OR15 high or below OR15 low
Enter on the breakout candle close
Stop loss: Opposite side of the range
Target: 2-3x the range size
Example:
OR15 range: $100.00 - $102.00 (Range = $2.00)
Long entry: Break above $102.00
Stop loss: $99.50 (below OR15 low)
Target: $104.00+ (2x range size)
Strategy 2: Multiple Confirmation
Setup:
Wait for OR5 break first (early signal)
Confirm with OR15 break in same direction
Enter on OR15 confirmation
Stop: Below OR30 if available, or OR15 opposite level
Why it works:
Multiple timeframe confirmation reduces false signals and increases probability of sustained moves.
Strategy 3: Failed Breakout Reversal
Setup:
Price breaks OR15 level but fails to hold
Wait for re-entry into the range
Enter reversal trade toward opposite OR level
Stop: Recent breakout high/low
Target: Opposite side of range + extension
Key insight: Failed breakouts often lead to strong moves in the opposite direction.
Advanced Techniques
Range Quality Assessment
High-Quality Ranges (Trade these):
Range size: 0.5% - 2% of stock price
Clean boundaries (not choppy)
Volume spike during range formation
Clear rejection at range levels
Low-Quality Ranges (Avoid these):
Very narrow ranges (<0.3% of stock price)
Extremely wide ranges (>3% of stock price)
Choppy, overlapping candles
Low volume during formation
Volume Confirmation
For Breakouts:
Look for volume spike (2x+ average) on breakout
Declining volume often signals false breakout
Rising volume during range formation shows interest
Market Context Filters
Best Conditions:
Trending market days (SPY/QQQ with clear direction)
Earnings reactions or news-driven moves
High-volume stocks with good liquidity
Volatility above average (VIX considerations)
Avoid Trading When:
Extremely low volume days
Major economic announcements pending
Holidays or half-days
Choppy, sideways market conditions
Risk Management Rules
Position Sizing
Conservative: Risk 0.5% of account per trade
Moderate: Risk 1% of account per trade
Aggressive: Risk 2% maximum per trade
Stop Loss Placement
Inside the range: Quick exit but higher stop-out rate
Outside opposite level: More room but larger risk
ATR-based: 1.5-2x Average True Range below entry
Profit Taking
Target 1: 1x range size (take 50% off)
Target 2: 2x range size (take 25% off)
Runner: Trail remaining 25% with moving stops
Specific Entry Techniques
Breakout Entry Methods
Method 1: Immediate Entry
Enter as soon as price closes above/below range
Fastest entry but highest false signal rate
Best for strong momentum situations
Method 2: Pullback Entry
Wait for breakout, then pullback to range level
Enter when price bounces off former resistance/support
Better risk/reward but may miss some moves
Method 3: Volume Confirmation
Wait for breakout + volume spike
Enter after volume confirmation candle
Reduces false signals significantly
Multiple Timeframe Entries
Aggressive: OR5 break → immediate entry
Conservative: OR5 + OR15 + OR30 all align → enter
Balanced: OR15 break with OR30 support → enter
Common Mistakes to Avoid
1. Trading Poor-Quality Ranges
❌ Don't trade ranges that are too narrow or too wide
✅ Focus on clean, well-defined ranges with good volume
2. Ignoring Volume
❌ Don't chase breakouts without volume confirmation
✅ Always check for volume spike on breakouts
3. Over-Trading
❌ Don't force trades when ranges are unclear
✅ Wait for high-probability setups only
4. Poor Risk Management
❌ Don't risk more than planned or use tight stops in volatile conditions
✅ Stick to predetermined risk levels
5. Fighting the Trend
❌ Don't fade breakouts in strongly trending markets
✅ Align trades with overall market direction
Daily Trading Routine
Pre-Market (8:00-9:30 AM)
Check overnight news and earnings
Review major indices (SPY, QQQ, IWM)
Identify potential opening range candidates
Set alerts for range breakouts
Market Open (9:30-10:00 AM)
Watch opening range formation
Note volume and price action quality
Mark key levels on charts
Prepare for breakout signals
Trading Session (10:00 AM - 4:00 PM)
Execute breakout strategies
Manage existing positions
Trail stops as profits develop
Look for additional setups
Post-Market Review
Analyze winning and losing trades
Review range quality vs. outcomes
Identify improvement areas
Prepare for next session
Best Stocks/ETFs for Opening Range Trading
Large Cap Stocks (Best for beginners):
AAPL, MSFT, GOOGL, AMZN, TSLA
High liquidity, predictable behavior
Good range formation most days
ETFs (Consistent patterns):
SPY, QQQ, IWM, XLF, XLE
Excellent liquidity
Clear range boundaries
Mid-Cap Growth (Advanced traders):
Stocks with good volume (1M+ shares daily)
Recent news catalysts
Clean technical patterns
Performance Optimization
Track These Metrics:
Win rate by range type (OR5 vs OR15 vs OR30)
Average R/R (risk vs reward ratio)
Best performing market conditions
Time of day performance
Continuous Improvement:
Keep detailed trade journal
Review failed breakouts for patterns
Adjust position sizing based on win rate
Refine entry timing based on backtesting
Final Tips for Success
Start small - Paper trade or use tiny positions initially
Focus on quality - Better to miss trades than take bad ones
Stay disciplined - Stick to your rules even during losing streaks
Adapt to conditions - What works in trending markets may fail in choppy conditions
Keep learning - Markets evolve, so should your approach
The opening range strategy is powerful because it captures natural market behavior, but like all strategies, it requires practice, discipline, and proper risk management to be profitable long-term.
EvoTrend-X Indicator — Evolutionary Trend Learner ExperimentalEvoTrend-X Indicator — Evolutionary Trend Learner
NOTE: This is an experimental Pine Script v6 port of a Python prototype. Pine wasn’t the original research language, so there may be small quirks—your feedback and bug reports are very welcome. The model is non-repainting, MTF-safe (lookahead_off + gaps_on), and features an adaptive (fitness-based) candidate selector, confidence gating, and a volatility filter.
⸻
What it is
EvoTrend-X is adaptive trend indicator that learns which moving-average length best fits the current market. It maintains a small “population” of fast EMA candidates, rewards those that align with price momentum, and continuously selects the best performer. Signals are gated by a multi-factor Confidence score (fitness, strength vs. ATR, MTF agreement) and a volatility filter (ATR%). You get a clean Fast/Slow pair (for the currently best candidate), optional HTF filter, a fitness ribbon for transparency, and a themed info panel with a one-glance STATUS readout.
Core outputs
• Selected Fast/Slow EMAs (auto-chosen from candidates via fitness learning)
• Spread cross (Fast – Slow) → visual BUY/SELL markers + alert hooks
• Confidence % (0–100): Fitness ⊕ Distance vs. ATR ⊕ MTF agreement
• Gates: Trend regime (Kaufman ER), Volatility (ATR%), MTF filter (optional)
• Candidate Fitness Ribbon: shows which lengths the learner currently prefers
• Export plot: hidden series “EvoTrend-X Export (spread)” for downstream use
⸻
Why it’s different
• Evolutionary learning (on-chart): Each candidate EMA length gets rewarded if its slope matches price change and penalized otherwise, with a gentle decay so the model forgets stale regimes. The best fitness wins the right to define the displayed Fast/Slow pair.
• Confidence gate: Signals don’t light up unless multiple conditions concur: learned fitness, spread strength vs. volatility, and (optionally) higher-timeframe trend.
• Volatility awareness: ATR% filter blocks low-energy environments that cause death-by-a-thousand-whipsaws. Your “why no signal?” answer is always visible in the STATUS.
• Preset discipline, Custom freedom: Presets set reasonable baselines for FX, equities, and crypto; Custom exposes all knobs and honors your inputs one-to-one.
• Non-repainting rigor: All MTF calls use lookahead_off + gaps_on. Decisions use confirmed bars. No forward refs. No conditional ta.* pitfalls.
⸻
Presets (and what they do)
• FX 1H (Conservative): Medium candidates, slightly higher MinConf, modest ATR% floor. Good for macro sessions and cleaner swings.
• FX 15m (Active): Shorter candidates, looser MinConf, higher ATR% floor. Designed for intraday velocity and decisive sessions.
• Equities 1D: Longer candidates, gentler volatility floor. Suits index/large-cap trend waves.
• Crypto 1H: Mid-short candidates, higher ATR% floor for 24/7 chop, stronger MinConf to avoid noise.
• Custom: Your inputs are used directly (no override). Ideal for systematic tuning or bespoke assets.
⸻
How the learning works (at a glance)
1. Candidates: A small set of fast EMA lengths (e.g., 8/12/16/20/26/34). Slow = Fast × multiplier (default ×2.0).
2. Reward/decay: If price change and the candidate’s Fast slope agree (both up or both down), its fitness increases; otherwise decreases. A decay constant slowly forgets the distant past.
3. Selection: The candidate with highest fitness defines the displayed Fast/Slow pair.
4. Signal engine: Crosses of the spread (Fast − Slow) across zero mark potential regime shifts. A Confidence score and gates decide whether to surface them.
⸻
Controls & what they mean
Learning / Regime
• Slow length = Fast ×: scales the Slow EMA relative to each Fast candidate. Larger multiplier = smoother regime detection, fewer whipsaws.
• ER length / threshold: Kaufman Efficiency Ratio; above threshold = “Trending” background.
• Learning step, Decay: Larger step reacts faster to new behavior; decay sets how quickly the past is forgotten.
Confidence / Volatility gate
• Min Confidence (%): Minimum score to show signals (and fire alerts). Raising it filters noise; lowering it increases frequency.
• ATR length: The ATR window for both the ATR% filter and strength normalization. Shorter = faster, but choppier.
• Min ATR% (percent): ATR as a percentage of price. If ATR% < Min ATR% → status shows BLOCK: low vola.
MTF Trend Filter
• Use HTF filter / Timeframe / Fast & Slow: HTF Fast>Slow for longs, Fast threshold; exit when spread flips or Confidence decays below your comfort zone.
2) FX index/majors, 15m (active intraday)
• Preset: FX 15m (Active).
• Gate: MinConf 60–70; Min ATR% 0.15–0.30.
• Flow: Focus on session opens (LDN/NY). The ribbon should heat up on shorter candidates before valid crosses appear—good early warning.
3) SPY / Index futures, 1D (positioning)
• Preset: Equities 1D.
• Gate: MinConf 55–65; Min ATR% 0.05–0.12.
• Flow: Use spread crosses as regime flags; add timing from price structure. For adds, wait for ER to remain trending across several bars.
4) BTCUSD, 1H (24/7)
• Preset: Crypto 1H.
• Gate: MinConf 70–80; Min ATR% 0.20–0.35.
• Flow: Crypto chops—volatility filter is your friend. When ribbon and HTF OK agree, favor continuation entries; otherwise stand down.
⸻
Reading the Info Panel (and fixing “no signals”)
The panel is your self-diagnostic:
• HTF OK? False means the higher-timeframe EMAs disagree with your intended side.
• Regime: If “Chop”, ER < threshold. Consider raising the threshold or waiting.
• Confidence: Heat-colored; if below MinConf, the gate blocks signals.
• ATR% vs. Min ATR%: If ATR% < Min ATR%, status shows BLOCK: low vola.
• STATUS (composite):
• BLOCK: low vola → increase Min ATR% down (i.e., allow lower vol) or wait for expansion.
• BLOCK: HTF filter → disable HTF or align with the HTF tide.
• BLOCK: confidence → lower MinConf slightly or wait for stronger alignment.
• OK → you’ll see markers on valid crosses.
⸻
Alerts
Two static alert hooks:
• BUY cross — spread crosses up and all gates (ER, Vol, MTF, Confidence) are open.
• SELL cross — mirror of the above.
Create them once from “Add Alert” → choose the condition by name.
⸻
Exporting to other scripts
In your other Pine indicators/strategies, add an input.source and select EvoTrend-X → “EvoTrend-X Export (spread)”. Common uses:
• Build a rule: only trade when exported spread > 0 (trend filter).
• Combine with your oscillator: oscillator oversold and spread > 0 → buy bias.
⸻
Best practices
• Let it learn: Keep Learning step moderate (0.4–0.6) and Decay close to 1.0 (e.g., 0.99–0.997) for smooth regime memory.
• Respect volatility: Tune Min ATR% by asset and timeframe. FX 1H ≈ 0.10–0.20; crypto 1H ≈ 0.20–0.35; equities 1D ≈ 0.05–0.12.
• MTF discipline: HTF filter removes lots of “almost” trades. If you prefer aggressive entries, turn it off and rely more on Confidence.
• Confidence as throttle:
• 40–60%: exploratory; expect more signals.
• 60–75%: balanced; good daily driver.
• 75–90%: selective; catch the clean stuff.
• 90–100%: only A-setups; patient mode.
• Watch the ribbon: When shorter candidates heat up before a cross, momentum is forming. If long candidates dominate, you’re in a slower trend cycle.
⸻
Non-repainting & safety notes
• All request.security() calls use lookahead=barmerge.lookahead_off, gaps=barmerge.gaps_on.
• No forward references; decisions rely on confirmed bar data.
• EMA lengths are simple ints (no series-length errors).
• Confidence components are computed every bar (no conditional ta.* traps).
⸻
Limitations & tips
• Chop happens: ER helps, but sideways microstructure can still flicker—use Confidence + Vol filter as brakes.
• Presets ≠ oracle: They’re sensible baselines; always tune MinConf and Min ATR% to your venue and session.
• Theme “Auto”: Pine cannot read chart theme; “Auto” defaults to a Dark-friendly palette.
⸻
Publisher’s Screenshots Checklist
1) FX swing — EURUSD 1H
• Preset: FX 1H (Conservative)
• Params: MinConf=70, ATR Len=14, Min ATR%=0.12, MTF ON (TF=4H, 20/50)
• Show: Clear BUY cross, STATUS=OK, green regime background; Fitness Ribbon visible.
2) FX intraday — GBPUSD 15m
• Preset: FX 15m (Active)
• Params: MinConf=60, ATR Len=14, Min ATR%=0.20, MTF ON (TF=60m)
• Show: SELL cross near London session open. HTF lines enabled (translucent).
• Caption: “GBPUSD 15m • Active session sell with MTF alignment.”
3) Indices — SPY 1D
• Preset: Equities 1D
• Params: MinConf=60, ATR Len=14, Min ATR%=0.08, MTF ON (TF=1W, 20/50)
• Show: Longer trend run after BUY cross; regime shading shows persistence.
• Caption: “SPY 1D • Trend run after BUY cross; weekly filter aligned.”
4) Crypto — BINANCE:BTCUSDT 1H
• Preset: Crypto 1H
• Params: MinConf=75, ATR Len=14, Min ATR%=0.25, MTF ON (TF=4H)
• Show: BUY cross + quick follow-through; Ribbon warming (reds/yellows → greens).
• Caption: “BTCUSDT 1H • Momentum break with high confidence and ribbon turning.”
Sector Rotation & Money Flow Dashboard📊 Overview
The Sector Rotation & Money Flow Dashboard is a comprehensive market analysis tool that tracks 39 major sector ETFs in real-time, providing institutional-grade insights into sector rotation, momentum shifts, and money flow patterns. This indicator helps traders identify which sectors are attracting capital, which are losing favor, and where the next opportunities might emerge.
Perfect for swing traders, position traders, and investors who want to stay ahead of sector rotation and ride the strongest trends while avoiding weak sectors.
🎯 What This Indicator Does
Tracks 39 Major Sectors: From technology to utilities, cryptocurrencies to commodities
Calculates Multiple Timeframes: 1-week, 1-month, 3-month, and 6-month performance
Advanced Momentum Metrics: Proprietary momentum score and acceleration calculations
Relative Strength Analysis: Compare sector performance against any benchmark index
Money Flow Signals: Visual indicators showing where institutional money is moving
Smart Filtering: Pre-built strategy filters for different trading styles
Trend Detection: Emoji-based visual system for quick trend identification
💡 Key Features
1. Performance Metrics
Multiple timeframe analysis (1W, 1M, 3M, 6M)
Month-over-month change tracking
Relative strength vs benchmark index
2. Advanced Analytics
Momentum Score: Weighted composite of recent performance
Acceleration: Rate of change in momentum (second derivative)
Money Flow Signals: IN/OUT/TURN/WATCH indicators
3. Strategy Preset Filters
🎯 Swing Trade: High momentum opportunities
📈 Trend Follow: Established uptrends
🔄 Mean Reversion: Oversold bounce candidates
💎 Value Hunt: Deep value opportunities
🚀 Breakout: Emerging strength
⚠️ Risk Off: Sectors to avoid
4. Customization
All 39 sector ETFs can be customized
Adjustable benchmark index
Flexible display options
Multiple sorting methods
📋 Settings Documentation
Display Settings
Show Table (Default: On)
Toggles the entire dashboard display
Table Position (Default: Middle Center)
Choose from 9 positions on your chart
Options: Top/Middle/Bottom × Left/Center/Right
Rows to Show (Default: 15)
Number of sectors displayed (5-40)
Useful for focusing on top/bottom performers
Sort By (Default: Momentum)
1M/3M/6M: Sort by specific timeframe performance
Momentum: Weighted recent performance score
Acceleration: Rate of momentum change
1M Change: Month-over-month improvement
RS: Relative strength vs benchmark
Flow: IN First: Prioritize sectors with inflows
Flow: TURN First: Focus on reversal candidates
Recovery Plays: Oversold sectors recovering
Oversold Bounce: Deepest declines with positive signs
Top Gainers/Losers 3M: Best/worst quarterly performers
Best Acc + Mom: Combined strength score
Worst Acc (Topping): Sectors losing momentum
Filter Settings
Strategy Preset Filter (Default: All)
All: No filtering
🎯 Swing Trade: Mom >5, Acc >2, Money flowing in
📈 Trend Follow: Positive 1M & 3M, RS >0
🔄 Mean Reversion: Oversold but improving
💎 Value Hunt: Down >10% with recovery signs
🚀 Breakout: Rapid momentum surge
⚠️ Risk Off: Declining or topping sectors
Custom Flow Filter: Use manual flow filter
Custom Flow Signal Filter (Default: All)
Only active when Strategy Preset = "Custom Flow Filter"
IN Only: Strong inflows
TURN Only: Reversal signals
WATCH Only: Recovery candidates
OUT Only: Outflow sectors
Active Flows Only: Any non-neutral signal
Hide Low Volume ETFs (Default: Off)
Filters out illiquid sectors (future enhancement)
Visual Settings
Show Trend Emojis (Default: On)
🚀 Breakout (Strong 1M + High Acceleration)
🔥 Hot Recovery (From -10% to positive)
💪 Steady Uptrend (All timeframes positive)
➡️ Sideways/Ranging
⚠️ Warning/Topping (Up >15%, now slowing)
📉 Falling (Negative + declining)
🔄 Bottoming (Improving from lows)
Compact Mode (Default: Off)
Removes decimals for cleaner display
Useful when showing many rows
Min Data Points Required (Default: 3)
Minimum data points needed to display a sector
Prevents showing sectors with insufficient data
Relative Strength Settings
RS Benchmark Index (Default: AMEX:SPY)
Index to compare all sectors against
Can use SPY, QQQ, IWM, or any other index
RS Period (Days) (Default: 21)
Lookback period for RS calculation
21 days = 1 month, 63 days = 3 months, etc.
Sector ETF Settings (Groups 1-39)
Each sector has two inputs:
Symbol: The ticker (e.g., "AMEX:XLF")
Name: Display name (e.g., "Financials")
All 39 sectors can be customized to track different ETFs or markets.
📈 Column Explanations
Sector: ETF name/description
1M%: 1-month (21-day) performance
3M%: 3-month (63-day) performance
6M%: 6-month (126-day) performance
Mom: Momentum score (weighted average, recent-biased)
Acc: Acceleration (momentum rate of change)
Δ1M: Month-over-month change
RS: Relative strength vs benchmark
Flow: Money flow signal
↗️ IN: Strong inflows
🔄 TURN: Potential reversal
👀 WATCH: Recovery candidate
↘️ OUT: Outflows
—: Neutral
🎮 Usage Tips
For Swing Traders (3-14 days)
Use "🎯 Swing Trade" filter
Sort by "Acceleration" or "Momentum"
Look for Flow = "IN" and Mom >10
Confirm with positive RS
For Position Traders (2-8 weeks)
Use "📈 Trend Follow" filter
Sort by "RS" or "Best Acc + Mom"
Focus on consistent green across timeframes
Ensure RS >3 for market leaders
For Value Investors
Use "💎 Value Hunt" filter
Sort by "Recovery Plays" or "Top Losers 3M"
Look for improving Δ1M
Check for "WATCH" or "TURN" signals
For Risk Management
Regularly check "⚠️ Risk Off" filter
Sort by "Worst Acc (Topping)"
Review holdings for ⚠️ warning emojis
Exit sectors showing "OUT" flow
Market Regime Recognition
Bull Market: Many sectors showing "IN" flow, positive RS
Bear Market: Widespread "OUT" flows, negative RS
Rotation: Mixed flows, some "IN" while others "OUT"
Recovery: Multiple "TURN" and "WATCH" signals
🔧 Pro Tips
Combine Filters + Sorting: Filter first to narrow candidates, then sort to prioritize
Multi-Timeframe Confirmation: Best setups show alignment across 1M, 3M, and momentum
RS is Key: Sectors outperforming SPY (RS >0) tend to continue outperforming
Acceleration Matters: Positive acceleration often precedes price breakouts
Flow Transitions: "WATCH" → "TURN" → "IN" progression identifies new trends early
Regular Scans:
Daily: Check "Acceleration" sort
Weekly: Review "1M Change"
Monthly: Analyze "RS" shifts
Divergence Signals:
Price up but Acceleration down = Potential top
Price down but Acceleration up = Potential bottom
Sector Pairs Trading: Long sectors with "IN" flow, short sectors with "OUT" flow
⚠️ Important Notes
This indicator makes 40 security requests (maximum allowed)
Best used on Daily timeframe
Data updates in real-time during market hours
Some ETFs may show "—" if data is unavailable
🎯 Common Strategies
"Follow the Flow"
Only trade sectors showing "IN" flow with positive RS
"Rotation Catcher"
Focus on "TURN" signals in sectors down >15% from highs
"Momentum Rider"
Trade top 3 sectors by Momentum score, exit when Acceleration turns negative
"Mean Reversion"
Buy sectors in bottom 20% by 3M performance when Δ1M improves
"Relative Strength Leader"
Maintain positions only in sectors with RS >5
Not financial advice - always do additional research
Defense Mode Dashboard ProWhat it is
A one‑look market regime dashboard for ES, NQ, YM, RTY, and SPY that tells you when to play defense, when you might have an offense cue, and when to chill. It blends VIX, VIX term structure, ATR 5 over 60, and session gap signals with clean alerts and a compact table you can park anywhere.
Why traders like it
Because it filters out the noise. Regime first, tactics second. You avoid trading size into landmines and lean in when volatility cooperates.
What it measures
Volatility stress with VIX level and VIX vs 20‑SMA
Term structure using VX1 vs VX2 with two modes
Diff mode: VX1 minus VX2
Ratio mode: VX1 divided by VX2
Realized volatility using ATR5 over ATR60 with optional smoothing
Session risk from RTH opening gaps and overnight range, normalized by ATR
How to use in 30 seconds
Pick a preset in the inputs. ES, NQ, YM, RTY, SPY are ready.
Leave thresholds at defaults to start.
Add one TradingView alert using “Any alert() function call”.
Trade smaller or stand aside when the header reads DEFENSE ON. Consider leaning in only when you see OFFENSE CUE and your playbook agrees.
Defaults we recommend
VIX triggers: 22 and 1.25× the 20‑SMA
Term mode: Diff with tolerance 0.00. Use Ratio at 1.00+ for choppier markets
ATR 5/60 defense: 1.25. Offense cue: 0.85 or lower
ATR smoothing: 1. Try 2 to 3 if you want fewer flips
Gap mode: RTH. Turn Both on if you want ON range to count too
RTH wild gap: 0.60× ATR5. ON wild range: 0.80× ATR5
Alert cadence: Once per RTH session
Snooze: Quick snooze first 30 minutes on. Fire on snooze exit off, unless you really want the catch‑up ping
New since the last description
Multi‑asset presets set symbols and RTH windows for ES, NQ, YM, RTY, SPY
Term ratio mode with near‑flat warning when ratio is between 1.00 and your trigger
ATR smoothing for the 5 over 60 ratio
RTH keying for cadence, so “Once per RTH session” behaves like a trader expects
Snooze upgrades with quick snooze tied to the first N minutes of RTH and an optional fire‑on‑snooze‑exit
Compact title merge and user color controls for labels, values, borders, and background
Exposed series for integrations: DefenseOn(1=yes) and OffenseCue(1=yes)
Debug toggle to visualize gap points, ON range, and term readings
Stronger NA handling with a clear “No core data” row when feeds are missing
Notes
Dynamic alerts require “Any alert() function call”.
Works on any chart timeframe. Daily reads and 1‑minute anchors handle the regime logic.
Volumetric Expansion/Contraction### Indicator Title: Volumetric Expansion/Contraction
### Summary
The Volumetric Expansion/Contraction (PCC) indicator is a comprehensive momentum oscillator designed to identify high-conviction price moves. Unlike traditional oscillators that only look at price, the PCC integrates four critical dimensions of market activity: **Price Change**, **Relative Volume (RVOL)**, **Cumulative Volume Delta (CVD)**, and **Average True Range (ATR)**.
Its primary purpose is to help traders distinguish between meaningful, volume-backed market expansions and noisy, unsustainable price action. It gives more weight to moves that occur in a controlled, low-volatility environment, highlighting potential starts of new trends or significant shifts in market sentiment.
### Key Concepts & Purpose
The indicator's unique formula synthesizes the following concepts:
1. **Price Change:** Measures the magnitude and direction of the primary move.
2. **Relative Volume (RVOL):** Confirms that the move is backed by significant volume compared to its recent average, indicating institutional participation.
3. **Cumulative Volume Delta (CVD):** Measures the underlying buying and selling pressure, confirming that the price move is aligned with the net flow of market orders.
4. **Inverse Volatility (ATR):** This is the indicator's unique twist. It normalizes the signal by the inverse of the Average True Range. This means the indicator's value is **amplified** when volatility (ATR) is low (signifying a controlled, confident expansion) and **dampened** when volatility is high (filtering out chaotic, less predictable moves).
The goal is to provide a single, easy-to-read oscillator that signals when price, volume, and order flow are all in alignment, especially during a breakout from a period of contraction.
### Features
* **Main Oscillator Line:** A single line plotted in a separate pane that represents the calculated strength of the volumetric expansion or contraction.
* **Zero Line:** A dotted reference line to easily distinguish between bullish (above zero) and bearish (below zero) regimes.
* **Visual Threshold Zones:** The background automatically changes color to highlight periods of significant strength:
* **Bright Green:** Indicates a "Strong Up Move" when the oscillator crosses above the user-defined upper threshold.
* **Bright Fuchsia:** Indicates a "Strong Down Move" when the oscillator crosses below the user-defined lower threshold.
### Configurable Settings & Filters
The indicator is fully customizable to allow for extensive testing and adaptation to different assets and timeframes.
#### Main Calculation Inputs
* **Price Change Lookback:** Sets the period for calculating the primary price change.
* **CVD Normalization Length:** The lookback period for normalizing the Cumulative Volume Delta.
* **RVOL Avg Volume Length:** The lookback for the simple moving average of volume, used to calculate RVOL.
* **RVOL Normalization Length:** The lookback period for normalizing the RVOL score.
* **ATR Length & Normalization Length:** Sets the periods for calculating the ATR and its longer-term average for normalization.
#### Weights
* Fine-tune the impact of each core component on the final calculation, allowing you to emphasize what matters most to your strategy (e.g., give more weight to CVD or RVOL).
#### External Market Filter (Powerful Feature)
* **Enable SPY/QQQ Filter for Up Moves?:** A checkbox to activate a powerful regime filter.
* **Symbol:** A dropdown to choose whether to filter signals based on the trend of **SPY** or **QQQ**.
* **SMA Period:** Sets the lookback period for the Simple Moving Average (default is 50).
* **How it works:** When enabled, this filter will **only allow "Strong Up Move" signals to appear if the chosen symbol (SPY or QQQ) is currently trading above its specified SMA**. This is an excellent tool for aligning your signals with the broader market trend and avoiding bullish entries in a bearish market.
#### Visuals
* **Upper/Lower Threshold:** Allows you to define what level the oscillator must cross to trigger the colored background zones, letting you customize the indicator's sensitivity.
***
**Disclaimer:** This tool is designed for market analysis and confluence. It is not a standalone trading system. Always use this indicator in conjunction with your own trading strategy, risk management, and other forms of analysis.
A+ Trade CheckList with Comprehensive Relative StrengthThe indicator designed for traders who need real-time market assessment across multiple timeframes and benchmarks. This comprehensive tool combines traditional technical analysis with sophisticated relative strength measurements to provide a complete market picture in one convenient table display.
The indicator tracks essential trading levels including:
QQQ and SPY trend analysis using exponential moving averages
Previous day and week high/low levels for key support and resistance
Market open levels from the first 5 and 15 minutes of trading (9:30 AM ET)
VWAP positioning for institutional price reference
Short-term EMA positioning for momentum assessment
Advanced Relative Strength Analysis
The standout feature of this indicator is its comprehensive 8-metric relative strength scoring system that compares your current ticker against both QQQ (Nasdaq-100) and SPY (S&P 500) benchmarks.
The 4-Metric Relative Strength System Explained
Metric 1: Relative Strength Ratio (RSR)
Purpose: Measures whether your ticker is outperforming or underperforming relative to its historical relationship with the benchmarks.
How it works:
Calculates the ratio of your ticker's price to QQQ/SPY prices
Compares current ratio to a 20-period moving average of the ratio
Scores +1 if ratio is above average (relative strength), -1 if below (relative weakness)
Trading significance: Identifies when a stock is breaking out of its normal correlation pattern with major indices.
Metric 2: Percentage-Based Relative Performance
Purpose: Compares short-term percentage changes to identify immediate relative momentum.
How it works:
Calculates 5-day percentage change for your ticker and benchmarks
Subtracts benchmark performance from ticker performance
Scores +1 if outperforming by >1%, -1 if underperforming by >1%, 0 for neutral
Trading significance: Captures recent momentum shifts and identifies stocks moving independently of market direction.
Metric 3: Beta-Adjusted Relative Strength (Alpha)
Purpose: Measures risk-adjusted performance by accounting for the ticker's natural volatility relationship with benchmarks.
How it works:
Calculates rolling beta (correlation and variance relationship)
Determines expected returns based on benchmark moves and beta
Measures alpha (excess returns above/below expectations)
Scores based on whether alpha is consistently positive or negative
Trading significance: Identifies stocks generating returns beyond what their risk profile would suggest, indicating fundamental strength or weakness.
Metric 4: Volume-Weighted Relative Strength
Purpose: Incorporates volume analysis to validate price-based relative strength signals.
How it works:
Compares VWAP-based percentage changes between ticker and benchmarks
Applies volume weighting factor based on relative volume strength
Enhances score when high relative volume confirms price movements
Trading significance: Distinguishes between genuine institutional-driven moves and low-volume price action that may not sustain.
Combined Scoring System
The indicator generates 8 individual scores (4 metrics × 2 benchmarks) that combine into a single strength assessment:
Score Interpretation
Strong (4-8 points): Ticker significantly outperforming both benchmarks across multiple methodologies
Moderate Strong (1-3 points): Ticker showing good relative strength with some mixed signals
Neutral (0 points): Balanced performance relative to benchmarks
Moderate Weak (-1 to -3 points): Ticker showing relative weakness with some mixed signals
Weak (-4 to -8 points): Ticker significantly underperforming both benchmarks
Display Format
The indicator shows results as: "Strong (6/8)" indicating the ticker scored 6 out of 8 possible points.
Capitulation Volume Detector by @RhinoTradezOverview
Hey traders, want to catch the market when it’s totally losing it? The Capitulation Volume Detector is your go-to buddy for spotting those wild moments when panic selling takes over. Picture this: prices plummet, volume explodes, and everyone’s bailing out—that’s capitulation, and it might just signal a turning point. This script throws a bright marker on your chart whenever the chaos hits, so you can decide if it’s time to jump in or sit tight. Built fresh in Pine Script v6, it’s sleek, customizable, and packs an alert to keep you posted—perfect for stocks, indices like SPY, or even crypto chaos.
Inspired by epic sell-offs like March 2020’s COVID crash, this tool’s here to help you navigate the storm with a smile (and maybe a profit).
What It Does
Capitulation volume is that “everyone’s out!” moment: a steep price drop meets a massive volume surge, hinting that sellers are tapped out. It’s not a guaranteed reversal—sometimes the bleeding continues—but it’s a loud clue that fear’s peaked. Here’s the magic:
Volume Check : Measures current volume against a customizable average (default: 20 bars).
Price Plunge : Tracks the percentage drop from the last close.
Capitulation Cal l: When volume rockets past your threshold (e.g., 2x average) and price tanks (e.g., -5%), you get a red triangle above the bar.
Stay Alert : Fires off a detailed message (e.g., “Volume 300M > 200M, Drop -10%”) so you’re never caught off guard.
Think of it as your market meltdown radar—simple, effective, and ready to roll.
Functionality Breakdown
Volume Surge Spotter :
Uses a 20-bar Simple Moving Average (SMA) of volume as your baseline.
Flags any bar where volume exceeds this average by your chosen multiplier (default: 2x).
Price Drop Detector :
Calculates the percentage change from the prior close.
Triggers when the drop’s bigger than your set limit (default: -5%).
Capitulation Marker:
Combines both signals: high volume + sharp drop = capitulation.
Slaps a red triangle above the bar for instant “whoa, there it is!” vibes.
Real-Time Alerts :
Sends a custom alert with volume and drop details, keeping you in the loop without babysitting the chart.
Customization Options
Tune it to your trading style with these easy settings:
Volume Multiplier (x Avg): Starts at 2.0 (2x average volume). Bump it to 3.0 for only the wildest spikes or dial it to 1.5 for more frequent catches. Range: 1.0-10.0, step 0.1.
Price Drop Threshold (%): Default 5.0 (a -5% drop). Go big with 10.0 for crash-level falls or ease to 3.0 for lighter dips. Range: 1.0-20.0, step 0.1.
Average Volume Period: Default 20 bars. Stretch it to 50 for a broader view or shrink to 10 for quick reactions. Range: 1-100.
Capitulation Marker Color: Red by default—because panic’s loud! Switch it to blue, green, or pink to match your chart’s personality.
How to Use It
Drop It On : Add it to any chart with volume data—SPY daily for market moves, /ES 15-minute for intraday action, or your go-to stock.
Play with Settings : Hit the indicator’s config gear and tweak the multiplier, drop threshold, period, or marker color to fit your vibe.
Set an Alert : Right-click the indicator, add an alert with “Any alert() function call,” and get pinged when capitulation strikes.
Watch the Action : Look for those red triangles on big drop days—pair with your favorite reversal signals for extra oomph.
Pro Tips
Daily Charts : Catch market-wide capitulations like March 23, 2020 (SPY: -10%, 3x volume).
Intraday : Spot flash crashes or sector sell-offs on 15-minute or 5-minute bars.
Context Matters : High volume alone isn’t enough—check the VIX or candlestick patterns (e.g., hammers) to confirm a bottom.
BKLevelsThis displays levels from a text input, levels from certain times on the previous day, and high/low/close from previous day. The levels are drawn for the date in the first line of the text input. Newlines are required between each level
Example text input:
2024-12-17
SPY,606,5,1,Lower Hvol Range,FIRM
SPY,611,1,1,Last 20K CBlock,FIRM
SPY,600,2,1,Last 20K PBlock,FIRM
SPX,6085,1,1,HvolC,FIRM
SPX,6080,2,1,HvolP,FIRM
SPX,6095,3,1,Upper PDVR,FIRM
SPX,6060,3,1,Lower PDVR,FIRM
For each line, the format is ,,,,,
For color, there are 9 possible user- configurable colors- so you can input numbers 1 through 9
For line style, the possible inputs are:
"FIRM" -> solid line
"SHORT_DASH" -> dotted line
"MEDIUM_DASH" -> dashed line
"LONG_DASH" -> dashed line
Correlation Coefficient [Giang]### **Introduction to the "Correlation Coefficient" Indicator**
#### **Idea behind the Indicator**
The "Correlation Coefficient" indicator was developed to analyze the linear relationship between Bitcoin (**BTCUSD**) and other important economic indices or financial assets, such as:
- **SPX** (S&P 500 Index): Represents the U.S. stock market.
- **DXY** (Dollar Index): Reflects the strength of the USD against major currencies.
- **SPY** (ETF representing the S&P 500): A popular trading instrument.
- **GOLD** (Gold price): A traditional safe-haven asset.
The correlation between these assets can help traders understand how Bitcoin reacts to market movements of traditional financial instruments, providing opportunities for more effective trading decisions.
Additionally, the indicator allows users to **customize asset symbols for comparison**, not limited to the default indices (SPX, DXY, SPY, GOLD). This flexibility enables traders to tailor their analysis to specific goals and portfolios.
---
#### **Significance and Use of Correlation in Trading**
**Correlation** is a measure of the linear relationship between two data series. In the context of this indicator:
- **The correlation coefficient ranges from -1 to 1**:
- **1**: Perfect positive relationship (both increase or decrease together).
- **0**: No linear relationship.
- **-1**: Perfect negative relationship (one increases while the other decreases).
- **Use in trading**:
- Identify **strong relationships or unusual divergences** between Bitcoin and other assets.
- Help determine **market sentiment**: For example, if Bitcoin has a negative correlation with DXY, traders might expect Bitcoin to rise when the USD weakens.
- Provide a foundation for hedging strategies or investments based on inter-asset relationships.
---
#### **Components of the Indicator**
The "Correlation Coefficient" indicator consists of the following key components:
1. **Main Data (BTCUSD)**:
- The closing price of Bitcoin is used as the central asset for calculations.
2. **Comparison Data**:
- Users can select different asset symbols for comparison. By default, the indicator supports:
- **SPX**: Stock market index.
- **DXY**: Dollar Index.
- **SPY**: Popular ETF.
- **GOLD**: Gold price.
3. **Correlation Coefficients**:
- Calculated between BTC and each comparison index, based on a Weighted Moving Average (WMA) over a user-defined period.
4. **Graphical Representation**:
- Displays individual correlation coefficients with each comparison index, making it easier for traders to track and analyze.
---
#### **How to Analyze and Use the Indicator**
**1. Identify Key Correlations:**
- Observe the correlation lines between BTC and the indices to determine positive or negative relationships.
- Example:
- If the **Correlation Coefficient (BTC-DXY)** sharply declines to -1, this indicates that when USD strengthens, Bitcoin tends to weaken.
**2. Analyze the Strength of Correlations:**
- **Strong Correlations**: If the coefficient is close to 1 or -1, the relationship between the two assets is very clear.
- **Weak Correlations**: If the coefficient is near 0, Bitcoin may be influenced by other factors outside the compared index.
**3. Develop Trading Strategies:**
- Use correlations to predict Bitcoin's price movements:
- If BTC has an inverse relationship with **DXY**, traders might consider selling BTC when the USD strengthens.
- If BTC and **SPX** are strongly correlated, traders can monitor the stock market to predict Bitcoin's trend.
**4. Evaluate Changes Over Time:**
- Use different timeframes (daily, weekly) to track the correlation's fluctuations.
- Look for unusual signals, such as a breakdown or shift from positive to negative relationships.
---
#### **Conclusion**
The "Correlation Coefficient" indicator is a powerful tool that helps traders analyze the relationship between Bitcoin and major financial indices. The ability to customize asset symbols for comparison makes the indicator flexible and suitable for various trading strategies. When used correctly, this indicator not only provides insights into market sentiment but also supports the development of intelligent trading strategies and optimized profits.
Daily MAs on Intraday ChartsThis is a very simple, yet powerful indicator, for intraday and swing traders.
The indicator plots price levels of key daily moving averages as horizontal lines onto intraday charts.
The key daily moving averages being:
5-day EMA
10-day EMA
21-day EMA
50-day SMA
100-day SMA
200-day SMA
The moving averages above can be toggled on and off to the users liking and different colours selected to show the locations of daily moving average price levels on intraday charts.
Below is a chart of the SPY on the 30-minute timeframe. The black line represents the price level of the SPY's 10-day EMA, and the blue line represents the price level of the SPY's 21-day EMA.
Key daily moving averages like those mentioned above can be areas of support or resistance for major indexes, ETFs, and individual stocks. Therefore, when using multiple timeframe analysis combining daily charts and intraday charts, it's useful to be aware of these key daily moving average levels for potential reversals.
This indicator clearly shows where the key daily moving average price levels are on intraday charts for the chosen ticker symbol, thus helping traders to identify potential points of interest for trading ideas - i.e., going long or pullbacks into key daily moving averages, or short on rallies into key daily moving averages subject to the trader's thoughts at the time.
By using the 'Daily MAs on Intraday Charts' the trader can now have a multi-chart layout and be easily aware of key price levels from daily moving averages when looking at various intraday timeframe charts such as the 1-minute, 5-minute, 15-minute, 30-minute, 1-hour etc. This can be essential information for opening long and short trading ideas.
Trade Entry Detector, Wick to Body Ratio Trade Entry Detector: Wick-to-Body Ratio Strategy with Bollinger Bands
Overview
The Trade Entry Detector is a custom strategy for TradingView that leverages the Bollinger Bands and a unique wick-to-body ratio approach to capture precise entry opportunities. This indicator is designed for traders who want to pinpoint high-probability reversal points when price interacts with Bollinger Bands, all while offering flexible entry fill options.
The strategy performs primary analysis on the daily time frame, regardless of your current chart setting, allowing you to view daily Bollinger Band levels and entry signals even on lower time frames. This approach is suitable for swing traders and short-term traders looking to align intraday moves with higher time frame signals.
How the Strategy Works
1. Bollinger Band Analysis on the Daily Time Frame
Bollinger Bands are calculated using a 20-period simple moving average (SMA) and a standard deviation multiplier (default is 2). These bands dynamically expand and contract based on market volatility, making them ideal for identifying overbought and oversold conditions:
* Upper Band: Indicates potential overbought levels.
* Lower Band: Indicates potential oversold levels.
2. Wick-to-Body Ratio Condition
This strategy places significant emphasis on candle wicks relative to the candle body. Here’s why:
* A large upper wick relative to the body signals potential selling pressure after testing the upper Bollinger Band.
* A large lower wick relative to the body indicates buying support after testing the lower Bollinger Band.
* Ratio Threshold: You can set a minimum wick-to-body ratio (default is 1.0), meaning that the wick must be at least equal in size to the body. This ensures only candles with significant reversals are considered for entry.
3. Flexible Entry Timing
To adapt to various trading styles, the indicator allows you to choose the entry fill timing:
* Daily Close: Enter at the close of the daily candle.
* Daily Open: Enter at the open of the following daily candle.
* HOD (High of Day): Set entry at the daily high, for those who want confirmation of upward momentum.
* LOD (Low of Day): Set entry at the daily low, ideal for confirming downward movement.
4. Position Sizing and Risk Management
The strategy calculates position size based on a fixed risk percentage of your account balance (default is 1%). This approach dynamically adjusts position sizes based on stop-loss distance:
* Stop Loss: Placed at the nearest swing high (for shorts) or swing low (for longs).
* Take Profit: Exits are triggered when the price reaches the opposite Bollinger Band.
5. Order Expiration
Each pending order (long or short) expires after two days if unfilled, allowing for new setups on subsequent candles if conditions are met again.
Using the Trade Entry Detector
Step-by-Step Guide
1. Set the Primary Time Frame
The core calculations run on the daily time frame, but the strategy can be applied to intraday charts (e.g., 65-minute or 15-minute) for deeper insights.
2. Adjust Bollinger Band Settings
* Length: Default is 20, which determines the period for calculating the moving average.
* Standard Deviation Multiplier: Default is 2.0, which sets the width of the bands. Adjusting this can help you capture broader or tighter volatility ranges.
3. Define the Wick-to-Body Ratio
Set the minimum ratio between wick and body (default 1.0). Higher values filter out candles with less wick-to-body contrast, focusing on stronger rejection moves.
4. Choose Entry Fill Timing
Select your preferred fill condition:
* Daily Close: Confirms the trade at the end of the daily session.
* Daily Open: Executes the entry at the open of the next day.
* HOD/LOD: Uses the daily high or low as an additional confirmation for upward or downward moves.
5. Position Sizing and Risk Management
* Set your account balance and risk percentage. The strategy automatically calculates position sizes based on the stop distance to manage risk efficiently.
* Stop Loss and Take Profit points are automatically set based on swing highs/lows and opposing Bollinger Bands, respectively.
Practical Example
Let’s say SPY (S&P 500 ETF) tests the lower Bollinger Band on the daily time frame, with a lower wick that is twice the size of the body (meeting the 1.0 ratio threshold). Here’s how the strategy might proceed:
1. Signal: The lower wick on SPY suggests buying interest at the lower Bollinger Band.
2. Entry Fill Timing: If you’ve selected "Daily Open," the entry order will be placed at the next day's open price.
3. Stop Loss: Positioned at the nearest daily swing low to minimize risk.
4. Take Profit: If SPY price moves up and reaches the upper Bollinger Band, the position is automatically closed.
Indicator Features and Benefits
* Multi-Time Frame Compatibility: Perform daily analysis while tracking signals on any intraday chart.
* Automatic Position Sizing: Tailor risk per trade based on account balance and desired risk percentage.
* Flexible Entry Options: Choose from close, open, HOD, or LOD for optimal timing.
* Effective Trend Reversal Identification: Uses wick-to-body ratio and Bollinger Band interaction to pinpoint potential reversals.
* Dynamic Visualization: Bollinger Bands are displayed on your chosen time frame, allowing seamless intraday tracking.
Summary
The Trade Entry Detector provides a unique, data-driven way to spot reversal points with customizable entry options. By combining Bollinger Bands with wick-to-body ratio conditions, it identifies potential trade setups where price has tested extremes and shown reversal signals. With its flexible entry timing, risk management features, and multi-time frame compatibility, this indicator is ideal for traders looking to blend daily market context with shorter-term execution.
Tips for Usage:
* For swing trading, consider the Daily Open or Close entry options.
* For momentum entries, HOD or LOD may offer better alignment with the direction of the wick.
* Backtest on different assets to find optimal Bollinger Band and wick-to-body settings for your market.
Use this indicator to enhance your understanding of price behavior at key levels and improve the precision of your entry points. Happy trading!
Simultaneous INSIDE Bar Break IndicatorSimultaneous Inside Bar Break Indicator (SIBBI) for The Strat Community
Overview:
The Simultaneous Inside Bar Break Indicator (SIBBI) is designed to help traders using The Strat methodology identify one of the most powerful breakout patterns: the Simultaneous Inside Bar Break across multiple symbols. This indicator detects when all four user-selected symbols form inside bars on the previous candle and then break those inside bars in the same direction (either bullish or bearish) on the current candle.
Inside bars represent consolidation periods where price action does not break the high or low of the previous candle. When a simultaneous break occurs across multiple symbols, this often signals a strong move in the market, making this a key actionable signal in The Strat trading strategy.
Key Features:
Multi-Symbol Analysis: You can track up to four different symbols simultaneously. By default, the indicator comes with SPY, QQQ, IWM, and DIA, but you can modify these to track any other assets or symbols.
Inside Bar Detection: The indicator checks whether all four symbols have inside bars on the previous candle. It only triggers when all symbols meet this condition, making it a highly specific and reliable signal.
Simultaneous Break Detection: Once all symbols have inside bars, the indicator waits for a breakout in the same direction across all four symbols. A simultaneous bullish break (prices breaking above the previous candle’s high) triggers a green label, while a simultaneous bearish break (prices breaking below the previous candle’s low) triggers a red label.
Dynamic Label Timeframe: The indicator dynamically adjusts the timeframe in the label based on the user’s selected timeframe. This allows traders to know precisely which timeframe the break is occurring on. If the user selects "Chart Timeframe," the indicator will evolve with the current chart's timeframe, making it more versatile.
Timeframe Flexibility: The indicator can be set to analyze any timeframe—15-minute, 30-minute, 60-minute, daily, weekly, and so on. It only works for the specific timeframe you set it to in the settings. If set to "Chart Timeframe," the label will adapt dynamically based on the timeframe you are currently viewing.
Customizable Labels: The user can choose the size of the labels (tiny, small, or normal), ensuring that the visual output is tailored to individual preferences and chart layouts.
Best Use Case:
The Simultaneous Inside Bar Break Indicator is particularly powerful when applied to multiple timeframes. Here’s how to use it for maximum impact:
Multi-Timeframe Setup: Set the indicator on various timeframes (e.g., 15-minute, 30-minute, 60-minute, and daily) across multiple charts. This allows you to monitor different timeframes and identify when lower timeframe breaks trigger potential moves on higher timeframes.
Anticipating Strong Moves: When a simultaneous inside bar break occurs on one timeframe (e.g., 30-minute), keep an eye on the higher timeframes (e.g., 60-minute or daily) to see if those timeframes also break. This stacking of inside bar breaks can signal powerful market moves.
Higher Conviction Signals: The indicator is designed to provide high-conviction signals. Since it requires all four symbols to break in the same direction simultaneously, it reduces false signals and focuses on higher probability setups, which is crucial for traders using The Strat to time their trades effectively.
How the Indicator Works:
Inside Bar Formation: The indicator first checks that all four selected symbols had inside bars in the previous bar (i.e., the current high and low are contained within the previous bar’s high and low).
Simultaneous Break Detection: After detecting inside bars, the indicator checks if all four symbols break out in the same direction—bullish (breaking above the previous bar’s high) or bearish (breaking below the previous bar’s low).
Label Display: When a simultaneous inside bar break occurs, a label is plotted on the chart—either green for a bullish break (below the candle) or red for a bearish break (above the candle). The label will display the timeframe you set in the settings (e.g., "IBSB 60" for a 60-minute break).
Chart Timeframe Option: If you prefer, you can set the indicator to evolve with the chart’s current timeframe. In this mode, the label will not show a specific timeframe but will still display the simultaneous inside bar break when it occurs.
Recommendations for Usage:
Focus on Multiple Timeframes: The Strat methodology is all about understanding the relationship between different timeframes. Use this indicator on multiple timeframes to get a better picture of potential moves.
Pair with Other Strat Techniques: This indicator is most powerful when combined with other Strat tools, such as broadening formations, timeframe continuity, and actionable signals (e.g., 2-2 reversals). The simultaneous inside bar break can help confirm or invalidate other signals.
Customize Symbols and Timeframes: Although the default symbols are SPY, QQQ, IWM, and DIA, feel free to replace them with symbols more relevant to your trading. This indicator works well across equities, indices, futures, and forex pairs.
How to Set It Up:
Select Symbols: Choose four symbols that you want to track. These can be index ETFs (like SPY and QQQ), individual stocks, or any other tradable instruments.
Set Timeframe: In the indicator’s settings, choose a specific timeframe (e.g., 15-minute, 30-minute, daily). The label will reflect the selected timeframe, making it clear which time-based break you are seeing.
Optional - Chart Timeframe Mode: If you want the indicator to adapt to the chart’s current timeframe, select the "Chart Timeframe" option in the settings. The indicator will plot the breaks without showing a specific timeframe in the label.
Customize Label Size: Depending on your chart layout and personal preference, you can adjust the size of the labels (tiny, small, or normal) in the settings.
Conclusion:
The Simultaneous Inside Bar Break Indicator is a powerful tool for traders using The Strat methodology, offering a highly specific and reliable signal that can indicate potential large market moves. By monitoring multiple symbols and timeframes, you can gain deeper insight into the market's behavior and act with greater confidence. This indicator is ideal for traders looking to catch high-conviction moves and align their trades with broader market continuity.
Note: The indicator works best when paired with multi-timeframe analysis, allowing you to see how breaks on lower timeframes might influence larger trends. For traders who prefer simplicity, setting it to the "Chart Timeframe" mode offers flexibility while maintaining the core benefits of this indicator.
TASC 2024.06 REIT ETF Trading System█ OVERVIEW
This strategy script demonstrates the application of the Real Estate Investment Trust (REIT) ETF trading system presented in the article by Markos Katsanos titled "Is The Price REIT?" from TASC's June 2024 edition of Traders' Tips .
█ CONCEPTS
REIT stocks and ETFs offer a simplified, diversified approach to real estate investment. They exhibit sensitivity to interest rates, often moving inversely to interest rate and treasury yield changes. Markos Katsanos explores this relationship and the correlation of prices with the broader market to develop a trading strategy for REIT ETFs.
The script employs Bollinger Bands and Donchian channel indicators to identify oversold conditions and trends in REIT ETFs. It incorporates the 10-year treasury yield index (TNX) as a proxy for interest rates and the S&P 500 ETF (SPY) as a benchmark for the overall market. The system filters trade entries based on their behavior and correlation with the REIT ETF price.
█ CALCULATIONS
The strategy initiates long entries (buy signals) under two conditions:
1. Oversold condition
The weekly ETF low price dips below the 15-week Bollinger Band bottom, the closing price is above the value by at least 0.2 * ATR ( Average True Range ), and the price exceeds the week's median.
Either of the following:
– The TNX index is down over 15% from its 25-week high, and its correlation with the ETF price is less than 0.3.
– The yield is below 2%.
2. Uptrend
The weekly ETF price crosses above the previous week's 30-week Donchian channel high.
The SPY ETF is above its 20-week moving average.
Either of the following:
– Over ten weeks have passed since the TNX index was at its 30-week high.
– The correlation between the TNX value and the ETF price exceeds 0.3.
– The yield is below 2%.
The strategy also includes three exit (sell) rules:
1. Trailing (Chandelier) stop
The weekly close drops below the highest close over the last five weeks by over 1.5 * ATR.
The TNX value rises over the latest 25 weeks, with a yield exceeding 4%, or its value surges over 15% above the 25-week low.
2. Stop-loss
The ETF's price declines by at least 8% of the previous week's close and falls below the 30-week moving average.
The SPY price is down by at least 8%, or its correlation with the ETF's price is negative.
3. Overbought condition
The ETF's value rises above the 100-week low by over 50%.
The ETF's price falls over 1.5 * ATR below the 3-week high.
The ETF's 10-week Stochastic indicator exceeds 90 within the last three weeks.
█ DISCLAIMER
This strategy script educates users on the system outlined by the TASC article. However, note that its default properties might not fully represent real-world trading conditions for an individual. By default, it uses 10% of equity as the order size and a slippage amount of 5 ticks. Traders should adjust these settings and the commission amount when using this script. Additionally, since this strategy utilizes compound conditions on weekly data to trigger orders, it will generate significantly fewer trades than other, higher-frequency strategies.
Leveraged Share Decay Tracker [SS]Releasing this utility tool for leveraged share traders and investors.
It is very difficult to track the amount of decay and efficiency that is associated with leveraged shares and since not all leveraged shares are created equally, I developed this tool to help investors/traders ascertain:
1. The general risk, in $$, per share associated with investing in a particular leveraged ETF
2. The ability of a leveraged share to match what it purports to do (i.e. if it is a 3X Bull share, is it actually returning consistently 3X the underlying or is there a large variance?)
3. The general decay at various timepoints expressed in $$$
How to use:
You need to be opened on the chart of the underlying. In the example above, the chart is on DIA, the leveraged share being tracked is UDOW (3X bull share of the DOW).
Once you are on the chart of the underlying, you then put in the leveraged share of interest. The indicator will perform two major assessments:
1. An analysis of the standard error between the underlying and the leveraged share. This is accomplished through linear regression, but instead of creating a linreg equation, it simply uses the results to ascertain the degree of error associated at various time points (the time points are 10, 20, 30, 40, 50, 100, 252).
2. An analysis of the variance of returns. The indicator requires you to put in the leverage amount. So if the leverage amount is 3% (i.e. SPXL or UPRO is 3 X SPY), be sure that you are putting that factor in the settings. It will then modify the underlying to match the leverage amount, and perform an assessment of variance over 10, 20, 30, 40, 50, 100, 252 days to ensure stability. This will verify whether the leveraged ETF is actually consistently performing how it purports to perform.
Here are some examples, and some tales of caution so you can see, for yourself, how not all leveraged shares are created equal.
SPY and SPXL:
SPY and UPRO:
XBI and LABU (3 x bull share):
XBI and LABD (3 x bear share):
SOX and SOXL:
AAPL and AAPU:
It is VERY pivotal you remember to check and adjust the Leveraged % factor.
For example, AAPU is leveraged 1.5%. You can see above it tracks this well. However, if you accidently leave it at 3%, you will get an erroneous result:
You can also see how some can fail to track the quoted leveraged amount, but still produce relatively lower risk decay.
And, as a final example, let's take a look at the worst leveraged share of life, BOIL:
Trainwreck that one. Stay far away from it!
The chart:
The chart will show you the drift (money value over time) and the variance (% variance between the expected and actual returns) over time. From here, you can ascertain the general length you feel comfortable holding a leveraged share. In general, for most stable shares, <= 50 trading days tends to be the sweet spot, but always check the chart.
There are also options to plot the variances and the drifts so you can see them visually.
And that is the indicator! Kind of boring, but there are absolutely 0 resources out there for doing this job, so hopefully you see the use for it!
Safe trades everyone!
SMA Cross with a Price FilterA moving average strategy generates an entry (buy) signal when the price goes above the moving average, and an exit (sell) signal when the price goes below the moving average. But it gives lots of whipsaws and noise depends on the moving average we use. A fast moving average gives more whipsaws and a slow moving average gives less whipsaws. To reduce the noise/whipsaws, we can add a filter on a fast/slow moving average. It will improve entry/exit performance significantly specially for those who don't want to watch the market actively.
I created this indicator with a price filter. This means the price of an underlying asset must be at least a specific percentage above its moving average to generate a buy signal and a specific percentage below its moving average to generate a sell signal. This price filter can also be a confirmation after the price crosses above/below its SMA. I couldn't find any indicator yet based on this idea. So I wrote this indicator and publishing it so it helps those who are interested.
I use 200 SMA and 3% price filter as default and using SPY as an example. So,
ENTRY signal when the closing price of SPY is 3% above its 200 SMA.
EXIT signal when the closing price of SPY is 3% below its 200 SMA.
Enjoy and let me know if it works.
** This chart only generates entry (buy) and exit (sell) signals. Please, do your own diligence to make any investment or trading decisions.
Spot-Vol CorrelationSpot-Vol Correlation Script Guide
Purpose:
This TradingView script measures the correlation between percentage changes in the spot price (e.g., for SPY, an ETF that tracks the S&P 500 index) and the changes in volatility (e.g., as indicated by the VIX, the Volatility Index). Its primary objective is to discern whether the relationship between spot price and volatility behaves as expected ("normal" condition) or diverges from the expected pattern ("abnormal" condition).
Normal vs. Abnormal Correlation:
Normal Correlation: Historically, the VIX (or volatility) and the spot price of major indices like the S&P 500 have an inverse relationship. When the spot price of the index goes up, the VIX tends to go down, indicating lower volatility. Conversely, when the index drops, the VIX generally rises, signaling increased volatility.
Abnormal Correlation: There are instances when this inverse relationship doesn't hold, and both the spot price and the VIX move in the same direction. This is considered an "abnormal" condition and might indicate unusual market dynamics, potential uncertainty, or impending shifts in market sentiment.
Using the Script:
Inputs:
First Symbol: This is set by default to VIX, representing volatility. However, users can input any other volatility metric they prefer.
Second Symbol: This is set to SPY by default, representing the spot price of the S&P 500 index. Like the first symbol, users can substitute SPY with any other asset or index of their choice.
Length of Calculation Period: Users can define the lookback period for the correlation calculation. By default, it's set to 10 periods (e.g., days for a daily chart).
Upper & Lower Bounds of Normal Zone: These parameters define the range of correlation values that are considered "normal" or expected. By default, this is set between -0.60 and -1.00.
Visuals:
Correlation Line: The main line plot shows the correlation coefficient between the two input symbols. When this line is within the "normal zone", it indicates that the spot price and volatility are inversely correlated. If it's outside this zone, the correlation is considered "abnormal".
Green Color: Indicates a period when the spot price and VIX are behaving as traditionally expected (i.e., one rises while the other falls).
Red Color: Denotes a period when the spot price and VIX are both moving in the same direction, which is an abnormal condition.
Shaded Area (Normal Zone): The area between the user-defined upper and lower bounds is shaded in green, highlighting the range of "normal" correlation values.
Interpretation:
Monitor the color and position of the correlation line relative to the shaded area:
If the line is green and within the shaded area, the market dynamics are as traditionally expected.
If the line is red or outside the shaded area, users should exercise caution as this indicates a divergence from typical behavior, which can precede significant market moves or heightened uncertainty.
Statistical Package for the Trading Sciences [SS]
This is SPTS.
It stands for Statistical Package for the Trading Sciences.
Its a play on SPSS (Statistical Package for the Social Sciences) by IBM (software that, prior to Pinescript, I would use on a daily basis for trading).
Let's preface this indicator first:
This isn't so much an indicator as it is a project. A passion project really.
This has been in the works for months and I still feel like its incomplete. But the plan here is to continue to add functionality to it and actually have the Pinecoding and Tradingview community contribute to it.
As a math based trader, I relied on Excel, SPSS and R constantly to plan my trades. Since learning a functional amount of Pinescript and coding a lot of what I do and what I relied on SPSS, Excel and R for, I use it perhaps maybe a few times a week.
This indicator, or package, has some of the key things I used Excel and SPSS for on a daily and weekly basis. This also adds a lot of, I would say, fairly complex math functionality to Pinescript. Because this is adding functionality not necessarily native to Pinescript, I have placed most, if not all, of the functionality into actual exportable functions. I have also set it up as a kind of library, with explanations and tips on how other coders can take these functions and implement them into other scripts.
The hope here is that other coders will take it, build upon it, improve it and hopefully share additional functionality that can be added into this package. Hence why I call it a project. Okay, let's get into an overview:
Current Functions of SPTS:
SPTS currently has the following functionality (further explanations will be offered below):
Ability to Perform a One-Tailed, Two-Tailed and Paired Sample T-Test, with corresponding P value.
Standard Pearson Correlation (with functionality to be able to calculate the Pearson Correlation between 2 arrays).
Quadratic (or Curvlinear) correlation assessments.
R squared Assessments.
Standard Linear Regression.
Multiple Regression of 2 independent variables.
Tests of Normality (with Kurtosis and Skewness) and recognition of up to 7 Different Distributions.
ARIMA Modeller (Sort of, more details below)
Okay, so let's go over each of them!
T-Tests
So traditionally, most correlation assessments on Pinescript are done with a generic Pearson Correlation using the "ta.correlation" argument. However, this is not always the best test to be used for correlations and determine effects. One approach to correlation assessments used frequently in economics is the T-Test assessment.
The t-test is a statistical hypothesis test used to determine if there is a significant difference between the means of two groups. It assesses whether the sample means are likely to have come from populations with the same mean. The test produces a t-statistic, which is then compared to a critical value from the t-distribution to determine statistical significance. Lower p-values indicate stronger evidence against the null hypothesis of equal means.
A significant t-test result, indicating the rejection of the null hypothesis, suggests that there is statistical evidence to support that there is a significant difference between the means of the two groups being compared. In practical terms, it means that the observed difference in sample means is unlikely to have occurred by random chance alone. Researchers typically interpret this as evidence that there is a real, meaningful difference between the groups being studied.
Some uses of the T-Test in finance include:
Risk Assessment: The t-test can be used to compare the risk profiles of different financial assets or portfolios. It helps investors assess whether the differences in returns or volatility are statistically significant.
Pairs Trading: Traders often apply the t-test when engaging in pairs trading, a strategy that involves trading two correlated securities. It helps determine when the price spread between the two assets is statistically significant and may revert to the mean.
Volatility Analysis: Traders and risk managers use t-tests to compare the volatility of different assets or portfolios, assessing whether one is significantly more or less volatile than another.
Market Efficiency Tests: Financial researchers use t-tests to test the Efficient Market Hypothesis by assessing whether stock price movements follow a random walk or if there are statistically significant deviations from it.
Value at Risk (VaR) Calculation: Risk managers use t-tests to calculate VaR, a measure of potential losses in a portfolio. It helps assess whether a portfolio's value is likely to fall below a certain threshold.
There are many other applications, but these are a few of the highlights. SPTS permits 3 different types of T-Test analyses, these being the One Tailed T-Test (if you want to test a single direction), two tailed T-Test (if you are unsure of which direction is significant) and a paired sample t-test.
Which T is the Right T?
Generally, a one-tailed t-test is used to determine if a sample mean is significantly greater than or less than a specified population mean, whereas a two-tailed t-test assesses if the sample mean is significantly different (either greater or less) from the population mean. In contrast, a paired sample t-test compares two sets of paired observations (e.g., before and after treatment) to assess if there's a significant difference in their means, typically used when the data points in each pair are related or dependent.
So which do you use? Well, it depends on what you want to know. As a general rule a one tailed t-test is sufficient and will help you pinpoint directionality of the relationship (that one ticker or economic indicator has a significant affect on another in a linear way).
A two tailed is more broad and looks for significance in either direction.
A paired sample t-test usually looks at identical groups to see if one group has a statistically different outcome. This is usually used in clinical trials to compare treatment interventions in identical groups. It's use in finance is somewhat limited, but it is invaluable when you want to compare equities that track the same thing (for example SPX vs SPY vs ES1!) or you want to test a hypothesis about an index and a leveraged share (for example, the relationship between FNGU and, say, MSFT or NVDA).
Statistical Significance
In general, with a t-test you would need to reference a T-Table to determine the statistical significance of the degree of Freedom and the T-Statistic.
However, because I wanted Pinescript to full fledge replace SPSS and Excel, I went ahead and threw the T-Table into an array, so that Pinescript can make the determination itself of the actual P value for a t-test, no cross referencing required :-).
Left tail (Significant):
Both tails (Significant):
Distributed throughout (insignificant):
As you can see in the images above, the t-test will also display a bell-curve analysis of where the significance falls (left tail, both tails or insignificant, distributed throughout).
That said, I have not included this function for the paired sample t-test because that is a bit more nuanced. But for the one and two tailed assessments, the indicator will provide you the P value.
Pearson Correlation Assessment
I don't think I need to go into too much detail on this one.
I have put in functionality to quickly calculate the Pearson Correlation of two array's, which is not currently possible with the "ta.correlation" function.
Quadratic (Curvlinear) Correlation
Not everything in life is linear, sometimes things are curved!
The Pearson Correlation is great for linear assessments, but tends to under-estimate the degree of the relationship in curved relationships. There currently is no native function to t-test for quadratic/curvlinear relationships, so I went ahead and created one.
You can see an example of how Quadratic and Pearson Correlations vary when you look at CME_MINI:ES1! against AMEX:DIA for the past 10 ish months:
Pearson Correlation:
Quadratic Correlation:
One or the other is not always the best, so it is important to check both!
R-Squared Assessments:
The R-squared value, or the square of the Pearson correlation coefficient (r), is used to measure the proportion of variance in one variable that can be explained by the linear relationship with another variable. It represents the goodness-of-fit of a linear regression model with a single predictor variable.
R-Squared is offered in 3 separate forms within this indicator. First, there is the generic R squared which is taking the square root of a Pearson Correlation assessment to assess the variance.
The next is the R-Squared which is calculated from an actual linear regression model done within the indicator.
The first is the R-Squared which is calculated from a multiple regression model done within the indicator.
Regardless of which R-Squared value you are using, the meaning is the same. R-Square assesses the variance between the variables under assessment and can offer an insight into the goodness of fit and the ability of the model to account for the degree of variance.
Here is the R Squared assessment of the SPX against the US Money Supply:
Standard Linear Regression
The indicator contains the ability to do a standard linear regression model. You can convert one ticker or economic indicator into a stock, ticker or other economic indicator. The indicator will provide you with all of the expected information from a linear regression model, including the coefficients, intercept, error assessments, correlation and R2 value.
Here is AAPL and MSFT as an example:
Multiple Regression
Oh man, this was something I really wanted in Pinescript, and now we have it!
I have created a function for multiple regression, which, if you export the function, will permit you to perform multiple regression on any variables available in Pinescript!
Using this functionality in the indicator, you will need to select 2, dependent variables and a single independent variable.
Here is an example of multiple regression for NASDAQ:AAPL using NASDAQ:MSFT and NASDAQ:NVDA :
And an example of SPX using the US Money Supply (M2) and AMEX:GLD :
Tests of Normality:
Many indicators perform a lot of functions on the assumption of normality, yet there are no indicators that actually test that assumption!
So, I have inputted a function to assess for normality. It uses the Kurtosis and Skewness to determine up to 7 different distribution types and it will explain the implication of the distribution. Here is an example of SP:SPX on the Monthly Perspective since 2010:
And NYSE:BA since the 60s:
And NVDA since 2015:
ARIMA Modeller
Okay, so let me disclose, this isn't a full fledge ARIMA modeller. I took some shortcuts.
True ARIMA modelling would involve decomposing the seasonality from the trend. I omitted this step for simplicity sake. Instead, you can select between using an EMA or SMA based approach, and it will perform an autogressive type analysis on the EMA or SMA.
I have tested it on lookback with results provided by SPSS and this actually works better than SPSS' ARIMA function. So I am actually kind of impressed.
You will need to input your parameters for the ARIMA model, I usually would do a 14, 21 and 50 day EMA of the close price, and it will forecast out that range over the length of the EMA.
So for example, if you select the EMA 50 on the daily, it will plot out the forecast for the next 50 days based on an autoregressive model created on the EMA 50. Here is how it looks on AMEX:SPY :
You can also elect to plot the upper and lower confidence bands:
Closing Remarks
So that is the indicator/package.
I do hope to continue expanding its functionality, but as of now, it does already have quite a lot of functionality.
I really hope you enjoy it and find it helpful. This. Has. Taken. AGES! No joke. Between referencing my old statistics textbooks, trying to remember how to calculate some of these things, and wanting to throw my computer against the wall because of errors in the code, this was a task, that's for sure. So I really hope you find some usefulness in it all and enjoy the ability to be able to do functions that previously could really only be done in external software.
As always, leave your comments, suggestions and feedback below!
Take care!
EMA 9/21 with Target Price [SS]Hey everyone,
Coming back with my EMA 9/21 indicator.
My original one was removed a long time ago because I didn't really realize that there were already plenty of similar indicators (my bad!) but this one is my unique, Steversteves edition haha.
About the Indicator:
Essentially, it just combines the 2 only EMA's I ever really use (the 9 and 21) with an ATR based analysis to calculate the average range a ticker undergoes after an EMA 9 / 21 Cross-over and Cross-under.
You can see the major example being in the chart above. I use this for dramatic effect as SPY just happened to have topped at the second expected bull target on the daily. But obviously the intention for this indicator is to be used on the smaller timeframes. Let's take a look at some examples with various tickers.
TSLA:
So let's just use the previous day as example (which was Friday). If we look to the chart below:
TSLA did an EMA 9/21 crossover (bullish) in premarket. This put the immediate TP at 234.59. If we play out the chart:
We shot right to it at open.
We then did a cross under with a TP of 225.93, but that was not realized as the sentiment was too bullish. We then cross back over to the upside, putthing next TP at 238.88 which was realized:
NVDA:
On Friday, NVDA was a bit of a mess, lots of whipsaw off open. But once we finally had a cross under with 3 consecutive closes below the EMA9/21 on the 5 minute chart, it solidified the likelihood of a short:
And this was the result:
We came down to the first target, held it actually as support before finally crossing back over, setting the next TP at 475.05. We got 3 consecutive closes above the EMA 9/21, so let's see what happened:
Nothing really, we closed before we got there, but we did make progress towards it.
And last but not least SPY:
We opened the day with a bullish crossover and 3 consecutive closes above the EMA9/21, making our TP 441.38 (chart above). Let's see what happened:
We came just shy of it after the fed release volatility slammed it down, where we got a crossunder (bearish) to a TP of 436.21:
This ended up playing out, we did get a bullish crossover later in the day and so let's see what happened then:
So those are the real examples, most recent examples of trading using this. They are not all perfect, which is intentional because you need to use a bit of your own analysis, of course, when you are using this type of strategy or indicator. The EMA 9/21 is not sufficient generally on its own, but it is very helpful to gauge the immediate PA and whether the expected move aligns with your overall thesis on the day in terms of realistic target prices.
Customizability:
In terms of the customizability, this is a very basic indicator aside from the assessment of ranges. So there really is not a lot to customize.
You can toggle off and on the labels if you do not want them, you can also adjust the lookback length for the ATR assessment. The lookback length is defaulted to 500, I do really highly suggest you leave it at 500 because this has worked well for me and in back-testing, it has performed above my own expectations.
But, that said, you can take this and back-test as you wish with whatever parameters you feel are most appropriate. I haven't back-tested this on every stock known to man, my go to's are SPY, QQQ, sometimes MSFT and so it works well on those. But perhaps some others will have differing results.
Final Thoughts:
That is the indicator in a nutshell! It is really self explanatory and its likely a strategy most of you already know. This just helps to add realistic price targets and context to those cross-overs and cross-unders.
It also works fine on larger timeframes. We can see it on the 1 hour with MSFT:
On the 2 hour hour with QQQ:
And I am sure you can find other examples!
That's it everyone, safe trades!
Baseline Indicator [SS]Hello,
This is the Baseline Indicator. I modelled it after one of my favourite Tradingview chart types, the baseline type (shown in image below):
I really love this chart, but I wanted a way for it to:
a) Be static and not move with the chart; and
b) Auto calculate the baseline average for a specified period of time.
So I created this indicator which does essentially that.
What it does:
The indicator will calculate the average between the high and low of a user defined timeframe. The timeframe is customizable, but it defaults to daily. It will then plot the average (or baseline) of the high and low over that specified timeframe. The default plot is a candle plot. It will change the colours of the candles to green (for above the baseline) and red (for below the baseline). The chart below shows an example of the indicator with candles on SPY. The Baseline timeframe is set to 1 hour:
You can choose whether you want to plot the current baseline average or the previous.
The advantage to plotting the previous is that this provide a static reference point and can be helpful on the 30 and 60 minute timeframe. Here is an example:
In this example on SPY, the indicator is plotting the previous average. You can see SPY is using this as support and creating a "staircase" pattern. This is indicative of a trend.
The example above is using the previous day average on the daily timeframe during a sideways day. You can see that the price action accumulates and is consistently drawn to this point.
Inversely, you can manually select your own baseline price if you want a static, self-calculated baseline reference point.
Options and Settings:
Below is an outline of the menu as well as a brief explanation of the options and settings:
To view your chart as a baseline chart, make sure you select the "Line" input and then hide the candles on your chart using your chart settings (see image below):
The purple arrow shows how to hide the candles. You select the "Eye" Icon which should then become greyed out and you will be left with the baseline chart from the indicator.
Why use baseline average?
The average between the high and low of a designated timeframe is a very helpful value. In choppy markets, this acts as a key point of frequent return. In trendy markets, this acts as a reference point of trend direction and strength. I encourage you to play around with the indicator and review some historical charts using it, and you will see some patterns emerge!
Final thoughts:
I have also done a quick tutorial video on the indicator for your reference, you can check that out below:
Thanks for checking out the indicator and I hope you like it!
