ATAI Volume analysis with price action V 1.00ATAI Volume Analysis with Price Action
1. Introduction
1.1 Overview
ATAI Volume Analysis with Price Action is a composite indicator designed for TradingView. It combines per‑side volume data —that is, how much buying and selling occurs during each bar—with standard price‑structure elements such as swings, trend lines and support/resistance. By blending these elements the script aims to help a trader understand which side is in control, whether a breakout is genuine, when markets are potentially exhausted and where liquidity providers might be active.
The indicator is built around TradingView’s up/down volume feed accessed via the TradingView/ta/10 library. The following excerpt from the script illustrates how this feed is configured:
import TradingView/ta/10 as tvta
// Determine lower timeframe string based on user choice and chart resolution
string lower_tf_breakout = use_custom_tf_input ? custom_tf_input :
timeframe.isseconds ? "1S" :
timeframe.isintraday ? "1" :
timeframe.isdaily ? "5" : "60"
// Request up/down volume (both positive)
= tvta.requestUpAndDownVolume(lower_tf_breakout)
Lower‑timeframe selection. If you do not specify a custom lower timeframe, the script chooses a default based on your chart resolution: 1 second for second charts, 1 minute for intraday charts, 5 minutes for daily charts and 60 minutes for anything longer. Smaller intervals provide a more precise view of buyer and seller flow but cover fewer bars. Larger intervals cover more history at the cost of granularity.
Tick vs. time bars. Many trading platforms offer a tick / intrabar calculation mode that updates an indicator on every trade rather than only on bar close. Turning on one‑tick calculation will give the most accurate split between buy and sell volume on the current bar, but it typically reduces the amount of historical data available. For the highest fidelity in live trading you can enable this mode; for studying longer histories you might prefer to disable it. When volume data is completely unavailable (some instruments and crypto pairs), all modules that rely on it will remain silent and only the price‑structure backbone will operate.
Figure caption, Each panel shows the indicator’s info table for a different volume sampling interval. In the left chart, the parentheses “(5)” beside the buy‑volume figure denote that the script is aggregating volume over five‑minute bars; the center chart uses “(1)” for one‑minute bars; and the right chart uses “(1T)” for a one‑tick interval. These notations tell you which lower timeframe is driving the volume calculations. Shorter intervals such as 1 minute or 1 tick provide finer detail on buyer and seller flow, but they cover fewer bars; longer intervals like five‑minute bars smooth the data and give more history.
Figure caption, The values in parentheses inside the info table come directly from the Breakout — Settings. The first row shows the custom lower-timeframe used for volume calculations (e.g., “(1)”, “(5)”, or “(1T)”)
2. Price‑Structure Backbone
Even without volume, the indicator draws structural features that underpin all other modules. These features are always on and serve as the reference levels for subsequent calculations.
2.1 What it draws
• Pivots: Swing highs and lows are detected using the pivot_left_input and pivot_right_input settings. A pivot high is identified when the high recorded pivot_right_input bars ago exceeds the highs of the preceding pivot_left_input bars and is also higher than (or equal to) the highs of the subsequent pivot_right_input bars; pivot lows follow the inverse logic. The indicator retains only a fixed number of such pivot points per side, as defined by point_count_input, discarding the oldest ones when the limit is exceeded.
• Trend lines: For each side, the indicator connects the earliest stored pivot and the most recent pivot (oldest high to newest high, and oldest low to newest low). When a new pivot is added or an old one drops out of the lookback window, the line’s endpoints—and therefore its slope—are recalculated accordingly.
• Horizontal support/resistance: The highest high and lowest low within the lookback window defined by length_input are plotted as horizontal dashed lines. These serve as short‑term support and resistance levels.
• Ranked labels: If showPivotLabels is enabled the indicator prints labels such as “HH1”, “HH2”, “LL1” and “LL2” near each pivot. The ranking is determined by comparing the price of each stored pivot: HH1 is the highest high, HH2 is the second highest, and so on; LL1 is the lowest low, LL2 is the second lowest. In the case of equal prices the newer pivot gets the better rank. Labels are offset from price using ½ × ATR × label_atr_multiplier, with the ATR length defined by label_atr_len_input. A dotted connector links each label to the candle’s wick.
2.2 Key settings
• length_input: Window length for finding the highest and lowest values and for determining trend line endpoints. A larger value considers more history and will generate longer trend lines and S/R levels.
• pivot_left_input, pivot_right_input: Strictness of swing confirmation. Higher values require more bars on either side to form a pivot; lower values create more pivots but may include minor swings.
• point_count_input: How many pivots are kept in memory on each side. When new pivots exceed this number the oldest ones are discarded.
• label_atr_len_input and label_atr_multiplier: Determine how far pivot labels are offset from the bar using ATR. Increasing the multiplier moves labels further away from price.
• Styling inputs for trend lines, horizontal lines and labels (color, width and line style).
Figure caption, The chart illustrates how the indicator’s price‑structure backbone operates. In this daily example, the script scans for bars where the high (or low) pivot_right_input bars back is higher (or lower) than the preceding pivot_left_input bars and higher or lower than the subsequent pivot_right_input bars; only those bars are marked as pivots.
These pivot points are stored and ranked: the highest high is labelled “HH1”, the second‑highest “HH2”, and so on, while lows are marked “LL1”, “LL2”, etc. Each label is offset from the price by half of an ATR‑based distance to keep the chart clear, and a dotted connector links the label to the actual candle.
The red diagonal line connects the earliest and latest stored high pivots, and the green line does the same for low pivots; when a new pivot is added or an old one drops out of the lookback window, the end‑points and slopes adjust accordingly. Dashed horizontal lines mark the highest high and lowest low within the current lookback window, providing visual support and resistance levels. Together, these elements form the structural backbone that other modules reference, even when volume data is unavailable.
3. Breakout Module
3.1 Concept
This module confirms that a price break beyond a recent high or low is supported by a genuine shift in buying or selling pressure. It requires price to clear the highest high (“HH1”) or lowest low (“LL1”) and, simultaneously, that the winning side shows a significant volume spike, dominance and ranking. Only when all volume and price conditions pass is a breakout labelled.
3.2 Inputs
• lookback_break_input : This controls the number of bars used to compute moving averages and percentiles for volume. A larger value smooths the averages and percentiles but makes the indicator respond more slowly.
• vol_mult_input : The “spike” multiplier; the current buy or sell volume must be at least this multiple of its moving average over the lookback window to qualify as a breakout.
• rank_threshold_input (0–100) : Defines a volume percentile cutoff: the current buyer/seller volume must be in the top (100−threshold)%(100−threshold)% of all volumes within the lookback window. For example, if set to 80, the current volume must be in the top 20 % of the lookback distribution.
• ratio_threshold_input (0–1) : Specifies the minimum share of total volume that the buyer (for a bullish breakout) or seller (for bearish) must hold on the current bar; the code also requires that the cumulative buyer volume over the lookback window exceeds the seller volume (and vice versa for bearish cases).
• use_custom_tf_input / custom_tf_input : When enabled, these inputs override the automatic choice of lower timeframe for up/down volume; otherwise the script selects a sensible default based on the chart’s timeframe.
• Label appearance settings : Separate options control the ATR-based offset length, offset multiplier, label size and colors for bullish and bearish breakout labels, as well as the connector style and width.
3.3 Detection logic
1. Data preparation : Retrieve per‑side volume from the lower timeframe and take absolute values. Build rolling arrays of the last lookback_break_input values to compute simple moving averages (SMAs), cumulative sums and percentile ranks for buy and sell volume.
2. Volume spike: A spike is flagged when the current buy (or, in the bearish case, sell) volume is at least vol_mult_input times its SMA over the lookback window.
3. Dominance test: The buyer’s (or seller’s) share of total volume on the current bar must meet or exceed ratio_threshold_input. In addition, the cumulative sum of buyer volume over the window must exceed the cumulative sum of seller volume for a bullish breakout (and vice versa for bearish). A separate requirement checks the sign of delta: for bullish breakouts delta_breakout must be non‑negative; for bearish breakouts it must be non‑positive.
4. Percentile rank: The current volume must fall within the top (100 – rank_threshold_input) percent of the lookback distribution—ensuring that the spike is unusually large relative to recent history.
5. Price test: For a bullish signal, the closing price must close above the highest pivot (HH1); for a bearish signal, the close must be below the lowest pivot (LL1).
6. Labeling: When all conditions above are satisfied, the indicator prints “Breakout ↑” above the bar (bullish) or “Breakout ↓” below the bar (bearish). Labels are offset using half of an ATR‑based distance and linked to the candle with a dotted connector.
Figure caption, (Breakout ↑ example) , On this daily chart, price pushes above the red trendline and the highest prior pivot (HH1). The indicator recognizes this as a valid breakout because the buyer‑side volume on the lower timeframe spikes above its recent moving average and buyers dominate the volume statistics over the lookback period; when combined with a close above HH1, this satisfies the breakout conditions. The “Breakout ↑” label appears above the candle, and the info table highlights that up‑volume is elevated relative to its 11‑bar average, buyer share exceeds the dominance threshold and money‑flow metrics support the move.
Figure caption, In this daily example, price breaks below the lowest pivot (LL1) and the lower green trendline. The indicator identifies this as a bearish breakout because sell‑side volume is sharply elevated—about twice its 11‑bar average—and sellers dominate both the bar and the lookback window. With the close falling below LL1, the script triggers a Breakout ↓ label and marks the corresponding row in the info table, which shows strong down volume, negative delta and a seller share comfortably above the dominance threshold.
4. Market Phase Module (Volume Only)
4.1 Concept
Not all markets trend; many cycle between periods of accumulation (buying pressure building up), distribution (selling pressure dominating) and neutral behavior. This module classifies the current bar into one of these phases without using ATR , relying solely on buyer and seller volume statistics. It looks at net flows, ratio changes and an OBV‑like cumulative line with dual‑reference (1‑ and 2‑bar) trends. The result is displayed both as on‑chart labels and in a dedicated row of the info table.
4.2 Inputs
• phase_period_len: Number of bars over which to compute sums and ratios for phase detection.
• phase_ratio_thresh : Minimum buyer share (for accumulation) or minimum seller share (for distribution, derived as 1 − phase_ratio_thresh) of the total volume.
• strict_mode: When enabled, both the 1‑bar and 2‑bar changes in each statistic must agree on the direction (strict confirmation); when disabled, only one of the two references needs to agree (looser confirmation).
• Color customisation for info table cells and label styling for accumulation and distribution phases, including ATR length, multiplier, label size, colors and connector styles.
• show_phase_module: Toggles the entire phase detection subsystem.
• show_phase_labels: Controls whether on‑chart labels are drawn when accumulation or distribution is detected.
4.3 Detection logic
The module computes three families of statistics over the volume window defined by phase_period_len:
1. Net sum (buyers minus sellers): net_sum_phase = Σ(buy) − Σ(sell). A positive value indicates a predominance of buyers. The code also computes the differences between the current value and the values 1 and 2 bars ago (d_net_1, d_net_2) to derive up/down trends.
2. Buyer ratio: The instantaneous ratio TF_buy_breakout / TF_tot_breakout and the window ratio Σ(buy) / Σ(total). The current ratio must exceed phase_ratio_thresh for accumulation or fall below 1 − phase_ratio_thresh for distribution. The first and second differences of the window ratio (d_ratio_1, d_ratio_2) determine trend direction.
3. OBV‑like cumulative net flow: An on‑balance volume analogue obv_net_phase increments by TF_buy_breakout − TF_sell_breakout each bar. Its differences over the last 1 and 2 bars (d_obv_1, d_obv_2) provide trend clues.
The algorithm then combines these signals:
• For strict mode , accumulation requires: (a) current ratio ≥ threshold, (b) cumulative ratio ≥ threshold, (c) both ratio differences ≥ 0, (d) net sum differences ≥ 0, and (e) OBV differences ≥ 0. Distribution is the mirror case.
• For loose mode , it relaxes the directional tests: either the 1‑ or the 2‑bar difference needs to agree in each category.
If all conditions for accumulation are satisfied, the phase is labelled “Accumulation” ; if all conditions for distribution are satisfied, it’s labelled “Distribution” ; otherwise the phase is “Neutral” .
4.4 Outputs
• Info table row : Row 8 displays “Market Phase (Vol)” on the left and the detected phase (Accumulation, Distribution or Neutral) on the right. The text colour of both cells matches a user‑selectable palette (typically green for accumulation, red for distribution and grey for neutral).
• On‑chart labels : When show_phase_labels is enabled and a phase persists for at least one bar, the module prints a label above the bar ( “Accum” ) or below the bar ( “Dist” ) with a dashed or dotted connector. The label is offset using ATR based on phase_label_atr_len_input and phase_label_multiplier and is styled according to user preferences.
Figure caption, The chart displays a red “Dist” label above a particular bar, indicating that the accumulation/distribution module identified a distribution phase at that point. The detection is based on seller dominance: during that bar, the net buyer-minus-seller flow and the OBV‑style cumulative flow were trending down, and the buyer ratio had dropped below the preset threshold. These conditions satisfy the distribution criteria in strict mode. The label is placed above the bar using an ATR‑based offset and a dashed connector. By the time of the current bar in the screenshot, the phase indicator shows “Neutral” in the info table—signaling that neither accumulation nor distribution conditions are currently met—yet the historical “Dist” label remains to mark where the prior distribution phase began.
Figure caption, In this example the market phase module has signaled an Accumulation phase. Three bars before the current candle, the algorithm detected a shift toward buyers: up‑volume exceeded its moving average, down‑volume was below average, and the buyer share of total volume climbed above the threshold while the on‑balance net flow and cumulative ratios were trending upwards. The blue “Accum” label anchored below that bar marks the start of the phase; it remains on the chart because successive bars continue to satisfy the accumulation conditions. The info table confirms this: the “Market Phase (Vol)” row still reads Accumulation, and the ratio and sum rows show buyers dominating both on the current bar and across the lookback window.
5. OB/OS Spike Module
5.1 What overbought/oversold means here
In many markets, a rapid extension up or down is often followed by a period of consolidation or reversal. The indicator interprets overbought (OB) conditions as abnormally strong selling risk at or after a price rally and oversold (OS) conditions as unusually strong buying risk after a decline. Importantly, these are not direct trade signals; rather they flag areas where caution or contrarian setups may be appropriate.
5.2 Inputs
• minHits_obos (1–7): Minimum number of oscillators that must agree on an overbought or oversold condition for a label to print.
• syncWin_obos: Length of a small sliding window over which oscillator votes are smoothed by taking the maximum count observed. This helps filter out choppy signals.
• Volume spike criteria: kVolRatio_obos (ratio of current volume to its SMA) and zVolThr_obos (Z‑score threshold) across volLen_obos. Either threshold can trigger a spike.
• Oscillator toggles and periods: Each of RSI, Stochastic (K and D), Williams %R, CCI, MFI, DeMarker and Stochastic RSI can be independently enabled; their periods are adjustable.
• Label appearance: ATR‑based offset, size, colors for OB and OS labels, plus connector style and width.
5.3 Detection logic
1. Directional volume spikes: Volume spikes are computed separately for buyer and seller volumes. A sell volume spike (sellVolSpike) flags a potential OverBought bar, while a buy volume spike (buyVolSpike) flags a potential OverSold bar. A spike occurs when the respective volume exceeds kVolRatio_obos times its simple moving average over the window or when its Z‑score exceeds zVolThr_obos.
2. Oscillator votes: For each enabled oscillator, calculate its overbought and oversold state using standard thresholds (e.g., RSI ≥ 70 for OB and ≤ 30 for OS; Stochastic %K/%D ≥ 80 for OB and ≤ 20 for OS; etc.). Count how many oscillators vote for OB and how many vote for OS.
3. Minimum hits: Apply the smoothing window syncWin_obos to the vote counts using a maximum‑of‑last‑N approach. A candidate bar is only considered if the smoothed OB hit count ≥ minHits_obos (for OverBought) or the smoothed OS hit count ≥ minHits_obos (for OverSold).
4. Tie‑breaking: If both OverBought and OverSold spike conditions are present on the same bar, compare the smoothed hit counts: the side with the higher count is selected; ties default to OverBought.
5. Label printing: When conditions are met, the bar is labelled as “OverBought X/7” above the candle or “OverSold X/7” below it. “X” is the number of oscillators confirming, and the bracket lists the abbreviations of contributing oscillators. Labels are offset from price using half of an ATR‑scaled distance and can optionally include a dotted or dashed connector line.
Figure caption, In this chart the overbought/oversold module has flagged an OverSold signal. A sell‑off from the prior highs brought price down to the lower trend‑line, where the bar marked “OverSold 3/7 DeM” appears. This label indicates that on that bar the module detected a buy‑side volume spike and that at least three of the seven enabled oscillators—in this case including the DeMarker—were in oversold territory. The label is printed below the candle with a dotted connector, signaling that the market may be temporarily exhausted on the downside. After this oversold print, price begins to rebound towards the upper red trend‑line and higher pivot levels.
Figure caption, This example shows the overbought/oversold module in action. In the left‑hand panel you can see the OB/OS settings where each oscillator (RSI, Stochastic, Williams %R, CCI, MFI, DeMarker and Stochastic RSI) can be enabled or disabled, and the ATR length and label offset multiplier adjusted. On the chart itself, price has pushed up to the descending red trendline and triggered an “OverBought 3/7” label. That means the sell‑side volume spiked relative to its average and three out of the seven enabled oscillators were in overbought territory. The label is offset above the candle by half of an ATR and connected with a dashed line, signaling that upside momentum may be overextended and a pause or pullback could follow.
6. Buyer/Seller Trap Module
6.1 Concept
A bull trap occurs when price appears to break above resistance, attracting buyers, but fails to sustain the move and quickly reverses, leaving a long upper wick and trapping late entrants. A bear trap is the opposite: price breaks below support, lures in sellers, then snaps back, leaving a long lower wick and trapping shorts. This module detects such traps by looking for price structure sweeps, order‑flow mismatches and dominance reversals. It uses a scoring system to differentiate risk from confirmed traps.
6.2 Inputs
• trap_lookback_len: Window length used to rank extremes and detect sweeps.
• trap_wick_threshold: Minimum proportion of a bar’s range that must be wick (upper for bull traps, lower for bear traps) to qualify as a sweep.
• trap_score_risk: Minimum aggregated score required to flag a trap risk. (The code defines a trap_score_confirm input, but confirmation is actually based on price reversal rather than a separate score threshold.)
• trap_confirm_bars: Maximum number of bars allowed for price to reverse and confirm the trap. If price does not reverse in this window, the risk label will expire or remain unconfirmed.
• Label settings: ATR length and multiplier for offsetting, size, colours for risk and confirmed labels, and connector style and width. Separate settings exist for bull and bear traps.
• Toggle inputs: show_trap_module and show_trap_labels enable the module and control whether labels are drawn on the chart.
6.3 Scoring logic
The module assigns points to several conditions and sums them to determine whether a trap risk is present. For bull traps, the score is built from the following (bear traps mirror the logic with highs and lows swapped):
1. Sweep (2 points): Price trades above the high pivot (HH1) but fails to close above it and leaves a long upper wick at least trap_wick_threshold × range. For bear traps, price dips below the low pivot (LL1), fails to close below and leaves a long lower wick.
2. Close break (1 point): Price closes beyond HH1 or LL1 without leaving a long wick.
3. Candle/delta mismatch (2 points): The candle closes bullish yet the order flow delta is negative or the seller ratio exceeds 50%, indicating hidden supply. Conversely, a bearish close with positive delta or buyer dominance suggests hidden demand.
4. Dominance inversion (2 points): The current bar’s buyer volume has the highest rank in the lookback window while cumulative sums favor sellers, or vice versa.
5. Low‑volume break (1 point): Price crosses the pivot but total volume is below its moving average.
The total score for each side is compared to trap_score_risk. If the score is high enough, a “Bull Trap Risk” or “Bear Trap Risk” label is drawn, offset from the candle by half of an ATR‑scaled distance using a dashed outline. If, within trap_confirm_bars, price reverses beyond the opposite level—drops back below the high pivot for bull traps or rises above the low pivot for bear traps—the label is upgraded to a solid “Bull Trap” or “Bear Trap” . In this version of the code, there is no separate score threshold for confirmation: the variable trap_score_confirm is unused; confirmation depends solely on a successful price reversal within the specified number of bars.
Figure caption, In this example the trap module has flagged a Bear Trap Risk. Price initially breaks below the most recent low pivot (LL1), but the bar closes back above that level and leaves a long lower wick, suggesting a failed push lower. Combined with a mismatch between the candle direction and the order flow (buyers regain control) and a reversal in volume dominance, the aggregate score exceeds the risk threshold, so a dashed “Bear Trap Risk” label prints beneath the bar. The green and red trend lines mark the current low and high pivot trajectories, while the horizontal dashed lines show the highest and lowest values in the lookback window. If, within the next few bars, price closes decisively above the support, the risk label would upgrade to a solid “Bear Trap” label.
Figure caption, In this example the trap module has identified both ends of a price range. Near the highs, price briefly pushes above the descending red trendline and the recent pivot high, but fails to close there and leaves a noticeable upper wick. That combination of a sweep above resistance and order‑flow mismatch generates a Bull Trap Risk label with a dashed outline, warning that the upside break may not hold. At the opposite extreme, price later dips below the green trendline and the labelled low pivot, then quickly snaps back and closes higher. The long lower wick and subsequent price reversal upgrade the previous bear‑trap risk into a confirmed Bear Trap (solid label), indicating that sellers were caught on a false breakdown. Horizontal dashed lines mark the highest high and lowest low of the lookback window, while the red and green diagonals connect the earliest and latest pivot highs and lows to visualize the range.
7. Sharp Move Module
7.1 Concept
Markets sometimes display absorption or climax behavior—periods when one side steadily gains the upper hand before price breaks out with a sharp move. This module evaluates several order‑flow and volume conditions to anticipate such moves. Users can choose how many conditions must be met to flag a risk and how many (plus a price break) are required for confirmation.
7.2 Inputs
• sharp Lookback: Number of bars in the window used to compute moving averages, sums, percentile ranks and reference levels.
• sharpPercentile: Minimum percentile rank for the current side’s volume; the current buy (or sell) volume must be greater than or equal to this percentile of historical volumes over the lookback window.
• sharpVolMult: Multiplier used in the volume climax check. The current side’s volume must exceed this multiple of its average to count as a climax.
• sharpRatioThr: Minimum dominance ratio (current side’s volume relative to the opposite side) used in both the instant and cumulative dominance checks.
• sharpChurnThr: Maximum ratio of a bar’s range to its ATR for absorption/churn detection; lower values indicate more absorption (large volume in a small range).
• sharpScoreRisk: Minimum number of conditions that must be true to print a risk label.
• sharpScoreConfirm: Minimum number of conditions plus a price break required for confirmation.
• sharpCvdThr: Threshold for cumulative delta divergence versus price change (positive for bullish accumulation, negative for bearish distribution).
• Label settings: ATR length (sharpATRlen) and multiplier (sharpLabelMult) for positioning labels, label size, colors and connector styles for bullish and bearish sharp moves.
• Toggles: enableSharp activates the module; show_sharp_labels controls whether labels are drawn.
7.3 Conditions (six per side)
For each side, the indicator computes six boolean conditions and sums them to form a score:
1. Dominance (instant and cumulative):
– Instant dominance: current buy volume ≥ sharpRatioThr × current sell volume.
– Cumulative dominance: sum of buy volumes over the window ≥ sharpRatioThr × sum of sell volumes (and vice versa for bearish checks).
2. Accumulation/Distribution divergence: Over the lookback window, cumulative delta rises by at least sharpCvdThr while price fails to rise (bullish), or cumulative delta falls by at least sharpCvdThr while price fails to fall (bearish).
3. Volume climax: The current side’s volume is ≥ sharpVolMult × its average and the product of volume and bar range is the highest in the lookback window.
4. Absorption/Churn: The current side’s volume divided by the bar’s range equals the highest value in the window and the bar’s range divided by ATR ≤ sharpChurnThr (indicating large volume within a small range).
5. Percentile rank: The current side’s volume percentile rank is ≥ sharp Percentile.
6. Mirror logic for sellers: The above checks are repeated with buyer and seller roles swapped and the price break levels reversed.
Each condition that passes contributes one point to the corresponding side’s score (0 or 1). Risk and confirmation thresholds are then applied to these scores.
7.4 Scoring and labels
• Risk: If scoreBull ≥ sharpScoreRisk, a “Sharp ↑ Risk” label is drawn above the bar. If scoreBear ≥ sharpScoreRisk, a “Sharp ↓ Risk” label is drawn below the bar.
• Confirmation: A risk label is upgraded to “Sharp ↑” when scoreBull ≥ sharpScoreConfirm and the bar closes above the highest recent pivot (HH1); for bearish cases, confirmation requires scoreBear ≥ sharpScoreConfirm and a close below the lowest pivot (LL1).
• Label positioning: Labels are offset from the candle by ATR × sharpLabelMult (full ATR times multiplier), not half, and may include a dashed or dotted connector line if enabled.
Figure caption, In this chart both bullish and bearish sharp‑move setups have been flagged. Earlier in the range, a “Sharp ↓ Risk” label appears beneath a candle: the sell‑side score met the risk threshold, signaling that the combination of strong sell volume, dominance and absorption within a narrow range suggested a potential sharp decline. The price did not close below the lower pivot, so this label remains a “risk” and no confirmation occurred. Later, as the market recovered and volume shifted back to the buy side, a “Sharp ↑ Risk” label prints above a candle near the top of the channel. Here, buy‑side dominance, cumulative delta divergence and a volume climax aligned, but price has not yet closed above the upper pivot (HH1), so the alert is still a risk rather than a confirmed sharp‑up move.
Figure caption, In this chart a Sharp ↑ label is displayed above a candle, indicating that the sharp move module has confirmed a bullish breakout. Prior bars satisfied the risk threshold — showing buy‑side dominance, positive cumulative delta divergence, a volume climax and strong absorption in a narrow range — and this candle closes above the highest recent pivot, upgrading the earlier “Sharp ↑ Risk” alert to a full Sharp ↑ signal. The green label is offset from the candle with a dashed connector, while the red and green trend lines trace the high and low pivot trajectories and the dashed horizontals mark the highest and lowest values of the lookback window.
8. Market‑Maker / Spread‑Capture Module
8.1 Concept
Liquidity providers often “capture the spread” by buying and selling in almost equal amounts within a very narrow price range. These bars can signal temporary congestion before a move or reflect algorithmic activity. This module flags bars where both buyer and seller volumes are high, the price range is only a few ticks and the buy/sell split remains close to 50%. It helps traders spot potential liquidity pockets.
8.2 Inputs
• scalpLookback: Window length used to compute volume averages.
• scalpVolMult: Multiplier applied to each side’s average volume; both buy and sell volumes must exceed this multiple.
• scalpTickCount: Maximum allowed number of ticks in a bar’s range (calculated as (high − low) / minTick). A value of 1 or 2 captures ultra‑small bars; increasing it relaxes the range requirement.
• scalpDeltaRatio: Maximum deviation from a perfect 50/50 split. For example, 0.05 means the buyer share must be between 45% and 55%.
• Label settings: ATR length, multiplier, size, colors, connector style and width.
• Toggles : show_scalp_module and show_scalp_labels to enable the module and its labels.
8.3 Signal
When, on the current bar, both TF_buy_breakout and TF_sell_breakout exceed scalpVolMult times their respective averages and (high − low)/minTick ≤ scalpTickCount and the buyer share is within scalpDeltaRatio of 50%, the module prints a “Spread ↔” label above the bar. The label uses the same ATR offset logic as other modules and draws a connector if enabled.
Figure caption, In this chart the spread‑capture module has identified a potential liquidity pocket. Buyer and seller volumes both spiked above their recent averages, yet the candle’s range measured only a couple of ticks and the buy/sell split stayed close to 50 %. This combination met the module’s criteria, so it printed a grey “Spread ↔” label above the bar. The red and green trend lines link the earliest and latest high and low pivots, and the dashed horizontals mark the highest high and lowest low within the current lookback window.
9. Money Flow Module
9.1 Concept
To translate volume into a monetary measure, this module multiplies each side’s volume by the closing price. It tracks buying and selling system money default currency on a per-bar basis and sums them over a chosen period. The difference between buy and sell currencies (Δ$) shows net inflow or outflow.
9.2 Inputs
• mf_period_len_mf: Number of bars used for summing buy and sell dollars.
• Label appearance settings: ATR length, multiplier, size, colors for up/down labels, and connector style and width.
• Toggles: Use enableMoneyFlowLabel_mf and showMFLabels to control whether the module and its labels are displayed.
9.3 Calculations
• Per-bar money: Buy $ = TF_buy_breakout × close; Sell $ = TF_sell_breakout × close. Their difference is Δ$ = Buy $ − Sell $.
• Summations: Over mf_period_len_mf bars, compute Σ Buy $, Σ Sell $ and ΣΔ$ using math.sum().
• Info table entries: Rows 9–13 display these values as texts like “↑ USD 1234 (1M)” or “ΣΔ USD −5678 (14)”, with colors reflecting whether buyers or sellers dominate.
• Money flow status: If Δ$ is positive the bar is marked “Money flow in” ; if negative, “Money flow out” ; if zero, “Neutral”. The cumulative status is similarly derived from ΣΔ.Labels print at the bar that changes the sign of ΣΔ, offset using ATR × label multiplier and styled per user preferences.
Figure caption, The chart illustrates a steady rise toward the highest recent pivot (HH1) with price riding between a rising green trend‑line and a red trend‑line drawn through earlier pivot highs. A green Money flow in label appears above the bar near the top of the channel, signaling that net dollar flow turned positive on this bar: buy‑side dollar volume exceeded sell‑side dollar volume, pushing the cumulative sum ΣΔ$ above zero. In the info table, the “Money flow (bar)” and “Money flow Σ” rows both read In, confirming that the indicator’s money‑flow module has detected an inflow at both bar and aggregate levels, while other modules (pivots, trend lines and support/resistance) remain active to provide structural context.
In this example the Money Flow module signals a net outflow. Price has been trending downward: successive high pivots form a falling red trend‑line and the low pivots form a descending green support line. When the latest bar broke below the previous low pivot (LL1), both the bar‑level and cumulative net dollar flow turned negative—selling volume at the close exceeded buying volume and pushed the cumulative Δ$ below zero. The module reacts by printing a red “Money flow out” label beneath the candle; the info table confirms that the “Money flow (bar)” and “Money flow Σ” rows both show Out, indicating sustained dominance of sellers in this period.
10. Info Table
10.1 Purpose
When enabled, the Info Table appears in the lower right of your chart. It summarises key values computed by the indicator—such as buy and sell volume, delta, total volume, breakout status, market phase, and money flow—so you can see at a glance which side is dominant and which signals are active.
10.2 Symbols
• ↑ / ↓ — Up (↑) denotes buy volume or money; down (↓) denotes sell volume or money.
• MA — Moving average. In the table it shows the average value of a series over the lookback period.
• Σ (Sigma) — Cumulative sum over the chosen lookback period.
• Δ (Delta) — Difference between buy and sell values.
• B / S — Buyer and seller share of total volume, expressed as percentages.
• Ref. Price — Reference price for breakout calculations, based on the latest pivot.
• Status — Indicates whether a breakout condition is currently active (True) or has failed.
10.3 Row definitions
1. Up volume / MA up volume – Displays current buy volume on the lower timeframe and its moving average over the lookback period.
2. Down volume / MA down volume – Shows current sell volume and its moving average; sell values are formatted in red for clarity.
3. Δ / ΣΔ – Lists the difference between buy and sell volume for the current bar and the cumulative delta volume over the lookback period.
4. Σ / MA Σ (Vol/MA) – Total volume (buy + sell) for the bar, with the ratio of this volume to its moving average; the right cell shows the average total volume.
5. B/S ratio – Buy and sell share of the total volume: current bar percentages and the average percentages across the lookback period.
6. Buyer Rank / Seller Rank – Ranks the bar’s buy and sell volumes among the last (n) bars; lower rank numbers indicate higher relative volume.
7. Σ Buy / Σ Sell – Sum of buy and sell volumes over the lookback window, indicating which side has traded more.
8. Breakout UP / DOWN – Shows the breakout thresholds (Ref. Price) and whether the breakout condition is active (True) or has failed.
9. Market Phase (Vol) – Reports the current volume‑only phase: Accumulation, Distribution or Neutral.
10. Money Flow – The final rows display dollar amounts and status:
– ↑ USD / Σ↑ USD – Buy dollars for the current bar and the cumulative sum over the money‑flow period.
– ↓ USD / Σ↓ USD – Sell dollars and their cumulative sum.
– Δ USD / ΣΔ USD – Net dollar difference (buy minus sell) for the bar and cumulatively.
– Money flow (bar) – Indicates whether the bar’s net dollar flow is positive (In), negative (Out) or neutral.
– Money flow Σ – Shows whether the cumulative net dollar flow across the chosen period is positive, negative or neutral.
The chart above shows a sequence of different signals from the indicator. A Bull Trap Risk appears after price briefly pushes above resistance but fails to hold, then a green Accum label identifies an accumulation phase. An upward breakout follows, confirmed by a Money flow in print. Later, a Sharp ↓ Risk warns of a possible sharp downturn; after price dips below support but quickly recovers, a Bear Trap label marks a false breakdown. The highlighted info table in the center summarizes key metrics at that moment, including current and average buy/sell volumes, net delta, total volume versus its moving average, breakout status (up and down), market phase (volume), and bar‑level and cumulative money flow (In/Out).
11. Conclusion & Final Remarks
This indicator was developed as a holistic study of market structure and order flow. It brings together several well‑known concepts from technical analysis—breakouts, accumulation and distribution phases, overbought and oversold extremes, bull and bear traps, sharp directional moves, market‑maker spread bars and money flow—into a single Pine Script tool. Each module is based on widely recognized trading ideas and was implemented after consulting reference materials and example strategies, so you can see in real time how these concepts interact on your chart.
A distinctive feature of this indicator is its reliance on per‑side volume: instead of tallying only total volume, it separately measures buy and sell transactions on a lower time frame. This approach gives a clearer view of who is in control—buyers or sellers—and helps filter breakouts, detect phases of accumulation or distribution, recognize potential traps, anticipate sharp moves and gauge whether liquidity providers are active. The money‑flow module extends this analysis by converting volume into currency values and tracking net inflow or outflow across a chosen window.
Although comprehensive, this indicator is intended solely as a guide. It highlights conditions and statistics that many traders find useful, but it does not generate trading signals or guarantee results. Ultimately, you remain responsible for your positions. Use the information presented here to inform your analysis, combine it with other tools and risk‑management techniques, and always make your own decisions when trading.
BTCUSD
Spiderlines BTCUSD - daily/weekly📘 Documentation – Daily and Weekly Spider Lines for Bitcoin
🔹 Purpose of the Script
This script draws dynamic “Spider Lines” in the Bitcoin chart.
The lines connect certain historical candles with a reference candle and extend to the right.
These act as guideline levels that can serve as potential support or resistance zones.
🔹 How It Works
The script operates in two modes, depending on the active chart timeframe:
Weekly Mode (timeframe.isweekly)
The reference date is July 1, 2019.
The number of weeks since that date is calculated.
This defines the connection candle (connection_candle).
Several predefined offsets (e.g., +32, +34, +36 …) are added to the reference to determine starting candles.
Lines are drawn from these candles toward the connection candle.
→ Line color: green
Daily Mode (timeframe.isdaily)
Same reference date: July 1, 2019.
The number of days since that date is calculated.
Again, a connection candle is set.
A different set of offsets (e.g., +224, +238, +252 …) defines the starting candles.
Lines are drawn accordingly.
→ Line color: red
🔹 Line Logic
Each line connects:
Start → bar_index at high
End → bar_index at close
Lines are extended indefinitely to the right (extend.right).
Appearance: dashed style, width 2.
🔹 Error Handling
If a calculated candle index does not exist in the chart history (e.g., chart data does not go back far enough),
a label is plotted in the chart showing the message:
"Daily idx out of range: 252"
This way, missing lines can be diagnosed easily.
🔹 Color Convention
Weekly Spider Lines → Green
Daily Spider Lines → Red
🔹 Use Cases
Visualization of historical cyclic line patterns.
Helps in technical chart analysis: spotting potential reaction zones in price movement.
Designed mainly for long-term traders and analysts observing Bitcoin in Daily or Weekly timeframes.
🔹 Limitations
Works only on Daily and Weekly charts.
Requires chart data going back to July 1, 2019.
Based purely on fixed offsets → not a classical indicator like Moving Averages or RSI.
Sequential Pattern Strength [QuantAlgo]🟢 Overview
The Sequential Pattern Strength indicator measures the power and sustainability of consecutive price movements by tracking unbroken sequences of up or down closes. It incorporates sequence quality assessment, price extension analysis, and automatic exhaustion detection to help traders identify when strong trends are losing momentum and approaching potential reversal or continuation points.
🟢 How It Works
The indicator's key insight lies in its sequential pattern tracking system, where pattern strength is measured by analyzing consecutive price movements and their sustainability:
if close > close
upSequence := upSequence + 1
downSequence := 0
else if close < close
downSequence := downSequence + 1
upSequence := 0
The system calculates sequence quality by measuring how "perfect" the consecutive moves are:
perfectMoves = math.max(upSequence, downSequence)
totalMoves = math.abs(bar_index - ta.valuewhen(upSequence == 1 or downSequence == 1, bar_index, 0))
sequenceQuality = totalMoves > 0 ? perfectMoves / totalMoves : 1.0
First, it tracks price extension from the sequence starting point:
priceExtension = (close - sequenceStartPrice) / sequenceStartPrice * 100
Then, pattern exhaustion is identified when sequences become overextended:
isExhausted = math.abs(currentSequence) >= maxSequence or
math.abs(priceExtension) > resetThreshold * math.abs(currentSequence)
Finally, the pattern strength combines sequence length, quality, and price movement with momentum enhancement:
patternStrength = currentSequence * sequenceQuality * (1 + math.abs(priceExtension) / 10)
enhancedSignal = patternStrength + momentum * 10
signal = ta.ema(enhancedSignal, smooth)
This creates a sequence-based momentum indicator that combines consecutive movement analysis with pattern sustainability assessment, providing traders with both directional signals and exhaustion insights for entry/exit timing.
🟢 Signal Interpretation
Positive Values (Above Zero): Sequential pattern strength indicating bullish momentum with consecutive upward price movements and sustained buying pressure = Long/Buy opportunities
Negative Values (Below Zero): Sequential pattern strength indicating bearish momentum with consecutive downward price movements and sustained selling pressure = Short/Sell opportunities
Zero Line Crosses: Pattern transitions between bullish and bearish regimes, indicating potential trend changes or momentum shifts when sequences break
Upper Threshold Zone: Area above maximum sequence threshold (2x maxSequence) indicating extremely strong bullish patterns approaching exhaustion levels
Lower Threshold Zone: Area below negative threshold (-2x maxSequence) indicating extremely strong bearish patterns approaching exhaustion levels
Justin's Bitcoin Power Law PredictorJustin's MSTR Powerlaw Price Predictor is a Pine Script v6 indicator for TradingView that adapts Giovanni Santostasi’s Bitcoin power law model to forecast MicroStrategy (MSTR) stock prices. Using the formula Price = A * (daysSinceGenesis)^B, it calculates fair, upper, and floor prices with constants A_fair = 1.16e-17, A_floor = 0.42e-17, and B = 5.82, starting from Bitcoin’s genesis (January 3, 2009). The script plots these prices, displays values in a table.
Source: www.ccn.com
Justin's MSTR Powerlaw Price PredictorJustin's MSTR Powerlaw Price Predictor is a Pine Script v6 indicator for TradingView that adapts Giovanni Santostasi’s Bitcoin power law model to forecast MicroStrategy (MSTR) stock prices. The price prediction is based on the the formula published in this article:
www.ccn.com
Auto Intelligence Selective Moving Average(AI/MA)# 🤖 Auto Intelligence Moving Average Strategy (AI/MA)
**AI/MA** is a state-adaptive moving average crossover strategy designed to **maximize returns from golden cross / death cross logic** by intelligently switching between different MA types and parameters based on market conditions.
---
## 🎯 Objective
To build a moving average crossover strategy that:
- **Adapts dynamically** to market regimes (trend vs range, rising vs falling)
- **Switches intelligently** between SMA, EMA, RMA, and HMA
- **Maximizes cumulative return** under realistic backtesting
---
## 🧪 materials amd methods
- **MA Types Considered**: SMA, EMA, RMA, HMA
- **Parameter Ranges**: Periods from 5 to 40
- **Market Conditions Classification**:
- Based on the slope of a central SMA(20) line
- And the relative position of price to the central line
- Resulting in 4 regimes: A (Bull), B (Pullback), C (Rebound), D (Bear)
- **Optimization Dataset**:
- **Bybit BTCUSDT.P**
- **1-hour candles**
- **2024 full-year**
- **Search Process**:
- **Random search**: 200 parameter combinations
- Evaluated by:
- `Cumulative PnL`
- `Sharpe Ratio`
- `Max Drawdown`
- `R² of linear regression on cumulative PnL`
- **Implementation**:
- Optimization performed in **Python (Pandas + Matplotlib + Optuna-like logic)**
- Final parameters ported to **Pine Script (v5)** for TradingView backtesting
---
## 📈 Performance Highlights (on optimization set)
| Timeframe | Return (%) | Notes |
|-----------|------------|----------------------------|
| 6H | +1731% | Strongest performance |
| 1D | +1691% | Excellent trend capture |
| 12H | +1438% | Balance of trend/range |
| 5min | +27.3% | Even survives scalping |
| 1min | +9.34% | Robust against noise |
- Leverage: 100x
- Position size: 100%
- Fees: 0.055%
- Margin calls: **none** 🎯
---
## 🛠 Technology Stack
- `Python` for data handling and optimization
- `Pine Script v5` for implementation and visualization
- Fully state-aware strategy, modular and extendable
---
## ✨ Final Words
This strategy is **not curve-fitted**, **not over-parameterized**, and has been validated across multiple timeframes. If you're a fan of dynamic, intelligent technical systems, feel free to use and expand it.
💡 The future of simple-yet-smart trading begins here.
Reversal IndicatorWhat does this indicator do?
This indicator is designed to help traders spot potential reversal points in the market by combining multiple conditions:
✅ Multi-Timeframe RSI – Checks RSI on a lower timeframe (like 5m) to see if the market is oversold or overbought.
✅ Higher Timeframe SMA Filter – Uses a higher timeframe SMA (like 1h) as a trend filter, so signals only trigger in the direction of the bigger trend.
✅ Candle Pattern Confirmation – Looks for bullish or bearish engulfing candles to confirm price exhaustion before signaling a reversal.
When all these conditions align, the indicator plots a triangle under/above the candle to highlight a possible reversal.
Why is this useful?
Many traders struggle with false RSI signals or candle patterns that fail because they don’t respect the larger trend.
This indicator filters out weak setups by requiring alignment between:
A lower timeframe RSI oversold/overbought condition,
A higher timeframe trend filter (SMA),
And a strong candle reversal pattern.
This multi-layer approach helps avoid chasing every RSI dip and focuses only on high-probability reversal zones.
How does it work?
Bullish reversal signal → appears when RSI on the lower TF is oversold, price is still above the higher TF SMA (trend still intact), AND a bullish engulfing candle forms.
Bearish reversal signal → appears when RSI on the lower TF is overbought, price is below the higher TF SMA, AND a bearish engulfing candle forms.
When all conditions match, the indicator plots a triangle under the candle for bullish signals and above the candle for bearish signals.
How to use it?
Choose your timeframes:
A timeframe for trend filtering (e.g. 1h).
A timeframe for RSI (e.g. 4h).
NOTICE: THE RSI TIMEFRAME SHOULD BE GREATER THEN THE TIMEFRAME FOR THE SMA
Otherwise it will not generate that much signals.
Watch for signals ONLY in the direction of the higher trend.
Use the signals as potential reversal points, not as guaranteed entries. Combine with your own confluence.
Optionally set alerts for bullish or bearish reversal conditions so you never miss a setup.
Customization
✅ Choose your RSI length & overbought/oversold levels.
✅ Select which timeframes you want for SMA & RSI.
✅ Toggle the higher TF SMA display on/off.
✅ Adjust signal appearance (triangles).
Important Notes
⚠️ This is not a standalone trading system. It’s a tool to help spot possible reversal areas. Always confirm with price action, support/resistance, or your own strategy
Bull Momentum GaugeBull Momentum Gauge
The Bull Momentum Gauge is a powerful momentum oscillator designed to identify the underlying strength and sustainability of major market trends. Instead of trying to predict tops and bottoms, this indicator helps traders and investors ride long-term bull markets by signaling when momentum is building and when it is starting to fade.
What it Does
At its core, this tool measures how statistically "stretched" or "compressed" an asset's price is relative to its long-term (1-year) trend. It does this by:
Calculating the price's deviation from its 365-day moving average.
Normalizing this deviation into a Z-score to measure its statistical significance.
Comparing the inverted Z-score to its own 200-day moving average to gauge the momentum of the trend itself.
The result is a single, smooth line that oscillates around a zero value.
How to Use It
The signals are simple and based on the indicator's relationship to the zero line:
Green Line (Gauge below 0): This indicates that the price has been compressed relative to its long-term trend and is now showing signs of building upward momentum. A cross into the green zone can be interpreted as a potential entry signal for a new bull run.
Red Line (Gauge above 0): This suggests that the price has become over-extended or "stretched" and the upward momentum is beginning to weaken. A cross into the red zone can be used as a potential exit signal, indicating it may be time to take profits and wait for the next cycle.
This indicator is designed to work across multiple timeframes (Daily, Weekly, Monthly) and provides a clear, data-driven framework for navigating major market cycles.
EMA 200 Monitor - Bybit CoinsEMA 200 Monitor - Bybit Coins
📊 OVERVIEW
The EMA 200 Monitor - Bybit Coins is an advanced indicator that automatically monitors 30 of the top cryptocurrencies traded on Bybit, alerting you when they are close to the 200-period Exponential Moving Average on the 4-hour timeframe.
This indicator was developed especially for traders who use the EMA 200 as a key support/resistance level in their swing trading and position trading strategies.
🎯 WHAT IT'S FOR
Multi-Asset Monitoring: Simultaneous monitoring of 30 cryptocurrencies without having to switch between charts
Opportunity Identification: Detects when coins are approaching the 200 EMA, a crucial technical level
Automated Alerts: Real-time notifications when a coin reaches the configured proximity
Time Efficiency: Eliminates the need to manually check chart collections
⚙️ HOW IT WORKS
Main Functionality
The indicator uses the request.security() function to fetch price data and calculate the 200 EMA of each monitored asset. With each new bar, the script:
Calculates the distance between the current price and the 200 EMA for each coin
Identifies proximity based on the configured percentage (default: 2%)
Displays results in a table organized on the chart
Generates automatic alerts when proximity is detected
Monitored Coins
Major : BTC, ETH, BNB, ADA, XRP, SOL, DOT, DOGE, AVAX
DeFi : UNI, LINK, ATOM, ICP, NEAR, OP, ARB, INJ
Memecoins : SHIB, PEPE, WIF, BONK, FLOKI
Emerging : SUI, TON, APT, POL (ex-MATIC)
📋 AVAILABLE SETTINGS
Adjustable Parameters
EMA Length (Default: 200): Exponential Moving Average Period
Proximity Percentage (Default: 2%): Distance in percentage to consider "close"
Show Table (Default: Active): Show/hide results table
Table Position: Position of the table on the chart (9 options available)
Color System
🔴 Red: Distance ≤ 1% (very close)
🟠 Orange: Distance ≤ 1.5% (close)
🟡 Yellow: Distance ≤ 2% (approaching)
🚀 HOW TO USE
Initial Configuration
Add the indicator to the 4-hour timeframe chart
Set the parameters according to your strategy
Position the table where there is no graphic preference
Setting Alerts
Click "Create Alert" in TradingView
Select the "EMA 200 Monitor" indicator
Set the notification frequency and method
Activate the alert to receive automatic notifications
Results Interpretation
The table shows:
Coin: Asset name (e.g. BTC, ETH)
Price: Current currency quote
EMA 200: Current value of the moving average
Distance: Percentage of proximity to the core code
💡 STRATEGIES TO USE
Reversal Trading
Entry: When price touches or approaches the EMA 200
Stop: Below/above the EMA with a safety margin
Target: Previous resistance/support levels
Breakout Trading
Monitoring: Watch for currencies consolidating near the EMA 200
Entry: When the media is finally broken
Confirmation: Volume and close above/below the EMA
Swing Trading
Identification: Use the monitor to detect setups in formation
Timing: Wait for the EMA 200 to approach for detailed analysis
Management: Use the EMA as a reference for stops dynamics
⚠️ IMPORTANT CONSIDERATIONS
Technical Limitations
Request Bybit data: Access to exchange symbols required
Specific timeframe: Optimized for 4-hour analysis
Minimum delay: Data updated with each new bar
Usage Recommendations
Combine with technical analysis: Use together with other indicators
Confirm the configuration: Check the graphic patterns before trading
Manage risk: Always use stop loss and adequate position sizing
Backtesting: Test your strategy before applying with real capital
Disclaimer
This indicator is a technical analysis tool and does not constitute investment advice. Always do your own analysis and manage detailed information about the risks of your operations.
🔧 TECHNICAL INFORMATION
Pine Script version: v6
Type: Indicator (overlay=true)
Compatibility: All TradingView plans
Resources used: request.security(), arrays, tables
Performance: Optimized for multiple simultaneous queries
📈 COMPETITIVE ADVANTAGES
✅ Simultaneous monitoring of 30 major assets ✅ Clear visual interface with intuitive core system ✅ Customizable alerts for different details ✅ Optimized code for maximum performance ✅ Flexible configuration adaptable to different strategies ✅ Real-time update without the need for manual refresh
Developed for traders who value efficiency and accuracy in identifying market opportunities based on the EMA 20
MestreDoFOMO MACD VisualMasterDoFOMO MACD Visual
Description
MasterDoFOMO MACD Visual is a custom indicator that combines a unique approach to MACD with stochastic logic and simulated Renko-based direction signals. It is designed to help traders identify entry and exit opportunities based on market momentum and trend changes, with a clear and intuitive visualization.
How It Works
Stylized MACD with Stochastic: The indicator calculates the MACD using EMAs (exponential moving averages) normalized by stochastic logic. This is done by subtracting the lowest price (lowest low) from a defined period and dividing by the range between the highest and lowest price (highest high - lowest low). The result is a MACD that is more sensitive to market conditions, magnified by a factor of 10 for better visualization.
Signal Line: An EMA of the MACD is plotted as a signal line, allowing you to identify crossovers that indicate potential trend reversals or continuations.
Histogram: The difference between the MACD and the signal line is displayed as a histogram, with distinct colors (fuchsia for positive, purple for negative) to make momentum easier to read.
Simulated Renko Direction: Uses ATR (Average True Range) to calculate the size of Renko "bricks", generating signals of change in direction (bullish or bearish). These signals are displayed as arrows on the chart, helping to identify trend reversals.
Purpose
The indicator combines the sensitivity of the Stochastic MACD with the robustness of Renko signals to provide a versatile tool. It is ideal for traders looking to capture momentum-based market movements (using the MACD and histogram) while confirming trend changes with Renko signals. This combination reduces false signals and improves accuracy in volatile markets.
Settings
Stochastic Period (45): Sets the period for calculating the Stochastic range (highest high - lowest low).
Fast EMA Period (12): Period of the fast EMA used in the MACD.
Slow EMA Period (26): Period of the slow EMA used in the MACD.
Signal Line Period (9): Period of the EMA of the signal line.
Overbought/Oversold Levels (1.0/-1.0): Thresholds for identifying extreme conditions in the MACD.
ATR Period (14): Period for calculating the Renko brick size.
ATR Multiplier (1.0): Adjusts the Renko brick size.
Show Histogram: Enables/disables the histogram.
Show Renko Markers: Enables/disables the Renko direction arrows.
How to Use
MACD Crossovers: A MACD crossover above the signal line indicates potential bullishness, while below suggests bearishness.
Histogram: Fuchsia bars indicate bullish momentum; purple bars indicate bearish momentum.
Renko Arrows: Green arrows (upward triangle) signal a change to an uptrend; red arrows (downward triangle) signal a downtrend.
Overbought/Oversold Levels: Use the levels to identify potential reversals when the MACD reaches extreme values.
Notes
The chart should be set up with this indicator in isolation for better clarity.
Adjust the periods and ATR multiplier according to the asset and timeframe used.
Use the built-in alerts ("Renko Up Signal" and "Renko Down Signal") to set up notifications of direction changes.
This indicator is ideal for day traders and swing traders who want a visually clear and functional tool for trading based on momentum and trends.
Momentum Long + Short Strategy (BTC 3H)Momentum Long + Short Strategy (BTC 3H)
🔍 How It Works, Step by Step
Detect the Trend (📈/📉)
Calculate two moving averages (100-period and 500-period), either EMA or SMA.
For longs, we require MA100 > MA500 (uptrend).
For shorts, we block entries if MA100 exceeds MA500 by more than a set percentage (to avoid fading a powerful uptrend).
Apply Momentum Filters (⚡️)
RSI Filter: Measures recent strength—only allow longs when RSI crosses above its smoothed average, and shorts when RSI dips below the oversold threshold.
ADX Filter: Gauges trend strength—ensures we only enter when a meaningful trend exists (optional).
ATR Filter: Confirms volatility—avoids choppy, low-volatility conditions by requiring ATR to exceed its smoothed value (optional).
Confirm Entry Conditions (✅)
Long Entry:
Price is above both MAs
Trend alignment & optional filters pass ✅
Short Entry:
Price is below both MAs and below the lower Bollinger Band
RSI is sufficiently oversold
Trend-blocker & ATR filter pass ✅
Position Sizing & Risk (💰)
Each trade uses 100 % of account equity by default.
One pyramid addition allowed, so you can scale in if the move continues.
Commission and slippage assumptions built in for realistic backtests.
Stops & Exits (🛑)
Long Stop-Loss: e.g. 3 % below entry.
Long Auto-Exit: If price falls back under the 500-period MA.
Short Stop-Loss: e.g. 3 % above entry.
Short Take-Profit: e.g. 4 % below entry.
🎨 Why It’s Powerful & Customizable
Modular Filters: Turn on/off RSI, ADX, ATR filters to suit different market regimes.
Adjustable Thresholds: Fine-tune stop-loss %, take-profit %, RSI lengths, MA gaps and more.
Multi-Timeframe Potential: Although coded for 3 h BTC, you can adapt it to stocks, forex or other cryptos—just recalibrate!
Backtest Fine-Tuned: Default settings were optimized via backtesting on historical BTC data—but they’re not guarantees of future performance.
⚠️ Warning & Disclaimer
This strategy is for educational purposes only and designed for a toy fund. Crypto markets are highly volatile—you can lose 100 % of your capital. It is not a predictive “holy grail” but a rules-based framework using past data. The parameters have been fine-tuned on historical data and are not valid for future trades without fresh calibration. Always practice with paper-trading first, use proper risk management, and do your own research before risking real money. 🚨🔒
Good luck exploring and experimenting! 🚀📊
MestreDoFOMO Future Projection BoxMestreDoFOMO Future Projection Box - Description & How to Use
Description
The "MestreDoFOMO Future Projection Box" is a TradingView indicator tailored for crypto traders (e.g., BTC/USDT on 1H, 4H, or 1D timeframes). It visualizes current price ranges, projects future levels, and confirms trends using semi-transparent boxes. With labeled price levels and built-in alerts, it’s a simple yet powerful tool for identifying support, resistance, and potential price targets.
How It Works
Blue Box (Current Channel): Shows the recent price range over the last 10 bars (adjustable). The top is the highest high plus an ATR buffer, and the bottom is the lowest low minus the buffer. Labels display exact levels (e.g., "Top: 114000", "Bottom: 102600").
Green Box (Future Projection): Projects the price range 10 bars ahead (adjustable) based on the trend slope of the moving average. Labels show "Proj Top" and "Proj Bottom" for future targets.
Orange Box (Moving Average): Traces a 50-period EMA (adjustable) to confirm the trend. An upward slope signals a bullish trend; a downward slope signals a bearish trend. A label shows the current MA value (e.g., "MA: 105000").
Alerts: Triggers when the price nears the projected top or bottom, helping you catch breakouts or retracements.
How to Use
Add the Indicator: Apply "MestreDoFOMO Future Projection Box" to your chart in TradingView.
Interpret the Trend: Check the orange box’s slope—upward for bullish, downward for bearish.
Identify Key Levels: Use the blue box’s top as resistance and bottom as support. On a 4H chart, if the top is 114,000, expect resistance; if the bottom is 102,600, expect support.
Plan Targets: Use the green box for future targets—top for profit-taking (e.g., 114,000), bottom for stop-loss or buying (e.g., 102,600).
Set Alerts: Enable alerts for "Near Upper Projection" or "Near Lower Projection" to get notified when the price hits key levels.
Trade Examples:
Bullish: If the price breaks above the blue box top (e.g., 114,000), buy with a target at the green box top. Set a stop-loss below the green box bottom.
Bearish: If the price rejects at the blue box top and drops below the orange MA, short with a target at the blue box bottom.
Customize: Adjust the lookback period, projection bars, ATR multiplier, and MA length in the settings to fit your trading style.
Tips
Use on 1H for short-term trades, 4H for swing trades, or 1D for long-term trends.
Combine with volume or RSI to confirm signals.
Validate levels with market structure (e.g., candlestick patterns).
BTC-USDT Liquidity Trend [Ajit Pandit]his script helps traders visualize trend direction and identify liquidity zones where price might react due to past pivot levels. The color-coded candles and extended pivot lines make it easier to spot support/resistance levels and potential breakout points.
Key Features:
1. Trend Detection Using EMA
Uses two EMA calculations to determine the trend:
emaValue: Standard EMA based on length1
correction: Adjusted price movement relative to EMA
Trend: Another EMA of the corrected value
Determines bullish (signalUp) and bearish (signalDn) signals when Trend crosses emaValue.
2. Candlestick Coloring Based on Trend
Candlesticks are colored:
Uptrend → Blue (up color)
Downtrend → Pink (dn color)
Neutral → No color
3. Liquidity Zones (Pivot Highs & Lows)
Identifies pivot highs and lows using a customizable pivot length.
Draws liquidity lines:
High pivot lines (Blue, adjustable width)
Low pivot lines (Pink, adjustable width)
Extends lines indefinitely until price breaks above/below the level.
Removes broken pivot levels dynamically.
Accurate Trend IndicatorAccurate Trend Indicator
The Accurate Trend Indicator is a powerful trend-following tool designed to help traders identify optimal buy and sell opportunities with precision. Based on the Supertrend algorithm, this indicator dynamically tracks market trends and provides clear entry and exit signals.
Features:
✅ Supertrend-Based Signals – Uses ATR (Average True Range) to determine trend direction.
✅ Buy & Sell Alerts – Displays green "BUY" labels and red "SELL" labels when trend changes.
✅ Color-Coded Candles – Bullish candles turn green, and bearish candles turn red for better visualization.
✅ Works on Any Market – Compatible with Forex, Stocks, Crypto, and Commodities.
✅ Customizable Inputs – Adjust the ATR length and multiplier to fit your trading strategy.
How It Works:
A BUY signal appears when the price crosses above the Supertrend line.
A SELL signal appears when the price crosses below the Supertrend line.
Candle colors change based on trend direction to enhance clarity.
This indicator is ideal for traders who want a simple yet effective tool to follow market trends and make informed decisions.
🚀 Try it now and enhance your trading strategy! 🚀
ADX for BTC [PineIndicators]The ADX Strategy for BTC is a trend-following system that uses the Average Directional Index (ADX) to determine market strength and momentum shifts. Designed for Bitcoin trading, this strategy applies a customizable ADX threshold to confirm trend signals and optionally filters entries using a Simple Moving Average (SMA). The system features automated entry and exit conditions, dynamic trade visualization, and built-in trade tracking for historical performance analysis.
⚙️ Core Strategy Components
1️⃣ Average Directional Index (ADX) Calculation
The ADX indicator measures trend strength without indicating direction. It is derived from the Positive Directional Movement (+DI) and Negative Directional Movement (-DI):
+DI (Positive Directional Index): Measures upward price movement.
-DI (Negative Directional Index): Measures downward price movement.
ADX Value: Higher values indicate stronger trends, regardless of direction.
This strategy uses a default ADX length of 14 to smooth out short-term fluctuations while detecting sustainable trends.
2️⃣ SMA Filter (Optional Trend Confirmation)
The strategy includes a 200-period SMA filter to validate trend direction before entering trades. If enabled:
✅ Long Entry is only allowed when price is above a long-term SMA multiplier (5x the standard SMA length).
✅ If disabled, the strategy only considers the ADX crossover threshold for trade entries.
This filter helps reduce entries in sideways or weak-trend conditions, improving signal reliability.
📌 Trade Logic & Conditions
🔹 Long Entry Conditions
A buy signal is triggered when:
✅ ADX crosses above the threshold (default = 14), indicating a strengthening trend.
✅ (If SMA filter is enabled) Price is above the long-term SMA multiplier.
🔻 Exit Conditions
A position is closed when:
✅ ADX crosses below the stop threshold (default = 45), signaling trend weakening.
By adjusting the entry and exit ADX levels, traders can fine-tune sensitivity to trend changes.
📏 Trade Visualization & Tracking
Trade Markers
"Buy" label (▲) appears when a long position is opened.
"Close" label (▼) appears when a position is exited.
Trade History Boxes
Green if a trade is profitable.
Red if a trade closes at a loss.
Trend Tracking Lines
Horizontal lines mark entry and exit prices.
A filled trade box visually represents trade duration and profitability.
These elements provide clear visual insights into trade execution and performance.
⚡ How to Use This Strategy
1️⃣ Apply the script to a BTC chart in TradingView.
2️⃣ Adjust ADX entry/exit levels based on trend sensitivity.
3️⃣ Enable or disable the SMA filter for trend confirmation.
4️⃣ Backtest performance to analyze historical trade execution.
5️⃣ Monitor trade markers and history boxes for real-time trend insights.
This strategy is designed for trend traders looking to capture high-momentum market conditions while filtering out weak trends.
Swing High/Low Pivots Strategy [LV]The Swing High/Low Pivots Strategy was developed as a counter-momentum trading tool.
The strategy is suitable for any market and the default values used in the input settings menu are set for Bitcoin (best on 15min). These values, expressed in minimum ticks (or pips if symbol is Forex) make this tool perfectly adaptable to every symbol and/or timeframe.
Check tooltips in the settings menu for more details about every user input.
STRTEGY ENTRY & EXIT MECHANISMS:
Trades Entry based on the detection of swing highs and lows for short and long entries respectively, validated by:
- Limit orders placed after each new pivot level confirmation
- Moving averages trend filter (if enabled)
- No active trade currently open
Trades Exit when the price reaches take-profit or stop-loss level as defined in the settings menu. A double entry/second take-profit level can be enabled for partial exits, with dynamic stop-loss adjustment for the remaining position.
Enhanced Trade Precision:
By limiting entries to confirmed swing high (HH, LH) or swing low (HL, LL) pivot points, the strategy ensures that trades occur at levels of significant price reversals. This precision reduces the likelihood of entering trades in the midst of a trend or during uncertain price action.
Risk Management Optimization:
The strategy incorporates clearly defined stop-loss (SL) and take-profit (TP) levels derived from the pivot points. This structured approach minimizes potential losses while locking in profits, which is critical for consistent performance in volatile markets.
Trend Filtering for Better Entry:
The use of a configurable moving average filter adds a layer of trend validation. This prevents entering trades against the dominant market trend, increasing the probability of success for each trade.
Avoidance of Noise:
The lookback period (length parameter) confirms pivots only after a set number of bars, effectively filtering out market noise and ensuring that entries are based on reliable, well-defined price movements.
Adaptability Across Markets:
The strategy is versatile and can be applied across different markets (Forex, stocks, crypto) due to its dynamic use of ticks and pips converters. It adapts seamlessly to varying price scales and asset types.
Dual Quantity Entries:
The original and optionnal double-entry mechanism allows traders to capture both short-term and extended profits by scaling out of positions. This adaptive approach caters to varying risk appetites and market conditions.
Clear Visualization:
The plotted pivot points, entry limits, SL, and TP levels provide visual clarity, making it easy for traders to track the strategy's behavior and make informed decisions.
Automated Execution with Alerts:
Integrated alerts for both entries and exits ensure timely actions without the need for constant market monitoring, enhancing efficiency. Configurable alert messages are suitable for API use.
Any feedback, comments, or suggestions for improvement are always welcome.
Hope you enjoy!
Cabal Dev IndicatorThis is a TradingView Pine Script (version 6) that creates a technical analysis indicator called the "Cabal Dev Indicator." Here's what it does:
1. Core Functionality:
- It calculates a modified version of the Stochastic Momentum Index (SMI), which is a momentum indicator that shows where the current close is relative to the high/low range over a period
- The indicator combines elements of stochastic oscillator calculations with exponential moving averages (EMA)
2. Key Components:
- Uses configurable input parameters for:
- Percent K Length (default 15)
- Percent D Length (default 3)
- EMA Signal Length (default 15)
- Smoothing Period (default 5)
- Overbought level (default 40)
- Oversold level (default -40)
3. Calculation Method:
- Calculates the highest high and lowest low over the specified period
- Finds the difference between current close and the midpoint of the high-low range
- Applies EMA smoothing to both the range and relative differences
- Generates an SMI value and further smooths it using a simple moving average (SMA)
- Creates an EMA signal line based on the smoothed SMI
4. Visual Output:
- Plots the smoothed SMI line in green
- Plots an EMA signal line in red
- Shows overbought and oversold levels as gray horizontal lines
- Fills the areas above the overbought level with light red
- Fills the areas below the oversold level with light green
This indicator appears designed to help traders identify potential overbought and oversold conditions in the market, as well as momentum shifts, which could be used for trading decisions.
Would you like me to explain any specific part of the indicator in more detail?
Adapted RSI w/ Multi-Asset Regime Detection v1.1The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of an asset's recent price changes to detect overbought or oversold conditions in the price of said asset.
In addition to identifying overbought and oversold assets, the RSI can also indicate whether your desired asset may be primed for a trend reversal or a corrective pullback in price. It can signal when to buy and sell.
The RSI will oscillate between 0 and 100. Traditionally, an RSI reading of 70 or above indicates an overbought condition. A reading of 30 or below indicates an oversold condition.
The RSI is one of the most popular technical indicators. I intend to offer a fresh spin.
Adapted RSI w/ Multi-Asset Regime Detection
Our Adapted RSI makes necessary improvements to the original Relative Strength Index (RSI) by combining multi-timeframe analysis with multi-asset monitoring and providing traders with an efficient way to analyse market-wide conditions across different timeframes and assets simultaneously. The indicator automatically detects market regimes and generates clear signals based on RSI levels, presenting this data in an organised, easy-to-read format through two dynamic tables. Simplicity is key, and having access to more RSI data at any given time, allows traders to prepare more effectively, especially when trading markets that "move" together.
How we calculate the RSI
First, the RSI identifies price changes between periods, calculating gains and losses from one look-back period to the next. This look-back period averages gains and losses over 14 periods, which in this case would be 14 days, and those gains/losses are calculated based on the daily closing price. For example:
Average Gain = Sum of Gains over the past 14 days / 14
Average Loss = Sum of Losses over the past 14 days / 14
Then we calculate the Relative Strength (RS):
RS = Average Gain / Average Loss
Finally, this is converted to the RSI value:
RSI = 100 - (100 / (1 + RS))
Key Features
Our multi-timeframe RSI indicator enhances traditional technical analysis by offering synchronised Daily, Weekly, and Monthly RSI readings with automatic regime detection. The multi-asset monitoring system allows tracking of up to 10 different assets simultaneously, with pre-configured major pairs that can be customised to any asset selection. The signal generation system provides clear market guidance through automatic regime detection and a five-level signal system, all presented through a sophisticated visual interface with dynamic RSI line colouring and customisable display options.
Quick Guide to Use it
Begin by adding the indicator to your chart and configuring your preferred assets in the "Asset Comparison" settings.
Position the two information tables according to your preference.
The main table displays RSI analysis across three timeframes for your current asset, while the asset table shows a comparative analysis of all monitored assets.
Signals are colour-coded for instant recognition, with green indicating bullish conditions and red for bearish conditions. Pay special attention to regime changes and signal transitions, using multi-timeframe confluence to identify stronger signals.
How it Works (Regime Detection & Signals)
When we say 'Regime', a regime is determined by a persistent trend or in this case momentum and by leveraging this for RSI, which is a momentum oscillator, our indicator employs a relatively simple regime detection system that classifies market conditions as either Bullish (RSI > 50) or Bearish (RSI < 50). Our benchmark between a trending bullish or bearish market is equal to 50. By leveraging a simple classification system helps determine the probability of trend continuation and the weight given to various signals. Whilst we could determine a Neutral regime for consolidating markets, we have employed a 'neutral' signal generation which will be further discussed below...
Signal generation occurs across five distinct levels:
Strong Buy (RSI < 15)
Buy (RSI < 30)
Neutral (RSI 30-70)
Sell (RSI > 70)
Strong Sell (RSI > 85)
Each level represents different market conditions and probability scenarios. For instance, extreme readings (Strong Buy/Sell) indicate the highest probability of mean reversion, while neutral readings suggest equilibrium conditions where traders should focus on the overall regime bias (Bullish/Bearish momentum).
This approach offers traders a new and fresh spin on a popular and well-known tool in technical analysis, allowing traders to make better and more informed decisions from the well presented information across multiple assets and timeframes. Experienced and beginner traders alike, I hope you enjoy this adaptation.
Simple Moving Average with Regime Detection by iGrey.TradingThis indicator helps traders identify market regimes using the powerful combination of 50 and 200 SMAs. It provides clear visual signals and detailed metrics for trend-following strategies.
Key Features:
- Dual SMA System (50/200) for regime identification
- Colour-coded candles for easy trend visualisation
- Metrics dashboard
Core Signals:
- Bullish Regime: Price < 200 SMA
- Bearish Regime: Price > 200 SMA
- Additional confirmation: 50 SMA Cross-over or Cross-under (golden cross or death cross)
Metrics Dashboard:
- Current Regime Status (Bull/Bear)
- SMA Distance (% from price to 50 SMA)
- Regime Distance (% from price to 200 SMA)
- Regime Duration (bars in current regime)
Usage Instructions:
1. Apply the indicator to your chart
2. Configure the SMA lengths if desired (default: 50/200)
3. Monitor the color-coded candles:
- Green: Bullish regime
- Red: Bearish regime
4. Use the metrics dashboard for detailed analysis
Settings Guide:
- Length: Short-term SMA period (default: 50)
- Source: Price calculation source (default: close)
- Regime Filter Length: Long-term SMA period (default: 200)
- Regime Filter Source: Price source for regime calculation (default: close)
Trading Tips:
- Use bullish regimes for long positions
- Use bearish regimes for capital preservation or short positions
- Consider regime duration for trend strength
- Monitor distance metrics for potential reversals
- Combine with other systems for confluence
#trend-following #moving average #regime #sma #momentum
Risk Management:
- Not a standalone trading system
- Should be used with proper position sizing
- Consider market conditions and volatility
- Always use stop losses
Best Practices:
- Monitor multiple timeframes
- Use with other confirmation tools
- Consider fundamental factors
Version: 1.0
Created by: iGREY.Trading
Release Notes
// v1.1 Allows table overlay customisation
// v1.2 Update to v6 pinescript
Bitcoin Cycle [BigBeluga]Bitcoin Cycle Indicator is designed exclusively for analyzing Bitcoin’s long-term market cycles, working only on the 1D BTC chart . This indicator provides an in-depth view of potential cycle tops and bottoms, assisting traders in identifying key phases in Bitcoin’s market evolution.
🔵 Key Features:
Heatmap Cycle Phases: The indicator colors each cycle from blue to red , reflecting Bitcoin’s market cycle progression. Cooler colors (blue/green) signal potential accumulation or early growth phases, while warmer colors (yellow/red) indicate maturation and potential top regions.
All-Time High (ATH) and Future ATH Projection: Tracks the current ATH in real-time, while applying a linear regression model to project a possible new ATH in the future. This projection aims to provide insights into the next major cycle peak for long-term strategy.
Dashboard Overview: Displays the current ATH, potential new ATH, and the percentage distance between them. This helps users assess how far the current price is from the projected target.
Top & Bottom Cycle Signals: Red down arrows mark significant price peaks, potentially indicating cycle tops. Up arrows, numbered sequentially (inside each cycle), denote possible bottom signals for strategic DCA (Dollar Cost Averaging) entries.
1D BTC Chart Only: Built solely for the 1D BTC timeframe. Switching to any other timeframe or asset will trigger a warning message: " BTC 1D Only ." This ensures accuracy in analyzing Bitcoin’s unique cyclical behavior.
🔵 When to Use:
Ideal for long-term Bitcoin investors and cycle analysts, the Bitcoin Cycle Indicator empowers users to:
Identify key accumulation and distribution phases.
Track Bitcoin’s cyclical highs and lows with visual heatmap cues.
Estimate future potential highs based on historical patterns.
Strategize long-term positions by monitoring cycle tops and possible accumulation zones.
By visualizing Bitcoin’s cycles with color-coded clarity and top/bottom markers, this indicator is an essential tool for any BTC analyst aiming to navigate market cycles effectively.
Sharpe Ratio Z-ScoreThe "Sharpe Ratio Z-Score" indicator is a powerful tool designed to measure risk-adjusted returns in financial assets. This script helps investors evaluate the performance of a security relative to its risk, using a Z-score based modification of the Sharpe Ratio. The indicator is suitable for assessing market environments and understanding periods of underperformance or overperformance relative to historical standards.
Features:
Risk Assessment and Scaling: The indicator calculates a modified version of the Sharpe Ratio
over a user-defined period. By using scaling and mean offset adjustments, it allows for better
fitting to different market conditions.
Customizable Settings:
Period Length: The number of bars used to calculate the Sharpe Ratio.
Mean Adjustment: Offset value to adjust the average return of the calculated Sharpe ratio.
Scale Factor: A multiplier for emphasizing or reducing the calculated score's impact.
Line Color: Easily customize the plot's appearance.
Visual Cues:
Plots horizontal lines and fills specific regions to visually represent significant Z-score levels.
Highlighted zones include risk thresholds, such as overbought (positive Z-scores) and oversold
(negative Z-scores) areas, using intuitive color fills:
Green for areas below -0.5 (potential buy opportunities).
Red for areas above 0.5 (potential sell opportunities).
Yellow for neutral zones between -0.5 and 0.5.
Use Cases:
Risk-Adjusted Decision Making: Understand when returns are favorable compared to risk, especially during volatile market conditions.
Timing Reversion to Mean: Use highlighted zones to identify potential reversion-to-mean scenarios.
Trend Analysis: Identify times when an asset's performance is significantly deviating from its
average risk-adjusted return.
How It Works:
The script computes the daily returns over a set period, calculates the standard deviation of
those returns, and then applies a modified Sharpe Ratio approach. The Z-score transformation
helps to visualize how far an asset's risk-adjusted return deviates from its historical average.
This "Sharpe Ratio Z-Score" indicator is well-suited for investors seeking to combine quantitative metrics with visual cues, enhancing decision-making for long and short positions while maintaining a risk-adjusted perspective.
Multi-Timeframe RangeThe Multi-Timeframe Range Indicator is designed for traders looking to monitor key price levels across various timeframes (Daily, Weekly, Monthly, Quarterly, and Yearly) directly on their charts. This indicator draws boxes and mid-lines for each timeframe’s high, low, and midpoint, enabling users to visualize price ranges and assess potential areas of support and resistance more effectively.
Features:
Dynamic Range Boxes: Displays the high, low, and midpoint levels for each specified timeframe, with customizable colors for easy differentiation.
Visual Cues for Monday’s Levels: Highlights Monday’s high, low, and midpoint levels each week to support intraday trading setups and weekly trend analysis.
Multi-Timeframe Flexibility: Easily toggle between timeframes to view ranges from daily to yearly, making this indicator suitable for both short-term and long-term traders.
Ideal Use Cases:
Identify key support and resistance zones based on multiple timeframes.
Assess weekly and monthly trends using the Monday range levels.
Gain insights into market structure across various timeframes.
Point and Figure Displacement IndicatorThe PnF Displacement indicator is my custom script for TradingView, designed to analyze Point and Figure (PnF) charts with displacement features.
Key components of the script include:
User Inputs:
Require FVG: A boolean input to determine if a Fair Value Gap (FVG) is required for displacement calculations.
Displacement Type: Allows users to choose between "Open to Close" and "High to Low" for column range calculations.
Displacement Length: Defines how far back to look for calculating the standard deviation of the column range.
Displacement Strength: Multiplier for the standard deviation to adjust sensitivity.
Box Size: Sets the size of each box in the PnF chart.
Number of Boxes for Minimum Displacement: Specifies how many boxes to consider for calculating the minimum displacement.
Displacement Logic:
The script calculates the column range based on the selected displacement type.
It computes a standard deviation of the candle range and determines a minimum displacement based on user-defined box size and count.
The displacement condition combines the FVG check and the column range against the calculated minimum.
Visual Representation:
The bars are colored based on displacement conditions, enhancing visual analysis on the chart.
This indicator aids traders in identifying significant price movements in PnF charts while incorporating user customization options for better analysis.
