Why EMA Isn't What You Think It IsMany new traders adopt the Exponential Moving Average (EMA) believing it's simply a "better Simple Moving Average (SMA)". This common misconception leads to fundamental misunderstandings about how EMA works and when to use it.
EMA and SMA differ at their core. SMA use a window of finite number of data points, giving equal weight to each data point in the calculation period. This makes SMA a Finite Impulse Response (FIR) filter in signal processing terms. Remember that FIR means that "all that we need is the 'period' number of data points" to calculate the filter value. Anything beyond the given period is not relevant to FIR filters – much like how a security camera with 14-day storage automatically overwrites older footage, making last month's activity completely invisible regardless of how important it might have been.
EMA, however, is an Infinite Impulse Response (IIR) filter. It uses ALL historical data, with each past price having a diminishing - but never zero - influence on the calculated value. This creates an EMA response that extends infinitely into the past—not just for the last N periods. IIR filters cannot be precise if we give them only a 'period' number of data to work on - they will be off-target significantly due to lack of context, like trying to understand Game of Thrones by watching only the final season and wondering why everyone's so upset about that dragon lady going full pyromaniac.
If we only consider a number of data points equal to the EMA's period, we are capturing no more than 86.5% of the total weight of the EMA calculation. Relying on he period window alone (the warm-up period) will provide only 1 - (1 / e^2) weights, which is approximately 1−0.1353 = 0.8647 = 86.5%. That's like claiming you've read a book when you've skipped the first few chapters – technically, you got most of it, but you probably miss some crucial early context.
▶️ What is period in EMA used for?
What does a period parameter really mean for EMA? When we select a 15-period EMA, we're not selecting a window of 15 data points as with an SMA. Instead, we are using that number to calculate a decay factor (α) that determines how quickly older data loses influence in EMA result. Every trader knows EMA calculation: α = 1 / (1+period) – or at least every trader claims to know this while secretly checking the formula when they need it.
Thinking in terms of "period" seriously restricts EMA. The α parameter can be - should be! - any value between 0.0 and 1.0, offering infinite tuning possibilities of the indicator. When we limit ourselves to whole-number periods that we use in FIR indicators, we can only access a small subset of possible IIR calculations – it's like having access to the entire RGB color spectrum with 16.7 million possible colors but stubbornly sticking to the 8 basic crayons in a child's first art set because the coloring book only mentioned those by name.
For example:
Period 10 → alpha = 0.1818
Period 11 → alpha = 0.1667
What about wanting an alpha of 0.17, which might yield superior returns in your strategy that uses EMA? No whole-number period can provide this! Direct α parameterization offers more precision, much like how an analog tuner lets you find the perfect radio frequency while digital presets force you to choose only from predetermined stations, potentially missing the clearest signal sitting right between channels.
Sidenote: the choice of α = 1 / (1+period) is just a convention from 1970s, probably started by J. Welles Wilder, who popularized the use of the 14-day EMA. It was designed to create an approximate equivalence between EMA and SMA over the same number of periods, even thought SMA needs a period window (as it is FIR filter) and EMA doesn't. In reality, the decay factor α in EMA should be allowed any valye between 0.0 and 1.0, not just some discrete values derived from an integer-based period! Algorithmic systems should find the best α decay for EMA directly, allowing the system to fine-tune at will and not through conversion of integer period to float α decay – though this might put a few traditionalist traders into early retirement. Well, to prevent that, most traditionalist implementations of EMA only use period and no alpha at all. Heaven forbid we disturb people who print their charts on paper, draw trendlines with rulers, and insist the market "feels different" since computers do algotrading!
▶️ Calculating EMAs Efficiently
The standard textbook formula for EMA is:
EMA = CurrentPrice × alpha + PreviousEMA × (1 - alpha)
But did you know that a more efficient version exists, once you apply a tiny bit of high school algebra:
EMA = alpha × (CurrentPrice - PreviousEMA) + PreviousEMA
The first one requires three operations: 2 multiplications + 1 addition. The second one also requires three ops: 1 multiplication + 1 addition + 1 subtraction.
That's pathetic, you say? Not worth implementing? In most computational models, multiplications cost much more than additions/subtractions – much like how ordering dessert costs more than asking for a water refill at restaurants.
Relative CPU cost of float operations :
Addition/Subtraction: ~1 cycle
Multiplication: ~5 cycles (depending on precision and architecture)
Now you see the difference? 2 * 5 + 1 = 11 against 5 + 1 + 1 = 7. That is ≈ 36.36% efficiency gain just by swapping formulas around! And making your high school math teacher proud enough to finally put your test on the refrigerator.
▶️ The Warmup Problem: how to start the EMA sequence right
How do we calculate the first EMA value when there's no previous EMA available? Let's see some possible options used throughout the history:
Start with zero : EMA(0) = 0. This creates stupidly large distortion until enough bars pass for the horrible effect to diminish – like starting a trading account with zero balance but backdating a year of missed trades, then watching your balance struggle to climb out of a phantom debt for months.
Start with first price : EMA(0) = first price. This is better than starting with zero, but still causes initial distortion that will be extra-bad if the first price is an outlier – like forming your entire opinion of a stock based solely on its IPO day price, then wondering why your model is tanking for weeks afterward.
Use SMA for warmup : This is the tradition from the pencil-and-paper era of technical analysis – when calculators were luxury items and "algorithmic trading" meant your broker had neat handwriting. We first calculate an SMA over the initial period, then kickstart the EMA with this average value. It's widely used due to tradition, not merit, creating a mathematical Frankenstein that uses an FIR filter (SMA) during the initial period before abruptly switching to an IIR filter (EMA). This methodology is so aesthetically offensive (abrupt kink on the transition from SMA to EMA) that charting platforms hide these early values entirely, pretending EMA simply doesn't exist until the warmup period passes – the technical analysis equivalent of sweeping dust under the rug.
Use WMA for warmup : This one was never popular because it is harder to calculate with a pencil - compared to using simple SMA for warmup. Weighted Moving Average provides a much better approximation of a starting value as its linear descending profile is much closer to the EMA's decay profile.
These methods all share one problem: they produce inaccurate initial values that traders often hide or discard, much like how hedge funds conveniently report awesome performance "since strategy inception" only after their disastrous first quarter has been surgically removed from the track record.
▶️ A Better Way to start EMA: Decaying compensation
Think of it this way: An ideal EMA uses an infinite history of prices, but we only have data starting from a specific point. This creates a problem - our EMA starts with an incorrect assumption that all previous prices were all zero, all close, or all average – like trying to write someone's biography but only having information about their life since last Tuesday.
But there is a better way. It requires more than high school math comprehension and is more computationally intensive, but is mathematically correct and numerically stable. This approach involves compensating calculated EMA values for the "phantom data" that would have existed before our first price point.
Here's how phantom data compensation works:
We start our normal EMA calculation:
EMA_today = EMA_yesterday + α × (Price_today - EMA_yesterday)
But we add a correction factor that adjusts for the missing history:
Correction = 1 at the start
Correction = Correction × (1-α) after each calculation
We then apply this correction:
True_EMA = Raw_EMA / (1-Correction)
This correction factor starts at 1 (full compensation effect) and gets exponentially smaller with each new price bar. After enough data points, the correction becomes so small (i.e., below 0.0000000001) that we can stop applying it as it is no longer relevant.
Let's see how this works in practice:
For the first price bar:
Raw_EMA = 0
Correction = 1
True_EMA = Price (since 0 ÷ (1-1) is undefined, we use the first price)
For the second price bar:
Raw_EMA = α × (Price_2 - 0) + 0 = α × Price_2
Correction = 1 × (1-α) = (1-α)
True_EMA = α × Price_2 ÷ (1-(1-α)) = Price_2
For the third price bar:
Raw_EMA updates using the standard formula
Correction = (1-α) × (1-α) = (1-α)²
True_EMA = Raw_EMA ÷ (1-(1-α)²)
With each new price, the correction factor shrinks exponentially. After about -log₁₀(1e-10)/log₁₀(1-α) bars, the correction becomes negligible, and our EMA calculation matches what we would get if we had infinite historical data.
This approach provides accurate EMA values from the very first calculation. There's no need to use SMA for warmup or discard early values before output converges - EMA is mathematically correct from first value, ready to party without the awkward warmup phase.
Here is Pine Script 6 implementation of EMA that can take alpha parameter directly (or period if desired), returns valid values from the start, is resilient to dirty input values, uses decaying compensator instead of SMA, and uses the least amount of computational cycles possible.
// Enhanced EMA function with proper initialization and efficient calculation
ema(series float source, simple int period=0, simple float alpha=0)=>
// Input validation - one of alpha or period must be provided
if alpha<=0 and period<=0
runtime.error("Alpha or period must be provided")
// Calculate alpha from period if alpha not directly specified
float a = alpha > 0 ? alpha : 2.0 / math.max(period, 1)
// Initialize variables for EMA calculation
var float ema = na // Stores raw EMA value
var float result = na // Stores final corrected EMA
var float e = 1.0 // Decay compensation factor
var bool warmup = true // Flag for warmup phase
if not na(source)
if na(ema)
// First value case - initialize EMA to zero
// (we'll correct this immediately with the compensation)
ema := 0
result := source
else
// Standard EMA calculation (optimized formula)
ema := a * (source - ema) + ema
if warmup
// During warmup phase, apply decay compensation
e *= (1-a) // Update decay factor
float c = 1.0 / (1.0 - e) // Calculate correction multiplier
result := c * ema // Apply correction
// Stop warmup phase when correction becomes negligible
if e <= 1e-10
warmup := false
else
// After warmup, EMA operates without correction
result := ema
result // Return the properly compensated EMA value
▶️ CONCLUSION
EMA isn't just a "better SMA"—it is a fundamentally different tool, like how a submarine differs from a sailboat – both float, but the similarities end there. EMA responds to inputs differently, weighs historical data differently, and requires different initialization techniques.
By understanding these differences, traders can make more informed decisions about when and how to use EMA in trading strategies. And as EMA is embedded in so many other complex and compound indicators and strategies, if system uses tainted and inferior EMA calculatiomn, it is doing a disservice to all derivative indicators too – like building a skyscraper on a foundation of Jell-O.
The next time you add an EMA to your chart, remember: you're not just looking at a "faster moving average." You're using an INFINITE IMPULSE RESPONSE filter that carries the echo of all previous price actions, properly weighted to help make better trading decisions.
EMA done right might significantly improve the quality of all signals, strategies, and trades that rely on EMA somewhere deep in its algorithmic bowels – proving once again that math skills are indeed useful after high school, no matter what your guidance counselor told you.
Cerca negli script per "3 ema"
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.
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.
Dema Ema Crossover | viResearchDema Ema Crossover | viResearch
Conceptual Foundation and Innovation
The "Dema Ema Crossover" indicator combines the strengths of the Double Exponential Moving Average (DEMA) with an Exponential Moving Average (EMA) crossover strategy. The DEMA is well-known for its ability to reduce lag compared to standard moving averages, offering smoother trend-following signals. In this script, the DEMA is used as the foundation, with two EMAs applied on top of it to further refine the trend detection and crossover points. This combination provides traders with a robust tool for identifying trend shifts and potential entry or exit points.
By leveraging the faster responsiveness of the DEMA and using EMA crossovers, the "Dema Ema Crossover" indicator helps traders detect and act on trend reversals more efficiently, making it a powerful solution for capturing both short- and long-term market movements.
Technical Composition and Calculation
The "Dema Ema Crossover" script consists of three main components: the Double Exponential Moving Average (DEMA), the fast EMA, and the slow EMA. The DEMA is calculated based on the selected length and source price, providing a smooth representation of market trends. Two EMAs are then applied to the DEMA, with one being faster (shorter period) and the other slower (longer period). The crossover between these two EMAs generates the signals for trend changes.
For the DEMA, the calculation uses the ta.dema function, which reduces lag while maintaining smoothness in the moving average. The fast and slow EMAs are calculated using the ta.ema function, with the fast EMA responding more quickly to price changes, while the slow EMA captures broader trends. The crossover between these two EMAs is used to generate buy and sell signals based on the direction of the crossover.
Features and User Inputs
The "Dema Ema Crossover" script offers several customizable inputs that allow traders to tailor the indicator to their trading strategies. The DEMA Length controls how smooth the DEMA is, with a longer length creating a slower-moving average and a shorter length providing a more responsive one. The Fast EMA Length and Slow EMA Length are also customizable, allowing traders to adjust the sensitivity of the crossover signals based on their market outlook and preferred trading timeframe.
Practical Applications
The "Dema Ema Crossover" indicator is designed for traders looking for a reliable crossover strategy that combines the responsiveness of the DEMA with the precision of EMA crossovers. This tool is particularly effective for:
Identifying Trend Reversals: The crossover between the fast and slow EMAs applied to the DEMA provides early signals of potential trend reversals, allowing traders to position themselves in the market more effectively. Confirming Trend Direction: The combined effect of the DEMA and EMA crossovers helps confirm the strength of a trend, improving decision-making around trade entries and exits. Adapting to Different Market Conditions: The customizable parameters allow traders to adjust the sensitivity of the crossover signals, making the indicator suitable for both fast-moving markets and slower, trending environments.
Advantages and Strategic Value
The "Dema Ema Crossover" script offers a significant advantage by combining the smoothness of the DEMA with the accuracy of EMA crossovers. The DEMA’s ability to reduce lag while maintaining responsiveness makes it ideal for trend-following strategies, while the crossover between the fast and slow EMAs provides precise entry and exit points. This combination reduces false signals and helps traders adapt to changing market conditions, resulting in a more reliable and efficient trend-following system.
Alerts and Visual Cues
The script includes alert conditions to notify traders of key crossover events. The "Dema Ema Crossover Long" alert is triggered when the fast EMA crosses above the slow EMA, signaling a potential upward trend. Conversely, the "Dema Ema Crossover Short" alert signals a possible downward trend when the fast EMA crosses below the slow EMA. Visual cues such as colored fills between the two EMAs highlight these crossover points on the chart, helping traders quickly identify trend shifts.
Summary and Usage Tips
The "Dema Ema Crossover | viResearch" indicator provides traders with a powerful combination of the DEMA and EMA crossovers, offering a smooth yet responsive tool for detecting trend reversals and confirming trend direction. By incorporating this script into your trading strategy, you can improve your ability to capture trend changes with greater accuracy, reducing the impact of market noise. Whether you are focused on short-term market moves or long-term trends, the "Dema Ema Crossover" indicator offers a flexible and reliable solution for traders at all levels.
Note: Backtests are based on past results and are not indicative of future performance.
Multi-Timeframe 20 EMA Horizontal LinesOverview
This Multi-Timeframe 20 EMA indicator provides intelligent trend analysis by displaying your current timeframe EMA alongside relevant higher timeframe EMA levels as horizontal support/resistance lines. On lower timeframes, you see all higher EMA levels for comprehensive multi-timeframe confluence, while on higher timeframes, it filters out lower timeframe noise to maintain focus on macro trends. This allows traders to align short-term entries with long-term market structure, identifying high-probability setups where multiple timeframe EMAs converge while using the current timeframe EMA for precise timing.
Feature
Multi-Timeframe Horizontal EMA Lines
The indicator fetches and displays 20 EMAs from five higher timeframes:
Daily (D): Daily 20 EMA
Weekly (W): Weekly 20 EMA
Monthly (M): Monthly 20 EMA
Quarterly (Q): 3-Month 20 EMA
Half-Yearly (HY): 6-Month 20 EMA
Intelligent Timeframe Filtering
Smart Display Logic: Only shows EMAs from timeframes higher than your current chart timeframe
Prevents Redundancy: Automatically filters out lower timeframe EMAs to avoid clutter
Example: On a 4-hour chart, you'll see Daily, Weekly, Monthly, Quarterly, and Half-Yearly EMAs, but on a Weekly chart, you'll only see Weekly and higher timeframes
Half-Yearly (HY): 6-Month 20 EMA
Shows only current timeframe EMA with half-yearly horizontal line, filtering out all lower timeframes.
Quarterly (Q): 3-Month 20 EMA
Displays current timeframe EMA with quarterly and higher horizontal lines, hiding monthly, weekly, and daily EMAs.
Monthly (M): Monthly 20 EMA
Shows current timeframe EMA with monthly and higher horizontal EMAs, excluding weekly and daily timeframes.
Weekly (W): Weekly 20 EMA
Displays current timeframe EMA with weekly and higher horizontal EMA lines, filtering out daily timeframe.
Daily (D):
Shows current timeframe EMA with all higher timeframe horizontal EMAs (daily, weekly, monthly, quarterly, half-yearly).
Note: Make sure to enable Price-Line in Style Settings after Importing Script.
Scalping trading system based on 4 ema linesScalping Trading System Based on 4 EMA Lines
Overview:
This is a scalping trading strategy built on signals from 4 EMA moving averages: EMA(8), EMA(12), EMA(24) and EMA(72).
Conditions:
- Time frame: H1 (1 hour).
- Trading assets: Applicable to major currency pairs with high volatility
- Risk management: Use a maximum of 1-2% of capital for each transaction. The order holding time can be from a few hours to a few days, depending on the price fluctuation amplitude.
Trading rules:
Determine the main trend:
Uptrend: EMA(8), EMA(12) and EMA(24) are above EMA(72).
Downtrend: EMA(8), EMA(12) and EMA(24) are below EMA(72).
Trade in the direction of the main trend** (buy in an uptrend and sell in a downtrend).
Entry conditions:
- Only trade in a clearly trending market.
Uptrend:
- Wait for the price to correct to the EMA(24).
- Enter a buy order when the price closes above the EMA(24).
- Place a stop loss below the bottom of the EMA(24) candle that has just been swept.
Downtrend:
- Wait for the price to correct to the EMA(24).
- Enter a sell order when the price closes below the EMA(24).
- Place a stop loss above the top of the EMA(24) candle that has just been swept.
Take profit and order management:
- Take profit when the price moves 20 to 40 pips in the direction of the trade.
Use Trailing Stop to optimize profits instead of setting a fixed Take Profit.
Note:
- Do not trade within 30 minutes before and after the announcement of important economic news, as the price may fluctuate abnormally.
Additional filters:
To increase the success rate and reduce noise, this strategy uses additional conditions:
1. The price is calculated only when the candle closes (no repaint).
2. When sweeping through EMA(24), the price needs to close above EMA(24).
3. The closing price must be higher than 50% of the candle's length.
4. **The bottom of the candle sweeping through EMA(24) must be lower than the bottom of the previous candle (liquidity sweep).
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Alert function:
When the EMA(24) sweep conditions are met, the system will trigger an alert if you have set it up.
- Entry point: The closing price of the candle sweeping through EMA(24).
- Stop Loss:
- Buy Order: Place at the bottom of the sweep candle.
- Sell Order: Place at the top of the sweep candle.
---
Note:
This strategy is designed to help traders identify profitable trading opportunities based on trends. However, no strategy is 100% guaranteed to be successful. Please test it thoroughly on a demo account before using it.
EMA RSI Trend Reversal Ver.1Overview:
The EMA RSI Trend Reversal indicator combines the power of two well-known technical indicators—Exponential Moving Averages (EMAs) and the Relative Strength Index (RSI)—to identify potential trend reversal points in the market. The strategy looks for key crossovers between the fast and slow EMAs, and uses the RSI to confirm the strength of the trend. This combination helps to avoid false signals during sideways market conditions.
How It Works:
Buy Signal:
The Fast EMA (9) crosses above the Slow EMA (21), indicating a potential shift from a downtrend to an uptrend.
The RSI is above 50, confirming strong bullish momentum.
Visual Signal: A green arrow below the price bar and a Buy label are plotted on the chart.
Sell Signal:
The Fast EMA (9) crosses below the Slow EMA (21), indicating a potential shift from an uptrend to a downtrend.
The RSI is below 50, confirming weak or bearish momentum.
Visual Signal: A red arrow above the price bar and a Sell label are plotted on the chart.
Key Features:
EMA Crossovers: The Fast EMA crossing above the Slow EMA signals potential buying opportunities, while the Fast EMA crossing below the Slow EMA signals potential selling opportunities.
RSI Confirmation: The RSI helps confirm trend strength—values above 50 indicate bullish momentum, while values below 50 indicate bearish momentum.
Visual Cues: The strategy uses green arrows and red arrows along with Buy and Sell labels for clear visual signals of when to enter or exit trades.
Signal Interpretation:
Green Arrow / Buy Label: The Fast EMA (9) has crossed above the Slow EMA (21), and the RSI is above 50. This is a signal to buy or enter a long position.
Red Arrow / Sell Label: The Fast EMA (9) has crossed below the Slow EMA (21), and the RSI is below 50. This is a signal to sell or exit the long position.
Strategy Settings:
Fast EMA Length: Set to 9 (this determines how sensitive the fast EMA is to recent price movements).
Slow EMA Length: Set to 21 (this smooths out price movements to identify the broader trend).
RSI Length: Set to 14 (default setting to track momentum strength).
RSI Level: Set to 50 (used to confirm the strength of the trend—above 50 for buy signals, below 50 for sell signals).
Risk Management (Optional):
Use take profit and stop loss based on your preferred risk-to-reward ratio. For example, you can set a 2:1 risk-to-reward ratio (2x take profit for every 1x stop loss).
Backtesting and Optimization:
Backtest the strategy on TradingView by opening the Strategy Tester tab. This will allow you to see how the strategy would have performed on historical data.
Optimization: Adjust the EMA lengths, RSI period, and risk-to-reward settings based on your asset and time frame.
Limitations:
False Signals in Sideways Markets: Like any trend-following strategy, this indicator may generate false signals during periods of low volatility or sideways movement.
Not Suitable for All Market Conditions: This indicator performs best in trending markets. It may underperform in choppy or range-bound markets.
Strategy Example:
XRP/USD Example:
If you're trading XRP/USD and the Fast EMA (9) crosses above the Slow EMA (21), while the RSI is above 50, the indicator will signal a Buy.
Conversely, if the Fast EMA (9) crosses below the Slow EMA (21), and the RSI is below 50, the indicator will signal a Sell.
Bitcoin (BTC/USD):
On the BTC/USD chart, when the indicator shows a green arrow and a Buy label, it’s signaling a potential long entry. Similarly, a red arrow and Sell label indicate a short entry or exit from a previous long position.
Summary:
The EMA RSI Trend Reversal Indicator helps traders identify potential trend reversals with clear buy and sell signals based on the EMA crossovers and RSI confirmations. By using green arrows and red arrows, along with Buy and Sell labels, this strategy offers easy-to-understand visual signals for entering and exiting trades. Combine this with effective risk management and backtesting to optimize your trading performance.
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.
Fourier Transformed & Kalman Filtered EMA Crossover [Mattes]The Fourier Transformed & Kalman Filtered EMA Crossover (FTKF EMAC) is a trend-following indicator that leverages Fourier Transform approximation, Kalman Filtration, and two Exponential Moving Averages (EMAs) of different lengths to provide accurate and smooth market trend signals. By combining these three components, it captures the underlying market cycles, reduces noise, and produces actionable insights, making it suitable for detecting both emerging trends and confirming existing ones.
TECHNICALITIES:
>>> The Fourier Transform approximation is designed to identify dominant cyclical patterns in price action by focusing on key frequencies, while filtering out noise and less significant movements. It emphasizes the most meaningful price cycles, enabling the indicator to isolate important trends while ignoring minor fluctuations. This cyclical awareness adds an extra layer of depth to trend detection, allowing the EMAs to work with a cleaner and more reliable data set.
>>> The Kalman Filter adds dynamic noise reduction, adjusting its predictions of future price trends based on past and current data. As new price data comes in, the filter recalibrates itself to ensure that the price action remains smooth and devoid of erratic movements. This real-time adjustment is key to minimizing lag while avoiding false signals, which ensures that the EMAs react to more accurate and stable market data. The Kalman Filter’s ability to smooth price data without losing sensitivity to trend changes complements the Fourier approximation, ensuring a high level of precision in volatile and stable market environments.
>>> The EMA Crossover involves using two EMAs: a shorter EMA that reacts quickly to price movements and a longer EMA that responds more slowly. The shorter EMA is responsible for capturing immediate market shifts, detecting potential bullish or bearish trends. The longer EMA smooths out price fluctuations and provides trend confirmation, working with the shorter EMA to ensure the signals are reliable. When the shorter EMA crosses above the longer EMA, it indicates a bullish trend, likewise when it goes below the longer EMA, it signals a bearish trend. This setup provides a clear way to track market direction, with color-coded signals (green for bullish, red for bearish) for visual clarity. The flexibility of adjusting the EMA periods allows traders to fine-tune the indicator to their preferred timeframe and strategy, making it adaptable to different market conditions.
|-> A key technical aspect is that the first EMA should always be shorter than the second one. If the first EMA is longer than the second, the tool’s effectiveness is compromised because the faster EMA is designed to signal long conditions, while the longer one is made for signaling a bearish trend. Reversing their roles would lead to delayed or confused signals, reducing the indicator’s ability to detect trend shifts early and making it less efficient in volatile markets. This is the only key weakness of the indicator, failure to submit to this rule will result in confusion.
>>> These components work together like a clock to create a comprehensive and effective trend-following system. The Fourier approximation highlights key cyclical movements, the Kalman Filter refines these movements by removing noise, and the EMAs interpret the filtered data to generate actionable trend signals. Each component enhances the next, ensuring that the final output is both responsive and reliable, with minimal false signals or lag. creating an indicator using widespread concepts which haven't been combined before.
Summary
This indicator combines Fourier Transform approximation, Kalman Filtration, and two EMAs of different lengths to deliver accurate and timely trend-following signals. The Fourier approximation identifies dominant market cycles, while the Kalman Filter dynamically removes noise and refines the price data in real time. The two EMAs then use this filtered data to generate buy and sell signals based on their crossovers. The shorter EMA reacts quickly to price changes, while the longer EMA provides smoother trend confirmation. The components work in synergy to capture trends with minimal false signals or lag, ensuring traders can act promptly on market shifts. Customizable EMA periods make the tool adaptable to different market conditions, enhancing its versatility for various trading strategies.
To use the indicator, traders should adjust the EMA lengths based on their timeframe and strategy, ensuring that the shorter EMA remains shorter than the longer EMA to preserve the tool’s responsiveness. The color-coded signals offer visual clarity, making it easy to identify potential entry and exit points. This confluence of Fourier, Kalman, and EMA methodologies provides a smooth, highly effective trend-following tool that excels in both trending and ranging markets.
Long/Short EMA Premium [NL]1. EMA Calculation :
- The script calculates three Exponential Moving Averages (EMAs): EMA 1, EMA 2, and EMA 50.
- The lengths of EMA 1 and EMA 2 are customizable by the user inputs `ema1Length` and `ema2Length`, respectively.
- EMA 50 is fixed with a length of 50.
2. EMA Crossover Detection :
- The script detects crossovers between EMA 1 and EMA 2 using the `ta.crossover()` and `ta.crossunder()` functions, storing the crossover events in the `cross` variable.
3. Crossover Symbol :
- A triangle-up shape is plotted below the bars when there is a crossover between EMA 1 and EMA 2. This symbol visually indicates the crossover points.
4. Trade Signals :
- Long and short signals are generated based on the crossover events and the relationship between the closing price and EMA 1.
- For a long signal, EMA 1 must cross above EMA 2, and both the current and previous closing prices must be above EMA 1.
- For a short signal, EMA 1 must cross below EMA 2, and both the current and previous closing prices must be below EMA 1.
5. Stop Conditions :
- Stop conditions are used to exit long or short trades.
- If in a long trade, the script checks if the low of the previous candle crossed below EMA 1 and the high of the current candle is below EMA 1. If true, it triggers the "Stop Long" condition.
- If in a short trade, the script checks if the high of the previous candle crossed above EMA 1 and the low of the current candle is above EMA 1. If true, it triggers the "Stop Short" condition.
6. Plotting :
- The script plots EMA 1, EMA 2, and EMA 50 on the chart to visualize their movements.
7. Alerts :
- The script generates alerts for EMA crossovers, long and short signals, as well as stop long and stop short conditions, allowing traders to receive notifications when these events occur.
Overall, the script provides a comprehensive EMA crossover strategy with customizable parameters and clear trade signals and exit conditions.
Triple EMA Trend TP Strategy (Filtered Entries + Dynamic Exit)Overview
The Triple EMA Trend TP Strategy is a robust trend-following approach designed for clear, disciplined entries and exits. It leverages a triple EMA crossover for entry signals, combined with a long‑term SMA trend filter, a fixed take‑profit percentage, and a dynamic dual‑EMA exit mechanism to optimize performance and risk management.
Key Features
Triple EMA Crossover Entry
Detects momentum shifts by waiting for the fast EMA to cross above the slow EMA, signaling bullish momentum buildup.
Trend Filter (SMA)
Ensures trades are only taken when price is above the long-term trend (SMA), filtering out low-probability setups.
Take Profit (TP)
Applies a customizable fixed TP, e.g., defaulting to 9.8%, allowing disciplined profit-taking.
Dual EMA Exit
Uses two EMAs on a separate exit logic—if the short exit EMA undercuts the mid exit EMA, the strategy closes the position.
Adjustable Parameters
All key lengths—including fast, mid, slow entry EMAs, trend SMA, exit EMAs, and TP percentage—are user-configurable to suit different assets and timeframes.
Date Range Control
Users can define a backtest window with start and end dates, preventing misleading performance outside intended periods.
Flexible Position Management
Supports full‑equity position sizing, pyramiding up to 10 entries, and runs every tick for high precision.
Setup & Inputs
fastLen: Entry Fast EMA
midLen: Entry Mid EMA
slowLen: Entry Slow EMA
trendLen: Trend Filter SMA
tpPercent: Take Profit Percentage
exitFastLen: Exit Fast EMA
exitMidLen: Exit Mid EMA
startDate / endDate: Backtest time range
Why This Strategy Stands Out
This strategy marries classic trend-following principles with modern risk-control tactics, making it both intuitive and advanced. It balances aggressive entry signals with safety checks via trend validation and layered exit logic. The inclusion of a TP ensures profits are locked in, while the dual EMA exit adds adaptive flexibility to close positions when momentum fades.
How to Use & Customize
Configure Inputs
Adjust EMAs, trend length, and TP percentage to fit your asset and timeframe. For example, shorter EMAs suit intraday trading; longer ones work well for swing strategies.
Set Backtest Range
Use the start/end date fields to limit your testing to the most relevant data, reducing noise from irrelevant market periods.
Backtest & Optimize
Review the Strategy Tester’s performance metrics—Equity curve, drawdown, profit factor, trade list—to assess effectiveness.
Fine‑Tune
Tweak TP, EMAs, or trend length to optimize drawdowns, win rate, or return profile.
VHX EMA 135/315📈 EMA 135/315 Cross Strategy – Your Trend Compass with Smart Confirmations
🔍 Core Idea
The EMA 135/315 Cross strategy is a trend-following system.
It tracks two moving averages:
EMA 135 → the “fast” line that reacts to short-term price moves
EMA 315 → the “slow” line that reacts to the bigger trend
When the fast EMA crosses above the slow EMA → market momentum is turning up → BUY signal 🟢
When the fast EMA crosses below the slow EMA → momentum is turning down → SELL signal 🔴
This gives you a clear entry trigger — no guessing, no overcomplication.
✨ On Your Chart
BUY/SELL Arrows
🟢 Green arrow = bullish cross → trend turning up
🔴 Red arrow = bearish cross → trend turning down
Trend Info Panel (Top Left)
Current Trend: BUY / SELL / Neutral
Last Cross: how many bars ago it happened
EMA Gap in %: measures the strength of the trend
Status: “Approaching” if EMAs are getting close → possible cross soon
Automatic TP/SL Levels
📈 TP line (+2% from entry)
📉 SL line (–0.5% from entry)
Saves time — you instantly see your target and protection
EMA Distance Meter
Big % gap = strong trend momentum 🚀
Small % gap = weak or sideways market ⚠️
Real-Time Alerts
You get notified when a cross happens, even if you’re away from the screen
🧠 The Logic Behind It
The EMA 135 reacts faster → it reflects short-term momentum
The EMA 315 moves slower → it reflects the main trend
When the fast EMA overtakes the slow EMA: short-term strength now aligns with the long-term trend → higher probability of a sustained move
The gap % tells you how strong the alignment is — large gap = cleaner moves, small gap = market in transition
“Approaching” status warns that the EMAs are converging, which often happens before a reversal
📊 Boosting the Strategy with Volume Analysis
The EMA cross is a strong trigger, but volume confirms the quality of the move:
High Volume + Cross → more reliable signal, as strong market participation is pushing the trend
Low Volume + Cross → caution, the move might be weak or a false breakout
💡 Tip:
Check the volume histogram or a volume-based indicator (e.g., Volume Profile, OBV).
On a BUY signal: volume should spike above the recent average.
On a SELL signal: watch for strong selling volume bars.
📍 Adding Support & Resistance for Precision
Support and resistance levels help filter out bad trades and optimize entries:
Best BUY setups:
EMA 135 crosses above EMA 315 near a known support zone
Bonus if volume confirms the move
Avoid buying directly into a strong resistance
Best SELL setups:
EMA 135 crosses below EMA 315 near a known resistance zone
Bonus if selling volume is strong
Avoid selling directly into a major support
💡 Use tools like horizontal lines, previous highs/lows, and Volume Profile nodes to spot these zones.
📈 Best Usage Practices
Timeframes
Lower timeframes (1m–5m) → more signals, but more noise → best for scalping with extra filters
Always Combine With Confirmation
EMA Cross = Trigger
Volume spike = Confirmation
S/R zone in your favor = High-probability setup
Manage Risk
Start with the built-in TP/SL
Adjust SL if volatility is higher than usual
Consider trailing stop once price moves in your favor
Avoid Sideways Markets
If EMA gap % is very small and crosses happen often → stand aside until a clear direction forms
Use Alerts
Set alerts for BUY & SELL crosses so you never miss a setup
In short:
This isn’t just an EMA cross indicator — it’s a trend system with built-in risk management, strength measurement, and pre-trade preparation. Combine it with volume confirmation and smart use of support/resistance, and you turn a simple signal into a high-probability trading edge.
Combined EMA Technical AnalysisThis script is written in Pine Script (version 5) for TradingView and creates a comprehensive technical analysis indicator called "Combined EMA Technical Analysis." It overlays multiple technical indicators on a price chart, including Exponential Moving Averages (EMAs), VWAP, MACD, PSAR, RSI, Bollinger Bands, ADX, and external data from the S&P 500 (SPX) and VIX indices. The script also provides visual cues through colors, shapes, and a customizable table to help traders interpret market conditions.
Here’s a breakdown of the script:
---
### **1. Purpose**
- The script combines several popular technical indicators to analyze price trends, momentum, volatility, and market sentiment.
- It uses color coding (green for bullish, red for bearish, gray/white for neutral) and a table to display key information.
---
### **2. Custom Colors**
- Defines custom RGB colors for bullish (`customGreen`), bearish (`customRed`), and neutral (`neutralGray`) signals to enhance visual clarity.
---
### **3. User Inputs**
- **EMA Colors**: Users can customize the colors of five EMAs (8, 20, 9, 21, 50 periods).
- **MACD Settings**: Adjustable short length (12), long length (26), and signal length (9).
- **RSI Settings**: Adjustable length (14).
- **Bollinger Bands Settings**: Length (20), multiplier (2), and proximity threshold (0.1% of band width).
- **ADX Settings**: Adjustable length (14).
- **Table Settings**: Position (e.g., "Bottom Right") and text size (e.g., "Small").
---
### **4. Indicator Calculations**
#### **Exponential Moving Averages (EMAs)**
- Calculates five EMAs: 8, 20, 9, 21, and 50 periods based on the closing price.
- Used to identify short-term and long-term trends.
#### **Volume Weighted Average Price (VWAP)**
- Resets daily and calculates the average price weighted by volume.
- Color-coded: green if price > VWAP (bullish), red if price < VWAP (bearish), white if neutral.
#### **MACD (Moving Average Convergence Divergence)**
- Uses short (12) and long (26) EMAs to compute the MACD line, with a 9-period signal line.
- Displays "Bullish" (green) if MACD > signal, "Bearish" (red) if MACD < signal.
#### **Parabolic SAR (PSAR)**
- Calculated with acceleration factors (start: 0.02, increment: 0.02, max: 0.2).
- Indicates trend direction: green if price > PSAR (bullish), red if price < PSAR (bearish).
#### **Relative Strength Index (RSI)**
- Measures momentum over 14 periods.
- Highlighted in green if > 70 (overbought), red if < 30 (oversold), white otherwise.
#### **Bollinger Bands (BB)**
- Uses a 20-period SMA with a 2-standard-deviation multiplier.
- Color-coded based on price position:
- Green: Above upper band or close to it.
- Red: Below lower band or close to it.
- Gray: Neutral (within bands).
#### **Average Directional Index (ADX)**
- Manually calculates ADX to measure trend strength:
- Strong trend: ADX > 25.
- Very strong trend: ADX > 50.
- Direction: Bullish if +DI > -DI, bearish if -DI > +DI.
#### **EMA Crosses**
- Detects bullish (crossover) and bearish (crossunder) events for:
- EMA 9 vs. EMA 21.
- EMA 8 vs. EMA 20.
- Visualized with green (bullish) or red (bearish) circles.
#### **SPX and VIX Data**
- Fetches daily closing prices for the S&P 500 (SPX) and VIX (volatility index).
- SPX trend: Bullish if EMA 9 > EMA 21, bearish if EMA 9 < EMA 21.
- VIX levels: High (> 25, fear), Low (< 15, stability).
- VIX color: Green if SPX bullish and VIX low, red if SPX bearish and VIX high, white otherwise.
---
### **5. Visual Outputs**
#### **Plots**
- EMAs, VWAP, and PSAR are plotted on the chart with their respective colors.
- EMA crosses are marked with circles (green for bullish, red for bearish).
#### **Table**
- Displays a summary of indicators in a customizable position and size.
- Indicators shown (if enabled):
- EMA 8/20, 9/21, 50: Green dot if bullish, red if bearish.
- VWAP: Green if price > VWAP, red if price < VWAP.
- MACD: Green if bullish, red if bearish.
- MACD Zero: Green if MACD > 0, red if MACD < 0.
- PSAR: Green if price > PSAR, red if price < PSAR.
- ADX: Arrows for very strong trends (↑/↓), dots for weaker trends, colored by direction.
- Bollinger Bands: Arrows (↑/↓) or dots based on price position.
- RSI: Numeric value, colored by overbought/oversold levels.
- VIX: Numeric value, colored based on SPX trend and VIX level.
---
### **6. Alerts**
- Triggers alerts for EMA 8/20 crosses:
- Bullish: "EMA 8/20 Bullish Cross on Candle Close!"
- Bearish: "EMA 8/20 Bearish Cross on Candle Close!"
---
### **7. Key Features**
- **Flexibility**: Users can toggle indicators on/off in the table and adjust parameters.
- **Visual Clarity**: Consistent use of green (bullish), red (bearish), and neutral colors.
- **Comprehensive**: Combines trend, momentum, volatility, and market sentiment indicators.
---
### **How to Use**
1. Add the script to TradingView.
2. Customize inputs (colors, lengths, table position) as needed.
3. Interpret the chart and table:
- Green signals suggest bullish conditions.
- Red signals suggest bearish conditions.
- Neutral signals indicate indecision or consolidation.
4. Set up alerts for EMA crosses to catch trend changes.
This script is ideal for traders who want a multi-indicator dashboard to monitor price action and market conditions efficiently.
Tandem EMA TrendsThis indicator helps to identify trends using 2 (tandem) EMAs: a fast EMA and a slow EMA. Set the lengths of the EMAs in the inputs (fast EMA should be a smaller number than the slow EMA).
The trend is bullish if the current value of the fast EMA > current value of the slow EMA AND the current value of the fast EMA > the prior bar's value of the fast EMA.
The trend is bearish if the current value of the fast EMA < current value of the slow EMA AND the current value of the fast EMA < the prior bar's value of the fast EMA.
The fast EMA is countertrend to the slow EMA if either of the following 2 conditions exist:
The current value of the fast EMA > current value of the slow EMA AND the current value of the fast EMA < the prior bar's value of the fast EMA (bullish countertrend).
-OR-
The current value of the fast EMA < current value of the slow EMA AND the current value of the fast EMA > the prior bar's value of the fast EMA (bearish countertrend).
Use this script to set custom alerts based off of the current trend like sending webhooks when specific conditions exist.
Customize the colors of the plots.
Daniels Script v2 EMA 4h y DTitle:
"EMA 200 Dynamic Projection on 4H and Daily Charts"
Description:
"This script is designed to provide traders with a comprehensive view of market trends by displaying the 200-period Exponential Moving Average (EMA) on both 4-hour and daily charts simultaneously. Unlike typical EMA representations, this script enhances user decision-making by projecting the potential future path of these EMAs using a dynamic slope calculation.
The dynamic projection feature calculates the slope based on recent changes in the EMA, allowing traders to visualize potential future trends more accurately. This innovative approach helps in identifying potential areas of support and resistance before they are fully formed, offering traders a strategic advantage in planning their entries and exits.
Key Features:
Dual Time Frame Analysis: View 200-period EMAs for both 4-hour and daily charts on a single graph.
Dynamic EMA Projections: Projected using a calculated slope from recent EMA changes, presented as dotted lines for clear distinction.
Enhanced Trend Visualization: Helps in recognizing trend continuations or reversals early, aiding in risk management and decision-making processes.
Usage:
Simply add the script to your chart, and the EMAs along with their projections will automatically be displayed. The 4-hour EMA is shown in green, while the daily EMA is in red. Projections extend from the last known data point, providing a visual guide to potential future movements.
This script is unique in its approach to combining real-time EMA analysis with predictive modeling, making it a valuable tool for traders looking to enhance their technical analysis capabilities."
## SPANISH
Título del Script:
"Proyección Dinámica de la EMA 200 en Gráficos de 4H y Diarios"
Descripción del Script:
"Este script está diseñado para proporcionar a los traders una visión integral de las tendencias del mercado al mostrar la Media Móvil Exponencial (EMA) de 200 periodos tanto en los gráficos de 4 horas como diarios simultáneamente. A diferencia de las representaciones típicas de la EMA, este script mejora la toma de decisiones del usuario al proyectar el posible camino futuro de estas EMAs utilizando un cálculo de pendiente dinámico.
La función de proyección dinámica calcula la pendiente basada en cambios recientes en la EMA, permitiendo a los traders visualizar tendencias futuras potenciales con mayor precisión. Este enfoque innovador ayuda a identificar áreas potenciales de soporte y resistencia antes de que se formen completamente, ofreciendo a los traders una ventaja estratégica en la planificación de sus entradas y salidas.
Características Clave:
Análisis de Doble Marco Temporal: Visualiza las EMAs de 200 periodos para los gráficos de 4 horas y diarios en un solo gráfico.
Proyecciones Dinámicas de la EMA: Proyectadas utilizando una pendiente calculada a partir de cambios recientes en la EMA, presentadas como líneas punteadas para una clara distinción.
Visualización Mejorada de Tendencias: Ayuda en el reconocimiento temprano de continuaciones o reversos de tendencias, asistiendo en la gestión de riesgos y en los procesos de toma de decisiones.
Uso:
Simplemente añade el script a tu gráfico, y las EMAs junto con sus proyecciones se mostrarán automáticamente. La EMA de 4 horas se muestra en verde, mientras que la EMA diaria está en rojo. Las proyecciones se extienden desde el último punto de datos conocido, proporcionando una guía visual hacia movimientos futuros potenciales.
Este script es único en su enfoque de combinar análisis de EMA en tiempo real con modelado predictivo, convirtiéndolo en una herramienta valiosa para traders que buscan mejorar sus capacidades de análisis técnico."
200 EMA w/ Ticker Memory200 EMA w/ Ticker Memory — Multi-Symbol & Multi-Timeframe EMA Tracker with Alerts
Overview
The 200 EMA w/ Ticker Memory indicator allows you to monitor the 200-period Exponential Moving Average (EMA) across multiple symbols and timeframes. Designed for traders managing multiple tickers, it provides customizable timeframe inputs per symbol and instant alerts on price touches of the 200 EMA.
Key Features
Multi-symbol support: Configure up to 20 different symbols, each with its own timeframe setting.
Flexible timeframe input: Assign specific timeframes per symbol or use a default timeframe fallback.
Accurate 200 EMA calculation: Uses request.security to fetch 200 EMA from the symbol-specific timeframe.
Visual EMA plots: Displays both the EMA on the selected timeframe and the EMA on the current chart timeframe for comparison.
Touch alerts: Configurable alerts when price “touches” the 200 EMA within a user-defined sensitivity percentage.
Ticker memory: Remembers your configured symbols and displays them in an on-chart table.
Compact info table: Displays current symbol status, alert settings, and timeframe in a clean, transparent table overlay.
How to Use
Configure Symbols and Timeframes:
Input your desired symbols (up to 20) and their respective timeframes under the “Symbol Settings” groups in the indicator’s settings pane.
Set Default Timeframe:
Choose a default timeframe to be used when no specific timeframe is assigned for a symbol.
Adjust Alert Settings:
Enable or disable alerts and set the touch sensitivity (% distance from EMA to trigger alerts).
Alerts
Alerts trigger once per bar when the price touches the 200 EMA within the defined sensitivity threshold.
Alert messages include:
Symbol / Current price / EMA value / EMA timeframe used / Chart timeframe / Timestamp
Customization
200 EMA Color: Change the line color for better visibility.
Touch Sensitivity: Fine-tune how close price must be to the EMA to count as a touch (default 0.1%).
Enable Touch Alerts: Turn on/off alert notifications easily.
For:
- Swing traders monitoring multiple stocks or assets.
- Day traders watching key EMA levels on different timeframes.
- Analysts requiring a quick visual and alert system for 200 EMA touches.
- Portfolio managers tracking key technical levels across various securities.
Limitations
Supports up to 20 configured symbols (can be extended manually if needed).
Works best on charts with reasonable bar frequency due to request.security usage.
Alert frequency is limited to once per bar for clarity.
Disclaimer
This indicator is provided “as-is” for educational and informational purposes only. It does not guarantee trading success or financial gain.
Consecutive Candles Above/Below EMADescription:
This indicator identifies and highlights periods where the price remains consistently above or below an Exponential Moving Average (EMA) for a user-defined number of consecutive candles. It visually marks these sustained trends with background colors and labels, helping traders spot strong bullish or bearish market conditions. Ideal for trend-following strategies or identifying potential trend exhaustion points, this tool provides clear visual cues for price behavior relative to the EMA.
How It Works:
EMA Calculation: The indicator calculates an EMA based on the user-specified period (default: 100). The EMA is plotted as a blue line on the chart for reference.
Consecutive Candle Tracking: It counts how many consecutive candles close above or below the EMA:
If a candle closes below the EMA, the "below" counter increments; any candle closing above resets it to zero.
If a candle closes above the EMA, the "above" counter increments; any candle closing below resets it to zero.
Highlighting Trends: When the number of consecutive candles above or below the EMA meets or exceeds the user-defined threshold (default: 200 candles):
A translucent red background highlights periods where the price has been below the EMA.
A translucent green background highlights periods where the price has been above the EMA.
Labeling: When the required number of consecutive candles is first reached:
A red downward arrow label with the text "↓ Below" appears for below-EMA streaks.
A green upward arrow label with the text "↑ Above" appears for above-EMA streaks.
Usage:
Trend Confirmation: Use the highlights and labels to confirm strong trends. For example, 200 candles above the EMA may indicate a robust uptrend.
Reversal Signals: Prolonged streaks (e.g., 200+ candles) might suggest overextension, potentially signaling reversals.
Customization: Adjust the EMA period to make it faster or slower, and modify the candle count to make the indicator more or less sensitive to trends.
Settings:
EMA Length: Set the period for the EMA calculation (default: 100).
Candles Count: Define the minimum number of consecutive candles required to trigger highlights and labels (default: 200).
Visuals:
Blue EMA line for tracking the moving average.
Red background for sustained below-EMA periods.
Green background for sustained above-EMA periods.
Labeled arrows to mark when the streak threshold is met.
This indicator is a powerful tool for traders looking to visualize and capitalize on persistent price trends relative to the EMA, with clear, customizable signals for market analysis.
Explain EMA calculation
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[SM-042] EMA 5-8-13 with ADX FilterWhat is the strategy?
The strategy combines three exponential moving averages (EMAs) — 5, 8, and 13 periods — with an optional ADX (Average Directional Index) filter. It is designed to enter long or short positions based on EMA crossovers and to exit positions when the price crosses a specific EMA. The ADX filter, if enabled, adds a condition that only allows trades when the ADX value is above a certain threshold, indicating trend strength.
Who is it for?
This strategy is for traders leveraging EMAs and trend strength indicators to make trade decisions. It can be used by anyone looking for a simple trend-following strategy, with the flexibility to adjust for trend strength using the ADX filter.
When is it used?
- **Long trades**: When the 5-period EMA crosses above the 8-period EMA, with an optional ADX condition (if enabled) that requires the ADX value to be above a specified threshold.
- **Short trades**: When the 5-period EMA crosses below the 8-period EMA, with the ADX filter again optional.
- **Exits**: The strategy exits a long position when the price falls below the 13-period EMA and exits a short position when the price rises above the 13-period EMA.
Where is it applied?
This strategy is applied on a chart with any asset on TradingView, with the EMAs and ADX plotted for visual reference. The strategy uses `strategy.entry` to open positions and `strategy.close` to close them based on the set conditions.
Why is it useful?
This strategy helps traders identify trending conditions and filter out potential false signals by using both EMAs (to capture short-term price movements) and the ADX (to confirm the strength of the trend). The ADX filter can be turned off if not desired, making the strategy flexible for both trending and range-bound markets.
How does it work?
- **EMA Crossover**: The strategy enters a long position when the 5-period EMA crosses above the 8-period EMA, and enters a short position when the 5-period EMA crosses below the 8-period EMA.
- **ADX Filter**: If enabled, the strategy checks whether the ADX value is above a set threshold (default is 20) before allowing a trade.
- **Exit Conditions**: Long positions are closed when the price falls below the 13-period EMA, and short positions are closed when the price rises above the 13-period EMA.
- **Plotting**: The strategy plots the three EMAs and the ADX value on the chart for visualization. It also displays a horizontal line at the ADX threshold.
This setup allows for clear decision-making based on the interaction between different time-frame EMAs and trend strength as indicated by ADX.
Adv EMA Cloud v6 (ADX, Alerts)Summary:
This indicator provides a multi-faceted view of market trends using Exponential Moving Averages (EMAs) arranged in visually intuitive clouds, enhanced with an optional ADX-based range filter and configurable alerts for key market conditions. It aims to help traders quickly gauge trend alignment across short, medium, and long timeframes while filtering signals during potentially choppy market conditions.
Key Features:
Multiple EMAs: Displays 10-period (Fast), 20-period (Mid), and 50-period (Slow) EMAs.
Long-Term Trend Filter: Includes a 200-period EMA to provide context for the overall dominant trend direction.
Dual EMA Clouds:
Fast/Mid Cloud (10/20 EMA): Fills the area between the 10 and 20 EMAs. Defaults to Green when 10 > 20 (bullish short-term momentum) and Red when 10 < 20 (bearish short-term momentum).
Mid/Slow Cloud (20/50 EMA): Fills the area between the 20 and 50 EMAs. Defaults to Aqua when 20 > 50 (bullish mid-term trend) and Fuchsia when 20 < 50 (bearish mid-term trend).
Optional ADX Range Filter: Uses the Average Directional Index (ADX) to identify potentially non-trending or choppy markets. When enabled and ADX falls below a user-defined threshold, the EMA clouds will turn grey, visually warning that trend-following signals may be less reliable.
Configurable Alerts: Provides several built-in alert conditions using Pine Script's alertcondition function:
Confluence Condition: Triggers when a 10/20 EMA crossover occurs while both EMA clouds show alignment (both bullish/green/aqua or both bearish/red/fuchsia) and price respects the 200 EMA filter and the ADX filter indicates a trend (if filters are enabled).
MA Filter Cross: Triggers when price crosses above or below the 200 EMA filter line.
Full Alignment Start: Triggers on the first bar where full bullish or bearish alignment occurs (both clouds aligned + MA filter respected + ADX trending, if filters are enabled).
How It Works:
EMA Calculation: Standard Exponential Moving Averages are calculated for the 10, 20, 50, and 200 periods based on the closing price.
Cloud Creation: The fill() function visually shades the area between the 10 & 20 EMAs and the 20 & 50 EMAs.
Cloud Coloring: The color of each cloud is determined by the relationship between the two EMAs that define it (e.g., if EMA 10 is above EMA 20, the first cloud is bullish-colored).
ADX Filter Logic: The script calculates the ADX value. If the "Use ADX Trend Filter?" input is checked and the calculated ADX is below the specified "ADX Trend Threshold", the script considers the market potentially ranging.
ADX Visual Effect: During detected ranging periods (if the ADX filter is active), the plotCloud12Color and plotCloud23Color variables are assigned a neutral grey color instead of their normal bullish/bearish colors before being passed to the fill() function.
Alert Logic: Boolean variables track the specific conditions (crossovers, cloud alignment, filter positions, ADX state). The alertcondition() function creates triggerable alerts based on these pre-defined conditions.
Potential Interpretation (Not Financial Advice):
Trend Alignment: When both clouds share the same directional color (e.g., both bullish - Green & Aqua) and price is on the corresponding side of the 200 EMA filter, it may suggest a stronger, more aligned trend. Conversely, conflicting cloud colors may indicate indecision or transition.
Dynamic Support/Resistance: The EMA lines themselves (especially the 20, 50, and 200) can sometimes act as dynamic levels where price might react.
Range Warning: Greyed-out clouds (when ADX filter is enabled) serve as a visual warning that trend-based strategies might face increased difficulty or whipsaws.
Confluence Alerts: The specific confluence alerts signal moments where multiple conditions align (crossover + cloud agreement + filters), which some traders might view as higher-probability setups.
Customization:
All EMA lengths (10, 20, 50, 200) are adjustable via the Inputs menu.
The ADX length and threshold are configurable.
The MA Trend Filter and ADX Trend Filter can be independently enabled or disabled.
Disclaimer:
This indicator is provided for informational and educational purposes only. Trading financial markets involves significant risk. Past performance is not indicative of future results. Always conduct your own thorough analysis and consider your risk tolerance before making any trading decisions. This indicator should be used in conjunction with other analysis methods and tools. Do not trade based solely on the signals or visuals provided by this indicator.
Supertrend and Fast and Slow EMA StrategyThis strategy combines Exponential Moving Averages (EMAs) and Average True Range (ATR) to create a simple, yet effective, trend-following approach. The strategy filters out fake or sideways signals by incorporating the ATR as a volatility filter, ensuring that trades are only taken during trending conditions. The key idea is to buy when the short-term trend (Fast EMA) aligns with the long-term trend (Slow EMA), and to avoid trades during low volatility periods.
How It Works:
EMA Crossover:
1). Buy Signal: When the Fast EMA (shorter-term, e.g., 20-period) crosses above the Slow EMA (longer-term, e.g., 50-period), this indicates a potential uptrend.
2). Sell Signal: When the Fast EMA crosses below the Slow EMA, this indicates a potential downtrend.
ATR Filter:
1). The ATR (Average True Range) is used to measure market volatility.
2). Trending Market: If the ATR is above a certain threshold, it indicates high volatility and a trending market. Only when ATR is above the threshold will the strategy generate buy/sell signals.
3). Sideways Market: If ATR is low (sideways or choppy market), the strategy will suppress signals to avoid entering during non-trending conditions.
When to Buy:
1). Condition 1: The Fast EMA crosses above the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, indicating that the market is trending (not sideways or choppy).
When to Sell:
1). Condition 1: The Fast EMA crosses below the Slow EMA.
2). Condition 2: The ATR is above the defined threshold, confirming that the market is in a downtrend.
When Not to Enter the Trade:
1). Sideways Market: If the ATR is below the threshold, signaling low volatility and sideways or choppy market conditions, the strategy will not trigger any buy or sell signals.
2). False Crossovers: In low volatility conditions, price action tends to be noisy, which could lead to false signals. Therefore, avoiding trades during these periods reduces the risk of false breakouts.
Additional Factors to Consider Adding:
=> RSI (Relative Strength Index): Adding an RSI filter can help confirm overbought or oversold conditions to avoid buying into overextended moves or selling too low.
1). RSI Buy Filter: Only take buy signals when RSI is below 70 (avoiding overbought conditions).
2). RSI Sell Filter: Only take sell signals when RSI is above 30 (avoiding oversold conditions).
=> MACD (Moving Average Convergence Divergence): Using MACD can help validate the strength of the trend.
1). Buy when the MACD histogram is above the zero line and the Fast EMA crosses above the Slow EMA.
2). Sell when the MACD histogram is below the zero line and the Fast EMA crosses below the Slow EMA.
=> Support/Resistance Levels: Adding support and resistance levels can help you understand market structure and decide whether to enter or exit a trade.
1). Buy when price breaks above a significant resistance level (after a valid buy signal).
2). Sell when price breaks below a major support level (after a valid sell signal).
=> Volume: Consider adding a volume filter to ensure that buy/sell signals are supported by strong market participation. You could only take signals if the volume is above the moving average of volume over a certain period.
=> Trailing Stop Loss: Instead of a fixed stop loss, use a trailing stop based on a percentage or ATR to lock in profits as the trade moves in your favor.
=> Exit Signals: Besides the EMA crossover, consider adding Take Profit or Stop Loss levels, or even using a secondary indicator like RSI to signal an overbought/oversold condition and exit the trade.
Example Usage:
=> Buy Example:
1). Fast EMA (20-period) crosses above the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is below 70, the buy signal is further confirmed as not being overbought.
=> Sell Example:
1). Fast EMA (20-period) crosses below the Slow EMA (50-period).
2). The ATR is above the threshold, confirming that the market is trending.
3). Optionally, if RSI is above 30, the sell signal is further confirmed as not being oversold.
Conclusion:
This strategy helps to identify trending markets and filters out sideways or choppy market conditions. By using Fast and Slow EMAs combined with the ATR volatility filter, it provides a reliable approach to catching trending moves while avoiding false signals during low-volatility, sideways markets.
Adaptive 12/48 EMAThe Adaptive 12/48 EMA is a trend-following indicator that dynamically changes color based on price positioning relative to key exponential moving averages (EMAs).
EMA Calculation:
The script calculates three EMAs—9 EMA (white), 12 EMA (adaptive color), and 48 EMA (adaptive color).
Trend Confirmation:
The 12 EMA turns green when the price (open, close, and low) is fully above it, indicating bullish momentum. The 12 EMA turns red when the price is fully below it, signaling bearish conditions.
Long-Term Trend (48 EMA):
The 48 EMA turns purple when the 12 EMA is above it, confirming an uptrend. The 48 EMA turns pink when the 12 EMA is below it, confirming a downtrend. Both EMAs turn gray when there's no clear trend.
How to Benefit from It:
Trend Trading: Use green/red shifts in the 12 EMA to time entries in the direction of momentum.
Trend Strength Confirmation: The 48 EMA color change helps determine the longer-term trend direction.
Confluence with Other Indicators: Works well with volume indicators or RSI for confirmation before entering trades.
This indicator provides a clear visual representation of trend strength and direction, helping traders make informed decisions based on price structure.
EMA Study Script for Price Action Traders, v2JR_EMA Research Tool Documentation
Version 2 Enhancements
Version 2 of the JR_EMA Research Tool introduces several powerful features that make it particularly valuable for studying price action around Exponential Moving Averages (EMAs). The key improvements focus on tracking and analyzing price-EMA interactions:
1. Cross Detection and Counting
- Implements flags for crossing bars that instantly identify when price crosses above or below the EMA
- Maintains running counts of closes above and below the EMA
- This feature helps students understand the persistence of trends and the frequency of EMA interactions
2. Bar Number Tracking
- Records the specific bar number when EMA crosses occur
- Stores the previous crossing bar number for reference
- Enables precise measurement of time between crosses, helping identify typical trend durations
3. Variable Reset Management
- Implements sophisticated reset logic for all counting variables
- Ensures accuracy when analyzing multiple trading sessions
- Critical for maintaining clean data when studying patterns across different timeframes
4. Cross Direction Tracking
- Monitors the direction of the last EMA cross
- Helps students identify the current trend context
- Essential for understanding trend continuation vs reversal scenarios
Educational Applications
Price-EMA Relationship Studies
The tool provides multiple ways to study how price interacts with EMAs:
1. Visual Analysis
- Customizable EMA bands show typical price deviation ranges
- Color-coded fills help identify "normal" vs "extreme" price movements
- Three different band calculation methods offer varying perspectives on price volatility
2. Quantitative Analysis
- Real-time tracking of closes above/below EMA
- Running totals help identify persistent trends
- Cross counting helps understand typical trend duration
Research Configurations
EMA Configuration
- Adjustable EMA period for studying different trend timeframes
- Customizable EMA color for visual clarity
- Ideal for comparing different EMA periods' effectiveness
Bands Configuration
Three distinct calculation methods:
1. Full Average Bar Range (ABR)
- Uses the entire range of price movement
- Best for studying overall volatility
2. Body Average Bar Range
- Focuses on the body of the candle
- Excellent for studying conviction in price moves
3. Standard Deviation
- Traditional statistical approach
- Useful for comparing to other technical studies
Signal Configuration
- Optional signal plotting for entry/exit studies
- Helps identify potential trading opportunities
- Useful for backtesting strategy ideas
Using the Tool for Study
Basic Analysis Steps
1. Start with the default 20-period EMA
2. Observe how price interacts with the EMA line
3. Monitor the data window for quantitative insights
4. Use band settings to understand normal price behavior
Advanced Analysis
1. Pattern Recognition
- Use the cross counting system to identify typical pattern lengths
- Study the relationship between cross frequency and trend strength
- Compare different timeframes for fractal analysis
2. Volatility Studies
- Compare different band calculation methods
- Identify market regimes through band width changes
- Study the relationship between volatility and trend persistence
3. Trend Analysis
- Use the closing price count system to measure trend strength
- Study the relationship between trend duration and subsequent reversals
- Compare different EMA periods for optimal trend following
Best Practices for Research
1. Systematic Approach
- Start with longer timeframes and work down
- Document observations about price behavior in different market conditions
- Compare results across multiple symbols and timeframes
2. Data Collection
- Use the data window to record significant events
- Track the number of bars between crosses
- Note market conditions when signals appear
3. Optimization Studies
- Test different EMA periods for your market
- Compare band calculation methods for your trading style
- Document which settings work best in different market conditions
Technical Implementation Notes
This tool is particularly valuable for educational purposes because it combines visual and quantitative analysis in a single interface, allowing students to develop both intuitive and analytical understanding of price-EMA relationships.
EMA SHIFT & PARALLEL [n_dot]BINANCE:ETHUSDT.P
This strategy was developed for CRYPTO FUTURES, (the settings for ETHUSDT.P) . I aimed for the strategy to function in a live environment, so I focused on making its operation realistic:
When determining the position, only 80% (adjustable) of the available cash is invested to reduce the risk of position liquidation.
I account for a 0.05% commission, typical on the futures market, for each entry and exit.
Concept:
I modified a simple, well-known method: the crossover of two exponential moving averages (FAST, SLOW) generates the entry and exit signals.
I enhanced the base idea as follows:
For the fast EMA, I incorporated a multiplier (offset) to filter out market noise and focus only on strong signals.
I use different EMAs for long and short entry points; both have their own FAST and SLOW EMAs and their own offset. For longs, the FAST EMA is adjusted downward (<1), while for shorts, it is adjusted upward (>1). Consequently, the signal is generated when the modified FAST EMA crosses the SLOW EMA.
Risk Management:
The position includes the following components:
Separate stop-losses for long and short positions.
Separate trailers for long and short positions.
The strategy operates so that the entry point is determined by the EMA crossover, while the exit is governed only by the Stop Loss or Trailer. Optionally, it can be set to close the position at the EMA recrossing ("Close at Signal").
Trailer Operation:
An entry percentage and offset are defined. The trailer activates when the price surpasses the entry price, calculated automatically by the system.
The trailer closes the position when the price drops by the offset percentage from the highest reached price.
Example for trailer:
Purchase Price = 100
Trailer Enter = 5% → Activation Price = 105 (triggers trailer if market price crosses it).
Trailer Offset = 2%
If the price rises to 110, the exit price becomes 107.8.
If the price goes to 120, the exit price becomes 117.6.
If the price falls below 117.6, the trailer closes the position.
Settings:
Source: Determines the market price reference.
End Close: Closes positions at the end of the simulation to avoid "shadow positions" and provide an objective result.
Lot proportional to free cash (%): Only a portion of free cash is invested to meet margin requirements.
Plot Short, Plot Long: Simplifies displayed information by toggling indicator lines on/off.
Long Position (toggleable):
EMA Fast ws: Window size for FAST EMA.
EMA Slow ws: Window size for SLOW EMA.
EMA Fast down shift: Adjustment factor for FAST EMA.
Stop Loss long (%): Percent drop to close the position.
Trailer enter (%): Percent above the purchase price to activate the trailer.
Trailer offset (%): Percent drop to close the position.
Short Position (toggleable):
EMA Fast ws: Window size for FAST EMA.
EMA Slow ws: Window size for SLOW EMA.
EMA Fast up shift: Adjustment factor for FAST EMA.
Stop Loss short (%): Percent rise to close the position.
Trailer enter (%): Percent below the purchase price to activate the trailer.
Trailer offset (%): Percent rise to close the position.
Operational Framework:
If in a long position and a short EMA crossover occurs, the strategy closes the long and opens a short (flip).
If in a short position and a long EMA crossover occurs, the strategy closes the short and opens a long (flip).
A position can close in three ways:
Stop Loss
Trailer
Signal Recrossing
If none are active, the position remains open until the end of the simulation.
Observations:
Shifts significantly deviating from 1 increase overfitting risk. Recommended ranges: 0.96–0.99 (long) and 1.01–1.05 (short).
The strategy's advantage lies in risk management, crucial in leveraged futures markets. It operates with relatively low DrawDown.
Recommendations:
Bullish Market: Higher entry threshold (e.g., 6%) and larger offset (e.g., 3%).
Volatile/Sideways Market: Tighter parameters (e.g., 3%, 1%).
The method is stable, and minor parameter adjustments do not significantly impact results, helping assess overfitting: if small changes lead to drastic differences, the strategy is over-optimized.
EMA Settings: Adjust FAST and SLOW EMAs based on the asset's volatility and cyclicality.
On the crypto market, especially in the Futures market, short time periods (1–15 minutes) often show significant noise, making patterns/repetitions hard to identify. I recommend setting the interval to at least 1 hour.
I hope this contributes to your success!
