Flowlyindicators — Indicators and Strategies

Open interest flow / Flowly Indicators - Overview 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. 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. - Concept Open interest flow is calculated using position of OI source relative to its moving average (by default set to SMA 10), referred to as relative open interest from hereon. When relative OI is positive (open interest is above its moving average), new positions are considered to enter the market. When relative OI is negative (open interest is below its moving average), existing positions are considered to exit the market. Open interest delta (side opening/closing positions, either net buyers/sellers) is calculated using relative price in a similar fashion to relative OI, but using close of viewed symbol as source. Price is considered to be up when relative price is positive, down when relative price is negative. Using relative OI and relative price in tandem, the following assumptions are applied: Price up, open interest up = longs entering market Price down, open interest up = shorts entering market Price down, open interest down = longs exiting market Price up, open interest down = shorts exiting market Bands depicting magnitude of open interest flows are calculated using average turning points in relative OI. +1 and -1 represent levels where flows on average turn towards mean rather than continue to increase/decrease. These levels are then multiplied up to +2 and -2, representing two times larger deviations from the normal. When inflows are above 1, positions opening have reached a point where flows historically turn down. Therefore, anything above 1 would be abnormal amount of open interest entering, an extreme stretch being at 2 or above. Same logic applies to outflows, but in a vice versa manner (below -1 abnormal, extreme at -2) Flow bursts further refine indications of aggressive inflows/outflows by taking into account change in open interest flows. Burst indications are activated when open interest is above its average turning point, coupled with a sufficient increase/decrease in flows simultaneously. Bursts are essentially a filtered version of abnormal flows and therefore a more reliable indication of exuberance/liquidations. Burst sensitivity can be adjusted via input menu, available in 5 settings. 1 sets OI burst requirements to loosest (more signals, more noise) while 5 sets OI burst requirements to strictest (less signals, less noise). Exact criteria applied to bursts can be viewed via input menu tooltip. - Features Users can opt for OI source auto-select for CRYPTO/USDT pairs. When auto-select is enabled and another chart is opened, corresponding open interest source is automatically selected as long as requirements mentioned above are met. Open interest flows can be visualized as chart color, available separately for flow states and flow bursts. Relative price line and flow guidelines (reminders for flow interpretation) can be enabled via input menu. All colors are customizable. - Alerts Available alerts are the following: - Abnormal long inflows/outflows - Abnormal short inflows/outflows - Abnormal inflows/outflows from either side - Aggressive longs/shorts (flow burst up) - Liquidated longs/shorts (flow burst down) - Aggressive or liquidated longs/shorts - Practical guide 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. 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.

Volume composition / Flowly Indicators — Overview While net volume is useful information, it can be a blunt data point. Volume composition breaks down the content of volume, allowing a more detailed look inside each volume node. Volume composition consists of the following information: 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. Buy and sell volume is defined by volume associated with lower timeframe up/down moves. This classification is further broken down to passive/active, standing for decreasing/increasing volume, e.g. a move up with volume higher than previous bar volume = active buy volume, a move up with volume lower than previous bar volume = passive buy volume. Volume data is fetched from a lower timeframe that is automatically adjusted to fit the timeframe you're using. By default, the following settings are applied: Charts <= 30 min: 1 minute timeframe Charts > 30 min & <= 3 hours : 5 minute timeframe Charts > 3 hours & <= 8 hours : 15 minute timeframe Charts > 8 hours & <= 1D: 1 hour timeframe Charts > 1D & <= 3D : 2 hour timeframe Charts > 3D: 4 hour timeframe Timeframe settings can be changed via input menu. The lower the timeframe, the more precision you get but with the cost of less historical data and slower loading time. Users can also choose which source to use for determining buy/sell volume, e.g. using close as source, a close that is higher than previous close would be considered as buy volume. This could be replaced with OHLC4 for example, resulting in a volume direction based on OHLC average. Volume composition of current chart can also be replaced with any other chart volume composition: — Visuals Breakdown of visual elements: 1. Symbol and timeframe used for volume composition calculations. By default the chart that is viewed and automatically selected lower timeframe. 2. Dominating volume threshold exceeded. Can be defined via input menu, 70% of total volume by default. 3. Dominating volume as percentage of total volume. Plotted below volume nodes, without % symbol. 4. Dominating active volume, + or - symbol, standing for buy and sell. Plotted below dominating volume percentage. When dominating volume and dominating active volume sides are in a disagreement (e.g. dominating volume is on buy side while dominating active volume is on sell side) this symbol will appear inside brackets, (+) or (-). 5. Dominating active volume as percentage of total active volume. Plotted below +/- symbol. 6. Dominating active volume threshold exceeded. Can be defined via input menu, 70% by default. Dominating volume & active volume percentages can be rounded to single numbers to avoid clutter caused by overlapping values. The percentage values will be rounded to closest single number value, e.g. dominating volume percentage at 54% = 5, dominating volume percentage at 55% = 6. Volume anomalies can be highlighted on the chart with a color for studying the events and their past implications in greater detail. Available anomalies for highlights are the following: Buy volume threshold exceeded Sell volume threshold exceeded Active buy volume threshold exceeded Active sell volume threshold exceeded Volume & active volume divergence — Practical guide Volume is arguably one of the most important data points as it directly relates to liquidity. High volume can be an indication of strength (price likely to continue moving) or absorption (price likely to halt/turn). Same applies to active volume, but with an element of aggression. High active volume serves as an indication of exuberance or otherwise forceful transacting, like stop losses triggering. With these principles in mind, the composition of volume allows distinguishing potentially important events. Example #1 : Identifying 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. Example #2 : Identifying 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. Example #3 : Identifying inflection points 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.

Session candles & reversals / Flowly Indicators — Overview Like traditional candles, 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). 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. By default, following session time periods are used: Session #1: London (08:00 - 17:00, UTC) Session #2: New York (13:00 - 22:00, UTC) Session #3: Sydney (21:00 - 06:00, UTC) Session #4: Tokyo (00:00 - 09:00, UTC) Session time periods can be changed via input menu. — Reversals Session reversals are patterns that show a rapid change in direction during session. These formations are more familiarly known as wicks or engulfing candles. Following criteria must be met to qualify as a session reversal: Wick up: Lower high, lower low, close >= 65% of session range (0% being the very low, 100% being the very high) and open >= 40% of session range. Wick down: Higher high, higher low, close <= 35% of session range and open <= 60% of session range. Engulfing up: Higher high, lower low, close >= 65% of session range. Engulfing down: Higher high, lower low, close <= 35% of session range. Session reversals are always based on prior corresponding session , e.g. to qualify as a NY session engulfing up, NY session must have a higher high and lower low relative to prior NY session , not just any session that has taken place in between. Session reversals should be viewed the same way wicks/engulfing formations are viewed on traditional timeframe based candles. Essentially, wick reversals (light green/red labels) tell you most of the motion during session was reversed. Engulfing reversals (dark green/red labels) on the other hand tell you all of the motion was reversed and new direction set. — Backtesting Session reversals are backtested using win rate and magnitude metrics. A session reversal is considered successful when next corresponding session closes higher/lower than session reversal close . Win rate is formed by dividing successful session reversal count with total reversal count, e.g. 5 successful reversals up / 10 reversals up total = 50% win rate. Win rate tells us what are the odds (historically) of session reversal producing a clean supporting move that was persistent enough to close that way too. When a session reversal is successful, its magnitude is measured using percentage increase/decrease from session reversal close to next corresponding session high/low . If NY session closes higher than prior NY session that was a reversal up, the percentage increase from prior session close (reversal close) to current session high is measured. If NY session closes lower than prior NY session that was a reversal down, the percentage decrease from prior session close to current session low is measured. Average magnitude is formed by dividing all percentage increases/decreases with total reversal count, e.g. 10 total reversals up with 1% increase each -> 10% net increase from all reversals -> 10% total increase / 10 total reversals up = 1% average magnitude. Magnitude metric supports win rate by indicating the depth of successful session reversal moves. To better understand the backtesting calculations and more importantly to verify their validity, backtesting visuals for each session can be plotted on the chart: All backtesting results are shown in the backtesting panel on top right corner, with highest win rates and magnitude metrics for both reversals up and down marked separately. Note that past performance is not a guarantee of future performance and session reversals as they are should not be viewed as a complete strategy for long/short plays. Always make sure reversal count is sufficient to draw reliable conclusions of performance. — Session moving average Users can form a session based moving average with their preferred smoothing method (SMA , EMA , HMA , WMA , RMA) and length, as well as choose which sessions to include in the moving average. For example, a moving average based on New York and Tokyo sessions can be formed, leaving London and Sydney completely out of the calculation. — Visuals By default, script hides your candles/bars, although in the case of candles borders will still be visible. Switching to bars/line will make your regular chart visuals 100% hidden. This setting can be turned off via input menu. As some sessions overlap, each session candle can be separately offsetted forward, clearing the overlaps. Users can also choose which session candles to show/hide. Session periods can be highlighted on the chart as a background color, applicable to only session candles that are activated. By default, session reversals are referred to as L (London), N (New York), S (Sydney) and T (Tokyo) in both reversal labels and backtesting table. By toggling on "Numerize sessions", these will be replaced with 1, 2, 3 and 4. This will be helpful when using a custom session that isn't any of the above. Visual settings example: Session candles are plotted in two formats, using boxes and lines as well as plotcandle() function. Session candles constructed using boxes and lines will be clear and much easier on the eyes, but will apply only to first 500 bars due to Tradingview related limitations. Rest of the session candles go back indefinitely, but won't be as clean: All colors can be customized via input menu. — Timeframe & session time period considerations As a rule of thumb, session candles should be used on timeframes at or below 1H, as higher timeframes might not match with session period start/end, leading to incorrect plots. Using 1 hour timeframe will bring optimal results as greatest amount historical data is available without sacrificing accuracy of OHLC values. If you are using a custom session that is not based on hourly period (e.g. 08:00 - 15:00 vs. 08.00 - 15.15) make sure you are using a timeframe that allows correct plots. Session time periods applied by default are rough estimates and might be out of bounds on some charts, like NYSE listed equities. This is rarely a problem on assets that have extensive trading hours, like futures or cryptocurrency. If a session is out of bounds (asset isn't traded during the set session time period) the script won't plot given session candle and its backtesting metrics will be NA. This can be fixed by changing the session time periods to match with given asset trading hours, although you will have to consider whether or not this defeats the purpose of having candles based on sessions. — Practical guide Whether based on traditional timeframes or sessions, reversals should always be considered as only one piece of evidence of price turning. Never react to them without considering other factors that might support the thesis, such as levels and multi-timeframe analysis. In short, same basic charting principles apply with session candles that apply with normal candles. Use discretion. Example #1 : Focusing 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. Example #2 : Focusing efforts on highest performing reversals and avoiding 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. Example #3 : Reversal clusters 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.

Time & volume point of control / Flowly Indicators What are TPOC & VPOC? TPOC (time point of control) and VPOC (volume point of control) are points in price where highest amount of time/volume was traded. 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). The script hides your candles/bars by default and forms a line in the middle representing candle range. In case of candles, borders will still be visible. This feature can be turned off in the settings. Volume and time data are fetched from a lower timeframe that is automatically adjusted to fit the timeframe you're using. By default, the following settings are applied: Charts <= 30 min: 1 minute timeframe Charts > 30 min & <= 3 hours : 5 minute timeframe Charts > 3 hours & <= 8 hours : 15 minute timeframe Charts > 8 hours & <= 1D: 1 hour timeframe Charts > 1D & <= 3D : 2 hour timeframe Charts > 3D: 4 hour timeframe Timeframe settings can be changed via input menu. The lower the timeframe, the more precision you get but with the cost of less historical data and slower loading time. Users can also choose which source to use for determining price for points of control, e.g. using close as source, the point of control is set to match the value of lower timeframe candle close. This could be replaced with OHLC4 for example, resulting in a point of control based on OHLC average. To identify more profound points of market participant interest, TPOC & VPOC as percentage of total time/volume thresholds can be set via input menu. When a point of control is equal to or greater than the set percentage threshold, visual elements will be highlighted in a different color, e.g. 50% VPOC threshold will activate a highlight whenever volume traded at VPOC is equal to or greater than 50% of total volume. All colors are customizable. VPOC is defined by fetching lower timeframe candle with the most amount of volume traded and using its close (by default) as a mark for point of control. For TPOC, each candle is divided into 10 lots which are used for calculating amount of closes taking place within the bracket values. The lot with highest amount of closes will be considered a point of control. This mark is displayed in the middle point of a lot: How to utilize TPOC & VPOC Example #1: 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: Example #2: 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: Example #3: POC supported trend 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: