ZH1/5-Min Opening Range Breakout Strategy with Market Biasx.com
"ZH1/5-Min Opening Range Breakout Strategy with Market Bias"
Moving Averages
Golden Cross 50/200 EMATrend-following systems are characterized by having a low win rate, yet in the right circumstances (trending markets and higher timeframes) they can deliver returns that even surpass those of systems with a high win rate.
Below, I show you a simple bullish trend-following system with clear execution rules:
System Rules
-Long entries when the 50-period EMA crosses above the 200-period EMA.
-Stop Loss (SL) placed at the lowest low of the 15 candles prior to the entry candle.
-Take Profit (TP) triggered when the 50-period EMA crosses below the 200-period EMA.
Risk Management
-Initial capital: $10,000
-Position size: 10% of capital per trade
-Commissions: 0.1% per trade
Important Note:
In the code, the stop loss is defined using the swing low (15 candles), but the position size is not adjusted based on the distance to the stop loss. In other words, 10% of the equity is risked on each trade, but the actual loss on the trade is not controlled by a maximum fixed percentage of the account — it depends entirely on the stop loss level. This means the loss on a single trade could be significantly higher or lower than 10% of the account equity, depending on volatility.
Implementing leverage or reducing position size based on volatility is something I haven’t been able to include in the code, but it would dramatically improve the system’s performance. It would fix a consistent percentage loss per trade, preventing losses from fluctuating wildly with changes in volatility.
For example, we can maintain a fixed loss percentage when volatility is low by using the following formula:
Leverage = % of SL you’re willing to risk / % volatility from entry point to stop loss
And when volatility is high and would exceed the fixed percentage we want to expose per trade (if the SL is hit), we could reduce the position size accordingly.
Practical example:
Imagine we only want to risk 15% of the position value if the stop loss is triggered on Tesla (which has high volatility), but the distance to the SL represents a potential 23.57% drop. In this case, we subtract the desired risk (15%) from the actual volatility-based loss (23.57%):
23.57% − 15% = 8.57%
Now suppose we normally use $200 per trade.
To calculate 8.57% of $200:
200 × (8.57 / 100) = $17.14
Then subtract that amount from the original position size:
$200 − $17.14 = $182.86
In summary:
If we reduce the position size to $182.86 (instead of the usual $200), even if Tesla moves 23.57% against us and hits the stop loss, we would still only lose approximately 15% of the original $200 position — exactly the risk level we defined. This way, we strictly respect our risk management rules regardless of volatility swings.
I hope this clearly explains the importance of capping losses at a fixed percentage per trade. This keeps risk under control while maintaining a consistent percentage of capital invested per trade — preventing both statistical distortion of the system and the potential destruction of the account.
About the code:
Strategy declaration:
The strategy is named 'Golden Cross 50/200 EMA'.
overlay=true means it will be drawn directly on the price chart.
initial_capital=10000 sets the initial capital to $10,000.
default_qty_type=strategy.percent_of_equity and default_qty_value=10 means each trade uses 10% of available equity.
margin_long=0 indicates no margin is used for long positions (this is likely for simulation purposes only; in real trading, margin would be required).
commission_type=strategy.commission.percent and commission_value=0.1 sets a 0.1% commission per trade.
Indicators:
Calculates two EMAs: a 50-period EMA (ema50) and a 200-period EMA (ema200).
Crossover detection:
bullCross is triggered when the 50-period EMA crosses above the 200-period EMA (Golden Cross).
bearCross is triggered when the 50-period EMA crosses below the 200-period EMA (Death Cross).
Recent swing:
swingLow calculates the lowest low of the previous 15 periods.
Stop Loss:
entryStopLoss is a variable initialized as na (not available) and is updated to the current swingLow value whenever a bullCross occurs.
Entry and exit conditions:
Entry: When a bullCross occurs, the initial stop loss is set to the current swingLow and a long position is opened.
Exit on opposite signal: When a bearCross occurs, the long position is closed.
Exit on stop loss: If the price falls below entryStopLoss while a position is open, the position is closed.
Visualization:
Both EMAs are plotted (50-period in blue, 200-period in red).
Green triangles are plotted below the bar on a bullCross, and red triangles above the bar on a bearCross.
A horizontal orange line is drawn that shows the stop loss level whenever a position is open.
Alerts:
Alerts are created for:Long entry
Exit on bearish crossover (Death Cross)
Exit triggered by stop loss
Favorable Conditions:
Tesla (45-minute timeframe)
June 29, 2010 – November 17, 2025
Total net profit: $12,458.73 or +124.59%
Maximum drawdown: $1,210.40 or 8.29%
Total trades: 107
Winning trades: 27.10% (29/107)
Profit factor: 3.141
Tesla (1-hour timeframe)
June 29, 2010 – November 17, 2025
Total net profit: $7,681.83 or +76.82%
Maximum drawdown: $993.36 or 7.30%
Total trades: 75
Winning trades: 29.33% (22/75)
Profit factor: 3.157
Netflix (45-minute timeframe)
May 23, 2002 – November 17, 2025
Total net profit: $11,380.73 or +113.81%
Maximum drawdown: $699.45 or 5.98%
Total trades: 134
Winning trades: 36.57% (49/134)
Profit factor: 2.885
Netflix (1-hour timeframe)
May 23, 2002 – November 17, 2025
Total net profit: $11,689.05 or +116.89%
Maximum drawdown: $844.55 or 7.24%
Total trades: 107
Winning trades: 37.38% (40/107)
Profit factor: 2.915
Netflix (2-hour timeframe)
May 23, 2002 – November 17, 2025
Total net profit: $12,807.71 or +128.10%
Maximum drawdown: $866.52 or 6.03%
Total trades: 56
Winning trades: 41.07% (23/56)
Profit factor: 3.891
Meta (45-minute timeframe)
May 18, 2012 – November 17, 2025
Total net profit: $2,370.02 or +23.70%
Maximum drawdown: $365.27 or 3.50%
Total trades: 83
Winning trades: 31.33% (26/83)
Profit factor: 2.419
Apple (45-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $8,232.55 or +80.59%
Maximum drawdown: $581.11 or 3.16%
Total trades: 140
Winning trades: 34.29% (48/140)
Profit factor: 3.009
Apple (1-hour timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $9,685.89 or +94.93%
Maximum drawdown: $374.69 or 2.26%
Total trades: 118
Winning trades: 35.59% (42/118)
Profit factor: 3.463
Apple (2-hour timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $8,001.28 or +77.99%
Maximum drawdown: $755.84 or 7.56%
Total trades: 67
Winning trades: 41.79% (28/67)
Profit factor: 3.825
NVDA (15-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $11,828.56 or +118.29%
Maximum drawdown: $1,275.43 or 8.06%
Total trades: 466
Winning trades: 28.11% (131/466)
Profit factor: 2.033
NVDA (30-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $12,203.21 or +122.03%
Maximum drawdown: $1,661.86 or 10.35%
Total trades: 245
Winning trades: 28.98% (71/245)
Profit factor: 2.291
NVDA (45-minute timeframe)
January 3, 2000 – November 17, 2025
Total net profit: $16,793.48 or +167.93%
Maximum drawdown: $1,458.81 or 8.40%
Total trades: 172
Winning trades: 33.14% (57/172)
Profit factor: 2.927
ATR Trend + RSI Pullback Strategy [Profit-Focused]This strategy is designed to catch high-probability pullbacks during strong trends using a combination of ATR-based volatility filters, RSI exhaustion levels, and a trend-following entry model.
Strategy Logic
Rather than relying on lagging crossovers, this model waits for RSI to dip into oversold zones (below 40) while price remains above a long-term EMA (default: 200). This setup captures pullbacks in strong uptrends, allowing traders to enter early in a move while controlling risk dynamically.
To avoid entries during low-volatility conditions or sideways price action, it applies a minimum ATR filter. The ATR also defines both the stop-loss and take-profit levels, allowing the model to adapt to changing market conditions.
Exit logic includes:
A take-profit at 3× the ATR distance
A stop-loss at 1.5× the ATR distance
An optional early exit if RSI crosses above 70, signaling overbought conditions
Technical Details
Trend Filter: 200 EMA – must be rising and price must be above it
Entry Signal: RSI dips below 40 during an uptrend
Volatility Filter: ATR must be above a user-defined minimum threshold
Stop-Loss: 1.5× ATR below entry price
Take-Profit: 3.0× ATR above entry price
Exit on Overbought: RSI > 70 (optional early exit)
Backtest Settings
Initial Capital: $10,000
Position Sizing: 5% of equity per trade
Slippage: 1 tick
Commission: 0.075% per trade
Trade Direction: Long only
Timeframes Tested: 15m, 1H, and 30m on trending assets like BTCUSD, NAS100, ETHUSD
This model is tuned for positive P&L across trending environments and volatile markets.
Educational Use Only
This strategy is for educational purposes only and should not be considered financial advice. Past performance does not guarantee future results. Always validate performance on multiple markets and timeframes before using it in live trading.
BTC EMA 5-9 Flip Strategy AutobotThis strategy is designed for fast and accurate trend-following trades on Bitcoin.
It uses a crossover between EMA 5 and EMA 9 to detect instant trend reversals and automatically flips between Long and Short positions.
How the strategy works
EMA 5 crossing above EMA 9 → Long
EMA 5 crossing below EMA 9 → Short
Automatically closes the opposite trade during a flip
Executes trades only on candle close
Prevents double entries with internal position-state logic
Fully compatible with automated trading via webhooks (Delta Exchange)
Why this strategy works
EMA 5–9 is extremely responsive for BTC’s volatility
Captures trend reversals early
Works best on 15-minute timeframe
Clean, simple logic without over-filtering reduces missed opportunities
Performs well in both uptrends and downtrends
Automation Ready
This strategy includes alert conditions and webhook-ready JSON for automated execution.
This is a fast-reacting BTC bot designed for intraday and swing crypto trend trading.
Moving Average Band StrategyOverview
The Moving Average Band Strategy is a fully customizable breakout and trend-continuation system designed for traders who need both simplicity and control.
The strategy creates adaptive bands around a user-selected moving average and executes trades when price breaks out of these bands, with advanced risk-management settings including optional Risk:Reward targets.
This script is suitable for intraday, swing, and positional traders across all markets — equities, futures, crypto, and forex.
Key Features
✔ Six Moving Average Types
Choose the MA that best matches your trading style:
SMA
EMA
WMA
HMA
VWMA
RMA
✔ Dynamic Bands
Upper Band built from MA of highs
Lower Band built from MA of lows
Adjustable band offset (%)
Color-coded band fill indicating price position
✔ Configurable Strategy Preferences
Toggle Long and/or Short trades
Toggle Risk:Reward Take-Profit
Adjustable Risk:Reward Ratio
Default position sizing: % of equity (configurable via strategy settings)
Entry Conditions
Long Entry
A long trade triggers when:
Price crosses above the Upper Band
Long trades are enabled
No existing long position is active
Short Entry
A short trade triggers when:
Price crosses below the Lower Band
Short trades are enabled
No existing short position is active
Clear entry markers and price labels appear on the chart.
Risk Management
This strategy includes a complete set of risk-controls:
Stop-Loss (Fixed at Entry)
Long SL: Lower Band
Short SL: Upper Band
These levels remain constant for the entire trade.
Optional Risk:Reward Take-Profit
Enabled/disabled using a toggle switch.
When enabled:
Long TP = Entry + (Risk × Risk:Reward Ratio)
Short TP = Entry – (Risk × Risk:Reward Ratio)
When disabled:
Exits are handled by reverse crossover signals.
Exit Conditions
Long Exit
Stop-Loss Hit (touch-based)
Take-Profit Hit (if enabled)
Reverse Band Crossover (if TP disabled)
Short Exit
Stop-Loss Hit (touch-based)
Take-Profit Hit (if enabled)
Reverse Band Crossover (if TP disabled)
Exit markers and price labels are plotted automatically.
Visual Tools
To improve clarity:
Upper & Lower Band (blue, adjustable width)
Middle Line
Dynamic band fill (green/red/yellow)
SL & TP line plotting when in position
Entry/Exit markers
Price labels for all executed trades
These are built to help users visually follow the strategy logic.
Alerts Included
Every trading event is covered:
Long Entry
Short Entry
Long SL / TP / Cross Exit
Short SL / TP / Cross Exit
Combined Alert for webhook/automation (JSON-formatted)
Perfect for algo trading, Discord bots, or automation platforms.
Best For
This strategy performs best in:
Trending markets
Breakout environments
High-momentum instruments
Clean intraday swings
Works seamlessly on:
Stocks
Index futures
Commodities
Crypto
Forex
⚠️ Important Disclaimer
This script is for educational purposes only.
Trading involves risk. Backtest results are not indicative of future performance.
Always validate settings and use proper position sizing.
Qullamagi EMA Breakout Autotrade (Crypto Futures L+S)Title: Qullamagi EMA Breakout – Crypto Autotrade
Overview
A crypto-focused, Qullamagi-style EMA breakout strategy built for autotrading on futures and perpetual swaps.
It combines a 5-MA trend stack (EMA 10/20, SMA 50/100/200), volatility contraction boxes, volume spikes and an optional higher-timeframe 200-MA filter. The script supports both long and short trades, partial take profit, trailing MA exits and percent-of-equity position sizing for automated crypto futures trading.
Key Features (Crypto)
Qullamagi MA Breakout Engine – trades only when price is aligned with a strong EMA/SMA trend and breaks out of a tight consolidation range. Longs use: Close > EMA10 > EMA20 > SMA50 > SMA100 > SMA200. Shorts are the mirror condition with all MAs sloping in the trend direction.
Strict vs Loose Modes – Strict (Daily) is designed for cleaner swing trades on 1H–4H (full MA stack, box+ATR and volume filters, optional HTF filter). Loose (Intraday) focuses on 10/20/50 alignment with relaxed filters for more frequent 15m–30m signals.
Volatility & Volume Filters for Crypto – ATR-based box height limit to detect volatility contraction, wide-candle filter to avoid chasing exhausted breakouts, and a volume spike condition requiring current volume to exceed an SMA of volume.
Higher-Timeframe Trend Filter (Optional) – uses a 200-period SMA on a higher timeframe (default: 1D). Longs only when HTF close is above the HTF 200-SMA, shorts only when it is below, helping avoid trading against dominant crypto trends.
Autotrade-Oriented Trade Management – position size as % of equity, initial stop anchored to a chosen MA (EMA10 / EMA20 / SMA50) with optional buffer, partial take profit at a configurable R-multiple, trailing MA exit for the remainder, and an optional cooldown after a full exit.
Markets & Timeframes
Best suited for BTC, ETH and major altcoin futures/perpetuals (Binance, Bybit, OKX, etc.).
Strict preset: 1H–4H charts for classic Qullamagi-style trend structure and fewer fake breakouts.
Loose preset: 15m–30m charts for higher trade frequency and more active intraday trading.
Always retune ATR length, box length, volume multiplier and position size for each symbol and exchange.
Strategy Logic (Quick Summary)
Long (Strict): MA stack in bullish alignment with all MAs sloping up → tight volatility box (ATR-based) → volume spike above SMA(volume) × multiplier → breakout above box high (close or intrabar) → optional HTF close above 200-SMA.
Short: Mirror logic: bearish MA stack, tight box, volume spike and breakdown below box low with optional HTF downtrend.
Best Practices for Crypto
Backtest on each symbol and timeframe you plan to autotrade, including commissions and slippage.
Start on higher timeframes (1H/4H) to learn the behavior, then move to 15m–30m if you want more signals.
Use the higher-timeframe filter when markets are strongly trending to reduce counter-trend trades.
Keep position-size percentage conservative until you fully understand the drawdowns.
Forward-test / paper trade before connecting to live futures accounts.
Webhook / Autotrade Integration
Designed to work with TradingView webhooks and external crypto trading bots.
Alert messages include structured fields such as: EVENT=ENTRY / SCALE_OUT / EXIT, SIDE=LONG / SHORT, STRATEGY=Qullamagi_MA.
Map each EVENT + SIDE combination to your bot logic (open long/short, partial close, full close, etc.) on your preferred exchange.
Important Notes & Disclaimer
Crypto markets are highly volatile and can change regime quickly. Backtest and forward-test thoroughly before using real capital. Higher timeframes generally produce cleaner MA structures and fewer fake breakouts.
This strategy is for educational and informational purposes only and does not constitute financial advice. Trading leveraged crypto products involves substantial risk of loss. Always do your own research, manage risk carefully, and never trade with money you cannot afford to lose.
Range Oscillator Strategy + Stoch Confirm🔹 Short summary
This is a free, educational long-only strategy built on top of the public “Range Oscillator” by Zeiierman (used under CC BY-NC-SA 4.0), combined with a Stochastic timing filter, an EMA-based exit filter and an optional risk-management layer (SL/TP and R-multiple exits). It is NOT financial advice and it is NOT a magic money machine. It’s a structured framework to study how range-expansion + momentum + trend slope can be combined into one rule-based system, often with intentionally RARE trades.
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0. Legal / risk disclaimer
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• This script is FREE and public. I do not charge any fee for it.
• It is for EDUCATIONAL PURPOSES ONLY.
• It is NOT financial advice and does NOT guarantee profits.
• Backtest results can be very different from live results.
• Markets change over time; past performance is NOT indicative of future performance.
• You are fully responsible for your own trades and risk.
Please DO NOT use this script with money you cannot afford to lose. Always start in a demo / paper trading environment and make sure you understand what the logic does before you risk any capital.
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1. About default settings and risk (very important)
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The script is configured with the following defaults in the `strategy()` declaration:
• `initial_capital = 10000`
→ This is only an EXAMPLE account size.
• `default_qty_type = strategy.percent_of_equity`
• `default_qty_value = 100`
→ This means 100% of equity per trade in the default properties.
→ This is AGGRESSIVE and should be treated as a STRESS TEST of the logic, not as a realistic way to trade.
TradingView’s House Rules recommend risking only a small part of equity per trade (often 1–2%, max 5–10% in most cases). To align with these recommendations and to get more realistic backtest results, I STRONGLY RECOMMEND you to:
1. Open **Strategy Settings → Properties**.
2. Set:
• Order size: **Percent of equity**
• Order size (percent): e.g. **1–2%** per trade
3. Make sure **commission** and **slippage** match your own broker conditions.
• By default this script uses `commission_value = 0.1` (0.1%) and `slippage = 3`, which are reasonable example values for many crypto markets.
If you choose to run the strategy with 100% of equity per trade, please treat it ONLY as a stress-test of the logic. It is NOT a sustainable risk model for live trading.
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2. What this strategy tries to do (conceptual overview)
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This is a LONG-ONLY strategy designed to explore the combination of:
1. **Range Oscillator (Zeiierman-based)**
- Measures how far price has moved away from an adaptive mean.
- Uses an ATR-based range to normalize deviation.
- High positive oscillator values indicate strong price expansion away from the mean in a bullish direction.
2. **Stochastic as a timing filter**
- A classic Stochastic (%K and %D) is used.
- The logic requires %K to be below a user-defined level and then crossing above %D.
- This is intended to catch moments when momentum turns up again, rather than chasing every extreme.
3. **EMA Exit Filter (trend slope)**
- An EMA with configurable length (default 70) is calculated.
- The slope of the EMA is monitored: when the slope turns negative while in a long position, and the filter is enabled, it triggers an exit condition.
- This acts as a trend-protection exit: if the medium-term trend starts to weaken, the strategy exits even if the oscillator has not yet fully reverted.
4. **Optional risk-management layer**
- Percentage-based Stop Loss and Take Profit (SL/TP).
- Risk/Reward (R-multiple) exit based on the distance from entry to SL.
- Implemented as OCO orders that work *on top* of the logical exits.
The goal is not to create a “holy grail” system but to serve as a transparent, configurable framework for studying how these concepts behave together on different markets and timeframes.
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3. Components and how they work together
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(1) Range Oscillator (based on “Range Oscillator (Zeiierman)”)
• The script computes a weighted mean price and then measures how far price deviates from that mean.
• Deviation is normalized by an ATR-based range and expressed as an oscillator.
• When the oscillator is above the **entry threshold** (default 100), it signals a strong move away from the mean in the bullish direction.
• When it later drops below the **exit threshold** (default 30), it can trigger an exit (if enabled).
(2) Stochastic confirmation
• Classic Stochastic (%K and %D) is calculated.
• An entry requires:
- %K to be below a user-defined “Cross Level”, and
- then %K to cross above %D.
• This is a momentum confirmation: the strategy tries to enter when momentum turns up from a pullback rather than at any random point.
(3) EMA Exit Filter
• The EMA length is configurable via `emaLength` (default 70).
• The script monitors the EMA slope: it computes the relative change between the current EMA and the previous EMA.
• If the slope turns negative while the strategy holds a long position and the filter is enabled, it triggers an exit condition.
• This is meant to help protect profits or cut losses when the medium-term trend starts to roll over, even if the oscillator conditions are not (yet) signalling exit.
(4) Risk management (optional)
• Stop Loss (SL) and Take Profit (TP):
- Defined as percentages relative to average entry price.
- Both are disabled by default, but you can enable them in the Inputs.
• Risk/Reward Exit:
- Uses the distance from entry to SL to project a profit target at a configurable R-multiple.
- Also optional and disabled by default.
These exits are implemented as `strategy.exit()` OCO orders and can close trades independently of oscillator/EMA conditions if hit first.
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4. Entry & Exit logic (high level)
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A) Time filter
• You can choose a **Start Year** in the Inputs.
• Only candles between the selected start date and 31 Dec 2069 are used for backtesting (`timeCondition`).
• This prevents accidental use of tiny cherry-picked windows and makes tests more honest.
B) Entry condition (long-only)
A long entry is allowed when ALL the following are true:
1. `timeCondition` is true (inside the backtest window).
2. If `useOscEntry` is true:
- Range Oscillator value must be above `entryLevel`.
3. If `useStochEntry` is true:
- Stochastic condition (`stochCondition`) must be true:
- %K < `crossLevel`, then %K crosses above %D.
If these filters agree, the strategy calls `strategy.entry("Long", strategy.long)`.
C) Exit condition (logical exits)
A position can be closed when:
1. `timeCondition` is true AND a long position is open, AND
2. At least one of the following is true:
- If `useOscExit` is true: Oscillator is below `exitLevel`.
- If `useMagicExit` (EMA Exit Filter) is true: EMA slope is negative (`isDown = true`).
In that case, `strategy.close("Long")` is called.
D) Risk-management exits
While a position is open:
• If SL or TP is enabled:
- `strategy.exit("Long Risk", ...)` places an OCO stop/limit order based on the SL/TP percentages.
• If Risk/Reward exit is enabled:
- `strategy.exit("RR Exit", ...)` places an OCO order using a projected R-multiple (`rrMult`) of the SL distance.
These risk-based exits can trigger before the logical oscillator/EMA exits if price hits those levels.
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5. Recommended backtest configuration (to avoid misleading results)
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To align with TradingView House Rules and avoid misleading backtests:
1. **Initial capital**
- 10 000 (or any value you personally want to work with).
2. **Order size**
- Type: **Percent of equity**
- Size: **1–2%** per trade is a reasonable starting point.
- Avoid risking more than 5–10% per trade if you want results that could be sustainable in practice.
3. **Commission & slippage**
- Commission: around 0.1% if that matches your broker.
- Slippage: a few ticks (e.g. 3) to account for real fills.
4. **Timeframe & markets**
- Volatile symbols (e.g. crypto like BTCUSDT, or major indices).
- Timeframes: 1H / 4H / **1D (Daily)** are typical starting points.
- I strongly recommend trying the strategy on **different timeframes**, for example 1D, to see how the behaviour changes between intraday and higher timeframes.
5. **No “caution warning”**
- Make sure your chosen symbol + timeframe + settings do not trigger TradingView’s caution messages.
- If you see warnings (e.g. “too few trades”), adjust timeframe/symbol or the backtest period.
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5a. About low trade count and rare signals
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This strategy is intentionally designed to trade RARELY:
• It is **long-only**.
• It uses strict filters (Range Oscillator threshold + Stochastic confirmation + optional EMA Exit Filter).
• On higher timeframes (especially **1D / Daily**) this can result in a **low total number of trades**, sometimes WELL BELOW 100 trades over the whole backtest.
TradingView’s House Rules mention 100+ trades as a guideline for more robust statistics. In this specific case:
• The **low trade count is a conscious design choice**, not an attempt to cherry-pick a tiny, ultra-profitable window.
• The goal is to study a **small number of high-conviction long entries** on higher timeframes, not to generate frequent intraday signals.
• Because of the low trade count, results should NOT be interpreted as statistically strong or “proven” – they are only one sample of how this logic would have behaved on past data.
Please keep this in mind when you look at the equity curve and performance metrics. A beautiful curve with only a handful of trades is still just a small sample.
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6. How to use this strategy (step-by-step)
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1. Add the script to your chart.
2. Open the **Inputs** tab:
- Set the backtest start year.
- Decide whether to use Oscillator-based entry/exit, Stochastic confirmation, and EMA Exit Filter.
- Optionally enable SL, TP, and Risk/Reward exits.
3. Open the **Properties** tab:
- Set a realistic account size if you want.
- Set order size to a realistic % of equity (e.g. 1–2%).
- Confirm that commission and slippage are realistic for your broker.
4. Run the backtest:
- Look at Net Profit, Max Drawdown, number of trades, and equity curve.
- Remember that a low trade count means the statistics are not very strong.
5. Experiment:
- Tweak thresholds (`entryLevel`, `exitLevel`), Stochastic settings, EMA length, and risk params.
- See how the metrics and trade frequency change.
6. Forward-test:
- Before using any idea in live trading, forward-test on a demo account and observe behaviour in real time.
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7. Originality and usefulness (why this is more than a mashup)
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This script is not intended to be a random visual mashup of indicators. It is designed as a coherent, testable strategy with clear roles for each component:
• Range Oscillator:
- Handles mean vs. range-expansion states via an adaptive, ATR-normalized metric.
• Stochastic:
- Acts as a timing filter to avoid entering purely on extremes and instead waits for momentum to turn.
• EMA Exit Filter:
- Trend-slope-based safety net to exit when the medium-term direction changes against the position.
• Risk module:
- Provides practical, rule-based exits: SL, TP, and R-multiple exit, which are useful for structuring risk even if you modify the core logic.
It aims to give traders a ready-made **framework to study and modify**, not a black box or “signals” product.
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8. Limitations and good practices
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• No single strategy works on all markets or in all regimes.
• This script is long-only; it does not short the market.
• Performance can degrade when market structure changes.
• Overfitting (curve fitting) is a real risk if you endlessly tweak parameters to maximise historical profit.
Good practices:
- Test on multiple symbols and timeframes.
- Focus on stability and drawdown, not only on how high the profit line goes.
- View this as a learning tool and a basis for your own research.
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9. Licensing and credits
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• Core oscillator idea & base code:
- “Range Oscillator (Zeiierman)”
- © Zeiierman, licensed under CC BY-NC-SA 4.0.
• Strategy logic, Stochastic confirmation, EMA Exit Filter, and risk-management layer:
- Modifications by jokiniemi.
Please respect both the original license and TradingView House Rules if you fork or republish any part of this script.
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10. No payments / no vendor pitch
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• This script is completely FREE to use on TradingView.
• There is no paid subscription, no external payment link, and no private signals group attached to it.
• If you have questions, please use TradingView’s comment system or private messages instead of expecting financial advice.
Use this script as a tool to learn, experiment, and build your own understanding of markets.
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11. Example backtest settings used in screenshots
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To avoid any confusion about how the results shown in screenshots were produced, here is one concrete example configuration:
• Symbol: BTCUSDT (or similar major BTC pair)
• Timeframe: 1D (Daily)
• Backtest period: from 2018 to the most recent data
• Initial capital: 10 000
• Order size type: Percent of equity
• Order size: 2% per trade
• Commission: 0.1%
• Slippage: 3 ticks
• Risk settings: Stop Loss and Take Profit disabled by default, Risk/Reward exit disabled by default
• Filters: Range Oscillator entry/exit enabled, Stochastic confirmation enabled, EMA Exit Filter enabled
If you change any of these settings (symbol, timeframe, risk per trade, commission, slippage, filters, etc.), your results will look different. Please always adapt the configuration to your own risk tolerance, market, and trading style.
Braid Filter StrategyThis strategy is like a sophisticated set of traffic lights and speed limit signs for trading. It only allows a trade when multiple indicators line up to confirm a strong move, giving it its "Braid Filter" name—it weaves together several conditions.
The strategy is set up to use 100% of your account equity (your trading funds) on a trade and does not "pyramid" (it won't add to an existing trade).
1. The Main Trend Check (The Traffic Lights)
The strategy uses three main filters that must agree before it considers a trade.
A. The "Chad Filter" (Direction & Strength)
This is the heart of the strategy, a custom combination of three different Moving AveragesThese averages have fast, medium, and slow settings (3, 7, and 14 periods).
Go Green (Buy Signal): The fastest average is higher than the medium average, AND the three averages are sufficiently separated (not tangled up, which indicates a strong move).
Go Red (Sell Signal): The medium average is higher than the fastest average, AND the three averages are sufficiently separated.
Neutral (Wait): If the averages are tangled or the separation isn't strong enough.
Key Trigger: A primary condition for a signal is when the Chad Filter changes color (e.g., from Red/Grey to Green).
B. The EMA Trend Bars (Secondary Confirmation)
This is a simpler, longer-term filter using a 34-period Exponential Moving Average (EMA). It checks if the current candle's average price is above or below this EMA.
Green Bars: The price is above the 34 EMA (Bullish Trend).
Red Bars: The price is below the 34 EMA (Bearish Trend).
Trades only happen if the signal direction matches the bar color. For a Buy, the bar must be Green. For a Sell, the bar must be Red.
C. ADX/DI Filter (The Speed Limit Sign)
This uses the Average Directional Index (ADX) and Directional Movement Indicators (DI) to check if a trend is actually in motion and getting stronger.
Must-Have Conditions:
The ADX value must be above 20 (meaning there is a trend, not just random movement).
The ADX line must be rising (meaning the trend is accelerating/getting stronger).
The strategy will only trade when the trend is strong and building momentum.
2. The Trading Action (Entry and Exit)
When all three filters (Chad Filter color change, EMA Trend Bar color, and ADX strength/slope) align, the strategy issues a signal, but it doesn't enter immediately.
Entry Strategy (The "Wait-for-Confirmation" Approach):
When a Buy Signal appears, the strategy sets a "Buy Stop" order at the signal candle's closing price.
It then waits for up to 3 candles (Candles Valid for Entry). The price must move up and hit that Buy Stop price within those 3 candles to confirm the move and enter the trade.
A Sell Signal works the same way but uses a "Sell Stop" at the closing price, waiting for the price to drop and hit it.
Risk Management (Stop Loss and Take Profit):
Stop Loss: To manage risk, the strategy finds a recent significant low (for a Buy) or high (for a Sell) over the last 20 candles and places the Stop Loss there. This is a logical place where the current move would be considered "broken" if the price reaches it.
Take Profit: It uses a fixed Risk:Reward Ratio (set to 1.5 by default). This means the potential profit (Take Profit distance) is $1.50 for every $1.00 of risk (Stop Loss distance).
3. Additional Controls
Time Filter: You can choose to only allow trades during specific hours of the day.
Visuals: It shows a small triangle on the chart where the signal happens and colors the background to reflect the Chad Filter's trend (Green/Red/Grey) and the candle bars to show the EMA trend (Lime/Red).
🎯 Summary of the Strategy's Goal
This strategy is designed to capture strong, confirmed momentum moves. It uses a fast, custom indicator ("Chad Filter") to detect the start of a new move, confirms that move with a slower trend filter (34 EMA), and then validates the move's strength with the ADX. By waiting a few candles for the price to hit the entry level, it aims to avoid false signals.
Braid Filter StrategyAnother of TradeIQ's youtube strategies. It looks a little messy but it combines all the indicators into one so there are no extra panes. This strategy is like a sophisticated set of traffic lights and speed limit signs for trading. It only allows a trade when multiple indicators line up to confirm a strong move, giving it its "Braid Filter" name—it weaves together several conditions.
The strategy is set up to use 100% of your account equity (your trading funds) on a trade and does not "pyramid" (it won't add to an existing trade).
1. The Main Trend Check (The Traffic Lights)
The strategy uses three main filters that must agree before it considers a trade.
A. The "Braid Filter" (Direction & Strength)
This is the heart of the strategy, a custom combination of three different Moving Averages
These averages have fast, medium, and slow settings (3, 7, and 14 periods).
Go Green (Buy Signal): The fastest average is higher than the medium average, AND the three averages are sufficiently separated (not tangled up, which indicates a strong move).
Go Red (Sell Signal): The medium average is higher than the fastest average, AND the three averages are sufficiently separated.
Neutral (Wait): If the averages are tangled or the separation isn't strong enough.
Key Trigger: A primary condition for a signal is when the Chad Filter changes color (e.g., from Red/Grey to Green).
B. The EMA Trend Bars (Secondary Confirmation)
This is a simpler, longer-term filter using a 34-period Exponential Moving Average (EMA). It checks if the current candle's average price is above or below this EMA.
Green Bars: The price is above the 34 EMA (Bullish Trend).
Red Bars: The price is below the 34 EMA (Bearish Trend).
Trades only happen if the signal direction matches the bar color. For a Buy, the bar must be Green. For a Sell, the bar must be Red.
C. ADX/DI Filter (The Speed Limit Sign)
This uses the Average Directional Index (ADX) and Directional Movement Indicators (DI) to check if a trend is actually in motion and getting stronger.
Must-Have Conditions:
The ADX value must be above 20 (meaning there is a trend, not just random movement).
The ADX line must be rising (meaning the trend is accelerating/getting stronger).
The strategy will only trade when the trend is strong and building momentum.
2. The Trading Action (Entry and Exit)
When all three filters (Chad Filter color change, EMA Trend Bar color, and ADX strength/slope) align, the strategy issues a signal, but it doesn't enter immediately.
Entry Strategy (The "Wait-for-Confirmation" Approach):
When a Buy Signal appears, the strategy sets a "Buy Stop" order at the signal candle's closing price.
It then waits for up to 3 candles (Candles Valid for Entry). The price must move up and hit that Buy Stop price within those 3 candles to confirm the move and enter the trade.
A Sell Signal works the same way but uses a "Sell Stop" at the closing price, waiting for the price to drop and hit it.
Risk Management (Stop Loss and Take Profit):
Stop Loss: To manage risk, the strategy finds a recent significant low (for a Buy) or high (for a Sell) over the last 20 candles and places the Stop Loss there. This is a logical place where the current move would be considered "broken" if the price reaches it.
Take Profit: It uses a fixed Risk:Reward Ratio (set to 1.5 by default). This means the potential profit (Take Profit distance) is $1.50 for every $1.00 of risk (Stop Loss distance).
3. Additional Controls
Time Filter: You can choose to only allow trades during specific hours of the day.
Visuals: It shows a small triangle on the chart where the signal happens and colors the background to reflect the Chad Filter's trend (Green/Red/Grey) and the candle bars to show the EMA trend (Lime/Red).
🎯 Summary of the Strategy's Goal
This strategy is designed to capture strong, confirmed momentum moves. It uses a fast, custom indicator ("Chad Filter") to detect the start of a new move, confirms that move with a slower trend filter (34 EMA), and then validates the move's strength with the ADX. By waiting a few candles for the price to hit the entry level, it aims to avoid false signals.
EMA Cross + RSI + ADX - Autotrade Strategy V2Overview
A versatile trend-following strategy combining EMA 9/21 crossovers with RSI momentum filtering and optional ADX trend strength confirmation. Designed for both cryptocurrency and traditional futures/options markets with built-in stop loss management and automated position reversals.
Key Features
Multi-Market Compatibility: Works on both crypto futures (Bitcoin, Ethereum) and traditional markets (NIFTY, Bank NIFTY, S&P 500 futures, equity options)
Triple Confirmation System: EMA crossover + RSI filter + ADX strength (optional)
Automated Risk Management: 2% stop loss with wick-touch detection
Position Auto-Reversal: Opposite signals automatically close and reverse positions
Webhook Ready: Six distinct alert messages for automation (Entry Buy/Sell, Close Long/Short, SL Hit Long/Short)
Performance Metrics
NIFTY Futures (15min): 50%+ win rate with ADX filter OFF
Crypto Markets: Requires extensive backtesting before live deployment
Optimal Timeframes: 15-minute to 1-hour charts (patience required for higher timeframes)
Strategy Logic
Entry Signals:
LONG: EMA 9 crosses above EMA 21 + RSI > 55 + ADX > 20 (if enabled)
SHORT: EMA 9 crosses below EMA 21 + RSI < 45 + ADX > 20 (if enabled)
Exit Signals:
Opposite EMA crossover (auto-closes current position)
Stop loss hit at 2% from entry price (tracks candle wicks)
Technical Indicators:
Fast EMA: 9-period (short-term trend)
Slow EMA: 21-period (primary trend)
RSI: 14-period with 55/45 thresholds (momentum confirmation)
ADX: 14-period with 20 threshold (trend strength filter - optional)
Market-Specific Settings
Traditional Markets (NIFTY, Bank NIFTY, S&P Futures, Options)
Recommended Settings:
ADX Filter: Turn OFF (less choppy, cleaner trends)
Timeframe: 15-minute chart
Win Rate: 50%+ on NIFTY Futures
Why No ADX: Traditional markets have more institutional participation and smoother price action, making ADX unnecessary
Cryptocurrency Markets (BTC, ETH, Altcoins)
Recommended Settings:
ADX Filter: Turn ON (ADX > 20)
Timeframe: 15-minute to 1-hour
Extensive backtesting required before live trading
Why ADX: Crypto markets are highly volatile and prone to false breakouts; ADX filters low-quality chop
Best Practices
✅ Backtest thoroughly on your specific instrument and timeframe
✅ Use larger timeframes (1H, 4H) for higher quality signals and better risk/reward
✅ Adjust RSI thresholds based on market volatility (try 52/48 for more signals, 60/40 for fewer but stronger)
✅ Monitor ADX effectiveness - disable for traditional markets, enable for crypto
✅ Proper position sizing - adjust default_qty_value based on your capital and instrument price
✅ Paper trade first - test for 2-4 weeks before risking real capital
Risk Management
Fixed 2% stop loss per trade (adjustable)
Stop loss tracks candle wicks for accurate execution
Positions auto-reverse on opposite signals (no manual intervention needed)
0.075% commission built into backtest (adjust for your broker)
Customization Options
All parameters are adjustable via inputs:
EMA periods (default: 9/21)
RSI length and thresholds (default: 14-period, 55/45 levels)
ADX length and threshold (default: 14-period, 20 threshold)
Stop loss percentage (default: 2%)
Webhook Automation
This strategy includes six distinct alert messages for automated trading:
"Entry Buy" - Long position opened
"Entry Sell" - Short position opened
"Close Long" - Long position closed on opposite crossover
"Close Short" - Short position closed on opposite crossover
"SL Hit Long" - Long stop loss triggered
"SL Hit Short" - Short stop loss triggered
Compatible with Delta Exchange, Binance Futures, 3Commas, Alertatron, and other webhook platforms.
Important Notes
⚠️ Crypto markets require extensive backtesting - volatility patterns differ significantly from traditional markets
⚠️ Higher timeframes = better results - 15min works but 1H/4H provide cleaner signals
⚠️ ADX toggle is critical - OFF for traditional markets, ON for crypto
⚠️ Not financial advice - always conduct your own research and use proper risk management
⚠️ Past performance ≠ future results - backtest results may not reflect live trading conditions
Disclaimer
This strategy is for educational and informational purposes only. Trading futures and options involves substantial risk of loss. Always backtest thoroughly, start with paper trading, and never risk more than you can afford to lose. The author assumes no responsibility for any trading losses incurred using this strategy.
3-Minute RSI and EMA Crossover Strategy 3-Minute RSI and EMA Crossover Sell Strategy with Exit Conditions and Re-entry
QQQ TimingThis is a trend-following position trading strategy designed for the QQQ and the leveraged ETF QLD (ProShares Ultra QQQ). The primary goal is to capture multi-month holds for maximal profit.
Key Instruments & Performance
The strategy performs best with QLD, which yields far superior results compared to QQQ.
TQQQ (triple-leveraged) results in higher drawdowns and is not the optimal choice.
Important: The system is not intended for use with other indexes, individual stocks, or investments (like crypto or gold), as performance can vary widely.
Buy Signals
The strategy's signals are rooted in the S&P 500 Index (SPX), as testing showed it provides more reliable triggers than using QQQ itself.
Primary Buy Signal (Credit to IBD/Mike Webster): The SPX triggers a buy when its low closes above the 21-day Exponential Moving Average (EMA) for three consecutive days.
Refinement with Downtrend Lines: During corrective or bear periods, results and drawdowns can be significantly improved by incorporating downtrend lines. These lines connect lower highs. The strategy waits for the price to close above a drawn downtrend line before executing a buy. This refinement can modify the primary signal, either by allowing for an earlier entry or, in some cases, completely nullifying a false signal until the trend change proves itself.
Risk Management & Exit Strategy
Initial Buy Risk: A 3.7% stop loss is applied immediately upon the initial entry.
Initial Exit Rule: An exit is required if the QQQ's low drops below the 50-day Simple Moving Average (SMA).
Note: The 3.7% stop often provides protection when the initial buy occurs below the 50-day SMA. However, if QQQ is already trading above its 50-day SMA at the time of the SPX signal (indicating relative strength), historically, it has been better to use the 50-day SMA rule to give the position more room to run.
Trend Exit (Profit-Taking): To stay in a strong trend for the optimal amount of time, the long position is exited when a moving average crossover to the downside is triggered, based around the 107-day Simple Moving Average (SMA).
RastaRasta — Educational Strategy (Pine v5)
Momentum · Smoothing · Trend Study
Overview
The Rasta Strategy is a visual and educational framework designed to help traders study momentum transitions using the interaction between a fast-reacting EMA line and a slower smoothed reference line.
It is not a signal generator or profit system; it’s a learning tool for understanding how smoothing, crossovers, and filters interact under different market conditions.
The script displays:
A primary EMA line (the fast reactive wave).
A Smoothed line (using your chosen smoothing method).
Optional fog zones between them for quick visual context.
Optional DNA rungs connecting both lines to illustrate volatility compression and expansion.
Optional EMA 8 / EMA 21 trend filter to observe higher-time-frame alignment.
Core Idea
The Rasta model focuses on wave interaction. When the fast EMA crosses above the smoothed line, it reflects a shift in short-term momentum relative to background trend pressure. Cross-unders suggest weakening or reversal.
Rather than treating this as a trading “signal,” use it to observe structure, study trend alignment, and test how smoothing type affects reaction speed.
Smoothing Types Explained
The script lets you experiment with multiple smoothing techniques:
Type Description Use Case
SMA (Simple Moving Average) Arithmetic mean of the last n values. Smooth and steady, but slower. Trend-following studies; filters noise on higher time frames.
EMA (Exponential Moving Average) Weights recent data more. Responds faster to new price action. Momentum or reactive strategies; quick shifts and reversals.
RMA (Relative Moving Average) Used internally by RSI; smooths exponentially but slower than EMA. Momentum confirmation; balanced response.
WMA (Weighted Moving Average) Linear weights emphasizing the most recent data strongly. Intraday scalping; crisp but potentially noisy.
None Disables smoothing; uses the EMA line alone. Raw comparison baseline.
Each smoothing method changes how early or late the strategy reacts:
Faster smoothing (EMA/WMA) = more responsive, good for scalping.
Slower smoothing (SMA/RMA) = more stable, good for trend following.
Modes of Study
🔹 Scalper Mode
Use short EMA lengths (e.g., 3–5) and fast smoothing (EMA or WMA).
Focus on 1 min – 15 min charts.
Watch how quick crossovers appear near local tops/bottoms.
Fog and rung compression reveal volatility contraction before bursts.
Goal: study short-term rhythm and liquidity pulses.
🔹 Momentum Mode
Use moderate EMA (5–9) and RMA smoothing.
Ideal for 1 H–4 H charts.
Observe how the fog color aligns with trend shifts.
EMA 8 / 21 filter can act as macro bias; “Enter” labels will appear only in its direction when enabled.
Goal: study sustained motion between pullbacks and acceleration waves.
🔹 Trend-Follower Mode
Use longer EMA (13–21) with SMA smoothing.
Great for daily/weekly charts.
Focus on periods where fog stays unbroken for long stretches — these illustrate clear trend dominance.
Watch rung spacing: tight clusters often precede consolidations; wide rungs signal expanding volatility.
Goal: visualize slow-motion trend transitions and filter whipsaw conditions.
Components
EMA Line (Red): Fast-reacting short-term direction.
Smoothed Line (Yellow): Reference trend baseline.
Fog Zone: Green when EMA > Smoothed (up-momentum), red when below.
DNA Rungs: Thin connectors showing volatility structure.
EMA 8 / 21 Filter (optional):
When enabled, the strategy will only allow Enter events if EMA 8 > EMA 21.
Use this to study higher-trend gating effects.
Educational Applications
Momentum Visualization: Observe how the fast EMA “breathes” around the smoothed baseline.
Trend Transitions: Compare different smoothing types to see how early or late reversals are detected.
Noise Filtering: Experiment with fog opacity and smoothing lengths to understand trade-off between responsiveness and stability.
Risk Concept Simulation: Includes a simple fixed stop-loss parameter (default 13%) for educational demonstrations of position management in the Strategy Tester.
How to Use
Add to Chart → “Strategy.”
Works on any timeframe and instrument.
Adjust Parameters:
Length: base EMA speed.
Smoothing Type: choose SMA, EMA, RMA, or WMA.
Smoothing Length: controls delay and smoothness.
EMA 8 / 21 Filter: toggles trend gating.
Fog & Rungs: visual study options only.
Study Behavior:
Use Strategy Tester → List of Trades for entry/exit context.
Observe how different smoothing types affect early vs. late “Enter” points.
Compare trend periods vs. ranging periods to evaluate efficiency.
Combine with External Tools:
Overlay RSI, MACD, or Volume for deeper correlation analysis.
Use replay mode to visualize crossovers in live sequence.
Interpreting the Labels
Enter: Marks where fast EMA crosses above the smoothed line (or when filter flips positive).
Exit: Marks where fast EMA crosses back below.
These are purely analytical markers — they do not represent trade advice.
Educational Value
The Rasta framework helps learners explore:
Reaction time differences between moving-average algorithms.
Impact of smoothing on signal clarity.
Interaction of local and global trends.
Visualization of volatility contraction (tight DNA rungs) and expansion (wide fog zones).
It’s a sandbox for studying price structure, not a promise of profit.
Disclaimer
This script is provided for educational and research purposes only.
It does not constitute financial advice, trading signals, or performance guarantees. Past market behavior does not predict future outcomes.
Users are encouraged to experiment responsibly, record observations, and develop their own understanding of price behavior.
Author: Michael Culpepper (mikeyc747)
License: Educational / Open for study and modification with credit.
Philosophy:
“Learning the rhythm of the market is more valuable than chasing its profits.” — Rasta
W%R Pullback+EMA Trend [TS_Indie]🔰 Core Concept of the Strategy
The main idea is “Trend-Following with Momentum Pullback.”
This means trading in the direction of the main trend (defined by EMA) while using Williams %R to identify pullback entries (buying the dip or selling the rally) where momentum returns to the trend direction.
📊 Indicators Used
1. EMA Fast – Defines the short-term trend.
2. EMA Slow – Defines the long-term trend (used as a trend filter).
3. Williams %R
• Overbought zone: above -20
• Oversold zone: below -80
⚙️ Entry Rules
🔹 Buy Setup
1. EMA Fast > EMA Slow → Uptrend condition.
2. Williams %R on the previous candle dropped below -80, and on the current candle, it crosses back above -80 → indicates momentum returning to the upside.
3. Current close is above EMA Fast.
4. Entry Buy at the close of the candle where %R crosses above -80.
🎯 Entry, Stop Loss, and Take Profit
1. Entry : At the candle close where the signal occurs.
2. Stop Loss : At the lowest low between the current and previous candles.
3. Take Profit : Calculated based on entry price and stop loss distance multiplied by the Risk/Reward Ratio.
🔹 Sell Setup
1. EMA Fast < EMA Slow → Downtrend condition.
2. Williams %R on the previous candle went above -20, and on the current candle, it crosses back below -20 → indicates renewed selling momentum.
3. Current price is below EMA Fast.
4. Entry Sell at the close of the candle where %R crosses below -20.
🎯 Entry, Stop Loss, and Take Profit
1. Entry : At the candle close where the signal occurs.
2. Stop Loss : At the highest high between the current and previous candles.
3. Take Profit : Calculated based on entry price and stop loss distance multiplied by the Risk/Reward Ratio.
⚙️ Optional Parameters
• Custom Risk/Reward Ratio for Take Profit.
• Option to add ATR buffer to Stop Loss.
• Adjustable EMA Fast period.
• Adjustable EMA Slow period.
• Adjustable Williams %R period.
• Option to enable Long only / Short only positions.
• Customizable Backtest start and end date.
• Customizable trading session time.
⏰ Alert Function
Alerts display:
• Entry price
• Stop Loss price
• Take Profit price
Guys, try adjusting the parameters yourselves!
I’ve been tweaking the settings for several days and managed to get great results on XAU/USD in the 5-minute timeframe.
I think this strategy is quite interesting and could potentially deliver good results on other instruments as well.
⚠️ Disclaimer
This indicator is designed for educational and research purposes only.
It does not guarantee profits and should not be considered financial advice.
Trading in financial markets involves significant risk, including the potential loss of capital.
tradingview_momentum_Hull-Suite-W-FVSO-NO-WeekendMomentum no weekend trades. It uses FVZO and Hull suite.
This strategy has low win rate but successfully catches trends. Works well on ETH in High Time Frame multi-year.
PSAR with ATR Trailing Stop + SMA Filter📈 Strategy Overview: PSAR + 6×ATR Trailing Stop with SMA Filter
This strategy is built around the principle of “Cut the losers, let the winners run” — a disciplined, trend-following approach that combines the Parabolic SAR indicator with dynamic risk management and a Simple Moving Average (SMA) trend filter.
🔍 Strategy Logic
Trend Filter Trades are only taken in the direction of the prevailing trend, defined by a user-selected SMA (default: 100).
✅ Long trades only when price is above the SMA
✅ Short trades only when price is below the SMA
Entry Signal: A trade is triggered when the Parabolic SAR flips to the opposite side of the price bars, signaling a potential trend reversal.
Stop Loss: The stop loss is dynamically set at 6×ATR from the entry price. This adapts to market volatility and is recalculated every bar — effectively acting as a trailing stop.
Exit Logic: There is no fixed take profit. The trade remains open until the trailing stop is hit — allowing winners to run and losers to be cut quickly.
Risk Management: Each trade risks 0.5% of total equity, ensuring consistent position sizing and capital preservation.
📊 Visual Elements
PSAR dots mark trend direction changes
SMA line shows the broader trend filter
Trailing stop crosses (with 50% opacity) indicate the current stop level without cluttering the chart
⚙️ Customizable Inputs
PSAR parameters: Start, Increment, Maximum
ATR length and multiplier
SMA length
Risk percentage per trade
This strategy is ideal for traders who want to stay aligned with the trend, automate disciplined exits, and avoid emotional decision-making. Clean, simple, and powerful.
Wishing you calm and successful trades!
CDC BACKTEST (MACD) FIX AMOUNT $200k per trade This strategy implements an Exponential Moving Average (EMA) Crossover System designed for backtesting and performance evaluation. EMA 12,26 (MACD)
The trading logic is based on the crossover between two EMAs — a short-term EMA (12) and a long-term EMA (26) — which serves as a momentum-based signal for trend identification.
Buy Condition:
A long (buy) position is entered when the 12-period EMA crosses above the 26-period EMA, indicating a potential upward trend or bullish momentum.
Sell Condition:
A position is closed, or a short (sell) position is opened, when the 12-period EMA crosses below the 26-period EMA, signaling a potential downward trend or bearish momentum.
Position Sizing:
Each trade with a fixed position size of 200,000 USD (default), while the starting account balance is set at 400,000 (USD).
Both the fixed trade amount and the initial balance are user-adjustable parameters, allowing flexibility for different risk preferences and portfolio sizes.
HEK Dinamik Fiyat Kanalı Stratejisi v1HEK Dynamic Price Channel Strategy
Concept
The HEK Dynamic Price Channel provides a channel structure that expands and contracts according to price momentum and time-based equilibrium.
Unlike fixed-band systems, it evaluates the interaction between price and its balance line through an adaptive channel width that dynamically adjusts to changing market conditions.
How It Works
When the price reacts to the midline, the channel bands automatically reposition themselves.
Touching the upper band indicates a strengthening trend, while touching the lower band signals weakening momentum.
This adaptive mechanism helps filter out false signals during sudden directional changes, enhancing overall signal quality.
Advantages
✅ Maintains trend continuity while avoiding overtrading.
✅ Automatically adapts to changing volatility conditions.
✅ Detects early signals of short- and mid-term trend reversals.
Applications
Directional confirmation in spot and futures markets.
A supporting tool in channel breakout strategies.
Identifying price consolidation and equilibrium zones.
Note
This strategy is intended for educational and research purposes only.
It should not be considered financial advice. Always consult a professional financial advisor before making investment decisions.
© HEK — Adaptive Channel Approach on Dynamic Market Structures
6 gün önce
Sürüm Notları
HEK Dynamic Price Channel Strategy
Concept
The HEK Dynamic Price Channel provides a channel structure that expands and contracts according to price momentum and time-based equilibrium.
Unlike fixed-band systems, it evaluates the interaction between price and its balance line through an adaptive channel width that dynamically adjusts to changing market conditions.
How It Works
When the price reacts to the midline, the channel bands automatically reposition themselves.
Touching the upper band indicates a strengthening trend, while touching the lower band signals weakening momentum.
This adaptive mechanism helps filter out false signals during sudden directional changes, enhancing overall signal quality.
Advantages
✅ Maintains trend continuity while avoiding overtrading.
✅ Automatically adapts to changing volatility conditions.
✅ Detects early signals of short- and mid-term trend reversals.
Applications
Directional confirmation in spot and futures markets.
A supporting tool in channel breakout strategies.
Identifying price consolidation and equilibrium zones.
Note
This strategy is intended for educational and research purposes only.
It should not be considered financial advice. Always consult a professional financial advisor before making investment decisions.
© HEK — Adaptive Channel Approach on Dynamic Market Structures
WIN1! • Crossing EMAs• (By Mesquita, v7)Moving average crossover strategy for intraday movements, especially in the continuous index (WIN1!) on the Brazilian stock exchange B³. The strategy is customizable for time windows, has a filter for trades only above the long-term average, whether only long, only short, or both, with or without stop loss.
MA strategyBuy / sell on MA cross. Use ATR or Swing for stop
Option for moving stop after second SwL / SwH
Knock yourself out modifying.
Trend Pullback System```{"variant":"standard","id":"36492","title":"Trend Pullback System Description"}
Trend Pullback System is a price-action trend continuation model that looks to enter on pullbacks, not breakouts. It’s designed to find high-quality long/short entries inside an already established trend, place the stop at meaningful structure, trail that stop as structure evolves, and warn you when the trade thesis is no longer valid.
Developed by: Mohammed Bedaiwi
---------------------------------
HOW IT WORKS
---------------------------------
1. Trend Detection
• The strategy defines overall bias using moving averages.
• Bullish environment (“uptrend”): price above the slower MA, fast MA above slow MA, and the slow MA is sloping up.
• Bearish environment (“downtrend”): price below the slower MA, fast MA below slow MA, and the slow MA is sloping down.
This prevents trading against chop and focuses on continuation moves in the dominant direction.
2. Pullback + Re-entry Logic
• The script waits for price to pull back into structure (support in an uptrend, resistance in a downtrend), and then push back in the direction of the main trend.
• That “push back” is the setup trigger. We don’t chase the first breakout candle — we buy/sell the retest + resume.
3. Structural Levels (“Diamonds”)
• Green diamond (below bar): bullish pivot low formed while the trend is bullish. This marks defended support.
- Use it as a re-entry zone for longs.
- Use it to trail a stop higher when you’re already long.
- Shorts can take profit here because buyers stepped in.
• Red diamond (above bar): bearish pivot high formed while the trend is bearish. This marks defended resistance.
- Use it as a re-entry zone for shorts.
- Use it to trail a stop lower when you’re already short.
- Longs can take profit here because sellers stepped in.
4. Entry Signals
• BUY arrow (green triangle up under the candle, text like “BUY” / “BUY Zone”):
- LongSetup is true.
- Trend is bullish or turning bullish.
- Price just bounced off recent defended support (green diamond) and reclaimed short-term momentum.
Meaning: enter long here or cover/exit shorts.
• SELL arrow (red triangle down above the candle):
- ShortSetup is true.
- Trend is bearish or turning bearish.
- Price just rolled down from defended resistance (red diamond) and lost short-term momentum.
Meaning: enter short here or take profit on longs.
These are the primary trade entries. They are meant to be actionable.
5. Weak Setups (“W” in yellow)
• Yellow triangle with “W”:
- A possible long/short idea is trying to form, BUT the higher-timeframe confirmation is not fully there yet.
- Think of it as early pressure / early caution, not a full signal.
• You usually watch these areas rather than jumping in immediately.
6. Exit Warning (orange “EXIT” label above a bar)
• The strategy will raise an EXIT marker when you’re in a trade and the *opposite* side just produced a confirmed setup.
- You’re short and a valid longSetup appears → EXIT.
- You’re long and a valid shortSetup appears → EXIT.
• This is basically: “Close or reduce — the other side just took control.”
• It’s not just a trailing stop hit; it’s a regime flip warning.
7. Stop, Target, and Trailing
• On every new setup, the script records:
- Initial stop: recent swing beyond the defended level (below support for longs, above resistance for shorts).
- Initial target: recent opposing swing.
• While you’re in position, if new confirming diamonds print in your favor, the stop can trail toward the new defended level.
• This creates structure-based risk management (not just fixed % or ATR).
8. Reference Levels
• The strategy also plots prior higher-timeframe closes (last week’s close, last month’s close, last year’s close). These can behave as magnets or stall points.
• They’re helpful for take-profit timing and for reading “are we trading above or below last month’s close?”
9. Momentum Panel (hidden by default)
• Internally, the script calculates an SMI-style momentum oscillator with overbought/oversold zones.
• This is optional visual confirmation and does not drive the core entry/exit logic.
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WHAT A TRADE LOOKS LIKE IN REAL PRICE ACTION
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Early warning
• Yellow W + red diamonds + red down arrows = “This is getting weak. Short setups are here.”
• You may also see something like “My Short Entry Id.” That’s where the short side actually engages.
Bearish follow-through, then exhaustion
• Price bleeds down.
• Then the orange EXIT appears.
→ Translation: “If you’re still short, close it. Buyers are stepping in hard. Risk of reversal is now high.”
Regime flip
• Right after EXIT, multiple green BUY arrows fire together (“BUY”, “BUYZone”).
• That’s the true long trigger.
→ This is where you either enter long or flip from short to long.
Expansion leg
• After that flip, price rips up for multiple candles / days / weeks.
• While it runs:
- Green diamonds appear under pullbacks → “dip buy zones / trail stop up here.”
- More BUY arrows show on minor pullbacks → continuation long / scale adds.
Distribution / topping
• Later, you start seeing new yellow W triangles again near local highs. That’s your “careful, this might be topping” warning.
• You finally get a hard red candle, and green diamonds stop stacking.
→ That’s where you tighten risk, scale out, or assume the move is mature.
In plain terms, the model is doing the following for you:
• It puts you short during weakness.
• It tells you when to get OUT of the short.
• It flips you long right as control changes.
• It gives you a structure-based trail the whole way up.
• It warns you again when momentum at the top starts cracking.
That is exactly how the logic was designed.
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QUICK INTERPRETATION CHEAT SHEET
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🔻 Red triangle + “Short Entry” near a red diamond
→ Short entry zone (or take profit on a long).
🟥 Red diamond above bar
→ Sellers defended here. Treat it as resistance. Good place to trail short stops just above that level. Avoid chasing longs straight into it.
🟨 Yellow W
→ Attention only. Early pressure / possible turn. Not fully confirmed.
🟧 EXIT (orange label)
→ The opposite side just printed a real setup. Close the old idea (cover shorts if you’re short, exit longs if you’re long). Thesis invalid.
🟩 Burst of green BUY triangles after EXIT
→ Long entry. Also a “cover shorts now” alert. This is the core money entry in bullish reversals.
💎 Green diamond below bar
→ Bulls defended that level. Good for trailing your long stop up, and good “buy the dip in trend” locations.
📈 Blue / teal MAs stacked and rising
→ Confirmed bullish structure. You’re in trend continuation mode, so dips are opportunities, not automatic exits.
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COLOR / SHAPE KEY
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• Green triangle up (“BUY”, “BUY Zone”):
Long entry / cover shorts / continuation long trigger.
• Red triangle down:
Short entry / take profit on longs / continuation short trigger.
• Orange “EXIT” label:
Opposite side just fired a real setup. The previous trade thesis is now invalid.
• Green diamond below price:
Bullish defended support in an uptrend. Use for dip buys, trailing stops on longs, and objective cover zones for shorts.
• Red diamond above price:
Bearish defended resistance in a downtrend. Use for re-entry shorts, trailing stops on shorts, and objective scale-out zones for longs.
• Yellow “W”:
Weak / early potential setup. Watch it, don’t blindly trust it.
• Moving average bands (fast MA, slow MA, Hull MA):
When stacked and rising, bullish control. When stacked and falling, bearish control.
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INTENT
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This system is built to:
• Trade with momentum, not against it.
• Enter on pullbacks into proven structure, not chase stretched breakouts.
• Automate stop/target logic around actual defended swing levels.
• Warn you when the other side takes over so you don’t give back gains.
Typical usage:
1. In an uptrend, wait for price to pull back, print a green diamond (support proved), then take the first BUY arrow that fires.
2. In a downtrend, wait for a bounce into resistance, print a red diamond (sellers proved), then take the first SELL arrow that fires.
3. Respect EXIT when it appears — that’s the model saying “this trade is done.”
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DISCLAIMER
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This script is for educational and research purposes only. It is not financial advice, investment advice, or a recommendation to buy or sell any security, cryptoasset, or derivative. Markets carry risk. Past performance does not guarantee future results. You are fully responsible for your own decisions, position sizing, risk management, and compliance with all applicable laws and regulations.
Iriza4 -DAX EMA+HULL+ADX TP40 SL205 MIN SKALP. Additional filters improve accuracy: the strategy blocks trades after too many consecutive bullish or bearish candles (streak filter) and ignores signals when price is too far from the EMA (measured by ATR distance).
Each position uses a fixed risk-to-reward ratio of 1 : 2 with clear stop-loss and take-profit targets, without partial exits or breakevens. The goal is to identify clean pullbacks inside strong trends and filter out late or exhausted entries






















