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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.
Pine Script®策略
由kulkarniabhishek38提供
2
SP500 Session Gap Fade StrategySummary in one paragraph SPX Session Gap Fade is an intraday gap fade strategy for index futures, designed around regular cash sessions on five minute charts. It helps you participate only when there is a full overnight or pre session gap and a valid intraday session window, instead of trading every open. The original part is the gap distance engine which anchors both stop and optional target to the previous session reference close at a configurable flat time, so every trade’s risk scales with the actual gap size rather than a fixed tick stop. Scope and intent • Markets. Primarily index futures such as ES, NQ, YM, and liquid index CFDs that exhibit overnight gaps and regular cash hours. • Timeframes. Intraday timeframes from one minute to fifteen minutes. Default usage is five minute bars. • Default demo used in the publication. Symbol CME:ES1! on a five minute chart. • Purpose. Provide a simple, transparent way to trade opening gaps with a session anchored risk model and forced flat exit so you are not holding into the last part of the session. • Limits. This is a strategy. Orders are simulated on standard candles only. Originality and usefulness • Unique concept or fusion. The core novelty is the combination of a strict “full gap” entry condition with a session anchored reference close and a gap distance based TP and SL engine. The stop and optional target are symmetric multiples of the actual gap distance from the previous session’s flat close, rather than fixed ticks. • Failure mode it addresses. Fixed sized stops do not scale when gaps are unusually small or unusually large, which can either under risk or over risk the account. The session flat logic also reduces the chance of holding residual positions into late session liquidity and news. • Testability. All key pieces are explicit in the Inputs: session window, minutes before session end, whether to use gap exits, whether TP or SL are active, and whether to allow candle based closes and forced flat. You can toggle each component and see how it changes entries and exits. • Portable yardstick. The main unit is the absolute price gap between the entry bar open and the previous session reference close. tp_mult and sl_mult are multiples of that gap, which makes the risk model portable across contracts and volatility regimes. Method overview in plain language The strategy first defines a trading session using exchange time, for example 08:30 to 15:30 for ES day hours. It also defines a “flat” time a fixed number of minutes before session end. At the flat bar, any open position is closed and the bar’s close price is stored as the reference close for the next session. Inside the session, the strategy looks for a full gap bar relative to the prior bar: a gap down where today’s high is below yesterday’s low, or a gap up where today’s low is above yesterday’s high. A full gap down generates a long entry; a full gap up generates a short entry. If the gap risk engine is enabled and a valid reference close exists, the strategy measures the distance between the entry bar open and that reference close. It then sets a stop and optional target as configurable multiples of that gap distance and manages them with strategy.exit. Additional exits can be triggered by a candle color flip or by the forced flat time. Base measures • Range basis. The main unit is the absolute difference between the current entry bar open and the stored reference close from the previous session flat bar. That value is used as a “gap unit” and scaled by tp_mult and sl_mult to build the target and stop. Components • Component one: Gap Direction. Detects full gap up or full gap down by comparing the current high and low to the previous bar’s high and low. Gap down signals a long fade, gap up signals a short fade. There is no smoothing; it is a strict structural condition. • Component two: Session Window. Only allows entries when the current time is within the configured session window. It also defines a flat time before the session end where positions are forced flat and the reference close is updated. • Component three: Gap Distance Risk Engine. Computes the absolute distance between the entry open and the stored reference close. The stop and optional target are placed as entry ± gap_distance × multiplier so that risk scales with gap size. • Optional component: Candle Exit. If enabled, a bullish bar closes short positions and a bearish bar closes long positions, which can shorten holding time when price reverses quickly inside the session. • Session windows. Session logic uses the exchange time of the chart symbol. When changing symbols or venues, verify that the session time string still matches the new instrument’s cash hours. Fusion rule All gates are hard conditions rather than weighted scores. A trade can only open if the session window is active and the full gap condition is true. The gap distance engine only activates if a valid reference close exists and use_gap_risk is on. TP and SL are controlled by separate booleans so you can use SL only, TP only, or both. Long and short are symmetric by construction: long trades fade full gap downs, short trades fade full gap ups with mirrored TP and SL logic. Signal rule • Long entry. Inside the active session, when the current bar shows a full gap down relative to the previous bar (current high below prior low), the strategy opens a long position. If the gap risk engine is active, it places a gap based stop below the entry and an optional target above it. • Short entry. Inside the active session, when the current bar shows a full gap up relative to the previous bar (current low above prior high), the strategy opens a short position. If the gap risk engine is active, it places a gap based stop above the entry and an optional target below it. • Forced flat. At the configured flat time before session end, any open position is closed and the close price of that bar becomes the new reference close for the following session. • Candle based exit. If enabled, a bearish bar closes longs, and a bullish bar closes shorts, regardless of where TP or SL sit, as long as a position is open. What you will see on the chart • Markers on entry bars. Standard strategy entry markers labeled “long” and “short” on the gap bars where trades open. • Exit markers. Standard exit markers on bars where either the gap stop or target are hit, or where a candle exit or forced flat close occurs. Exit IDs “long_gap” and “short_gap” label gap based exits. • Reference levels. Horizontal lines for the current long TP, long SL, short TP, and short SL while a position is open and the gap engine is enabled. They update when a new trade opens and disappear when flat. • Session background. This version does not add background shading for the session; session logic runs internally based on time. • No on chart table. All decisions are visible through orders and exit levels. Use the Strategy Tester for performance metrics. Inputs with guidance Session Settings • Trading session (sess). Session window in exchange time. Typical value uses the regular cash session for each contract, for example “0830-1530” for ES. Adjust if your broker or symbol uses different hours. • Minutes before session end to force exit (flat_before_min). Minutes before the session end where positions are forced flat and the reference close is stored. Typical range is 15 to 120. Raising it closes trades earlier in the day; lowering it allows trades later in the session. Gap Risk • Enable gap based TP/SL (use_gap_risk). Master switch for the gap distance exit engine. Turning it off keeps entries and forced flat logic but removes automatic TP and SL placement. • Use TP limit from gap (use_gap_tp). Enables gap based profit targets. Typical values are true for structured exits or false if you want to manage exits manually and only keep a stop. • Use SL stop from gap (use_gap_sl). Enables gap based stop losses. This should normally remain true so that each trade has a defined initial risk in ticks. • TP multiplier of gap distance (tp_mult). Multiplier applied to the gap distance for the target. Typical range is 0.5 to 2.0. Raising it places the target further away and reduces hit frequency. • SL multiplier of gap distance (sl_mult). Multiplier applied to the gap distance for the stop. Typical range is 0.5 to 2.0. Raising it widens the stop and increases risk per trade; lowering it tightens the stop and may increase the number of small losses. Exit Controls • Exit with candle logic (use_candle_exit). If true, closes shorts on bullish candles and longs on bearish candles. Useful when you want to react to intraday reversal bars even if TP or SL have not been reached. • Force flat before session end (use_forced_flat). If true, guarantees you are flat by the configured flat time and updates the reference close. Turn this off only if you understand the impact on overnight risk. Filters There is no separate trend or volatility filter in this version. All trades depend on the presence of a full gap bar inside the session. If you need extra filtering such as ATR, volume, or higher timeframe bias, they should be added explicitly and documented in your own fork. Usage recipes Intraday conservative gap fade • Timeframe. Five minute chart on ES regular session. • Gap risk. use_gap_risk = true, use_gap_tp = true, use_gap_sl = true. • Multipliers. tp_mult around 0.7 to 1.0 and sl_mult around 1.0. • Exits. use_candle_exit = false, use_forced_flat = true. Focus on the structured TP and SL around the gap. Intraday aggressive gap fade • Timeframe. Five minute chart. • Gap risk. use_gap_risk = true, use_gap_tp = false, use_gap_sl = true. • Multipliers. sl_mult around 0.7 to 1.0. • Exits. use_candle_exit = true, use_forced_flat = true. Entries fade full gaps, stops are tight, and candle color flips flatten trades early. Higher timeframe gap tests • Timeframe. Fifteen minute or sixty minute charts on instruments with regular gaps. • Gap risk. Keep use_gap_risk = true. Consider slightly higher sl_mult if gaps are structurally wider on the higher timeframe. • Note. Expect fewer trades and be careful with sample size; multi year data is recommended. Properties visible in this publication • On average our risk for each position over the last 200 trades is 0.4% with a max intraday loss of 1.5% of the total equity in this case of 100k $ with 1 contract ES. For other assets, recalculations and customizations has to be applied. • Initial capital. 100 000. • Base currency. USD. • Default order size method. Fixed with size 1 contract. • Pyramiding. 0. • Commission. Flat 2 USD per order in the Strategy Tester Properties. (2$ buying + 2$selling) • Slippage. One tick in the Strategy Tester Properties. • Process orders on close. ON. Realism and responsible publication • No performance claims are made. Past results do not guarantee future outcomes. • Costs use a realistic flat commission and one tick of slippage per trade for ES class futures. • Default sizing with one contract on a 100 000 reference account targets modest per trade risk. In practice, extreme slippage or gap through events can exceed this, so treat the one and a half percent risk target as a design goal, not a guarantee. • All orders are simulated on standard candles. Shapes can move while a bar is forming and settle on bar close. Honest limitations and failure modes • Economic releases, thin liquidity, and limit conditions can break the assumptions behind the simple gap model and lead to slippage or skipped fills. • Symbols with very frequent or very large gaps may require adjusted multipliers or alternative risk handling, especially in high volatility regimes. • Very quiet periods without clean gaps will produce few or no trades. This is expected behavior, not a bug. • Session windows follow the exchange time of the chart. Always confirm that the configured session matches the symbol. • When both the stop and target lie inside the same bar’s range, the TradingView engine decides which is hit first based on its internal intrabar assumptions. Without bar magnifier, tie handling is approximate. Legal Education and research only. This strategy is not investment advice. You remain responsible for all trading decisions. Always test on historical data and in simulation with realistic costs before considering any live use.
Pine Script®策略
由exlux提供
2
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.
Pine Script®策略
由ravi_matrix提供
27
MOMO – Imbalance Trend (SIMPLE BUY/SELL)MOMO – Imbalance Trend (SIMPLE BUY/SELL) This strategy combines trend breaks, imbalance detection, and first-tap supply/demand entries to create a clean and disciplined trading model. It automatically highlights imbalance candles, draws fresh zones, and waits for the first retest to deliver precise BUY and SELL signals. Performance On optimized settings, this strategy shows an estimated 57%–70% win-rate, depending on the asset and timeframe. Actual performance may vary, but the model is built for consistency, discipline, and improved decision-making. How it works Detects trend structure shifts (BOS / Break of Trend) Identifies displacement (imbalance) candles Creates supply and demand zones from imbalance origin Waits for first tap only (no second chances) Confirms direction using trend logic Generates clean BUY/SELL arrows Automatic SL/TP based on user settings Features Clean BUY/SELL markers Auto-drawn supply & demand zones Trend break markers Imbalance tags Smart first-tap confirmation Customizable stop loss & take profit Works on crypto, gold, forex, indices Best on M5–H1 for day trading Note This strategy is designed for day traders who want clarity, structure, and zero emotional trading. Use it with discipline — and it will serve you well. Good luck, soldier.
Pine Script®策略
由mohamed030402提供
3
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.
Pine Script®策略
由asefzxizexvsadf提供
GMH : Tech Bubble Good Morning Holding Simulating How to Ride the Bubble — and Jump Out Before the Crash Be careful! Most simulation results show that this strategy sometimes underperforms a simple buy-and-hold, because it gives away positions during deep retracements and buys back at higher thresholds. Humans often struggle with cutting losses. When the pain becomes too much, they lose the confidence needed to execute even a reasonable strategy. But in terms of mentality, this approach reduces long-term portfolio volatility. It helps investors feel more at peace, especially during real market crashes like the tech bubble in 2021. How to use : Select TimeFrame 4HR on trading view
Pine Script®策略
由gmhfund提供
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. ──────────────────────── 0. Legal / risk disclaimer ──────────────────────── • 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. ──────────────────────── 1. About default settings and risk (very important) ──────────────────────── 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. ──────────────────────── 2. What this strategy tries to do (conceptual overview) ──────────────────────── 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. ──────────────────────── 3. Components and how they work together ──────────────────────── (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. ──────────────────────── 4. Entry & Exit logic (high level) ──────────────────────── 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. ──────────────────────── 5. Recommended backtest configuration (to avoid misleading results) ──────────────────────── 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. ──────────────────────── 5a. About low trade count and rare signals ──────────────────────── 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. ──────────────────────── 6. How to use this strategy (step-by-step) ──────────────────────── 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. ──────────────────────── 7. Originality and usefulness (why this is more than a mashup) ──────────────────────── 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. ──────────────────────── 8. Limitations and good practices ──────────────────────── • 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. ──────────────────────── 9. Licensing and credits ──────────────────────── • 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. ──────────────────────── 10. No payments / no vendor pitch ──────────────────────── • 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. ──────────────────────── 11. Example backtest settings used in screenshots ──────────────────────── 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.
Pine Script®策略
由jokiniemi提供
Stochastic + Bollinger Bands Multi-Timeframe StrategyThis strategy fuses the Stochastic Oscillator from the 4-hour timeframe with Bollinger Bands from the 1-hour timeframe, operating on a 10-hour chart to capture a unique volatility rhythm and temporal alignment discovered through observational alpha. By blending momentum confirmation from the higher timeframe with short-term volatility extremes, the strategy leverages what some traders refer to as “rotating volatility” — a phenomenon where multi-timeframe oscillations sync to reveal hidden trade opportunities. 🧠 Strategy Logic ✅ Long Entry Condition: Stochastic on the 4H timeframe: %K crosses above %D Both %K and %D are below 20 (oversold zone) Bollinger Bands on the 1H timeframe: Price crosses above the lower Bollinger Band, indicating a potential reversal → A long trade is opened when both momentum recovery and volatility reversion align. ✅ Long Exit Condition: Stochastic on the 4H: %K crosses below %D Both %K and %D are above 80 (overbought zone) Bollinger Bands on the 1H: Price reaches or exceeds the upper Bollinger Band, suggesting exhaustion → The long trade is closed when either signal suggests a potential reversal or overextension. 🧬 Temporal Structure & Alpha This strategy is deployed on a 10-hour chart — a non-standard timeframe that may align more effectively with multi-timeframe mean reversion dynamics. This subtle adjustment exploits what some traders identify as “temporal drift” — the desynchronization of volatility across timeframes that creates hidden rhythm in price action. → For example, Stochastic on 4H (lookback 17) and Bollinger Bands on 1H (lookback 20) may periodically sync around 10H intervals, offering unique alpha windows. 📊 Indicator Components 🔹 Stochastic Oscillator (4H, Length 17) Detects momentum reversals using %K and %D crossovers Helps define overbought/oversold zones from a mid-term view 🔹 Bollinger Bands (1H, Length 20, ±2 StdDev) Measures price volatility using standard deviation around a moving average Entry occurs near lower band (support), exits near upper band (resistance) 🔹 Multi-Timeframe Logic Uses request.security() to safely reference 4H and 1H indicators from a 10H chart Avoids repainting by using closed higher-timeframe candles only 📈 Visualization A plot selector input allows toggling between: Stochastic Plot (%K & %D, with overbought/oversold levels) Bollinger Bands Plot (Upper, Basis, Lower from 1H data) This helps users visually confirm entry/exit triggers in real time. 🛠 Customization Fully configurable Stochastic and BB settings Timeframes are independently adjustable Strategy settings like position sizing, slippage, and commission are editable ⚠️ Disclaimer This strategy is intended for educational and informational purposes only. It does not constitute financial advice or a recommendation to buy or sell any asset. Market conditions vary, and past performance does not guarantee future results. Always test any trading strategy in a simulated environment and consult a licensed financial advisor before making real-world investment decisions.
Pine Script®策略
由RWCS_LTD提供
Quasimodo Pattern Strategy Back Test [TradingFinder] QM Trading🔵 Introduction The QM pattern, also known as the Quasimodo pattern, is one of the popular patterns in price action, and it is often used by technical analysts. The QM pattern is used to identify trend reversals and provides a very good risk-to-reward ratio. One of the advantages of the QM pattern is its high frequency and visibility in charts. Additionally, due to its strength, it is highly profitable, and as mentioned, its risk-to-reward ratio is very good. The QM pattern is highly popular among traders in supply and demand, and traders also use this pattern. The Price Action QM pattern, like other Price Action patterns, has two types: Bullish QM and Bearish QM patterns. To identify this pattern, you need to be familiar with its types to recognize it. 🔵 Identifying the QM Pattern 🟣 Bullish QM In the bullish QM pattern, as you can see in the image below, an LL and HH are formed. As you can see, the neckline is marked as a dashed line. When the price reaches this range, it will start its upward movement. 🟣 Bearish QM The Price Action QM pattern also has a bearish pattern. As you can see in the image below, initially, an HH and LL are formed. The neckline in this image is the dashed line, and when the LL is formed, the price reaches this neckline. However, it cannot pass it, and the downward trend resumes. 🔵 How to Use The Quasimodo pattern is one of the clearest structures used to identify market reversals. It is built around the concept of a structural break followed by a pullback into an area of trapped liquidity. Instead of relying on lagging indicators, this pattern focuses purely on price action and how the market reacts after exhausting one side of liquidity. When understood correctly, it provides traders with precise entry points at the transition between trend phases. 🟣 Bullish Quasimodo A bullish Quasimodo forms after a clear downtrend when sellers start losing control. The market continues to make lower lows until a sudden higher high appears, signaling that buyers are entering with strength. Price then pulls back to retest the previous low, creating what is known as the Quasimodo low. This area often becomes the final trap for sellers before the market shifts upward. A visible rejection or displacement from this zone confirms bullish momentum. Traders usually place entries near this level, stops below the low, and targets at previous highs or the next resistance zone. Combining the setup with demand zones or Fair Value Gaps increases its accuracy. 🟣 Bearish Quasimodo A bearish Quasimodo forms near the top of an uptrend when buyers begin to lose strength. The market continues to make higher highs until a sudden lower low breaks the bullish structure, showing that selling pressure is entering the market. Price then retraces upward to retest the previous high, forming the Quasimodo high, where breakout buyers are often trapped. Once rejection appears at this level, it indicates a likely reversal. Traders can enter short near this area, with stop-losses placed above the high and targets near the next support or previous lows. The setup gains more reliability when aligned with supply zones, SMT divergence, or bearish Fair Value Gaps. 🔵 Setting Pivot Period : You can use this parameter to use your desired period to identify the QM pattern. By default, this parameter is set to the number 5. Take Profit Mode : You can choose your desired Take Profit in three ways. Based on the logic of the QM strategy, you can select two Take Profit levels, TP1 and TP2. You can also choose your take profit based on the Reward to Risk ratio. You must enter your desired R/R in the Reward to Risk Ratio parameter. Stop Loss Refine : The loss limit of the QM strategy is based on its logic on the Head pattern. You can refine it using the ATR Refine option to prevent Stop Hunt. You can enter your desired coefficient in the Stop Loss ATR Adjustment Coefficient parameter. Reward to Risk Ratio : If you set Take Profit Mode to R/R, you must enter your desired R/R here. For example, if your loss limit is 10 pips and you set R/R to 2, your take profit will be reached when the price is 20 pips away from your entry point. Stop Loss ATR Adjustment Coefficient : If you set Stop Loss Refine to ATR Refine, you must adjust your loss limit coefficient here. For example, if your buy position's loss limit is at the price of 1000, and your ATR is 10, if you set Stop Loss ATR Adjustment Coefficient to 2, your loss limit will be at the price of 980. Entry Level Validity : Determines how long the Entry level remains valid. The higher the level, the longer the entry level will remain valid. By default it is 2 and it can be set between 2 and 15. 🔵 Results The following examples show the backtest results of the Quasimodo (QM) strategy in action. Each image is based on specific settings for the symbol, timeframe, and input parameters, illustrating how the QM logic can generate signals under different market conditions. The detailed configuration for each backtest is also displayed on the image. ⚠ Important Note : Even with identical settings and the same symbol, results may vary slightly across different brokers due to data feed variations and pricing differences. Default Properties of Backtests : OANDA:XAUUSD | TimeFrame: 5min | Duration: 1 Year : BINANCE:BTCUSD | TimeFrame: 5min | Duration: 1 Year : CAPITALCOM:US30 | TimeFrame: 5min | Duration: 1 Year : NASDAQ:QQQ | TimeFrame: 5min | Duration: 5 Year : OANDA:EURUSD | TimeFrame: 5min | Duration: 5 Year : PEPPERSTONE:US500 | TimeFrame: 5min | Duration: 5 Year :
Pine Script®策略
由TFlab提供
18
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.
Pine Script®策略
由varuns_back提供
5
週一普跌策略 Monday shit Strategy Strategy Description / 策略敘述 EN This strategy takes a short position at the start of each Monday, based on the hypothesis that cryptocurrency markets tend to experience post-weekend risk-off behavior. The system enters a full-equity short position at the Tokyo open (Taipei 08:00), aiming to capture Monday downside pressure resulting from accumulated weekend information and macro sentiment adjustments when traditional financial markets reopen. Risk management uses fixed percentage take-profit and stop-loss levels, emphasizing asymmetric reward-to-risk (large occasional gains, small frequent losses). The model reflects the increasing alignment between crypto price behavior and traditional financial market cycles. ZH-TW 本策略於每週一開盤時做空，基於假設加密資產在週末後具有風險釋放與補跌傾向。 系統會在台北時間早上 08:00 以全倉做空，目標捕捉因週末累積消息與傳統金融市場重新開盤所造成的下跌壓力。 風控採固定止盈、止損百分比，強調高報酬／低風險的不對稱結構（小虧多次、偶爾大賺）。 此模型反映加密貨幣市場行為與華爾街週期愈趨一致的市場現象。
Pine Script®策略
由crypto_two_face提供
FVG Session Break Strategy with ATR RR🧠 FVG Session Break Strategy with ATR RR — Timezone-Aware, Session-Savvy, and Risk-Calibrated This strategy captures high-probability reversals and continuations by combining Fair Value Gap (FVG) imbalances with session-based breakout logic and ATR-calibrated risk management. It’s designed for traders who want to exploit structural inefficiencies during key market sessions — with precision and portability across global exchanges. 🔍 Core Logic: Fair Value Gap Detection: Identifies bullish and bearish FVGs using a 3-bar displacement pattern. Session Breakout Engine: Tracks session highs and lows (Asian, London, NY) and triggers trades only when price breaks these levels — ensuring trades occur at meaningful inflection points. ATR-Based RR Control: Dynamically sizes stop-loss and take-profit levels using ATR × multiplier, maintaining consistent risk across volatility regimes. 🌐 Timezone-Aware Session Logic: Session boundaries are defined in UTC-5 (e.g., NY: 0930–1600) but automatically converted to the exchange’s local timezone using timestamp("Etc/GMT+5", ...). This ensures: Accurate session detection across all markets and assets No manual timezone adjustments needed Robust performance on crypto, forex, and global equities 📈 Visuals: Session highs and lows plotted in orange Bullish and bearish FVGs marked with green and red triangles Strategy entries and exits shown on chart with full RR logic This strategy is ideal for traders who want to combine structural edge with session context and disciplined risk.
Pine Script®策略
由slopip提供
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).
Pine Script®策略
由market_quester提供
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
Pine Script®策略
由mikeyc747提供