Linear Regression Channel [TradingFinder] Existing Trend Line🔵 Introduction
The Linear Regression Channel indicator is one of the technical analysis tool, widely used to identify support, resistance, and analyze upward and downward trends.
The Linear Regression Channel comprises five main components : the midline, representing the linear regression line, and the support and resistance lines, which are calculated based on the distance from the midline using either standard deviation or ATR.
This indicator leverages linear regression to forecast price changes based on historical data and encapsulates price movements within a price channel.
The upper and lower lines of the channel, which define resistance and support levels, assist traders in pinpointing entry and exit points, ultimately aiding better trading decisions.
When prices approach these channel lines, the likelihood of interaction with support or resistance levels increases, and breaking through these lines may signal a price reversal or continuation.
Due to its precision in identifying price trends, analyzing trend reversals, and determining key price levels, the Linear Regression Channel indicator is widely regarded as a reliable tool across financial markets such as Forex, stocks, and cryptocurrencies.
🔵 How to Use
🟣 Identifying Entry Signals
One of the primary uses of this indicator is recognizing buy signals. The lower channel line acts as a support level, and when the price nears this line, the likelihood of an upward reversal increases.
In an uptrend : When the price approaches the lower channel line and signs of upward reversal (e.g., reversal candlesticks or high trading volume) are observed, it is considered a buy signal.
In a downtrend : If the price breaks the lower channel line and subsequently re-enters the channel, it may signal a trend change, offering a buying opportunity.
🟣 Identifying Exit Signals
The Linear Regression Channel is also used to identify sell signals. The upper channel line generally acts as a resistance level, and when the price approaches this line, the likelihood of a price decrease increases.
In an uptrend : Approaching the upper channel line and observing weakness in the uptrend (e.g., declining volume or reversal patterns) indicates a sell signal.
In a downtrend : When the price reaches the upper channel line and reverses downward, this is considered a signal to exit trades.
🟣 Analyzing Channel Breakouts
The Linear Regression Channel allows traders to identify price breakouts as strong signals of potential trend changes.
Breaking the upper channel line : Indicates buyer strength and the likelihood of a continued uptrend, often accompanied by increased trading volume.
Breaking the lower channel line : Suggests seller dominance and the possibility of a continued downtrend, providing a strong sell signal.
🟣 Mean Reversion Analysis
A key concept in using the Linear Regression Channel is the tendency for prices to revert to the midline of the channel, which acts as a dynamic moving average, reflecting the price's equilibrium over time.
In uptrends : Significant deviations from the midline increase the likelihood of a price retracement toward the midline.
In downtrends : When prices deviate considerably from the midline, a return toward the midline can be used to identify potential reversal points.
🔵 Settings
🟣 Time Frame
The time frame setting enables users to view higher time frame data on a lower time frame chart. This feature is especially useful for traders employing multi-time frame analysis.
🟣 Regression Type
Standard : Utilizes classical linear regression to draw the midline and channel lines.
Advanced : Produces similar results to the standard method but may provide slightly different alignment on the chart.
🟣 Scaling Type
Standard Deviation : Suitable for markets with stable volatility.
ATR (Average True Range) : Ideal for markets with higher volatility.
🟣 Scaling Coefficients
Larger coefficients create broader channels for broader trend analysis.
Smaller coefficients produce tighter channels for precision analysis.
🟣 Channel Extension
None : No extension.
Left: Extends lines to the left to analyze historical trends.
Right : Extends lines to the right for future predictions.
Both : Extends lines in both directions.
🔵 Conclusion
The Linear Regression Channel indicator is a versatile and powerful tool in technical analysis, providing traders with support, resistance, and midline insights to better understand price behavior. Its advanced settings, including time frame selection, regression type, scaling options, and customizable coefficients, allow for tailored and precise analysis.
One of its standout advantages is its ability to support multi-time frame analysis, enabling traders to view higher time frame data within a lower time frame context. The option to use scaling methods like ATR or standard deviation further enhances its adaptability to markets with varying volatility.
Designed to identify entry and exit signals, analyze mean reversion, and assess channel breakouts, this indicator is suitable for a wide range of markets, including Forex, stocks, and cryptocurrencies. By incorporating this tool into your trading strategy, you can make more informed decisions and improve the accuracy of your market predictions.
Cari dalam skrip untuk "break"
300-Candle Weighted Average Zones w/50 EMA SignalsThis indicator is designed to deliver a more nuanced view of price dynamics by combining a custom, weighted price average with a volatility-based zone and a trend filter (in this case, a 50-period exponential moving average). The core concept revolves around capturing the overall price level over a relatively large lookback window (300 candles) but with an intentional bias toward recent market activity (the most recent 20 candles), thereby offering a balance between long-term context and short-term responsiveness. By smoothing this weighted average and establishing a “zone” of standard deviation bands around it, the indicator provides a refined visualization of both average price and its recent volatility envelope. Traders can then look for confluence with a standard trend filter, such as the 50 EMA, to identify meaningful crossover signals that may represent trend shifts or opportunities for entry and exit.
What the Indicator Does:
Weighted Price Average:
Instead of using a simple or exponential moving average, this indicator calculates a custom weighted average price over the past 300 candles. Most historical candles receive a base weight of 1.0, but the most recent 20 candles are assigned a higher weight (for example, a weight of 2.0). This weighting scheme ensures that the calculation is not simply a static lookback average; it actively emphasizes current market conditions. The effect is to generate an average line that is more sensitive to the most recent price swings while still maintaining the historical context of the previous 280 candles.
Smoothing of the Weighted Average:
Once the raw weighted average is computed, an exponential smoothing function (EMA) is applied to reduce noise and produce a cleaner, more stable average line. This smoothing helps traders avoid reacting prematurely to minor price fluctuations. By stabilizing the average line, traders can more confidently identify actual shifts in market direction.
Volatility Zone via Standard Deviation Bands:
To contextualize how far price can deviate from this weighted average, the indicator uses standard deviation. Standard deviation is a statistical measure of volatility—how spread out the price values are around the mean. By adding and subtracting one standard deviation from the smoothed weighted average, the indicator plots an upper band and a lower band, creating a zone or channel. The area between these bands is filled, often with a semi-transparent color, highlighting a volatility corridor within which price and the EMA might oscillate.
This zone is invaluable in visualizing “normal” price behavior. When the 50 EMA line and the weighted average line are both within this volatility zone, it indicates that the market’s short- to mid-term trend and its average pricing are aligned well within typical volatility bounds.
Incorporation of a 50-Period EMA:
The inclusion of a commonly used trend filter, the 50 EMA, adds another layer of context to the analysis. The 50 EMA, being a widely recognized moving average length, is often considered a baseline for intermediate trend bias. It reacts faster than a long-term average (like a 200 EMA) but is still stable enough to filter out the market “chop” seen in very short-term averages.
By overlaying the 50 EMA on this custom weighted average and the surrounding volatility zone, the trader gains a dual-dimensional perspective:
Trend Direction: If the 50 EMA is generally above the weighted average, the short-term trend is gaining bullish momentum; if it’s below, the short-term trend has a bearish tilt.
Volatility Normalization: The bands, constructed from standard deviations, provide a sense of whether the price and the 50 EMA are operating within a statistically “normal” range. If the EMA crosses the weighted average within this zone, it signals a potential trend initiation or meaningful shift, as opposed to a random price spike outside normal volatility boundaries.
Why a Trader Would Want to Use This Indicator:
Contextualized Price Level:
Standard MAs may not fully incorporate the most recent price dynamics in a large lookback window. By weighting the most recent candles more heavily, this indicator ensures that the trader is always anchored to what the market is currently doing, not just what it did 100 or 200 candles ago.
Reduced Whipsaw with Smoothing:
The smoothed weighted average line reduces noise, helping traders filter out inconsequential price movements. This makes it easier to spot genuine changes in trend or sentiment.
Visual Volatility Gauge:
The standard deviation bands create a visual representation of “normal” price movement. Traders can quickly assess if a breakout or breakdown is statistically significant or just another oscillation within the expected volatility range.
Clear Trade Signals with Confirmation:
By integrating the 50 EMA and designing signals that trigger only when the 50 EMA crosses above or below the weighted average while inside the zone, the indicator provides a refined entry/exit criterion. This avoids chasing breakouts that occur in abnormal volatility conditions and focuses on those crossovers likely to have staying power.
How to Use It in an Example Strategy:
Imagine you are a swing trader looking to identify medium-term trend changes. You apply this indicator to a chart of a popular currency pair or a leading tech stock. Over the past few days, the 50 EMA has been meandering around the weighted average line, both confined within the standard deviation zone.
Bullish Example:
Suddenly, the 50 EMA crosses decisively above the weighted average line while both are still hovering within the volatility zone. This might be your cue: you interpret this crossover as the 50 EMA acknowledging the recent upward shift in price dynamics that the weighted average has highlighted. Since it occurred inside the normal volatility range, it’s less likely to be a head-fake. You place a long position, setting an initial stop just below the lower band to protect against volatility.
If the price continues to rise and the EMA stays above the average, you have confirmation to hold the trade. As the price moves higher, the weighted average may follow, reinforcing your bullish stance.
Bearish Example:
On the flip side, if the 50 EMA crosses below the weighted average line within the zone, it suggests a subtle but meaningful change in trend direction to the downside. You might short the asset, placing your protective stop just above the upper band, expecting that the statistically “normal” level of volatility will contain the price action. If the price does break above those bands later, it’s a sign your trade may not work out as planned.
Other Indicators for Confluence:
To strengthen the reliability of the signals generated by this weighted average zone approach, traders may want to combine it with other technical studies:
Volume Indicators (e.g., Volume Profile, OBV):
Confirm that the trend crossover inside the volatility zone is supported by volume. For instance, an uptrend crossover combined with increasing On-Balance Volume (OBV) or volume spikes on up candles signals stronger buying pressure behind the price action.
Momentum Oscillators (e.g., RSI, Stochastics):
Before taking a crossover signal, check if the RSI is above 50 and rising for bullish entries, or if the Stochastics have turned down from overbought levels for bearish entries. Momentum confirmation can help ensure that the trend change is not just an isolated random event.
Market Structure Tools (e.g., Pivot Points, Swing High/Low Analysis):
Identify if the crossover event coincides with a break of a previous pivot high or low. A bullish crossover inside the zone aligned with a break above a recent swing high adds further strength to your conviction. Conversely, a bearish crossover confirmed by a breakdown below a previous swing low can make a short trade setup more compelling.
Volume-Weighted Average Price (VWAP):
Comparing where the weighted average zone lies relative to VWAP can provide institutional insight. If the bullish crossover happens while the price is also holding above VWAP, it can mean that the average participant in the market is in profit and that the trend is likely supported by strong hands.
This indicator serves as a tool to balance long-term perspective, short-term adaptability, and volatility normalization. It can be a valuable addition to a trader’s toolkit, offering enhanced clarity and precision in detecting meaningful shifts in trend, especially when combined with other technical indicators and robust risk management principles.
Ultra Market StructureThe Ultra Market Structure indicator detects key market structure breaks, such as Break of Structure (BoS) and Change of Character (CHoCH), to help identify trend reversals. It plots lines and labels on the chart to visualize these breakpoints with alerts for important signals.
Introduction
This script is designed to help traders visualize important market structure events, such as trend breaks and reversals, using concepts like Break of Structure (BoS) and Change of Character (CHoCH). The indicator highlights internal and external price levels where the market shifts direction. It offers clear visual signals and alerts to keep traders informed of potential changes in the market trend.
Detailed Description
The indicator focuses on detecting "market structure breaks," which occur when the price moves past significant support or resistance levels, suggesting a potential reversal or continuation of the trend.
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Type of structure
Internal Structure: Focuses on smaller, shorter-term price levels within the current market trend.
External Structure: Focuses on larger, longer-term price levels that may indicate more significant shifts in the market.
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Key events
Break of Structure (BoS): A market structure break where the price surpasses a previous high (bullish BoS) or low (bearish BoS).
Change of Character (CHoCH): A shift in market behavior when the price fails to continue in the same direction, indicating a possible trend reversal.
Once a break or shift is detected, the script plots lines and labels on the chart to visually mark the breakpoints.
It also provides alerts when a BoS or CHoCH occurs, keeping traders informed in real-time.
The indicator can color the background and candles based on the market structure, making it easy to identify the current trend.
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Special feature
At news events or other momentum pushes most structure indicators will go into "sleep mode" because of too far away structure highs/lows. This indicator has a structure reset feature to solve this issue.
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Detects Break of Structure (BoS) and Change of Character (CHoCH) signals.
Marks internal and external support/resistance levels where market trends change.
Provides visual cues (lines, labels) and real-time alerts for structure breaks.
Offers background and candle color customization to highlight market direction.
lib_smcLibrary "lib_smc"
This is an adaptation of LuxAlgo's Smart Money Concepts indicator with numerous changes. Main changes include integration of object based plotting, plenty of performance improvements, live tracking of Order Blocks, integration of volume profiles to refine Order Blocks, and many more.
This is a library for developers, if you want this converted into a working strategy, let me know.
buffer(item, len, force_rotate)
Parameters:
item (float)
len (int)
force_rotate (bool)
buffer(item, len, force_rotate)
Parameters:
item (int)
len (int)
force_rotate (bool)
buffer(item, len, force_rotate)
Parameters:
item (Profile type from robbatt/lib_profile/32)
len (int)
force_rotate (bool)
swings(len)
INTERNAL: detect swing points (HH and LL) in given range
Parameters:
len (simple int) : range to check for new swing points
Returns: values are the price level where and if a new HH or LL was detected, else na
method init(this)
Namespace types: OrderBlockConfig
Parameters:
this (OrderBlockConfig)
method delete(this)
Namespace types: OrderBlock
Parameters:
this (OrderBlock)
method clear_broken(this, broken_buffer)
INTERNAL: delete internal order blocks box coordinates if top/bottom is broken
Namespace types: map
Parameters:
this (map)
broken_buffer (map)
Returns: any_bull_ob_broken, any_bear_ob_broken, broken signals are true if an according order block was broken/mitigated, broken contains the broken block(s)
create_ob(id, mode, start_t, start_i, top, end_t, end_i, bottom, break_price, early_confirmation_price, config, init_plot, force_overlay)
INTERNAL: set internal order block coordinates
Parameters:
id (int)
mode (int) : 1: bullish, -1 bearish block
start_t (int)
start_i (int)
top (float)
end_t (int)
end_i (int)
bottom (float)
break_price (float)
early_confirmation_price (float)
config (OrderBlockConfig)
init_plot (bool)
force_overlay (bool)
Returns: signals are true if an according order block was broken/mitigated
method align_to_profile(block, align_edge, align_break_price)
Namespace types: OrderBlock
Parameters:
block (OrderBlock)
align_edge (bool)
align_break_price (bool)
method create_profile(block, opens, tops, bottoms, closes, values, resolution, vah_pc, val_pc, args, init_calculated, init_plot, force_overlay)
Namespace types: OrderBlock
Parameters:
block (OrderBlock)
opens (array)
tops (array)
bottoms (array)
closes (array)
values (array)
resolution (int)
vah_pc (float)
val_pc (float)
args (ProfileArgs type from robbatt/lib_profile/32)
init_calculated (bool)
init_plot (bool)
force_overlay (bool)
method create_profile(block, resolution, vah_pc, val_pc, args, init_calculated, init_plot, force_overlay)
Namespace types: OrderBlock
Parameters:
block (OrderBlock)
resolution (int)
vah_pc (float)
val_pc (float)
args (ProfileArgs type from robbatt/lib_profile/32)
init_calculated (bool)
init_plot (bool)
force_overlay (bool)
track_obs(swing_len, hh, ll, top, btm, bull_bos_alert, bull_choch_alert, bear_bos_alert, bear_choch_alert, min_block_size, max_block_size, config_bull, config_bear, init_plot, force_overlay, enabled, extend_blocks, clear_broken_buffer_before, align_edge_to_value_area, align_break_price_to_poc, profile_args_bull, profile_args_bear, use_soft_confirm, soft_confirm_offset, use_retracements_with_FVG_out)
Parameters:
swing_len (int)
hh (float)
ll (float)
top (float)
btm (float)
bull_bos_alert (bool)
bull_choch_alert (bool)
bear_bos_alert (bool)
bear_choch_alert (bool)
min_block_size (float)
max_block_size (float)
config_bull (OrderBlockConfig)
config_bear (OrderBlockConfig)
init_plot (bool)
force_overlay (bool)
enabled (bool)
extend_blocks (simple bool)
clear_broken_buffer_before (simple bool)
align_edge_to_value_area (simple bool)
align_break_price_to_poc (simple bool)
profile_args_bull (ProfileArgs type from robbatt/lib_profile/32)
profile_args_bear (ProfileArgs type from robbatt/lib_profile/32)
use_soft_confirm (simple bool)
soft_confirm_offset (float)
use_retracements_with_FVG_out (simple bool)
method draw(this, config, extend_only)
Namespace types: OrderBlock
Parameters:
this (OrderBlock)
config (OrderBlockConfig)
extend_only (bool)
method draw(blocks, config)
INTERNAL: plot order blocks
Namespace types: array
Parameters:
blocks (array)
config (OrderBlockConfig)
method draw(blocks, config)
INTERNAL: plot order blocks
Namespace types: map
Parameters:
blocks (map)
config (OrderBlockConfig)
method cleanup(this, ob_bull, ob_bear)
removes all Profiles that are older than the latest OrderBlock from this profile buffer
Namespace types: array
Parameters:
this (array type from robbatt/lib_profile/32)
ob_bull (OrderBlock)
ob_bear (OrderBlock)
_plot_swing_points(mode, x, y, show_swing_points, linecolor_swings, keep_history, show_latest_swings_levels, trail_x, trail_y, trend)
INTERNAL: plot swing points
Parameters:
mode (int) : 1: bullish, -1 bearish block
x (int) : x-coordingate of swing point to plot (bar_index)
y (float) : y-coordingate of swing point to plot (price)
show_swing_points (bool) : switch to enable/disable plotting of swing point labels
linecolor_swings (color) : color for swing point labels and lates level lines
keep_history (bool) : weater to remove older swing point labels and only keep the most recent
show_latest_swings_levels (bool)
trail_x (int) : x-coordinate for latest swing point (bar_index)
trail_y (float) : y-coordinate for latest swing point (price)
trend (int) : the current trend 1: bullish, -1: bearish, to determine Strong/Weak Low/Highs
_pivot_lvl(mode, trend, hhll_x, hhll, super_hhll, filter_insignificant_internal_breaks)
INTERNAL: detect whether a structural level has been broken and if it was in trend direction (BoS) or against trend direction (ChoCh), also track the latest high and low swing points
Parameters:
mode (simple int) : detect 1: bullish, -1 bearish pivot points
trend (int) : current trend direction
hhll_x (int) : x-coordinate of newly detected hh/ll (bar_index)
hhll (float) : y-coordinate of newly detected hh/ll (price)
super_hhll (float) : level/y-coordinate of superior hhll (if this is an internal structure pivot level)
filter_insignificant_internal_breaks (bool) : if true pivot points / internal structure will be ignored where the wick in trend direction is longer than the opposite (likely to push further in direction of main trend)
Returns: coordinates of internal structure that has been broken (x,y): start of structure, (trail_x, trail_y): tracking hh/ll after structure break, (bos_alert, choch_alert): signal whether a structural level has been broken
_plot_structure(x, y, is_bos, is_choch, line_color, line_style, label_style, label_size, keep_history)
INTERNAL: plot structural breaks (BoS/ChoCh)
Parameters:
x (int) : x-coordinate of newly broken structure (bar_index)
y (float) : y-coordinate of newly broken structure (price)
is_bos (bool) : whether this structural break was in trend direction
is_choch (bool) : whether this structural break was against trend direction
line_color (color) : color for the line connecting the structural level and the breaking candle
line_style (string) : style (line.style_dashed/solid) for the line connecting the structural level and the breaking candle
label_style (string) : style (label.style_label_down/up) for the label above/below the line connecting the structural level and the breaking candle
label_size (string) : size (size.small/tiny) for the label above/below the line connecting the structural level and the breaking candle
keep_history (bool) : weater to remove older swing point labels and only keep the most recent
structure_values(length, super_hh, super_ll, filter_insignificant_internal_breaks)
detect (and plot) structural breaks and the resulting new trend
Parameters:
length (simple int) : lookback period for swing point detection
super_hh (float) : level/y-coordinate of superior hh (for internal structure detection)
super_ll (float) : level/y-coordinate of superior ll (for internal structure detection)
filter_insignificant_internal_breaks (bool) : if true pivot points / internal structure will be ignored where the wick in trend direction is longer than the opposite (likely to push further in direction of main trend)
Returns: trend: direction 1:bullish -1:bearish, (bull_bos_alert, bull_choch_alert, top_x, top_y, trail_up_x, trail_up): whether and which level broke in a bullish direction, trailing high, (bbear_bos_alert, bear_choch_alert, tm_x, btm_y, trail_dn_x, trail_dn): same in bearish direction
structure_plot(trend, bull_bos_alert, bull_choch_alert, top_x, top_y, trail_up_x, trail_up, hh, bear_bos_alert, bear_choch_alert, btm_x, btm_y, trail_dn_x, trail_dn, ll, color_bull, color_bear, show_swing_points, show_latest_swings_levels, show_bos, show_choch, line_style, label_size, keep_history)
detect (and plot) structural breaks and the resulting new trend
Parameters:
trend (int) : crrent trend 1: bullish, -1: bearish
bull_bos_alert (bool) : if there was a bullish bos alert -> plot it
bull_choch_alert (bool) : if there was a bullish choch alert -> plot it
top_x (int) : latest shwing high x
top_y (float) : latest swing high y
trail_up_x (int) : trailing high x
trail_up (float) : trailing high y
hh (float) : if there was a higher high
bear_bos_alert (bool) : if there was a bearish bos alert -> plot it
bear_choch_alert (bool) : if there was a bearish chock alert -> plot it
btm_x (int) : latest swing low x
btm_y (float) : latest swing low y
trail_dn_x (int) : trailing low x
trail_dn (float) : trailing low y
ll (float) : if there was a lower low
color_bull (color) : color for bullish BoS/ChoCh levels
color_bear (color) : color for bearish BoS/ChoCh levels
show_swing_points (bool) : whether to plot swing point labels
show_latest_swings_levels (bool) : whether to track and plot latest swing point levels with lines
show_bos (bool) : whether to plot BoS levels
show_choch (bool) : whether to plot ChoCh levels
line_style (string) : whether to plot BoS levels
label_size (string) : label size of plotted BoS/ChoCh levels
keep_history (bool) : weater to remove older swing point labels and only keep the most recent
structure(length, color_bull, color_bear, super_hh, super_ll, filter_insignificant_internal_breaks, show_swing_points, show_latest_swings_levels, show_bos, show_choch, line_style, label_size, keep_history, enabled)
detect (and plot) structural breaks and the resulting new trend
Parameters:
length (simple int) : lookback period for swing point detection
color_bull (color) : color for bullish BoS/ChoCh levels
color_bear (color) : color for bearish BoS/ChoCh levels
super_hh (float) : level/y-coordinate of superior hh (for internal structure detection)
super_ll (float) : level/y-coordinate of superior ll (for internal structure detection)
filter_insignificant_internal_breaks (bool) : if true pivot points / internal structure will be ignored where the wick in trend direction is longer than the opposite (likely to push further in direction of main trend)
show_swing_points (bool) : whether to plot swing point labels
show_latest_swings_levels (bool) : whether to track and plot latest swing point levels with lines
show_bos (bool) : whether to plot BoS levels
show_choch (bool) : whether to plot ChoCh levels
line_style (string) : whether to plot BoS levels
label_size (string) : label size of plotted BoS/ChoCh levels
keep_history (bool) : weater to remove older swing point labels and only keep the most recent
enabled (bool)
_check_equal_level(mode, len, eq_threshold, enabled)
INTERNAL: detect equal levels (double top/bottom)
Parameters:
mode (int) : detect 1: bullish/high, -1 bearish/low pivot points
len (int) : lookback period for equal level (swing point) detection
eq_threshold (float) : maximum price offset for a level to be considered equal
enabled (bool)
Returns: eq_alert whether an equal level was detected and coordinates of the first and the second level/swing point
_plot_equal_level(show_eq, x1, y1, x2, y2, label_txt, label_style, label_size, line_color, line_style, keep_history)
INTERNAL: plot equal levels (double top/bottom)
Parameters:
show_eq (bool) : whether to plot the level or not
x1 (int) : x-coordinate of the first level / swing point
y1 (float) : y-coordinate of the first level / swing point
x2 (int) : x-coordinate of the second level / swing point
y2 (float) : y-coordinate of the second level / swing point
label_txt (string) : text for the label above/below the line connecting the equal levels
label_style (string) : style (label.style_label_down/up) for the label above/below the line connecting the equal levels
label_size (string) : size (size.tiny) for the label above/below the line connecting the equal levels
line_color (color) : color for the line connecting the equal levels (and it's label)
line_style (string) : style (line.style_dotted) for the line connecting the equal levels
keep_history (bool) : weater to remove older swing point labels and only keep the most recent
equal_levels_values(len, threshold, enabled)
detect (and plot) equal levels (double top/bottom), returns coordinates
Parameters:
len (int) : lookback period for equal level (swing point) detection
threshold (float) : maximum price offset for a level to be considered equal
enabled (bool) : whether detection is enabled
Returns: (eqh_alert, eqh_x1, eqh_y1, eqh_x2, eqh_y2) whether an equal high was detected and coordinates of the first and the second level/swing point, (eql_alert, eql_x1, eql_y1, eql_x2, eql_y2) same for equal lows
equal_levels_plot(eqh_x1, eqh_y1, eqh_x2, eqh_y2, eql_x1, eql_y1, eql_x2, eql_y2, color_eqh, color_eql, show, keep_history)
detect (and plot) equal levels (double top/bottom), returns coordinates
Parameters:
eqh_x1 (int) : coordinates of first point of equal high
eqh_y1 (float) : coordinates of first point of equal high
eqh_x2 (int) : coordinates of second point of equal high
eqh_y2 (float) : coordinates of second point of equal high
eql_x1 (int) : coordinates of first point of equal low
eql_y1 (float) : coordinates of first point of equal low
eql_x2 (int) : coordinates of second point of equal low
eql_y2 (float) : coordinates of second point of equal low
color_eqh (color) : color for the line connecting the equal highs (and it's label)
color_eql (color) : color for the line connecting the equal lows (and it's label)
show (bool) : whether plotting is enabled
keep_history (bool) : weater to remove older swing point labels and only keep the most recent
Returns: (eqh_alert, eqh_x1, eqh_y1, eqh_x2, eqh_y2) whether an equal high was detected and coordinates of the first and the second level/swing point, (eql_alert, eql_x1, eql_y1, eql_x2, eql_y2) same for equal lows
equal_levels(len, threshold, color_eqh, color_eql, enabled, show, keep_history)
detect (and plot) equal levels (double top/bottom)
Parameters:
len (int) : lookback period for equal level (swing point) detection
threshold (float) : maximum price offset for a level to be considered equal
color_eqh (color) : color for the line connecting the equal highs (and it's label)
color_eql (color) : color for the line connecting the equal lows (and it's label)
enabled (bool) : whether detection is enabled
show (bool) : whether plotting is enabled
keep_history (bool) : weater to remove older swing point labels and only keep the most recent
Returns: (eqh_alert) whether an equal high was detected, (eql_alert) same for equal lows
_detect_fvg(mode, enabled, o, h, l, c, filter_insignificant_fvgs, change_tf)
INTERNAL: detect FVG (fair value gap)
Parameters:
mode (int) : detect 1: bullish, -1 bearish gaps
enabled (bool) : whether detection is enabled
o (float) : reference source open
h (float) : reference source high
l (float) : reference source low
c (float) : reference source close
filter_insignificant_fvgs (bool) : whether to calculate and filter small/insignificant gaps
change_tf (bool) : signal when the previous reference timeframe closed, triggers new calculation
Returns: whether a new FVG was detected and its top/mid/bottom levels
_clear_broken_fvg(mode, upper_boxes, lower_boxes)
INTERNAL: clear mitigated FVGs (fair value gaps)
Parameters:
mode (int) : detect 1: bullish, -1 bearish gaps
upper_boxes (array) : array that stores the upper parts of the FVG boxes
lower_boxes (array) : array that stores the lower parts of the FVG boxes
_plot_fvg(mode, show, top, mid, btm, border_color, extend_box)
INTERNAL: plot (and clear broken) FVG (fair value gap)
Parameters:
mode (int) : plot 1: bullish, -1 bearish gap
show (bool) : whether plotting is enabled
top (float) : top level of fvg
mid (float) : center level of fvg
btm (float) : bottom level of fvg
border_color (color) : color for the FVG box
extend_box (int) : how many bars into the future the FVG box should be extended after detection
fvgs_values(o, h, l, c, filter_insignificant_fvgs, change_tf, enabled)
detect (and plot / clear broken) FVGs (fair value gaps), and return alerts and level values
Parameters:
o (float) : reference source open
h (float) : reference source high
l (float) : reference source low
c (float) : reference source close
filter_insignificant_fvgs (bool) : whether to calculate and filter small/insignificant gaps
change_tf (bool) : signal when the previous reference timeframe closed, triggers new calculation
enabled (bool) : whether detection is enabled
Returns: (bullish_fvg_alert, bull_top, bull_mid, bull_btm): whether a new bullish FVG was detected and its top/mid/bottom levels, (bearish_fvg_alert, bear_top, bear_mid, bear_btm): same for bearish FVGs
fvgs_plot(bullish_fvg_alert, bull_top, bull_mid, bull_btm, bearish_fvg_alert, bear_top, bear_mid, bear_btm, color_bull, color_bear, extend_box, show)
Parameters:
bullish_fvg_alert (bool)
bull_top (float)
bull_mid (float)
bull_btm (float)
bearish_fvg_alert (bool)
bear_top (float)
bear_mid (float)
bear_btm (float)
color_bull (color) : color for bullish FVG boxes
color_bear (color) : color for bearish FVG boxes
extend_box (int) : how many bars into the future the FVG box should be extended after detection
show (bool) : whether plotting is enabled
Returns: (bullish_fvg_alert, bull_top, bull_mid, bull_btm): whether a new bullish FVG was detected and its top/mid/bottom levels, (bearish_fvg_alert, bear_top, bear_mid, bear_btm): same for bearish FVGs
fvgs(o, h, l, c, filter_insignificant_fvgs, change_tf, color_bull, color_bear, extend_box, enabled, show)
detect (and plot / clear broken) FVGs (fair value gaps)
Parameters:
o (float) : reference source open
h (float) : reference source high
l (float) : reference source low
c (float) : reference source close
filter_insignificant_fvgs (bool) : whether to calculate and filter small/insignificant gaps
change_tf (bool) : signal when the previous reference timeframe closed, triggers new calculation
color_bull (color) : color for bullish FVG boxes
color_bear (color) : color for bearish FVG boxes
extend_box (int) : how many bars into the future the FVG box should be extended after detection
enabled (bool) : whether detection is enabled
show (bool) : whether plotting is enabled
Returns: (bullish_fvg_alert): whether a new bullish FVG was detected, (bearish_fvg_alert): same for bearish FVGs
OrderBlock
Fields:
id (series int)
dir (series int)
left_top (chart.point)
right_bottom (chart.point)
break_price (series float)
early_confirmation_price (series float)
ltf_high (array)
ltf_low (array)
ltf_volume (array)
plot (Box type from robbatt/lib_plot_objects/49)
profile (Profile type from robbatt/lib_profile/32)
trailing (series bool)
extending (series bool)
awaiting_confirmation (series bool)
touched_break_price_before_confirmation (series bool)
soft_confirmed (series bool)
has_fvg_out (series bool)
hidden (series bool)
broken (series bool)
OrderBlockConfig
Fields:
show (series bool)
show_last (series int)
show_id (series bool)
show_profile (series bool)
args (BoxArgs type from robbatt/lib_plot_objects/49)
txt (series string)
txt_args (BoxTextArgs type from robbatt/lib_plot_objects/49)
delete_when_broken (series bool)
broken_args (BoxArgs type from robbatt/lib_plot_objects/49)
broken_txt (series string)
broken_txt_args (BoxTextArgs type from robbatt/lib_plot_objects/49)
broken_profile_args (ProfileArgs type from robbatt/lib_profile/32)
use_profile (series bool)
profile_args (ProfileArgs type from robbatt/lib_profile/32)
SMB MagicSMB Magic
Overview: SMB Magic is a powerful technical strategy designed to capture breakout opportunities based on price movements, volume spikes, and trend-following logic. This strategy works exclusively on the XAU/USD symbol and is optimized for the 15-minute time frame. By incorporating multiple factors, this strategy identifies high-probability trades with a focus on risk management.
Key Features:
Breakout Confirmation:
This strategy looks for price breakouts above the previous high or below the previous low, with a significant volume increase. A breakout is considered valid when it is supported by strong volume, confirming the strength of the price move.
Price Movement Filter:
The strategy ensures that only significant price movements are considered for trades, helping to avoid low-volatility noise. This filter targets larger price swings to maximize potential profits.
Exponential Moving Average (EMA):
A long-term trend filter is applied to ensure that buy trades occur only when the price is above the moving average, and sell trades only when the price is below it.
Fibonacci Levels:
Custom Fibonacci retracement levels are drawn based on recent price action. These levels act as dynamic support and resistance zones and help determine the exit points for trades.
Take Profit/Stop Loss:
The strategy incorporates predefined take profit and stop loss levels, designed to manage risk effectively. These levels are automatically applied to trades and are adjusted based on the market's volatility.
Volume Confirmation:
A volume multiplier confirms the strength of the breakout. A trade is only considered when the volume exceeds a certain threshold, ensuring that the breakout is supported by sufficient market participation.
How It Works:
Entry Signals:
Buy Signal: A breakout above the previous high, accompanied by significant volume and price movement, occurs when the price is above the trend-following filter (e.g., EMA).
Sell Signal: A breakout below the previous low, accompanied by significant volume and price movement, occurs when the price is below the trend-following filter.
Exit Strategy:
Each position (long or short) has predefined take-profit and stop-loss levels, which are designed to protect capital and lock in profits at key points in the market.
Fibonacci Levels:
Fibonacci levels are drawn to identify potential areas of support or resistance, which can be used to guide exits and stop-loss placements.
Important Notes:
Timeframe Restriction: This strategy is designed specifically for the 15-minute time frame.
Symbol Restriction: The strategy works exclusively on the XAU/USD (Gold) symbol and is not recommended for use with other instruments.
Best Performance in Trending Markets: It works best in trending conditions where breakouts occur frequently.
Disclaimer:
Risk Warning: Trading involves risk, and past performance is not indicative of future results. Always conduct your own research and make informed decisions before trading.
Day High/Low and Horizontal Lines with Custom Increments How It Works:
Day High and Day Low: The indicator tracks and displays the highest and lowest prices of the current trading day. These values are updated dynamically throughout the day.
Custom Horizontal Lines: The user specifies a starting price and an increment value. The indicator then plots multiple horizontal lines above and below the starting price, spaced at the given increment. Up to 15 lines can be drawn in both directions (above and below).
Alerts: Alerts are triggered when the price crosses any of the horizontal lines, helping traders monitor potential breakouts or reversals.
Use Case:
This indicator is useful for traders who want to:
Track the Day High/Low: Easily reference the high and low of the current day as key price levels.
Monitor Key Price Levels: Draw and observe custom horizontal levels above and below a specific price, such as support/resistance levels or price targets.
Set Alerts: Receive notifications when the price crosses these key levels, helping identify potential breakout or breakdown points in the market.
Why Use This Indicator:
Day Trading: Traders can monitor the high and low of the current trading day to see if the price breaks through key levels.
Breakout Strategy: The custom horizontal lines provide reference points for potential breakout levels, with alerts helping traders act in real-time.
Support and Resistance: The plotted lines can represent predefined support or resistance levels, allowing traders to plan their entries and exits effectively.
The indicator gives a structured way to visualize price movements, highlight important price levels, and react quickly with alerts when the price crosses those levels.
Daily CRTDaily CRT Indicator
The Daily CRT Indicator is a custom technical analysis tool designed to help traders identify and visualize key price patterns on the daily timeframe. Specifically, it detects and marks the "Sweep and Close Inside" pattern, which is a price action pattern that can signal potential trading opportunities.
Key Features:
Pattern Detection:
The indicator detects two specific price action patterns:
Sweep and Close Above: When the current price sweeps above the previous day’s high and closes inside the range, indicating a potential bullish breakout or continuation.
Sweep and Close Below: When the current price sweeps below the previous day’s low and closes inside the range, signaling a potential bearish move.
Horizontal Lines:
The indicator automatically draws horizontal lines at the previous day’s high and low levels whenever a pattern is detected, providing a visual reference for key support and resistance zones.
These lines are displayed in real-time on the chart and adjust dynamically as new patterns form.
Customizable Line Appearance:
Choose the color, thickness, and style (solid, dashed, or dotted) of the lines to fit your preferred chart aesthetic.
Alert System:
The indicator comes with built-in alerts. Set an alert to notify you when the Sweep and Close Inside pattern is detected, helping you stay on top of potential trade setups.
History Management:
Show History: Optionally display the detected patterns on previous bars (past patterns).
Customizable History Duration: Control how far back you want to view the patterns, allowing you to adjust for a cleaner chart and focus on the most recent setups.
Visual Labels:
When the pattern is detected, the indicator can display a label under the bar (customizable) to highlight the occurrence of the pattern, making it easier for traders to spot potential trade signals.
Built for the Daily Timeframe:
This indicator is specifically designed to work on the daily timeframe and is ideal for swing traders and longer-term traders who are focused on the daily price action and want to capture patterns that indicate potential market reversals or breakouts.
How It Works:
The indicator monitors the previous day's price action and looks for situations where the current price action either sweeps the previous day's high or low and then closes inside the range of the previous day's bar. This type of price movement can often signal that a reversal or continuation is about to occur. The indicator marks these setups by drawing horizontal lines and optionally displays labels for quick identification.
Settings & Customization:
Line Color: Customize the color of the lines marking the previous day’s high and low.
Line Thickness: Choose from different thickness levels for better visibility.
Line Style: Pick from solid, dashed, or dotted styles.
Show History: Toggle the display of historical patterns, with the option to control how many days back to show.
Show Labels: Option to toggle the display of labels when the pattern is detected.
Alert Condition: Receive alerts when a pattern is detected, ensuring you never miss a trade opportunity.
Ideal For:
Swing Traders: This indicator is perfect for traders looking to capture swings in the market based on daily price action.
Pattern Traders: Those who trade based on specific chart patterns will benefit from this tool, as it identifies important reversal and breakout signals.
Technical Analysts: Anyone who incorporates price action patterns into their strategy can use this tool as a supplemental analysis tool to improve their trading decisions.
By using the Daily CRT Indicator, you’ll have a powerful tool to help you spot important price action patterns that may indicate key market moves. Whether you're looking to catch breakouts, reversals, or simply track significant support and resistance levels, this indicator is a versatile addition to your trading toolkit.
This description provides a clear understanding of how the Daily CRT Indicator works and what value it offers, making it easy for traders to know if it fits their trading style. Feel free to tweak the description further depending on the details you’d like to emphasize.
Globex time (New York Time)This indicator is designed to highlight and analyze price movements within the Globex session. Primarily geared toward the Globex Trap trading strategy, this tool visually identifies the session's high and low prices, allowing traders to better assess price action during extended hours. Here’s a comprehensive breakdown of its features and functionality:
Purpose
The "Globex Time (New York Time)" indicator tracks price levels during the Globex trading session, providing a clear view of overnight market activity. This session, typically running from 6 p.m. ET (18:00) until the following morning at 8:30 a.m. ET, is a critical period where significant market positioning can occur before the regular session opens. In the Globex Trap strategy, the session high and low are essential levels, as price movements around these areas often indicate potential support, resistance, or reversal zones, which traders use to set up entries or exits when the regular trading session begins.
Key Features
Customizable Session Start and End Times
The indicator allows users to specify the exact start and end times of the Globex session in New York time. The default settings are:
Start: 6 p.m. ET (18:00)
End: 8:30 a.m. ET
These settings can be adjusted to align with specific market hours or personal preferences.
Session High and Low Identification
Throughout the defined session, the indicator dynamically calculates and tracks:
Session High: The highest price reached within the session.
Session Low: The lowest price reached within the session.
These levels are essential for the Globex Trap strategy, as price action around them can indicate likely breakout or reversal points when regular trading resumes.
Vertical Lines for Session Start and End
The indicator draws vertical lines at both the session start and end times:
Session Start Line: A solid line marking the exact beginning of the Globex session.
Session End Line: A similar vertical line marking the session’s conclusion.
Both lines are customizable in terms of color and thickness, making it easy to distinguish the session boundaries visually on the chart.
Horizontal Lines for Session High and Low
At the end of the session, the indicator plots horizontal lines representing the Globex session's high and low levels. Users can customize these lines:
Color: Define specific colors for the session high (default: red) and session low (default: green) to easily differentiate them.
Line Style: Options to set the line style (solid, dashed, or dotted) provide flexibility for visual preferences and chart organization.
Automatic Reset for Daily Tracking
To adapt to the next trading day, the indicator resets the session high and low data once the current session ends. This reset prepares it to start tracking new levels at the beginning of the next session without manual intervention.
Practical Application in the Globex Trap Strategy
In the Globex Trap strategy, traders are primarily interested in price behavior around the high and low levels established during the overnight session. Common applications of this indicator for this strategy include:
Breakout Trades: Watching for price to break above the Globex high or below the Globex low, indicating potential momentum in the breakout direction.
Reversal Trades: Monitoring for failed breakouts or traps where price tests and rejects the Globex high or low, suggesting a reversal as liquidity is trapped in these zones.
Support and Resistance Zones: Using the session high and low as key support and resistance levels during the regular trading session, with potential entry or exit points when price approaches these areas.
Additional Configuration Options
Vertical Line Color and Width: Define the color and thickness of the vertical session start and end lines to match your chart’s theme.
Upper and Lower Line Colors and Styles: Customize the appearance of the session high and low horizontal lines by setting color and line style (solid, dashed, or dotted), making it easy to distinguish these critical levels from other chart markings.
Summary
This indicator is a valuable tool for traders implementing the Globex Trap strategy. It visually segments the Globex session and marks essential price levels, helping traders analyze market behavior overnight. Through its customizable options and clear visual representation, it simplifies tracking overnight price activity and identifying strategic levels for potential trade setups during the regular session.
Confirmed market structure buy/sell indicatorOverview
The Swing Point Breakout Indicator with Multi-Timeframe Dashboard is a TradingView tool designed to identify potential buy and sell signals based on swing point breakouts on the primary chart's timeframe while simultaneously providing a snapshot of the market structure across multiple higher timeframes. This dual approach helps traders make informed decisions by aligning short-term signals with broader market trends.
Key Features
Swing Point Breakout Detection
Swing Highs and Lows: Identifies significant peaks and troughs based on a user-defined lookback period.
Breakout Signals:
Bullish Breakout (Buy Signal): Triggered when the price closes above the latest swing high.
Bearish Breakout (Sell Signal): Triggered when the price closes below the latest swing low.
Visual Indicators: Highlights breakout bars with colors (lime for bullish, red for bearish) and plots buy/sell markers on the chart.
Multi-Timeframe Dashboard
Timeframes Monitored: 1m, 5m, 15m, 1h, 4h, 1D, and 1W.
Market Structure Status:
Bullish: Indicates upward market structure.
Bearish: Indicates downward market structure.
Neutral: No clear trend.
Visual Table: Displays each timeframe with its current status, color-coded for quick reference (green for bullish, red for bearish, gray for neutral).
Operational Workflow
Initialization:
Sets up a dashboard table on the chart's top-right corner with headers "Timeframe" and "Status".
Swing Point Detection:
Continuously scans the main timeframe for swing highs and lows using the specified lookback period.
Updates the latest swing high and low levels.
Signal Generation:
Detects when the price breaks above the last swing high (bullish) or below the last swing low (bearish).
Activates potential buy/sell setups and confirms signals based on subsequent price movements.
Dashboard Update:
For each defined higher timeframe, assesses the market structure by checking for breakouts of swing points.
Updates the dashboard with the current status for each timeframe, aiding in trend confirmation.
Visualization:
Colors the bars where breakouts occur.
Plots buy and sell signals directly on the chart for easy identification.
Value at Risk [OmegaTools]The "Value at Risk" (VaR) indicator is a powerful financial risk management tool that helps traders estimate the potential losses in a portfolio over a specified period of time, given a certain level of confidence. VaR is widely used by financial institutions, traders, and risk managers to assess the probability of portfolio losses in both normal and volatile market conditions. This TradingView script implements a comprehensive VaR calculation using several models, allowing users to visualize different risk scenarios and adjust their trading strategies accordingly.
Concept of Value at Risk
Value at Risk (VaR) is a statistical technique used to measure the likelihood of losses in a portfolio or financial asset due to market risks. In essence, it answers the question: "What is the maximum potential loss that could occur in a given portfolio over a specific time horizon, with a certain confidence level?" For instance, if a portfolio has a one-day 95% VaR of $10,000, it means that there is a 95% chance the portfolio will not lose more than $10,000 in a single day. Conversely, there is a 5% chance of losing more than $10,000. VaR is a key risk management tool for portfolio managers and traders because it quantifies potential losses in monetary terms, allowing for better-informed decision-making.
There are several ways to calculate VaR, and this indicator script incorporates three of the most commonly used models:
Historical VaR: This approach uses historical returns to estimate potential losses. It is based purely on past price data, assuming that the past distribution of returns is indicative of future risks.
Variance-Covariance VaR: This model assumes that asset returns follow a normal distribution and that the risk can be summarized using the mean and standard deviation of past returns. It is a parametric method that is widely used in financial risk management.
Exponentially Weighted Moving Average (EWMA) VaR: In this model, recent data points are given more weight than older data. This dynamic approach allows the VaR estimation to react more quickly to changes in market volatility, which is particularly useful during periods of market stress. This model uses the Exponential Weighted Moving Average Volatility Model.
How the Script Works
The script starts by offering users a set of customizable input settings. The first input allows the user to choose between two main calculation modes: "All" or "OCT" (Only Current Timeframe). In the "All" mode, the script calculates VaR using all available methodologies—Historical, Variance-Covariance, and EWMA—providing a comprehensive risk overview. The "OCT" mode narrows the calculation to the current timeframe, which can be particularly useful for intraday traders who need a more focused view of risk.
The next input is the lookback window, which defines the number of historical periods used to calculate VaR. Commonly used lookback periods include 21 days (approximately one month), 63 days (about three months), and 252 days (roughly one year), with the script supporting up to 504 days for more extended historical analysis. A longer lookback period provides a more comprehensive picture of risk but may be less responsive to recent market conditions.
The confidence level is another important setting in the script. This represents the probability that the loss will not exceed the VaR estimate. Standard confidence levels are 90%, 95%, and 99%. A higher confidence level results in a more conservative risk estimate, meaning that the calculated VaR will reflect a more extreme loss scenario.
In addition to these core settings, the script allows users to customize the visual appearance of the indicator. For example, traders can choose different colors for "Bullish" (Risk On), "Bearish" (Risk Off), and "Neutral" phases, as well as colors for highlighting "Breaks" in the data, where returns exceed the calculated VaR. These visual cues make it easy to identify periods of heightened risk at a glance.
The actual VaR calculation is broken down into several models, starting with the Historical VaR calculation. This is done by computing the logarithmic returns of the asset's closing prices and then using linear interpolation to determine the percentile corresponding to the desired confidence level. This percentile represents the potential loss in the asset over the lookback period.
Next, the script calculates Variance-Covariance VaR using the mean and standard deviation of the historical returns. The standard deviation is multiplied by a z-score corresponding to the chosen confidence level (e.g., 1.645 for 95% confidence), and the resulting value is subtracted from the mean return to arrive at the VaR estimate.
The EWMA VaR model uses the EWMA for the sigma parameter, the standard deviation, obtaining a specific dynamic in the volatility. It is particularly useful in volatile markets where recent price behavior is more indicative of future risk than older data.
For traders interested in intraday risk management, the script provides several methods to adjust VaR calculations for lower timeframes. By using intraday returns and scaling them according to the chosen timeframe, the script provides a dynamic view of risk throughout the trading day. This is especially important for short-term traders who need to manage their exposure during high-volatility periods within the same day. The script also incorporates an EWMA model for intraday data, which gives greater weight to the most recent intraday price movements.
In addition to calculating VaR, the script also attempts to detect periods where the asset's returns exceed the estimated VaR threshold, referred to as "Breaks." When the returns breach the VaR limit, the script highlights these instances on the chart, allowing traders to quickly identify periods of extreme risk. The script also calculates the average of these breaks and displays it for comparison, helping traders understand how frequently these high-risk periods occur.
The script further visualizes the risk scenario using a risk phase classification system. Depending on the level of risk, the script categorizes the market as either "Risk On," "Risk Off," or "Risk Neutral." In "Risk On" mode, the market is considered bullish, and the indicator displays a green background. In "Risk Off" mode, the market is bearish, and the background turns red. If the market is neither strongly bullish nor bearish, the background turns neutral, signaling a balanced risk environment.
Traders can customize whether they want to see this risk phase background, along with toggling the display of the various VaR models, the intraday methods, and the break signals. This flexibility allows traders to tailor the indicator to their specific needs, whether they are day traders looking for quick intraday insights or longer-term investors focused on historical risk analysis.
The "Risk On" and "Risk Off" phases calculated by this Value at Risk (VaR) script introduce a novel approach to market risk assessment, offering traders an advanced toolset to gauge market sentiment and potential risk levels dynamically. These risk phases are built on a combination of traditional VaR methodologies and proprietary logic to create a more responsive and intuitive way to manage exposure in both normal and volatile market conditions. This method of classifying market conditions into "Risk On," "Risk Off," or "Risk Neutral" is not something that has been traditionally associated with VaR, making it a groundbreaking addition to this indicator.
How the "Risk On" and "Risk Off" Phases Are Calculated
In typical VaR implementations, the focus is on calculating the potential losses at a given confidence level without providing an overall market outlook. This script, however, introduces a unique risk classification system that takes the output of various VaR models and translates it into actionable signals for traders, marking whether the market is in a Risk On, Risk Off, or Risk Neutral phase.
The Risk On and Risk Off phases are primarily determined by comparing the current returns of the asset to the average VaR calculated across several different methods, including Historical VaR, Variance-Covariance VaR, and EWMA VaR. Here's how the process works:
1. Threshold Setting and Effect Calculation: The script first computes the average VaR using the selected models. It then checks whether the current returns (expressed as a negative value to signify loss) exceed the average VaR value. If the current returns surpass the calculated VaR threshold, this indicates that the actual market risk is higher than expected, signaling a potential shift in market conditions.
2. Break Analysis: In addition to monitoring whether returns exceed the average VaR, the script counts the number of instances within the lookback period where this breach occurs. This is referred to as the "break effect." For each period in the lookback window, the script checks whether the returns surpass the calculated VaR threshold and increments a counter. The percentage of periods where this breach occurs is then calculated as the "effect" or break percentage.
3. Dual Effect Check (if "Double" Risk Scenario is selected): When the user chooses the "Double" risk scenario mode, the script performs two layers of analysis. First, it calculates the effect of returns exceeding the VaR threshold for the current timeframe. Then, it calculates the effect for the lower intraday timeframe as well. Both effects are compared to the user-defined confidence level (e.g., 95%). If both effects exceed the confidence level, the market is deemed to be in a high-risk situation, thus triggering a Risk Off phase. If both effects fall below the confidence level, the market is classified as Risk On.
4. Risk Phases Determination: The final risk phase is determined by analyzing these effects in relation to the confidence level:
- Risk On: If the calculated effect of breaks is lower than the confidence level (e.g., fewer than 5% of periods show returns exceeding the VaR threshold for a 95% confidence level), the market is considered to be in a relatively safe state, and the script signals a "Risk On" phase. This is indicative of bullish conditions where the potential for extreme loss is minimal.
- Risk Off: If the break effect exceeds the confidence level (e.g., more than 5% of periods show returns breaching the VaR threshold), the market is deemed to be in a high-risk state, and the script signals a "Risk Off" phase. This indicates bearish market conditions where the likelihood of significant losses is higher.
- Risk Neutral: If the break effect hovers near the confidence level or if there is no clear trend indicating a shift toward either extreme, the market is classified as "Risk Neutral." In this phase, neither bulls nor bears are dominant, and traders should remain cautious.
The phase color that the script uses helps visualize these risk phases. The background will turn green in Risk On conditions, red in Risk Off conditions, and gray in Risk Neutral phases, providing immediate visual feedback on market risk. In addition to this, when the "Double" risk scenario is selected, the background will only turn green or red if both the current and intraday timeframes confirm the respective risk phase. This double-checking process ensures that traders are only given a strong signal when both longer-term and short-term risks align, reducing the likelihood of false signals.
A New Way of Using Value at Risk
This innovative Risk On/Risk Off classification, based on the interaction between VaR thresholds and market returns, represents a significant departure from the traditional use of Value at Risk as a pure risk measurement tool. Typically, VaR is employed as a backward-looking measure of risk, providing a static estimate of potential losses over a given timeframe with no immediate actionable feedback on current market conditions. This script, however, dynamically interprets VaR results to create a forward-looking, real-time signal that informs traders whether they are operating in a favorable (Risk On) or unfavorable (Risk Off) environment.
By incorporating the "break effect" analysis and allowing users to view the VaR breaches as a percentage of past occurrences, the script adds a predictive element that can be used to time market entries and exits more effectively. This **dual-layer risk analysis**, particularly when using the "Double" scenario mode, adds further granularity by considering both current timeframe and intraday risks. Traders can therefore make more informed decisions not just based on historical risk data, but on how the market is behaving in real-time relative to those risk benchmarks.
This approach transforms the VaR indicator from a risk monitoring tool into a decision-making system that helps identify favorable trading opportunities while alerting users to potential market downturns. It provides a more holistic view of market conditions by combining both statistical risk measurement and intuitive phase-based market analysis. This level of integration between VaR methodologies and real-time signal generation has not been widely seen in the world of trading indicators, marking this script as a cutting-edge tool for risk management and market sentiment analysis.
I would like to express my sincere gratitude to @skewedzeta for his invaluable contribution to the final script. From generating fresh ideas to applying his expertise in reviewing the formula, his support has been instrumental in refining the outcome.
STANDARD DEVIATION INDICATOR BY WISE TRADERWISE TRADER STANDARD DEVIATION SETUP: The Ultimate Volatility and Trend Analysis Tool
Unlock the power of STANDARD DEVIATIONS like never before with the this indicator, a versatile and comprehensive tool designed for traders who seek deeper insights into market volatility, trend strength, and price action. This advanced indicator simultaneously plots three sets of customizable Deviations, each with unique settings for moving average types, standard deviations, and periods. Whether you’re a swing trader, day trader, or long-term investor, the STANDARD DEVIATION indicator provides a dynamic way to spot potential reversals, breakouts, and trend-following opportunities.
Key Features:
STANDARD DEVIATIONS Configuration : Monitor three different Bollinger Bands at the same time, allowing for multi-timeframe analysis within a single chart.
Customizable Moving Average Types: Choose from SMA, EMA, SMMA (RMA), WMA, and VWMA to calculate the basis of each band according to your preferred method.
Dynamic Standard Deviations: Set different standard deviation multipliers for each band to fine-tune sensitivity for various market conditions.
Visual Clarity: Color-coded bands with adjustable thicknesses provide a clear view of upper and lower boundaries, along with fill backgrounds to highlight price ranges effectively.
Enhanced Trend Detection: Identify potential trend continuation, consolidation, or reversal zones based on the position and interaction of price with the three bands.
Offset Adjustment: Shift the bands forward or backward to analyze future or past price movements more effectively.
Why Use Triple STANDARD DEVIATIONS ?
STANDARD DEVIATIONS are a popular choice among traders for measuring volatility and anticipating potential price movements. This indicator takes STANDARD DEVIATIONS to the next level by allowing you to customize and analyze three distinct bands simultaneously, providing an unparalleled view of market dynamics. Use it to:
Spot Volatility Expansion and Contraction: Track periods of high and low volatility as prices move toward or away from the bands.
Identify Overbought or Oversold Conditions: Monitor when prices reach extreme levels compared to historical volatility to gauge potential reversal points.
Validate Breakouts: Confirm the strength of a breakout when prices move beyond the outer bands.
Optimize Risk Management: Enhance your strategy's risk-reward ratio by dynamically adjusting stop-loss and take-profit levels based on band positions.
Ideal For:
Forex, Stocks, Cryptocurrencies, and Commodities Traders looking to enhance their technical analysis.
Scalpers and Day Traders who need rapid insights into market conditions.
Swing Traders and Long-Term Investors seeking to confirm entry and exit points.
Trend Followers and Mean Reversion Traders interested in combining both strategies for maximum profitability.
Harness the full potential of STANDARD DEVIATIONS with this multi-dimensional approach. The "STANDARD DEVIATIONS " indicator by WISE TRADER will become an essential part of your trading arsenal, helping you make more informed decisions, reduce risks, and seize profitable opportunities.
Who is WISE TRADER ?
Wise Trader is a highly skilled trader who launched his channel in 2020 during the COVID-19 pandemic, quickly building a loyal following. With thousands of paid subscribed members and over 70,000 YouTube subscribers, Wise Trader has become a trusted authority in the trading world. He is known for his ability to navigate significant events, such as the Indian elections and stock market crashes, providing his audience with valuable insights into market movements and volatility. With a deep understanding of macroeconomics and its correlation to global stock markets, Wise Trader shares informed strategies that help traders make better decisions. His content covers technical analysis, trading setups, economic indicators, and market trends, offering a comprehensive approach to understanding financial markets. The channel serves as a go-to resource for traders who want to enhance their skills and stay informed about key market developments.
Kurutoga Histogram with HTF and LTF
Kurutoga Histogram:
The Kurutoga Histogram is a technical analysis indicator designed to measure price divergence from the 50% level of a recent price range. By calculating how far the current price is from the midpoint of a selected base length of candles, the histogram provides insight into the momentum, strength, and potential reversals in the market. Additionally, it can be applied across multiple timeframes to provide a comprehensive view of both short- and long-term market dynamics.
Key Components:
Base Length:
The base length is the number of candles (bars) over which the high and low prices are observed. The default base length is typically 14 periods, but it can be adjusted according to the trader's preference.
This base length defines the range from which the 50% level, or midpoint, is calculated.
50% Level (Midpoint):
The midpoint is the average of the highest high and the lowest low over the selected base length. This 50% level acts as an equilibrium point around which the price fluctuates.
Formula:
Midpoint = (Highest High + Lowest Low) / 2
The price’s distance from this midpoint is an indicator of how strong the current trend or divergence is.
Price Divergence:
The main calculation of the histogram is the difference between the current closing price and the midpoint of the price range.
Formula:
Divergence = Close Price − Midpoint
A positive divergence (price above the midpoint) indicates bullish strength, while a negative divergence (price below the midpoint) indicates bearish strength.
Multi-Timeframe Analysis:
The Kurutoga Histogram can be applied to both the current timeframe and a higher timeframe (HTF), allowing traders to gauge price movement in both short-term and long-term contexts.
By comparing the histograms of multiple timeframes, traders can determine if there is alignment (confluence) between trends, which can strengthen trade signals or provide additional confirmation.
Color-Coded Histogram:
Blue Bars (Positive Divergence): Represent that the price is above the 50% level, indicating bullish momentum. Taller blue bars suggest stronger upward momentum, while shrinking bars suggest weakening strength.
Red Bars (Negative Divergence): Represent that the price is below the 50% level, indicating bearish momentum. Taller red bars suggest stronger downward momentum, while shrinking bars suggest a potential reversal or consolidation.
The histogram’s color intensity and transparency can be adjusted to enhance the visual effect, distinguishing between current timeframe (LTF) and higher timeframe (HTF) divergence.
Interpretation:
Bullish Signals: When the histogram bars are blue and growing, the price is gaining momentum above the midpoint of its recent range. This could signal an ongoing uptrend.
Bearish Signals: When the histogram bars are red and growing, the price is gaining momentum below the midpoint, signaling an ongoing downtrend.
Momentum Shifts: When the histogram bars shrink in size (whether blue or red), it could indicate that the current trend is losing strength and may reverse or enter consolidation.
Neutral or Sideways Movement: When the histogram bars hover around zero, it means the price is trading near the midpoint of its recent range, often signaling a lack of strong momentum in either direction.
Multi-Timeframe Confluence:
When the current timeframe (LTF) histogram aligns with the higher timeframe (HTF) histogram (e.g., both are showing strong bullish or bearish divergence), it may provide stronger confirmation of the trend's strength.
Divergence between timeframes (e.g., bullish on LTF but bearish on HTF) may suggest that price movements on lower timeframes are not yet reflected in the broader trend, signaling caution.
Applications:
Trend Identification: The Kurutoga Histogram is highly useful for detecting when the price is trending away from its equilibrium point, providing insight into the strength of ongoing trends.
Momentum Analysis: By measuring the divergence from the 50% level, the histogram helps traders identify when momentum is increasing or decreasing.
Reversal Detection: Shrinking histogram bars can signal weakening momentum, which often precedes trend reversals.
Consolidation and Breakouts: When the histogram remains near zero for an extended period, it suggests consolidation, which often precedes a breakout in either direction.
Advantages:
Clear Visuals: The use of a color-coded histogram makes it easy to visually assess whether the market is gaining bullish or bearish momentum.
Multi-Timeframe Utility: The ability to compare current timeframe signals with higher timeframe signals adds an extra layer of confirmation, reducing false signals.
Dynamic Adjustment: By adjusting the base length, traders can fine-tune the sensitivity of the indicator to match different markets or trading styles.
Limitations:
Lagging Indicator: Like most divergence indicators, the Kurutoga Histogram may lag slightly behind actual price movements, especially during fast, volatile markets.
Requires Confirmation: This indicator works best when used in conjunction with other technical tools like moving averages, support/resistance levels, or volume indicators, to avoid relying on divergence alone.
Conclusion:
The Kurutoga Histogram is a versatile and visually intuitive tool for measuring price divergence from a key equilibrium point, helping traders to assess the strength of trends and identify potential reversal points. Its use across multiple timeframes provides deeper insights, making it a valuable addition to any trading strategy that emphasizes momentum and trend following.
Swiss Knife [MERT]Introduction
The Swiss Knife indicator is a comprehensive trading tool designed to provide a multi-dimensional analysis of the market. By integrating a wide array of technical indicators across multiple timeframes, it offers traders a holistic view of market sentiment, momentum, and potential reversal points. This indicator is particularly useful for traders looking to combine trend analysis, momentum indicators, volume data, and price action into a single, easy-to-read format.
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Key Features
Multi-Timeframe Analysis : Evaluates indicators on Daily , 4-Hour , 1-Hour , and 15-Minute timeframes.
Comprehensive Indicator Suite : Incorporates MACD , Awesome Oscillator (AO) , Parabolic SAR , SuperTrend , DPO , RSI , Stochastic Oscillator , Bollinger Bands , Ichimoku Cloud , Chande Momentum Oscillator (CMO) , Donchian Channels , ADX , volume-based momentum indicators, Fractals , and divergence detection.
Market Sentiment Scoring : Aggregates signals from multiple indicators to provide an overall sentiment score.
Visual Aids : Displays EMA lines, trendlines, divergence signals, and a sentiment table directly on the chart.
Super Trend Reversal Signals : Identifies potential market reversal points by assessing the momentum of automated trading bots.
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Explanation of Each Indicator
Moving Average Convergence Divergence (MACD)
- Purpose : Measures the relationship between two moving averages of price.
- Interpretation : A positive histogram suggests bullish momentum; a negative histogram indicates bearish momentum.
Awesome Oscillator (AO)
- Purpose : Gauges market momentum by comparing recent market movements to historic ones.
- Interpretation : Above zero indicates bullish momentum; below zero indicates bearish momentum.
Parabolic SAR (SAR)
- Purpose : Identifies potential reversal points in price direction.
- Interpretation : Dots below price suggest an uptrend; dots above price suggest a downtrend.
SuperTrend
- Purpose : Determines the prevailing market trend.
- Interpretation : Provides buy or sell signals based on price movements relative to the SuperTrend line.
Detrended Price Oscillator (DPO)
- Purpose : Removes trend from price to identify cycles.
- Interpretation : Values above zero suggest price is above the moving average; values below zero indicate it is below.
Relative Strength Index (RSI)
- Purpose : Measures the speed and change of price movements.
- Interpretation : Values above 50 indicate bullish momentum; values below 50 indicate bearish momentum.
Stochastic Oscillator
- Purpose : Compares a particular closing price to a range of its prices over a certain period.
- Interpretation : Values above 50 indicate bullish conditions; values below 50 indicate bearish conditions.
Bollinger Bands (BB)
- Purpose : Measures market volatility and provides relative price levels.
- Interpretation : Price above the middle band suggests bullishness; below the middle band suggests bearishness.
Ichimoku Cloud
- Purpose : Provides support and resistance levels, trend direction, and momentum.
- Interpretation : Bullish signals when price is above the cloud; bearish signals when price is below the cloud.
Chande Momentum Oscillator (CMO)
- Purpose : Measures momentum on both up and down days.
- Interpretation : Values above 50 indicate strong upward momentum; values below -50 indicate strong downward momentum.
Donchian Channels
- Purpose : Identifies volatility and potential breakouts.
- Interpretation : Price above the upper band suggests bullish breakout; below the lower band suggests bearish breakout.
Average Directional Index (ADX)
- Purpose : Measures the strength of a trend.
- Interpretation : DI+ above DI- indicates bullish trend; DI- above DI+ indicates bearish trend.
Volume Momentum Indicators (VolMom, CumVolMom, POCMom)
- Purpose : Analyze volume to assess buying and selling pressure.
- Interpretation : Positive values suggest bullish volume momentum; negative values indicate bearish volume momentum.
Fractals
- Purpose : Identify potential reversal points in the market.
- Interpretation : Up fractals may indicate a future downtrend; down fractals may indicate a future uptrend.
Divergence Detection
- Purpose : Identifies divergences between price and various indicators (RSI, MACD, Stochastic, OBV, MFI, A/D Line).
- Interpretation : Bullish divergences suggest potential upward reversal; bearish divergences suggest potential downward reversal.
- Note : This functionality utilizes the library from Divergence Indicator .
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Coloring Scheme
Background Color
- Purpose : Reflects the overall market sentiment by combining sentiment scores from all indicators across different timeframes.
- Interpretation :
- Green Shades : Indicate bullish market sentiment.
- Red Shades : Indicate bearish market sentiment.
- Intensity : The strength of the color corresponds to the strength of the sentiment score.
Sentiment Table
- Purpose : Displays the status of each indicator across different timeframes.
- Interpretation :
- Green Cell : The indicator suggests a bullish signal.
- Red Cell : The indicator suggests a bearish signal.
- Percentage Score : Indicates the overall bullish or bearish sentiment on that timeframe.
Exponential Moving Averages (EMAs)
- Purpose : Provide dynamic support and resistance levels.
- Colors :
- EMA 10 : Lime
- EMA 20 : Yellow
- EMA 50 : Orange
- EMA 100 : Red
- EMA 200 : Purple
Trendlines
- Purpose : Visual representation of support and resistance levels based on pivot points.
- Interpretation :
- Upward Trendlines : Colored green , indicating support levels.
- Downward Trendlines : Colored red , indicating resistance levels.
- Note : Trendlines are drawn using the library from Simple Trendlines .
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Utility of Market Sentiment
The indicator aggregates signals from multiple technical indicators across various timeframes to compute an overall market sentiment score . This comprehensive approach helps traders understand the prevailing market conditions by:
Confirming Trends : Multiple indicators pointing in the same direction can confirm the strength of a trend.
Identifying Reversals : Divergences and fractals can signal potential turning points.
Timeframe Alignment : Aligning signals across different timeframes can enhance the probability of successful trades.
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Divergences
Divergence occurs when the price of an asset moves in the opposite direction of a technical indicator, suggesting a potential reversal.
- Bullish Divergence : Price makes a lower low, but the indicator makes a higher low.
- Bearish Divergence : Price makes a higher high, but the indicator makes a lower high.
The indicator detects divergences for:
RSI
MACD
Stochastic Oscillator
On-Balance Volume (OBV)
Money Flow Index (MFI)
Accumulation/Distribution Line (A/D Line)
By identifying these divergences, traders can spot early signs of trend reversals and adjust their strategies accordingly.
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Trendlines
Trendlines are essential tools for identifying support and resistance levels. The indicator automatically draws trendlines based on pivot points:
- Upward Trendlines (Support) : Connect higher lows, indicating an uptrend.
- Downward Trendlines (Resistance) : Connect lower highs, indicating a downtrend.
These trendlines help traders visualize the trend direction and potential breakout or reversal points.
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Super Trend Reversals (ST Reversal)
The core idea behind the Super Trend Reversals indicator is to assess the momentum of automated trading bots (often referred to as 'Supertrend bots') that enter the market during critical turning points. Specifically, the indicator is tuned to identify when the market is nearing bottoms or peaks, just before it shifts direction based on the triggered Supertrend signals. This approach helps traders:
Engage Early : Enter the market as reversal momentum builds up.
Optimize Entries and Exits : Enter under favorable conditions and exit before momentum wanes.
By capturing these reversal points, traders can enhance their trading performance.
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Conclusion
The Swiss Knife indicator serves as a versatile tool that combines multiple technical analysis methods into a single, comprehensive indicator. By assessing various aspects of the market—including trend direction, momentum, volume, and price action—it provides traders with valuable insights to make informed trading decisions.
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Citations
- Divergence Detection Library : Divergence Indicator by DevLucem
- Trendline Drawing Library : Simple Trendlines by HoanGhetti
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Note : This indicator is intended for informational purposes and should be used in conjunction with other analysis techniques. Always perform due diligence before making trading decisions.
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Change in State of Delivery CISD ICT [TradingFinder] Liquidity 1🔵 Introduction
🟣 What is CISD ?
Change in State of Delivery (CISD) is a key concept in technical analysis, similar to Change of Character (ChoCh) and Market Structure Shift (MSS) in the ICT (Inner Circle Trader) and Smart Money trading styles. Like ChoCh and MSS, CISD helps traders identify critical changes in market structure and make timely entries into trades.
To determine the CISD Level, traders typically review the last 1 to 4 candles to identify the first positive or negative candle. The CISD Level is then set using the opening price of the next candle.
In this version of the indicator, support and resistance levels are defined based on liquidity, which includes patterns such as SFP (Swing Failure Pattern), fake breakout, and false breakout.
Bullish CISD :
Bearish CISD :
🔵 How to Use
🟣 Bullish CISD (Change in State of Delivery Upward)
In Bullish CISD, the trend shifts from bearish to bullish after the price hits a liquidity zone, typically indicated by patterns such as SFP, fake breakout, or false breakout.
The steps to identify Bullish CISD are as follow s:
Identify the liquidity zone (SFP, fake breakout).
Review the candles and find the first positive candle.
Set the CISD Level using the opening price of the next candle after the positive candle.
Confirm the change in state of delivery when the price closes above the CISD Level.
Enter the trade after CISD confirmation.
🟣 Bearish CISD (Change in State of Delivery Downward)
In Bearish CISD, the trader looks for a shift from a bullish to a bearish trend. This change typically occurs when the price hits a liquidity level, indicated by patterns such as SFP or false breakout.
The steps to identify Bearish CISD are :
Identify the liquidity zone.
Review the candles and find the first negative candle.
Set the CISD Level using the opening price of the next candle after the negative candle.
Confirm the change in state of delivery when the price closes below the CISD Level.
Enter a short trade after CISD confirmation.
🟣 CISD Compared to ChoCh and MSS (CISD Vs ChoCh/ MSS)
CISD, ChoCh, and MSS are all tools for identifying trend changes in the market, but they have some differences :
CISD: Focuses on a change in the state of delivery and uses liquidity patterns (SFP, fake breakout) and key candles to confirm trend reversals.
ChoCh: Identifies a change in the market’s character, often signaling rapid shifts in trend direction.
MSS: Focuses on changes in market structure and identifies the breaking of key levels as a signal of trend shifts.
🔵 Settings
🟣 CISD Logical settings
Bar Back Check : Determining the return of candles to identify the CISD level.
CISD Level Validity : CISD level validity period based on the number of candles.
🟣 SFP Logical settings
Swing period : You can set the swing detection period.
Max Swing Back Method : It is in two modes "All" and "Custom". If it is in "All" mode, it will check all swings, and if it is in "Custom" mode, it will check the swings to the extent you determine.
Max Swing Back : You can set the number of swings that will go back for checking.
🟣 CISD Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🟣 SFP Display settings
Displaying or not displaying swings and setting the color of labels and lines.
🔵 Conclusion
CISD is a powerful tool for identifying trend reversals using liquidity patterns and key candle analysis. Traders can use the CISD Level to detect trend changes and find optimal entry and exit points.
This concept is similar to ChoCh and MSS but stands out with its focus on confirming trend changes through liquidity and specific patterns. With the right approach, CISD helps traders capitalize on market movements more effectively.
Change in State of Delivery (CISD) [LuxAlgo]The Change In State Of Delivery (CISD) indicator detects and displays Change in State Of Delivery, a concept related to market structures.
Users can choose between two different CISD detection methods. Various filtering options are also included to filter out less significant CISDs.
🔶 USAGE
A Change in State of Delivery (CISD) is a concept closely related to market structures, where price breaks a level of interest, confirming trends and their continuations from the resulting breakouts.
Unlike more traditional market structures which rely on swing points, CISDs rely on a persistent sequence of candles, using the sequence extremes as breakout levels.
CISDs are detected as follows:
Bullish: The price closes above the opening price of the first candle in a sequence of bearish candles (or its own opening price if it's the only candle).
Bearish: The price closes below the opening price of the first candle in a sequence of bullish candles (or its own opening price if it's the only candle).
If a newly detected CISD aligns with the indicator's current established trend, this confirms a trend continuation (represented with a dashed line).
On the other hand, if a newly detected CISD is in the opposite direction to the detected trend it can confirm a trend reversal (represented with a solid line).
🔹 Liquidity Sweep Detection Method
Using Liquidity Sweeps to update CISD breakout levels allows us to obtain less frequent and more relevant levels that are less sensitive to noisy price variations.
Sweeps are obtained from detected Swing Points , with a higher Swing Length allowing us to obtain longer-term swing levels and potentially more detected sweeps from a specific level over time.
Note: The 'Swing Length' setting is only applicable on the Liquidity Sweep Detection Method and will only change the Liquidity levels.
A Liquidity Sweep is valid when the price reaches an important liquidity level , after which the price closes below/above this level.
Bullish scenario: The price goes below a previous unbroken Swing Low but closes above.
Bearish scenario: The price goes above a previous unbroken Swing High but closes below.
After a Liquidity Sweep has been detected, the last level of importance acts as support/resistance . Breaking this level in the other direction changes the state of delivery .
Users must keep observing the price and significant levels, as highlighted by the white rectangle in the above example.
🔹 CISD Filtering
Users can adjust the following two settings:
Minimum CISD Duration: The minimum length of the 'CISD' line
Maximum Swing Validity: The maximum length of the 'CISD' line; potential CISD lines that aren't broken are deleted when exceeding the limit.
The chart can get cluttered when the Minimum CISD Duration is low. Users could focus on a switch in trend (first solid line CISD ), where the following dashed CISD lines can be seen as extra opportunities/confirmations.
🔶 DETAIL
🔹 Using Different Timeframes
When an important liquidity level (Previous Swing high/low, FVG, etc.) is reached on the higher timeframe, the user can move to a lower timeframe to check whether there is a CISD .
Above example:
The high of the last candle breaches a liquidity level (previous Swing High). The opening price of the last candle acts as a trigger/confirmation level.
A confirmed CISD is seen in a lower timeframe, just after this Liquidity Sweep. This could be an early opportunity.
Later, a confirmed CISD on the higher timeframe is established.
🔶 SETTINGS
Detection Method: Classic or Liquidity Sweep
Swing Length: Period used for the swing detection, with higher values returning longer-term Swing Levels.
Minimum CISD Duration: The minimum length of the CISD line
Maximum Swing Validity: The maximum length of the CISD line; potential CISD lines that aren't broken are deleted when exceeding the limit.
Market Analysis Assistant This indicator uniquely maps and interprets key market conditions using Moving Averages, MACD, RSI, and Bollinger Bands. Unlike traditional indicators that only display visual signals, this tool provides written analysis directly on your chart as soon as specific conditions are met. This feature makes it easier to understand the market’s current state and anticipate potential moves.
Why Moving Averages? Moving Averages are essential for identifying the overall trend of the market. By analyzing the 200, 20, and 9-period Moving Averages, this indicator helps traders quickly determine whether the market is in an uptrend, downtrend, or sideways phase. The integration of multiple averages offers a comprehensive view, allowing for more accurate trend identification.
Why MACD? The MACD is a powerful tool for spotting trend reversals and momentum shifts. By monitoring MACD crossovers, divergences, and the position of the MACD line relative to the zero line, this indicator helps you identify potential changes in the trend direction before they fully develop, giving you a critical edge.
Why RSI? RSI is crucial for understanding the market's overbought and oversold conditions. By tracking RSI levels and its crossover with its moving average, this indicator provides early warnings for potential trend reversals or continuations, helping you time your entries and exits more effectively.
Why Bollinger Bands? Bollinger Bands are used to measure market volatility and identify breakout opportunities. By analyzing the price’s relationship with the upper and lower bands, this indicator helps traders spot potential overbought or oversold conditions, as well as possible breakout scenarios, offering a clear view of market dynamics.
Trend Identification (getTrend()): Detects whether the market is in an uptrend, downtrend, or sideways phase by analyzing the position of the price relative to the 200, 20, and 9-period moving averages.
MACD Analysis (analyzeMACD()): Identifies potential trend reversals or continuations through MACD divergence, crossovers, and the MACD signal line's position relative to the zero line.
RSI Monitoring (analyzeRSI()): Detects overbought and oversold conditions and anticipates trend continuation or corrections based on RSI crossings with its moving average.
Trap Zone Detection (analyzeTrapZone()): Highlights areas of potential price consolidation between the 20 and 200-period moving averages, indicating possible breakouts.
Bollinger Bands Analysis (analyzeBollingerBands()): Analyzes the price’s relationship with Bollinger Bands to identify overbought/oversold conditions, breakouts, and potential trend continuations or correction.
Fibonacci retracement will also check the moment the price tests a monthly or daily weekly Fibonacci retracement
What Makes This Indicator Unique?
This indicator stands out by transforming complex technical analysis into clear, written insights directly on your chart. As soon as specific conditions are met—such as a MACD crossover or an RSI overbought/oversold level—this tool immediately displays a written summary of the event, helping traders to quickly understand and act on market developments.
How to Use My Indicator:
The indicator is designed to provide detailed, real-time market condition analysis using Moving Averages, MACD, RSI, and Bollinger Bands. When certain market conditions are met, such as the price testing a specific moving average or the MACD indicating a potential reversal, the indicator displays this information in written form directly on the chart, in both English and Portuguese.
How to Interpret the Displayed Information:
The information displayed by the indicator can be used for:
Identifying Support and Resistance: The indicator can help identify when the price is testing an important support or resistance level, such as a moving average or a Fibonacci level, allowing the user to decide whether to enter or exit a position.
Trend Detection: If the indicator shows that the price is above the 200, 20, and 9-period moving averages, this may be a sign of an uptrend, indicating that the user should consider maintaining or opening buy positions.
Correction Signals: When the MACD indicates a potential correction, the user may decide to protect their profits by adjusting stops or even exiting the position to avoid losses.
Identifying Overbought/Oversold Conditions: Based on the RSI, the indicator can alert to overbought or oversold conditions, helping the user avoid entering a trade at an unfavorable time.
Example of Use:
the indicator shows several important pieces of information, such as:
"US100 Price is at the 50.0% Fibonacci level (Last Monthly)."
This suggests that the price is testing a significant Fibonacci level, which could be a point of reversal or continuation. A trader can use this information to adjust their entry or exit strategy.
"DXY RSI below 30: Indication of oversold condition"
This indicates that the DXY is in an oversold condition, which might suggest an upcoming bullish reversal. A trader could consider this when trading DXY-related assets.
"Bullish Trend: Price is above the 200, 20, and 9-period moving averages."
This confirms an uptrend, giving the user more confidence to hold long positions.
Availability:
This indicator is available in two languages: English and Portuguese. It is ideal for traders who prefer analysis in English as well as those who prefer it in Portuguese, making it a versatile and accessible tool for traders from different backgrounds
Este indicador mapeia e interpreta de forma única as principais condições de mercado utilizando Médias Móveis, MACD, RSI e Bandas de Bollinger. Ao contrário dos indicadores tradicionais que apenas exibem sinais visuais, esta ferramenta oferece uma análise escrita diretamente no seu gráfico assim que determinadas condições são atendidas. Isso facilita o entendimento do estado atual do mercado e a antecipação de possíveis movimentos.
Por que Médias Móveis? As Médias Móveis são essenciais para identificar a tendência geral do mercado. Ao analisar as Médias Móveis de 200, 20 e 9 períodos, este indicador ajuda os traders a determinarem rapidamente se o mercado está em tendência de alta, baixa ou em fase lateral. A integração de múltiplas médias oferece uma visão abrangente, permitindo uma identificação mais precisa das tendências.
Por que MACD? O MACD é uma ferramenta poderosa para identificar reversões de tendência e mudanças de momentum. Monitorando os cruzamentos do MACD, divergências e a posição da linha MACD em relação à linha zero, este indicador ajuda você a identificar possíveis mudanças na direção da tendência antes que elas se desenvolvam completamente, dando-lhe uma vantagem crítica.
Por que RSI? O RSI é crucial para entender as condições de sobrecompra e sobrevenda do mercado. Acompanhando os níveis do RSI e seu cruzamento com sua média móvel, este indicador fornece avisos antecipados para possíveis reversões ou continuações de tendência, ajudando você a cronometrar suas entradas e saídas de forma mais eficaz.
Por que Bandas de Bollinger? As Bandas de Bollinger são usadas para medir a volatilidade do mercado e identificar oportunidades de rompimento. Ao analisar a relação do preço com as bandas superior e inferior, este indicador ajuda os traders a identificar condições de sobrecompra ou sobrevenda, bem como possíveis cenários de rompimento, oferecendo uma visão clara da dinâmica do mercado.
Identificação de Tendências (getTrend()): Detecta se o mercado está em tendência de alta, baixa ou em fase lateral, analisando a posição do preço em relação às médias móveis de 200, 20 e 9 períodos.
Análise de MACD (analyzeMACD()): Identifica possíveis reversões ou continuações de tendência através de divergências do MACD, cruzamentos, e a posição da linha de sinal do MACD em relação à linha zero.
Monitoramento do RSI (analyzeRSI()): Detecta condições de sobrecompra e sobrevenda e antecipa a continuação da tendência ou correções com base nos cruzamentos do RSI com sua média móvel.
Detecção de Zona de Armadilha (analyzeTrapZone()): Destaca áreas de possível consolidação de preços entre as médias móveis de 20 e 200 períodos, indicando possíveis rompimentos.
Análise das Bandas de Bollinger (analyzeBollingerBands()): Analisa a relação do preço com as Bandas de Bollinger para identificar condições de sobrecompra/sobrevenda, rompimentos e possíveis continuações de tendência ou correção.
A retração de Fibonacci também verificará o momento em que o preço testa uma retração de Fibonacci semanal mensal ou diária
O que Torna Este Indicador Único?
Este indicador se destaca por transformar análises técnicas complexas em insights escritos claros diretamente no seu gráfico. Assim que condições específicas são atendidas—como um cruzamento do MACD ou um nível de sobrecompra/sobrevenda do RSI—esta ferramenta exibe imediatamente um resumo escrito do evento, ajudando os traders a entenderem e agirem rapidamente sobre as mudanças do mercado.
Como Utilizar o Meu Indicador:
O indicador foi desenvolvido para oferecer uma análise detalhada e em tempo real das condições de mercado, utilizando os conceitos de Médias Móveis, MACD, RSI e Bandas de Bollinger. Quando certas condições de mercado são atingidas, como o preço testando uma média móvel específica ou o MACD indicando uma possível reversão, o indicador exibe essas informações de forma escrita diretamente no gráfico, em inglês e português.
Como Interpretar as Informações Exibidas:
As informações exibidas pelo indicador podem ser usadas para:
Identificação de Suportes e Resistências: O indicador pode ajudar a identificar quando o preço está testando um nível de suporte ou resistência importante, como uma média móvel ou um nível de Fibonacci, permitindo ao usuário decidir se deve entrar ou sair de uma posição.
Detecção de Tendências: Se o indicador mostra que o preço está acima das médias móveis de 200, 20 e 9 períodos, isso pode ser um sinal de uma tendência de alta, indicando que o usuário deve considerar manter ou abrir posições de compra.
Sinais de Correção: Quando o MACD indica uma possível correção, o usuário pode decidir proteger seus lucros ajustando os stops ou até mesmo saindo da posição para evitar perdas.
Identificação de Condições de Sobrecompra/Sobrevenda: Com base no RSI, o indicador pode alertar sobre condições de sobrecompra ou sobrevenda, ajudando o usuário a evitar entrar em uma operação em um momento desfavorável.
Exemplo de Utilização:
o indicador mostra várias informações importantes, como:
"O preço do US100 está no nível de Fibonacci de 50,0% (mês passado)."
Isso sugere que o preço está testando um nível significativo de Fibonacci, o que pode ser um ponto de reversão ou continuação. Um trader pode usar essa informação para ajustar sua estratégia de entrada ou saída.
DXY RSI abaixo de 30: Indicação de condição de sobrevenda"
Isso indica que o DXY está em uma condição de sobrevenda, o que pode sugerir uma reversão de alta em breve. Um trader pode considerar isso ao fazer operações relacionadas ao DXY.
"Tendência de alta: o preço está acima das médias móveis de 200, 20 e 9 períodos."
Isso confirma uma tendência de alta, dando ao usuário mais confiança para manter posições longas.
Disponibilidade:
Este indicador está disponível em dois idiomas: inglês e português. Ele é ideal tanto para traders que preferem análises em inglês quanto para aqueles que preferem em português. Isso o torna uma ferramenta versátil e acessível para traders de diferentes origens.
Enhanced BOS Strategy with SL/TP and EMA TableDescription:
The Enhanced BOS (Break of Structure) Strategy is an advanced open-source trading indicator designed to identify key market structure changes, integrated with dynamic Stop Loss (SL) and Take Profit (TP) levels, along with an informative EMA (Exponential Moving Average) table for added trend analysis.
Key Features:
Break of Structure (BOS) Detection:
The script detects bullish and bearish BOS by identifying pivot points using a custom pivot period. When the price crosses above or below these points, it signals a potential market trend reversal or continuation.
Dynamic SL/TP Levels:
Users can toggle static SL/TP settings, which automatically calculate levels based on user-defined points. These levels are visualized on the chart with dotted lines and labeled for clarity.
Volume Filters:
The strategy includes a volume condition filter to ensure that only trades within a specified volume range are considered. This helps in avoiding low-volume trades that might lead to false signals.
EMA Table Display:
An on-chart table displaying the current values of the 13-period, 50-period, and 200-period EMAs. This provides a quick reference for trend identification and confirmation, helping traders to stay aligned with the broader market trend.
How It Works:
The script utilizes a combination of moving averages and pivot points to identify potential breakouts or breakdowns in market structure. When a bullish BOS is detected, and the volume conditions are met, the strategy suggests a long position, marking potential SL/TP levels. Similarly, it suggests short positions for bearish BOS.
The EMA table serves as a visual aid, providing real-time updates of the EMA values, allowing traders to gauge the market’s directional bias quickly.
How to Use:
Setting Parameters:
Adjust the pivot period to fine-tune BOS detection according to your trading style and the asset’s volatility.
Configure the SL/TP settings based on your risk tolerance and target profit levels.
Interpreting Signals:
A “Buy” label on the chart indicates a bullish BOS with volume confirmation, signaling a potential long entry.
A “Sell” label indicates a bearish BOS with volume confirmation, signaling a potential short entry.
The EMA table aids in confirming these signals, where the position of the fast, mid, and slow EMAs can provide additional context to the trend’s strength and direction.
Volume Filtering:
Ensure your trades are filtered through the script’s volume condition, which allows for the exclusion of low-volume periods that might generate unreliable signals.
Unique Value:
Unlike many other BOS strategies, this script integrates volume conditions and a visual EMA table, providing a comprehensive toolkit for traders looking to capture market structure shifts while maintaining an eye on trend direction and trade execution precision.
Additional Information:
This script is designed for use on standard bar or candlestick charts for best results.
It is open-source and free to use, encouraging collaboration and improvement by the TradingView community.
By combining powerful trend-following EMAs with the precision of BOS detection and the safety of volume filtering, the Enhanced BOS Strategy offers a balanced approach to trading market structure changes.
Composite Z-Score with Linear Regression Bands [UAlgo]The Composite Z-Score with Linear Regression Bands is a technical indicator designed to provide traders with a comprehensive analysis of price momentum, volatility, and volume. By combining multiple moving averages with slope analysis, volume/volatility compression-expansion metrics, and Z-Score calculations, this indicator aims to highlight potential breakout and breakdown points with high accuracy. The inclusion of linear regression bands further enhances the analysis by providing dynamic support and resistance levels, which adapt to market conditions. This makes the indicator particularly useful in identifying overbought/oversold conditions, volume squeezes, and the overall direction of the trend.
🔶 Key Features
Multi-Length Slope Calculation: The indicator uses multiple Hull Moving Averages (HMA) across various lengths to calculate slope angles, which are then converted into Z-Scores. This helps in capturing both short-term and long-term price momentum.
Volume/Volatility Composite Analysis: By calculating a composite value derived from both volume and volatility, the indicator identifies periods of compression (squeezes) and expansion, which are crucial for detecting potential breakout opportunities.
Linear Regression Bands: The inclusion of dynamic linear regression bands provides traders with adaptive support and resistance levels. These bands are enhanced by the composite value, which adjusts the band width based on market conditions, offering a clearer view of possible price reversals.
Overbought/Oversold Detection: The indicator highlights overbought and oversold conditions by comparing Z-Scores against the upper and lower bounds of the regression bands, which can signal potential reversal points.
Customizable Inputs: Users can customize key parameters such as the lengths of the moving averages, the regression band period, and the number of deviations used for the bands, allowing for flexibility in adapting the indicator to different market environments.
🔶 Interpreting the Indicator
Z-Score Plots: The individual Z-Score plots represent the normalized slope of the Hull Moving Averages over different periods. Positive values indicate upward momentum, while negative values suggest downward momentum. The combined Z-Sum provides a broader view of the overall market momentum.
Composite Value: The composite value is a ratio of volume to volatility, which highlights periods of market compression and expansion. When the composite value rises, it suggests increasing market activity, often preceding a breakout.
Why are we calculating values for multiple lengths?
The Composite Z-Score with Linear Regression Bands indicator employs a multi-timeframe analysis by calculating Z-scores for various moving average lengths. This approach provides a more comprehensive view of market dynamics and helps to identify trends and potential reversals across different timeframes. By considering multiple lengths, we can:
Capture a broader range of market behaviors: Different moving average lengths capture different aspects of price movement. Shorter lengths are more sensitive to recent price changes, while longer lengths provide a smoother representation of the underlying trend.
Reduce the impact of noise: By combining Z-scores from multiple lengths, we can help to filter out some of the noise that can be present in shorter-term data and obtain a more robust signal.
Enhance the reliability of signals: When Z-scores from multiple lengths align, it can increase the confidence in the identified trend or potential reversal. This can help to reduce the likelihood of false signals.
In essence, calculating values for multiple lengths allows the indicator to provide a more nuanced and reliable assessment of market conditions, making it a valuable tool for traders and analysts.
Linear Regression Bands: The central line represents the linear regression of the Z-Sum, while the upper and lower bands represent the dynamic resistance and support levels, respectively. The deviation from the regression line indicates the strength of the current trend. When price moves beyond these bands, it may signal an overbought (above upper band) or oversold (below lower band) condition.
Volume/Volatility Squeeze: When the price moves between the regression bands and the volume/volatility-adjusted bands, the market is in a squeeze. Breakouts from this squeeze can lead to significant price moves, which are indicated by the filling of areas between the Z-Score plots and the bands.
Color Interpretation: The indicator uses color changes to make it easier to interpret the data. Teal colors generally indicate upward momentum or strong conditions, while red suggests downward momentum or weakening conditions. The intensity of the color reflects the strength of the signal.
Overbought/Oversold Signals: The indicator marks potential overbought and oversold conditions when Z-Scores cross above or below the upper and lower regression bands, respectively. These signals are crucial for identifying potential reversal points in the market.
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Uptrick: FVG Market Zones**Uptrick: FVG Market Zones**
---
### Introduction
**Uptrick: FVG Market Zones** is a cutting-edge technical analysis tool designed to identify and visualize Fair Value Gaps (FVGs) within financial markets. This indicator focuses on pinpointing critical price levels where significant gaps occur, which can act as potential support and resistance zones. By integrating advanced volatility analysis and user-configurable parameters, the **Uptrick: FVG Market Zones** provides traders with a robust framework for understanding market dynamics and making informed trading decisions.
### Purpose and Functionality
The primary purpose of the **Uptrick: FVG Market Zones** indicator is to detect and highlight Fair Value Gaps, which are areas on a price chart where there is a significant price movement without any trading activity in between. These gaps can provide critical insights into market behavior, as they often indicate areas where the market has not fully accounted for the supply and demand dynamics. Traders use these zones to anticipate potential reversals, breakouts, or consolidations, making this tool highly valuable for both short-term and long-term trading strategies.
### Unique Features and Originality
The **Uptrick: FVG Market Zones** indicator is distinguished by its focus on FVGs and its ability to integrate this concept into a broader market analysis framework. Unlike other indicators that may offer generalized support and resistance levels, this tool specifically identifies and visualizes gaps based on volatility-adjusted criteria. This precision allows traders to focus on the most relevant market zones, improving their ability to anticipate market movements.
One of the standout features of this indicator is its user-configurable settings, which provide a high degree of customization. This flexibility ensures that traders can tailor the indicator to suit their specific trading style and the particular market they are analyzing. Additionally, the indicator's visualization capabilities are enhanced with customizable colors and gap-filling options, making it easier for traders to interpret and act on the information presented.
### Inputs and Configurations
**Uptrick: FVG Market Zones** comes with several user inputs that allow traders to customize the indicator's behavior and appearance. Each input plays a crucial role in determining how the indicator identifies and visualizes FVGs on the chart. Here’s a detailed breakdown of each input:
1. **FVG Analysis Period (fvgPeriod):**
- **Description:** This input determines the period over which the indicator analyzes the chart for identifying FVGs. By adjusting this value, traders can control how far back in time the indicator looks to detect significant gaps.
- **Default Value:** 25
- **Purpose:** A shorter period may focus on more recent market activity, making the indicator more sensitive to recent price movements. In contrast, a longer period allows the indicator to identify gaps that have remained unfilled for an extended time, potentially acting as stronger support or resistance levels.
2. **Analysis Mode (mode):**
- **Description:** The Analysis Mode input allows traders to choose between different methods of analyzing the chart for FVGs.
- **Options:** "Recent Gaps" and "Extended View"
- **Default Option:** "Recent Gaps"
- **Purpose:**
- **Recent Gaps:** Focuses on the latest significant gaps, providing traders with up-to-date information on the most relevant market zones.
- **Extended View:** Considers a broader range of gap patterns, which can be useful in markets where historical gaps may still influence current price action.
3. **Volatility Sensitivity (volatilityFactor):**
- **Description:** This input adjusts the sensitivity of the indicator to market volatility. It is used in calculating the threshold for identifying FVGs.
- **Default Value:** 0.3
- **Step Size:** 0.1
- **Purpose:** A higher sensitivity will cause the indicator to detect smaller gaps, which might be more frequent but less significant. Lower sensitivity focuses on larger, more impactful gaps, which are less frequent but potentially more powerful in predicting market behavior.
4. **Highlight Market Gaps (showGaps):**
- **Description:** A boolean input that determines whether the identified FVGs should be highlighted on the chart.
- **Default Value:** True
- **Purpose:** This input allows traders to toggle the visualization of FVGs. When enabled, the indicator highlights gaps using colored boxes, making them visually prominent on the chart.
5. **Bullish Highlight Color (bullColor):**
- **Description:** Sets the color used to highlight bullish FVGs (gaps that may indicate support).
- **Default Value:** #00FF7F (a shade of green)
- **Purpose:** The color choice is crucial for quickly distinguishing bullish zones from bearish ones. Green is typically associated with upward price movement, making it intuitive for traders to identify potential support areas.
6. **Bearish Highlight Color (bearColor):**
- **Description:** Sets the color used to highlight bearish FVGs (gaps that may indicate resistance).
- **Default Value:** #FF4500 (a shade of red)
- **Purpose:** Red is commonly associated with downward price movement, making it easy for traders to identify potential resistance areas. This color coding helps in quickly assessing the chart.
7. **Fill Gap Areas (fillGaps):**
- **Description:** A boolean input that determines whether the FVGs should be filled with a color on the chart.
- **Default Value:** True
- **Purpose:** Filling the gap areas provides a more solid visual cue for traders. It enhances the visibility of the gaps, making it easier to spot these zones during fast-paced trading sessions.
8. **Hidden Color (hidden):**
- **Description:** A color input that is used when certain elements should be hidden from the chart.
- **Default Value:** color.rgb(0,0,0,100) (a semi-transparent black)
- **Purpose:** This input is useful for controlling the visibility of certain plots or elements on the chart, ensuring that the indicator remains clean and uncluttered.
### Market Gap Detection
The core functionality of the **Uptrick: FVG Market Zones** indicator lies in its ability to detect Fair Value Gaps. These gaps occur when the price makes a significant jump from one level to another without any trading activity in between. The indicator uses a combination of price action analysis and volatility thresholds to identify these gaps.
- **Volatility Measurement:** The indicator begins by measuring market volatility using the Average True Range (ATR). This volatility measurement is then adjusted by the user-defined sensitivity factor, which determines the threshold for identifying significant gaps.
- **Gap Identification:** The indicator checks for instances where the current low is higher than the high two bars ago (bullish gap) or where the current high is lower than the low two bars ago (bearish gap). These conditions signify a potential FVG.
- **Gap Storage and Management:** Once a gap is identified, it is stored in an array. The indicator also manages the size of these arrays based on the selected analysis mode, ensuring that only the most relevant gaps are considered in the analysis.
### Visualization
Visualization is a key component of the **Uptrick: FVG Market Zones** indicator. By providing clear and customizable visual cues, the indicator ensures that traders can quickly and easily interpret the information it provides.
- **Gap Highlighting:** When enabled, the indicator highlights the identified FVGs on the chart using colored boxes. Bullish gaps are highlighted in green, while bearish gaps are highlighted in red. This color coding helps traders instantly recognize potential support and resistance zones.
- **Gap Filling:** The indicator can also fill the identified gaps with a semi-transparent color. This option enhances the visibility of the gaps, making them more prominent on the chart. Filled gaps are particularly useful for traders who want to keep track of these zones over multiple trading sessions.
- **Gap Averages:** The indicator calculates the average level of the identified gaps and plots these averages as lines on the chart. These lines represent the general area of support or resistance based on the detected gaps, providing traders with a reference point for setting their stop losses or profit targets.
- **Text Labels:** The indicator also labels each FVG with the text "FVG" inside the highlighted area. This feature ensures that traders can easily identify these zones even in charts with dense price action.
### Practical Applications
The **Uptrick: FVG Market Zones** indicator is versatile and can be applied to a wide range of trading strategies across different markets and timeframes. Here are a few examples of how this indicator can be used in practice:
1. **Support and Resistance Trading:**
- Traders can use the identified FVGs as dynamic support and resistance levels. By placing their trades based on these levels, they can take advantage of potential reversals or continuations at key market zones.
2. **Gap Filling Strategy:**
- Some traders focus on the concept of gap filling, where the market eventually returns to "fill" the gap created by rapid price movements. The **Uptrick: FVG Market Zones** indicator can
help identify such gaps and anticipate when the market might return to these levels.
3. **Breakout Trading:**
- The indicator can be used to identify breakouts from significant gaps. When the price moves beyond the identified FVGs, it may signal a strong trend continuation, providing an opportunity for breakout traders.
4. **Reversal Trading:**
- By monitoring the signals generated by the indicator, traders can identify potential market reversals. A sell signal after a prolonged uptrend or a buy signal after a downtrend may indicate a reversal, allowing traders to position themselves accordingly.
5. **Risk Management:**
- The average levels of the FVGs can be used to set stop-loss and take-profit levels. By aligning these levels with the FVG zones, traders can improve their risk management practices and enhance their trading discipline.
### Customization and Flexibility
One of the standout features of the **Uptrick: FVG Market Zones** indicator is its high level of customization. Traders can adjust various parameters to tailor the indicator to their specific needs and preferences.
- **Customizable Colors:** The indicator allows traders to choose their preferred colors for highlighting bullish and bearish gaps. This flexibility ensures that the indicator can be integrated seamlessly into any trading setup, regardless of the trader's color scheme preferences.
- **Adjustable Periods and Sensitivity:** By allowing traders to adjust the analysis period and volatility sensitivity, the indicator can be fine-tuned to suit different market conditions. For example, a trader might use a shorter analysis period and higher sensitivity in a volatile market, while opting for a longer period and lower sensitivity in a more stable market.
- **Toggling Visual Elements:** Traders can choose to enable or disable various visual elements of the indicator, such as gap highlighting, gap filling, and text labels. This level of control allows traders to declutter their charts and focus on the information that is most relevant to their trading strategy.
### Advantages and Benefits
The **Uptrick: FVG Market Zones** indicator offers several key advantages that make it a valuable tool for traders:
1. **Precision:** By focusing on Fair Value Gaps, the indicator provides highly precise levels of support and resistance, which are often more reliable than traditional horizontal levels.
2. **Clarity:** The clear visual representation of FVGs, along with the text labels and color coding, ensures that traders can quickly interpret the indicator's signals and incorporate them into their trading decisions.
3. **Adaptability:** The indicator's customizable settings allow it to be adapted to different markets, timeframes, and trading styles. Whether you are a day trader, swing trader, or long-term investor, this indicator can be tailored to meet your needs.
4. **Enhanced Decision-Making:** The trading signals generated by the indicator provide actionable insights that can help traders make more informed decisions. By aligning their trades with the identified FVG zones, traders can improve their chances of success.
5. **Risk Management:** The use of FVG zones as reference points for stop-loss and take-profit levels enhances risk management practices, helping traders protect their capital while maximizing their profit potential.
### Conclusion
The **Uptrick: FVG Market Zones** indicator is a powerful and versatile tool for traders seeking to enhance their market analysis and improve their trading outcomes. By focusing on Fair Value Gaps and providing a high level of customization, this indicator offers a unique blend of precision, clarity, and adaptability. Whether you are looking to identify key market zones, generate trading signals, or improve your risk management practices, the **Uptrick: FVG Market Zones** indicator is a valuable addition to any trader's toolkit.
With its innovative approach to market analysis and user-friendly design, **Uptrick: FVG Market Zones** stands out as an essential tool for traders who want to stay ahead of the market and make more informed trading decisions. Whether you are trading stocks, forex, commodities, or cryptocurrencies, this indicator provides the insights you need to navigate the markets with confidence and success.
Prometheus Cauchy ProbabilityThe Cauchy probability distribution is a distribution that is better suited to be used on non normal data, such as stock returns. Markets characterized by volatility and fat-tails can be better modeled like this.
This script provides two values to a user. The blue line represents the probability for the underlying to rise. The purple line represents its probability to fall. Rise and fall by how much? By default a prediction of 0.5% is set, but users can adjust it. The script automatically calculates based on how many bars would be in an entire day. For example there are 390 minutes from 9:30am to 4:00pm est. time so the script uses 390 bars. Users have the option to set a custom bars back length.
Developer’s note. This script works best with extended market hours on. Every example shown will have it on. The more price and volatility the better!
Code breakdown:
cauchy_cdf(x, x0, gamma)=>
1 / math.pi * math.atan((x - x0) / gamma) + 0.5
This function is what calculates the Cauchy cumulative density function.
// Calculate x and gamma
x = close * (1 + pred)
x0 = hi
gamma := ta.stdev(close, Len, false)
y = cauchy_cdf(x, x0, gamma)
//down
x_lo = close * (1 - pred)
x0_lo = lo
y_lo = cauchy_cdf(x_lo, x0_lo, gamma)
x represents the target price. x0 represents the current highest price of the day. Gamma is the standard deviation of prices over the desired length. x_lo, x0_lo, are variables to determine the probability of falling. Inputting these values into the function we get back our chance of rising and falling. Our blue and purple line.
Trade Examples:
Step 1: After a move down there is some choppiness, the values are close to each other and moving sharply.
Step 2: The chance to rise (Blue Line) strongly moves above the chance to fall (Purple Line), uptrend ensues.
Step 3: Small breaks below the purple line show breaks in the overall trend.
Step 4: Strong move down in price, and up in purple line end up trend.
Step 1: Strong cross in purple and blue line, marking the start of a downtrend.
Step 2: Small breaks above the purple line show breaks in the overall trend.
Step 3: Strong move up in price, and up in the blue line end downtrend.
Day trading example:
Custom input:
Step 1: Pre market weakness ends with a move up in the blue line and price.
Step 2: Consolidation in the uptrend with a small downtrend and above the purple line.
Step 3: Strong move up in price, and up in the blue line end consolidation and resumes strong uptrend.
This example is with custom input: 100 bars back, and 1% prediction.
Step 1: Downtrend starts after a big move up.
Step 2: Big crossover in blue and purple line. Uptrend starts.
Step 3: Lines get close signaling choppiness.
Step 4: Purple crosses over blue ending uptrend.
No indicator is 100% accurate, we encourage traders to use them along with their own discretion. Please use these tools with your own decision making. Comments about desired features and updates are encouraged!
Historical Swing High-Low Gann IndicatorThe Historical Swing High-Low Gann Indicator is a powerful tool designed to track and visualize key market swing points over time. This indicator identifies significant swing highs and lows within a specified time frame and draws connecting lines between these points, allowing traders to observe the natural ebb and flow of the market.
What sets this indicator apart is its ability to maintain all previously drawn swing lines, creating a comprehensive historical view of market movements. Additionally, the indicator projects Gann-style lines from the most recent swing highs and lows, providing traders with potential future support and resistance levels based on the geometric progression of price action.
Features:
Swing Detection: Automatically detects significant swing highs and lows over a user-defined period (default is 3 hours).
Persistent Historical Lines: Keeps all previously drawn lines, offering a complete visual history of the market's swing points.
Gann-Style Projections: Draws forward-looking lines from the latest swing points to help predict possible future market levels.
Customizable Parameters: Allows users to adjust the swing detection period to suit different trading styles and time frames.
This indicator is ideal for traders who rely on price action, support and resistance levels, and Gann theory for their analysis. Whether used in isolation or as part of a broader strategy, the Historical Swing High-Low Gann Indicator provides valuable insights into the market's behavior over time.
Ultimate Bands [BigBeluga]Ultimate Bands
The Ultimate Bands indicator is an advanced technical analysis tool that combines elements of volatility bands, oscillators, and trend analysis. It provides traders with a comprehensive view of market conditions, including trend direction, momentum, and potential reversal points.
🔵 KEY FEATURES
● Ultimate Bands
Consists of an upper band, lower band, and a smooth middle line
Based on John Ehler's SuperSmoother algorithm for reduced lag
Bands are calculated using Root Mean Square Deviation (RMSD) for adaptive volatility measurement
Helps identify potential support and resistance levels
● Ultimate Oscillator
Derived from the price position relative to the Ultimate Bands
Oscillates between overbought and oversold levels
Provides insights into potential reversals and trend strength
● Trend Signal Line
Based on a Hull Moving Average (HMA) of the Ultimate Oscillator
Helps identify the overall trend direction
Color-coded for easy trend interpretation
● Heatmap Visualization
Displays the current state of the oscillator and trend signal
Provides an intuitive visual representation of market conditions
Shows overbought/oversold status and trend direction at a glance
● Breakout Signals
Optional feature to detect and display breakouts beyond the Ultimate Bands
Helps identify potential trend reversals or continuations
Visualized with arrows on the chart and color-coded candles
🔵 HOW TO USE
● Trend Identification
Use the color and position of the Trend Signal Line to determine the overall market trend
Refer to the heatmap for a quick visual confirmation of trend direction
● Entry Signals
Look for price touches or breaks of the Ultimate Bands for potential entry points
Use oscillator extremes in conjunction with band touches for stronger signals
Consider breakout signals (if enabled) for trend-following entries
● Exit Signals
Use opposite band touches or breakouts as potential exit points
Monitor the oscillator for divergences or extreme readings as exit signals
● Overbought/Oversold Analysis
Use the Ultimate Oscillator and heatmap to identify overbought/oversold conditions
Look for potential reversals when the oscillator reaches extreme levels
● Confirmation
Combine Ultimate Bands, Oscillator, and Trend Signal for stronger trade confirmation
Use the heatmap for quick visual confirmation of market conditions
🔵 CUSTOMIZATION
The Ultimate Bands indicator offers several customization options:
Adjust the main calculation length for bands and oscillator
Modify the number of standard deviations for band calculation
Change the signal line length for trend analysis
Toggle the display of breakout signals and candle coloring
By fine-tuning these settings, traders can adapt the Ultimate Bands indicator to various market conditions and personal trading strategies.
The Ultimate Bands indicator provides a multi-faceted approach to market analysis, combining volatility-based bands, oscillator analysis, and trend identification in one comprehensive tool. Its adaptive nature and visual cues make it suitable for both novice and experienced traders across various timeframes and markets. The integration of multiple analytical elements offers traders a rich set of data points to inform their trading decisions.
Prometheus IQR bandsThis indicator is a tool that uses market data to plot bands along with a price chart.
This tool uses interquartile range (IQR) instead of Standard Deviation (STD) because market returns are not normally distributed. There is also no way to tell if the pocket of the market you are looking at is normally distributed. So using methods that work better with non-normal data minimizes risk more than using a different process.
Calculation
Code for helper functions:
// Function to calculate the percentile value
percentile(arr, p) =>
index = math.floor(p * (array.size(arr) - 1) + 0.5)
array.get(arr, index)
manual_iqr(data, lower_percentile, upper_percentile)=>
// Sort the data
data_arr = array.new()
for i = 0 to lkb_
data_arr.push(close )
array.sort(data_arr)
sorted_data = data_arr.copy()
n = array.size(data_arr)
// Calculate the specified percentiles
Q1 = percentile(sorted_data, lower_percentile)
Q3 = percentile(sorted_data, upper_percentile)
// Calculate IQR
IQR = Q3 - Q1
// Return the IQR
IQR
IQRB(lkb_, sens)=>
sens_l = sens/100
sens_h = (100-sens)/100
val = manual_iqr(close, sens_l, sens_h)
sma = ta.sma(close, int(lkb_))
upper = sma + val
lower = sma - val
Percentile Calculation (percentile function):
Calculates the percentile value of an array (arr) at a given percentile (p).
Uses linear interpolation to find the exact percentile value in a sorted array.
Manual IQR Calculation (manual_iqr function):
Converts the input data into an array (data_arr) and sorts it.
Computes the lower and upper quartiles (Q1 and Q3) using the specified percentiles (lower_percentile and upper_percentile).
Computes the Interquartile Range (IQR) as IQR = Q3 - Q1.
Returns the computed IQR.
IQRB Function Calculation (IQRB function):
Converts the sensitivity percentage (sens) into decimal values (sens_l for lower percentile and sens_h for upper percentile).
Calls manual_iqr with the closing prices (close) and the lower and upper percentiles.
Calculates the Simple Moving Average (SMA) of the closing prices (close) over a specified period (lkb_).
Computes the upper and lower bands of the IQR using the SMA and the calculated IQR (val).
Returns an array containing the upper band, lower band, and SMA values.
After the IQR is calculated at the specified sensitivity it is added to and subtracted from a SMA of the specified period.
This provides us with bands of the IQR sensitivity we want.
Trade Examples
Step 1: Price quickly and strongly breaks below the bottom band and continues there for some bars.
Step 2: Price re-enters the bottom band and has a strong reversal.
Step 1: Price strongly breaks above the top band and continues higher.
Step 2: Price breaks below the top band and reverses to the downside.
Step 3: Price breaks below the bottom band after our previous reversal.
Step 4: Price regains that bottom band and reverses to the upside.
Step 5: Price continues moving higher and does not break above the top band or reverse.
Step 1: Price strongly breaks above the top band and continues higher.
Step 2: Price breaks below the top band and reverses to the downside.
Step 3: Price breaks below the bottom band after our previous reversal.
Step 4: Price regains that bottom band and reverses to the upside.
Step 5: Price strongly breaks above the top band after the previous reversal.
Step 6: Price breaks below the top band and reverses down.
Step 7: Price strongly breaks above the top band and continues moving higher.
Step 8: Price breaks below the top band and reverses down.
Step 9: Price strongly breaks above the top band and continues moving higher.
Step 10: Price breaks below the top band and reverses down.
Step 1: Price breaks above the top band.
Step 2: Price drops below the top band and chops slightly, without a large reversal from that break.
Step 3: Price breaks below the bottom band.
Step 4: Price re-enters the bottom band and just chops, no large reversal.
Step 5: Price breaks below the bottom band.
Step 6: Price retakes the bottom band and strongly reverses.
This tool can be uses to spot reversals and see when trends may continue as the stay inside the bands. No indicator is 100% accurate, we encourage traders to not follow them blindly and use them as tools.
