VWAP Entry Assistant (v1.0)Description:
Anchored VWAP with a lightweight assistant for VWAP reversion trades.
It shows the distance to VWAP, an estimated hit probability for the current bar, the expected number of bars to reach VWAP, and a recommended entry price.
If the chance of touching VWAP is low, the script suggests an adjusted limit using a fraction of ATR.
The VWAP line is white by default, and a compact summary table appears at the bottom-left.
Educational tool. Not financial advice. Not affiliated with TradingView or any exchange. Always backtest before use.
Swing-trading
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.
Recent Range DetectorOverview
The Recent Range Detector is a specialized indicator designed to identify when an asset is currently range-bound, providing traders with clear support and resistance levels for range trading strategies. Unlike traditional indicators that focus on trend detection, this tool specifically answers the question: "Is the price range-bound right now, and what are the exact trading levels?"
Key Features
✅ Smart Range Detection - Uses a multi-factor scoring system to identify legitimate ranges
✅ Dynamic Support/Resistance Levels - Automatically calculates and displays key trading levels
✅ Range Quality Scoring - Provides confidence levels (Strong/Moderate/Weak Range)
✅ Touch Validation - Counts actual price touches to confirm range reliability
✅ Breakout Detection - Alerts when price exits the established range
✅ Visual Clarity - Clean boxes, lines, and labels for easy interpretation
How It Works
The indicator analyses recent price action using three core metrics:
Touch Quality (40%) - How many times price has respected support/resistance levels
Containment Quality (40%) - What percentage of recent bars stayed within the range
Recent Respect (20%) - Whether the latest price action confirms the range
These combine into a Range Score (0-1) that determines range strength and reliability.
Settings & Parameters
Range Lookback Period (Default: 15)
Number of bars to analyse for range detection
Shorter periods = more responsive to recent ranges
Longer periods = more stable, fewer false signals
Range Tolerance (Default: 2.0%)
Tolerance for price touches around exact highs/lows
Lower values = stricter range requirements
Higher values = more flexible range detection
Minimum Touches (Default: 3)
Required number of support/resistance touches for valid range
Higher values = more confirmed ranges, fewer signals
Lower values = more sensitive, earlier detection
Visual Options
Show Range Box: Displays the range boundaries
Show Support/Resistance Lines: Extends levels into the future
Understanding the Output
Range Score (0.000 - 1.000)
0.7+ = Strong Range (Green) - High confidence range trading setup
0.5-0.7 = Moderate Range (Yellow) - Decent range with some caution
0.3-0.5 = Weak Range (Orange) - Low confidence, be careful
<0.3 = Not Ranging - Avoid range trading strategies
Range Status Classifications
Strong Range - Perfect for range trading strategies
Moderate Range - Good range with normal risk
Weak Range - Marginal range, use smaller positions
Not Ranging - Price is trending or too choppy for range trading
Key Metrics in Info Table
Range Size (%) - Size of the range relative to price level
5-15% = Ideal range size for most strategies
<5% = Tight range, lower profit potential
>15% = Wide range, higher profit potential but more risk
Support/Resistance Levels - Exact price levels for entries/exits
Use these as your key trading levels
Support = potential buy zone
Resistance = potential sell zone
Total Touches - Number of times price respected the levels
3-5 touches = Newly formed range
6-10 touches = Well-established range
10+ touches = Very strong, reliable range
Price Position (%) - Current location within the range
0-20% = Near support (potential long opportunity)
80-100% = Near resistance (potential short opportunity)
40-60% = Middle of range (wait for better entry)
Visual Elements
Range Box
Green Box = Strong Range (Score ≥ 0.7)
Yellow Box = Moderate Range (Score 0.5-0.7)
Orange Box = Weak Range (Score 0.3-0.5)
Support/Resistance Lines
- Horizontal lines showing exact trading levels
- Extend into the future for forward guidance
- Colour matches the range strength
Background Colouring
- Subtle background tint during range periods
- Helps quickly identify ranging vs trending markets
Breakout Signals
- 📈 RANGE BREAK UP - Price breaks above resistance
- 📉 RANGE BREAK DOWN - Price breaks below support
- Only appears for confirmed ranges (Score ≥ 0.5)
Trading Applications
Range Trading Strategy
1. Look for Range Score ≥ 0.5
2. Buy near support (Price Position 0-20%)
3. Sell near resistance (Price Position 80-100%)
4. Set stops just outside the range
5. Exit on breakout signals
Breakout Strategy
1. Identify strong ranges (Score ≥ 0.7)
2. Wait for volume-confirmed breakout
3. Enter in breakout direction
4. Use previous resistance as support (or vice versa)
Market Context
- Strong ranges often occur after trending moves
- Use higher timeframes to confirm overall market structure
- Combine with volume analysis for better entries/exits
Best Practices
What to Look For
✅ Range Score ≥ 0.5 for trading consideration
✅ Multiple touches (5+) for confirmation
✅ Clear price rejection at levels
✅ Reasonable range size (5-15% for most assets)
✅ Recent price respect of boundaries
What to Avoid
❌ Trading ranges with Score < 0.3
❌ Very tight ranges (<3% size) - low profit potential
❌ Ranges with only 1-2 touches - not confirmed
❌ Ignoring breakout signals
❌ Trading against the higher timeframe trend
Alerts Available
- Range Detected - New range formation
- Range Break Up - Upward breakout
- Range Break Down - Downward breakout
- Range Ended - Range condition ended
Timeframe Recommendations
- Daily Charts - Best for swing trading ranges
- 4H Charts - Good for intermediate-term ranges
- 1H Charts - Suitable for day trading ranges
- Lower Timeframes - May produce more noise
Conclusion
The Recent Range Detector eliminates guesswork in range identification by providing objective, quantified range analysis. It's particularly valuable for traders who prefer range-bound strategies or need to identify when trending strategies should be avoided.
Remember: No indicator is perfect. Always combine with proper risk management, volume analysis, and broader market context for best results.
Disclaimer
This indicator is for educational purposes only and should not be considered as financial advice. Trading involves risk, and past performance does not guarantee future results. Always conduct your own research and consider your risk tolerance before making any trading decisions.
Ultimate Precision Buy/Sell with SL - Clean Labels FIXThis is a premium indicator designed for traders who demand accuracy, simplicity, and clean visual signals.
✅ Key Features:
📈 Precise Buy/Sell entries based on trend confirmation (EMA) and momentum (RSI)
🛡️ Automatic Stop Loss (SL) drawn for every trade, calculated from ATR
🔄 SL line dynamically moves with each new candle to reflect live action
❗ Only one active signal at a time – no clutter, no repaints
⏱ Optimized for 1H timeframe
💰 Best for Forex pairs, Gold (XAUUSD), Silver (XAGUSD), Platinum (XPTUSD)
🧠 How it works:
Buy Signal: When fast EMA > slow EMA & RSI crosses above 30
Sell Signal: When fast EMA < slow EMA & RSI crosses below 70
A single SL line is drawn per trade and remains until either:
Opposite signal appears, or
SL is hit
⚠️ No repainting. No noise. Just precision.
If you want to trade smart, clean and with confidence – this indicator is built for you.
R Manager PRO++ – Multi-Setup Risk/Reward ToolDescription
The R Manager PRO++ V1.3d is an advanced risk/reward management tool designed for traders who want to visually plan, track, and manage multiple trade setups directly on their charts.
This script allows you to plot up to three independent setups (A, B, and C) simultaneously. For each setup, you can manually input your Entry and Stop Loss levels, and the tool will automatically calculate and display R-multiple levels (1R to 5R), providing a clear overview of your potential profit targets.
Key Features
Multi-Setup Management (A, B, C)
Track up to three separate trades at the same time, each with individual colors and controls.
Manual Entry & Stop Loss Input
Enter your trade levels manually for flexible usage across any market or strategy.
Automatic R-Multiple Calculation (1R to 5R)
The indicator automatically draws lines and labels for 1R to 5R targets based on your risk distance.
Live R Display
Real-time calculation of your current R multiple, updating with every price move.
Custom Symbol Selection
Link each setup to a specific symbol (e.g., EURUSD, XAUUSD, NAS100) to manage multiple markets without clutter.
Reset Function
One-click reset button to quickly clear individual setups.
Alerts for Reached R-Levels
Receive alerts when price reaches each R level (1R to 5R) to monitor trades without constant chart-watching.
How to Use
- Select Entry and Stop Loss levels manually in the input panel.
- Choose the symbol for each setup (supports Forex, Indices, Gold).
- Enable or disable setups individually with the Activate checkbox.
- Optional: Use the Reset button to clear a setup quickly.
- Monitor R-multiples visually and via alerts as price evolves.
Suitable For
- Swing traders
- Day traders
- Risk-based trading strategies (R-multiples)
- Multi-market portfolio management
First Round Break TrackerA simple indicator that tracks the first-time breakouts of round number levels (psychological levels) on any chart. Clean interface with minimal configuration needed
First Breakout Only : Marks each round level only once when broken for the first time
Customizable Step Size : Adjustable round number intervals (e.g., 100, 1000, 10000 etc.)
Clean Visual Alerts : Green labels with "FIRST:" prefix appear exactly at breakout moments
Real-time Info Panel : Shows current price, next target level, and total breakouts count
Suvorov Pro SFP+Indicator: Logic-based Swing Failure Pattern (SFP)
What is the logic of my indicator based on and what makes it unique:
1. The indicator can calculate extreme candles that close with huge shadows and a small body and it works on any timeframe.
2. The indicator analyzes the volumes on which the desired bar was closed. This function is customizable. That is, you can build a search for signals according to your trading strategy, based on the number of volumes. What does this mean - you select the number of previous bars where the indicator calculates the average value and based on these numbers, you can set up: how many times the desired candle should be larger than the previous average volume.
3. Since SFP is based on the removal of important liquidity, the search for such situations occurs from swing structures (swing high/low). When these parameters are found on the chart (on history), the indicator draws the situation and shows where important liquidity was removed and why the trading situation appeared right now.
4. The indicator gives recommendations on possible takes and stops.
The structure of takes has a built-in logic for searching for previous swings to remove liquidity, as well as searching for imbalances to cover them (50 and 100%).
5. For TP (Take Profit): there are 3 TPthat can be adjusted to your trading strategy (Risk/Profit). For example: you always trade from 2 to 1 on the 1st Take, 3 to 1 on the second, 5 to 1 on the third: you can set all this in the indicator and all your targets will be detected by the indicator, taking into account the logic of searching for important ranges. If, for example, in your 3 to 1 range there are no important zones for TP, then the indicator writes that NaN (not found).
6. The indicator works on any timeframe.
7. The indicator has a built-in RSI logic, which comes as an additional function to the indicator. If this function is enabled, then trading situations are detected only when there is a divergence (from the swing point to the extreme bar that has formed).
Compression Patterns (w/ Trend + Proximity Filter)🧠 Description:
This indicator identifies high-probability price compression patterns within trending environments — a setup prized by experienced swing and day traders alike. It combines the classic NR4, NR7, 2-Bar NR, 3-Bar NR, and Inside Day formations with a powerful trend filter and proximity logic to deliver clear, focused signals.
🔍 What's Inside:
▪️ Compression Patterns
The core of this tool lies in the logic of price compression. These patterns signal the market taking a breath — volatility contracts, volume dries up, and price coils like a spring.
When this happens in the right context, the next move is often explosive.
NR4 / NR7: Narrowest range in 4 or 7 bars — excellent for spotting the quiet before the storm.
2-Bar NR / 3-Bar NR: These identify the tightest consecutive 2 or 3-day ranges over the past 20 days — contextually rare and powerful.
Inside Day: A simple but highly effective consolidation pattern, especially when it clusters around key moving averages.
▪️ Trend Filter (EMA Stack)
You could say this is where most indicators fall apart — no context.
This one doesn’t make that mistake.
Signals only fire when the 10 EMA > 20 EMA > 50 EMA, and price is above the 20 EMA. That’s a strong, established uptrend — the only environment where breakouts are statistically favourable.
Why?
Because trend following works.
It may not give you fixed daily returns, but it’s the only strategy with theoretically infinite profit potential. You risk little, trade less, and position yourself for rare but massive moves. That’s the edge.
▪️ Proximity Filter (1 ATR to EMA)
We’ve added another layer of discipline. Signals only fire when price is:
Within 1 ATR of the 10 EMA (if price is above it), or
Within 1 ATR of the 20 EMA (if price is below the 10 EMA)
This ensures you’re not chasing. You’re waiting for tight, controlled pullbacks into dynamic support — exactly where institutions add size, not exit.
⚙️ Fully Customisable:
Toggle visibility of each pattern
Custom colours and transparency for label & background
Adjustable ATR length and multiplier
Change label text if needed (useful for translations or tweaks)
🎯 Ideal Use Case:
Swing trading off the daily chart
Day trading with VWAP/MACD filters (in alternate versions)
Supplementing price action strategies
🔚 Final Word:
This isn’t an “everything scanner.”
It’s a discerning sniper scope for traders who wait patiently for clean trends, tight consolidations, and perfect proximity — then strike.
Triad Macro Gauge__________________________________________________________________________________
Introduction
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The Triad Macro Gauge (TMG) is designed to provide traders with a comprehensive view of the macroeconomic environment impacting financial markets. By synthesizing three critical market signals— VIX (volatility) , Credit Spreads (credit risk) , and the Stocks/Bonds Ratio (SPY/TLT) —this indicator offers a probabilistic assessment of market sentiment, helping traders identify bullish or bearish macro conditions.
Holistic Macro Analysis: Combines three distinct macroeconomic indicators for multi-dimensional insights.
Customization & Flexibility: Adjust weights, thresholds, lookback periods, and visualization styles.
Visual Clarity: Dynamic table, color-coded plots, and anomaly markers for quick interpretation.
Fully Consistent Scores: Identical values across all timeframes (4H, daily, weekly).
Actionable Signals: Clear bull/bear thresholds and volatility spike detection.
Optimized for timeframes ranging from 4 hour to 1 week , the TMG equips swing traders and long-term investors with a robust tool to navigate macroeconomic trends.
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Key Indicators
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VIX (CBOE:VIX): Measures market volatility (negatively weighted for bearish signals).
Credit Spreads (FRED:BAMLH0A0HYM2EY): Tracks high-yield bond spreads (negatively weighted).
Stocks/Bonds Ratio (SPY/TLT): Evaluates equity sentiment relative to treasuries (positively weighted).
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Originality and Purpose
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The TMG stands out by combining VIX, Credit Spreads, and SPY/TLT into a single, cohesive indicator. Its unique strength lies in its fully consistent scores across all timeframes, a critical feature for multi-timeframe analysis.
Purpose: To empower traders with a clear, actionable tool to:
Assess macro conditions
Spot market extremes
Anticipate reversals
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How It Works
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VIX Z-Score: Measures volatility deviations (inverted for bearish signals).
Credit Z-Score: Tracks credit spread deviations (inverted for bearish signals).
Ratio Z-Score: Assesses SPY/TLT strength (positively weighted for bullish signals).
TMG Score: Weighted composite of z-scores (bullish > +0.30, bearish < -0.30).
Anomaly Detection: Identifies extreme volatility spikes (z-score > 3.0).
All calculations are performed using daily data, ensuring that scores remain consistent across all chart timeframes.
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Visualization & Interpretation
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The script visualizes data through:
A dynamic table displaying TMG Score , VIX Z, Credit Z, Ratio Z, and Anomaly status, with color gradients (green for positive, red for negative, gray for neutral/N/A).
A plotted TMG Score in Area, Histogram, or Line mode , with adaptive opacity for clarity.
Bull/Bear thresholds as horizontal lines (+0.30/-0.30) to signal market conditions.
Anomaly markers (orange circles) for volatility spikes.
Crossover signals (triangles) for bull/bear threshold crossings.
The table provides an immediate snapshot of macro conditions, while the plot offers a visual trend analysis. All values are consistent across timeframes, simplifying multi-timeframe analysis.
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Script Parameters
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Extensive customization options:
Symbol Selection: Customize VIX, Credit Spreads, SPY, TLT symbols
Core Parameters: Adjust lookback periods, weights, smoothing
Anomaly Detection: Enable/disable with custom thresholds
Visual Style: Choose display modes and colors
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Conclusion
__________________________________________________________________________________
The Triad Macro Gauge by Ox_kali is a cutting-edge tool for analyzing macroeconomic trends. By integrating VIX, Credit Spreads, and SPY/TLT, TMG provides traders with a clear, consistent, and actionable gauge of market sentiment.
Recommended for: Swing traders and long-term investors seeking to navigate macro-driven markets.
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Credit & Inspiration
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Special thanks to Caleb Franzen for his pioneering work on macroeconomic indicator blends – his research directly inspired the core framework of this tool.
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Notes & Disclaimer
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This is the initial public release (v2.5.9). Future updates may include additional features based on user feedback.
Please note that the Triad Macro Gauge is not a guarantee of future market performance and should be used with proper risk management. Past performance is not indicative of future results.
MTF Fractals [RunRox]🔽 MTF Fractals is a powerful indicator designed to visualize fractals from multiple timeframes directly on your chart, highlight liquidity sweeps at these fractal levels, and provide several additional features we’ll cover in detail below.
We created this indicator because we couldn’t find a suitable tool that met our specific needs on TradingView. Therefore, we decided to develop a valuable indicator for the entire TradingView community, combining simplicity and versatility.
⁉️ WHAT IS A FRACTALS?
In trading, a fractal is a technical analysis pattern composed of five consecutive candles, typically highlighting local market turning points. Specifically, a fractal high is formed when a candle’s high is higher than the highs of the two candles on either side, whereas a fractal low occurs when a candle’s low is lower than the lows of the two adjacent candles on both sides.
Traders use fractals as reference points for identifying significant support and resistance levels, potential reversal areas, and liquidity zones within price action analysis. Below is a screenshot illustrating clearly formed fractals on the chart.
📙 FRACTAL FORMATION
Here’s how fractals form depending on your chosen setting (3, 5, 7, or 9):
▶️ 3-bar fractal – forms when the central candle is higher (for highs) or lower (for lows) than one candle on each side.
▶️ 5-bar fractal – forms when the central candle is higher or lower than two candles on both sides.
▶️ 7-bar fractal – forms when the central candle is higher or lower compared to the three candles on each side.
▶️ 9-bar fractal – forms similarly but requires four candles on each side, making the fractal significantly more reliable and robust.
A higher number of bars ensures stronger fractal levels, highlighting more significant potential reversal points on the chart.
Now that we’ve covered the theory behind fractal formation, let’s explore the indicator’s functionality in more detail.
Below, I’ll explain each feature clearly and illustrate how you can effectively utilize this indicator in your trading.
🕐 MULTI-TIMEFRAME FRACTALS
We realized that displaying fractals only from the current timeframe isn’t always convenient, so we’ve introduced Multi-Timeframe Fractals into this indicator.
Now you can easily display fractals from higher timeframes directly on your current chart, providing you with broader market context and clearer trading signals.
Fractals from Current Timeframe – Fractals identified directly on the chart’s current timeframe.
Fractals from Higher Timeframes – Fractals sourced from higher timeframes and displayed clearly on your current chart for enhanced market perspective.
📈 FRACTAL LINES
Since fractals represent areas of high liquidity, we’ve added an option to extend fractal levels horizontally as Fractal Lines across your chart.
This feature allows you to clearly visualize critical liquidity areas from higher timeframes, directly on your current timeframe chart, as demonstrated in the screenshot below.
With this approach, you can clearly visualize significant fractal levels from higher timeframes directly on your current chart - for example, projecting fractals from the 1-hour (1H) timeframe onto a 3-minute (3m) chart. ✅ This helps you easily identify critical liquidity areas and potential reversal zones without the need to switch between multiple timeframes.
💰 LIQUDITY SWEEP (LIQUDITY GRAB)
To enhance your trading experience, we’ve introduced a feature that clearly identifies liquidity sweeps of fractal levels.
A Liquidity Sweep occurs when a candle closes beyond a fractal line, leaving a wick that pierces through it, signaling that liquidity has been collected at this level.
Below, you’ll find two examples illustrating this functionality:
▶️ Fractal lines from the current timeframe
▶️ Fractal lines projected from higher timeframes
The first example illustrates liquidity being swept from fractals on the current timeframe .
Here, the candle clearly closes beyond the fractal line, leaving a wick through it. This indicates a liquidity sweep at the fractal level, visually highlighting a potential reversal or continuation opportunity directly on your chart.
In the second example, fractals from the higher timeframe are projected onto your current chart.
When a candle on your current timeframe closes beyond an HTF fractal line - leaving a wick through this level - the indicator highlights it clearly. This signals to traders a potential reversal zone, indicating that liquidity has been swept, and price may reverse or significantly react from this area.
You can also enable the display of additional labels on the chart. These labels clearly mark liquidity sweeps at fractal levels, making it easier to visually identify potential reversal points directly on your chart.
⚙️ SETTINGS
Below are the indicator settings with detailed explanations for each parameter.
🔷 Bars in Fractal – Number of candles to the right and left required to form a fractal.
🔷 Fractal Timeframe – Select the timeframe from which you want to display fractals on the current chart.
🔷 Max Age, bars – Number of bars during which the fractal will remain active.
🔷 Show Fractal Line – Display or hide fractal lines.
🔷 Line Style – Choose the style of the line displayed on the chart.
🔷 Line Width – Thickness of the fractal line.
🔷 High Fractal – Style and color of bearish fractals.
🔷 Low Fractal – Style and color of bullish fractals.
🔷 Fractal Label Size – Select the size of fractal labels.
🔷 Show Sweep Labels – Option to display labels when a liquidity sweep occurs.
🔷 Label Color – Color and transparency of the area marked on the chart during a sweep.
🔷 Shade Sweep Area – Show or hide the sweep area shading.
🔷 Area Color – Color and transparency settings for the sweep area.
🔶 We’d love to hear your feedback and any suggestions for additional features you’d like to see in this indicator. We’ll be happy to consider your ideas and continue improving the indicator!
Enhanced Cumulative Volume Delta + MAThe Enhanced Cumulative Volume Delta (CVD) indicator is designed to help traders analyze the cumulative buying and selling pressure in the market by examining the delta between the up and down volume. By tracking this metric, traders can gain insights into the strength of a trend and potential reversals. This indicator uses advanced volume analysis combined with customizable moving averages to provide a more detailed view of market dynamics.
How to Use This Indicator:
Volume Delta Visualization:
The indicator plots the cumulative volume delta (CVD) using color-coded candles, where teal represents positive delta (buying pressure) and soft red represents negative delta (selling pressure).
Moving Averages:
Use the moving averages to smooth the CVD data and identify long-term trends. You can choose between SMA and EMA for each of the three available moving averages. The first and third moving averages are typically used for short-term and long-term trend analysis, respectively, while the second moving average can serve as a medium-term filter.
Arrow Markers:
The indicator will display arrows (green triangle up for crossing above, red triangle down for crossing below) when the CVD volume crosses the 3rd moving average. You can control the visibility of these arrows through the input parameters.
Volume Data:
The indicator provides error handling in case no volume data is available for the selected symbol, ensuring that you're not misled by incomplete data.
Practical Applications:
Trend Confirmation: Use the CVD and moving averages to confirm the overall trend direction and strength. Positive delta and a rising CVD can confirm an uptrend, while negative delta and a falling CVD indicate a downtrend.
Volume Breakouts: The arrows marking when the CVD crosses the 3rd moving average can help you spot potential volume breakouts or reversals, making them useful for entry or exit signals.
Volume Divergence: Pay attention to divergences between price and CVD, as these can often signal potential trend reversals or weakening momentum.
Fibonacci-Only StrategyFibonacci-Only Strategy
This script is a custom trading strategy designed for traders who leverage Fibonacci retracement levels to identify potential trade entries and exits. The strategy is versatile, allowing users to trade across multiple timeframes, with built-in options for dynamic stop loss, trailing stops, and take profit levels.
Key Features:
Custom Fibonacci Levels:
This strategy calculates three specific Fibonacci retracement levels: 19%, 82.56%, and the reverse 19% level. These levels are used to identify potential areas of support and resistance where price reversals or breaks might occur.
The Fibonacci levels are calculated based on the highest and lowest prices within a 100-bar period, making them dynamic and responsive to recent market conditions.
Dynamic Entry Conditions:
Touch Entry: The script enters long or short positions when the price touches specific Fibonacci levels and confirms the move with a bullish (for long) or bearish (for short) candle.
Break Entry (Optional): If the "Use Break Strategy" option is enabled, the script can also enter positions when the price breaks through Fibonacci levels, providing more aggressive entry opportunities.
Stop Loss Management:
The script offers flexible stop loss settings. Users can choose between a fixed percentage stop loss or an ATR-based stop loss, which adjusts based on market volatility.
The ATR (Average True Range) stop loss is multiplied by a user-defined factor, allowing for tailored risk management based on market conditions.
Trailing Stop Mechanism:
The script includes an optional trailing stop feature, which adjusts the stop loss level as the market moves in favor of the trade. This helps lock in profits while allowing the trade to run if the trend continues.
The trailing stop is calculated as a percentage of the difference between the entry price and the current market price.
Multiple Take Profit Levels:
The strategy calculates seven take profit levels, each at incremental percentages above (for long trades) or below (for short trades) the entry price. This allows for gradual profit-taking as the market moves in the trade's favor.
Each take profit level can be customized in terms of the percentage of the position to be closed, providing precise control over exit strategies.
Strategy Backtesting and Results:
Realistic Backtesting:
The script has been backtested with realistic account sizes, commission rates, and slippage settings to ensure that the results are applicable to actual trading scenarios.
The backtesting covers various timeframes and markets to ensure the strategy's robustness across different trading environments.
Default Settings:
The script is published with default settings that have been optimized for general use. These settings include a 15-minute timeframe, a 1.0% stop loss, a 2.0 ATR multiplier for stop loss, and a 1.5% trailing stop.
Users can adjust these settings to better fit their specific trading style or the market they are trading.
How It Works:
Long Entry Conditions:
The strategy enters a long position when the price touches the 19% Fibonacci level (from high to low) or the reverse 19% level (from low to high) and confirms the move with a bullish candle.
If the "Use Break Strategy" option is enabled, the script will also enter a long position when the price breaks below the 19% Fibonacci level and then moves back up, confirming the break with a bullish candle.
Short Entry Conditions:
The strategy enters a short position when the price touches the 82.56% Fibonacci level and confirms the move with a bearish candle.
If the "Use Break Strategy" option is enabled, the script will also enter a short position when the price breaks above the 82.56% Fibonacci level and then moves back down, confirming the break with a bearish candle.
Stop Loss and Take Profit Logic:
The stop loss for each trade is calculated based on the selected method (fixed percentage or ATR-based). The strategy then manages the trade by either trailing the stop or taking profit at predefined levels.
The take profit levels are set at increments of 0.5% above or below the entry price, depending on whether the position is long or short. The script gradually exits the trade as these levels are hit, securing profits while minimizing risk.
Usage:
For Fibonacci Traders:
This script is ideal for traders who rely on Fibonacci retracement levels to find potential trade entries and exits. The script automates the process, allowing traders to focus on market analysis and decision-making.
For Trend and Swing Traders:
The strategy's flexibility in handling both touch and break entries makes it suitable for trend-following and swing trading strategies. The multiple take profit levels allow traders to capture profits in trending markets while managing risk.
Important Notes:
Originality: This script uniquely combines Fibonacci retracement levels with dynamic stop loss management and multiple take profit levels. It is not just a combination of existing indicators but a thoughtful integration designed to enhance trading performance.
Disclaimer: Trading involves risk, and it is crucial to test this script in a demo account or through backtesting before applying it to live trading. Users should ensure that the settings align with their individual risk tolerance and trading strategy.
Swing Algo V1.4◆ Introduction
The latest version of the Swing Algo features a complementary system consisting of two internal swing trading logics: an enhanced Swing Algo V1.3 and a secondary control engine to stabilize the overall strategy behaviour in times of increased market chop. Both algorithms feature different averaging lines as well as oscillators, leading to a higher strategy diversification for swing trading as well as a reduced maximum drawdown in comparison to each stand-alone strategy.
While the Swing Algo V1.x series so far featured a single trend-following swing algorithm for each release, where one just switches between Long and Short trades based on one general logic, here two strategies, which act independently of each other, are applied. Due to this, we introduce a third position a trader can be in: the Hedge. The overall logic is as follows:
When both sub-logics are Long, the overall strategy is Long.
When both sub-logics are Short, the overall strategy is Short.
When one sub-logic is Long and the other is Short, the overall strategy is in a Hedge position. It doesn't matter which component is Short and which is Long.
As PineScript doesn't currently offer a real steady hedging-function for two competing swing trading sub-logics (in the sense of a continuously applied Hedge state after hedging conditions are met at least once for an entry), a workaround via position closes was created for this release. For each new internal sub-signal, the overall strategy changes its state (Long/Short/Hedge) visibly on the chart, and the trader can adjust their position accordingly.
For detailed differences to previous Swing Algo V1.x releases, see further below.
◆ Purpose of this Script
This indicator will give Long, Short and Hedge signals on the chart that can be used for e.g. swing trading. Each of the aforementioned sub-logics uses a combination of several (custom) functions and rules to find good entry points for trend trading. After many iterations and tests I came up with this particular setup, which is highly optimized for the ETH/USD trading pair on the daily (D) timeframe.
Attention was also paid to stability, as all parameters are set onto plateaus, so that smaller changes in the characteristic price action should not affect the efficiancy too much, done as an attempt to reduce overfitting as much as possible. Additionally this dual algorithm system is specifically designed to have a safety net: should for the unlikely scenario one swing trading algorithm not trigger at a certain mid-term reversal point, the probability is high that the other will trigger, resulting in an overall hedged position (so that no money is lost in the meantime) until the first algorithm can rejoin at the next mid-term trend change.
For other assets and/or timeframes it is in principle possible to change algorithmic parameters within the indicator settings to tune the swing algorithms, though it is strongly recommended to use the standard asset and timeframe mentioned above.
◆ Viability
For the here presented backtest data, we omitted the biggest portion of the cryptocurrency bullrun in 2017 (starting only at 1st July 2017) so that the results become more realistic for long-term swing traders (investing at least 2-4 years into trading) if such large runs do not happen again. As cryptocurrencies like Ethereum are still to this date capable of doing comparatively smaller runs of about 2-3x in a few weeks/months during accumulation phases (as witnessed e.g. in 2020 and more recently in 2023) and bigger runs during bullmarkets (as witnessed in 2021), the quality of the shown results is still realistic for long-term trend trading efforts over several years, Note that very conservative trading parameters as mentioned below in "Forwardtesting and Backtesting" are used here.
Generally do not expect results in a matter of days or weeks, and of course as with any trading strategy past performances are not indicative of future results.
◆ Forwardtesting and Backtesting
The individual components have been back- and partially forwardtested: The first sub-logic is an advancement of Swing Algo V1.3, with which we have extensive experience running back to October 2020 for its release, while the secondary control strategy, which was privately published for DeanTrader members as a stand-alone script on TradingView in June 2022 and was running in the background since then, is showing good & expected behaviour so far.
While this does not mean that fowardtesting was performed specifically for the combined Swing Algo V1.4 system we have now (which cannot be done realistically considering the timeframes used, i.e. months and especially years), we can at least look at some considerable experience with the individual components. Then again, as I have implemented an exact hedging-function so that both sub-algorithms run independently from each other, it is not likely to see any unexpected behaviour resulting purely from the combination into one script.
For strategy backtesting you can choose the backtest time interval to test the performance of this algorithm for different time windows and different trading pairs. Here various backtesting parameters (e.g. trading fees) can be customized. Default settings for the shown backtest are a starting balance of $1000, a slippage of 20 ticks (= $0.20) and a trading fee of 0.05 % (which is the worst taker fee on the Kraken Pro futures exchange) to have realistic settings. However as we do not conduct many trades with this strategy, fees should not impact our performance too much. As long-term swing traders, we at DeanTrader generally devote one initial portion of our portfolio to swing trading and from then on always use 100% of this portion for the next trade to get the compounding starting. This is in difference to other trading styles which use various, often very small, percentage values for their short- or mid-term trades. Please note that for the here presented backtest only 10% of compounded equity is used for each successive trade to show an estimation for a lower risk & lower reward approach . Keep this in mind when evaluating the backtest data. You can set appropriate values for each backtest parameter in the "Properties" setting menu of the strategy, including the order size percentage of equity value for your trades. Also note that due to the small number of trades the statistical significance is low. It is not possible to gather an abundance of long-term trend signals in the order of hundreds or thousands trades, as much more time would have to pass for this in the case of rather new assets like Ethereum.
Additionally to the TradingView Strategy Tester you can also plot your equity directly on the chart to get a sense for the performance. For this you can also scale the equity graph to e.g. match the starting point of your equity with some price point on the chart to get a direct comparison to 'Buy & Hold' strategies over time.
This indicator (and all other content I provide) is no financial advice. If you use this indicator you agree to my Terms and Conditions which can be found on my website linked on my TradingView profile or in my signature.
◆ Visual Representation on the Chart
Shown below is a screenshot of how the chart looks like when the strategy is applied. Here we can see two different averaging lines, where each line belongs to one of the two sub-logics respectively. Note that this is not a MA-crossover strategy, and the crossing of the lines is not accounted for in the code at all and therefore has no effect on the strategy's signal output. Also note that the price scale is set on logarithmic.
The space between the lines is filled with a faint background color as a rough visual indicator. Magenta-colored fills indicate zones where only Short or Hedge signals can appear, while green-colored fills indicate zones where only Long or Hedge signals can appear. Gray-colored fills mark zones where only Hedge signals can appear, which also means that Hedge signals can appear in any zone. So treat those background fills more as a visual aid to roughly know what can happen next, but pay most attention to the actual signals (with arrows) that appear on the chart.
◆ Differences to Other Versions
Consists now of two competing sub-algorithms instead of just one algorithm. The new system outputs Long, Short and Hedge signals instead of just Long and Short signals.
The first sub-logic is the spiritual successor of the original Swing Algo V1.3 release, with a modified oscillator part.
The second sub-logic serves as a control algorithm (while still having equal rights in terms of strategy impact), newly introduced to the Swing Algo series, but already forwardtested for roughly a year at time of release.
Lowers risk significantly by diversifying swing trading strategies, so that for the rare scenario of a missed trend on one sub-algorithm, losses are prevented as the overall strategy is hedged during that time.
Lowers risk further as the maximum drawdown of the combined strategy is reduced by roughly 1/3 in comparison to each stand-alone strategy while almost retaining the same net profit over a 6-year backtest compared to the first, leading sub-logic.
No guesswork anymore when to use which short leverage (1x corresponding to a Hedge, or 2x corresponding to a Short with an asset-value-change-to-gain-proportionality of -1) as it is clearly defined within the trading system via the displayed signals. In earlier Swing Algo versions, the short leverage for any particular Short signal had to be chosen by hand dependent on market sentiment, which required further market analysis, or was fixed at 2x, leading to less flexibility.
◆ Access
For access please contact me via DM on TradingView or via other channels (linked on my TradingView profile and in my signature).
Damage Indicator by Scipio ProScipio Pro's Damage Indicator detects strong momentum on tops and bottoms. It is intended for swing trading.
The script analyzes both recent and less-recent price action and performs candle stick analysis. It also uses SDs and multiple Bollinger Bands to find dynamic levels for entries.
A Bears Damaged signal emerges whenever there is convincing proof of strength at a bottom. Often, when the market reverses quickly, traders are caught offside and are forced to buy higher. The reverse goes for Bulls Damaged signals, which mean there is convincing proof of bearish strength at a (local?) top.
Whether the move gets legs depends in large part on the structure in which the show of momentum takes place. It is sensible to wonder after each signal whether the market structure (and other relevant context such as the majority of cash having been sidelined) dictates that risk-reward is skewed to the upside or to the downside. If, for example, a Bears Damaged signal emerges on the daily and risk-reward on the weekly is skewed to the upside, go 4x larger (again, just an example). If, on the other hand, the same signal emerges on the daily while the risk-reward is skewed to the downside on the weekly, bet much smaller and tighten your stop-loss. For best results, I suggest you always check one timeframe higher for your long-term risk-reward bias. (No financial advice, of course.)
Under Settings you'll find the so-called Noise Protection , which is switched "on" by default. We recommend you keep this switched on. Noise Protection ensures you do not see Damage signals on timeframes lower than the 4 hour. After all, chasing momentum on low timeframes is a losing game. The amount of noise increases exponentially as you move lower down the timeframes. Again, this indicator is for swing trades. Don't use it for scalping.
It should be useful for all assets, but is of course more useful on some than on others. As with all indicators, signals tend to be more meaningful if the asset in question is at least somewhat liquid, for instance.
As always, use at your own risk. Using indicators is no substitute for using one's brain.
Theory Affinity TrendlinesThis indicator is perfect for traders who want to identify trend lines on a chart. It draws higher low uptrends and lower high downtrends, making it easy to see where the trend is going. You can also customize the settings to fit your needs, making it the perfect tool for your trading arsenal.
With this new tool, you can easily customize your experience to get the most out of your trading and analysis. With options like max lines, strength multiplier, pivot plots/text, and more, you can easily create the perfect trading analysis environment.
So why wait? Try it out today!
Leave feedback and let me know what you think.
// ############################################################################################## Input Descriptions
Pivot Left ----------------- look left n bars
Pivot Right ---------------- look right n bars
Strength ------------------- Pivot multiplier (Higher = Wider Trend lines)
Max Lines ------------------ Number of lines for each Uptrend and Downtrend
Structure Text ------------ Show HH, LL, etc. on chart
Structure Markers -------- Dots at the Pivot Highs and Lows
Plots ------------------------ Draw a line at Pivot Highs and Lows
Last Up Width ------------- Width of the current Uptrend line
Historical Up Width ------ Width of previous Uptrend lines
Last Down Width --------- Width of the current Downtrend lines
Historical Down Width --- Width of previous Downtrend lines
Line Offset ---------------- Shift trend lines right or left
* Lines may or may not "repaint". For use to identify trends that are more than likely already established and to identify trend line breaks.
v1 Swing TradeHello friends
I have completed the "Swing Trading" Indicator that I have been working on for a long time.
I would like to briefly explain what it does and how it works.
Cryptocurrency Markets have high volatility. Of course, money is made by holding, but we are aware that there are more opportunities in the market as the ebb and flow. I must underline that it is "SMALL" by taking small risks to seize this opportunity. This indicator, which will help us to turn these opportunities to our advantage by taking small risks, briefly works as follows.
It is a blend of 1 indicator, which is based on fibonacci and pivot points, and supports atr indicator data in the background.
I determined the important values of Fibonnaci as entry and exit points. I then completed it with the atr indicator. atr fibonacci automatically pulls the walking graph invisibly.
This data is automatically mixed with the atr indicator.
When the price candles rise above the atr band, the long entry of the entry price comes. immediately after, the stop loss level is set “SMALL”.
Likewise, at the end of 1 Rising Trend, Stuck Prices Will Correct. When the price candles fall below the Atr Band, a short signal comes. and then a "SMALL" Stoploss level is determined together with the entry price.
After entering the position, the following stoploss and take profit work. ( Moves with the Trend, Stop Price Does Not Slip In The Opposite Direction After The First Entry. )
If the trade turns into profit after the stop loss level you entered, you should move your stop loss level together with the algorithm and exit the trade with minimum loss and maximum profit.
Trailing Stoploss
Now it's time to close the position. Price started to shrink. Swing trading Opportunity May Come.
What should the user pay attention to ?
Signal should be expected as in the first image.
When entering the trade, you should definitely put a stoploss.
If the Trade Opportunity is Late, the Transaction should not be entered.
And most importantly, you should carry your stoploss level with the algorithm.
Matters to be Considered in the Settings Tab;
Candles to lookback ( Do not reduce the number of past candles below 50.)
Reverse Target Point ( Definitely Must Stay Active. Don't turn it off.)
Formula a and formula b values increase the signal rate. But Too Many Signals Are Not Healthy.
I wish everyone a lot of earnings.
CuandoCrypto's Swing Trade IndicatorThis indicator combines RSI, MACD, Williams %R and Z-Score to determine if there's a high probability of an imminent trend reversal. This indicator is best used on higher timeframes.
AYN: Buy-, Sell-, Trend- and SwingSignals incl. AutoFibo
Hi,
i want to introduce you to my AllYouNeed-Indicator. I calculate the buy sell signals within different timeframes independent in wich timeframe you are, therefore Pinescript suppose the Signal could be repainted. I was not able to fix this error, but after frequent checks of the result i haven't found a single repaint. Please try it out and let me know me, if you still get caught by a repaint.
Features:
- Short, Mid and Longterm-Trends
- Buy and Sell Signals and Results as well with Labels (Prices, Percentage, Win/Lose)
- Length Multiplier for different Marketsituations
- Trend-Signals with Barcolors (Lime=Uptrend, Fuchsia=Downtrend)
- Swing-Signals with Barcolors (Lime=Upswing, Orange=Downswing)
- Auto-Fibonacci with changing Linecolors as Support(green) / Resistance(red)
Hope you like it, feel free to contact me for further informations.
Please leave a comment on what I can do better, thanks.
Best regards,
snurk
