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Recherche dans les scripts pour "ema"

EMA RSI Strategy Simple strategy ============= If the last two closes are in ascending order, the rsi is below 50 and ascending, and the current candle is above 200 ema, then LONG. If the last two closes are in descending order, the rsi is above 50 and descending, and the current candle is below 200 ema, then SHORT. LONG Exit strategy: ATR: Last 14 day Lowest: The lowest value of the last 14 candles Limit points = (Trade Price - Lowest + ATR) * 100000 trail_points : Limit/2 trail_offset = Limit/2 SHORT Exit strategy: ATR: Last 14 day Highest: The higher value of the last 14 candles Limit points = (Trade Price - Highest + ATR) * 100000 trail_points : Limit/2 trail_offset = Limit/2 Backtest results for the AUDUSD pair gave positive results over the last three months. I am testing this strategy using a python bot in a real environment this week and will update the results at the end of the week. Disclaimer This is not financial advice. You should seek independent advice to check how the strategy information relates to your unique circumstances. We are not liable for any loss caused, whether due to negligence or otherwise arising from the use of, or reliance on, the information provided directly or indirectly by this strategy.
Stratégie Pine Script®
par anjanakap
EMA StrategyThis is a simple EMA cross strategy. This script was published by CaptJava. I added in the ability to check off a box and allow shorting, the ability to select a back testing date range and also the ability to enter the buy message and sell message in the properties.  You then create the webhook alert and put only this in the message: {{strategy.order.alert_message}} That will pull in your alert message dynamically. I may add more features to this over time.
Stratégie Pine Script®
par REV0LUTI0N
2
EMA EnvelopeThis is an attempt to convert gunbot's SG strategy into a proper TradingView strategy. The problem is that SG Sell Level relies on % above purchase price, which we don't actually know in TradingView. So we could try to get the average of the next bar or something, which maybe this is what the Slippage setting is? I'm not sure. Anyways, using % above EMA does actually work as a strategy a bit. It's nothing like Turtle Rules by tmr0 though! Will keep working on this gradually; feedback greatly appreciated!
Stratégie Pine Script®
par vosechu
2
Triple EMA Crossover StrategyTriple EMA Crossover Strategy Overview The Triple EMA Crossover Strategy is a trend-following trading system that utilizes three Exponential Moving Averages (EMAs) to identify potential entry and exit points in the market. This strategy is based on the principle that when shorter-term prices cross above longer-term prices, it can indicate a bullish trend, and conversely when they cross below, it can signal a bearish trend. Components Exponential Moving Averages (EMAs): Short EMA: A fast-moving average that reacts quickly to price changes (commonly set to 9 periods). Medium EMA: A medium-term average that smooths out price data and helps confirm trends (commonly set to 21 periods). Long EMA: A slow-moving average that helps identify the overall trend direction (commonly set to 55 periods). Trading Signals: Buy Signal: A long entry is triggered when: The Short EMA (9) crosses above the Medium EMA (21). The Medium EMA (21) is above the Long EMA (55). Sell Signal: A short entry is signaled when: The Short EMA (9) crosses below the Medium EMA (21). The Medium EMA (21) is below the Long EMA (55). Stop Loss and Take Profit: Stop Loss: Implement a predefined percentage or ATR-based stop loss to limit potential losses. Take Profit: Set a target based on a risk-to-reward ratio that reflects your trading strategy's goals. Advantages Trend Identification: The EMA crossover system allows traders to identify the current trend dynamically, focusing on upward or downward price movements. Simplicity: The strategy is straightforward, making it accessible for both new and experienced traders. Flexibility: This method can be applied across multiple timeframes and asset classes, making it versatile for various trading styles. Disadvantages Lagging Indicator: Moving averages are lagging indicators, meaning signals may come later than the actual price movement, which can lead to missed opportunities. Whipsaw Effect: In ranging markets, the strategy may produce false signals leading to potential losses.
Stratégie Pine Script®
par hold-and-hope
Advanced EMA Cross with Normalized ATR Filter, Controlling ADX Description: This strategy is based on EMA cross strategy and additional filters are used to get better results, a normalized ATR filter, and ADX control... It aims to provide traders with a code base that generates signals for long positions based on market conditions defined by various indicators. How it Works: 1. EMA: Uses short (8 periods) and long (20 periods) EMAs to identify crossovers. 2. ATR: Uses a 14-period ATR, normalized to its 20-period historical range, to filter out noise. 3. ADX: Uses a 14-period RMA to identify strong trends. 4. Volume: Filters trades based on a 14-period SMA of volume. 5. Super Trend: Uses a Super Trend indicator to identify the market direction. How to Use: - Buy Signal: Generated when EMA short crosses above EMA long, and other conditions like ATR and market direction are met. - Sell Signal: Generated based on EMA crossunder and high ADX value. Originality and Usefulness: This script combines EMA, ATR, ADX, and Super Trend indicators to filter out false signals and identify more reliable trading opportunities. USD Strength in the code is not working, just simulated it as PSEUDO CODE: Strategy Results: - Account Size: $1000 - Commission: Not considered - Slippage: Not considered - Risk: Manageable through parameters, now less than 5% per trade - Dataset: Aim for more than 100 trades for a sufficient sample size - Test Conditions: Test in 30 min chart for BTCUSDT IMPORTANT NOTE: This script should be used for educational purposes and should not be considered as financial advice. Chart: - The script's output is plotted as Buy and Sell signals on the chart. - No other scripts are included for clarity. - Have tested with 30mins period - You are encouraged to play with parameters, let me know if it helps you and/or if you can upgrade the code to a better level. WHY DID I USE ATR AND ADX? ATR filter is usually used for the following purposes. Market Volatility: ATR measures how volatile the market is. High ATR values indicate that the price is experiencing significant fluctuations. Filtering: Crossing a certain ATR threshold may indicate that the market is active enough to present trading opportunities. Risk Management: ATR can also be used to set stop-loss and take-profit levels, helping to manage risk effectively. And ADX is usually used for; Trend Strength: ADX measures the strength of a trend. High ADX values indicate a strong trend. Filtering: An ADX value above a certain level suggests that the trend is strong and it might be safer to trade. Versatility: ADX does not indicate the direction of the trend, only its strength. This makes it useful in both bullish and bearish markets. Using these indicators together can help filter out false signals and produce more reliable trading signals. While ATR helps to determine if the market is active enough, ADX measures the strength of the trend. Combined, they can create a more complex and effective trading strategy. I've used ADX data to support generating a buy signal after a golden cross (bullish trend) and waiting until this is a strong trend. It sounds good to check for different trend strengths for bullish and bearish markets to decide a buy signal. Additionally I used ATR to check if the market has enough fluctuations.
Stratégie Pine Script®
par gundoganfa
1
Mathias & Christer EMASo this Strategy is my first at when writing it's not 100% finnished. The strategy idé builds on EMA (9) being clearly over/under the EMA for some bars. If the EMA is over this will make a triggerline that when EMA (1) crosses this line it signals a buy/sell. I don't have a great TP or SL for this yet so as of now I'm only using oposit crossing of close for now. Colors and indicators: light green/red - indicates that EMA (9) has been crossed and that a new Triggerline is painted at that candles close position. dark green/red and Up /down Arrow - indicats that the triggerline has been crossed and an order should be taken here. green/red squares - are where the order closed. purple line - EMA (9) blue line - EMA (1)
Stratégie Pine Script®
par mattehalen
Triangle Breakout Strategy with TP/SL, EMA Filter📌 Triangle Breakout Strategy with TP/SL, EMA Filters, and Backtest – Explained. ✅ 1. Pattern Detection – Triangle Breakout The script scans for triangle patterns by detecting local pivot highs and pivot lows. It uses two recent highs and two recent lows to draw converging trendlines (upper and lower boundaries of the triangle). If the price breaks above the upper trendline, a bullish breakout signal is generated. 🎯 2. TP (Take Profit) & SL (Stop Loss) When a bullish breakout is detected: A buy order is placed using strategy.entry. TP and SL levels are calculated relative to the current close price: TP = 3% above the entry price SL = 1.5% below the entry price These are defined using strategy.exit. 📊 3. EMA Filter An optional filter checks if: Price is above both EMA 20 and EMA 50 Only if this condition is met, the strategy allows a long entry. You can toggle the filter on or off with useEMAFilter. 📈 4. Backtesting with Strategy Tester This script uses strategy() instead of indicator() to enable TradingView’s built-in backtest engine. Every buy entry and exit (based on TP or SL) is recorded. 📌 5. Visuals EMA 20 and EMA 50 lines are plotted on the chart. A label is shown when a breakout is detected: "Breakout Up" Results (profit, win rate, drawdown, etc.) can be viewed in the Strategy Tester panel.
Stratégie Pine Script®
par Reanimate_
inwCoin Simple EMA Cross Risk% Strategy.========================= English ========================= Just very basic simple EMA cross I'm using EMA 18 and EMA 120 daily Buy : EMA18 crossover EMA120 Sell : EMA18 crossunder EMA120 this proven profitable for BTC since it likely to hover over EMA120 in bull market. ========================== Thai ========================== บางทีกลยุทธ ที่ดูเหมือนง่ายๆ โง่ๆ อย่าง EMA สองเส้น ตัดกัน ถ้าดูตาม TF ใหญ่ มันก็ทำกำไรได้ ค่อนข้างดีเลยทีเดียวนะเนี่ย บางที คนเราก็พยายามจะเล่นสั้นกันแทบตาย หาสูตรพิสดารพันลึก สุดท้าย เอาเข้าจริงๆ เล่นง่ายๆ ตามระบบง่ายๆ ใน TF ใหญ่ๆ ระดับ Daily หรือ Weekly ขึ้นไป ...ก็ได้ตังเหมือนกัน ปัญหาคือ คนส่วนใหญ่ ทนกันไม่ได้ และนั่งเฉยๆ ไม่เป็นน่ะ 55555 มันคันมือเหลือเกิน จะต้องทำกำไรให้ได้ทุกวัน ไม่งั้นไม่เท่ สุดท้าย ไปเข้าๆ ออกๆ รัวๆ แทนที่เงินจะงอก ดันเสียเงินอีก ดีไม่ดีเมาหมัด ยิ่งเทรดยิ่งเสีย เจ๊งกันเข้าไปใหญ่
Stratégie Pine Script®
par Real_inwCoin
3 EMA + RSI with Trail Stop [Free990] (LOW TF)This trading strategy combines three Exponential Moving Averages (EMAs) to identify trend direction, uses RSI to signal exit conditions, and applies both a fixed percentage stop-loss and a trailing stop for risk management. It aims to capture momentum when the faster EMAs cross the slower EMA, then uses RSI thresholds, time-based exits, and stops to close trades. Short Explanation of the Logic Trend Detection: When the 10 EMA crosses above the 20 EMA and both are above the 100 EMA (and the current price bar closes higher), it triggers a long entry signal. The reverse happens for a short (the 10 EMA crosses below the 20 EMA and both are below the 100 EMA). RSI Exit: RSI crossing above a set threshold closes long trades; crossing below another threshold closes short trades. Time-Based Exit: If a trade is in profit after a set number of bars, the strategy closes it. Stop-Loss & Trailing Stop: A fixed stop-loss based on a percentage from the entry price guards against large drawdowns. A trailing stop dynamically tightens as the trade moves in favor, locking in potential gains. Detailed Explanation of the Strategy Logic Exponential Moving Average (EMA) Setup Short EMA (out_a, length=10) Medium EMA (out_b, length=20) Long EMA (out_c, length=100) The code calculates three separate EMAs to gauge short-term, medium-term, and longer-term trend behavior. By comparing their relative positions, the strategy infers whether the market is bullish (EMAs stacked positively) or bearish (EMAs stacked negatively). Entry Conditions Long Entry (entryLong): Occurs when: The short EMA (10) crosses above the medium EMA (20). Both EMAs (short and medium) are above the long EMA (100). The current bar closes higher than it opened (close > open). This suggests that momentum is shifting to the upside (short-term EMAs crossing up and price action turning bullish). If there’s an existing short position, it’s closed first before opening a new long. Short Entry (entryShort): Occurs when: The short EMA (10) crosses below the medium EMA (20). Both EMAs (short and medium) are below the long EMA (100). The current bar closes lower than it opened (close < open). This indicates a potential shift to the downside. If there’s an existing long position, that gets closed first before opening a new short. Exit Signals RSI-Based Exits: For long trades: When RSI exceeds a specified threshold (e.g., 70 by default), it triggers a long exit. RSI > short_rsi generally means overbought conditions, so the strategy exits to lock in profits or avoid a pullback. For short trades: When RSI dips below a specified threshold (e.g., 30 by default), it triggers a short exit. RSI < long_rsi indicates oversold conditions, so the strategy closes the short to avoid a bounce. Time-Based Exit: If the trade has been open for xBars bars (configurable, e.g., 24 bars) and the trade is in profit (current price above entry for a long, or current price below entry for a short), the strategy closes the position. This helps lock in gains if the move takes too long or momentum stalls. Stop-Loss Management Fixed Stop-Loss (% Based): Each trade has a fixed stop-loss calculated as a percentage from the average entry price. For long positions, the stop-loss is set below the entry price by a user-defined percentage (fixStopLossPerc). For short positions, the stop-loss is set above the entry price by the same percentage. This mechanism prevents catastrophic losses if the market moves strongly against the position. Trailing Stop: The strategy also sets a trail stop using trail_points (the distance in price points) and trail_offset (how quickly the stop “catches up” to price). As the market moves in favor of the trade, the trailing stop gradually tightens, allowing profits to run while still capping potential drawdowns if the price reverses. Order Execution Flow When the conditions for a new position (long or short) are triggered, the strategy first checks if there’s an opposite position open. If there is, it closes that position before opening the new one (prevents going “both long and short” simultaneously). RSI-based and time-based exits are checked on each bar. If triggered, the position is closed. If the position remains open, the fixed stop-loss and trailing stop remain in effect until the position is exited. Why This Combination Works Multiple EMA Cross: Combining 10, 20, and 100 EMAs balances short-term momentum detection with a longer-term trend filter. This reduces false signals that can occur if you only look at a single crossover without considering the broader trend. RSI Exits: RSI provides a momentum oscillator view—helpful for detecting overbought/oversold conditions, acting as an extra confirmation to exit. Time-Based Exit: Prevents “lingering trades.” If the position is in profit but failing to advance further, it takes profit rather than risking a trend reversal. Fixed & Trailing Stop-Loss: The fixed stop-loss is your safety net to cap worst-case losses. The trailing stop allows the strategy to lock in gains by following the trade as it moves favorably, thus maximizing profit potential while keeping risk in check. Overall, this approach tries to capture momentum from EMA crossovers, protect profits with trailing stops, and limit risk through both a fixed percentage stop-loss and exit signals from RSI/time-based logic.
Stratégie Pine Script®
par Free990
25
EMA 12/26 With ATR Volatility StoplossThe EMA 12/26 With ATR Volatility Stoploss The EMA 12/26 With ATR Volatility Stoploss strategy is a meticulously designed systematic trading approach tailored for navigating financial markets through technical analysis. By integrating the Exponential Moving Average (EMA) and Average True Range (ATR) indicators, the strategy aims to identify optimal entry and exit points for trades while prioritizing disciplined risk management. At its core, it is a trend-following system that seeks to capitalize on price momentum, employing volatility-adjusted stop-loss mechanisms and dynamic position sizing to align with predefined risk parameters. Additionally, it offers traders the flexibility to manage profits either by compounding returns or preserving initial capital, making it adaptable to diverse trading philosophies. This essay provides a comprehensive exploration of the strategy’s underlying concepts, key components, strengths, limitations, and practical applications, without delving into its technical code. ===== Core Philosophy and Objectives The EMA 12/26 With ATR Volatility Stoploss strategy is built on the premise of capturing short- to medium-term price trends with a high degree of automation and consistency. It leverages the crossover of two EMAs—a fast EMA (12-period) and a slow EMA (26-period)—to generate buy and sell signals, which indicate potential trend reversals or continuations. To mitigate the inherent risks of trading, the strategy incorporates the ATR indicator to set stop-loss levels that adapt to market volatility, ensuring that losses remain within acceptable bounds. Furthermore, it calculates position sizes based on a user-defined risk percentage, safeguarding capital while optimizing trade exposure. A distinctive feature of the strategy is its dual profit management modes: SnowBall (Compound Profit): Profits from successful trades are reinvested into the capital base, allowing for progressively larger position sizes and potential exponential portfolio growth. ZeroRisk (Fixed Equity): Profits are withdrawn, and trades are executed using only the initial capital, prioritizing capital preservation and minimizing exposure to market downturns. This duality caters to both aggressive traders seeking growth and conservative traders focused on stability, positioning the strategy as a versatile tool for various market environments. ===== Key Components of the Strategy 1. EMA-Based Signal Generation The strategy’s trend-following mechanism hinges on the interaction between the Fast EMA (12-period) and Slow EMA (26-period). EMAs are preferred over simple moving averages because they assign greater weight to recent price data, enabling quicker responses to market shifts. The key signals are: Buy Signal: Triggered when the Fast EMA crosses above the Slow EMA, suggesting the onset of an uptrend or bullish momentum. Sell Signal: Occurs when the Fast EMA crosses below the Slow EMA, indicating a potential downtrend or the end of a bullish phase. To enhance signal reliability, the strategy employs an Anchor Point EMA (AP EMA), a short-period EMA (e.g., 2 days) that smooths the input price data before calculating the primary EMAs. This preprocessing reduces noise from short-term price fluctuations, improving the accuracy of trend detection. Additionally, users can opt for a Consolidated EMA (e.g., 18-period) to display a single trend line instead of both EMAs, simplifying chart analysis while retaining trend insights. ===== 2. Volatility-Adjusted Risk Management with ATR Risk management is a cornerstone of the strategy, achieved through the use of the Average True Range (ATR), which quantifies market volatility by measuring the average price range over a specified period (e.g., 10 days). The ATR informs the placement of stop-loss levels, which are set at a multiple of the ATR (e.g., 2x ATR) below the entry price for long positions. This approach ensures that stop losses are proportionate to current market conditions—wider during high volatility to avoid premature exits, and narrower during low volatility to protect profits. For example, if a stock’s ATR is $1 and the multiplier is 2, the stop loss for a buy at $100 would be set at $98. This dynamic adjustment enhances the strategy’s adaptability, preventing stop-outs from normal market noise while capping potential losses. ===== 3. Dynamic Position Sizing The strategy calculates position sizes to align with a user-defined Risk Per Trade, typically expressed as a percentage of capital (e.g., 2%). The position size is determined by: The available capital, which varies depending on whether SnowBall or ZeroRisk mode is selected. The distance between the entry price and the ATR-based stop-loss level, which represents the per-unit risk. The desired risk percentage, ensuring that the maximum loss per trade does not exceed the specified threshold. For instance, with a $1,000 capital, a 2% risk per trade ($20), and a stop-loss distance equivalent to 5% of the entry price, the strategy computes the number of units (shares or contracts) to ensure the total loss, if the stop loss is hit, equals $20. To prevent over-leveraging, the strategy includes checks to ensure that the position’s dollar value does not exceed available capital. If it does, the position size is scaled down to fit within the capital constraints, maintaining financial discipline. ===== 4. Flexible Capital Management The strategy’s dual profit management modes—SnowBall and ZeroRisk—offer traders strategic flexibility: SnowBall Mode: By compounding profits, traders can increase their capital base, leading to larger position sizes over time. This is ideal for those with a long-term growth mindset, as it harnesses the power of exponential returns. ZeroRisk Mode: By withdrawing profits and trading solely with the initial capital, traders protect their gains and limit exposure to market volatility. This conservative approach suits those prioritizing stability over aggressive growth. These options allow traders to tailor the strategy to their risk tolerance, financial goals, and market outlook, enhancing its applicability across different trading styles. ===== 5. Time-Based Trade Filtering To optimize performance and relevance, the strategy includes an option to restrict trading to a specific time range (e.g., from 2018 onward). This feature enables traders to focus on periods with favorable market conditions, avoid historically volatile or unreliable data, or align the strategy with their backtesting objectives. By confining trades to a defined timeframe, the strategy ensures that performance metrics reflect the intended market context. ===== Strengths of the Strategy The EMA 12/26 With ATR Volatility Stoploss strategy offers several compelling advantages: Systematic and Objective: By adhering to predefined rules, the strategy eliminates emotional biases, ensuring consistent execution across market conditions. Robust Risk Controls: The combination of ATR-based stop losses and risk-based position sizing caps losses at user-defined levels, fostering capital preservation. Customizability: Traders can adjust parameters such as EMA periods, ATR multipliers, and risk percentages, tailoring the strategy to specific markets or preferences. Volatility Adaptation: Stop losses that scale with market volatility enhance the strategy’s resilience, accommodating both calm and turbulent market phases. Enhanced Visualization: The use of color-coded EMAs (green for bullish, red for bearish) and background shading provides intuitive visual cues, simplifying trend and trade status identification. ===== Limitations and Considerations Despite its strengths, the strategy has inherent limitations that traders must address: False Signals in Range-Bound Markets: EMA crossovers may generate misleading signals in sideways or choppy markets, leading to whipsaws and unprofitable trades. Signal Lag: As lagging indicators, EMAs may delay entry or exit signals, causing traders to miss rapid trend shifts or enter trades late. Overfitting Risk: Excessive optimization of parameters to fit historical data can impair the strategy’s performance in live markets, as past patterns may not persist. Impact of High Volatility: In extremely volatile markets, wider stop losses may result in larger losses than anticipated, challenging risk management assumptions. Data Reliability: The strategy’s effectiveness depends on accurate, continuous price data, and discrepancies or gaps can undermine signal accuracy. ===== Practical Applications The EMA 12/26 With ATR Volatility Stoploss strategy is versatile, applicable to diverse markets such as stocks, forex, commodities, and cryptocurrencies, particularly in trending environments. To maximize its potential, traders should adopt a rigorous implementation process: Backtesting: Evaluate the strategy’s historical performance across various market conditions to assess its robustness and identify optimal parameter settings. Forward Testing: Deploy the strategy in a demo account to validate its real-time performance, ensuring it aligns with live market dynamics before risking capital. Ongoing Monitoring: Continuously track trade outcomes, analyze performance metrics, and refine parameters to adapt to evolving market conditions. Additionally, traders should consider market-specific factors, such as liquidity and volatility, when applying the strategy. For instance, highly liquid markets like forex may require tighter ATR multipliers, while less liquid markets like small-cap stocks may benefit from wider stop losses. ===== Conclusion The EMA 12/26 With ATR Volatility Stoploss strategy is a sophisticated, systematic trading framework that blends trend-following precision with disciplined risk management. By leveraging EMA crossovers for signal generation, ATR-based stop losses for volatility adjustment, and dynamic position sizing for risk control, it offers a balanced approach to capturing market trends while safeguarding capital. Its flexibility—evident in customizable parameters and dual profit management modes—makes it suitable for traders with varying risk appetites and objectives. However, its limitations, such as susceptibility to false signals and signal lag, necessitate thorough testing and prudent application. Through rigorous backtesting, forward testing, and continuous refinement, traders can harness this strategy to achieve consistent, risk-adjusted returns in trending markets, establishing it as a valuable tool in the arsenal of systematic trading.
Stratégie Pine Script®
par Wongsakon