Breakout Reversal Entry on WMA - NG1! Overnight ver 1This script is for learning purposes only
This strategy will plot arrows when price breaks so far above/below WMA. The strategy will enter when the price breaks away from WMA. All entries are reversals. Users can set WMA length and source; also the distance of the price away from WMA to enter. Adjustable bracket orders are placed for exit, with trailing stop or market stop choice. Last, users can set the time of day they want to enter a trade.
My Preference: I am testing this strategy on NG1! over night on 1 minute candle. with .003 on price drop/climb, I get entries almost every night. Also 10 tick stop and 5 tick profit seems backward to most, but with a high win/loss ratio, it performs quite well. Trailing stops generally help out as well.
INPUTS:
Length - The is the WMA length
Source - WMA source (High, Low, Open, Close...)
When Price Drops - This is the distance in ticks when the price drops away from WMA, an arrow is plotted, and reversal entry order is placed
When Price Climbs - Same as price drop, just in the opposite direction
Trailing Stop check box - Check if you want to place a trailing stop so many tick away from entry. Unchecked is Market (hard) stop so many ticks from entry.
Stop - Number of ticks away from entry a the stop or trailing stop is set (for NG 1 tick = $0.001)
Limit Out - Number of ticks away from entry a limit order is placed to take profits
Limit Time of day check box - check to use the time of day to limit what time of day order entry will occur.
Start/Stop Trades (Est Time) - First box is when the strategy will be allowed to start buying and stop is when the strategy will stop being allowed to buy. Sell orders continue until a stop or limit triggers an exit. These times are Eastern time zone
PROPERTIES:
Pyramiding - This feature will allow multiple entries to occur. If set to 1, the strategy should only trade 1 contract at a time. If set to 2, the strategy will enter a second order if entry requirements are met. This allows you to be holding 2 contracts. Basically on a good day, it will multiply your earnings, on a bad day, you'll just lose more. For testing, I keep this on 1.
TIPS:
- If you want to go long only, set "When Price Climbs" to an impossible number, like 10,000. It's not possible for NG to move $10 is a matter of minutes so it will not enter the market with a short order. Also keep in mind you can set different requirements for going long vs going short. If you think there is more pull on the market in a particular direction.
Pesquisar nos scripts por "文华财经tick价格"
Acc/Dist. Cloud with Fractal Deviation Bands by @XeL_ArjonaACCUMULATION / DISTRIBUTION CLOUD with MORPHIC DEVIATION BANDS
Ver. 2.0.beta.23:08:2015
by Ricardo M. Arjona @XeL_Arjona
DISCLAIMER
The Following indicator/code IS NOT intended to be a formal investment advice or recommendation by the author, nor should be construed as such. Users will be fully responsible by their use regarding their own trading vehicles/assets.
The embedded code and ideas within this work are FREELY AND PUBLICLY available on the Web for NON LUCRATIVE ACTIVITIES and must remain as is.
Pine Script code MOD's and adaptations by @XeL_Arjona with special mention in regard of:
Buy (Bull) and Sell (Bear) "Power Balance Algorithm by Vadim Gimelfarb published at Stocks & Commodities V. 21:10 (68-72).
Custom Weighting Coefficient for Exponential Moving Average (nEMA) adaptation work by @XeL_Arjona with contribution help from @RicardoSantos at TradingView @pinescript chat room.
Morphic Numbers (PHI & Plastic) Pine Script adaptation from it's algebraic generation formulas by @XeL_Arjona
Fractal Deviation Bands idea by @XeL_Arjona
CHANGE LOG:
ACCUMULATION / DISTRIBUTION CLOUD: I decided to change it's name from the Buy to Sell Pressure. The code is essentially the same as older versions and they are the center core (VORTEX?) of all derived New stuff which are:
MORPHIC NUMBERS: The "Golden Ratio" expressed by the result of the constant "PHI" and the newer and same in characteristics "Plastic Number" expressed as "PN". For more information about this regard take a look at: HERE!
CUSTOM(K) EXPONENTIAL MOVING AVERAGE: Some code has cleaned from last version to include as custom function the nEMA , which use an additional input (K) to customise the way the "exponentially" is weighted from the custom array. For the purpose of this indicator, I implement a volatility algorithm using the Average True Range of last 9 periods multiplied by the morphic number used in the fractal study. (Golden Ratio as default) The result is very similar in response to classic EMA but tend to accelerate or decelerate much more responsive with wider bars presented in trending average.
FRACTAL DEVIATION BANDS: The main idea is based on the so useful Standard Deviation process to create Bands in favor of a multiplier (As John Bollinger used in it's own bands) from a custom array, in which for this case is the "Volume Pressure Moving Average" as the main Vortex for the "Fractallitly", so then apply as many "Child bands" using the older one as the new calculation array using the same morphic constant as multiplier (Like Fibonacci but with other approach rather than %ratios). Results are AWSOME! Market tend to accelerate or decelerate their Trend in favor of a Fractal approach. This bands try to catch them, so please experiment and feedback me your own observations.
EXTERNAL TICKER FOR VOLUME DATA: I Added a way to input volume data for this kind of study from external tickers. This is just a quicky-hack given that currently TradingView is not adding Volume to their Indexes so; maybe this is temporary by now. It seems that this part of the code is conflicting with intraday timeframes, so You are advised.
This CODE is versioned as BETA FOR TESTING PROPOSES. By now TradingView Admins are changing lot's of things internally, so maybe this could conflict with correct rendering of this study with special tickers or timeframes. I will try to code by itself just the core parts of this study in order to use them at discretion in other areas. ALL NEW IDEAS OR MODIFICATIONS to these indicator(s) are Welcome in favor to deploy a better and more accurate readings. I will be very glad to be notified at Twitter or TradingView accounts at: @XeL_Arjona
Small-Cap — Sell Every Spike (Rendon1) Small-Cap — Sell Every Spike v6 — Strict, No Look-Ahead
Educational use only. This is not financial advice or a signal service.
This strategy targets low/ mid-float runners (≤ ~20M) that make parabolic spikes. It shorts qualified spikes and scales out into flushes. Logic is deliberately simple and transparent to avoid curve-fit.
What the strategy does
Detects a parabolic up move using:
Fast ROC over N bars
Big range vs ATR
Volume spike vs SMA
Fresh higher high (no stale spikes)
Enters short at bar close when conditions are met (no same-bar fills).
Manages exits with ATR targets and optional % covers.
Tracks float rotation intraday (manual float input) and blocks trades above a hard limit.
Draws daily spike-high resistance from confirmed daily bars (no repaint / no look-ahead).
Timeframes & market
Designed for 1–5 minute charts.
Intended for US small-caps; turn Premarket on.
Works intraday; avoid illiquid tickers or names with constant halts.
Entry, Exit, Risk (short side)
Entry: parabolic spike (ROC + Range≥ATR×K + Vol≥SMA×K, new HH).
Optional confirmations (OFF by default to “sell every spike”): upper-wick and VWAP cross-down.
Stop: ATR stop above entry (default 1.2× ATR).
Targets: TP1 = 1.0× ATR, TP2 = 2.0× ATR + optional 10/20/30% covers.
Safety: skip trades if RVOL is low or Float Rotation exceeds your limit (default warn 5×, hard 7×).
Inputs (Balanced defaults)
Price band: $2–$10
Float Shares: set per ticker (from Finviz).
RVOL(50) ≥ 1.5×
ROC(5) ≥ 1.0%, Range ≥ 1.6× ATR, Vol ≥ 1.8× SMA
Cooldown: 10 bars; Max trades/day: 6
Optional: Require wick (≥35%) and/or Require VWAP cross-down.
Presets suggestion:
• Balanced (defaults above)
• Safer: wick+VWAP ON, Range≥1.8×, trades/day 3–4
• Micro-float (<5M): ROC 1.4–1.8%, Range≥1.9–2.2×, Vol≥2.2×, RVOL≥2.0, wick 40–50%
No look-ahead / repaint notes
Daily spike-highs use request.security(..., lookahead_off) and shifted → only closed daily bars.
Orders arm next bar after entry; entries execute at bar close.
VWAP/ATR/ROC/Vol/RVOL are computed on the chart timeframe (no HTF peeking).
How to use
Build a watchlist: Float <20M, RelVol >2, Today +20% (Finviz).
Open 1–5m chart, enter Float Shares for the ticker.
Start with Balanced, flip to Safer on halty/SSR names or repeated VWAP reclaims.
Scale out into flushes; respect the stop and rotation guard.
Limitations & risk
Backtests on small-caps can be optimistic due to slippage, spreads, halts, SSR, and limited premarket data. Always use conservative sizing. Low-float stocks can squeeze violently.
Alerts
Parabolic UP (candidate short)
SHORT Armed (conditions met; entry at bar close)
RTH Levels: VWAP + PDH/PDL + ONH/ONL + IBAlgo Index — Levels Pro (ONH/ONL • PDH/PDL • VWAP±Bands • IB • Gaps)
Purpose. A session-aware, non-repainting levels tool for intraday decision-making. Designed for futures and indices, with clean visuals, alerts, and a one-click Minimal Mode for screenshot-ready charts.
What it plots
• PDH/PDL (RTH-only) – Prior Regular Trading Hours high/low, computed intraday and frozen at the RTH close (no 24h mix-ups, no repainting).
• ONH/ONL – Prior Overnight high/low, held throughout RTH.
• RTH VWAP with ±σ bands – Volume-weighted variance, reset each RTH.
• Initial Balance (IB) – First N minutes of RTH, plus 1.5× / 2.0× extensions after IB completes.
• Today’s RTH Open & Prior RTH Close – With gap detection and “gap filled” alert.
• Killzone shading – NY Open (09:30–10:30 ET) and Lunch (11:15–13:30 ET).
• Values panel (top-right) – Each level with live distance in points & ticks.
• Right-edge level tags – With anti-overlap (stagger + vertical jitter).
• Price-scale tags – Native trackprice markers that always “stick” to the axis.
⸻
New in v6.4
• Minimal Mode: one click for a clean look (thinner lines, VWAP bands/IB extensions hidden, on-chart right-edge labels off; price-scale tags remain).
• Theme presets: Dark Hi-Contrast / Light Minimal / Futures Classic / Muted Dark.
• Anti-overlap controls: horizontal staggering, vertical jitter, and baseline offset to keep tags readable even when levels cluster.
⸻
Quick start (2 minutes)
1. Add to chart → keep defaults.
2. Sessions (ET):
• RTH Session default: 09:30–16:00 (US equities cash hours).
• Overnight Session default: 18:00–09:29.
Adjust for your market if you use different “day” hours (e.g., many use 08:20–13:30 ET for COMEX Gold).
3. Theme & Minimal Mode: pick a Theme Preset; enable Minimal Mode for screenshots.
4. Visibility: toggle PD/ON/VWAP/IB/References/Panel to taste.
5. Right-edge labels: turn Show Right-Edge Labels on. If they crowd, tune:
• Anti-overlap: min separation (ticks)
• Horizontal offset per tag (bars)
• Vertical jitter per step (ticks)
• Right-edge baseline offset (bars)
6. Alerts: open Add alert → Condition: and pick the events you want.
⸻
How levels are computed (no repainting)
• PDH/PDL: Intraday H/L are accumulated only while in RTH and saved at RTH close for “yesterday’s” values.
• ONH/ONL: Accumulated across the defined Overnight window and then held during RTH.
• RTH VWAP & ±σ: Volume-weighted mean and standard deviation, reset at the RTH open.
• IB: First N minutes of RTH (default 60). Extensions (1.5×/2.0×) appear after IB completes.
• Gaps: Today’s RTH open vs prior RTH close; “Gap Filled” triggers when price trades back to prior close.
⸻
Practical playbooks (how to trade around the levels)
1) PDH/PDL interactions
• Rejection: Price taps PDH/PDL then closes back inside → mean-reversion toward VWAP/IB.
• Acceptance: Close/hold beyond PDH/PDL with momentum → continuation to next HTF/IB target.
• Alert: PD Touch/Break.
2) ONH/ONL “taken”
• Often one ON extreme is taken during RTH. ONH Taken / ONL Taken → check if it’s a clean break or sweep & reclaim.
• Sweep + reclaim near VWAP can fuel rotations through the ON range.
3) VWAP ±σ framework
• Balanced: First tag of ±1σ often reverts toward VWAP.
• Trend: Persistent trade beyond ±1σ + IB break → target ±2σ/±3σ.
• Alerts: VWAP Cross and VWAP Reject (cross then immediate fail back).
4) IB breaks
• After IB completes, a clean IB break commonly targets 1.5× and sometimes 2.0×.
• Quick return inside IB = possible fade back to the opposite IB edge/VWAP.
• Alerts: IB Break Up / Down.
5) Gaps
• Gap-and-go: Opening drive away from prior close + VWAP support → trend until IB completion.
• Gap-fill: Weak open and VWAP overhead/underfoot → trade toward prior close; manage on Gap Filled alert.
Pro tip: Stack confluences (e.g., ONL sweep + VWAP reclaim + IB hold) and respect your execution rules (e.g., require a 5-minute close in direction, or your order-flow confirmation).
⸻
Inputs you’ll actually touch
• Sessions (ET): Session Timezone, RTH Session, Overnight Session.
• Visibility: toggles for PD/ON/VWAP/IB/Ref/Panel.
• VWAP bands: set σ multipliers (±1/±2/±3).
• IB: duration (minutes) and extension multipliers (1.5× / 2.0×).
• Style & Theme: Theme Preset, Main Line Width, Trackprice, Minimal Mode, and anti-overlap controls.
⸻
Alerts included
• PD Touch/Break — High ≥ PDH or Low ≤ PDL
• ONH Taken / ONL Taken — First in-RTH take of ONH/ONL
• VWAP Cross — Close crosses VWAP
• VWAP Reject — Cross then immediate fail back
• IB Break Up / Down — Break of IB High/Low after IB completes
• Gap Filled — Price trades back to prior RTH close
Setup: Add alert → Condition: Algo Index — Levels Pro → choose event → message → Notify on app/email.
⸻
Panel guide
The top-right panel shows each level plus live distance from last price:
LevelValue (Δpoints | Δticks)
Coloring: green if level is below current price, red if above.
⸻
Styling & screenshot tips
• Use Theme Preset that matches your chart.
• For dark charts, “Dark Hi-Contrast” with Main Line Width = 3 works well.
• Enable Trackprice for crisp axis tags that always stick to the right edge.
• Turn on Minimal Mode for cleaner screenshots (no VWAP bands or IB extensions, on-chart tags off; price-scale tags remain).
• If tags crowd, increase min separation (ticks) to 30–60 and horizontal offset to 3–5; add vertical jitter (4–12 ticks) and/or push tags farther right with baseline offset (bars).
⸻
Behavior & limitations
• Levels are computed incrementally; tables refresh on the last bar for efficiency.
• Right-edge labels are placed at bar_index + offset and do not track extra right-margin scrolling (TradingView limitation). The price-scale tags (from trackprice) do track the axis.
• “RTH” is what you define in inputs. If your market uses different day hours, change the session strings so PDH/PDL reflect your definition of “yesterday’s session.”
⸻
FAQ
Q: My PDH/PDL don’t match the daily chart.
A: By design this uses RTH-only highs/lows, not 24h daily bars. Adjust sessions if you want a different definition.
Q: Right-edge tags overlap or don’t sit at the far right.
A: Increase min separation / horizontal offset / vertical jitter and/or push tags farther with baseline offset. If you want markers that always hug the axis, rely on Trackprice.
Q: Can I change killzones?
A: Yes—edit the session strings in settings or request a version with user inputs for custom windows.
⸻
Disclaimer
Educational use only. This is not financial advice. Always apply your own risk management and confirmation rules.
⸻
Enjoy it? Please ⭐ the script and share screenshots using Minimal Mode + a Theme Preset that fits your style.
Frahm FactorIntended Usage of the Frahm Factor Indicator
The Frahm Factor is designed to give you a rapid, at-a-glance assessment of how volatile the market is right now—and how large the average candle has been—over the most recent 24-hour window. Here’s how to put it to work:
Gauge Volatility Regimes
Volatility Score (1–10)
A low score (1–3, green) signals calm seas—tight ranges, low risk of big moves.
A mid score (4–6, yellow) warns you that volatility is picking up.
A high score (7–10, red) tells you to prepare for disorderly swings or breakout opportunities.
How to trade off it
In low-volatility periods, you might favor mean-reversion or range-bound strategies.
As the score climbs into the red zone, consider widening stops, scaling back position size, or switching to breakout momentum plays.
Monitor Average Candle Size
Avg Candle (ticks) cell shows you the mean true-range of each bar over that 24h window in ticks.
When candles are small, you know the market is consolidating and liquidity may be thin.
When candles are large, momentum and volume are driving strong directional bias.
The optional dynamic color ramp (green→yellow→red) immediately flags when average bar size is unusually small or large versus its own 24h history.
Customize & Stay Flexible
Timeframes: Works on any intraday chart—from 1-minute scalping to 4-hour swing setups—because it always looks back exactly 24 hours.
Toggles:
Show or hide the Volatility and Avg-Candle cells to keep your screen uncluttered.
Turn on the dynamic color ramp only when you want that extra visual cue.
Alerts: Built-in alerts fire automatically at meaningful thresholds (Volatility ≥ 8 or ≤ 3), so you’ll never miss regime shifts, even if you step away.
Real-World Applications
Risk Management: Automatically adjust your stop-loss distances or position sizing based on the current volatility band.
Strategy Selection: Flip between range-trading and momentum strategies as the volatility regime changes.
Session Analysis: Pinpoint when during the day volatility typically ramps—perfect for doorway sessions like London opening or the US midday news spikes.
Bottom line: the Frahm Factor gives you one compact dashboard to see the pulse of the market—so you can make choices with conviction, dial your risk in real time, and never be caught off guard by sudden volatility shifts.
Logic Behind the Frahm Factor Indicator
24-Hour Rolling Window
On every intraday bar, we append that bar’s True Range (TR) and timestamp to two arrays.
We then prune any entries older than 24 hours, so the arrays always reflect exactly the last day of data.
Volatility Score (1–10)
We count how many of those 24 h TR values are less than or equal to the current bar’s TR.
Dividing by the total array size gives a percentile (0–1), which we scale and round into a 1–10 score.
Average Candle Size (ticks)
We sum all TR values in the same 24 h window, divide by array length to get the mean TR, then convert that price range into ticks.
Optionally, a green→yellow→red ramp highlights when average bar size is unusually small, medium or large versus its own 24 h history.
Color & Alerts
The Volatility cell flips green (1–3), yellow (4–6) or red (7–10) so you see regime shifts at a glance.
Built-in alertcondition calls fire when the score crosses your high (≥ 8) or low (≤ 3) thresholds.
Modularity
Everything—table location, which cells to show, dynamic coloring—is controlled by simple toggles, so you can strip it back or layer on extra visual cues as needed.
That’s the full recipe: a true 24 h look-back, a percentile-ranked volatility gauge, and a mean-bar-size meter, all wrapped into one compact dashboard.
Candle Range-BarsThe Candle Range Bars indicator visually represents the range of each candlestick in either pips or ticks, depending on your preference. It plots vertical bars to show the size of each candle, making it easy to identify periods of high or low volatility. The indicator also displays the exact range value (in pips or ticks) above each bar, with customizable text size and color for better readability.
Key Features
Pips or Ticks Mode:
Choose to display the candle range in pips (for forex traders) or ticks (for other instruments).
Customizable Text:
Adjust the text color and text size (Tiny, Small, Normal, Large) to suit your chart style.
Clear Visuals:
Bars are colored green for bullish candles and red for bearish candles, making it easy to distinguish between up and down moves.
Flexible Use:
Ideal for analyzing volatility, identifying consolidation zones, and comparing candle ranges across different timeframes.
How to Use:
Add the indicator to your chart.
Customize the settings:
Choose between pips or ticks.
Adjust the text color and text size for the range values.
Observe the bars and their corresponding range values to analyze market volatility.
Why Use This Indicator?:
Simplify Range Analysis: Quickly see the size of each candlestick without manual calculations.
Customizable: Tailor the appearance to match your trading style.
Versatile: Works on any instrument and timeframe.
Settings:
Show Pips (Otherwise Ticks): Toggle between pips and ticks mode.
Text Color: Choose the color of the range value text.
Text Size: Select the size of the range value text (Tiny, Small, Normal, Large).
Ideal For:
Forex, stocks, commodities, and crypto traders.
Traders who focus on volatility and range analysis.
Anyone looking for a clear and customizable way to visualize candle ranges.
This description highlights the key features, benefits, and usability of your indicator, making it appealing to other TradingView members. Let me know if you'd like to tweak it further! 😊
hinton_map█ HINTON MAP
This library provides functions to create and display a Hinton Map visualization. A Hinton map uses squares to represent the magnitude and direction of values in a matrix. This library allows you to display multiple ticker/timeframe/indicator combinations on a single chart, using color/boxsize/bnordersize to represent the values used. The values must be from -1.0 to 1.0 in value. 3 different values can be input per square.
Example Usage:
The example below demonstrates how to create a Hinton Map for two symbols (AAPL and MSFT) across three timeframes (1 minute, 5 minutes, and 1 day).
var hintonData = hinton_map.initHintonData(2, 3)
tickers = array.from("AAPL", "MSFT")
timeframes = array.from("1", "5", "1D")
for i = 0 to array.size(tickers) - 1
for j = 0 to array.size(timeframes) - 1
ticker = array.get(tickers, i)
timeframe = array.get(timeframes, j)
= request.security(ticker, timeframe, [close, close , ta.rsi(close, 14)], lookahead = barmerge.lookahead_on)
percent_change = (close_current - close_previous) / close_previous * 100
rsi_deviation = rsi_current - 50
hintonData.unitMatrix.set(i, j, hinton_map.createHintonUnit(
fillValue = percent_change,
borderValue = rsi_deviation,
innerValue = percent_change * rsi_deviation,
boxText = dv.from_string(str.tostring(math.round(percent_change, 2)) + "%"),
tooltipText = dv.from_string(syminfo.ticker + ", " + timeframe + ": " + str.tostring(math.round(percent_change, 2)) + "%, RSI: " + str.tostring(math.round(rsi_current, 2)))
))
hinton_map.drawHintonMap(hintonData)
█ createHintonUnit
Creates a Hinton unit.
• fillValue
Value to determine the fill color hue.
Type: float
Default Value: 0.0
• borderValue
Value to determine the border color hue and width.
Type: float
Default Value: 0.0
• innerValue
Value to determine the inner box color hue.
Type: float
Default Value: 0.0
• boxText
Text to display in the inner box.
Type: dv.DisplayValue
Default Value: na
• tooltipText
Tooltip text for the inner box.
Type: dv.DisplayValue
Default Value: na
Returns: HintonUnit
█ initHintonData
Initializes Hinton map data structure.
• rows
Number of rows.
Type: int
• columns
Number of columns.
Type: int
Returns: HintonData
█ drawHintonMap
Draws a Hinton map.
• hintonData
Hinton map data.
Type: HintonData
• unitSize
Size of each unit in bars.
Type: int
Default Value: 10
• borderWidth
Base width of the inner box border.
Type: int
Default Value: 5
• plusHue
Hue value for positive values (0-360).
Type: float
Default Value: 180
• minusHue
Hue value for negative values (0-360).
Type: float
Default Value: -30
█ HintonUnit
Data for a Hinton unit.
• fillValue
Value to determine the fill color hue.
Type: float
• borderValue
Value to determine the border color hue and width.
Type: float
• innerValue
Value to determine the inner box color hue.
Type: float
• boxText
Text to display in the inner box.
Type: dv.DisplayValue
• tooltipText
Tooltip text for the inner box.
Type: dv.DisplayValue
█ HintonData
Structure to store Hinton map data.
• unitMatrix
Matrix of Hinton units.
Type: matrix
• lineMatrix
Matrix of lines.
Type: matrix
• labelMatrix
Matrix of labels.
Type: matrix
• boxMatrix
Matrix of boxes.
Type: matrix
• fillMatrix
Matrix of line fills.
Type: matrix
Candle Range Theory | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Candle Range Theory Indicator! This powerful tool offers a strategy built around the Candle Range Theory, which analyzes market movements through the relative size and structure of price candles. For more information about the process, check the "HOW DOES IT WORK" section.
Features of the new Candle Range Theory Indicator :
Implementation of the Candle Range Theory
FVG & Order Block Entry Methods
2 Different TP / SL Methods
Customizable Execution Settings
Customizable Backtesting Dashboard
Alerts for Buy, Sell, TP & SL Signals
📌 HOW DOES IT WORK ?
The Candle Range Theory (CRT) indicator operates by identifying significant price movements through the relative size and structure of candlesticks. A key part of the strategy is determining large candles based on their range compared to the Average True Range (ATR) in a higher timeframe. Once identified, a breakout of either the high wick or the low wick of the large candle is required. This breakout is considered a liquidity grab. After that, the indicator waits for confirmation through Fair Value Gaps (FVGs) or Order Blocks (OBs). The confirmation structure must be the opposite direction of the breakout, for example if the high wick is broken, a bearish FVG is required for the short entry. After a confirmation signal is received, the indicator will trigger entry points based on your chosen entry method (FVG or OB), and exit points will be calculated using either a dynamic ATR-based TP/SL method or fixed percentages. Alerts for Buy, Sell, Take-Proft, and Stop-Loss are available.
🚩 UNIQUENESS
This indicator stands out because it combines two highly effective entry methods: Fair Value Gaps (FVGs) and Order Blocks (OBs). You can choose between these strategies depending on market conditions. Additionally, the dynamic TP/SL system uses the ticker's volatility to automatically calculate stop-loss and take-profit targets. The backtesting dashboard provides metrics about the performance of the indicator. You can use it to tune the settings for best use in the current tiker. The Candle Range Theory approach offers more flexibility compared to traditional indicators, allowing for better customization and control based on your risk tolerance.
⚙️ SETTINGS
1. General Configuration
Higher Timeframe: Customize the higher timeframe for analysis. Recommended combinations include M15 -> H4, H4 -> Daily, Daily -> Weekly, and Weekly -> Monthly.
HTF Candle Size: Define the size of the higher timeframe candles as Big, Normal, or Small to filter valid setups based on their range relative to ATR.
Entry Mode: Choose between FVGs and Order Blocks for your entry triggers.
Require Retracement: Enable this option if you want a retracement to the FVG or OB for entry confirmation.
Show HTF Candle Lines: Toggle to display the higher timeframe candle lines for better visual clarity.
2. Fair Value Gaps
FVG Sensitivity: You may select between Low, Normal, High or Extreme FVG detection sensitivity. This will essentially determine the size of the spotted FVGs, with lower sensitivities resulting in spotting bigger FVGs, and higher sensitivities resulting in spotting all sizes of FVGs.
3. Order Blocks
Swing Length: Swing length is used when finding order block formations. Smaller values will result in finding smaller order blocks.
4. TP / SL
TP / SL Method:
a) Dynamic: The TP / SL zones will be auto-determined by the algorithm based on the Average True Range (ATR) of the current ticker.
b) Fixed : You can adjust the exact TP / SL ratios from the settings below.
Dynamic Risk: The risk you're willing to take if "Dynamic" TP / SL Method is selected. Higher risk usually means a better winrate at the cost of losing more if the strategy fails. This setting is has a crucial effect on the performance of the indicator, as different tickers may have different volatility so the indicator may have increased performance when this setting is correctly adjusted.
SOL & BTC EMA with BTC/SOL Price Difference % and BTC Dom EMAThis script is designed to provide traders with a comprehensive analysis of Solana (SOL) and Bitcoin (BTC) by incorporating Exponential Moving Averages (EMAs) and price difference percentages. It also includes the BTC Dominance EMA to offer insights into the overall market dominance of Bitcoin.
Features:
SOL EMA: Plots the Exponential Moving Average (EMA) for Solana (SOL) based on a customizable period length.
BTC EMA: Plots the Exponential Moving Average (EMA) for Bitcoin (BTC) based on a customizable period length.
BTC Dominance EMA: Plots the Exponential Moving Average (EMA) for BTC Dominance, which helps in understanding Bitcoin's market share relative to other cryptocurrencies.
BTC/SOL Price Difference %: Calculates and plots the percentage difference between BTC and SOL prices, adjusted for their respective EMAs. This helps in identifying relative strength or weakness between the two assets.
Background Highlight: Colors the background to visually indicate whether the BTC/SOL price difference percentage is positive (green) or negative (red), aiding in quick decision-making.
Inputs:
SOL Ticker: Symbol for Solana (default: BINANCE
).
BTC Ticker: Symbol for Bitcoin (default: BINANCE
).
BTC Dominance Ticker: Symbol for Bitcoin Dominance (default: CRYPTOCAP
.D).
EMA Length: The length of the EMA (default: 20 periods).
Usage:
This script is intended for traders looking to analyze the relationship between SOL and BTC, using EMAs to smooth out price data and highlight trends. The BTC/SOL price difference percentage can help traders identify potential trading opportunities based on the relative movements of SOL and BTC.
Note: Leverage trading involves significant risk and may not be suitable for all investors. Ensure you have a good understanding of the market conditions and employ proper risk management techniques.
Tapak 20RThis strategy originally developed by Jatrader. Kudos to him for giving me chance to develop this indicator.
This script should be use Light Crude Oil Futures 20 Range chart. (This strategy only proven for 20R range chart, Crude Oil.)
How it works?
If current 20R candle is closed green, the closing value must be higher than previous candle to take long position.
If not, it stays as previous direction.
If current candle is closed red, the closing value must be lower than previous candle to take short position.
If not, it stays as previous direction.
How to use this indicator?
1. First, determine the stoploss point from high or low candle.(if current candle is green, stoploss is set higher than high candle and vice versa)
2. Determine how many tick you want to allowed for stoploss, how much profit (ticks) you want to achieve.
3. Determine the color and thickness of each line.
The table will display all value involved with this strategy such as entry value, stoploss value and target profit value.
Please kept in mind that, this is scalping strategy. So, the recommended target profit should be around 10 - 20 ticks.
Thank you.
RSI Sector analysis
Screening tool that produces a table with the various sectors and their RSI values. The values are shown in 3 rows, each with a user-defined length, and can be averaged out and displayed as a single value. The chart is color coded as well. Each ETF representing a sector can be looked at individually, with the top holdings in each preprogrammed, but users can define their own if they wish. The left most ticker is the "benchmark"; SPY is the benchmark for the various sectors, and the ETF is the benchmark for the tickers within.
Symbols are color coded: light blue text indicates that a symbol has greater RSI values in all three timeframes than the benchmark (the leftmost symbol). Orange text indicates that a symbol has a lower RSI value for all three timeframes. In the first row, light blue text indicates the largest RSI increase from the third row to the first row. Orange text indicates the largest RSI decrease from the third row to the first row.
A blue highlight indicates that the value is the highest among the tickers, excluding the benchmark, and an orange highlight indicates that the value is the lowest among the tickers, also excluding the benchmark. A blue highlight on the ticker indicates that it has the highest average value of the 3 rows, and a orange highlight on the ticker indicates that it has the lowest average value of the 3 rows.
Market Structures Screener | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Market Structures Screener! This screener can provide information about the latest market structures in up to 5 tickers. You can also customize the styling of the screener.
Features of the new Market Structures Screener :
Find Latest Market Structures Across 5 Tickers
Break Of Structure (BOS)
Change of Character (CHoCH)
Change of Character+ (CHoCH+)
Customizable Algoritm / Styling
📌 HOW DOES IT WORK ?
Sometimes specific market structures form and break as the market fills buy & sell orders. Formed Change of Character (CHoCH) and Break of Structure (BOS) often mean that market will change direction, and they can be spotted by inspecting low & high pivot points of the chart.
This screener then finds market structures across 5 different tickers, and shows the latest information about them.
🚩UNIQUENESS
Formed market structures can be strong hints about the current direction and the state of the market, and our screener has the ability to detect Change Of Character structures of the market with higher sensitivity (CHoCH+), so you will miss less hints. This screener will then show the elapsed time of the found BOS, CHoCH and CHoCH+ structures.
⚙️SETTINGS
1. Tickers
You can set up to 5 tickers for the screener to scan market structures here. You can also enable / disable them and set their individual timeframes.
Liquidity Grab Screener | Flux Charts💎 GENERAL OVERVIEW
Introducing our new Liquidity Grab Screener! This screener can provide information about the latest liquidity grabs in up to 5 tickers. You can also customize the algorithm that finds the liquidity grabs and the styling of the screener.
Features of the new Liquidity Grab Screener :
Find Latest Liquidity Grabs Accross 5 Tickers
Price, Size, Status Information
Customizable Algoritm / Styling
📌 HOW DOES IT WORK ?
Liquidity grabs occur when one of the latest pivots has a false breakout. Then, if the wick to body ratio of the bar is higher than 0.5 (can be changed from the settings) a bubble is plotted.
The bubble size is determined by the wick to body ratio of the candle.
This screener then finds liquidity grabs accross 5 different tickers, and shows the latest information about them.
Price -> The price when the liquidity grab happened.
Size -> Size of the liquidity grab, determined by the wick-body ratio.
Status -> Shows the elapsed time of the liquidity grab.
🚩UNIQUENESS
Liquidity grabs can be useful when determining candles that have executed a lot of market orders, and planning your trades accordingly. This screener will find liquidity grabs from up to 5 tickers and give information about their price, size and status. The screener also lets you customize the pivot length and the wick-body ratio for liquidity grabs.
⚙️SETTINGS
1. Tickers
You can set up to 5 tickers for the screener to scan order blocks here. You can also enable / disable them and set their individual timeframes.
2. General Configuration
Pivot Length -> This setting determines the range of the pivots. This means a candle has to have the highest / lowest wick of the previous X bars and the next X bars to become a high / low pivot.
Wick-Body Ratio -> After a pivot has a false breakout, the wick-body ratio of the latest candle is tested. The resulting ratio must be higher than this setting for it to be considered as a liquidity grab.
3 Important Value CompositesCalculated on February 17, 2024. USDT 378 items, BTC 282 items, BINANCE
This is a watchlist, along with the most accurate computed values that I could achieve. It may be beneficial for those who want to change values from the "120x ticker screener (composite tickers)" indicator, which is one of the excellent indicators to bypass the limitation of the request. security() function that limits to only 40 requests. I've thought about this before but couldn't succeed, but someone finally did it. :)
--> 120x ticker screener (composite tickers)
Thank you once again for this idea.
You must look for this and change it.
t1 = 'symbol', n1 = Multiply , r1 = Pricescale(decimal)
Example of grouping: Group 1
BINANCE:ETHUSDT , BINANCE:FDUSDUSDT , BINANCE:BTCUSDT
2, 4, 2
13, 10
█ Note
• Tickers: For your watchlist, arrange them from left to right, pairing them in groups of 3.
• Pricescale: This represents the decimal length, arrange them from left to right, pairing them in groups of 3.
• Multiply: This involves multiplying the first 2 items in each pair of watchlists. Arrange them from left to right, pairing them in groups of 2.
* If you group items incorrectly, it may lead to inaccurate results.
* Please be advised that if one of the values in the "Pricescale"(decimal) trio changes, there may be a need to adjust those values accordingly to ensure correct digit separation. Otherwise, within the group, the numbers might appear peculiar.
ORB Algo | Flux Charts💎 GENERAL OVERVIEW
Introducing our new ORB Algo indicator! ORB stands for "Opening Range Breakout" which is a common trading strategy. The indicator can analyze the market trend in the current session and give "Buy / Sell", "Take Profit" and "Stop Loss" signals. For more information about the analyzing process of the indicator, you can read "How Does It Work ?" section of the description.
Features of the new ORB Algo indicator :
Buy & Sell Signals
Up To 3 Take Profit Signals
Stop-Loss Signals
Alerts for Buy / Sell, Take-Profit and Stop-Loss
Customizable Algoritm
Session Dashboard
Backtesting Dashboard
📌 HOW DOES IT WORK ?
This indicator works best in 1-minute timeframe. The idea is that the trend of the current session can be forecasted by analyzing the market for a while after the session starts. However, each market has it's own dynamics and the algorithm will need fine-tuning to get the best performance possible. So, we've implemented a "Backtesting Dashboard" that shows the past performance of the algorithm in the current ticker with your current settings. Always keep in mind that past performance does not guarantee future results.
Here are the steps of the algorithm explained briefly :
1. The algorithm follows and analyzes the first 30 minutes (can be adjusted) of the session.
2. Then, algorithm checks for breakouts of the opening range's high or low.
3. If a breakout happens in a bullish or a bearish direction, the algorithm will now check for retests of the breakout. Depending on the sensitivity setting, there must be 0 / 1 / 2 / 3 failed retests for the breakout to be considered as reliable.
4. If the breakout is reliable, the algorithm will give an entry signal.
5. After the position entry, algorithm will now wait for Take-Profit or Stop-Loss zones and signal if any of them occur.
If you wonder how does the indicator find Take-Profit & Stop-Loss zones, you can check the "Settings" section of the description.
🚩UNIQUENESS
While there are indicators that show the opening range of the session, they come short with features like indicating breakouts, entries, and Take-Profit & Stop-Loss zones. We are also aware of that different stock markets have different dynamics, and tuning the algorithm for different markets is really important for better results, so we decided to make the algorithm fully customizable. Besides all that, our indicator contains a detailed backtesting dashboard, so you can see past performance of the algorithm in the current ticker. While past performance does not yield any guarantee for future results, we believe that a backtesting dashboard is necessary for tuning the algorithm. Another strength of this indicator is that there are multiple options for detection of Take-Profit and Stop-Loss zones, which the trader can select one of their liking.
⚙️SETTINGS
Keep in mind that best chart timeframe for this indicator to work is the 1-minute timeframe.
TP = Take-Profit
SL = Stop-Loss
EMA = Exponential Moving Average
OR = Opening Range
ATR = Average True Range
1. Algorithm
ORB Timeframe -> This setting determines the timeframe that the algorithm will analyze the market after a new session begins before giving any signals. It's important to experiment with this setting and find the best option that suits the current ticker for the best performance. More volatile stocks will often require this setting to be larger, while more stabilized stocks may have this setting shorter.
Sensitivity -> This setting determines how much failed retests are needed to take a position entry. Higher senstivity means that less retests are needed to consider the breakout as reliable. If you think that the current ticker makes strong movements in a bullish & bearish direction after a breakout, you should set this setting higher. If you think the opposite, meaning that the ticker does not decide the trend right after a breakout, this setting show be lower.
(High = 0 Retests, Medium = 1 Retest, Low = 2 Retests, Lowest = 3 Retests)
Breakout Condition -> The condition for the algorithm to detect breakouts.
Close = Bar needs to close higher than the OR High Line in a bullish breakout, or lower than the OR Low Line in a bearish breakout. EMA = The EMA of the bar must be higher / lower than OR Lines instead of the close price.
TP Method -> The method for the algorithm to use when determining TP zones.
Dynamic = This TP method essentially tries to find the bar that price starts declining the current trend and going to the other direction, and puts a TP zone there. To achieve this, it uses an EMA line, and when the close price of a bar crosses the EMA line, It's a TP spot.
ATR = In this TP method, instead of a dynamic approach the TP zones are pre-determined using the ATR of the entry bar. This option is generally for traders who just want to know their TP spots beforehand while trading. Selecting this option will also show TP zones at the ORB Dashboard.
"Dynamic" option generally performs better, while the "ATR" method is safer to use.
EMA Length -> This setting determines the length of the EMA line used in "Dynamic TP method" and "EMA Breakout Condition". This is completely up to the trader's choice, though the default option should generally perform well. You might want to experiment with this setting and find the optimal length for the current ticker.
Stop-Loss -> Algorithm will place the Stop-Loss zone using setting.
Safer = The SL zone will be placed closer to the OR High for a bullish entry, and closer to the OR Low for a bearish entry.
Balanced = The SL zone will be placed in the center of OR High & OR Low
Risky = The SL zone will be placed closer to the OR Low for a bullish entry, and closer to the OR High for a bearish entry.
Adaptive SL -> This option only takes effect if the first TP zone is hit.
Enabled = After the 1st TP zone is hit, the SL zone will be moved to the entry price, essentially making the position risk-free.
Disabled = The SL zone will never change.
2. ORB Dashboard
ORB Dashboard shows the information about the current session.
3. ORB Backtesting
ORB Backtesting Dashboard allows you to see past performance of the algorithm in the current ticker with current settings.
Total amount of days that can be backtested depends on your TV subscription.
Backtesting Exit Ratios -> You can select how much of percent your entry will be closed at any TP zone while backtesting. For example, %90, %5, %5 means that %90 of the position will be closed at the first TP zone, %5 of it will be closed at the 2nd TP zone, and %5 of it will be closed at the last TP zone.
COSTAR Strategy [SS]A little late posting this but here it is, as promised!
This is the companion to the COSTAR indicator.
What it does:
It creates a co-integration paired relationship with a separate, cointegrated ticker. It then plots out the expected range based on the value of the cointegrated pair. When the current ticker is below the value of its co-integrated partner, it becomes a "Buy" and should be longed. When it becomes overvalued in comparison, it becomes a "Sell" and should be shorted.
The example above is with BA and USO, which have a strong inverse relationship.
How it works:
I made the strategy version a bit more intuitive. Instead of you selecting the parameters for your model, it will autoselect the ideal parameters based on your desired co-integrated pair. You simply enter the ticker you want to compare against, and it will sort through the values at various lags to find significance and stationarity. It will then create a model and plot the model out for you on your chart, as you can see above.
The premise of the strategy:
The premise of the strategy is as stated before. You long when the ticker is undervalued in comparison to its co-integrated pair, and short when it is overvalued. The conditions for entry are simply a co-integrated pair being over the expected range (short) or below the expected range (long).
The condition to exit is a "re-integration", or a crossover of the expected value of the ticker (the centreline).
What if it can't find a relationship?
In some instances, the indicator will not be able to determine a co-integrated relationship, owning to a lack of stationarity between the data. When this happens, you will get the following error:
The indicator provides you with prompts, such as switching the timeframe or trying an alternative ticker. In the case displayed above, if we simply switch to the 1 hour timeframe, we have a viable model with great backtest results:
You can toggle in the settings menu the various parameters, such as timeframe, fills and displays.
And that is the strategy in a nutshell, be sure to check out its partner indicator, COSTAR, for more information on the premise of using co-integrated models for trading. And let me know your questions below!
Safe trades everyone!
Bollinger Bands (Nadaraya Smoothed) | Flux ChartsTicker: AMEX:SPY , Timeframe: 1m, Indicator settings: default
General Purpose
This script is an upgrade to the classic Bollinger Bands. The idea behind Bollinger bands is the detection of price movements outside of a stock's typical fluctuations. Bollinger Bands use a moving average over period n plus/minus the standard deviation over period n times a multiplier. When price closes above or below either band this can be considered an abnormal movement. This script allows for the classic Bollinger Band interpretation while de-noising or "smoothing" the bands.
Efficacy
Ticker: AMEX:SPY , Timeframe: 1m, Indicator settings: Standard Dev: 2; Level 1 : off; Level 2: off; labels: off
Upper Band Key:
Blue: Bollinger No smoothing
Orange: Bollinger SMA smoothing period of 10
Purple: Bollinger EMA smoothing period of 10
Red: Nadaraya Smoothed Bollinger bandwidth of 6
Here we chose periods so that each would have a similar offset from the original Bollinger's. Notice that the Red Band has a much smoother result while on average having a similar fit to the other smoothing techniques. Increasing the EMA's or SMA's period would result in them being smoother however the offset would increase making them less accurate to the original data.
Ticker: AMEX:SPY , Timeframe: 1m, Indicator settings: Standard Dev: 2; Level 1: off; Level 2: off; labels: off
Upper Band Key:
Blue: Bollinger No smoothing
Orange: Bollinger SMA smoothing period of 20
Purple: Bollinger EMA smoothing period of 20
Red: Nadaraya Smoothed Bollinger bandwidth of 6
This makes the Nadaraya estimator a particularly efficacious technique in this use case as it achieves a superior smoothness to fit ratio.
How to Use
This indicator is not intended to be used on its own. Its use case is to identify outlier movements and periods of consolidation. The Smoothing Factor when lowered results in a more reactive but noisy graph. This setting is also known as the "bandwidth" ; it essentially raises the amplitude of the kernel function causing a greater weighting to recent data similar to lowering the period of a SMA or EMA. The repaint smoothing simply draws on the Bollinger's each chart update. Typically repaint would be used for processing and displaying discrete data however currently it's simply another way to display the Bollinger Bands.
What makes this script unique.
Since Bollinger bands use standard deviation they have excess noise. By noise we mean minute fluctuations which most traders will not find useful in their strategies. The Nadaraya-Watson estimator, as used, is essentially a weighted average akin to an ema. A gaussian kernel is placed at the candlestick of interest. That candlestick's value will have the highest weight. From that point the other candlesticks' values effect on the average will decrease with the slope of the kernel function. This creates a localized mean of the Bollinger Bands allowing for reduced noise with minimal distortion of the original Bollinger data.
Modern Portfolio Management IndicatorAfter weeks of grueling over this indicator, I am excited to be releasing it!
Intro:
This is not a sexy, technical or math based indicator that will give you buy and sell signals or anything fancy, but it is an indicator that I created in hopes to bridge a gap I have noticed. That gap is the lack of indicators and technical resources for those who also like to plan their investments. This indicator is tailored to those who are either established investors and to those who are looking to get into investing but don't really know where to start.
The premise of this indicator is based on Modern Portfolio Theory (MPT). Before we get into the indicator itself, I think its important to provide a quick synopsis of MPT.
About MPT:
Modern Portfolio Theory (MPT) is an investment framework that was developed by Harry Markowitz in the 1950s. It is based on the idea that an investor can optimize their investment portfolio by considering the trade-off between risk and return. MPT emphasizes diversification and holds that the risk of an individual asset should be assessed in the context of its contribution to the overall portfolio's risk. The theory suggests that by diversifying investments across different asset classes with varying levels of risk, an investor can achieve a more efficient portfolio that maximizes returns for a given level of risk or minimizes risk for a desired level of return. MPT also introduced the concept of the efficient frontier, which represents the set of portfolios that offer the highest expected return for a given level of risk. MPT has been widely adopted and used by investors, financial advisors, and portfolio managers to construct and manage portfolios.
So how does this indicator help with MPT?
The thinking and theory that went behind this indicator was this: I wanted an indicator, or really just a "way" to test and back-test ticker performance over time and under various circumstances and help manage risk.
Over the last 3 years we have seen a massive bull market, followed by a pretty huge bear market, followed by a very unexpected bull market. We have been and continue to be plagued with economic and political uncertainty that seems to constantly be looming over everyone with each waking day. Some people have liquidated their retirement investments, while others are fomoing in to catch this current bull run. But which tickers are sound and how tickers and funds have compared amongst each other remains somewhat difficult to ascertain, absent manually reviewing and calculating each ticker individually.
That is where this indicator comes in. This indicator permits the user to define up to 5 equities that they are potentially interested in investing in, or are already invested in. The user can then select a specific period in time, say from the beginning of 2022 till now. The user can then define how much they want to invest in each company by number of shares, so if they want to buy 1 share a week, or 2 shares a month, they can input these variables into the indicator to draw conclusions. As many brokers are also now permitting fractional share trading, this ability is also integrated into the indicator. So for shares, you can put in, say, 0.25 shares of SPY and the indicator will accept this and account for this fractional share.
The indicator will then show you a portfolio summary of what your earnings and returns would be for the defined period. It will provide a percent return as well as the projected P&L based on your desired investment amount and frequency.
But it goes beyond just that, you can also have the indicator display a simple forecasting projection of the portfolio. It will show the projected P&L and % Return over various periods in time on each of the ticker (see image below):
The indicator will also break down your portfolio allocation, it will show where the majority of your holdings are and where the majority of your P&L in coming from (best performers will show a green fill and worst will show a red fill, see image below):
This colour coding also extends to the portfolio breakdown itself.
Dollar cost averaging (DCA) is incorporated into the indicator itself, by assuming ongoing contributions. If you want to stop contributions at a certain point, you just select your end time for contributions at the point in which you would stop contributing.
The indicator also provides some basic fundamental information about the company tickers (if applicable). Simply select the "Fundamental" chart and it will display a breakdown of the fundamentals, including dividends paid, market cap and earnings yield:
The indicator also provides a correlation assessment of each holding against each other holding. This emphasizes the profound role of diversification on portfolios. The less correlation you have in your portfolio among your holdings, the better diversified you are. As well, if you have holdings that are perfectly inverse other holdings, you have a pseudo hedge against the downturn of one of your holdings. This is even more helpful if the inverse is a company with solid fundamentals.
In the below example you will see NASDAQ:IRDM in the portfolio. You will be able to see that NASDAQ:IRDM has a slight inverse relationship to SPY:
Yet IRDM has solid fundamentals and is performing well fundamentally. Thus, this makes IRDIM a solid addition to your portfolio as it can potentially hedge against a downturn for SPY and is less risky than simply holding an inverse leveraged share on SPY which is most likely just going to cost you money than make you money.
Concluding remarks:
There are many fun and interesting things you can do with this indicator and I encourage you to try it out and have fun with it! The overall objective with the indicator is to help you plan for your portfolio and not necessarily to manage your portfolio. If you have a few stocks you are looking at and contemplating investing in, this will help you run some theoretical scenarios with this stock based on historical performance and also help give you a feel of how it will perform in the future based on past behaviour.
It is important to remember that past behaviour does not indicate future behaviour, but the indicator provides you with tools to get a feel for how a stock has performed under various circumstances and get a general feel of the fundamentals of the company you could potentially be investing in.
Please note, this indicator is not meant to replace full, fundamental analyses of individual companies. It is simply meant to give you a "gist" of how companies are fundamentally and how they have performed historically.
I hope you enjoy it!
Safe trades everyone!
Autocorrelation OscillatorReleasing the autocorrelation oscillator.
NOTE! Please be sure to read the description. This is a theoretical indicator and its important to understand the theory behind its use.
About the indicator:
Before getting into the indicator and its functionality, its important to discuss the theoretical underpinnings of the indicator.
The autocorrelation oscillator operates on two theories of market behaviour that go hand in hand. Those theories are the market efficiency theory and the random walk theory (or hypothesis ).
Market efficiency theory: The market efficiency theory or "Efficient Market Hypothesis (EMH)" postulates that all available information is reflected in a ticker's price almost instantaneously and thus it is impossible for an investor or trader to get ahead of the market because we cannot respond to the speed that the market responds. Of course, there are many holes in this theory, the most notable being that the market is a function of humans. Absent humans and their technological integrations into the market, the market would cease to react at all. But that's besides the point. This is a widely accepted theory and one in which I can mathematically observe through statistical tests. The truth behind this theory is the market is efficient for responding to evolving economic and financial information, likely owning to huge amounts of computer and algorithmic integration into trading, and thus the market is more efficient than the average person is capable (absent computerized algorithms and integration) of ascertaining nuanced financial and economic circumstances. By the time we the people can appraise information, the market has already acted on it. And that is the main premise of the EMH.
The next theory is the Random Walk Theory or Hypothesis (RWH). This builds on the EMH and essentially postulates that the market reacts so quickly to price in current circumstances that it is too random for people to truly exploit and benefit from.
The result of these two theories is two-fold and can be summarized as such:
a) The market behaves in a chaotic fashion that is seemingly random and is incapable of being predicted effectively; and
b) The market is more efficient than a person in incorporating key fundamental information, contributing to the high degree of seemingly random behaviour.
So, how does this help us?
It is said, because of the EMH and the RWH, the only way to truly exploit the market for profit is by:
a) Buying and holding and investing under the bias that stocks will eventually rise in value; or
b) For short term trading, exploiting the pricing anomalies within the data.
So how do we exploit pricing anomalies within the data?
Well, in my own research on market efficiency and behaviour, I have identified many ways of figuring out some anomalies. One of the most effective ways is by looking at simple correlation of lagged values, or autocorrelation for short.
What is autocorrelation and how to use it in relation to EMH and RWH?
Autocorrelation refers to the correlative relationship among the values in a series. Put simply, its the relationship of the same variable over time. For example, if we wanted to look at the auto-correlation of a ticker's high price, we would take, say, 5 to 7 previous high prices and correlate them with the current high price in a series dataset. If the EMH and RWH are true, the correlation among all the variables should have an average less than 0.5 or greater than -0.5. This would indicate true randomness in the dataset and thus an efficient market.
However, if the average of all of the sum's of these correlations are greater than or equal to 0.5 or less than or equal to -0.5, that indicates there is a high degree of autocorrelation and thus the EMH ad RWH is being invalidated as the market is not operating efficiently. This is an anomaly and this anomaly can be exploited.
So how do we exploit it?
Well, when the EMH and RWH hypothesis is being invalidated, we can expect what I coin as a "Regression to Chaos" i.e. the market will revert back to an efficient equilibrium state. So if we have a high correlation of the lagged variables and a strong uptrend or downtrend correlation, we can expect an inefficient market to correct back to an efficient market (i.e. have a reversal from the current trend).
So how does the indicator work?
The indicator measures the lagged correlation of the previous 5 highs and lows of a ticker. A high correlation among all of the highs and lows that exceeds 0.8 would be an invalidation of the EMH and RWH and thus signal a correction to come (i.e. a Regression to Chaos).
The indicator will display this by changing colour. Red for a bearish reversal and green for a bullish. Let's take a look below using the ticker MSFT:
Above we can see the indicator identifying observed inefficiencies within the MSFT ticker on the 1 minute timeframe. The green vertical lines correspond to potential bullish reversals as a result of bearish inefficiencies, the red correspond to bearish reversals as a result of bullish inefficiencies.
You can see these lead to reversals within the ticker.
Components of the indicator:
In the chart above we see the following that are being indicated by arrows:
Red Arrows: Show the identified inefficiencies. Red for bullish inefficiencies (i.e. bearish reversal), green for bearish inefficiencies (i.e. bullish reversal)
Yellow Arrow: The lagged variable chart. This will display the current correlation among all the lagged variables the indicator is assessing.
Teal arrow: Displays the current strength of the trend by correlating the trend to time. A strong negative value (i.e. a value less than or equal to -0.5) indicates a strong downtrend, a strong positive value indicates the inverse.
You can unselect the data-tables in the settings menu if you just want to view the correlation line itself. This part of the indicator is customizable. You can also define the lookback period; however, it is strongly recommended to leave it at 14 as this maintains the use of this indicator as an oscillator.
And that is the indicator! Let me know your comments, questions and feedback below.
Safe trades everyone!
Open Interest Chart [LuxAlgo]The Open Interest Chart displays Commitments of Traders %change of futures open interest , with a unique circular plotting technique, inspired from this publication Periodic Ellipses .
🔶 USAGE
Open interest represents the total number of contracts that have been entered by market participants but have not yet been offset or delivered. This can be a direct indicator of market activity/liquidity, with higher open interest indicating a more active market.
Increasing open interest is highlighted in green on the circular plot, indicating money coming into the market, while decreasing open interests highlighted in red indicates money coming out of the market.
You can set up to 6 different Futures Open interest tickers for a quick follow up:
🔶 DETAILS
Circles are drawn, using plot() , with the functions createOuterCircle() (for the largest circle) and createInnerCircle() (for inner circles).
Following snippet will reload the chart, so the circles will remain at the right side of the chart:
if ta.change(chart.left_visible_bar_time ) or
ta.change(chart.right_visible_bar_time)
n := bar_index
Here is a snippet which will draw a 39-bars wide circle that will keep updating its position to the right.
//@version=5
indicator("")
n = bar_index
barsTillEnd = last_bar_index - n
if ta.change(chart.left_visible_bar_time ) or
ta.change(chart.right_visible_bar_time)
n := bar_index
createOuterCircle(radius) =>
var int end = na
var int start = na
var basis = 0.
barsFromNearestEdgeCircle = 0.
barsTillEndFromCircleStart = radius
startCylce = barsTillEnd % barsTillEndFromCircleStart == 0 // start circle
bars = ta.barssince(startCylce)
barsFromNearestEdgeCircle := barsTillEndFromCircleStart -1
basis := math.min(startCylce ? -1 : basis + 1 / barsFromNearestEdgeCircle * 2, 1) // 0 -> 1
shape = math.sqrt(1 - basis * basis)
rad = radius / 2
isOK = barsTillEnd <= barsTillEndFromCircleStart and barsTillEnd > 0
hi = isOK ? (rad + shape * radius) - rad : na
lo = isOK ? (rad - shape * radius) - rad : na
start := barsTillEnd == barsTillEndFromCircleStart ? n -1 : start
end := barsTillEnd == 0 ? start + radius : end
= createOuterCircle(40)
plot(h), plot(l)
🔶 LIMITATIONS
Due to the inability to draw between bars, from time to time, drawings can be slightly off.
Bar-replay can be demanding, since it has to reload on every bar progression. We don't recommend using this script on bar-replay. If you do, please choose the lowest speed and from time to time pause bar-replay for a second. You'll see the script gets reloaded.
🔶 SETTINGS
🔹 TICKERS
Toggle :
• Enabled -> uses the first column with a pre-filled list of Futures Open Interest tickers/symbols
• Disabled -> uses the empty field where you can enter your own ticker/symbol
Pre-filled list : the first column is filled with a list, so you can choose your open interest easily, otherwise you would see COT:088691_F_OI aka Gold Futures Open Interest for example.
If applicable, you will see 3 different COT data:
• COT: Legacy Commitments of Traders report data
• COT2: Disaggregated Commitments of Traders report data
• COT3: Traders in Financial Futures report data
Empty field : When needed, you can pick another ticker/symbol in the empty field at the right and disable the toggle.
Timeframe : Commitments of Traders (COT) data is tallied by the Commodity Futures Trading Commission (CFTC) and is published weekly. Therefore data won't change every day.
Default set TF is Daily
🔹 STYLE
From middle:
• Enabled (default): Drawings start from the middle circle -> towards outer circle is + %change , towards middle of the circle is - %change
• Disabled: Drawings start from the middle POINT of the circle, towards outer circle is + OR -
-> in both options, + %change will be coloured green , - %change will be coloured red .
-> 0 %change will be coloured blue , and when no data is available, this will be coloured gray .
Size circle : options tiny, small, normal, large, huge.
Angle : Only applicable if "From middle" is disabled!
-> sets the angle of the spike:
Show Ticker : Name of ticker, as seen in table, will be added to labels.
Text - fill
• Sets colour for +/- %change
Table
• Sets 2 text colours, size and position
Circles
• Sets the colour of circles, style can be changed in the Style section.
You can make it as crazy as you want:
Ultimate P&L IndicatorHello everyone,
Excited to release this P&L Indicator! Read below for more details.
What it does:
This is an indicator that permits you to track your active P&L live on Tradingview. As well, it provides some insight into DCAing your position by giving you live estimates of your revised DCA if you were to add to your position at various targets/price points.
Who is it for:
I developed it because I trade 100% off of Tradingview but my broker does not support Tradingview integration. So I wanted a way to track my position live on the Tradingview platform without having to constantly reference my broker. I also wanted to be able to set position specific alerts right on Tradingview.
How does it work:
It works by the user manually inputting their trade information, including their DCA, position size and the date and time of position entry. The indicator can provide real time and live DCA adjusted estimates if you were to add to your position at the current stock price, or you can manually calculcate your revised DCA at a specific price target.
The indicator also displays your current and past performance on your position for the duration of the position period:
Elements:
Capabilities:
The indicator is compatible with both futures and share trading.
Option trading is not directly available, however, you can get an idea for your option position P&L by following the 1 option contract = 100 share rule.
So if you have 5 option contracts that you bought at a ticker price of, say, 38$, your average cost or DCA would be 38 and your position size would be 500. This will not be 100% accurate, but will be close enough to give you a feel for your active P&L.
If you are trading futures, you will need to select "Futures Trading" and specify the TIck and Index costs. A cheat sheet has been provided in the tool tip for ES, Oil and MNQ. The default is set for ES1! mini futures at 0.25 ticks per 50$.
Important tips:
1. Select the date and time of your position (optional): This is optional but will provide you with the clearest and most accurate review of how your position has performed, including the highest and lowest (drawdown).
2. Select whether it is a share position or a futures position (this is required).
3. Select whether it is a long or short position (this is required).
4. Input your DCA and position size (this is required).
5. Most importantly, select the ticker your position is based in!
I have also prepared a quick start video which is linked below:
As always, please let me know your comments/questions and feedback for the indicator.
Thanks for checking it out and safe trades everyone!
mex_fundingScript for calculating Bitmex funding based on the Premium tickers Bitmex submits to Tradingview
Make sure you add the correct Bitmex Interest Base and Quote Symbols in the input settings
For example for www.bitmex.com the inputs are:
Chart ticker: XBTUSDPI8H
Input Settings
Interest Base: XBTBON8H
Interest Quote: USDBON8H
Accumulated Put/Call Ratio V2This is an updated version of the Accumulated P/C Ratio. Some changes include:
- Pinescript privacy changed from protected to open.
- Utilizes the "request.security_lower_tf" function for weekly and monthly charts.
- Now acquires and sums raw put volume (ticker: PVOL) and call volume (ticker: CVOL) separately, then divides the aggregate put to aggregate call to get the P/C ratio, as opposed to the original version which directly sums the put call ratio (ticker: PCC). Mathematically this calculation makes more sense, but the major drawback of this change seems to be that PVOL and CVOL don't have as much historical data as PCC.
The way to interpret the indicator is the same as the original version - higher values are bullish while lower values are bearish. A solid (0 transparency) bar means that the value is beyond 3 standard deviations within a particular period.
