Many of our open source tools have gained recognition that we truly did not expect: hundreds of comments, hundreds in donations (a big thanks!) and a few Editors' Picks nominations. One particularly appreciated addition on our publications is the Practical guide section, covering ideas for using the tools in practical ways that can be applied to real world use cases.

Here's our 10 most popular open source market analysis tools and 24 ways to trade them. Covering a variety of concepts from volatility, volume, open interest to market breadth. Aggregated, updated and expanded with practical examples not published before.

🛠️ Tool #1: Broad market index

Broad market index is a market breadth based oscillator, depicting broad market trend by analysing ratio between symbols moving up and symbols moving down in a given market. When market breadth is positive, more symbols are going up and when negative, more symbols are going down. As markets tend to correlate, broad market trend dictates likely path for all individual symbols that make up the market.

Broad market index / quantifytools


This tool provides market breadth for US equities (based on NYSE advancers - decliners) and ability to build two custom breadth baskets with up to 39 symbols included in each. Market breadth can be customized with variety of smoothing options, weighting and threshold modes to find most optimal rules for trend following. Performance of the model is reflected on metrics showing percentage of up/down moves during bullish/bearish states.

💭 Way #1: Follow broad market trend

The utility of market breadth is based on the idea that markets correlate and individual symbols making up the market will eventually join the broad market trend. With this in mind, going against broad market is like swimming upstream, it's going to be the hard way. A well performing basket with clear skew for upside and downside on respective breadth states can be used to form directional bias for trades and risk on/off regimes for investing.

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💭 Way #2 : Catch broad market reversals

Thrusts signify two things: a historical extreme in breadth and an aggressive move to the opposite direction. Thrusts are valuable clues for exhaustion in broad market trend, potentially leading to a reversal.

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💭 Way #3: Identify unsustainable trends

Market breadth and price diverging signify events where most symbols that make up the market are going one way but a few high weight symbols (big tech for SP500) are going the other way. In other words, only a few symbols are moving the market while general interest and intention is to the other direction. Divergences in breadth and price are not ideal for sustainable trend and can be expected to eventually revert to the direction of broad market.

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🛠️ Tool #2: Volume composition

Volume composition breaks down the content of volume, allowing a more detailed look inside each volume node. In this tool, volume types are divided into buy and sell volume and further broken down to active (rising) and passive (falling) volume.

Volume composition / quantifytools


Volume types are visually classified as follows:

Total volume (buy and sell). By default gray node.
Dominating volume (buy or sell). By default dark green/dark red node.
Dominating active volume (buy or sell). By default light green/light red node.
Dominating volume as percentage of total volume.
Dominating active volume as percentage of total active volume.

💭 Way #4: Identify areas of trapped market participants

Often when volume spikes distinctively, we can make the case that price has found sufficient liquidity to halt/turn. Since we know which side was absorbed, in what quantity and type (passive/active), we can identify areas of trapped market participants. In such scenarios, the higher the dominant active volume and volume spike itself, the better.

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💭 Way #5: Identify a healthy trend

A healthy trend is one that has an active and consistent bid driving it. When this is the case, it can be seen in consistently supportive active volume.

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💭 Way #6: Identify inflection points, prepare for expansion

When dominant side of volume and dominant side of active volume diverge, something is up. A divergence often marks an area of indecision, hinting an imminent move one way or the other.

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🛠️ Tool #3: Fair value bands

Fair value bands depict dynamic points in price where price behaviour is normal or abnormal, i.e. trading at/around mean (price at fair value) or deviating from mean (price outside fair value).

Fair value bands / quantifytools


Unlike constantly readjusting standard deviation based bands, fair value bands are designed to be smooth and constant, based on typical historical deviations. The script calculates pivots that take place above/below fair value basis and forms median deviation bands based on this information. These points are then multiplied up to 3, representing more extreme deviations.

💭 Way #7: Risk on at fair value, risk off outside fair value

Ideal trend stays inside fair value and provides sufficient cool offs between the moves. When this is the case, fair value bands can be used for sensible entry/exit levels within the trend.

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💭 Way #8: Catch reversals at extremes

When price shows exuberance into an extreme deviation, followed by a stall and signs of exhaustion (wicks), an opportunity for mean reversion emerges. The higher the deviation, the more volatility in the move, the more signalling of exhaustion, the better.

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💭 Way #9: Customize the bands to suit your needs

The faster the length of fair value basis, the more momentum price needs to hit extreme deviation levels, as bands too are moving faster alongside price. Decreasing fair value basis length typically leads to more quick and aggressive deviations and less steady trends outside fair value.

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🛠️ Tool #4: Time & volume point of control

Time & volume point of control detects key points of control found on market profile indicators. Time & volume POC's are points in price where highest amount of time/volume was traded.

Time & volume point of control / quantifytools


This is considered key information in a market profile, as it shows where market participant interest was highest. Unlike full fledged market profile that shows total time/volume distribution, this script shows the points of control for each candle, plotted with a line (time) and a dot (volume)

💭 Way #10: Identify trapped market participants

One or both points of control at one end of candle range (wick tail) and candle close at the other end serves as an indication of market participants trapped in an awkward position. When price runs away further from these trapped participants, they are eventually forced to cover and drive price even further to the opposite direction:

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💭 Way #11: Identify trend initiation

A large move that leaves TPOC behind while VPOC is supportive serves as an indication of a trend initiation. Essentially, this is one way to identify an event where price traded sideways most of the time and suddenly moved away with volume:

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💭 Way #12: Identify a strong trend supported by POC

A trend is healthy when it's supported by a point of control. Ideally you want to see either time or volume supporting a trend:

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🛠️ Tool #5: Session candles & reversals

Session based candles are a visualization of open, high, low and close values, but based on session time periods instead of typical timeframes such as daily or weekly. Session candles are formed by fetching price at session start (open), highest price during session (high), lowest price during session (low) and price at session end (close).

Session candles & reversals / quantifytools


On top of candles, session based moving average is formed and session reversals detected. Session reversals are also backtested, using win rate and magnitude metrics to better understand what to expect from session reversals and which ones have historically performed the best.

💭 Way #13: Focus efforts on session reversals at distinct support/resistance levels

A reversal against a level holds more value than a reversal by itself, as you know it's a placement where liquidity can be expected. A reversal serves as a confirming reaction for this expectation.

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💭 Way #14: Focus efforts on highest performing reversals, avoid poorly performing ones

As you have data backed evidence of session reversal performance, it makes sense to focus your efforts on the ones that perform best. If some session reversal is clearly performing poorly, you would want to avoid it, since there's nothing backing up its validity.

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💭 Way #15: Identify session reversals reliably

Two is better than one, three is better than two and so on. If there are rapid changes in direction within multiple sessions consecutively, there's heavier evidence of a dynamic shift in price. In such case, it makes sense to hold more confidence in price halting/turning.

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🛠️ Tool #6:: Open interest flow

Open interest flow detects inflows (positions opening) and outflows (positions closing) using open interest and estimates delta (net buyers/sellers) for the flows. Users are able to choose any open interest source available on Tradingview, by default set to BTCUSDT OI fetched from Binance.

Open interest flow / quantifytools


Using historical open interest flows, bands depicting typical magnitude of flows are formed for benchmarking intensity of flows. On the inflow side, +1 represents average inflows while +2 represents 2x above average inflows, a level considered an extreme. In a vice versa manner, -1 represents average outflows while -2 represents 2x above average outflows. Extreme inflows indicate aggressive position opening, in other words exuberance. Extreme outflows on the other hand indicate forced exiting of positions, in other words liquidations.

💭 Way #16: Identify greed/fear by gauging inflows/outflows

Open interest as a standalone data point does not reveal which side is likely opening/exiting positions and how extreme the participant behavior is. Using the additional data provided by open interest flows, moments of greed and fear can be detected. Smart money does not short into dips and buy into rips. When buyers or sellers have participated in a large move and continue to show interest even when efforts are not rewarded at an already overextended price, participants are asking for trouble.

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💭 Way #17: Identify liquidations

Similar events can be observed when extreme outflows take place, indicating forced exits such as stop-losses triggering. When enough participants are forced out, price is likely to take the path of least resistance which is to the opposite direction.

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🛠️ Tool #7: Volatility patterns

Volatility patterns detect various forms of indecisive price action, on a larger scale as a compressed range and on a smaller scale as indecision candles. Indecisive and volatility suppressing price action can be thought of as a spring being pressed down.

Volatility patterns / quantifytools


The more suppression, the more tension is built and eventually released as a spike or series of spikes in volatility. Each volatility pattern is assigned an influence period, during which average and peak relative volatility is recorded and stored to volatility metrics.

💭 Way #18: Navigate volatility

Volatility is not a bad thing from a trading perspective, but can actually be fertile ground for executing trade setups. Trading volatility influence periods from higher timeframes on lower timeframes gives greater resolution to work with and opportunities to take advantage of the wild swings created.

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💭 Way #19: Find bias for volatility patterns

Points of confluence where it anyway makes sense to favor one side over the other can be used for establishing bias for indecisive price action as well. At face value, it makes sense to expect bearish reactions at range highs and bullish reactions at range low, for which volatility patterns can provide a catalyst.

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💭 Way #20: Bet on initiation

Betting on direction of the first volatile move can easily go against you, but if risk/reward is able to compensate for the poor win rate, it's a valid idea to consider and explore.

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🛠️ Tool #8: Bar metrics

Rather than eyeball evaluating bullishness/bearishness in any given bar, bar metrics allow a quantified approach using three basic fundamental data points: relative close, relative volatility and relative volume. These data points are visualized in a discreet data dashboard form, next to all real-time bars. Each value also has a dot in front, representing color coded extremes in the values.

Bar metrics / quantifytools


Relative close represents position of bar's close relative to high and low, high of bar being 100% and low of bar being 0%. Relative close indicates strength of bulls/bears in a given bar, the higher the better for bulls, the lower the better for bears. Relative volatility (bar range, high - low) and relative volume are presented in a form of a multiplier, relative to their respective moving averages (SMA 20).

A value of 1x indicates volume/volatility being on par with moving average, 2x indicates volume/volatility being twice as much as moving average and so on. Relative volume and volatility can be used for measuring general market participant interest, the "weight of the bar" as it were.

💭 Way #21: Identify bullish/bearish impulses

By configuring bar metrics to highlight exuberant bullish bars (high volume/volatility and close at highs), we can identify bullish impulses in a simple, yet effective way. Impulsive moves can mark either initiation (price likely to continue in the initiated direction) or exhaustion (price likely to reverse)

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Same impulses can be identified for the downside by simply creating a close at lows condition.

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🛠️ Tool #9: Global & local RSI

As the terms global and local imply, global RSI describes broad relative strength, whereas local RSI describes local relative strength within the broad moves. A macro and micro view of relative strength so to speak. Global and local RSI are simply regular RSI and stochastic RSI.

Global & local RSI / quantifytools


Local RSI extremes ( stochastic RSI oversold/overbought) often mark a pivot in RSI which naturally reflects to price. Local RSI extremes are visualized inside the global RSI bands (upper band for overbought, lower band for oversold) in a "heat map" style.

💭 Way #22: Identify local extremes in RSI

As an oscillator, RSI depicts extreme when above or below extreme values (above 70, below 30) but that does not mean RSI is not at an extreme in between. The benefit of having a stochastic RSI extremes on the side (visualized using heatmap color on upper and lower bands) is being able to identify local extremes in the broader moves.

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💭 Way #23: Identify hidden reversals

RSI visualized in candles has a special quality: hidden reversals. Hidden reversals are candles with a wick-ish shape in relative strength, which are not always seen on the main chart itself.

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🛠️ Tool #10: Auto-magnifier

Auto-magnifier shows a lower timeframe view of candles and volume bars inside any main timeframe candle by zooming into it. Candles and volume bars as they develop are shown chronologically from left to right. By default, magnifier is triggered when less than 3 candles are visible on the chart.

Auto-magnifier / quantifytools


By default, 20 lower timeframe candles are displayed by splitting main timeframe into 20 parts. The amount of candles displayed is a target rate, meaning the script will use a lower timeframe that has the closest match to 20 candles and therefore will vary a bit. Users can override automatic timeframe calculation and opt in to display any specific lower timeframe or adjust amount of candles shown (e.g. 20 -> 30 candles) per each main timeframe candle.

💭 Way #24: Navigate lower timeframe resistance/support

Auto-magnifier gives a quick and easy access to a lower timeframe view of any main timeframe candle. With greater resolution, more distinct support/and resistance levels can be spotted by looking for a re-test of points of interest (preferably with signs of exhaustion as well)

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