Elder's Market Thermometer [LazyBear]Market temperature, introduced by Dr.Alexander Elder, helps differentiate between sleepy, quiet and hot market periods.
Following is Mr.Elder's explanation on how to use this indicator (from his book "Come in to my Trading Room"):
"When markets are quiet, the adjacent bars tend to overlap. The consensus of value is well established, and the crowd does little buying or selling outside of yesterday’s range. When highs and lows exceed their previous day’s values, they do so only by small margins. Market Thermometer falls and its EMA slants down, indicating a sleepy market. When a market begins to run, either up or down, its daily bars start pushing outside of the previous ranges. The histogram of Market Thermometer grows taller and crosses above its EMA, which soon turns up, confirming the new trend."
"Market Thermometer gives four trading signals, based on the relationship between its histogram and its moving average:
1) The best time to enter new positions is when Market Thermometer falls below its moving average. When Market Thermometer falls below its EMA, it indicates that the market is quiet. If your system flashes an entry signal, try to enter when the market is cooler than usual. When Market Thermometer rises above its moving average, it warns that the market is hot and slippage more likely.
2) Exit positions when Market Thermometer rises to triple the height of its moving average. A spike of Market Thermometer indicates a runaway move. When the crowd feels jarred by a sudden piece of news and surges, it is a good time to take profits. Panics tend to be short-lived, offering a brief opportunity to cash in. If the EMA of Market Thermometer stands at 5 cents, but the Thermometer itself shoots up to 15 cents, take profits. Test these values for the market you are trading.
3) Get ready for an explosive move if the Thermometer stays below its moving average for five to seven trading days. Quiet markets put amateurs to sleep. They become careless and stop watching prices. Volatility and volume fall, and professionals get a chance to run away with the market. Explosive moves often erupt from periods of inactivity.
4) Market Thermometer can help you set a profit target for the next trading day. If you are a short-term trader and are long, add the value of today’s Thermometer EMA to yesterday’s high and place a sell order there. If you are short, subtract the value of the Thermometer’s EMA from yesterday’s low and place an order to cover at that level."
You can configure the "Explosive Move threshold" (default: 3), "Idle Market Threshold" (default: 7) and "Thermometer EMA length" (default: 22) via Options page.
More info:
"Come in to my Trading Room - A complete Guide to Trading" by Dr.Alexander Elder. (Page 162)
List of my other indicators:
- Chart:
- GDoc: docs.google.com
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Custom Indicator - No Trade Zone Warning Back Ground Highlights!Years ago I did an analysis of my trades. Every period of the day was profitable except for two. From 10:00-1030, and 1:00 to 1:30. (I was actively Day Trading Futures) Imagine a vertical graph broken down in to 30 minute time segments. I had nice Green bars in every time slot (Showing Net Profits), and HUGE Red Bars from 10 to 10:30 and 1 to 1:30. After analysis I found I made consistent profits at session open, but then I would enter in to bad setups around 10 to make more money. I also found after I took lunch when I came back at 1:00 I would force trades instead of patiently waiting for a great trade setup. I created an indicator that plotted a red background around those times telling me I was not allowed to enter a trade. Profits went up!!! Details on How to adjust times are in 1st Post. You can adjust times and colors to meet your own trading needs.
Liquidity Sweep DetectorThe Liquidity Sweep Detector represents a technical analysis tool specifically designed to identify market microstructure patterns typically associated with institutional trading activity. According to Harris (2003), institutional traders frequently employ tactics where they momentarily break through price levels to trigger stop orders before redirecting the market in the opposite direction. This phenomenon, commonly referred to as "stop hunting" or "liquidity sweeping," constitutes a significant aspect of institutional order flow analysis (Osler, 2003). The current implementation provides retail traders with a means to identify these patterns, potentially aligning their trading decisions with institutional movements rather than becoming victims of such strategies.
Osler's (2003) research documents how stop-loss orders tend to cluster around significant price levels, creating concentrations of liquidity. Taylor (2005) argues that sophisticated institutional participants systematically exploit these liquidity clusters by inducing price movements that trigger these orders, subsequently profiting from the ensuing price reaction. The algorithmic detection of such patterns involves several key processes. First, the indicator identifies swing points—local maxima and minima—through comparison with historical price data within a definable lookback period. These swing points correspond to what Bulkowski (2011) describes as "significant pivot points" that frequently serve as liquidity zones where stop orders accumulate.
The core detection algorithm utilizes a multi-stage process to identify potential sweeps. For high sweeps, it monitors when price exceeds a previous swing high by a specified threshold percentage, followed by a bearish candle that closes below the original swing high level. Conversely, for low sweeps, it detects when price drops below a previous swing low by the threshold percentage, followed by a bullish candle closing above the original swing low. As noted by Lo and MacKinlay (2011), these price patterns often emerge when large institutional players attempt to capture liquidity before initiating significant directional moves.
The indicator maintains historical arrays of detected sweep events with their corresponding timestamps, enabling temporal analysis of market behavior following such events. Visual elements include horizontal lines marking sweep levels, background color highlighting for sweep events, and an information table displaying active sweeps with their corresponding price levels and elapsed time since detection. This visualization approach allows traders to quickly identify potential institutional activity without requiring complex interpretation of raw price data.
Parameter customization includes adjustable lookback periods for swing point identification, sweep threshold percentages for signal sensitivity, and display duration settings. These parameters allow traders to adapt the indicator to various market conditions and timeframes, as markets demonstrate different liquidity characteristics across instruments and periods (Madhavan, 2000).
Empirical studies by Easley et al. (2012) suggest that retail traders who successfully identify and act upon institutional liquidity sweeps may achieve superior risk-adjusted returns compared to conventional technical analysis approaches. However, as cautioned by Chordia et al. (2008), such patterns should be considered within broader market context rather than in isolation, as their predictive value varies significantly with overall market volatility and liquidity conditions.
References:
Bulkowski, T. (2011). Encyclopedia of Chart Patterns (2nd ed.). John Wiley & Sons.
Chordia, T., Roll, R., & Subrahmanyam, A. (2008). Liquidity and market efficiency. Journal of Financial Economics, 87(2), 249-268.
Easley, D., López de Prado, M., & O'Hara, M. (2012). Flow Toxicity and Liquidity in a High-frequency World. The Review of Financial Studies, 25(5), 1457-1493.
Harris, L. (2003). Trading and Exchanges: Market Microstructure for Practitioners. Oxford University Press.
Lo, A. W., & MacKinlay, A. C. (2011). A Non-Random Walk Down Wall Street. Princeton University Press.
Madhavan, A. (2000). Market microstructure: A survey. Journal of Financial Markets, 3(3), 205-258.
Osler, C. L. (2003). Currency Orders and Exchange Rate Dynamics: An Explanation for the Predictive Success of Technical Analysis. Journal of Finance, 58(5), 1791-1820.
Taylor, M. P. (2005). Official Foreign Exchange Intervention as a Coordinating Signal in the Dollar-Yen Market. Pacific Economic Review, 10(1), 73-82.
[blackcat] L2 Market Risk MeterOVERVIEW
The L2 Market Risk Meter is designed to evaluate market conditions using various technical indicators including Moving Averages (MA), Moving Average Convergence Divergence (MACD), and Bollinger Bands 📈🔍. By analyzing these elements, the script helps traders identify potential buying opportunities and assess the overall market sentiment more effectively. This comprehensive approach aids in making informed trading decisions by providing clear visual representations of critical market factors 🚀💸.
Key components include the calculation of short-term and long-term moving averages, MACD lines, and Bollinger Bands, which are then used to plot histograms and labels directly on the chart. These visual cues assist traders in quickly interpreting complex market data, thereby enhancing their ability to navigate volatile markets and capitalize on emerging trends ✅✨.
FEATURES
Advanced Technical Analysis:
Utilizes Short and Long Moving Averages (MAs) to capture different trend durations.
Implements MACD for detecting changes in the strength, direction, momentum, and duration of a trend.
Incorporates Bollinger Bands to measure volatility and provide dynamic support/resistance levels.
Comprehensive Visualization:
Generates colored histograms representing positive and negative MACD values.
Displays labels indicating "Safe," "Risk," and "Buy" signals at crucial points on the chart.
Flexible Settings:
Allows customization of the short_ma_period and long_ma_period to tailor the analysis to individual trading styles or asset types.
Provides configurable colors and styles for histograms and labels to suit personal preferences.
Real-Time Feedback:
Updates dynamically as new price data becomes available, ensuring timely insights.
Facilitates rapid identification of shifts in market conditions through clear graphical outputs.
HOW TO USE
Adding the Indicator:
Begin by adding the L2 Market Risk Meter to your chart on TradingView. You can do this via the "Pine Editor" located at the bottom of the screen. Simply copy-paste the script into the editor and click "Add to Chart."
Configuring Parameters:
Adjust the short_ma_period and long_ma_period inputs based on your preferred timeframes and strategies. For example, shorter periods will react faster but may be noisier, while longer periods offer smoother trends but slower reactions.
Interpreting Histograms:
Monitor the plotted histograms closely:
Positive Values: Represent bullish momentum where the closing prices are higher than the moving average.
Negative Values: Suggest bearish pressure when the closing prices fall below the moving average.
Understanding Labels:
Pay attention to generated labels for actionable insights:
"Safe" Zone: Appears when the price crosses from below to above the lower Bollinger Band, suggesting reduced risk.
"Risk" Zone: Indicates heightened caution if the price breaches upward from below the upper Bollinger Band.
"Buy" Signal: Triggered under stringent bullish conditions combining all predefined criteria, signaling an opportune moment to enter long positions.
Integrating with Other Tools:
Use the L2 Market Risk Meter alongside other technical studies and fundamental analyses to corroborate findings and strengthen your trading strategy.
Regular Review:
Periodically revisit and tweak your parameters and interpretations in light of changing market environments and performance evaluations.
LIMITATIONS
Dependency on Historical Data: Since the indicator relies extensively on historical price movements, its predictions about future trends should be viewed cautiously.
Not Standalone Solution: Like any other tool, it does not guarantee profitability and must be part of a holistic trading plan that includes multiple confirmation methods.
Parameter Sensitivity: Optimal performance depends greatly on selecting appropriate MA period lengths; improper choices could lead to misleading signals.
Volatility Assumptions: The effectiveness of Bollinger Bands varies across different market conditions, especially during low volatility phases where bands might fail to expand significantly.
NOTES
Understanding individual components such as MAs, MACDs, and Bollinger Bands is essential before fully depending on this script's output.
Always backtest any new strategy incorporating this meter thoroughly against diverse market scenarios to gauge reliability.
Consider employing supplementary filters like volume spikes or candlestick patterns to validate signals further.
Be mindful of sudden news events or economic releases impacting asset prices independently of underlying trends highlighted here.
THANKS
A big thank you goes out to fellow members of the TradingView community who have contributed invaluable feedback and suggestions throughout the development process of this indicator 🙏. Your input has been instrumental in refining and improving the functionality and usability of the L2 Market Risk Meter. Continue sharing your experiences so we can collectively enhance our trading capabilities!
Colored SMA by Time & TrendScalping script for XAUUSD this indicator checks times in which there is a usual uptrend or downtrend for this instrument. When green, a buy is likely to be profitable (at least for a few bars) and when red, a sell is likely to be profitable (for the next few bars).
高點突破策略進場條件：突破前20根K棒的高點自動進場
出場條件：
停利：+3%
停損：-1.5%
適合時間週期： 可用於1小時或日線圖
適合標的:股票 期貨 加密貨幣 個股
如果要使用請自行回測找到最符合的標的
一律建議用模擬帳戶嘗試,沒問題過後再用真金白銀
Entry Condition:
Automatically enter a long position when the price breaks above the highest high of the past 20 candles.
Exit Conditions:
Take Profit: +3%
Stop Loss: -1.5%
Recommended Timeframes:
Suitable for 1-hour or daily charts.
Applicable Instruments:
Stocks, futures, cryptocurrencies, and individual equities.
Important:
Please perform your own backtesting to identify the most suitable assets.
We strongly recommend using a demo account first. Only trade with real money after confirming the strategy works well.
seekho roj kamao 3 **Seekho Roj Kamao** is a powerful trend continuation indicator designed to enhance your trading strategy with precise entry and exit signals. It combines the strength of RSI, CMO, and MACD to identify momentum shifts, while ATR-based trailing stops help manage risk effectively. The indicator dynamically plots buy/sell signals on the chart, along with clearly labeled take profit and stop loss levels. Whether you're a beginner or an experienced trader, this tool offers a structured and disciplined approach to trading trends. Seekho Roj Kamao empowers you to make informed decisions and aim for consistent profits in volatile market conditions.
External Signals Strategy Tester v5External Signals Strategy Tester v5 – User Guide (English)
1. Purpose
This Pine Script strategy is a universal back‑tester that lets you plug in any external buy/sell series (for example, another indicator, webhook feed, or higher‑time‑frame condition) and evaluate a rich set of money‑management rules around it – with a single click on/off workflow for every module.
2. Core Workflow
Feed signals
Buy Signal / Sell Signal inputs accept any series (price, boolean, output of request.security(), etc.).
A crossover above 0 is treated as “signal fired”.
Date filter
Start Date / End Date restricts the test window so you can exclude unwanted history.
Trade engine
Optional Long / Short enable toggles.
Choose whether opposite signals simply close the trade or reverse it (flip direction in one transaction).
Risk modules – all opt‑in via check‑boxes
Classic % block – fixed % Take‑Profit / Stop‑Loss / Break‑Even.
Fibonacci Bollinger Bands (FBB) module
Draws dynamic VWMA/HMA/SMA/EMA/DEMA/TEMA mid‑line with ATR‑scaled Fibonacci envelopes.
Every line can be used for stops, trailing, or multi‑target exits.
Separate LONG and SHORT sub‑modules
Each has its own SL plus three Take‑Profits (TP1‑TP3).
Per TP you set line, position‑percentage to close, and an optional trailing flag.
Executed TP/SLs deactivate themselves so they cannot refire.
Trailing behaviour
If Trail is checked, the selected line is re‑evaluated once per bar; the order is amended via strategy.exit().
3. Inputs Overview
Group Parameter Notes
Trade Settings Enable Long / Enable Short Master switches
Close on Opposite / Reverse Position How to react to a counter‑signal
Risk % Use TP / SL / BE + their % Traditional fixed‑distance management
Fibo Bands FIBO LEVELS ENABLE + visual style/length Turn indicator overlay on/off
FBB LONG SL / TP1‑TP3 Enable, Line, %, Trail Rules applied only while a long is open
FBB SHORT SL / TP1‑TP3 Enable, Line, %, Trail Rules applied only while a short is open
Line choices: Basis, 0.236, 0.382, 0.5, 0.618, 0.764, 1.0 – long rules use lower bands, short rules use upper bands automatically.
4. Algorithm Details
Position open
On the very first bar after entry, the script checks the direction and activates the corresponding LONG or SHORT module, deactivating the other.
Order management loop (every bar)
FBB Stop‑Loss: placed/updated at chosen band; if trailing, follows the new value.
TP1‑TP3: each active target updates its limit price to the selected band (or holds static if trailing is off).
The classic % block runs in parallel; its exits have priority because they call strategy.close_all().
Exit handling
When any strategy.exit() fires, the script reads exit_id and flips the *_Active flag so that order will not be recreated.
A Stop‑Loss (SL) also disables all remaining TPs for that leg.
5. Typical Use Cases
Scenario Suggested Setup
Scalping longs into VWAP‐reversion Enable LONG TP1 @ 0.382 (30 %), TP2 @ 0.618 (40 %), SL @ 0.236 + trailing
Fade shorts during news spikes Enable SHORT SL @ 1.0 (no trail) and SHORT TP1,2,3 on consecutive lowers with small size‑outs
Classic trend‑follow Use only classic % TP/SL block and disable FBB modules
6. Hints & Tips
Signal quality matters – this script manages exits, it does not generate entries.
Keep TV time zone in mind when picking start/end dates.
For portfolio‑style testing allocate smaller default_qty_value than 100 % or use strategy.percent_of_equity sizing.
You can combine FBB exits with fixed‑% ones for layered management.
7. Limitations / Safety
No pyramiding; the script holds max one position at a time.
All calculations are bar‑close; intra‑bar touches may differ from real‑time execution.
The indicator overlay is optional, so you can run visual‑clean tests by unchecking FIBO LEVELS ENABLE.
Multi RSI IndicatorRSI is one of the best indicator for measuring the momentum and trend of any tradable asset, be it Stocks, crypto currencies, commodities, forex or their derivatives.
Higher period RSIs tells the trend and have lower sensitivity towards momentum while lower period RSIs are more sensitive towards momentum.
So a combination of different periods and different time frame RSIs will measure trend and momentum both.
For example if in 15 minute time frame, 35 period RSI is above 50, the trend is bullish and vice versa. But if 7 period RSI is above 70 means momentum is high. Along with that if 14 period RSI in 30 minute time frame is above 60 that means in higher time frame also momentum is high. So chances of success in bullish trade becomes high.
So this Multiple RSI indicator is a combination of 8 RSIs. 4 RSIs are of different periods such as 7,14, 21 and 28 (periods can be selected as per choice). Another 4 RSIs are of different time frames to measure the major trend and momentum. Such as on 5 minute chart, apart from different period RSIs of 5 minutes, you can also place 14 period RSIs of 15 minutes, 30 minutes, hourly and day time frames to give broader spectrum of trend and momentum. In this way you can get a clear picture of trend and momentum both and can trade in trend direction more accurately, thus enhancing you trade accuracy and profitability.
EXODUS EXODUS by (DAFE) Trading Systems
EXODUS is a sophisticated trading algorithm built by Dskyz (DAFE) Trading Systems for competitive and competition purposes, designed to identify high-probability trades with robust risk management. this strategy leverages a multi-signal voting system, combining three core components—SPR, VWMO, and VEI—alongside ADX, choppiness filters, and ATR-based volatility gates to ensure trades are taken only in favorable market conditions. the algo uses a take-profit to stop-loss ratio, dynamic position sizing, and a strict voting mechanism requiring all signals to align before entering a trade.
EXODUS was not overfitted for any specific symbol. instead, it uses a generic tuned setting, making it versatile across various markets. while it can trade futures, it’s not currently set up for it but has the potential to do more with further development. visuals are intentionally minimal due to its competition focus, prioritizing performance over aesthetics. a more visually stunning version may be released in the future with enhanced graphics.
The Unique Core Components Developed for EXODUS
SPR (Session Price Recalibration)
SPR measures momentum during regular trading hours (RTH, 0930-1600, America/New_York) to catch session-specific trends.
spr_lookback = input.int(15, "SPR Lookback") this sets how many bars back SPR looks to calculate momentum (default 15 bars). it compares the current session’s price-volume score to the score 15 bars ago to gauge momentum strength.
how it works: a longer lookback smooths out the signal, focusing on bigger trends. a shorter one makes SPR more sensitive to recent moves.
how to adjust: on a 1-hour chart, 15 bars is 15 hours (about 2 trading days). if you’re on a shorter timeframe like 5 minutes, 15 bars is just 75 minutes, so you might want to increase it to 50 or 100 to capture more meaningful trends. if you’re trading a choppy stock, a shorter lookback (like 5) can help catch quick moves, but it might give more false signals.
spr_threshold = input.float (0.7, "SPR Threshold")
this is the cutoff for SPR to vote for a trade (default 0.7). if SPR’s normalized value is above 0.7, it votes for a long; below -0.7, it votes for a short.
how it works: SPR normalizes its momentum score by ATR, so this threshold ensures only strong moves count. a higher threshold means fewer trades but higher conviction.
how to adjust: if you’re getting too few trades, lower it to 0.5 to let more signals through. if you’re seeing too many false entries, raise it to 1.0 for stricter filtering. test on your chart to find a balance.
spr_atr_length = input.int(21, "SPR ATR Length") this sets the ATR period (default 21 bars) used to normalize SPR’s momentum score. ATR measures volatility, so this makes SPR’s signal relative to market conditions.
how it works: a longer ATR period (like 21) smooths out volatility, making SPR less jumpy. a shorter one makes it more reactive.
how to adjust: if you’re trading a volatile stock like TSLA, a longer period (30 or 50) can help avoid noise. for a calmer stock, try 10 to make SPR more responsive. match this to your timeframe—shorter timeframes might need a shorter ATR.
rth_session = input.session("0930-1600","SPR: RTH Sess.") rth_timezone = "America/New_York" this defines the session SPR uses (0930-1600, New York time). SPR only calculates momentum during these hours to focus on RTH activity.
how it works: it ignores pre-market or after-hours noise, ensuring SPR captures the main market action.
how to adjust: if you trade a different session (like London hours, 0300-1200 EST), change the session to match. you can also adjust the timezone if you’re in a different region, like "Europe/London". just make sure your chart’s timezone aligns with this setting.
VWMO (Volume-Weighted Momentum Oscillator)
VWMO measures momentum weighted by volume to spot sustained, high-conviction moves.
vwmo_momlen = input.int(21, "VWMO Momentum Length") this sets how many bars back VWMO looks to calculate price momentum (default 21 bars). it takes the price change (close minus close 21 bars ago).
how it works: a longer period captures bigger trends, while a shorter one reacts to recent swings.
how to adjust: on a daily chart, 21 bars is about a month—good for trend trading. on a 5-minute chart, it’s just 105 minutes, so you might bump it to 50 or 100 for more meaningful moves. if you want faster signals, drop it to 10, but expect more noise.
vwmo_volback = input.int(30, "VWMO Volume Lookback") this sets the period for calculating average volume (default 30 bars). VWMO weights momentum by volume divided by this average.
how it works: it compares current volume to the average to see if a move has strong participation. a longer lookback smooths the average, while a shorter one makes it more sensitive.
how to adjust: for stocks with spiky volume (like NVDA on earnings), a longer lookback (50 or 100) avoids overreacting to one-off spikes. for steady volume stocks, try 20. match this to your timeframe—shorter timeframes might need a shorter lookback.
vwmo_smooth = input.int(9, "VWMO Smoothing")
this sets the SMA period to smooth VWMO’s raw momentum (default 9 bars).
how it works: smoothing reduces noise in the signal, making VWMO more reliable for voting. a longer smoothing period cuts more noise but adds lag.
how to adjust: if VWMO is too jumpy (lots of false votes), increase to 15. if it’s too slow and missing trades, drop to 5. test on your chart to see what keeps the signal clean but responsive.
vwmo_threshold = input.float(10, "VWMO Threshold") this is the cutoff for VWMO to vote for a trade (default 10). above 10, it votes for a long; below -10, a short.
how it works: it ensures only strong momentum signals count. a higher threshold means fewer but stronger trades.
how to adjust: if you want more trades, lower it to 5. if you’re getting too many weak signals, raise it to 15. this depends on your market—volatile stocks might need a higher threshold to filter noise.
VEI (Velocity Efficiency Index)
VEI measures market efficiency and velocity to filter out choppy moves and focus on strong trends.
vei_eflen = input.int(14, "VEI Efficiency Smoothing") this sets the EMA period for smoothing VEI’s efficiency calc (bar range / volume, default 14 bars).
how it works: efficiency is how much price moves per unit of volume. smoothing it with an EMA reduces noise, focusing on consistent efficiency. a longer period smooths more but adds lag.
how to adjust: for choppy markets, increase to 20 to filter out noise. for faster markets, drop to 10 for quicker signals. this should match your timeframe—shorter timeframes might need a shorter period.
vei_momlen = input.int(8, "VEI Momentum Length") this sets how many bars back VEI looks to calculate momentum in efficiency (default 8 bars).
how it works: it measures the change in smoothed efficiency over 8 bars, then adjusts for inertia (volume-to-range). a longer period captures bigger shifts, while a shorter one reacts faster.
how to adjust: if VEI is missing quick reversals, drop to 5. if it’s too noisy, raise to 12. test on your chart to see what catches the right moves without too many false signals.
vei_threshold = input.float(4.5, "VEI Threshold") this is the cutoff for VEI to vote for a trade (default 4.5). above 4.5, it votes for a long; below -4.5, a short.
how it works: it ensures only strong, efficient moves count. a higher threshold means fewer trades but higher quality.
how to adjust: if you’re not getting enough trades, lower to 3. if you’re seeing too many false entries, raise to 6. this depends on your market—fast stocks like NQ1 might need a lower threshold.
Features
Multi-Signal Voting: requires all three signals (SPR, VWMO, VEI) to align for a trade, ensuring high-probability setups.
Risk Management: uses ATR-based stops (2.1x) and take-profits (4.1x), with dynamic position sizing based on a risk percentage (default 0.4%).
Market Filters: ADX (default 27) ensures trending conditions, choppiness index (default 54.5) avoids sideways markets, and ATR expansion (default 1.12) confirms volatility.
Dashboard: provides real-time stats like SPR, VWMO, VEI values, net P/L, win rate, and streak, with a clean, functional design.
Visuals
EXODUS prioritizes performance over visuals, as it was built for competitive and competition purposes. entry/exit signals are marked with simple labels and shapes, and a basic heatmap highlights market regimes. a more visually stunning update may be released later, with enhanced graphics and overlays.
Usage
EXODUS is designed for stocks and ETFs but can be adapted for futures with adjustments. it performs best in trending markets with sufficient volatility, as confirmed by its generic tuning across symbols like TSLA, AMD, NVDA, and NQ1. adjust inputs like SPR threshold, VWMO smoothing, or VEI momentum length to suit specific assets or timeframes.
Setting I used: (Again, these are a generic setting, each security needs to be fine tuned)
SPR LB = 19 SPR TH = 0.5 SPR ATR L= 21 SPR RTH Sess: 9:30 – 16:00
VWMO L = 21 VWMO LB = 18 VWMO S = 6 VWMO T = 8
VEI ES = 14 VEI ML = 21 VEI T = 4
R % = 0.4
ATR L = 21 ATR M (S) =1.1 TP Multi = 2.1 ATR min mult = 0.8 ATR Expansion = 1.02
ADX L = 21 Min ADX = 25
Choppiness Index = 14 Chop. Max T = 55.5
Backtesting: TSLA
Frame: Jan 02, 2018, 08:00 — May 01, 2025, 09:00
Slippage: 3
Commission .01
Disclaimer
this strategy is for educational purposes. past performance is not indicative of future results. trading involves significant risk, and you should only trade with capital you can afford to lose. always backtest and validate any strategy before using it in live markets.
(This publishing will most likely be taken down do to some miscellaneous rule about properly displaying charting symbols, or whatever. Once I've identified what part of the publishing they want to pick on, I'll adjust and repost.)
About the Author
Dskyz (DAFE) Trading Systems is dedicated to building high-performance trading algorithms. EXODUS is a product of rigorous research and development, aimed at delivering consistent, and data-driven trading solutions.
Use it with discipline. Use it with clarity. Trade smarter.
**I will continue to release incredible strategies and indicators until I turn this into a brand or until someone offers me a contract.
2025 Created by Dskyz, powered by DAFE Trading Systems. Trade smart, trade bold.
Rawstocks 15 Minute ModelRawstocks 15-Minute Model
The Rawstocks 15-Minute Model is a precision intraday trading strategy designed for the US stock market (9:30 AM - 4:00 PM ET), optimized for the 15-minute timeframe. It combines institutional order flow concepts with Fibonacci retracements to identify high-probability reversal setups while enforcing strict risk management and session-based rules.
Key Features
Time-Based Execution
Trading Hours: 9:30 AM - 4:00 PM ET (no new entries after 4:00 PM)
Force Close: All positions auto-exit at 4:30 PM ET (prevents overnight risk)
Entry Logic
Order Block + Fib Confluence:
Identifies institutional order blocks (previous swing highs/lows)
Requires price pullback to 61.8% or 79% Fibonacci level
Liquidity Confirmation:
Waits for stop runs (liquidity sweeps) before reversal entries
Exit Rules
Stop Loss: 1x ATR (14) from entry
Take Profit: 2:1 Risk-Reward (adjustable)
Visual Signals
Green Triangle: Valid long setup (pullback to bullish OB + Fib)
Red Triangle: Valid short setup (pullback to bearish OB + Fib)
Blue/Purple Background: Highlights active trading vs. close period
How It Works
Identify the Setup
Wait for a strong impulse move (break of structure)
Mark the order block (institutional zone)
Confirm Pullback
Price must retrace to 61.8% or 79% Fib level
Must occur within trading hours (9:30 AM - 4:00 PM)
Enter on Confirmation
Long: Break of pullback candle high (stop below recent swing low)
Short: Break of pullback candle low (stop above recent swing high)
Manage the Trade
Trail stop or exit at 2R (risk-to-reward)
All positions close at 4:30 PM sharp
SMC Entry Signals MTF v2📘 User Guide for the SMC Entry Signals MTF v2 Indicator
🎯 Purpose of the Indicator
This indicator is designed to identify reversal entry points based on Smart Money Concepts (SMC) and candlestick confirmation. It’s especially useful for traders who use:
Imbalance zones, order blocks, breaker blocks
Liquidity grabs
Multi-timeframe confirmation (MTF)
📈 How to Use the Signals on the Chart
✅ LONG Signal (green triangle below the candle):
Conditions:
Price is in a discount zone (below the FIB 50% level)
A bullish engulfing candle appears
A bullish Order Block (OB) or Breaker Block is detected
There’s an upward imbalance
A bullish OB is confirmed on the higher timeframe
➡️ How to act:
Consider entering long on the current or next candle.
Place your stop-loss below the OB or the nearest swing low.
Take profit at the nearest liquidity zone or premium area (above FIB 50%).
🔻 SHORT Signal (red triangle above the candle):
Conditions:
Price is in a premium zone (above FIB 50%)
A bearish engulfing candle appears
A bearish OB or Breaker Block is detected
There’s a downward imbalance
A bearish OB is confirmed on the higher timeframe
➡️ How to act:
Consider short entry after the signal.
Place your stop-loss above the OB or swing high.
Target the discount zone or the next liquidity pocket.
⚙️ Recommended Settings by Trading Style
Trading Style Suggested Settings Notes
Intraday (1–15m) fibLookback = 20–50, obLookback = 5–10, htf_tf = 1H/4H Fast signals. Use Discount/Premium + Engulfing.
Swing/Position (1H–1D) fibLookback = 50–100, obLookback = 10–20, htf_tf = 1D/1W Higher trust in MTF confirmation. Ideal with fundamentals.
Scalping (1m) fibLookback = 10–20, obLookback = 3–5, htf_tf = 15m/1H Remove Breaker and MTF for quick reaction trades.
🧠 Best Practices for Traders
Trend Filtering:
Use EMAs or volume to confirm the current trend.
Take longs only in uptrends, shorts in downtrends.
Liquidity Zones:
Use this indicator after liquidity grabs.
OBs and Breakers often appear right after stop hunts.
Combine with Manual Zones:
This works best when paired with manually drawn OBs and key levels.
Backtest the Signals:
Use Bar Replay mode on TradingView to test past signals.
🧪 Example Trade Setup
Example on BTCUSDT 15m:
Price drops into the discount zone.
A green triangle appears (bullish engulfing + OB + imbalance + HTF OB).
You enter long, stop below the OB, target the premium zone.
🎯 This type of setup often gives a risk/reward ratio of 1:2 or better — profitable even with a 40% win rate.
⏰ Alerts & Automation
Enable alerts:
"SMC Long Entry" — fires when a long signal appears.
"SMC Short Entry" — fires when a short signal appears.
You can integrate this with bots via webhook, like:
TradingConnector, 3Commas, Alertatron, etc.
✅ What This Indicator Gives You
High-probability entries using SMC logic
Customizable filters for entry logic
Multi-timeframe confirmation for stronger setups
Suitable for both intraday and swing trading
ADR% Extension Levels from SMA 50I created this indicator inspired by RealSimpleAriel (a swing trader I recommend following on X) who does not buy stocks extended beyond 4 ADR% from the 50 SMA and uses extensions from the 50 SMA at 7-8-9-10-11-12-13 ADR% to take profits with a 20% position trimming.
RealSimpleAriel's strategy (as I understood it):
-> Focuses on leading stocks from leading groups and industries, i.e., those that have grown the most in the last 1-3-6 months (see on Finviz groups and then select sector-industry).
-> Targets stocks with the best technical setup for a breakout, above the 200 SMA in a bear market and above both the 50 SMA and 200 SMA in a bull market, selecting those with growing Earnings and Sales.
-> Buys stocks on breakout with a stop loss set at the day's low of the breakout and ensures they are not extended beyond 4 ADR% from the 50 SMA.
-> 3-5 day momentum burst: After a breakout, takes profits by selling 1/2 or 1/3 of the position after a 3-5 day upward move.
-> 20% trimming on extension from the 50 SMA: At 7 ADR% (ADR% calculated over 20 days) extension from the 50 SMA, takes profits by selling 20% of the remaining position. Continues to trim 20% of the remaining position based on the stock price extension from the 50 SMA, calculated using the 20-period ADR%, thus trimming 20% at 8-9-10-11 ADR% extension from the 50 SMA. Upon reaching 12-13 ADR% extension from the 50 SMA, considers the stock overextended, closes the remaining position, and evaluates a short.
-> Trailing stop with ascending SMA: Uses a chosen SMA (10, 20, or 50) as the definitive stop loss for the position, depending on the stock's movement speed (preferring larger SMAs for slower-moving stocks or for long-term theses). If the stock's closing price falls below the chosen SMA, the entire position is closed.
In summary:
-->Buy a breakout using the day's low of the breakout as the stop loss (this stop loss is the most critical).
--> Do not buy stocks extended beyond 4 ADR% from the 50 SMA.
--> Sell 1/2 or 1/3 of the position after 3-5 days of upward movement.
--> Trim 20% of the position at each 7-8-9-10-11-12-13 ADR% extension from the 50 SMA.
--> Close the entire position if the breakout fails and the day's low of the breakout is reached.
--> Close the entire position if the price, during the rise, falls below a chosen SMA (10, 20, or 50, depending on your preference).
--> Definitively close the position if it reaches 12-13 ADR% extension from the 50 SMA.
I used Grok from X to create this indicator. I am not a programmer, but based on the ADR% I use, it works.
Below is Grok from X's description of the indicator:
Script Description
The script is a custom indicator for TradingView that displays extension levels based on ADR% relative to the 50-period Simple Moving Average (SMA). Below is a detailed description of its features, structure, and behavior:
1. Purpose of the Indicator
Name: "ADR% Extension Levels from SMA 50".
Objective: Draw horizontal blue lines above and below the 50-period SMA, corresponding to specific ADR% multiples (4, 7, 8, 9, 10, 11, 12, 13). These levels represent potential price extension zones based on the average daily percentage volatility.
Overlay: The indicator is overlaid on the price chart (overlay=true), so the lines and SMA appear directly on the price graph.
2. Configurable Inputs
The indicator allows users to customize parameters through TradingView settings:
SMA Length (smaLength):
Default: 50 periods.
Description: Specifies the number of periods for calculating the Simple Moving Average (SMA). The 50-period SMA serves as the reference point for extension levels.
Constraint: Minimum 1 period.
ADR% Length (adrLength):
Default: 20 periods.
Description: Specifies the number of days to calculate the moving average of the daily high/low ratio, used to determine ADR%.
Constraint: Minimum 1 period.
Scale Factor (scaleFactor):
Default: 1.0.
Description: An optional multiplier to adjust the distance of extension levels from the SMA. Useful if levels are too close or too far due to an overly small or large ADR%.
Constraint: Minimum 0.1, increments of 0.1.
Tooltip: "Adjust if levels are too close or far from SMA".
3. Main Calculations
50-period SMA:
Calculated with ta.sma(close, smaLength) using the closing price (close).
Serves as the central line around which extension levels are drawn.
ADR% (Average Daily Range Percentage):
Formula: 100 * (ta.sma(dhigh / dlow, adrLength) - 1).
Details:
dhigh and dlow are the daily high and low prices, obtained via request.security(syminfo.tickerid, "D", high/low) to ensure data is daily-based, regardless of the chart's timeframe.
The dhigh / dlow ratio represents the daily percentage change.
The simple moving average (ta.sma) of this ratio over 20 days (adrLength) is subtracted by 1 and multiplied by 100 to obtain ADR% as a percentage.
The result is multiplied by scaleFactor for manual adjustments.
Extension Levels:
Defined as ADR% multiples: 4, 7, 8, 9, 10, 11, 12, 13.
Stored in an array (levels) for easy iteration.
For each level, prices above and below the SMA are calculated as:
Above: sma50 * (1 + (level * adrPercent / 100))
Below: sma50 * (1 - (level * adrPercent / 100))
These represent price levels corresponding to a percentage change from the SMA equal to level * ADR%.
4. Visualization
Horizontal Blue Lines:
For each level (4, 7, 8, 9, 10, 11, 12, 13 ADR%), two lines are drawn:
One above the SMA (e.g., +4 ADR%).
One below the SMA (e.g., -4 ADR%).
Color: Blue (color.blue).
Style: Solid (style=line.style_solid).
Management:
Each level has dedicated variables for upper and lower lines (e.g., upperLine1, lowerLine1 for 4 ADR%).
Previous lines are deleted with line.delete before drawing new ones to avoid overlaps.
Lines are updated at each bar with line.new(bar_index , level, bar_index, level), covering the range from the previous bar to the current one.
Labels:
Displayed only on the last bar (barstate.islast) to avoid clutter.
For each level, two labels:
Above: E.g., "4 ADR%", positioned above the upper line (style=label.style_label_down).
Below: E.g., "-4 ADR%", positioned below the lower line (style=label.style_label_up).
Color: Blue background, white text.
50-period SMA:
Drawn as a gray line (color.gray) for visual reference.
Diagnostics:
ADR% Plot: ADR% is plotted in the status line (orange, histogram style) to verify the value.
ADR% Label: A label on the last bar near the SMA shows the exact ADR% value (e.g., "ADR%: 2.34%"), with a gray background and white text.
5. Behavior
Dynamic Updating:
Lines update with each new bar to reflect new SMA 50 and ADR% values.
Since ADR% uses daily data ("D"), it remains constant within the same day but changes day-to-day.
Visibility Across All Bars:
Lines are drawn on every bar, not just the last one, ensuring visibility on historical data as well.
Adaptability:
The scaleFactor allows level adjustments if ADR% is too small (e.g., for low-volatility symbols) or too large (e.g., for cryptocurrencies).
Compatibility:
Works on any timeframe since ADR% is calculated from daily data.
Suitable for symbols with varying volatility (e.g., stocks, forex, cryptocurrencies).
6. Intended Use
Technical Analysis: Extension levels represent significant price zones based on average daily volatility. They can be used to:
Identify potential price targets (e.g., take profit at +7 ADR%).
Assess support/resistance zones (e.g., -4 ADR% as support).
Measure price extension relative to the 50 SMA.
Trading: Useful for strategies based on breakouts or mean reversion, where ADR% levels indicate reversal or continuation points.
Debugging: Labels and ADR% plot help verify that values align with the symbol’s volatility.
7. Limitations
Dependence on Daily Data: ADR% is based on daily dhigh/dlow, so it may not reflect intraday volatility on short timeframes (e.g., 1 minute).
Extreme ADR% Values: For low-volatility symbols (e.g., bonds) or high-volatility symbols (e.g., meme stocks), ADR% may require adjustments via scaleFactor.
Graphical Load: Drawing 16 lines (8 upper, 8 lower) on every bar may slow the chart for very long historical periods, though line management is optimized.
ADR% Formula: The formula 100 * (sma(dhigh/dlow, Length) - 1) may produce different values compared to other ADR% definitions (e.g., (high - low) / close * 100), so users should be aware of the context.
8. Visual Example
On a chart of a stock like TSLA (daily timeframe):
The 50 SMA is a gray line tracking the average trend.
Assuming an ADR% of 3%:
At +4 ADR% (12%), a blue line appears at sma50 * 1.12.
At -4 ADR% (-12%), a blue line appears at sma50 * 0.88.
Other lines appear at ±7, ±8, ±9, ±10, ±11, ±12, ±13 ADR%.
On the last bar, labels show "4 ADR%", "-4 ADR%", etc., and a gray label shows "ADR%: 3.00%".
ADR% is visible in the status line as an orange histogram.
9. Code: Technical Structure
Language: Pine Script @version=5.
Inputs: Three configurable parameters (smaLength, adrLength, scaleFactor).
Calculations:
SMA: ta.sma(close, smaLength).
ADR%: 100 * (ta.sma(dhigh / dlow, adrLength) - 1) * scaleFactor.
Levels: sma50 * (1 ± (level * adrPercent / 100)).
Graphics:
Lines: Created with line.new, deleted with line.delete to avoid overlaps.
Labels: Created with label.new only on the last bar.
Plots: plot(sma50) for the SMA, plot(adrPercent) for debugging.
Optimization: Uses dedicated variables for each line (e.g., upperLine1, lowerLine1) for clear management and to respect TradingView’s graphical object limits.
10. Possible Improvements
Option to show lines only on the last bar: Would reduce visual clutter.
Customizable line styles: Allow users to choose color or style (e.g., dashed).
Alert for anomalous ADR%: A message if ADR% is too small or large.
Dynamic levels: Allow users to specify ADR% multiples via input.
Optimization for short timeframes: Adapt ADR% for intraday timeframes.
Conclusion
The script creates a visual indicator that helps traders identify price extension levels based on daily volatility (ADR%) relative to the 50 SMA. It is robust, configurable, and includes debugging tools (ADR% plot and labels) to verify values. The ADR% formula based on dhigh/dlow
Sweep Reversal 5M PRO – by [TuNombre]🔹 **Sweep Reversal 5M PRO – by ** 🔹
This indicator is built to detect high-probability *Institutional Sweeps* using Swing Failure Patterns (SFP), fully filtered with Smart Money Concepts (SMC) logic and volume confirmation.
✅ Identifies key liquidity grabs
✅ Confirms with strong impulse candle + increasing volume
✅ Filters out false signals (doji, weak zones, low volume)
✅ Optimized for the 5-minute timeframe (5M)
✅ Compatible with push alerts to your mobile
---
**How to use it:**
1. Wait for a “BUY” or “SELL” signal on the chart
2. Only enter if the next candle confirms with momentum
3. Place a tight stop just beyond the sweep
4. Recommended Take Profit: 1:1 minimum / 2:1 ideal
---
💡 Inspired by institutional trading (SMC, ICT-style setups)
🔒 Developed by – private or team-based use
📲 Activate alerts to get real-time trade opportunities on your phone
---
⚠️ This script does not repaint.
Built for serious traders who want precision, not noise.
Bitcoin NUPL IndicatorThe Bitcoin NUPL (Net Unrealized Profit/Loss) Indicator is a powerful metric that shows the difference between Bitcoin's market cap and realized cap as a percentage of market cap. This indicator helps identify different market cycle phases, from capitulation to euphoria.
// How It Works
NUPL measures the aggregate profit or loss held by Bitcoin investors, calculated as:
```
NUPL = ((Market Cap - Realized Cap) / Market Cap) * 100
```
// Market Cycle Phases
The indicator automatically color-codes different market phases:
• **Deep Red (< 0%)**: Capitulation Phase - Most coins held at a loss, historically excellent buying opportunities
• **Orange (0-25%)**: Hope & Fear Phase - Early accumulation, price uncertainty and consolidation
• **Yellow (25-50%)**: Optimism & Anxiety Phase - Emerging bull market, increasing confidence
• **Light Green (50-75%)**: Belief & Denial Phase - Strong bull market, high conviction
• **Bright Green (> 75%)**: Euphoria & Greed Phase - Potential market top, historically good profit-taking zone
// Features
• Real-time NUPL calculation with customizable smoothing
• RSI indicator for additional momentum confirmation
• Color-coded background reflecting current market phase
• Reference lines marking key transition zones
• Detailed metrics table showing NUPL value, market sentiment, market cap, realized cap, and RSI
// Strategy Applications
• **Long-term investors**: Use extreme negative NUPL values (deep red) to identify potential bottoms for accumulation
• **Swing traders**: Look for transitions between phases for potential trend changes
• **Risk management**: Consider taking profits when entering the "Euphoria & Greed" phase (bright green)
• **Mean reversion**: Watch for overbought/oversold conditions when NUPL reaches historical extremes
// Settings
• **RSI Length**: Adjusts the period for RSI calculation
• **NUPL Smoothing Length**: Applies moving average smoothing to reduce noise
// Notes
• Premium TradingView subscription required for Glassnode and Coin Metrics data
• Best viewed on daily timeframes for macro analysis
• Historical NUPL extremes have often marked cycle bottoms and tops
• Use in conjunction with other indicators for confirmation
Triple Confirmation Scalper v2 - Alarm CompatibleTriple Confirmation Scalper Strategy
A high-probability scalping strategy combining trend momentum, overbought/sold conditions, and volume confirmation to filter low-noise signals.
📊 Strategy Logic
Trend Direction
Dual EMA crossover (9 & 21 periods) for momentum and trend bias.
Overbought/Oversold Zones
RSI (14-period) to avoid entries at extremes.
Volume Spike Filter
OBV + 20-period volume average to confirm breakout validity.
Dynamic Risk Management
Stop-loss: Adaptive to recent price action (5-candle low/high ±1%).
Take-profit: 1.5% target (1.5:1 risk/reward).
🔍 Advanced Features
Precision VWAP (20-period, HLC3-based) for dynamic S/R levels.
Visual Aids:
EMA/VWAP bands + trend-colored background.
Volume spike alerts.
TradingView Alerts pre-configured for long/short signals.
⚙️ Default Settings
Commission: 0.1% factored into backtests.
Mode: Supports both long/short positions.
⚠️ Disclaimer
This is a technical analysis tool, not financial advice.
Past performance ≠ future results. Test thoroughly in a demo account.
Adjust parameters (e.g., EMA periods, RSI thresholds) to match your risk tolerance.
✅ TradingView Compliance Notes:
No exaggerated claims (e.g., "100% win rate").
Clear disclaimer included.
Focus on objective strategy logic (no promotional language).
TrendTwisterV1.5 (Forex Ready + Indicators)A Precision Trend-Following TradingView Strategy for Forex**
HullShiftFX is a Pine Script strategy for TradingView that combines the power of the **Hull Moving Average (HMA)** and a **shifted Exponential Moving Average (EMA)** with multi-layered momentum filters including **RSI** and **dual Stochastic Oscillators**.
It’s designed for traders looking to catch high-probability breakouts with tight risk management and visual clarity.
Chart settings:
1. Select "Auto - Fits data to screen"
2. Please Select "Scale Price Chart Only" (To make the chart not squished)
### ✅ Entry Conditions
**Long Position:**
- Price closes above the 12-period Hull Moving Average.
- Price closes above the 5-period EMA shifted forward by 2 bars.
- RSI is above 50.
- Stochastic Oscillator (12,3,3) %K is above 50.
- Stochastic Oscillator (5,3,3) %K is above 50.
- Hull MA crosses above the shifted EMA.
**Short Position:**
- Price closes below the 12-period Hull Moving Average.
- Price closes below the 5-period EMA shifted forward by 2 bars.
- RSI is below 50.
- Stochastic Oscillator (12,3,3) %K is below 50.
- Stochastic Oscillator (5,3,3) %K is below 50.
- Hull MA crosses below the shifted EMA.
---
## 📉 Risk Management
- **Stop Loss:** Set at the low (for long) or high (for short) of the previous 2 candles.
- **Take Profit:** Calculated at a risk/reward ratio of **1.65x** the stop loss distance.
---
## 📊 Indicators Used
- **Hull Moving Average (12)**
- **Exponential Moving Average (5) **
- **Relative Strength Index (14)**
- **Stochastic Oscillators:**
- %K (12,3,3)
- %K (5,3,3)
Dkoderweb repainting issue fix strategyHarmonic Pattern Recognition Trading Strategy
This TradingView strategy called "Dkoderweb repainting issue fix strategy" is designed to identify and trade harmonic price patterns with optimized entry and exit points using Fibonacci levels. The strategy implements various popular harmonic patterns including Bat, Butterfly, Gartley, Crab, Shark, ABCD, and their anti-patterns.
Key Features
Pattern Recognition: Identifies 17+ harmonic price patterns including standard and anti-patterns
Fibonacci-Based Entries and Exits: Uses customizable Fibonacci levels for precision entries, take profits, and stop losses
Alternative Timeframe Analysis: Option to use higher timeframes for pattern identification
Heiken Ashi Support: Optional use of Heiken Ashi candles instead of regular candlesticks
Visual Indicators:
Pattern visualization with ZigZag indicator
Buy/sell signal markers
Color-coded background to highlight active trade zones
Customizable Fibonacci level display
How It Works
The strategy uses a ZigZag-based pattern identification system to detect pivot points
When a valid harmonic pattern forms, the strategy calculates the optimal entry window using the specified Fibonacci level (default 0.382)
Entries trigger when price returns to the entry window after pattern completion
Take profit and stop loss levels are automatically set based on customizable Fibonacci ratios
Visual alerts notify you of entries and exits
The strategy tracks active trades and displays them with background color highlights
Customizable Settings
Trade size
Entry window Fibonacci level (default 0.382)
Take profit Fibonacci level (default 0.618)
Stop loss Fibonacci level (default -0.618)
Alert messages for entries and exits
Display options for specific Fibonacci levels
Alternative timeframe selection
This strategy is designed to fix repainting issues that are common in harmonic pattern strategies, ensuring more reliable signals and backtesting results.
Larsson Line Replica (Yellow = Bullish, Blue = Bearish)📘 Interpretation with Flipped Colors
🟨 Yellow Zones – Bullish Trend
• Signals uptrend confirmation.
• SMMA(15) > SMMA(29) indicates upward momentum.
• Ideal for:
• Holding or adding to long positions
• Buying pullbacks within or near the band
• Ignoring short setups on lower timeframes unless reversal signals show up
🟦 Blue Zones – Bearish Trend
• SMMA(15) < SMMA(29) confirms a downtrend.
• Useful for:
• Risk-off posture: take profits, reduce exposure
• Considering short trades
• Waiting out until trend flips yellow again before longing
🩶 Gray Zones – Transition / Unclear
• Represents possible trend change or indecision.
• Appears around crossovers.
• Great time to be cautious — wait for confirmation (either yellow or blue)
• Often coincides with low-volatility consolidation zones or false breakouts
📊 Timeframe Interpretation Tips (with Updated Colors)
🕰️ Weekly – Macro Regime Filter
• 🟨 Yellow = Swing longs allowed
• 🟦 Blue = Risk-off, short setups more reliable
• Use this timeframe as your macro bias anchor
• Combine with higher timeframe market structure, moving averages, or on-chain trends
⸻
📅 Daily – Tactical Entry & Position Management
• Use the slope of the bands for early momentum detection
• 🟦 Blue to Yellow flips = potential trend reversal to the upside → re-enter longs, cut shorts
• 🟨 Yellow to Blue flips = trend weakness or downtrend return → consider profit-taking or short setups
• Great timeframe for:
• Refining entries
• Managing exits
• Spotting trend shifts before weekly confirms
⸻
⏱ Lower Timeframes (4H, 1H) – Execution
• Treat the band like a dynamic trend channel
• Enter trades in direction of the current color:
• 🟨 Yellow → Buy pullbacks to the midline
• 🟦 Blue → Sell bounces into the midline
• Avoid trading against the band unless clear structure or divergence forms
• Pair with RSI/MACD for confluence
Daily Bollinger Band StrategyOverview of the Daily Bollinger Band Strategy
1. Strategy Overview and Features
This strategy is a tool for backtesting a trading method that uses Bollinger Bands. It is *not* a tool for automated trading.
1-1. Main Display Items
The main chart displays the Bollinger Bands and the 200-day moving average.
It also shows the entry and exit points along with the position size (in units of 100 shares).
1-2. Summary of Trading Rules
For long (buy) strategies, the trade enters when the price crosses above the +1σ line of the Bollinger Bands, aiming to ride an upward trend. The position is exited when the price crosses below the middle band.
For short (sell) strategies, the trade enters when the price crosses below the -1σ line of the Bollinger Bands, aiming to ride a downward trend. The position is exited when the price crosses above the middle band.
1-3. Strategic Enhancements
The strategy uses the slope of the 200-day moving average to determine the trend direction and enter trades accordingly. This improves the win rate and payoff ratio.
Additionally, to reduce the probability of ruin, the risk per trade is limited to 1.0% of capital, and position sizing is adjusted using ATR (a volatility indicator).
2. Trading Rules
2-1. Chart Type
Only daily charts are used.
2-2. Indicators Used
(1) Bollinger Bands** (used for entry and exit signals)
- Period: Fixed at 80 days
- Upper and lower bands: Fixed at ±1σ
(2) Moving Average** (used to determine trend direction)
- Period: Fixed at 200 days
- Trend direction is judged based on whether the difference from the previous day is positive (upward) or negative (downward)
2-3. Buy Rules
Setup:
- Price crosses above the +1σ line from below
- Both the middle band and 200-day moving average are upward sloping
Entry:
- Buy at the next day’s market open using a market order
Exit:
- If the price crosses below the middle band, sell at the next day’s open using a market order
2-4. Sell Rules
Setup:
- Price crosses below the -1σ line from above
- Both the middle band and 200-day moving average are downward sloping
Entry:
- Sell at the next day’s market open using a market order
Exit:
- If the price crosses above the middle band, buy back at the next day’s open using a market order
2-5. Risk Management Rules
- Risk per trade: 1.0% of total capital (acceptable loss = capital × 1.0%)
- Position size: Acceptable loss ÷ 2ATR (rounded down to the nearest unit of 100 shares)
2-6. Other Notes
- No brokerage fees
- No pyramiding
- No partial exits
- No reverse positions (no “stop-and-reverse” trades)
3. Strategy Parameters
The following settings can be specified:
3-1. Period Settings
- Start date: Set the start date for the backtest period
- Stop date: Set the end date for the backtest period
3-2. Display of Trend and Signals
- Show trend: When checked, the background color of the bars is light red for an uptrend and light blue for a downtrend
- Show signal: When checked, entry and exit signals are displayed (note: signals are executed at the next day’s open, so there is a one-day lag in the display)
3-3. Capital Management Settings
- Funds: Capital available for trading (in JPY)
- Risk rate: Specify what percentage of the capital to risk per trade
Settings in the “Properties” tab are not used in this strategy.
4. Backtest Results (Example)
Here are the backtest results conducted by the author:
- Target Stocks: All components of the Nikkei 225
- Test Period: January 4, 2000 – December 30, 2024
- Data Points: 12,886
- Win Rate: 33.45%
- Net Profit: ¥82,132,380
- Payoff Ratio: 2.450
- Expected Value: ¥6,373.8
- Risk Rate: 1.0%
- Probability of Ruin: 0.00%
---
デイリー・ボリンジャーバンド・ストラテジーの概要
1. ストラテジーの概要と特徴
このストラテジーは、ボリンジャーバンドを使ったトレード手法のバックテストを行うツールです。自動売買を行うツールではありません。
1-1. 主な表示項目
メインチャートにボリンジャーバンドと 200日移動平均線を表示します。
また、エントリーと手仕舞いのタイミングと数量（100株単位）も表示されます。
1-2. トレードルールの概要
買い戦略の場合、ボリンジャーバンドの +1σ 超えでエントリーして上昇トレンドに乗り、ミドルバンドを割ったら決済します。
売り戦略の場合、ボリンジャーバンドの -1σ 割りでエントリーして下降トレンドに乗り、ミドルバンドを上抜けたら決済します。
1-3. ストラテジーの工夫点
200日移動平均線の傾きを見てトレンド方向にエントリーをしています。こうして勝率とペイオフレシオの成績を向上しています。
また、破産確率を抑えるために、リスク資金比率を 1.0% にして、ATR（ボラティリティ指標） を使って注文数を調整しています。
2. 売買ルール
2-1. 使用するチャート
日足チャートに限定します
2-2. 使用する指標
(1) ボリンジャーバンド（仕掛けと手仕舞いのシグナルに使用）
期間は80日に固定
上下バンドは ±1σ に固定
(2) 移動平均線（トレンドの方向を見るために使用）
期間は200日に固定
移動平均の値の前日との差がプラスのとき上向き、マイナスのとき下向きと判断
2-3. 買いのルール
セットアップ：ボリンジャーバンドの +1σ を価格が下から上に交差 かつ ミドルバンドと 200日移動平均線が上向き
仕掛け：翌日の寄り付きに成行で買う
手仕舞い：ボリンジャーバンドのミドルバンドを価格が上から下に交差したら、翌日の寄り付きに成行で売る
2-4. 売りのルール
セットアップ：ボリンジャーバンドの -1σ を価格が上から下に交差 かつ ミドルバンドと 200日移動平均線が下向き
仕掛け：翌日の寄り付きに成行で売る
手仕舞い：ボリンジャーバンドのミドルバンドを価格が下から上に交差したら、翌日の寄り付きに成行で買い戻す
2-5. 資金管理のルール
リスク資金比率：資産の 1.0%（許容損失 = 資産 × 1.0%）
注文数：許容損失 ÷ 2ATR（単元株数未満は切り捨て）
2-6. その他
仲介手数料：なし
ピラミッディング：なし
分割決済：なし
ドテン：しない
3. ストラテジーのパラメーター
次の項目が指定できます。
3-1. 期間の設定
Staer date : バックテストの検証期間の開始日を指定します
Stop date : バックテストの検証期間の終了日を指定します
3-2. トレンドとシグナルの表示
Show trend : チェックを入れると、バーの背景色が、トレンドが上昇のときは薄い赤で、下落のときは薄い青で表示されます
Show signal : チェックを入れると、エントリーと手仕舞いのシグナルを表示します（シグナルの出た翌日の寄り付きに売買をするので表示に1日のずれがあります）
3-3. 資金管理用の設定
Funds : トレード用の資金(円)
Risk rate : 許容損失を資金の何%にするかで指定します
「プロパティタブ」で設定する値は、このストラテジーでは有効ではありません。
4. バックテストの結果（例）
作者がバックテストを実施した結果をお知らせします。
対象銘柄：日経225構成銘柄すべて
対象期間：2000年1月4日～2024年12月30日
データ件数：12,886
勝率：33.45%
純利益：82,132,380
ペイオフレシオ：2.450
期待値：6,373.8
リスク資金比率：1.0%
破産確率：0.00%
NY First Candle Break and RetestStrategy Overview
Session and Time Parameters:
The strategy focuses on the New York trading session, starting at 9:30 AM and lasting for a predefined session length, typically 3 to 4 hours. This timing captures the most active market hours, providing ample trading opportunities.
Strategy Parameters:
Utilizes the Average True Range (ATR) to set dynamic stop-loss levels, ensuring risk is managed according to market volatility.
Employs a reward-to-risk ratio to determine take profit levels, aiming for a balanced approach between potential gains and losses.
Strategy Settings:
Incorporates simple moving averages (EMA) and the Volume Weighted Average Price (VWAP) to identify trend direction and price levels.
Volume confirmation is used to validate breakouts, ensuring trades are based on significant market activity.
Trade Management:
Features a trailing stop mechanism to lock in profits as the trade moves in favor, with multiple take profit levels to secure gains incrementally.
The strategy is designed to handle both long and short positions, adapting to market conditions.
Alert Settings:
Provides alerts for key events such as session start, breakout, retest, and entry signals, helping traders stay informed and act promptly.
Visual cues on the chart highlight entry and exit points, making it easier for beginners to follow the strategy.
This strategy is particularly suited for the current volatile market environment, where simplicity and clear guidelines can help beginner traders navigate the complexities of trading. It emphasizes risk management and uses straightforward indicators to make informed trading decisions.
I put together this Trading View scalping strategy for futures markets with some help from Claude AI. Shoutout to everyone who gave me advice along the way—I really appreciate it! I’m sure there’s room for improvement, so feel free to share your thoughts… just go easy on me. :)
Dskyz Adaptive Futures Elite (DAFE)Dskyz Adaptive Futures Edge (DAFE)
imgur.com
A Dynamic Futures Trading Strategy
DAFE adapts to market volatility and price action using technical indicators and advanced risk management. It’s built for high-stakes futures trading (e.g., MNQ, BTCUSDT.P), offering modular logic for scalpers and swing traders alike.
Key Features
Adaptive Moving Averages
Dynamic Logic: Fast and slow SMAs adjust lengths via ATR, reacting to momentum shifts and smoothing in calm markets.
Signals: Long entry on fast SMA crossing above slow SMA with price confirmation; short on cross below.
RSI Filtering (Optional)
Momentum Check: Confirms entries with RSI crossovers (e.g., above oversold for longs). Toggle on/off with custom levels.
Fine-Tuning: Adjustable lookback and thresholds (e.g., 60/40) for precision.
Candlestick Pattern Recognition
Eng|Enhanced Detection: Identifies strong bullish/bearish engulfing patterns, validated by volume and range strength (vs. 10-period SMA).
Conflict Avoidance: Skips trades if both patterns appear in the lookback window, reducing whipsaws.
Multi-Timeframe Trend Filter
15-Minute Alignment: Syncs intrabar trades with 15-minute SMA trends; optional for flexibility.
Dollar-Cost Averaging (DCA) New!
Scaling: Adds up to a set number of entries (e.g., 4) on pullbacks/rallies, spaced by ATR multiples.
Control: Caps exposure and resets on exit, enhancing trend-following potential.
Trade Execution & Risk Management
Entry Rules: Prioritizes moving averages or patterns (user choice), with volume, volatility, and time filters.
Stops & Trails:
Initial Stop: ATR-based (2–3.5x, volatility-adjusted).
Trailing Stop: Locks profits with configurable ATR offset and multiplier.
Discipline
Cooldown: Pauses post-exit (e.g., 0–5 minutes).
Min Hold: Ensures trades last a set number of bars (e.g., 2–10).
Visualization & Tools
Charts: Overlays MAs, stops, and signals; trend shaded in background.
Dashboard: Shows position, P&L, win rate, and more in real-time.
Debugging: Logs signal details for optimization.
Input Parameters
Parameter Purpose Suggested Use
Use RSI Filter - Toggle RSI confirmation *Disable 4 price-only
trading
RSI Length - RSI period (e.g., 14) *7–14 for sensitivity
RSI Overbought/Oversold - Adjust for market type *Set levels (e.g., 60/40)
Use Candlestick Patterns - Enables engulfing signals *Disable for MA focus
Pattern Lookback - Pattern window (e.g., 19) *10–20 bars for balance
Use 15m Trend Filter - Align with 15-min trend *Enable for trend trades
Fast/Slow MA Length - Base MA lengths (e.g., 9/19) *10–25 / 30–60 per
timeframe
Volatility Threshold - Filters volatile spikes *Max ATR/close (e.g., 1%)
Min Volume - Entry volume threshold *Avoid illiquid periods
(e.g., 10)
ATR Length - ATR period (e.g., 14) *Standard volatility
measure
Trailing Stop ATR Offset - Trail distance (e.g., 0.5) *0.5–1.5 for tightness
Trailing Stop ATR Multi - Trail multiplier (e.g., 1.0) *1–3 for trend room
Cooldown Minutes - Post-exit pause (e.g., 0–5) *Prevents overtrading
Min Bars to Hold - Min trade duration (e.g., 2) *5–10 for intraday
Trading Hours - Active window (e.g., 9–16) *Focus on key sessions
Use DCA - Toggle DCA *Enable for scaling
Max DCA Entries - Cap entries (e.g., 4) *Limit risk exposure
DCA ATR Multiplier Entry spacing (e.g., 1.0) *1–2 for wider gaps
Compliance
Realistic Testing: Fixed quantities, capital, and slippage for accurate backtests.
Transparency: All logic is user-visible and adjustable.
Risk Controls: Cooldowns, stops, and hold periods ensure stability.
Flexibility: Adapts to various futures and timeframes.
Summary
DAFE excels in volatile futures markets with adaptive logic, DCA scaling, and robust risk tools. Currently in prop account testing, it’s a powerful framework for precision trading.
Caution
DAFE is experimental, not a profit guarantee. Futures trading risks significant losses due to leverage. Backtest, simulate, and monitor actively before live use. All trading decisions are your responsibility.
TQ's Support & Resistance(My goal creating this indicator): Provide a way to categorize and label key structures on multiple different levels so I can create a plan based on those observable facts.
The Underlying Concept / What is Momentum?
Momentum indicates transaction pressure. If the algorithm detects price is going up, that would be considered positive momentum. If the algorithm detects price is going down negative momentum would be detected.
The Momentum shown is derived from a price action pattern. Unlike my previous Support & Resistance indicator that used Super Trend, this indicator uses a unique pattern I created. On the first bar bearish momentum is detected a resistance Level is made at the highest point of the previous bullish condition. On the first bar bullish momentum is detected a support Level is made at the lowest point of the previous bearish condition. This happens on 5 different Momentum Levels, (short-term to long-term). I currently use this pattern to trade so the source code is protected.
What is Severity?
Severity is How we differentiate the importance of different Highs and Lows. If Momentum is detected on a higher level the Supply or Demand Level is updated. The Color and Size representing that Level will be shown. Demand and Supply Levels made by higher levels are more SEVERE than a demand level made by a lower level.
Technical Inputs
- to ensure the correct calculation of Support and Resistance levels change BAR_INDEX. BAR_INDEX creates a buffer at the start of the chart. For example: If you set BAR_INDEX to 300. The script will wait for 300 bars to elapse on the current chart before running. This allows the script more time to gather data. Which is needed in order for our dynamic lookback length to never return an error (Dynamic lookback length can't be negative or zero). The lower the timeframe the greater the number of bars need. For Example, if I open up a 1min chart I would enter 5000 as my BAR_INDEX since that will provide enough data to ensure the correct calculation of Support and Resistance levels. If I was on a daily chart, I would enter a lower number such as 800. Don't be afraid to play around with this.
- Toggle options (Close) or (High & Low) creates Support and Resistance Levels using the Lowest close and Highest close or using the Lowest low and Highest high.
Level Inputs
- The indicator has 5 Different Levels indicating SEVEREITY of a Supply and Demand Levels. The higher the Level the more SEVERE the Level.
Display Inputs
- You have the option to customize the Length, Width, Line Style, and Colors of all 5 different
- This indicator includes a Trend Chart. To Easily verify the current trend of any displayed by this indicator toggle on Chart On/Off. You also get the option to change the Chart Position and the size of the Trend Chart
How Trend Is being Determined?
(Close > Current Supply Level) if this statement is true technically price made a HH, so the trend is bullish.
(Close < Current Demand Level) if this statement is true technically price made a LL, so the trend is bearish.
- Fully customize how you display Market Structure on different levels. Line Length, Line Width, Line Style, and Line color can all be customized.
How it can be used?
(Examples of Different ways you can use this indicator): Easily categorize the severity of each and every Supply or Demand Level in the market (The higher Level the stronger the level)
: Quickly Determine the trend of any Level.
: Get a consistent view of a market and how different Levels are behaving but just use one chart.
: Take the discretion from hand drawing support and resistance lines out of your trading.
: Find and categorize strong levels for potential breakouts.
: Trend Analysis, use Levels to create a narrative based on observable facts from these Levels.
: Different Targets to take money off the table.
: Use Severity to differentiate between different trend line setups.
: Find Great places to move your stop loss too.
