Aggregated BTC VolumeTracks BTC volume since a desired date and time, lets you set a volume goal to be notified upon hitting with an alert.
Indikatoren und Strategien
CANDLESThe script is designed to display Higher Timeframe (HTF) candles on a chart, with a maximum of 6 candle sets
Trend Indicator with ArrowsTrend Indicator with arrows is a NoBrainer indicator to see the trend clearly.
UpTrend is defined as a candle closing above previous high. I
DownTrend is defined as a candle closing below previous low
A consolidation is defined as a candle closing inside previous candle high low.
UpTrend - Indicated with a green arrow below the candle with the current indicator.
DownTrend - ndicated with a red arrow above the candle with the current indicator.
So How to use this Indicator?
Identify zones of consolidation where the indicator doesn't show any arrows. Upon shift from consolidation to UpTrend or DownTrend take a entry. This is one way.
Second and most useful way is wait for Support or resistant hit.
If it's a support. Upon support hit wait for Consolidation, DownTrend and then UpTrend/(Consolidation again with uptrend) for long entry.
If its a resistance. Upon resistance hit wait for Consolidation, Uptrend and then DownTrend/(Consolidation again with DownTrend) for short Entry.
AlphaFlow: Oscillator Panelv2AlphaFlow: Oscillator Panel v2 – CryptoFace-Inspired Multi-Oscillator with Smart Signal Labels
This script is a tribute to the legendary CryptoFace and inspired by the visual power of Market Cipher. AlphaFlow expands on that concept with customization options, real-time confluence detection, and intelligent wave labeling for entries and exits.
Designed for discretionary trading, AlphaFlow offers a fully modular oscillator panel built from WaveTrend, RSI, VWAP-MACD, BBWP, Hybrid Money Flow, and HTF OBV Bias.
🎨 Visual Customization (Style Tab)
You can style this indicator to match your preferred look:
💠 Set WT fill area to blue @ 32% to get that Market Cipher vibe
💰 Set Hybrid Money Flow to Area style @ 80% opacity for clearer flow visualization
🔵 Change crosses to circles on WaveTrend turns for a cleaner chart
Everything is visible, togglable, and stylable via the Style tab.
🛠️ Inputs Panel (How to Tune It)
The Inputs tab gives you full control over:
WaveTrend lengths and OB/OS levels
RSI thresholds
BBWP squeeze lookbacks
MFI & CMF money flow weighting
Higher Timeframe (HTF) setting
✅ Suggestion: Try these timeframe combos for high-confidence MTF setups:
LTF (chart) HTF suggestion
1m or 3m 15m – 30m
5m 1h
15m 4h
1h 1D
4h 1D / 1W
🧠 v2 Features – Signal Labels: A / T / 👀
These new chart labels give you clear signals within structure:
🅰️ A = Anchor
A possible bottom/top forming, deep oversold/overbought WT1 pivot.
🟢 T = Trigger
Momentum confirmation after Anchor — your potential entry zone.
👀 Snake Eyes
Two Anchors forming within proximity — high-probability reversal signal.
These fire in real-time, based on wave structure — not repainting.
⚡ Multi-Timeframe Confluence Table
A real-time panel shows aligned conditions across:
WT1 crossovers (LTF & HTF)
RSI > 50 on both frames
VWAP MACD strength
OBV HTF bias (rising/falling)
When all are aligned ➜ “⚡ Fire Confirmed” shows up in the panel = high probability setup
🔐 License & Originality
Open Source | Pine Script™ v5
No repainting | No lookahead bias
Built from scratch to echo the visual experience of CryptoFace's Market Cipher, while using public indicators and original logic
This script is for educational, discretionary, and strategic use only — no auto buy/sell logic.
What Makes This Script Unique
AlphaFlow is not just a mashup of indicators — it’s a purpose-built multi-oscillator framework designed around real-world discretionary flow trading.
While inspired by Market Cipher’s visual principles, AlphaFlow introduces:
✅ Wave sequence signal labeling (Anchor / Trigger / Snake Eyes) to visually track pivot-confirmation momentum patterns in real time — this is not available in Market Cipher or standard indicators
✅ A Hybrid Money Flow Engine combining MFI + CMF into a single normalized flow stream
✅ Real-time Multi-Timeframe Confluence Matrix, showing alignment across WT, RSI, VWAP-MACD, and OBV HTF bias
✅ Full visual customization and minimalist styling options (color-coded WT fills, hybrid flow areas, and cleaner circles)
In addition to data — AlphaFlow gives you structure.
You don’t just see what’s happening — you understand the sequence behind the move.
Filtered QQE + EMA + Supertrend (Alternating Signals)used qqe mod + supertrend + 20 ema to build perfectly working script.
XRP/USD Advanced Trading StrategyKey Features:
Triple Confirmation System combines:
Moving Average crossover (9-period vs 21-period)
RSI oversold/overbought conditions (14-period)
MACD histogram crossover
Risk Management:
Built-in stop loss/profit taking (modify via strategy settings)
Margin requirements specified (100:1 leverage)
Visual Elements:
Clean price chart overlay
Clear buy/sell arrows with labels
Moving average plots for trend identification
Optimization Tips:
Adjust MA lengths for different timeframes (shorter for day trading)
Modify RSI levels based on market volatility
Combine with Ichimoku Cloud for additional confirmation
Use Bollinger Bands® to filter false breakouts
Backtesting:
Test on multiple timeframes (4h/daily weekly)
Check performance during different market conditions
Optimize parameters using Strategy Tester
This strategy reduces false signals by requiring confirmation from three different technical indicators while maintaining clarity in signal generation. Always validate with fundamental analysis and market news before executing trade
RSI with EMA and WMA on RSI
> "This is an indicator that combines EMA and WMA on the RSI.
> It highlights the strength of price waves as well as support and resistance zones."
Z-Score Normalized VIX StrategyThis strategy leverages the concept of the Z-score applied to multiple VIX-based volatility indices, specifically designed to capture market reversals based on the normalization of volatility. The strategy takes advantage of VIX-related indicators to measure extreme levels of market fear or greed and adjusts its position accordingly.
1. Overview of the Z-Score Methodology
The Z-score is a statistical measure that describes the position of a value relative to the mean of a distribution in terms of standard deviations. In this strategy, the Z-score is calculated for various volatility indices to assess how far their values are from their historical averages, thus normalizing volatility levels. The Z-score is calculated as follows:
Z = \frac{X - \mu}{\sigma}
Where:
• X is the current value of the volatility index.
• \mu is the mean of the index over a specified period.
• \sigma is the standard deviation of the index over the same period.
This measure tells us how many standard deviations the current value of the index is away from its average, indicating whether the market is experiencing unusually high or low volatility (fear or calm).
2. VIX Indices Used in the Strategy
The strategy utilizes four commonly referenced volatility indices:
• VIX (CBOE Volatility Index): Measures the market’s expectations of 30-day volatility based on S&P 500 options.
• VIX3M (3-Month VIX): Reflects expectations of volatility over the next three months.
• VIX9D (9-Day VIX): Reflects shorter-term volatility expectations.
• VVIX (VIX of VIX): Measures the volatility of the VIX itself, indicating the level of uncertainty in the volatility index.
These indices provide a comprehensive view of the current volatility landscape across different time horizons.
3. Strategy Logic
The strategy follows a long entry condition and an exit condition based on the combined Z-score of the selected volatility indices:
• Long Entry Condition: The strategy enters a long position when the combined Z-score of the selected VIX indices falls below a user-defined threshold, indicating an abnormally low level of volatility (suggesting a potential market bottom and a bullish reversal). The threshold is set as a negative value (e.g., -1), where a more negative Z-score implies greater deviation below the mean.
• Exit Condition: The strategy exits the long position when the combined Z-score exceeds the threshold (i.e., when the market volatility increases above the threshold, indicating a shift in market sentiment and reduced likelihood of continued upward momentum).
4. User Inputs
• Z-Score Lookback Period: The user can adjust the lookback period for calculating the Z-score (e.g., 6 periods).
• Z-Score Threshold: A customizable threshold value to define when the market has reached an extreme volatility level, triggering entries and exits.
The strategy also allows users to select which VIX indices to use, with checkboxes to enable or disable each index in the calculation of the combined Z-score.
5. Trade Execution Parameters
• Initial Capital: The strategy assumes an initial capital of $20,000.
• Pyramiding: The strategy does not allow pyramiding (multiple positions in the same direction).
• Commission and Slippage: The commission is set at $0.05 per contract, and slippage is set at 1 tick.
6. Statistical Basis of the Z-Score Approach
The Z-score methodology is a standard technique in statistics and finance, commonly used in risk management and for identifying outliers or unusual events. According to Dumas, Fleming, and Whaley (1998), volatility indices like the VIX serve as a useful proxy for market sentiment, particularly during periods of high uncertainty. By calculating the Z-score, we normalize volatility and quantify the degree to which the current volatility deviates from historical norms, allowing for systematic entry and exit based on these deviations.
7. Implications of the Strategy
This strategy aims to exploit market conditions where volatility has deviated significantly from its historical mean. When the Z-score falls below the threshold, it suggests that the market has become excessively calm, potentially indicating an overreaction to past market events. Entering long positions under such conditions could capture market reversals as fear subsides and volatility normalizes. Conversely, when the Z-score rises above the threshold, it signals increased volatility, which could be indicative of a bearish shift in the market, prompting an exit from the position.
By applying this Z-score normalized approach, the strategy seeks to achieve more consistent entry and exit points by reducing reliance on subjective interpretation of market conditions.
8. Scientific Sources
• Dumas, B., Fleming, J., & Whaley, R. (1998). “Implied Volatility Functions: Empirical Tests”. The Journal of Finance, 53(6), 2059-2106. This paper discusses the use of volatility indices and their empirical behavior, providing context for volatility-based strategies.
• Black, F., & Scholes, M. (1973). “The Pricing of Options and Corporate Liabilities”. Journal of Political Economy, 81(3), 637-654. The original Black-Scholes model, which forms the basis for many volatility-related strategies.
Supertrend + Fair Value Gap [Combined]//@version=5
indicator("Supertrend + Fair Value Gap ", overlay = true, max_lines_count = 500, max_boxes_count = 500)
// === SUPER TREND ===
atrPeriod = input.int(10, "ATR Length", minval = 1)
factor = input.float(3.0, "Factor", minval = 0.01, step = 0.01)
= ta.supertrend(factor, atrPeriod)
supertrend := bar_index == 0 ? na : supertrend
upTrend = plot(direction < 0 ? supertrend : na, "Up Trend", color=color.green, style=plot.style_linebr)
downTrend = plot(direction < 0 ? na : supertrend, "Down Trend", color=color.red, style=plot.style_linebr)
bodyMiddle = plot(bar_index == 0 ? na : (open + close) / 2, "Body Middle", display=display.none)
fill(bodyMiddle, upTrend, title="Uptrend background", color=color.new(color.green, 90), fillgaps=false)
fill(bodyMiddle, downTrend, title="Downtrend background", color=color.new(color.red, 90), fillgaps=false)
alertcondition(direction > direction, title='Downtrend to Uptrend', message='The Supertrend value switched from Downtrend to Uptrend')
alertcondition(direction < direction, title='Uptrend to Downtrend', message='The Supertrend value switched from Uptrend to Downtrend')
alertcondition(direction != direction, title='Trend Change', message='The Supertrend value switched trend')
// === FAIR VALUE GAP ===
thresholdPer = input.float(0, "FVG Threshold %", minval=0, maxval=100, step=.1, inline='threshold')
auto = input.bool(false, "Auto", inline='threshold')
showLast = input.int(0, "Unmitigated Levels", minval=0)
mitigationLevels = input.bool(false, "Mitigation Levels")
tf = input.timeframe('', "FVG Timeframe")
extend = input.int(20, "Extend", minval=0, inline='extend', group="Style")
dynamic = input.bool(false, "Dynamic", inline='extend', group="Style")
bullCss = input.color(color.new(#089981, 70), "Bullish FVG", group="Style")
bearCss = input.color(color.new(#f23645, 70), "Bearish FVG", group="Style")
showDash = input.bool(false, "Show Dashboard", group="Dashboard")
dashLoc = input.string("Top Right", "Location", options= , group="Dashboard")
textSize = input.string("Small", "Text Size", options= , group="Dashboard")
type fvg
float max
float min
bool isbull
int t = time
method tosolid(color id) => color.rgb(color.r(id), color.g(id), color.b(id))
n = bar_index
detect() =>
var new_fvg = fvg.new(na, na, na, na)
threshold = auto ? ta.cum((high - low) / low) / bar_index : thresholdPer / 100
bull_fvg = low > high and close > high and (low - high ) / high > threshold
bear_fvg = high < low and close < low and (low - high) / high > threshold
if bull_fvg
new_fvg := fvg.new(low, high , true)
else if bear_fvg
new_fvg := fvg.new(low , high, false)
var float max_bull_fvg = na, var float min_bull_fvg = na, var bull_count = 0, var bull_mitigated = 0
var float max_bear_fvg = na, var float min_bear_fvg = na, var bear_count = 0, var bear_mitigated = 0
var t = 0
var fvg_records = array.new(0)
var fvg_areas = array.new(0)
= request.security(syminfo.tickerid, tf, detect())
if bull_fvg and new_fvg.t != t
if dynamic
max_bull_fvg := new_fvg.max
min_bull_fvg := new_fvg.min
if not dynamic
fvg_areas.unshift(box.new(n - 2, new_fvg.max, n + extend, new_fvg.min, na, bgcolor=bullCss))
fvg_records.unshift(new_fvg)
bull_count += 1
t := new_fvg.t
else if dynamic
max_bull_fvg := math.max(math.min(close, max_bull_fvg), min_bull_fvg)
if bear_fvg and new_fvg.t != t
if dynamic
max_bear_fvg := new_fvg.max
min_bear_fvg := new_fvg.min
if not dynamic
fvg_areas.unshift(box.new(n - 2, new_fvg.max, n + extend, new_fvg.min, na, bgcolor=bearCss))
fvg_records.unshift(new_fvg)
bear_count += 1
t := new_fvg.t
else if dynamic
min_bear_fvg := math.min(math.max(close, min_bear_fvg), max_bear_fvg)
// Mitigation logic
if fvg_records.size() > 0
for i = fvg_records.size() - 1 to 0
get = fvg_records.get(i)
if get.isbull and close < get.min
if mitigationLevels
line.new(get.t, get.min, time, get.min, xloc.bar_time, color=bullCss, style=line.style_dashed)
if not dynamic
area = fvg_areas.remove(i)
area.delete()
fvg_records.remove(i)
bull_mitigated += 1
else if not get.isbull and close > get.max
if mitigationLevels
line.new(get.t, get.max, time, get.max, xloc.bar_time, color=bearCss, style=line.style_dashed)
if not dynamic
area = fvg_areas.remove(i)
area.delete()
fvg_records.remove(i)
bear_mitigated += 1
// Unmitigated lines
var unmitigated = array.new(0)
if barstate.islast and showLast > 0 and fvg_records.size() > 0
for element in unmitigated
element.delete()
unmitigated.clear()
for i = 0 to math.min(showLast - 1, fvg_records.size() - 1)
get = fvg_records.get(i)
unmitigated.push(line.new(get.t, get.isbull ? get.min : get.max, time, get.isbull ? get.min : get.max, xloc.bar_time, color=get.isbull ? bullCss : bearCss))
// Dashboard
var table_position = dashLoc == 'Bottom Left' ? position.bottom_left : dashLoc == 'Top Right' ? position.top_right : position.bottom_right
var table_size = textSize == 'Tiny' ? size.tiny : textSize == 'Small' ? size.small : size.normal
var tb = table.new(table_position, 3, 3, bgcolor=#1e222d, border_color=#373a46, border_width=1, frame_color=#373a46, frame_width=1)
if showDash
if bar_index == 0
tb.cell(1, 0, "Bullish", text_color=bullCss.tosolid(), text_size=table_size)
tb.cell(2, 0, "Bearish", text_color=bearCss.tosolid(), text_size=table_size)
tb.cell(0, 1, "Count", text_color=color.white, text_size=table_size)
tb.cell(0, 2, "Mitigated", text_color=color.white, text_size=table_size)
if barstate.islast
tb.cell(1, 1, str.tostring(bull_count), text_color=bullCss.tosolid(), text_size=table_size)
tb.cell(2, 1, str.tostring(bear_count), text_color=bearCss.tosolid(), text_size=table_size)
tb.cell(1, 2, str.tostring(bull_mitigated / bull_count * 100, format.percent), text_color=bullCss.tosolid(), text_size=table_size)
tb.cell(2, 2, str.tostring(bear_mitigated / bear_count * 100, format.percent), text_color=bearCss.tosolid(), text_size=table_size)
// Plots for dynamic
max_bull_plot = plot(max_bull_fvg, color=na)
min_bull_plot = plot(min_bull_fvg, color=na)
fill(max_bull_plot, min_bull_plot, color=bullCss)
max_bear_plot = plot(max_bear_fvg, color=na)
min_bear_plot = plot(min_bear_fvg, color=na)
fill(max_bear_plot, min_bear_plot, color=bearCss)
// Alerts
alertcondition(bull_count > bull_count , "Bullish FVG", "Bullish FVG detected")
alertcondition(bear_count > bear_count , "Bearish FVG", "Bearish FVG detected")
alertcondition(bull_mitigated > bull_mitigated , "Bullish FVG Mitigation", "Bullish FVG mitigated")
alertcondition(bear_mitigated > bear_mitigated , "Bearish FVG Mitigation", "Bearish FVG mitigated")
Fiyat Hareket EtkinliğiA simple script I generated using ChatGPT to detect divergences in momentum and volume changes.
Sometimes, after a candle with strong momentum and high volume, the trend continues, but that level of volume and momentum is never reached again — which can signal a potential reversal.
VWAP + Volume Spike + Momentum (Options)it is regarding vwasp stategy and how it willperform on vwap and movmentum
OBVX Conviction Bias🧮 The OBVX Conviction Bias overlay tracks the flow of directional volume using the classic On-Balance Volume calculation, then filters it through a layered moving average system to expose crowd commitment, pressure transitions, and momentum fatigue. The tool applies two smoothed averages to the OBV line—a fast curve and a longer-term baseline scaled using Euler’s constant (2.718×)—and visualizes their relationship using a color-coded crossover ribbon and pressure fills. When used correctly, it reveals whether a move is being supported by meaningful volume, or whether the crowd is starting to disengage.
🚦 The core signal compares OBV to its fast moving average. When OBV climbs above the short average, it fills green—suggesting real directional effort. When OBV sinks below, the fill turns maroon—flagging fading conviction or pullback potential. A second fill between the short and long OBV moving averages captures the broader trend of volume intention. If the short is above the long, this space fills greenish, showing constructive pressure. If it flips, the fill fades red, signaling crowd hesitation, rotation, or early exhaustion.
⚖️ All smoothing is user-selectable, defaulting to VWMA for effort-sensitive structure. The long-term average is auto-scaled using the natural exponential multiplier (2.718), offering rhythm that reflects the curve of participation. OBV Intention Bias isn’t trying to predict—it’s trying to show you where the crowd is leaning, and whether that lean is gaining traction or losing strength.
🧐 Ideal use-cases:
• Detect divergence between volume flow and price action
• Confirm breakout validity with volume alignment
• Fade breakouts where OBV fails to follow through
• Time pullback entries when OBV pressure resumes in trend direction
🍷 Recommended pairings:
• ΣVOL to measure whether volume is statistically significant or just noise (as shown)
• RVOL Effort Matrix to validate crowd effort by tier and structure zone (not shown)
• SUPeR TReND 2.718 and/or MA Ribbons for directional confluence
• ATR Turbulence to track volatility-phase alignment with volume intention
RVOL Effort Matrix⚖️ RVOL Effort Matrix is a tiered volume framework that translates crowd participation into structure-aware visual zones. Rather than simply flagging spikes, it measures each bar’s volume as a ratio of its historical average and classifies that effort dynamic tiers to create a real-time map of conviction, exhaustion, and imbalance—before price even confirms.
💪🏻 At its core, the tool builds a histogram of relative volume (RVOL) When enabled, a second layer overlays directional effort by estimating buy vs sell volume using candle body logic. If the candle closes higher, green (buy) volume dominates. If it closes lower, red (sell) volume leads. These components are stacked proportionally and inset beneath a colored cap line—a small but powerful layer that maintains visibility of the true effort tier even when split bars are active. The cap matches the original zone color, preserving context at all times.
Coloration communicates rhythm, tempo, and potential turning points:
• 🔴 = structurally weak effort, i.e. failed moves, fake-outs or trend exhaustion
• 🟡 = neutral volume, as seen in consolidations or pullbacks
• 🟢 = genuine commitment, good for continuation, breakout filters, or early rotation signals
• 🟣 = explosive volume signaling either climax or institutional entry—beware!
Background shading (optional) mirrors these zones across the pane for structural scanning at a glance. Volume bars can be toggled between full-stack mode or clean column view. Every layer is modular—built for composability with tools like ΣVOL or the OBV Intention Bias overlay.
🧐 Ideal use-cases:
• 🕰 HTF bias anchoring → LTF execution
• 🧭 Identifying when structure is being driven by real crowd pressure
• 🚫 Fading green/fuchsia bars that fail to break structure
• ✅ Riding green/fuchsia follow-through in directional moves
🍷 Recommended pairings:
• ΣVOL for statistically significant volume anomaly detection
• OBV Intention Bias ↔️ for directional confirmation of effort zones
• SUPeR TReND 2.718 for structure-congruent entry filtering
• ATR Turbulence Ribbon to distinguish expansion pressure from churn
🥁 RVOL Effort Matrix is all about seeing—how much pressure is behind a move, whether that pressure is sustainable, and whether the crowd is aligned with price. It's volume, but readable. It’s structure, but dynamic. It’s the difference between chasing noise and trading with rhythm.
Normalized MACD with RSI & Stoch RSI + SignalsNormalized MACD with RSI & Stoch RSI Indicator
Overview:
This indicator combines three popular momentum indicators (MACD, RSI, and Stochastic RSI) into a single cohesive, normalized view, making it easier for traders to interpret market momentum and potential buy/sell signals. It specifically addresses an important issue—the different scale ranges of indicators—by normalizing MACD values to match the 0–100 scale of RSI and Stochastic RSI.
Here’s a clear and concise description of your updated Pine Script indicator:
⸻
Normalized MACD with RSI & Stoch RSI Indicator
Overview:
This indicator combines three popular momentum indicators (MACD, RSI, and Stochastic RSI) into a single cohesive, normalized view, making it easier for traders to interpret market momentum and potential buy/sell signals. It specifically addresses an important issue—the different scale ranges of indicators—by normalizing MACD values to match the 0–100 scale of RSI and Stochastic RSI.
⸻
Key Components:
① MACD (Normalized):
• The Moving Average Convergence Divergence (MACD) originally has an unlimited numerical range.
• Normalization Method:
• Uses a custom tanh(x) function implemented directly in Pine Script:
\tanh(x) = \frac{e^{x}-e^{-x}}{e^{x}+e^{-x}}
• MACD values are scaled using this method to a range of 0–100, with the neutral line at exactly 50.
• Interpretation:
• Values above 50 indicate bullish momentum.
• Values below 50 indicate bearish momentum.
② RSI (Relative Strength Index):
• Measures market momentum on a 0–100 scale.
• Traditional RSI interpretation:
• Overbought conditions: RSI > 70–80.
• Oversold conditions: RSI < 30–20.
③ Stochastic RSI:
• Combines RSI and Stochastic Oscillator to give short-term, highly sensitive signals.
• Helps identify immediate market extremes:
• Above 80 → Short-term overbought.
• Below 20 → Short-term oversold.
⸻
How the Indicator Works:
• Visualization:
• All three indicators (Normalized MACD, RSI, Stochastic RSI) share the same 0–100 scale.
• Clear visual lines and reference levels:
• Midline at 50 indicates neutral momentum.
• Dashed lines at 20 and 80 clearly mark oversold/overbought zones.
• Trading Signals (Recommended approach):
• Bullish Signal (Potential Buy):
• Normalized MACD crosses above 50.
• RSI below or approaching oversold zone (below 30–20).
• Stochastic RSI below 20, indicating short-term oversold conditions.
• Bearish Signal (Potential Sell):
• Normalized MACD crosses below 50.
• RSI above or approaching overbought zone (above 70–80).
• Stochastic RSI above 80, indicating short-term overbought conditions.
⸻
Why Use This Indicator?
• Harmonized Signals:
Normalization of MACD significantly improves clarity and comparability with RSI and Stochastic RSI, providing a unified momentum picture.
• Intuitive Analysis:
Traders can rapidly and intuitively identify momentum shifts without needing multiple indicator windows.
• Improved Decision-Making:
Clear visual references and signals help reduce subjective interpretation, potentially improving trading outcomes.
⸻
Suggested Usage:
• Combine with traditional support
EMA 34 Crossover with Break Even Stop LossEMA 34 Crossover with Break Even Stop Loss Strategy
This trading strategy is based on the 34-period Exponential Moving Average (EMA) and aims to enter long positions when the price crosses above the EMA 34. The strategy is designed to manage risk effectively with a dynamic stop loss and take-profit mechanism.
Key Features:
EMA 34 Crossover:
The strategy generates a long entry signal when the closing price of the current bar crosses above the 34-period EMA, with the condition that the previous closing price was below the EMA. This crossover indicates a potential upward trend.
Risk Management:
Upon entering a trade, the strategy sets a stop loss at the low of the previous bar. This helps in controlling the downside risk.
A take profit level is set at a 10:1 risk-to-reward ratio, meaning the potential profit is ten times the amount risked on the trade.
Break-even Stop Loss:
As the price moves in favor of the trade and reaches a 3:1 risk-to-reward ratio, the strategy moves the stop loss to the entry price (break-even). This ensures that no loss will be incurred if the market reverses, effectively protecting profits.
Exit Conditions:
The strategy exits the trade when either the stop loss is hit (if the price drops below the stop loss level) or the take profit target is reached (if the price rises to the take profit level).
If the price reaches the break-even level (entry price), the stop loss is adjusted to lock in profits and prevent any loss.
Visualization:
The stop loss and take profit levels are plotted on the chart for easy visualization, helping traders track the status of their trade.
Trade Management Summary:
Long Entry: When price crosses above the 34-period EMA.
Stop Loss: Set to the low of the previous candle.
Take Profit: Set to a 10:1 risk-to-reward ratio.
Break-even: Stop loss is moved to entry price when a 3:1 risk-to-reward ratio is reached.
Exit: The trade is closed either when the stop loss or take profit levels are hit.
This strategy is designed to minimize losses by employing a dynamic stop loss and to maximize gains by setting a favorable risk-to-reward ratio, making it suitable for traders who prefer a structured, automated approach to risk management and trend-following.
Death Cross ReversalThis indicator tracks the recovery of the EMA20 slope after a death cross (when EMA200 crosses above EMA50). At the death cross, it records the current EMA20 slope as a baseline. As the slope improves from its negative baseline, the indicator plots sequential signals:
A Strength Signal when the slope recovers 50% of the baseline gap,
An Early Momentum Signal at 75% recovery, and
A Reversal Signal when the slope finally crosses above +50.
It also displays a histogram of the EMA20 slope (green for positive, gray for negative). Once the reversal signal fires, no further signals are generated until a golden cross resets the cycle.
RSI Trigger Count (30 Days) - Both SidesRSI Dual Trigger Counter (30 Days)
This indicator tracks both oversold ( crossunder ) and overbought ( crossover ) RSI events on a 30-minute chart, featuring:
Dual-Mode Selector:
Counts either RSI < 30 (oversold) or RSI > 70 (overbought) crossings
Toggle between modes via input menu
30-Day Rolling Count:
Displays total triggers in the last 30 days (e.g., "Times triggered (Oversold) ① 19")
Visual Alerts:
Red triangles ↓ for oversold crossunders
Green triangles ↑ for overbought crossovers
Customizable:
Adjustable RSI length (2-100) and thresholds (1-100)
Works on any timeframe (auto-scales calculations)
Purpose: Identifies frequent reversal signals for both buying dips (oversold) and selling rallies (overbought).
Session Coloring Bar with ICT Macro [dani]The Session Coloring Bar is customizable Pine Script indicator designed to visually enhance your charts by applying unique colors to specific trading sessions or timeframes. This tool allows traders to easily identify and differentiate between macro sessions (e.g., 24-hour cycles) and custom-defined sessions (e.g., Session A, Session B), making it ideal for analyzing market activity during specific periods.
In the context of trading, the term "ICT Macro" , as discussed by Michael J. Huddleston (ICT), refers to specific timeframes or "windows" where market behavior often follows predictable patterns. Traders typically focus on the last 10 minutes of an hour and the first 10 minutes of the next hour (e.g., 0150-0210 , 0050-0110 , or 0950-1010 ) to identify key price movements, liquidity shifts, or market inefficiencies.
This script highlights these macro timeframes, enabling traders to visually analyze price action during these critical periods. Use this tool to support your strategy, but always combine it with your own analysis and risk management.
With this indicator, you can:
Highlight Macro Sessions : Automatically color bars based on predefined 24-hour macro sessions.
Customize Session Settings : Define up to three custom sessions (A & B) with individual start/end times, visibility toggles, and unique bar colors.
Timeframe Filtering : Hide session coloring above a specified timeframe to avoid clutter on higher timeframes.
Personal Notes : Add comments to each session for better organization and quick reference.
Dynamic Color Logic : Bars are colored based on their direction (up, down, or neutral) within the active session.
How to Use:
Enable/Disable Sessions :
Use the Show Coloring toggle to enable or disable session coloring for Macro, Session A, Session B, or Session C.
Set Session Times :
Define the start and end times for each session in the format HHMM-HHMM (e.g., 1600-0930 for an overnight session).
Choose Colors :
Assign unique colors for upward (Bar Up) and downward (Bar Down) bars within each session.
Adjust Timeframe Visibility :
Use the Hide above this TF input to specify the maximum timeframe where session coloring will be visible.
Add Notes :
Use the Comment field to add personal notes or labels for each session.
Example Use Cases:
Overnight Sessions :
Highlight overnight trading hours (e.g., 1600-0930) to analyze price action during low liquidity periods.
Asian/European/US Sessions : Define separate sessions for major trading regions to track regional market behavior.
Macro Analysis : Use the predefined 24-hour macro sessions to study hourly price movements across a full trading day.
Disclaimer:
The Session Coloring Bar is not a trading signal generator and does not predict market direction or provide buy/sell signals. Instead, it is a visualization tool designed to help you identify and analyze specific trading sessions or timeframes on your chart. By highlighting key sessions and their corresponding price movements, this indicator enables you to focus on periods of interest and make more informed trading decisions.
Thank you for choosing this indicator! I hope it becomes a valuable part of your trading toolkit. Remember, trading is a journey, and having the right tools can make all the difference. Whether you're a seasoned trader or just starting out, this indicator is designed to help you stay organized and focused on what matters most—price action. Happy trading, and may your charts be ever in your favor! 😊
STRADUK - Moving Average Simple INC RVOLBY STRADUK
what is says on the tin
SMA with and added RVOL Icon. with ease of settings change for time periods.
YOUR WELCOME
FROM THE STRADUK TEAM
Days Live CounterThis quite simply tracks how many days an asset has been on Trading View for.
The indicator calculates the day count based on the timestamp of the first visible bar in your current chart view. Since monthly charts generally load data from further back in time than daily or intraday charts, they'll show a larger day count.
This isn't a bug in the indicator - it's correctly counting the days from the first bar it can see in each timeframe.
Million Minority Strategy (Visualizer)This Indicator breaks up the candles on a 1 min chart into 5 minute blocks. THis can then provide an indication of what trade will open the next 5 min block.
