ReversalThe primary objective of this indicator is to discern candles that exhibit characteristics suggestive of potential market reversals through the application of candlestick analysis. Extensive observation across various assets and timeframes has revealed the existence of a recurrent reversal pattern. This pattern typically manifests as a sequence of one to three candles that abruptly diverge from the prevailing price action or trend, offering a distinctive signal indicating a potential reversal.
By leveraging the insights gained from this observation, the indicator aims to assist traders in identifying these noteworthy candle patterns that hold the potential to indicate significant market shifts.
The indicator operates as follows: initially, it identifies the lowest close (in the case of a bullish reversal) or the highest close (in the case of a bearish reversal) within a specified number of previous candles, as determined by user input (referred to as "Candle Lookback").
Next, the indicator examines whether the closing price surpasses the high of the previously identified lowest (bullish reversal) or highest (bearish reversal) closed candle within a designated number of candles, as specified by the user (referred to as "Confirm Within").
Sentiment
Currency Pair Index IndicatorHere's how it works step by step:
The indicator takes an input parameter called "length," which determines the number of bars to consider for the calculation. A higher length value will result in a smoother indicator, while a lower length value will make it more sensitive to recent price changes.
It then calculates the bullish sentiment by summing the volume multiplied by the price change (close - open) for each bar where the close price is greater than the open price. If the close price is not greater than the open price, the value for that bar is set to zero. The sum of these values is divided by the total volume for the selected bars.
Similarly, the bearish sentiment is calculated by summing the volume multiplied by the price change (open - close) for each bar where the close price is less than the open price. If the close price is not less than the open price, the value for that bar is set to zero. The sum of these values is divided by the total volume for the selected bars.
The bullish and bearish values are then plotted on the chart as separate line graphs. The bullish sentiment is represented by a green line, while the bearish sentiment is represented by a red line.
The difference between the bullish and bearish values is also plotted as a blue line. This line represents the overall sentiment of the currency pair index.
Additionally, arrow symbols are plotted below the price bars to indicate bullish or bearish signals. A green arrow is displayed when the bullish sentiment is higher than the bearish sentiment, indicating a bullish signal. A red arrow is displayed when the bearish sentiment is higher than the bullish sentiment, indicating a bearish signal.
By observing the indicator's line graphs and arrow symbols, traders can get an idea of the overall sentiment of the currency pair and identify potential bullish or bearish trading opportunities.
120x ticker screener (composite tickers)In specific circumstances, it is possible to extract data, far above the 40 `request.*()` call limit for 1 single script .
The following technique uses composite tickers . Changing tickers needs to be done in the code itself as will be explained further.
⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯
🔶 PRINCIPLE
Standard example:
c1 = request.security('MTLUSDT' , 'D', close)
This will give the close value from 1 ticker (MTLUSDT); c1 for example is 1.153
Now let's add 2 tickers to MTLUSDT; XMRUSDT and ORNUSDT with, for example, values of 1.153 (I), 143.4 (II) and 0.8242 (III) respectively.
Just adding them up 'MTLUSDT+XMRUSDT+ORNUSDT' would give 145.3772 as a result, which is not something we can use...
Let's multiply ORNUSDT by 100 -> 14340
and multiply MTLUSDT by 1000000000 -> 1153000000 (from now, 10e8 will be used instead of 1000000000)
Then we make the sum.
When we put this in a security call (just the close value) we get:
c1 = request.security('MTLUSDT*10e8+XMRUSDT*100+ORNUSDT', 'D', close)
'MTLUSDT*10e8+XMRUSDT*100+ORNUSDT' -> 1153000000 + 14340 + 0.8242 = 1153014340.8242 (a)
This (a) will be split later on, for example:
1153014330.8242 / 10e8 = 1.1530143408242 -> round -> in this case to 1.153 (I), multiply again by 10e8 -> 1153000000.00 (b)
We subtract this from the initial number:
1153014340.8242 (a)
- 1153000000.0000 (b)
–––––––––––––––––
14340.8242 (c)
Then -> 14340.8242 / 100 = 143.408242 -> round -> 143.4 (II) -> multiply -> 14340.0000 (d)
-> subtract
14340.8242 (c)
- 14340.0000 (d)
––––––––––––
0.8242 (III)
Now we have split the number again into 3 tickers: 1.153 (I), 143.4 (II) and 0.8242 (III)
⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯⎯
In this publication the function compose_3_() will make a composite ticker of 3 tickers, and the split_3_() function will split these 3 tickers again after passing 1 request.security() call.
In this example:
t46 = 'BINANCE:MTLUSDT', n46 = 10e8 , r46 = 3, t47 = 'BINANCE:XMRUSDT', n47 = 10e1, r47 = 1, t48 = 'BINANCE:ORNUSDT', r48 = 4 // T16
•••
T16= compose_3_(t48, t47, n47, t46, n46)
•••
= request.security(T16, res, )
•••
= split_3_(c16, n46, r46, n47, r47, r48)
🔶 CHANGING TICKERS
If you need to change tickers, you only have to change the first part of the script, USER DEFINED TICKERS
Back to our example, at line 26 in the code, you'll find:
t46 = 'BINANCE:MTLUSDT', n46 = 10e8 , r46 = 3, t47 = 'BINANCE:XMRUSDT', n47 = 10e1, r47 = 1, t48 = 'BINANCE:ORNUSDT', r48 = 4 // T16
( t46 , T16 ,... will be explained later)
You need to figure out how much you need to multiply each ticker, and the number for rounding, to get a good result.
In this case:
'BINANCE:MTLUSDT', multiply number = 10e8, round number is 3 (example value 1.153)
'BINANCE:XMRUSDT', multiply number = 10e1, round number is 1 (example value 143.4)
'BINANCE:ORNUSDT', NO multiply number, round number is 4 (example value 0.8242)
The value with most digits after the decimal point by preference is placed to the right side (ORNUSDT)
If you want to change these 3, how would you do so?
First pick your tickers and look for the round values, for example:
'MATICUSDT', example value = 0.5876 -> round -> 4
'LTCUSDT' , example value = 77.47 -> round -> 2
'ARBUSDT' , example value = 1.0231 -> round -> 4
Value with most digits after the decimal point -> MATIC or ARB, let's pick ARB to go on the right side, LTC at the left of ARB, and MATIC at the most left side.
-> 'MATICUSDT', LTCUSDT', ARBUSDT'
Then check with how much 'LTCUSDT' and 'MATICUSDT' needs to be multiplied to get this: 5876 0 7747 0 1.0231
'MATICUSDT' -> 10e10
'LTCUSDT' -> 10e3
Replace:
t46 = 'BINANCE:MTLUSDT', n46 = 10e8 , r46 = 3, t47 = 'BINANCE:XMRUSDT', n47 = 10e1, r47 = 1, t48 = 'BINANCE:ORNUSDT', r48 = 4 // T16
->
t46 = 'BINANCE:MATICUSDT', n46 = 10e10 , r46 = 4, t47 = 'BINANCE:LTCUSDT', n47 = 10e3, r47 = 2, t48 = 'BINANCE:ARBUSDT', r48 = 4 // T16
DO NOT change anything at t46, n46,... if you don't know what you're doing!
Only
• tickers ('BINANCE:MTLUSDT', 'BINANCE:XMRUSDT', 'BINANCE:ORNUSDT', ...),
• multiply numbers (10e8, 10e1, ...) and
• round numbers (3, 1, 4, ...)
should be changed.
There you go!
🔶 LIMITATIONS
🔹 The composite ticker fails when 1 of the 3 isn't in market in the weekend, while the other 2 are.
That is the reason all tickers are crypto. I think it is possible to combine stock,... tickers, but they have to share the same market hours.
🔹 The number cannot be as large as you want, the limit lays around 15-16 digits.
This means when you have for example 123, 45.67 and 0.000000000089, you'll get issues when composing to this:
-> 123045670.000000000089 (21 digits)
Make sure the numbers are close to each other as possible, with 1 zero (or 2) in between:
-> 1.230045670089 (13 digits by doing -> (123 * 10e-3) + (45.67 * 10e-7) + 0.000000000089)
🔹 This script contains examples of calculated values, % change, SMA, RMA and RSI.
These values need to be calculated from HTF close data at current TF (timeframe).
This gives challenges. For example the SMA / %change is not a problem (same values at 1h TF from Daily data).
RMA , RSI is not so easy though...
Daily values are rather similar on a 2-3h TF, but 1h TF and lower is quite different.
At the moment I haven't figured out why, if someone has an idea, don't hesitate to share.
The main goal of this publication is 'composite tickers ~ request.security()' though.
🔹 When a ticker value changes substantially (x10, x100), the multiply number needs to be adjusted accordingly.
🔶 SETTINGS
SHOW SETS
SET
• Length : length of SMA, RMA and RSI
• HTF : Higher TimeFrame (default Daily)
TABLE
• Size table : \ _ Self-explanatory
• Include exchange name : /
• Sort : If exchange names are shown, the exchanges will be sorted first
COLOURS
• CH%
• RSI
• SMA (RMA)
DEBUG
Remember t46 , T16 ,... ?
This can be used for debugging/checking
ALWAYS DISABLE " sort " when doing so.
Example:
Set string -> T1 (tickers FIL, CAKE, SOL)
(Numbers are slightly different due to time passing by between screen captures)
Placing your tickers at the side panel makes it easy to compare with the printed label below the table (right side, 332201415014.45 ),
together with the line T1 in the script:
t1 = 'BINANCE:FILUSDT' , n1 = 10e10, r1 = 4, t2 = 'BINANCE:CAKEUSDT' , n2 = 10e5 , r2 = 3, t3 = 'BINANCE:SOLUSDT' , r3 = 2 // T1
FIL : 3.322
CAKE: 1.415
SOL : 14.56
Now it is easy to check whether the tickers are placed close enough to each other, with 1-2 zero's in between.
If you want to check a specific ticker, use " Show Ticker" , see out initial example:
Set string -> T16
Show ticker -> 46 (in the code -> t46 = 'BINANCE:MTLUSDT')
(Set at 0 to disable " check string " and NONE to disable " Set string ")
-> Debug/check/set away! 😀
🔶 OTHER TECHNIQUES
• REGEX ( Regular expression ) and str.match() is used to delete the exchange name from the ticker, in other words, everything before ":" is deleted by following regex:
exch(t) => incl_exch ? t : str.match(t, "(?<=:) +")
• To sort, array.sort_indices() is used (line 675 in the code), just as in my first "sort" publication Sort array alphabetically - educational
aSort = arrT.copy()
sort_Indices = array.sort_indices(id= aSort, order= order.ascending)
• Numbers and text colour will adjust automatically when switching between light/dark mode by using chart.fg_color / chart.bg_color
🔹 DISCLAIMER
Please don't ask me for custom screeners, thank you.
[SMA Cross + HHLL] Signal Clean Up Analysis with Backtest (TSO) This is a DEMO indicator with a simple 2 SMAs cross for signals + HHLL for TP/SL. It mainly demonstrates chained (NOTE: You can select several or ALL of the features, this is not limited to either one) signal cleanup and analysis approach with scheduling and alerting capabilities. Works with most popular timeframes: 1M, 5M, 15M, 1H, 4H, D.
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Here are some pre-set examples with nice Backtesting results (try em out!):
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>>> Indexes – SPY (INTRADAY SETUP ): Timeframe: 5M | Trading Schedule: ON, 10:00-15:45 ET, EOD: At Market Close | Trading System: Open Until Closed by TP or SL | MULTIPROFIT: TP (take profit) System: Dynamic | MULTIPROFIT: SL (stop loss) System (This is only for “Dynamic” TP System ONLY!!!): Dynamic | # of TPs: 5 | Skip opposite candle types in signals, which are opposite to direction of candle color (for example: bearish green hammer) | Everything else: Default
>>> Bitcoin – BTCUSD (24/7 SETUP): Timeframe: 1H | Trading Schedule: OFF, End of Day (EOD): OFF | Trading System: Open Until Closed by TP or SL | MULTIPROFIT: TP (take profit) System: Dynamic | MULTIPROFIT: SL (stop loss) System (This is only for “Dynamic” TP System ONLY!!!): Dynamic | # of TPs: 3 | TP(s) Offset: on, TP(s) offset amount: 50 | ATR confirmation | Everything else: Default
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Explanation of all the Features | Configuration Guide | Indicator Settings
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Signal cleanup analysis:
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>>> Customizable Backtesting for a specific date range, results via TradingView strategy, which includes “Deep Backtesting” for largest amounts of data on trading results.
>>> Trading Schedule with customizable trading daily time range, automatic closing/alert trades before Power Hour or right before market closes or leave it open until next day.
>>> 3 Trading Systems.
>>> Static/Dynamic Take-Profit setups (HILIGHT: momentum catch dynamic Take-Profit approach).
>>> Static/Dynamic Stop-Loss setups (HIGHLIGHT: smart trailing Stop-Loss which minimizes risk).
>>> Single or Multiple profit targets (up to 5).
>>> Take-Profit customizable offset feature (set your Take-Profit targets slightly before everyone is expecting it!).
>>> Candle bar signal analysis (skip opposite structured and/or doji candle uncertain signals).
>>> Additional analysis of VWAP/EMA/ATR/EWO (Elliot Wave Oscillator)/Divergence MACD+RSI signal confirmation (clean up your chart with indicator showing only the best potential signals!).
>>> Advanced Alerts setup, which can be potentially setup with a trading bot over TradingView Webhook (NOTE: This will require advanced programming knowledge).
>>> Customize your signal SOURCE and your Take-Profit/Stop-Loss SOURCES as you desire.
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Labels, plots, colors explanations:
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>>>>> Signal SOURCE: SMA crossings (green and red BIG circles) .
>>>>> Take-profit/Stop-loss SOURCE: HHLL (Highest High Lowest Low) .
>>>>> LONG open: green arrow below candle bar.
>>>>> SHORT open: red arrow above candle bar.
>>>>> LONG/SHORT take-profit target: green/red circles (multi-profit > TP2/3/4/5 smaller circles).
>>>>> LONG/SHORT take-profit hits: green/red diamonds.
>>>>> LONG/SHORT stop-loss target: green/red + crosses.
>>>>> LONG/SHORT stop-loss hits: green/red X-crosses.
>>>>> LONG/SHORT EOD close (profitable trade): green/red squares.
>>>>> LONG/SHORT EOD close (loss trade): green/red PLUS(+)-crosses.
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Date Range and Trading Schedule Settings
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>>>>> Date Range: Select your start and/or end dates (uncheck “End” for indicator to show results up to the very moment and to use for LIVE trading) for backtesting results, if not using backtesting – uncheck “Start”/“End” to turn it off.
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>>>>> Use TradingView “Strategy Tester” to see backtesting results
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NOTE: If Strategy Tester does not show any results with Date Ranged fully unchecked, there may be an issue where a script opens a trade, but there is not enough TradingView power to set the Take-Profit and Stop-Loss and somehow an open trade gets stuck and never closes, so there are “no trades present”. In such case you will need to manually check “Start”/“End” dates or use “Depp Backtesting” feature!
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>>>>> Trading Schedule: This is where you can setup Intraday Session or any custom session schedule you wish. Turn it ON. Select trading hours. Select EOD (End of Day) setting (NOTE: If it will be OFF, the indicator will assume you are holding your position open until next day!).
>>>>> Trading System: 1) Open Until Closed by TP or SL – once the trade is open, it can only be closed by Take-Profit, Stop-Loss or at EOD (if turned on) ||| 2) OCA – Opposite Trade will Open Closing Current Trade – Same as 1), except that when and if an OPPOSITE signal is received > indicator will close current trade immediately (profit or loss) and open a new one(NOTE: This will only happen with an OPPOSITE direction trade!) ||| 3) Open Until Opposite Signal or EOD (if turned on) – This approach is the simplest one, there are no Take-Profits or Stop-Losses, the trade is open until an OPPOSITE signal is received or until EOD (if turned on).
Take-Profit, Stop-Loss and Multi-Profit Settings
>>>>> MULTIPROFIT | TP (Take-Profit) System: 1) Static – Once the trade is open, all Take-Profit target(s) are immediately calculated and set for the trade > once the target(s) is hit > trade will be partially closed (if candle bar closes beyond several Take-Profit targets > trade will be reduced accordingly to the amount of how many Take-Profit targets were hit) ||| 2) Dynamic – Once the trade is open, only the 1st Take-Profit target is calculated, once the 1st Take-Profit is hit > next Take-Profit distance is calculated based on the distance from trade Entry to where 1st Take-Profit was taken, once 2nd Take-Profit is taken > 3rd Take-Profit is calculated per same logic, these are good for price momentum as with price speeding up – profits increase as well!
NOTE: Below 2 settings, each correspond to only 1 setting of the TP (Take-Profit) System, please pay attention to the above TP system setting before changing SL settings!
>>>>> MULTIPROFIT | SL (Stop-Loss) System : 1) Static – Once the trade is open, Stop-Loss is calculated and set for the remaining of the trade ||| 2) Dynamic – At trade open, Stop-Loss is calculated and set the same way, however once 1st Take-Profit is taken > Stop-Loss is moved to Entry, reducing the risk.
>>>>> MULTIPROFIT | SL (Stop-Loss) System : 1) Static - Once the trade is open, Stop-Loss is calculated and set for the remaining of the trade ||| 2) Dynamic – At trade open, Stop-Loss is calculated and set the same way, however with each Take-Profit taken, Stop-Loss will be moved to previous Take-Profit (TP1 taken > SL:Entry | TP2 taken > SL:TP1 | TP3 taken > SL:TP2 | TP4 taken > SL:TP3 | TP5 taken > trade closed), this is basically a smart Stop-Loss trailing system!
>>>>> # of TPs (number of take profit targets): Just like it is named, this is where you select the number of Take-Profit targets for your trading system (NOTE: If “3) Open Until Opposite Signal or EOD (if turned on)” Trading System is selected, this setting won’t do anything, since there are no TP or SLs for that system).
>>>>> TP(s) offset: This is a special feature for all Take-Profit targets, where you can turn on a customizable offset, so that if the price is almost hitting the Take-Profit target, but never actually touches it > you will capture it. This is good to use with HHLL (Highest High Lowest Low), which is pretty much a Support/Resistance as often the price will nearly touch these strong areas and turn around…
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Dynamic/Static Take-Profit and Stop-Loss visual examples:
1) Fully Dynamic Take-Profit and Stop-Loss setup for BTCUSD
See how Take-Profit distances increase with price momentum and how Stop-Loss is following the trade reducing the risk!
2) Static/Dynamic, Static Take-Profit and Dynamic Stop-Loss setup for SPY (S&P500 ETF TRUST)
You can see a static Take-Profit set at position open, while Stop-Loss is semi-dynamic adjusting to Entry once TP1 target is taken!
3) Fully Static Take-Profit and Stop-Loss setup for SPY (S&P500 ETF TRUST)
This one is a fully static setup for both Take-Profit and Stop-Loss, you can also observe how trade is closed right before the Power Hour (trade can be closed right before Power Hour or right before Market Closes or left overnight as you desire).
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Trade Analysis and Cleanup Settings
>>>>> Candle Analysis | Candle Color signal confirmation: If closed candle bar color does not match the signal direction > no trade will be open.
>>>>> Candle Analysis | Skip opposite candle signals: If closed candle bar color will match the signal direction, but candle structure will be opposite (for example: bearish green hammer, long high stick on top of a small green square) > no trade will be open.
>>>>> Candle Analysis | Skip doji candle signals: If closed candle bar will be the uncertain doji > no trade will be open.
>>>>> Divergence/Oscillator Analysis | EWO (Elliot Wave Oscillator) signal confirmation: LONG will only be open if at signal, EWO is green or will be at bullish slope (you can select which setting you desire), SHORT if EWO is red or will be at bearish slope.
>>>>> Divergence/Oscillator Analysis | VWAP signal confirmation: LONG will only be open if at signal, the price will be above VWAP, SHORT if below.
>>>>> Divergence/Oscillator Analysis | Moving Average signal confirmation: LONG will only be open if at signal, the price will be above selected Moving Average, SHORT if below.
>>>>> Divergence/Oscillator Analysis | ATR signal confirmation: LONG will only be open if at signal, the price will be above ATR, SHORT if below.
>>>>> Divergence/Oscillator Analysis | RSI + MACD signal confirmation: LONG will only be open if at signal, RSI + MACD will be bullish, SHORT if RSI + MACD will be bearish.
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Alert Settings (you don’t have to touch this section unless you will be using TradingView alerts through a Webhook to use with trading bot)
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Here is how a LONG OPEN alert looks like (each label is customizable + I can add up more items/labels if needed):
COIN: BTCUSD
TIMEFRAME: 15M
LONG: OPEN
ENTRY: 20000
TP1: 20500
TP2: 21000
TP3: 21500
SL: 19000
Leverage: 0
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Trade Open Signal SOURCE + Take-Profit/Stop-Loss SOURCE
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>>> Customize your signal SOURCE, Take-Profit and Stop-Loss SOURCE as desired (NOTE: These are pre-configured and should be usable on majority of markets, however feel free to play around with these settings as there is nearly an infinite amount of setups out there!
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Adding Alerts in TradngView
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-Right-click anywhere on the TradingView chart
-Click on Add alert
-Condition: Select this indicator by it’s name
-Alert name: Whatever you want
-Hit “Create”
-Note: If you change ANY Settings within the indicator – you must DELETE the current alert and create a new one per steps above, otherwise it will continue triggering alerts per old Settings!
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If you have any questions or issues with the indicator, please message me directly via TradingView.
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Good Luck! (NOTE: Trading is very risky, so please trade responsibly!)
Order Block Scanner - Institutional ActivityIntroducing the Order Block Scanner: Unleash the Power of Institutional Insight!
Unlock a whole new realm of trading opportunities with the Order Block Scanner, your ultimate weapon in the dynamic world of financial markets. This cutting-edge indicator is meticulously designed to empower you with invaluable insights into potential Institutional and Hedge Funds activity like never before. Prepare to harness the intelligence that drives the giants of the industry and propel your trading success to new heights.
Institutional trading has long been veiled in secrecy, an exclusive realm accessible only to the chosen few. But with the Order Block Scanner, the doors to this realm swing open, inviting you to step inside and seize the advantage. Our revolutionary technology employs advanced algorithms to scan and analyze market data, pinpointing the telltale signs of institutional activity that can make or break your trades.
Imagine having the power to identify key levels where Institutional and Hedge Funds are initiating significant trades. With the Order Block Scanner, these hidden order blocks are unveiled, allowing you to ride the coattails of the market giants. This game-changing tool decodes their strategies, offering you a window into their actions and allowing you to align your trading decisions accordingly.
Forget the guesswork and uncertainty that plague so many traders. The Order Block Scanner empowers you with precision and clarity, helping you make informed decisions based on real-time data. Identify when the big players enter or exit the market, recognize their accumulation or distribution patterns, and position yourself for maximum profit potential.
Step into the realm of trading mastery and unleash your potential with the Order Block Scanner. Elevate your trading game, tap into the world of institutional trading, and take your profits to soaring heights. Don't let opportunity pass you by – invest in the Order Block Scanner today and embark on a thrilling journey toward trading success like never before.
The algorithm operates on data from Options and Darkpool markets, which is first exported to Quandl DB and then imported to TradingView using an API. The indicator also identifies patterns based on volume, volatility, and market movements, increasing the number of identified institutional activities on the markets.
AIAE IndicatorAggregate (or Average) Investor Allocation to Equities.
When it comes to predicting long-term equity returns, several well-known indicators come to mind—for example, the CAPE ratio, Tobin’s Q, and Market Cap to GDP, to name a few.
Yet there is another indicator without nearly as high of a profile that has outperformed the aforementioned indicators significantly when it comes to both forecasting and tactical asset allocation.
That indicator, known as the Aggregate (or Average) Investor Allocation to Equities (AIAE), was developed by the pseudonymous financial pundit, Jesse Livermore, and published on his blog in 2013.
In an essay titled, “The Single Greatest Predictor of Future Stock Market Returns,” Livermore makes the case that the primary driver of long-term equity returns is not valuation, but rather the supply of equities relative to the combined supply of bonds and cash.
Accordingly, the AIAE is computed by taking the total market value of equities and dividing by the sum of a) the total market value of equities, b) the total market value of bonds, and c) the total amount of cash available to investors (i.e., that in circulation plus bank deposits):
This ratio gives the market-wide allocation to equities (or, equivalently, the average investor allocation to equities weighted by portfolio size). (Note that every share of stock, every bond, and every unit of cash in existence must be held in some portfolio somewhere at all times.)
Livermore explains that, in practice, the total market value of bonds plus cash can be estimated by the total liabilities held by the five classes of economic borrowers: Households, Non-Financial Corporations, State and Local Governments, the Federal Government, and the Rest of the World.
This follows from the fact that if these entities borrow directly from investors, new bonds are created. Whereas, if they borrow directly from banks, new bank deposits (cash) are created.
As the economy grows, the supply of bonds and cash steadily increases. Historically, the rate of increase of the supply of bonds and cash has been about 7.5% per annum. Consequently, if the market portfolio is to maintain the same allocation to equities, the supply of equities must increase at the exact same rate.
The supply of equities can increase either by new equity issuance or by price increases. Historically, net new equity issuance has been negligible (with issuances being offset by buybacks and acquisitions). Thus, in order for equities not to become an ever-smaller portion of the average investor’s portfolio, the price of stocks must rise over the long-term.
While we often hear that stock prices follow earnings, in the 1980s earnings fell slightly from the beginning of the decade to the end of the decade, yet stocks rose at an annualized rate of 17% during that time. How could this be?
Well, at the beginning of the decade the average investor’s portfolio had a 25% allocation to equities. During the decade, the supply of bonds and cash rose strongly. If the price of equities had not risen, the average investor’s allocation to equities would have fallen to a mere 13% (as the supply of cash and bonds grew). Thus, equities had no choice but to rise despite the fall in earnings.
US Market SentimentThe "US Market Sentiment" indicator is designed to provide insights into the sentiment of the US market. It is based on the calculation of an oscillator using data from the High Yield Ratio. This indicator can be helpful in assessing the overall sentiment and potential market trends.
Key Features:
Trend Direction: The indicator helps identify the general trend direction of market sentiment. Positive values indicate a bullish sentiment, while negative values indicate a bearish sentiment. Traders and investors can use this information to understand the prevailing market sentiment.
Overbought and Oversold Levels: The indicator can highlight overbought and oversold conditions in the market. When the oscillator reaches high positive levels, it suggests excessive optimism and a potential downside correction. Conversely, high negative levels indicate excessive pessimism and the possibility of an upside rebound.
Divergence Analysis: The indicator can reveal divergences between the sentiment oscillator and price movements. Divergences occur when the price reaches new highs or lows, but the sentiment oscillator fails to confirm the move. This can signal a potential trend reversal or weakening of the current trend.
Confirmation of Trading Signals: The "US Market Sentiment" indicator can be used to confirm other trading signals or indicators. For instance, if a momentum indicator generates a bullish signal, a positive reversal in the sentiment oscillator can provide additional confirmation for the trade.
Usage and Interpretation:
Positive values of the "US Market Sentiment" indicate a bullish sentiment, suggesting potential buying opportunities.
Negative values suggest a bearish sentiment, indicating potential selling or shorting opportunities.
Extreme positive or negative values may signal overbought or oversold conditions, respectively, and could precede a market reversal.
Divergences between the sentiment oscillator and price trends may suggest a potential change in the current market direction.
Traders and investors can combine the "US Market Sentiment" indicator with other technical analysis tools to enhance their decision-making process and gain deeper insights into the US market sentiment.
Cumulative TICK [Pt]Cumulative TICK Indicator, shown as the bottom indicator, is a robust tool designed to provide traders with insights into market trends using TICK data. This indicator visualizes the cumulative TICK trend in the form of colored columns on a separate chart below the main price chart.
Here's an overview of the key features of the Cumulative TICK Indicator:
1. Selectable TICK Source 🔄: The indicator allows users to choose from four different TICK data sources, namely USI:TICK , USI:TICKQ , USI:TICKI , and $USI:TICKA.
2. TICK Data Type Selection 🎚️: Users can select the type of TICK data to be used. The options include: Close, Open, hl2, ohlc4, hlc3.
3. Optional Simple Moving Average (SMA) 📊: The indicator offers an option to apply an SMA to the Cumulative TICK values, with a customizable length.
4. After-hour Background Color 🌙: The background color changes during after-hours to provide a clear distinction between regular and after-hour trading sessions.
🛠️ How it Works:
The Cumulative TICK Indicator uses TICK data accumulated during the regular market hours (9:30-16:00) as per the New York time zone. At the start of a new session or at the end of the regular session, this cumulative TICK value is reset.
The calculated Cumulative TICK is plotted in a column-style graph. If the SMA is applied, the SMA values are used for the column plots instead. The columns are colored green when the Cumulative TICK is positive and red when it is negative. The shades of green and red vary based on whether the Cumulative TICK is increasing or decreasing compared to the previous value.
This is a simple yet powerful tool to track market sentiment throughout the day using TICK data. Please note that this indicator is intended to be used as part of a comprehensive trading strategy. Always ensure you are managing risk appropriately and consulting various data sources to make informed trading decisions.
Bank nifty puller and Dragger Hello Guys
using the below script you can check the nifty bank puller and draggers at live
how to use it?
it's straightforward
in the table, we will see the points contribution by each bank to Bank nifty
graph shows the overall strength of the buyers and sellers
using graphs also you can trade
but If you want to use a graph please note these important points
1:when the evergreen line cut the red line from below to top (cross-over) it says that buyers are strong but sometimes cross-over may fail and fall again
2: same things happen with the red line also
3: sometimes the graph shows that's a big difference between the red line and the green line that the market opened gap up gap down ( its difficult to define ) will update soon
4:when the market consolidates red and green lines will be very near to each other
5: when the green line is upper side the buyers are strong when the red line is upside sellers are strong (but sometimes it may mislead please be careful )
using the table you can check the overall view of all important banks
according to the time frame, data will be shown
this image shows the break out at 12.45 pm
2nd image shows the consolidation face of the market
this image shows that directly after opening the market sellers became stronger
this is how you can use the indicator
you can use graph or you can use table to get the over all view of the Bank nifty
Biddles OIWAP-Price SpreadThis indicator is the companion to my OIWAP (Open Interested-Weighted Average price) open source indicator.
In observing the OIWAP, what seemed most interesting was the distance between price and OIWAP.
This indicator plots that spread in a histogram.
It seems when price is too high above all OIWAPs, it's locally overbought (sentiment is overly bullish), and vice versa when it's too far below all OIWAPs (sentiment is overly bearish).
But I think there are more unique observations to be made beyond that - I am still in discovery phase myself.
For example: Looking at the SPX while using the ticker override to display BINANCE:BTCUSDT.P OI-Price spread data.
It works on any asset that Tradingview has OI data for. But it's also interesting to view correlated assets by using ticker override in the indicator settings (open the correlated asset w/o OI data in your chart, then set ticker override to a symbol with OI data, like the SPX example above).
>> If you find any interesting observations using it, have suggestions for improving the script, etc., hit me up on Twitter!
>>> @thalamu_
Initial Balance Panel Strategy for BitcoinInitial Balance Strategy
Initial Balance Strategy uses a source code of "Initial Balance Monitoring Panel" that build from "Initial Balance Markets Time Zones - Overall Highest and Lowest".
Initial Balance is based on the highest and lowest price action within the first 60 minutes of trading. Reading online this can depict which way the market can trend for the session. More information about Initial Balance Panel you can read at the end of the article.
Strategy idea
The main idea is to catch the trend move when most of the 16 Crypto pairs break the Low or High levels together. I found good results when 15 of 16 pairs is break that levels and after we manage the trade within some trail stop indicator, I choose Volatility Stop for this strategy.
Additional Strategy idea
The second one idea that was not made is to catch the pullback after fully green/red zones in Initial Balance Panel become white. That mean the main trend can be finished and we can try to catch good pullback in opposite direction.
Binance Crypto pairs
The strategy use the 16 default Crypto currencies pairs from the Binance. As additional variations of the strategy can be changing the currencies pairs and their number.
List of default pairs:
BINANCE:BTCUSDT, BINANCE:ETHUSDT, BINANCE:EOSUSDT, BINANCE:LTCUSDT, BINANCE:XRPUSDT, BINANCE:DASHUSDT, BINANCE:IOTAUSDT, BINANCE:NEOUSDT, BINANCE:QTUMUSDT, BINANCE:XMRUSDT, BINANCE:ZECUSDT, BINANCE:ETCUSDT, BINANCE:ADAUSDT, BINANCE:XTZUSDT, BINANCE:LINKUSDT, BINANCE:DOTUSDT
Summary
The strategy works very well for a buy trades with settings 15 crypto pairs of 16 that follow the trend with breaking the long initial balance level.
Initial Balance Monitoring Panel
Allows you to have an instant view of 16 Crypto pairs within a monitoring panel, monitoring Initial Balance (Asia, London, New York Stock Exchanges).
The code can easily be changed to suit the crypto pairs you are trading.
The setup of my chart would also include this indicator and the "Initial Balance Markets Time Zones - Overall Highest and Lowest" (with all IBs enabled) as shown above.
Initial Balance is based on the highest and lowest price action within the first 60 minutes of trading. Reading online this can depict which way the market can trend for the session.
The indicator has been coded for Crypto (so other symbols may not work as expected).
Though Initial Balance is based off the first 60 minutes of the trading markets opening, but Crypto is 24/7, this indicator looks at how Asia, London and New York Stock Exchanges opening trading can affect Crypto price action.
Source: Initial Balance Monitoring Panel
ICT Donchian Smart Money Structure (Expo)█ Concept Overview
The Inner Circle Trader (ICT) methodology is focused on understanding the actions and implications of the so-called "smart money" - large institutions and professional traders who often influence market movements. Key to this is the concept of market structure and how it can provide insights into potential price moves.
Over time, however, there has been a notable shift in how some traders interpret and apply this methodology. Initially, it was designed with a focus on the fractal nature of markets. Fractals are recurring patterns in price action that are self-similar across different time scales, providing a nuanced and dynamic understanding of market structure.
However, as the ICT methodology has grown in popularity, there has been a drift away from this fractal-based perspective. Instead, many traders have started to focus more on pivot points as their primary tool for understanding market structure.
Pivot points provide static levels of potential support and resistance. While they can be useful in some contexts, relying heavily on them could provide a skewed perspective of market structure. They offer a static, backward-looking view that may not accurately reflect real-time changes in market sentiment or the dynamic nature of markets.
This shift from a fractal-based perspective to a pivot point perspective has significant implications. It can lead traders to misinterpret market structure and potentially make incorrect trading decisions.
To highlight this issue, you've developed a Donchian Structure indicator that mirrors the use of pivot points. The Donchian Channels are formed by the highest high and the lowest low over a certain period, providing another representation of potential market extremes. The fact that the Donchian Structure indicator produces the same results as pivot points underscores the inherent limitations of relying too heavily on these tools.
While the Donchian Structure indicator or pivot points can be useful tools, they should not replace the original, fractal-based perspective of the ICT methodology. These tools can provide a broad overview of market structure but may not capture the intricate dynamics and real-time changes that a fractal-based approach can offer.
It's essential for traders to understand these differences and to apply these tools correctly within the broader context of the ICT methodology and the Smart Money Concept Structure. A well-rounded approach that incorporates fractals, along with other tools and forms of analysis, is likely to provide a more accurate and comprehensive understanding of market structure.
█ Smart Money Concept - Misunderstandings
The Smart Money Concept is a popular concept among traders, and it's based on the idea that the "smart money" - typically large institutional investors, market makers, and professional traders - have superior knowledge or information, and their actions can provide valuable insight for other traders.
One of the biggest misunderstandings with this concept is the belief that tracking smart money activity can guarantee profitable trading.
█ Here are a few common misconceptions:
Following Smart Money Equals Guaranteed Success: Many traders believe that if they can follow the smart money, they will be successful. However, tracking the activity of large institutional investors and other professionals isn't easy, as they use complex strategies, have access to information not available to the public, and often intentionally hide their moves to prevent others from detecting their strategies.
Instantaneous Reaction and Results: Another misconception is that market movements will reflect smart money actions immediately. However, large institutions often slowly accumulate or distribute positions over time to avoid moving the market drastically. As a result, their actions might not produce an immediate noticeable effect on the market.
Smart Money Always Wins: It's not accurate to assume that smart money always makes the right decisions. Even the most experienced institutional investors and professional traders make mistakes, misjudge market conditions, or are affected by unpredictable events.
Smart Money Activity is Transparent: Understanding what constitutes smart money activity can be quite challenging. There are many indicators and metrics that traders use to try and track smart money, such as the COT (Commitments of Traders) reports, Level II market data, block trades, etc. However, these can be difficult to interpret correctly and are often misleading.
Assuming Uniformity Among Smart Money: 'Smart Money' is not a monolithic entity. Different institutional investors and professional traders have different strategies, risk tolerances, and investment horizons. What might be a good trade for a long-term institutional investor might not be a good trade for a short-term professional trader, and vice versa.
█ Market Structure
The Smart Money Concept Structure deals with the interpretation of price action that forms the market structure, focusing on understanding key shifts or changes in the market that may indicate where 'smart money' (large institutional investors and professional traders) might be moving in the market.
█ Three common concepts in this regard are Change of Character (CHoCH), and Shift in Market Structure (SMS), Break of Structure (BMS/BoS).
Change of Character (CHoCH): This refers to a noticeable change in the behavior of price movement, which could suggest that a shift in the market might be about to occur. This might be signaled by a sudden increase in volatility, a break of a trendline, or a change in volume, among other things.
Shift in Market Structure (SMS): This is when the overall structure of the market changes, suggesting a potential new trend. It usually involves a sequence of lower highs and lower lows for a downtrend, or higher highs and higher lows for an uptrend.
Break of Structure (BMS/BoS): This is when a previously defined trend or pattern in the price structure is broken, which may suggest a trend continuation.
A key component of this approach is the use of fractals, which are repeating patterns in price action that can give insights into potential market reversals. They appear at all scales of a price chart, reflecting the self-similar nature of markets.
█ Market Structure - Misunderstandings
One of the biggest misunderstandings about the ICT approach is the over-reliance or incorrect application of pivot points. Pivot points are a popular tool among traders due to their simplicity and easy-to-understand nature. However, when it comes to the Smart Money Concept and trying to follow the steps of professional traders or large institutions, relying heavily on pivot points can create misconceptions and lead to confusion. Here's why:
Delayed and Static Information: Pivot points are inherently backward-looking because they're calculated based on the previous period's data. As such, they may not reflect real-time market dynamics or sudden changes in market sentiment. Furthermore, they present a static view of market structure, delineating pre-defined levels of support and resistance. This static nature can be misleading because markets are fundamentally dynamic and constantly changing due to countless variables.
Inadequate Representation of Market Complexity: Markets are influenced by a myriad of factors, including economic indicators, geopolitical events, institutional actions, and market sentiment, among others. Relying on pivot points alone for reading market structure oversimplifies this complexity and can lead to a myopic understanding of market dynamics.
False Signals and Misinterpretations: Pivot points can often give false signals, especially in volatile markets. Prices might react to these levels temporarily but then continue in the original direction, leading to potential misinterpretation of market structure and sentiment. Also, a trader might wrongly perceive a break of a pivot point as a significant market event, when in fact, it could be due to random price fluctuations or temporary volatility.
Over-simplification: Viewing market structure only through the lens of pivot points simplifies the market to static levels of support and resistance, which can lead to misinterpretation of market dynamics. For instance, a trader might view a break of a pivot point as a definite sign of a trend, when it could just be a temporary price spike.
Ignoring the Fractal Nature of Markets: In the context of the Smart Money Concept Structure, understanding the fractal nature of markets is crucial. Fractals are self-similar patterns that repeat at all scales and provide a more dynamic and nuanced understanding of market structure. They can help traders identify shifts in market sentiment or direction in real-time, providing more relevant and timely information compared to pivot points.
The key takeaway here is not that pivot points should be entirely avoided or that they're useless. They can provide valuable insights and serve as a useful tool in a trader's toolbox when used correctly. However, they should not be the sole or primary method for understanding the market structure, especially in the context of the Smart Money Concept Structure.
█ Fractals
Instead, traders should aim for a comprehensive understanding of markets that incorporates a range of tools and concepts, including but not limited to fractals, order flow, volume analysis, fundamental analysis, and, yes, even pivot points. Fractals offer a more dynamic and nuanced view of the market. They reflect the recursive nature of markets and can provide valuable insights into potential market reversals. Because they appear at all scales of a price chart, they can provide a more holistic and real-time understanding of market structure.
In contrast, the Smart Money Concept Structure, focusing on fractals and comprehensive market analysis, aims to capture a more holistic and real-time view of the market. Fractals, being self-similar patterns that repeat at different scales, offer a dynamic understanding of market structure. As a result, they can help to identify shifts in market sentiment or direction as they happen, providing a more detailed and timely perspective.
Furthermore, a comprehensive market analysis would consider a broader set of factors, including order flow, volume analysis, and fundamental analysis, which could provide additional insights into 'smart money' actions.
█ Donchian Structure
Donchian Channels are a type of indicator used in technical analysis to identify potential price breakouts and trends, and they may also serve as a tool for understanding market structure. The channels are formed by taking the highest high and the lowest low over a certain number of periods, creating an envelope of price action.
Donchian Channels (or pivot points) can be useful tools for providing a general view of market structure, and they may not capture the intricate dynamics associated with the Smart Money Concept Structure. A more nuanced approach, centered on real-time fractals and a comprehensive analysis of various market factors, offers a more accurate understanding of 'smart money' actions and market structure.
█ Here is why Donchian Structure may be misleading:
Lack of Nuance: Donchian Channels, like pivot points, provide a simplified view of market structure. They don't take into account the nuanced behaviors of price action or the complex dynamics between buyers and sellers that can be critical in the Smart Money Concept Structure.
Limited Insights into 'Smart Money' Actions: While Donchian Channels can highlight potential breakout points and trends, they don't necessarily provide insights into the actions of 'smart money'. These large institutional traders often use sophisticated strategies that can't be easily inferred from price action alone.
█ Indicator Overview
We have built this Donchian Structure indicator to show that it returns the same results as using pivot points. The Donchian Structure indicator can be a useful tool for market analysis. However, it should not be seen as a direct replacement or equivalent to the original Smart Money concept, nor should any indicator based on pivot points. The indicator highlights the importance of understanding what kind of trading tools we use and how they can affect our decisions.
The Donchian Structure Indicator displays CHoCH, SMS, BoS/BMS, as well as premium and discount areas. This indicator plots everything in real-time and allows for easy backtesting on any market and timeframe. A unique candle coloring has been added to make it more engaging and visually appealing when identifying new trading setups and strategies. This candle coloring is "leading," meaning it can signal a structural change before it actually happens, giving traders ample time to plan their next trade accordingly.
█ How to use
The indicator is great for traders who want to simplify their view on the market structure and easily backtest Smart Money Concept Strategies. The added candle coloring function serves as a heads-up for structure change or can be used as trend confirmation. This new candle coloring feature can generate many new Smart Money Concepts strategies.
█ Features
Market Structure
The market structure is based on the Donchian channel, to which we have added what we call 'Structure Response'. This addition makes the indicator more useful, especially in trending markets. The core concept involves traders buying at a discount and selling or shorting at a premium, depending on the order flow. Structure response enables traders to determine the order flow more clearly. Consequently, more trading opportunities will appear in trending markets.
Structure Candles
Structure Candles highlight the current order flow and are significantly more responsive to structural changes. They can provide traders with a heads-up before a break in structure occurs
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Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
BANKNIFTY STOCKS VWAP PlotsThis script plots a line in different colors based on how many high weightage stocks of banknifty are under vwap.
WORKS BEST on 1m and 2m candles.
stocks used to track are :
HDFC BANK
ICICI BANK
KOTAK BANK
SBI
INDUSIND BANK
If > 80% are below vwap then RED
If > 60% to < 80% below vwap then orange
if > 40% and < 60% below vwap then yellow
if < 40% below vwap then green
Any suggestions to add extra indicators is most welcomed.
Cumulative TICK Trend[Pt]Cumulative TICK Trend indicator is a comprehensive trading tool that uses TICK data to define the market's cumulative trend. Trend is shown on ATR EMA bands, which is overlaid on the price chart. Cumulative TICK shown on the bottom pane is for reference only.
Main features of the Cumulative TICK Trend Indicator include:
Selectable TICK Source: You have the flexibility to choose your preferred TICK source from the following options, depending on the market you trade: USI:TICK, USI:TICKQ, USI:TICKI, and USI:TICKA.
TICK Data Type: Select the type of TICK data to use, options include: Close, Open, hl2, ohlc4, hlc3.
Simple Moving Average (SMA): You can choose to apply an SMA on the calculated Cumulative TICK values with a customizable length.
Average True Range (ATR) Bands: It provides the option to display ATR bands with adjustable settings. This includes the ATR period, EMA period, source for the ATR calculation, and the ATR multiplier for the upper band.
Trend Color Customization: You can customize the color of the bull and bear trends according to your preference.
Smooth Line Option: This setting allows you to smooth the ATR Bands with a customizable length.
How it Works:
This indicator accumulates TICK data during market hours (9:30-16:00) as per the New York time zone and resets at the start of a new session or the end of the regular session. This cumulative TICK value is then used to determine the trend.
The trend is defined as bullish if the SMA of cumulative TICK is equal to or greater than zero and bearish if it's less than zero. Additionally, this indicator plots the ATR bands, which can be used as volatility measures. The Upper ATR Band and Lower ATR Band can be made smoother using the SMA, according to the trader's preference.
The plot includes two parts for each trend: a stronger color (Red for bear, Green for bull) when the trend is ongoing, and a lighter color when the trend seems to be changing.
Remember, this tool is intended to be used as part of a comprehensive trading strategy. Always ensure you are managing risk appropriately and consulting various data sources to make informed trading decisions.
VISION 1.0Introducing the VISION Indicator:
The VISION Indicator is an advanced tool that empowers users to analyze and predict market trends by utilizing three distinct boxes: Box A, Box B, and Box C. Each box represents a specific time range, allowing users to customize their analysis based on their preferred intervals.
Located at the top panel of the indicator, users can easily identify which boxes have a higher likelihood of representing the high or low points of the day. This information assists traders in focusing their attention on the specific boxes that are more likely to contain significant market turning points.
To provide additional insights, the indicator incorporates color-coded panels on the right side. These panels enhance the usability of the indicator by offering valuable information on accuracy and volume characteristics.
The red panel indicates the most accurate predictions for the low of the day. By examining this panel, traders can quickly determine which box historically demonstrates a higher probability of correctly predicting the market's lowest points.
Similarly, the green panel highlights the most accurate predictions for the high of the day. This panel provides traders with a visual representation of which box has historically shown a higher probability of correctly predicting the market's highest points.
Additionally, the blue panel showcases the box with the highest volume percentage. Traders can leverage this information to gauge the intensity of trading activity within different time intervals. By understanding volume patterns, traders can make informed decisions about optimal entry and exit points.
Overall, the VISION Indicator offers a comprehensive visual representation of different time intervals and their respective probabilities for market highs, lows, and trading volume. With this valuable tool, traders can gain insights into potential market trends and make informed trading decisions based on historical patterns and volume analysis.
Investor Satisfaction/Price Divergence Ox_kali The "Investor Satisfaction/Price Divergence" is an indicator designed to quantify investor satisfaction and pinpoint potential price divergences.
The primary goal of this indicator is to provide a reliable tool for gauging investor sentiment and identifying price divergences. These insights can be instrumental in predicting possible market trend reversals.
Key Features
Calculation of the highest and lowest prices over a user-defined period.
Computation of the average satisfaction of investors who have invested over a user-defined period.
Normalization of average satisfaction between 0 and 1 to provide a standardized measure of investor sentiment.
Identification of price divergence between the normalized satisfaction and the actual asset price.
Detection of anomalies in satisfaction change, which can suggest unusual market conditions.
Plotting an histogram display of the difference between normalized satisfaction and price divergence.
Functionality Analysis:
This indicator begins by identifying the highest and lowest prices over a period defined by the user. It then calculates the average investor satisfaction based on the change in the closing price from the investment point to the current price, relative to the range between the highest and lowest prices.
This satisfaction measure is then normalized between 0 and 1, providing a uniform measure of investor sentiment. The indicator also identifies potential price divergence by comparing the normalized satisfaction with the normalized price. This divergence is then plotted as a histogram, with the color of the histogram bars indicating whether the market is oversold, overbought, or in a normal state. Anomalies in satisfaction change are highlighted, helping traders to spot unusual market behavior.
Trading Application
The "Investor Satisfaction & Price Divergence" indicator can be incorporated into a variety of trading strategies. A significant divergence between normalized satisfaction and the asset price can signal a potential market reversal. Additionally, a sudden drop or rise in investor satisfaction could indicate a sell-off or a buying spree, respectively. Additionally, the capability to spot irregularities in satisfaction change may be useful in recognizing unusual market conditions, possibly providing early indications of noteworthy market events
Please note that the investor Satisfaction/Price Divergence by Ox_kali is provided for educational purposes only and is not meant to constitute financial advice. Thi indicator is not a guarantee of future market performance and should be used in conjunction with proper risk management. Always ensure that you have a thorough understanding of the indicator’s methodology and its limitations before making any investment decisions. Additionally, past performance is not indicative of future results.
Market Order Bubbles + Trapped Positions [Pt]"Market Order Bubbles + Trapped Positions" is a multifaceted TradingView indicator, employing volume data to depict intensified market activities. By highlighting aggressive buying/selling behaviors, this tool serves as a dependable aid in pinpointing potential trading reversals. Additionally, it proves an effective device for real-time market trend monitoring. The unique ability of this indicator to spotlight 'Trapped Positions'—resulting from such vigorous trading activity—helps identify crucial price levels or ranges that may lead to significant price responses.
Market Order Bubbles
The Market Order Bubbles feature capitalizes on volume data to estimate market orders. High bullish volume is indicative of a surge in buy orders, while strong bearish volume flags an increase in sell orders. These orders are visually represented by bubbles of different sizes, corresponding directly to the volume strength, thus providing traders with an immediate, intuitive understanding of market activity.
Trapped Positions/Zones
The concept of Trapped Positions emerges when sizable buy orders appear during a bearish market trend, or vice versa. For instance, if a considerable sell order is detected during a bullish uptrend, it signifies that those short positions may be 'trapped'. These positions help in plotting potential price range zones. When the price revisits these zones and the market trend maintains its bullish inclination, trapped shorts might opt for liquidation near break-even to mitigate losses. The reverse holds true in a bearish downtrend.
Trend Follower
The Trend Follower feature is a supportive tool that aims to discern price trends, color-coding candle bars for clarity. This function assists traders by presenting a simplified view of the prevailing trend, helping to minimize distractions caused by minor price shifts.
The utility of the Trend Follower is its ability to aid traders in focusing on the larger market direction. It allows traders to concentrate on the more substantial trend and make decisions that align with this broader market movement, rather than reacting to every minor price fluctuation. As a result, this feature may support traders in maintaining their positions for a longer duration, which could potentially enhance their trading outcomes. The Trend Follower, therefore, offers a helpful contribution to a balanced and effective trading approach.
In essence, the "Market Order Bubbles + Trapped Positions" indicator with its Trend Follower feature provides traders with a comprehensive understanding of market dynamics, allowing them to navigate the financial markets with increased precision and confidence. Its unique features, designed to highlight significant market activities and trends, can greatly aid in refining trading strategies, making it a potentially invaluable tool in a trader's arsenal.
BANKNIFTY position screenerThe script takes present day's price range of the stocks (stocks of the Index being tracked included in this screener) into account, to hint strength or weakness in the underlying Index (for example: BANKNIFTY here). The day's price range of a stock is gauged on a scale of 0-100, where 0 is Day's price low and 100 is day's price high.
If a stock is in 90-100 price range section the cell with title "90" illuminates hinting the stock is trading near day's high.
Likewise, if a stock is in 0-10 price range section the cell with title "10" illuminates hinting that the stock is trading near day's low.
The price range of 10-25 is represented in the cell titled "25"
The price range of 75-90 is represented in the cell titled "75"
Only one cell from the day's range illuminates at a time for a stock, signaling the present position of that stock in the Day's range at that instant.
The script works best above 10 second time frame.
Idea: If majority of the heavy weight stocks of the Index being tracked are trading near Day's high the underlying Index must be going strong at that very instant and Vice versa.
Disclaimer: Only for studying Index movement ideas intraday, trading is not advised.
Market Order Bubbles - By Leviathan"Market Order Bubbles" is a volume-based indicator that helps visualize the occurrences of increased aggressiveness in market buying/selling and can serve as a useful confluence for trading reversals or as a simple tool for observing real-time market dynamics.
I created Market Order Bubbles six months ago as an additional tool included in my Liquidation Levels script. Due to their popularity, I decided to publish them as a standalone indicator with some new features. The script is based on a calculation that uses volume data (imitation of CVD) and price action to estimate where there is a surge in the quantity and magnitude of market buy and sell orders. These occurrences are visualized with circles (bubbles) that appear above the bar (market buy orders) or below the bar (market sell orders). Most of the time, the approach to interpreting the bubbles is contrarian, meaning that the appearance of Market Buy Order Bubbles can serve as a confluence to look for shorts, and the appearance of Market Sell Order Bubbles can serve as a confluence to look for longs.
The concept behind taking a contrarian approach:
Market Buy Order Bubbles appear above the price and possibly signal the following:
- Short positions being liquidated (exit short = buy order)
- New traders entering late longs based on FOMO (enter long = buy order)
- Smarter traders getting their limit sell orders filled by aggressive buyers/stopped out shorts
⇒ Possible reversal to the downside / short-term pullback / start of ranging price action (PA)
Market Sell Order Bubbles appear below the price and possibly signal the following:
- Long positions being liquidated (exit long = sell order)
- New traders entering late shorts based on FOMO (enter short = sell order)
- Smarter traders getting their limit buy orders filled by aggressive sellers/stopped out longs
⇒ Possible reversal to the upside / short-term pullback / start of the ranging PA
These events are identified and filtered by EMA and STDEV-based "thresholds," which can be modified in the indicator settings.
1. If the buy/sell volume exceeds the first threshold, a Small Bubble is displayed.
2. If the buy/sell volume surpasses the second threshold, a Medium Bubble is displayed.
3. If the buy/sell volume exceeds the third threshold, a Large Bubble is displayed.
Increasing the multipliers effectively increases the threshold for a given bubble to appear, making the conditions for its occurrence more strict.
Decreasing the multipliers effectively decreases the threshold for a given bubble to appear, making the conditions for its occurrence less strict.
Settings Overview
"Bubble Position" - Choose whether the bubbles are displayed above/below the candle, at the candle high/low, or at the intrabar POC of the candle.
"Strength Gradient Color" - This option adjusts the transparency of the bubble's color relative to the volume on that bar.
"Threshold EMA Length" - Choose the length of the EMA used for determining the thresholds.
"Threshold STDEV Length" - Choose the length of the ta.stdev() function used on the EMA.
"Appearance Delay" - This input allows you to delay the appearance of the bubble for x number of bars. The default is 0.
"Show POC" - Show/hide intrabar POCs displayed as "-".
"Timeframe-Adjusted Settings" - Different timeframes might require different parameters. In this section, you can set custom parameters (Lengths and Multipliers) for four different timeframes, and the script will automatically switch to those settings as you browse through different timeframes.
Aggregated Funding RateThis funding rate indicator combines data from two of the largest cryptocurrency exchanges, BitMex and Binance, and supports USD, USDT, and BUSD currency pairs. Moreover, it covers a wide range of 31 different crypto assets to choose from, providing users with a comprehensive view of the funding rate for each asset.
The aggregation is formed by calculating the funding rate of the cryptocurrency for each perpetual chart respectively (Binance - USDT & BUSD and BitMex - USDT & USD). The calculation itself is based on each exchange's official formula, hence the reasoning behind including only 4 sources, they are currently the only ones which can be calculated this way in Tradingview.
Afterwards, it is either summed or averaged based on the user input. Additionaly, the user may choose freely which of the four sources will be included.
What is Funding Rate ?
The funding rate is the cost of holding a cryptocurrency position on a futures exchange. It is essentially an interest rate paid by the long or short position holder to the counterparty. If the funding rate is positive, longs pay shorts, and if it is negative, shorts pay longs. This rate is adjusted periodically, typically every eight hours, to ensure that the futures price of the cryptocurrency remains close to its spot price.
Utility :
The funding rate indicator can be used in a variety of ways. Traders can use it to gauge the sentiment of the market. If the funding rate is consistently positive, it suggests that there is more demand for long positions than short positions, indicating that the market is bullish. On the other hand, if the funding rate is consistently negative, it suggests that there is more demand for short positions than long positions, indicating that the market is bearish.
In addition, the funding rate indicator can be used to identify potential trading opportunities. If the funding rate is significantly higher than usual, it may indicate that longs are overpaying shorts, creating a potential arbitrage opportunity. Alternatively, if the funding rate is significantly lower than usual, it may indicate that shorts are overpaying longs, creating a potential arbitrage opportunity in the opposite direction.
Key Features
Aggregation type
31 supported cryptocurrencies
Simple or Depth style options
Sources to aggregate
BTC bottom top MACRO indicator based on: Cost per transaction(w)Predicting tops and bottoms in any market is a challenging task, and the Bitcoin market is no exception. Many traders and analysts use a combination of various indicators and models to help them make educated guesses about where the market might be heading. One such metric that can provide valuable insights is the Bitcoin cost per transaction indicator.
Here's how it could potentially be superior to just using price action for predicting macro tops and bottoms:
Transaction Cost as an Indicator of Network Activity: The cost per transaction on the Bitcoin network can give an indication of how much activity is taking place. When transaction costs are high, it may signal increased network usage, which often coincides with periods of market enthusiasm or FOMO (Fear of Missing Out) that can precede market tops. Conversely, lower transaction costs might indicate reduced network activity, potentially signaling a lack of investor interest that might precede market bottoms.
Reflects Real-World Use and Demand: Unlike price action, which can be influenced by speculative trading and may not always reflect the underlying fundamentals, the cost per transaction is directly tied to the use of the Bitcoin network. It offers a more fundamental approach to understanding market dynamics.
Complements Price Action Analysis: While price action can give signals about potential tops and bottoms based on historical price patterns and technical analysis, the cost per transaction can add an additional layer of information by reflecting network activity. In this way, the two can be used together to give a more complete picture of the market.
May Precede Price Changes: Changes in transaction costs could potentially precede price changes, giving advanced warning of tops and bottoms. For instance, a sudden increase in transaction costs might indicate a surge in network activity and investor interest, potentially signaling a market top. On the other hand, a decrease in transaction costs might suggest declining network activity and investor interest, potentially signaling a market bottom.
However, it's important to note that while the cost per transaction can provide valuable insights, it's not a foolproof method for predicting market tops and bottoms. Like all indicators, it should be used in conjunction with other tools and analysis methods, and traders should also consider the broader market context. As always, past performance is not indicative of future results, and all trading and investment strategies carry the risk of loss.
Liquidation Levels on OIThis indicator is used to display estimated contract liquidation prices. When there are dense liquidation areas on the chart, it indicates that there may be a lot of liquidity at that price level. The horizontal lines of different colors on the chart represent different leverage ratios. See below for details.
Let me introduce the principle behind this indicator:
1. When position trading volume increases or decreases significantly higher than usual levels in a specific candlestick chart, it indicates that a large number of contracts were opened during that period. We use the 60-day moving average change as a benchmark line. If the position trading volume changes more than 1.2x, 2x or 3x its MA60 value, it is considered small, medium or large abnormal increase or decrease.
2. This indicator takes an approximate average between high, open, low and close prices of that candlestick as opening price.
3. Since contracts involve liquidity provided by both buyers and sellers with equal amounts of long and short positions corresponding to each contract respectively; since we cannot determine actual settlement prices for contract positions; therefore this indicator estimates settlement prices instead which marks five times (5x), ten times (10x), twenty-five times (25x), fifty times (50x) and one hundred times (100x) long/short settlement prices corresponding to each candlestick chart generating liquidation lines with different colors representing different leverage levels.
4. We can view areas where dense liquidation lines appear as potential liquidation zones which will have high liquidity.
5. We can adjust orders based on predicted liquidation areas because most patterns in these areas will be quickly broken.
6. We provide a density histogram to display the liquidation density of each price range.
Special thanks to the following TradingView community members for providing open-source indicators and contributing to the development of this indicator!
Liquidation - @Mysterysauce
Open Interest Delta - By Leviathan - @LeviathanCapital
Regarding the relationship with the above-mentioned open source indicators:
1. Indicator Liquidation - @Mysterysauce can also draw a liquidation line in the chart, but:
(1) Our indicator generates a liquidation line based on abnormal changes in open interest; their indicator generates a liquidation line based on trading volume.
(2) Our indicator will generate both long and short liquidation lines at the same time; their indicator will only generate a liquidation line in a single direction.
We refer to their method of drawing liquidation lines when drawing our own.
2. Indicator Open Interest Delta - By Leviathan - @LeviathanCapital obtained OI data for Binance USDT perpetual contracts in the code. We refer to their method of obtaining OI data in our code.
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此指标用于显示估计合约清算价格。当图表上有密集的清算区域时，表示该价格水平可能存在大量流动性。图表上不同颜色的水平线代表不同杠杆比率。详情请参见下面的说明。
让我介绍一下这个指标背后的原理：
1. 当特定蜡烛图对应的合约仓位增加量（OI Delta）显著高于通常水平时，表示在那段时间有大量合约开仓。我们使用OI Delta的60日移动均线作为基准线。如果OI Delta超过其MA60值的1.2倍、2倍或3倍，则认为是小型、中型或大型的异常OI Delta。
2. 该指标将上述蜡烛图高、开、低和收盘价的平均值作为近似的合约开仓价。
3. 由于合约涉及买方和卖方之间相互提供流动性，每个合约对应相等数量的多头和空头头寸。由于我们无法确定合约头寸的实际清算价格，因此该指标估计了清算价格。它标记了与该蜡烛图相对应的多头和空头5倍、10倍、25倍、50倍和100倍的清算价格，生成清算线。不同杠杆水平用不同颜色表示。
4. 我们可以将出现密集清算线的区域视为潜在的清算区域。这些区域将具有高流动性。
5. 我们可以根据预测到的清算区域调整自己的订单，因为根据规律，这些清算区域大部分都会很快被击穿。
6. 我们提供了密度直方图来显示每个价格范围的清算密度
特别感谢以下TradingView社区成员提供开源指标并为该指标的开发做出贡献！
Liquidation - @Mysterysauce
Open Interest Delta - By Leviathan - @LeviathanCapital
与上述开源指标的关系：
1. 指标Liquidation - @Mysterysauce也可以在图中绘制清算线，但是：
（1）我们的指标是基于open interest的异常变化生成的清算线；他们的指标是基于成交量生成的清算线
（2）我们的指标会同时生成多头和空头清算线；他们的指标仅会在单一方向生成清算线
我们的指标在绘制清算线上参考了他们绘制清算线的方式
2. 指标Open Interest Delta - By Leviathan - @LeviathanCapital在代码中获取了Binance USDT永续合约的OI数据。我们在代码中参考他们获取OI数据的方式
Open Interest OffsetThis indicator is used to display whether there has been an abnormal increase or decrease in recent contract positions. Its usage is similar to the RSI indicator.
Please note that this indicator uses fixed (customizable) thresholds of 0.4 and 0.6 to indicate when abnormal opening and closing occur respectively. For some altcoins, their values may far exceed 0.4 so please adjust accordingly based on your symbol.
(1) When there is an abnormal increase in recent contract positions, the value of the indicator will be above 0.4. This means that there may be a liquidation market situation occurring subsequently. If the market background at this time is rising, it may not be suitable to continue buying because the indicator shows that it is currently overbought. On the contrary, it may be appropriate to sell now.
(2) When there is an abnormal decrease in recent contract positions, the value of the indicator will be below -0.4. This means that a liquidation market situation has occurred recently. If the market background at this time is falling, it may not be suitable to continue shorting because the indicator shows that it is currently oversold. On the contrary, it may be appropriate to buy now.
Special thanks to the following TradingView community members for providing open-source indicators and contributing to the development of this indicator!
Open Interest Delta - By Leviathan - @LeviathanCapital
Regarding the relationship with the above-mentioned open source indicator:
Indicator Open Interest Delta - By Leviathan - @LeviathanCapital obtained OI data for Binance USDT perpetual contracts in the code. We refer to their method of obtaining OI data in our code.
============= 中文版本 =============
该指标用于显示近期合约持仓量是否有异常的增加和减少。它的用法类似于RSI指标
请注意，该指标使用了固定的（可定制的）阈值0.4和0.6来提示异常开仓和平仓的发生。对于某些山寨币而言，指标的数值可能远大于0.4。请根据你所关注的标的自行调整
（1）当近期合约持仓量有异常的增加时，指标的值会在0.4以上。这意味着后续可能有清算行情的发生。若此时市场背景为上涨，此时可能不太适合继续做多，因为指标显示目前处于超买行情。相反，现在可能适合卖出
（2）当近期合约的持仓量有异常的减少时，指标的值会在-0.4以下。这意味着近期已经发生了清算行情。若此时市场背景为下跌，此时可能不太适合继续做空，因为指标显示目前处于超卖行情。相反，现在可能适合买入
特别感谢以下TradingView社区成员提供开源指标并为该指标的开发做出贡献！
Open Interest Delta - By Leviathan - @LeviathanCapital
与上述开源指标的关系：
指标Open Interest Delta - By Leviathan - @LeviathanCapital在代码中获取了Binance USDT永续合约的OI数据。我们在代码中参考他们获取OI数据的方式
