Weight Gain 4000 - (Adjustable Volume Weighted MA) - [mutantdog]Short Version:
This is a fairly self-contained system based upon a moving average crossover with several unique features. The most significant of these is the adjustable volume weighting system, allowing for transformations between standard and weighted versions of each included MA. With this feature it is possible to apply partial weighting which can help to improve responsiveness without dramatically altering shape. Included types are SMA, EMA, WMA, RMA, hSMA, DEMA and TEMA. Potentially more will be added in future (check updates below).
In addition there are a selection of alternative 'weighted' inputs, a pair of Bollinger-style deviation bands, a separate price tracker and a bunch of alert presets.
This can be used out-of-the-box or tweaked in multiple ways for unusual results. Default settings are a basic 8/21 EMA cross with partial volume weighting. Dev bands apply to MA2 and are based upon the type and the volume weighting. For standard Bollinger bands use SMA with length 20 and try adding a small amount of volume weighting.
A more detailed breakdown of the functionality follows.
Long Version:
ADJUSTABLE VOLUME WEIGHTING
In principle any moving average should have a volume weighted analogue, the standard VWMA is just an SMA with volume weighting for example. Actually, we can consider the SMA to be a special case where volume is a constant 1 per bar (the value is somewhat arbitrary, the important part is that it's constant). Similar principles apply to the 'elastic' EVWMA which is the volume weighted analogue of an RMA. In any case though, where we have standard and weighted variants it is possible to transform one into the other by gradually increasing or decreasing the weighting, which forms the basis of this system. This is not just a simple multiplier however, that would not work due to the relative proportions being the same when set at any non zero value. In order to create a meaningful transformation we need to use an exponent instead, eg: volume^x , where x is a variable determined in this case by the 'volume' parameter. When x=1, the full volume weighting applies and when x=0, the volume will be reduced to a constant 1. Values in between will result in the respective partial weighting, for example 0.5 will give the square root of the volume.
The obvious question here though is why would you want to do this? To answer that really it is best to actually try it. The advantages that volume weighting can bring to a moving average can sometimes come at the cost of unwanted or erratic behaviour. While it can tend towards much closer price tracking which may be desirable, sometimes it needs moderating especially in markets with lower liquidity. Here the adjustability can be useful, in many cases i have found that adding a small amount of volume weighting to a chosen MA can help to improve its responsiveness without overpowering it. Another possible use case would be to have two instances of the same MA with the same length but different weightings, the extent to which these diverge from each other can be a useful indicator of trend strength. Other uses will become apparent with experimentation and can vary from one market to another.
THE INCLUDED MODES
At the time of publication, there are 7 included moving average types with plans to add more in future. For now here is a brief explainer of what's on offer (continuing to use x as shorthand for the volume parameter), starting with the two most common types.
SMA: As mentioned above this is essentially a standard VWMA, calculated here as sma(source*volume^x,length)/sma(volume^x,length). In this case when x=0 then volume=1 and it reduces to a standard SMA.
RMA: Again mentioned above, this is an EVWMA (where E stands for elastic) with constant weighting. Without going into detail, this method takes the 1/length factor of an RMA and replaces it with volume^x/sum(volume^x,length). In this case again we can see that when x=0 then volume=1 and the original 1/length factor is restored.
EMA: This follows the same principle as the RMA where the standard 2/(length+1) factor is replaced with (2*volume^x)/(sum(volume^x,length)+volume^x). As with an RMA, when x=0 then volume=1 and this reduces back to the standard 2/(length+1).
DEMA: Just a standard Double EMA using the above.
TEMA: Likewise, a standard Triple EMA using the above.
hSMA: This is the same as the SMA except it uses harmonic mean calculations instead of arithmetic. In most cases the differences are negligible however they can become more pronounced when volume weighting is introduced. Furthermore, an argument can be made that harmonic mean calculations are better suited to downtrends or bear markets, in principle at least.
WMA: Probably the most contentious one included. Follows the same basic calculations as for the SMA except uses a WMA instead. Honestly, it makes little sense to combine both linear and volume weighting in this manner, included only for completeness and because it can easily be done. It may be the case that a superior composite could be created with some more complex calculations, in which case i may add that later. For now though this will do.
An additional 'volume filter' option is included, which applies a basic filter to the volume prior to calculation. For types based around the SMA/VWMA system, the volume filter is a WMA-4, for types based around the RMA/EVWMA system the filter is a RMA-2.
As and when i add more they will be listed in the updates at the bottom.
WEIGHTED INPUTS
The ohlc method of source calculations is really a leftover from a time when data was far more limited. Nevertheless it is still the method used in charting and for the most part is sufficient. Often the only important value is 'close' although sometimes 'high' and 'low' can be relevant also. Since we are volume weighting however, it can be useful to incorporate as much information as possible. To that end either 'hlc3' or 'hlcc4' tend to be the best of the defaults (in the case of 24/7 charting like crypto or intraday trading, 'ohlc4' should be avoided as it is effectively the same as a lagging version of 'hlcc4'). There are many other (infinitely many, in fact) possible combinations that can be created, i have included a few here.
The premise is fairly straightforward, by subtracting one value from another, the remaining difference can act as a kind of weight. In a simple case consider 'hl2' as simply the midrange ((high+low)/2), instead of this using 'high+low-open' would give more weight to the value furthest from the open, providing a good estimate of the median. An even better estimate can be achieved by combining that with 'high+low-close' to give the included result 'hl-oc2'. Similarly, 'hlc3' can be considered the basic mean of the three significant values, an included weighted version 'hlc2-o2' combines a sum with subtraction of open to give an estimated mean that may be more accurate. Finally we can apply a similar principle to the close, by subtracting the other values, this one potentially gets more complex so the included 'cc-ohlc4' is really the simplest. The result here is an overbias of the close in relation to the open and the midrange, while in most cases not as useful it can provide an estimate for the next bar assuming that the trend continues.
Of the three i've included, hlc2-o2 is in my opinion the most useful especially in this context, although it is perhaps best considered to be experimental in nature. For that reason, i've kept 'hlcc4' as the default for both MAs.
Additionally included is an 'aux input' which is the standard TV source menu and, where possible, can be set as outputs of other indicators.
THE SYSTEM
This one is fairly obvious and straightforward. It's just a moving average crossover with additional deviation (bollinger) bands. Not a lot to explain here as it should be apparent how it works.
Of the two, MA1 is considered to be the fast and MA2 is considered to be the slow. Both can be set with independent inputs, types and weighting. When MA1 is above, the colour of both is green and when it's below the colour of both is red. An additional gradient based fill is there and can be adjusted along with everything else in the visuals section at the bottom. Default alerts are available for crossover/crossunder conditions along with optional marker plots.
MA2 has the option for deviation bands, these are calculated based upon the MA type used and volume weighted according to the main parameter. In the case of a unweighted SMA being used they will be standard Bollinger bands.
An additional 'source direct' price tracker is included which can be used as the basis for an alert system for price crossings of bands or MAs, while taking advantage of the available weighted inputs. This is displayed as a stepped line on the chart so is also a good way to visualise the differences between input types.
That just about covers it then. The likelihood is that you've used some sort of moving average cross system before and are probably still using one or more. If so, then perhaps the additional functionality here will be of benefit.
Thanks for looking, I welcome any feedack
Pesquisar nos scripts por "liquidity"
MTF fair value gap v2 thigh gaps yumwell load in 2 FVG indicators one for current chart then one for MTF of interest.
Higher timeframe FVGs are more important and can be used for bias or even targets for internal liquidity.
big thanks @shanxia for basically re-doing the FVGs into arrays hehehe..
Can now delete mitigated or change mitigated color..
I dont know who uses extensions but if you want to suffer in your private time then go ahead...
pre sure this is the sexiest FVG indicator validate me in the description pls
Relative Volume Force IndexThis indicator can anticipate the market movements. Its posible because it calculates how much force (volume) it's necessary to move the price up or down. If it's necessary a lot of volume to move the price a little it's a reversion signal, but if a little volume could change the price whit elevate volatility, it's signal of reversion too. The indicator plots red if the market is down, and green if it's up, the size and the color of the bars cand demonstrate the movement relative force. Does it by the configurable averages. Not works well whit poor liquidity.
TBR(3AM, 9AM, 3PM)How It Works
• Monitors 3 key institutional hours: 3AM (London Open), 9AM (New York Open), and 3PM (US Close)
• Captures the full range (high and low) of each 1H candle at those times
• Confirms breakout only if the next 1H candle closes above or below the range
• Draws the zone (box) aligned with the original hourly candle (not delayed)
• Displays retracement lines at:
- 25% (initial reaction)
- 50% (mitigation level)
- 75% (deep retracement entry)
Key Features
• Precise zone alignment — Boxes are anchored to the actual breakout candle
• Mitigation logic — Zones are considered mitigated once price revisits the 0.5 level
• Expiry filter — Zones automatically remove after 7 days
• Time zone support — Choose from major time zones or fixed UTC offsets (e.g., Etc/GMT+4)
• Multi-timeframe compatible — Works on all timeframes (1m, 5m, 15m, etc.)
• Clean structure — No duplicated boxes on lower timeframes
• Fully customizable colors and visibility toggles
Settings
• Toggle visibility for 3AM / 9AM / 3PM zones independently
• Choose time zone (supports America/New_York, UTC, Asia/Tokyo, etc.)
• Adjust how long zones stay visible (in hours)
• Enable/disable auto-removal after mitigation
Ideal For
• ICT traders
• Smart money concepts (SMC)
• Zone-based entries and liquidity grabs
• Traders using mitigation and premium/discount retracement logic
Tip
• Use this script with liquidity/volume indicators or SMT divergence for even stronger confluence.
Swing Failure Pattern by EmreKbThe indicator detect to swing failure pattern and shows it.
Swing Failure Pattern (or SFP) is a type of reversal pattern in which (swing) traders target stop-losses above a key swing low or below a key swing high to push the price in the other direction by generating enough liquidity.
Financial DeepeningFinancial Deepening is defined as increases in the ratio of a country's financial assets to its GDP. It has the effect of increasing liquidity. Having access to money can provide more opportunities for investment growth. If done properly financial deepening can increase the country's resilience and boost economic growth.
US Money Supply M2 / US GDP. (ratio)
AltSessionHello World
It’s no secret that trading sessions play a massive role in market movement and liquidity. We can clearly see in the image about how important identifying international trading hours are for a trader.
The Asian session starts around 1am GMT and often has a bearish bias through this session lasting for a few hours, after which Frankfurt and London traders start to come online and can often reverse the Asian sentiment.
The London session is the best session to trade traditionally starting around 7am GMT before the American traders come online and reverse market once again.
We have designed this indicator to help identify different trading hours easily with a background shade on the chart and also high/lows of the training session, as these levels can often be revisited.
We hope you find this indicator useful and please feel free to drop a comment if you have any updates you wish to be made or any future indicator script ideas, thank you.
3 Seas RSI Wave OscillatorTraditional Triple RSI Oscillator combining a Fast, Normal, and Slow RSI to achieve high accuracy entry and exit strategies. This indicator is UNIQUE because it uses a mathematical filter to trim false signals from the RSI, thus creating a reliable RSI driven entry and exit indicator represented by red and green arrows. For additional functionality divergences are identified and live plotted. UNIQUELY Alongside the 0 axis an OBV function is charted relative to the RSI to allow OBV and RSI divergences to be observed on equal mathematical scales, this is exceedingly useful to observe relative strength at pools of liquidity. The three main configured RSI's are also plotted for traditional usage case but can be removed.
Green arrow indicates a Buy opportunity optimized for standard Dollar Cost Averaging strategies.
Red arrow indicates a Sell opportunity optimized for standard Dollar Cost Averaging strategies.
Not Financial Advice.
EBB & Flow: a multi-EMA-based BB cloudIntro
This is an idea evolved out of the market maker method and EMA convergence, divergence, and mean reversion.
The market maker method informs us that the 5, 13, 50 and 200 EMAs are important to regulating price. Those EMA lengths are multiples of the 50 and 200 on lower major timeframes -- the 1 minute, 5, 15, 1H, 4H, 1D. I include the 21 because it is also a multiple and in crypto very often respected.
When market makers are testing price, they set their range and spike in the direction they test for liquidity. This can get chaotic. For instance, in a shorter time frame consolidation inside a bigger timeframe uptrend, it can be too easy to forget where you are in the many trends playing out.
When the EMAs are dragged over each other during normal price movement, you get these crisscrossing tracks of price, and the individual breaks can be hard to trace.
The range is what matters, ultimately, and the range is dynamic. In that case, the Bollinger Band is a great tool for detecting outliers in this case.
The Answer
So the answer this indicator seeks to give, is to look for outliers. This gives you a scalping strategy built on Traders Reality thinking and best put together with the PVSRA indicator, which I may include in this indicator just for the sake of concision, but they can work alongside each other or separately.
The key thing is the different EMA clouds, which are bollinger bands. Tight bands mean imminent breaks, favouring the trend. Vector candles out of a zone, pins to the low/high, etc. are all very relevant alongside this indicator.
You can also use it on its own and scalp the breaks of a cloud.
How it works
Each cloud is a standard deviation from their respective EMA, all in the same colour. The deviation multiple is 1.618 by default. Yes, fibonacci sequences are usually nonsense, but it works better with the BB than 2, 2.5 or 3.
Using just the clouds, you can see where each EMA is headed and how it behaves within the deviation of the others.
But that on its own isn't enough.
The indicator will also print snowflakes above and below the candle for notable outliers. It will be in the colour of the cloud it breaks, but only if that break is also breaking the smaller EMA clouds too.
The most snowflakes will be yellow because that's the 13 EMA. That one is dependent on nothing else and every break will print a snowflake. The 21 will be dependent on the 13. The 50 dependent on the 13 and 21 breaks. The 200 the most important.
For example, if the 200 EMA-BB or EBB is broken at the upper band, deviating by more than 162% of price over a 200 period EMA, and that break is not above the 50 EMA cloud, there will be no snowflake. However, if it exceeds the 13, 21, 50, and 200 clouds, then a purple snowflake will appear above the bar.
Any snowflake is an extreme in price. The purple is an especially good point of entry. That doesn't mean it is a perfect entry. You can build position from it, though, and be relatively certain of a price correction in the near future, because not only was this major EMA cloud violated, but all of the smaller ones too.
Reminder
You still need your PVSRA and candlesticks. This indicator on its own may have a nice hit rate for scalping and building position, as an alternative to the TDI or alongside it, but it is not enough on its own, just like the TDI.
Enjoy!
Rolling Relative VolumeThis script sums the volume for the selected period and compares it to the selected period before that. It works on a rolling basis, so it is suitable for 24/7 markets such as crypto. That is the main difference between this and the regular RVOL indicator. Of course lower timeframes can also be selected for comparing changes in volume, but you should be aware how the times when markets are closed affect the calculation. For example, if used on stocks, the indicator will use the data that is available, meaning that the amount of data needed to calculate daily cumulative volume can be stretched out over a few days. If the stock session is 8 hours long, that comes out to 3 days.
There are 2 windows of reference when summing the volume:
1) The Recent volume window -> sums the volume between the current candle and the start of the window
2) The previous volume window -> sums the volume from the start of the current window until the start of the previous window
An example follows at the end :)
How to set up:
1) In settings, select the Timeframe; weekly, daily and hourly (W,D,H) are supported.
2) Choose the multiplier of the recent timeframe (for example 4 for cumulative volume over the last 4h)
3) Choose the multiplier of the previous timeframe (for example 8, if you want cumulative volume of the 8h before the start of the recent window)
Example:
Settings:
Timeframe: D
Recent volume multiplier: 3
Previous volume multiplier: 1
The chart set to 1h timeframe
This will calculate the cumulative volume for the past 24h, starting at the recent candle. Then it will calculate the cumulative volume for 72 hours before the start of the recent (24h) window. So in total it will need 24 + 72 = 96 hours of data to calculate.
After that it will compare the volume of the recent window with the average of the previous window. If values are above 1 the volume is increasing, if below 1 it is decreasing.
Why is this useful?
It's easy to spot changes in the volume and see if the volume is increasing and by how much, compared to previous days. Of course volume also drives liquidity. If volume is picking up, that could be the start of a bigger move.
WARNING!!!
Use on very low timeframes (1m, 3m) with big lookback periods (W) can break the script or make it execute very slowly due to the nature of the indicator.
Because this works on bar data it's possible that changing timeframes will change the calculation slightly. Generally, lower timeframes produce more accurate results, but take longer to calculate. The selected timeframe for the indicator should always be higher than the timeframe of the chart, otherwise the calculations won't make sense.
Leave a comment or send a DM for any improvements, bugs or ideas for automation / algo trading.
Y2050 Market Cap: GRINMethodology:
Composite of Bittrex and Poloniex to smoothen out the skewed values from lack of liquidity.
To be concise, the main advantage that a Y2050 market cap has over a 'regular' market cap is that it takes into account:
Inflation
What supply should be in the future
What the market cap could be in world of tomorrow
I'm having difficulty publishing the script so bear with me if the professional quality of the description is lacking. As always, I hope you are able to make use of this indicator and find new ways to create a consistent system to test out.
NB
Armando Bitmex Liquidation LevelsHi Guys!
- This script show you liquidations levels with leverage of 100X, 50X, 25X & 10X (shorts & longs).
- This indicator "only" works for XBT on Bitmex.
- Other indicators only show the liquidations up to 25X.
- You need to set the time frame according to your graph. e.g. 1, 60, 240, D, 3D, W, etc.
- The idea of this indicator is to help the user to determine those levels where Bitmex hunt liquidity.
Best Regards.
Armando M.
Thunder Cloud Suiteput together a few log space clouds generated by filled in MA's, 2 averages and a confirmed reversal meme i took from the gambit trading suite (dont have access to the code, made my own)
instructions
self explanatory by the pic above. long green bounces, short red ones.
no buzz words like liquidity. i apologize in advance. just trade the bloody thing
LongEntriesA composite signal only to be used by intraday traders . This was originally developed for Indian markets , NSE specifically , but can be applied in any other markets having equivalent liquidity. As the name suggests this currently work best for long signals.
BEATR CandlesThis script isolates candle sticks that are less than 50% of its range and those having range more than 100 period ATR.
These candles collectively help to follow the market movement based on the potential supply and demand nature of trading activities for a short period of time. This does not give any direct signal or does not scope for long term movement. Other parameters and the past movement of the price action can dictate the user to make decision on the potential validity of an entry/exit.
This can be applied to any market where the instruments have higher liquidity.
Pairs Volume FXCM mini accountScript shows the volume of the currency pairs in the FXCM mini account. I set it daily or weekly to see which pair is picking up in activity. My style of currency trading is short holds on the highest volatility. This helps me determine which pairs have the highest volume (or tick activity since there is no true exchange for currency). I use this in conjunction with the other script I wrote, "Pairs Range" which shows which pairs have the highest daily range. This script has a built in 5-sma on each pair. High daily range and high volume is volatility and liquidity. **** This does not include currencies in CHF ****
Forex Session OverlapApplies gray background coloring for each major active Forex session, the more sessions active the lighter the background. Adjusted coloring for low (Sydney, Tokyo) and high (Frankfurt, London, New York) liquidity. Market opening hours for Sydney, Tokyo, Frankfurt, London and New York have been set to 08:00 - 17:00 local time and are converted to EST while taking daylight saving time into account across regions (REMEMBER: configure manually!). Sessions can be turned on or off separately. By default this indicator hides itself in larger time-frames (>30min by default). Enabling session breaks or daily pivots helps distinguish between sessions.
SMC ICT – Simplified Daily Trend & Reversal AnalyzerThis Pine Script provides a simplified approach to analyzing daily trends and potential reversals using concepts inspired by Smart Money Concepts (SMC) and ICT (Inner Circle Trader).
What It Does:
• Detects daily uptrend and downtrend conditions by comparing the current daily high/low to the previous day’s values.
• Highlights potential bullish or bearish reversal zones when price behavior suggests a shift in sentiment.
• Automatically draws dashed lines for the previous day's high and low.
• Labels these high/low levels for quick visual reference.
How to Use:
Apply this indicator to any timeframe chart. Use the plotted trend markers to assess daily direction and potential reversal signals. The dashed lines (previous high/low) can be used as reference points for liquidity zones or break/retest entries.
User Interface:
The indicator displays labels and shapes in English. This script is intended for educational and trading workflow enhancement purposes.
Note:
This is an open-source tool designed for clarity and basic SMC/ICT application. It is best used in combination with other confluences like FVGs, order blocks, and liquidity sweeps.
CRT POSSIBILLITY INDCICATOR(V0.1)UNDER CONSTRUCTION!
This indicator is designed for traders who focus on liquidity grabs and smart money concepts (SMC). It identifies when the previous 1-hour high or low is swept (liquidity taken) and then waits for a 5-minute candle confirmation to validate the move.
Impulse Profile Zones [BigBeluga]🔵 OVERVIEW
Impulse Profile Zones is a volume-based tool designed to highlight high-impact candles and visualize hidden liquidity zones inside them using microstructure data. It’s ideal for identifying volume concentration and potential reaction points during impulsive market moves.
Whenever a candle exceeds a specified size threshold, this indicator captures its structure and overlays a detailed intrabar volume profile (from a 10x lower timeframe), allowing traders to analyze the distribution of interest within powerful market impulses.
🔵 CONCEPTS
Filters candles that exceed a user-defined threshold by size.
For qualifying candles, retrieves lower timeframe price and volume data.
Divides the candle’s body into 10 volume bins and calculates the volume per zone. Highlights the bin with the highest volume as the Point of Control (POC) .
Each POC line extends forward until a new impulse is detected.
🔵 FEATURES
Impulse Candle Detection:
Triggers only when a candle’s body size is larger than the defined threshold.
Lower Timeframe Profiling:
Aggregates 10-bin volume data from a lower timeframe (typically 1/10 of current TF).
Volume Distribution Bars:
Each bin displays a stylized bar using unicode block characters (e.g., ▇▇▇, ▇▇ or ▇--).
The bar size reflects the relative volume intensity.
POC Zone Mapping:
The bin with the highest volume is marked with a bold horizontal line.
Its value is labeled and extended until the next valid impulse.
🔵 HOW TO USE
Use large candle profiles to assess which price levels inside a move were most actively traded.
Watch the POC line as a magnet for future price interaction (support/resistance or reaction).
Combine with market structure or order block indicators to identify confluence levels.
Adjust the “Filter Large Candles” input to detect more or fewer events based on volatility.
🔵 CONCLUSION
Impulse Profile Zones is a hybrid microstructure tool that bridges lower timeframe volume with higher timeframe impulse candles. By revealing where most of the volume occurred inside large moves, traders gain a deeper view into hidden liquidity, enabling smarter trade entries and more confident profit-taking zones.
USDTUSD Stochastic RSI [SAKANE]Release Note
■ Overview
The USDTUSD Stochastic RSI indicator visualizes shifts in market sentiment and liquidity by applying the Stochastic RSI to the USDT/USD price pair.
Rather than tracking the price of Bitcoin directly, this tool observes the momentum of USDT, a key intermediary in most crypto transactions, to detect early signals of trend reversals.
■ Background & Motivation
USDT exhibits two distinct characteristics:
Its credibility as a long-term store of value is limited.
Yet, it serves as one of the most liquid assets in the crypto space and is widely used as a trading base pair.
Because most BTC trades involve converting fiat into USDT and vice versa, USDT/USD frequently deviates slightly from its peg to USD.
These deviations—though subtle—often occur just before major shifts in the broader crypto market.
This indicator is designed to detect such moments of structural imbalance by applying momentum analysis to USDT itself.
■ Feature Highlights
Calculates RSI and Stochastic RSI on the USDT/USD closing price
Supports customizable smoothing via SMA or EMA
Background shading dynamically visualizes overheated or cooled market states (thresholds are adjustable)
Displayed in a separate pane, keeping it visually distinct from the price chart
■ Usage Insights
This indicator is based on an observable pattern:
When the Stochastic RSI bottoms out, Bitcoin tends to form a price bottom shortly afterward
Conversely, when the indicator peaks, Bitcoin tends to top out with a slight delay
Since USDT acts as a gateway for capital in and out of the market, changes in its momentum often foreshadow turning points in BTC.
This allows traders to anticipate shifts in sentiment rather than merely reacting to them.
■ Unique Value Proposition
Unlike conventional price-based indicators, this tool offers a structural perspective.
It focuses on USDT as a mechanism of liquidity flow, making it possible to detect the "hidden rhythm" of the crypto market.
In that sense, this is not just a technical tool, but an entry point into market microstructure analysis—allowing users to read the market’s intentions rather than just its movements.
■ Practical Tips
Look for reversals in momentum as potential BTC entry or exit points.
Overlay this indicator with the BTC chart to compare timing and divergence.
Combine with other tools such as on-chain data or macro indicators for comprehensive analysis.
■ Final Thoughts
USDTUSD Stochastic RSI is designed with the belief that the most important market signals often come from what drives the price, not the price itself.
By tuning into the “heartbeat” of capital flow, this indicator sheds light on market dynamics that would otherwise remain unseen.
We hope it proves useful in your trading and research.
USDTUSD Stoh RSI [SAKANE]Release Note
■ Overview
The USDTUSD Stoch RSI indicator visualizes shifts in market sentiment and liquidity by applying the Stochastic RSI to the USDT/USD price pair.
Rather than tracking the price of Bitcoin directly, this tool observes the momentum of USDT, a key intermediary in most crypto transactions, to detect early signals of trend reversals.
■ Background & Motivation
USDT exhibits two distinct characteristics:
Its credibility as a long-term store of value is limited.
Yet, it serves as one of the most liquid assets in the crypto space and is widely used as a trading base pair.
Because most BTC trades involve converting fiat into USDT and vice versa, USDT/USD frequently deviates slightly from its peg to USD.
These deviations—though subtle—often occur just before major shifts in the broader crypto market.
This indicator is designed to detect such moments of structural imbalance by applying momentum analysis to USDT itself.
■ Feature Highlights
Calculates RSI and Stochastic RSI on the USDT/USD closing price
Supports customizable smoothing via SMA or EMA
Background shading dynamically visualizes overheated or cooled market states (thresholds are adjustable)
Displayed in a separate pane, keeping it visually distinct from the price chart
■ Usage Insights
This indicator is based on an observable pattern:
When the Stochastic RSI bottoms out, Bitcoin tends to form a price bottom shortly afterward
Conversely, when the indicator peaks, Bitcoin tends to top out with a slight delay
Since USDT acts as a gateway for capital in and out of the market, changes in its momentum often foreshadow turning points in BTC.
This allows traders to anticipate shifts in sentiment rather than merely reacting to them.
■ Unique Value Proposition
Unlike conventional price-based indicators, this tool offers a structural perspective.
It focuses on USDT as a mechanism of liquidity flow, making it possible to detect the "hidden rhythm" of the crypto market.
In that sense, this is not just a technical tool, but an entry point into market microstructure analysis—allowing users to read the market’s intentions rather than just its movements.
■ Practical Tips
Look for reversals in momentum as potential BTC entry or exit points.
Overlay this indicator with the BTC chart to compare timing and divergence.
Combine with other tools such as on-chain data or macro indicators for comprehensive analysis.
■ Final Thoughts
USDTUSD Stoch RSI is designed with the belief that the most important market signals often come from what drives the price, not the price itself.
By tuning into the “heartbeat” of capital flow, this indicator sheds light on market dynamics that would otherwise remain unseen.
We hope it proves useful in your trading and research.
SB TrendSB Trend Strategy Overview
The SB Trend Strategy is a quantitative, trend-following trading system designed to capture strong momentum moves in the stock market. Its primary objective is to optimize trade entries and exits to maximize profits during clear uptrends while limiting risk during market corrections.
Originally adapted from international momentum-based models, the strategy has been customized for the Vietnamese stock market, taking into account its specific conditions such as liquidity trends, volatility, and regulatory environment.
Core Principles
Trend-Focused Trading: The strategy only takes positions in the direction of confirmed market trends, avoiding trades that go against the prevailing direction.
Breakout-Driven Entries: Buy signals are generated when a stock breaks above a predefined price level, usually recent highs over a set lookback period.
Momentum-Based Exits: Positions are closed when momentum indicators indicate signs of trend weakness or potential reversals.
Selective Stock Universe: Trading is limited to stocks with strong liquidity and trading value to ensure efficient execution in the Vietnamese market context.
JPMorgan G7 Volatility IndexThe JPMorgan G7 Volatility Index: Scientific Analysis and Professional Applications
Introduction
The JPMorgan G7 Volatility Index (G7VOL) represents a sophisticated metric for monitoring currency market volatility across major developed economies. This indicator functions as an approximation of JPMorgan's proprietary volatility indices, providing traders and investors with a normalized measurement of cross-currency volatility conditions (Clark, 2019).
Theoretical Foundation
Currency volatility is fundamentally defined as "the statistical measure of the dispersion of returns for a given security or market index" (Hull, 2018, p.127). In the context of G7 currencies, this volatility measurement becomes particularly significant due to the economic importance of these nations, which collectively represent more than 50% of global nominal GDP (IMF, 2022).
According to Menkhoff et al. (2012, p.685), "currency volatility serves as a global risk factor that affects expected returns across different asset classes." This finding underscores the importance of monitoring G7 currency volatility as a proxy for global financial conditions.
Methodology
The G7VOL indicator employs a multi-step calculation process:
Individual volatility calculation for seven major currency pairs using standard deviation normalized by price (Lo, 2002)
- Weighted-average combination of these volatilities to form a composite index
- Normalization against historical bands to create a standardized scale
- Visual representation through dynamic coloring that reflects current market conditions
The mathematical foundation follows the volatility calculation methodology proposed by Bollerslev et al. (2018):
Volatility = σ(returns) / price × 100
Where σ represents standard deviation calculated over a specified timeframe, typically 20 periods as recommended by the Bank for International Settlements (BIS, 2020).
Professional Applications
Professional traders and institutional investors employ the G7VOL indicator in several key ways:
1. Risk Management Signaling
According to research by Adrian and Brunnermeier (2016), elevated currency volatility often precedes broader market stress. When the G7VOL breaches its high volatility threshold (typically 1.5 times the 100-period average), portfolio managers frequently reduce risk exposure across asset classes. As noted by Borio (2019, p.17), "currency volatility spikes have historically preceded equity market corrections by 2-7 trading days."
2. Counter-Cyclical Investment Strategy
Low G7 volatility periods (readings below the lower band) tend to coincide with what Shin (2017) describes as "risk-on" environments. Professional investors often use these signals to increase allocations to higher-beta assets and emerging markets. Campbell et al. (2021) found that G7 volatility in the lowest quintile historically preceded emerging market outperformance by an average of 3.7% over subsequent quarters.
3. Regime Identification
The normalized volatility framework enables identification of distinct market regimes:
- Readings above 1.0: Crisis/high volatility regime
- Readings between -0.5 and 0.5: Normal volatility regime
- Readings below -1.0: Unusually calm markets
According to Rey (2015), these regimes have significant implications for global monetary policy transmission mechanisms and cross-border capital flows.
Interpretation and Trading Applications
G7 currency volatility serves as a barometer for global financial conditions due to these currencies' centrality in international trade and reserve status. As noted by Gagnon and Ihrig (2021, p.423), "G7 currency volatility captures both trade-related uncertainty and broader financial market risk appetites."
Professional traders apply this indicator in multiple contexts:
- Leading indicator: Research from the Federal Reserve Board (Powell, 2020) suggests G7 volatility often leads VIX movements by 1-3 days, providing advance warning of broader market volatility.
- Correlation shifts: During periods of elevated G7 volatility, cross-asset correlations typically increase what Brunnermeier and Pedersen (2009) term "correlation breakdown during stress periods." This phenomenon informs portfolio diversification strategies.
- Carry trade timing: Currency carry strategies perform best during low volatility regimes as documented by Lustig et al. (2011). The G7VOL indicator provides objective thresholds for initiating or exiting such positions.
References
Adrian, T. and Brunnermeier, M.K. (2016) 'CoVaR', American Economic Review, 106(7), pp.1705-1741.
Bank for International Settlements (2020) Monitoring Volatility in Foreign Exchange Markets. BIS Quarterly Review, December 2020.
Bollerslev, T., Patton, A.J. and Quaedvlieg, R. (2018) 'Modeling and forecasting (un)reliable realized volatilities', Journal of Econometrics, 204(1), pp.112-130.
Borio, C. (2019) 'Monetary policy in the grip of a pincer movement', BIS Working Papers, No. 706.
Brunnermeier, M.K. and Pedersen, L.H. (2009) 'Market liquidity and funding liquidity', Review of Financial Studies, 22(6), pp.2201-2238.
Campbell, J.Y., Sunderam, A. and Viceira, L.M. (2021) 'Inflation Bets or Deflation Hedges? The Changing Risks of Nominal Bonds', Critical Finance Review, 10(2), pp.303-336.
Clark, J. (2019) 'Currency Volatility and Macro Fundamentals', JPMorgan Global FX Research Quarterly, Fall 2019.
Gagnon, J.E. and Ihrig, J. (2021) 'What drives foreign exchange markets?', International Finance, 24(3), pp.414-428.
Hull, J.C. (2018) Options, Futures, and Other Derivatives. 10th edn. London: Pearson.
International Monetary Fund (2022) World Economic Outlook Database. Washington, DC: IMF.
Lo, A.W. (2002) 'The statistics of Sharpe ratios', Financial Analysts Journal, 58(4), pp.36-52.
Lustig, H., Roussanov, N. and Verdelhan, A. (2011) 'Common risk factors in currency markets', Review of Financial Studies, 24(11), pp.3731-3777.
Menkhoff, L., Sarno, L., Schmeling, M. and Schrimpf, A. (2012) 'Carry trades and global foreign exchange volatility', Journal of Finance, 67(2), pp.681-718.
Powell, J. (2020) Monetary Policy and Price Stability. Speech at Jackson Hole Economic Symposium, August 27, 2020.
Rey, H. (2015) 'Dilemma not trilemma: The global financial cycle and monetary policy independence', NBER Working Paper No. 21162.
Shin, H.S. (2017) 'The bank/capital markets nexus goes global', Bank for International Settlements Speech, January 15, 2017.