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Reversal off EMASimple script find when a probable reversal will start. When price moves sharply away from the 13 EMA a BUY/SELL signal will pop up. Scripted to work on 5m 1h, 4h, and daily chart. But it doesn't work on all charts. Not sure why. I'm a forex trader and use this on NZDUSD. It doesn't give too good results on the JPY charts. I think its a fairly good reversal indicator. It definitely doesn't catch them all, and if there is a strong bearish or bullish impulse it doesn't work too well. But with all indicators, you need other conformations when to get in and when to get out. Hope it helps someone.
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shamgar331 tarafından
Multi SMA EMA VWAP1. Moving Average Crossover This is one of the most common strategies with moving averages, and it involves observing crossovers between EMAs and SMAs to determine buy or sell signals. Buy signal: When a faster EMA (like a short-term EMA) crosses above a slower SMA, it can indicate a potential upward movement. Sell signal: When a faster EMA crosses below a slower SMA, it can indicate a potential downward movement. With 4 EMAs and 5 SMAs, you can set up crossovers between different combinations, such as: EMA(9) crosses above SMA(50) → buy. EMA(9) crosses below SMA(50) → sell. 2. Divergence Confirmation Between EMAs and SMAs Divergence between the EMAs and SMAs can offer additional confirmation. If the EMAs are pointing in one direction and the SMAs are still in the opposite direction, it is a sign that the movement could be stronger and continue in the same direction. Positive divergence: If the EMAs are making new highs while the SMAs are still below, it could be a sign that the market is in a strong trend. Negative divergence: If the EMAs are making new lows and the SMAs are still above, you might consider that the market is in a downtrend or correction. 3. Using EMAs as Dynamic Support and Resistance EMAs can act as dynamic support and resistance in strong trends. If the price approaches a faster EMA from above and doesn’t break it, it could be a good entry point for a long position (buy). If the price approaches a slower EMA from below and doesn't break it, it could be a good point to sell (short). Buy: If the price is above all EMAs and approaches the fastest EMA (e.g., EMA(9)), it could be a good buy point if the price bounces upward. Sell: If the price is below all EMAs and approaches the fastest EMA, it could be a good sell point if the price bounces downward. 4. Combining SMAs and EMAs to Filter Signals SMAs can serve as a trend filter to avoid trading in sideways markets. For example: Bullish trend condition: If the longer-term SMAs (such as SMA(100) or SMA(200)) are below the price, and the shorter EMAs are aligned upward, you can look for buy signals. Bearish trend condition: If the longer-term SMAs are above the price and the shorter EMAs are aligned downward, you can look for sell signals. 5. Consolidation Zone Between EMAs and SMAs When the price moves between EMAs and SMAs without a clear trend (consolidation zone), you can expect a breakout. In this case, you can use the EMAs and SMAs to identify the direction of the breakout: If the price is in a narrow range between the EMAs and SMAs and then breaks above the fastest EMA, it’s a sign that an upward trend may begin. If the price breaks below the fastest EMA, it could indicate a potential downward trend. 6. "Golden Cross" and "Death Cross" Strategy These are classic strategies based on crossovers between moving averages of different periods. Golden Cross: Occurs when a faster EMA (e.g., EMA(50)) crosses above a slower SMA (e.g., SMA(200)), which suggests a potential bullish trend. Death Cross: Occurs when a faster EMA crosses below a slower SMA, which suggests a potential bearish trend. Additional Recommendations: Combining with other indicators: You can combine EMA and SMA signals with other indicators like the RSI (Relative Strength Index) or MACD (Moving Average Convergence/Divergence) for confirmation and to avoid false signals. Risk management: Always use stop-loss and take-profit orders to protect your capital. Moving averages are trend-following indicators but don’t guarantee that the price will move in the same direction. Timeframe analysis: It’s recommended to use different timeframes to confirm the trend (e.g., use EMAs on hourly charts along with SMAs on daily charts). VWAP 1. VWAP + EMAs for Trend Confirmation VWAP can act as a trend filter, confirming the direction provided by the EMAs. Buy Signal: If the price is above the VWAP and the EMAs are aligned in an uptrend (e.g., short-term EMAs are above longer-term EMAs), this indicates that the trend is bullish and you can look for buy opportunities. Sell Signal: If the price is below the VWAP and the EMAs are aligned in a downtrend (e.g., short-term EMAs are below longer-term EMAs), this suggests a bearish trend and you can look for sell opportunities. In this case, VWAP is used to confirm the overall trend. For example: Bullish: Price above VWAP, EMAs aligned to the upside (e.g., EMA(9) > EMA(50) > EMA(200)), buy. Bearish: Price below VWAP, EMAs aligned to the downside (e.g., EMA(9) < EMA(50) < EMA(200)), sell. 2. VWAP as Dynamic Support and Resistance VWAP can act as a dynamic support or resistance level during the day. Combining this with EMAs and SMAs helps you refine your entry and exit points. Support: If the price is above VWAP and starts pulling back to VWAP, it could act as support. If the price bounces off the VWAP and aligns with bullish EMAs (e.g., EMA(9) crossing above EMA(50)), you can consider entering a buy position. Resistance: If the price is below VWAP and approaches VWAP from below, it can act as resistance. If the price fails to break through VWAP and aligns with bearish EMAs (e.g., EMA(9) crossing below EMA(50)), it could be a good signal for a sell.
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laguiler tarafından
Quadruple EMA (QEMA)The Quadruple Exponential Moving Average (QEMA) is an advanced technical indicator that extends the concept of lag reduction beyond TEMA (Triple Exponential Moving Average) to a fourth order. By applying a sophisticated four-stage EMA cascade with optimized coefficient distribution, QEMA provides the ultimate evolution in EMA-based lag reduction techniques. Unlike traditional compund moving averages like DEMA and TEMA, QEMA implements a progressive smoothing system that strategically distributes alphas across four EMA stages and combines them with balanced coefficients (4, -6, 4, -1). This approach creates an indicator that responds extremely quickly to price changes while still maintaining sufficient smoothness to be useful for trading decisions. QEMA is particularly valuable for traders who need the absolute minimum lag possible in trend identification. ▶️ **Core Concepts** Fourth-order processing: Extends the EMA cascade to four stages for maximum possible lag reduction while maintaining a useful signal Progressive alpha system: Uses mathematically derived ratio-based alpha progression to balance responsiveness across all four EMA stages Optimized coefficients: Employs calculated weights (4, -6, 4, -1) to effectively eliminate lag while preserving compound signal stability Numerical stability control: Implements initialization and alpha distribution to ensure consistent results from the first calculation bar QEMA achieves its exceptional lag reduction by combining four progressive EMAs with mathematically optimized coefficients. The formula is designed to maximize responsiveness while minimizing the overshoot problems that typically occur with aggressive lag reduction techniques. The implementation uses a ratio-based alpha progression that ensures each EMA stage contributes appropriately to the final result. ▶️ **Common Settings and Parameters** Period: Default: 15| Base smoothing period | When to Adjust: Decrease for extremely fast signals, increase for more stable output Alpha: Default: auto | Direct control of base smoothing factor | When to Adjust: Manual setting allows precise tuning beyond standard period settings Source: Default: Close | Data point used for calculation | When to Adjust: Change to HL2 or HLC3 for more balanced price representation Pro Tip: Professional traders often use QEMA with longer periods than other moving averages (e.g., QEMA(20) instead of EMA(10)) since its extreme lag reduction provides earlier signals even with longer periods. ▶️ **Calculation and Mathematical Foundation** Simplified explanation: QEMA works by calculating four EMAs in sequence, with each EMA taking the previous one as input. It then combines these EMAs using balancing weights (4, -6, 4, -1) to create a moving average with extremely minimal lag and high level of smoothness. The alpha factors for each EMA are progressively adjusted using a mathematical ratio to ensure balanced responsiveness across all stages. Technical formula: QEMA = 4 × EMA₁ - 6 × EMA₂ + 4 × EMA₃ - EMA₄ Where: EMA₁ = EMA(source, α₁) EMA₂ = EMA(EMA₁, α₂) EMA₃ = EMA(EMA₂, α₃) EMA₄ = EMA(EMA₃, α₄) α₁ = 2/(period + 1) is the base smoothing factor r = (1/α₁)^(1/3) is the derived ratio α₂ = α₁ × r, α₃ = α₂ × r, α₄ = α₃ × r are the progressive alphas Mathematical Rationale for the Alpha Cascade: The QEMA indicator employs a specific geometric progression for its smoothing factors (alphas) across the four EMA stages. This design is intentional and aims to optimize the filter's performance. The ratio between alphas is **r = (1/α₁)^(1/3)** - derived from the cube root of the reciprocal of the base alpha. For typical smoothing (α₁ < 1), this results in a sequence of increasing alpha values (α₁ < α₂ < α₃ < α₄), meaning that subsequent EMAs in the cascade are progressively faster (less smoothed). This specific progression, when combined with the QEMA coefficients (4, -6, 4, -1), is chosen for the following reasons: 1. Optimized Frequency Response: Using the same alpha for all EMA stages (as in a naive multi-EMA approach) can lead to an uneven frequency response, potentially causing over-shooting of certain frequencies or creating undesirable resonance. The geometric progression of alphas in QEMA helps to create a more balanced and controlled filter response across a wider range of movement frequencies. Each stage's contribution to the overall filtering characteristic is more harmonized. 2. Minimized Phase Lag: A key goal of QEMA is extreme lag reduction. The specific alpha cascade, particularly the relationship defined by **r**, is designed to minimize the cumulative phase lag introduced by the four smoothing stages, while still providing effective noise reduction. Faster subsequent EMAs contribute to this reduced lag. 🔍 Technical Note: The ratio-based alpha progression is crucial for balanced response. The ratio r is calculated as the cube root of 1/α₁, ensuring that the combined effect of all four EMAs creates a mathematically optimal response curve. All EMAs are initialized with the first source value rather than using progressive initialization, eliminating warm-up artifacts and providing consistent results from the first bar. ▶️ **Interpretation Details** QEMA provides several key insights for traders: When price crosses above QEMA, it signals the beginning of an uptrend with minimal delay When price crosses below QEMA, it signals the beginning of a downtrend with minimal delay The slope of QEMA provides immediate insight into trend direction and momentum QEMA responds to price reversals significantly faster than other moving averages Multiple QEMA lines with different periods can identify immediate support/resistance levels QEMA is particularly valuable in fast-moving markets and for short-term trading strategies where speed of signal generation is critical. It excels at capturing the very beginning of trends and identifying reversals earlier than any other EMA-derived indicator. This makes it especially useful for breakout trading and scalping strategies where getting in early is essential. ▶️ **Limitations and Considerations** Market conditions: Can generate excessive signals in choppy, sideways markets due to its extreme responsiveness Overshooting: The aggressive lag reduction can create some overshooting during sharp reversals Calculation complexity: Requires four separate EMA calculations plus coefficient application, making it computationally more intensive Parameter sensitivity: Small changes in the base alpha or period can significantly alter behavior Complementary tools: Should be used with momentum indicators or volatility filters to confirm signals and reduce false positives ▶️ **References** Mulloy, P. (1994). "Smoothing Data with Less Lag," Technical Analysis of Stocks & Commodities . Ehlers, J. (2001). Rocket Science for Traders . John Wiley & Sons.
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mihakralj tarafından