Papercuts Price Distance TravelledPapercuts Price Distance Travelled
aka
Maximum Per-Share Profit Potential
For: Intraday swing and scalp Traders.
This is a simple idea i wanted to explore where you could visualize the data of how much a price actually moves during the day.
Measuring through Daily ATR is helpful, but it only measures OHLC of the day, and way more tradeable movement happens than that.
So this measures movement a different way to increase perspective and awareness of price action.
Its like taking a pleated filter and unpleating it, which reveals a way longer structure.
It does this by aggregating the path of travel of an RSVAEMA (Relative Strength Volume Adjusted EMA) and returns the absolute value of its results.
Then it resets this daily, and returns the peak into an array that gets averaged.
This is helpful for seeing how normal or abnormal a days move might actually be. Many days feel extreme, but they are not, and vice versa.
This can be utilized to see how much movement actually happens at different levels. TSLA on 5m is an average daily movement of around 20$, but TSLA 15sec chart shows an average movement of around 100$. Pretty insane.
Educational
Arbitrage SpreadThis indicator helps to find spreads between cryptocurrencies, assess their correlation, spread, z score and atr z score.
The graphs are plotted as a percentage. Because of the limitation in pine tradingview for 5000 bars a period was introduced (after which a new starting point of the graph construction will be started), if you want it can be disabled
The multiplier parameter affects only the construction of the joint diagram on which z score and atr z score are calculated (construction of the diagram is done by dividing one pair by another and multiplying by the multiplier parameter) is shown with a red line
To create a notification you have to specify the data for parameters other than zero which you want to monitor. For parameters z score and atr z score data are counted in both directions
The data can be tracked via the data window
Link to image of the data window prnt.sc
Rounded Forex Levels: Big-Figure, Mid-Figure, 80-20 levels, BFRNSimple indicator to show Rounded levels in typical Forex pairs: Big figure, Mid-figure, 80-20 Insitutional Levels, 10pip levels, 5pip levels
Wrote this indicator because other ones out there seem to clutter the chart. This is simple, low-clutter and can be set by user to have arbitrary start and end points for the lines.
I wanted the ability for lines to plot discreetly to the right hand side of price as in the chart above, since in my opinion, these are only of secondary consideration to a trader, an extra confirmation/confluence to an existing idea.
//Purpose & Usage:
-Big-figure levels (100pips) & Mid-figure levels (50pips) will have a senstitivity to price, that can be an additional tool when looking for confluence for a target or an entry.
-As well as BF levels and MF levels; Institutional levels (20pips below and 20 pips above a Big Figure level) and standard 10pip or 5pip levels, can be useful in the right context (i.e added confirmation that of a minor sweep target; added conviction in an idea if the level aligns with another seperately derived level).
//User inputs:
-Toggle on/off each of the types of level.
-Line spacing: choose pip spacing of lines .
-Number of lines above/below (i.e. setting of 5 will be 11 lines. One central, 5 above, 5 below).
-Formatting: for each class of lines, code by color, style and width (as per the example chart below).
-Line start offset and line end offset: bars forward/back for each of start point and end point. So lines could be spread right across chart; or neatly pushed to the far right or left of the chart.
//Notes:
-Designed for typical Forex pairs with units close to 1.0 (like Eur/Usd, Usd/Cad, Aud/Usd, Gbp/Usd, Eur/Gbp, Nzd/Usd).
-Lines are based from the rounded close of the previous bar, Updating (if applicable) on each new bar.
Demo Plotting levels in the past; Dialog box example display:
Inversion GapsAn inverted fair value gap (FVG) occurs when candles start closing below a bullish FVG or above a bearish FVG and in this case, support FVGs become resistances and vice versa. This is a smart money concept introduced by ICT. While we a number of have indicators for FVGs, we don't have any for inversion FVGs. This indicator is just for that - it shows FVGs only after they're inverted.
The meat of it comes from being able to plot HTF inverted FVGs in LTF. In the above BTC chart, you can see M15 inverted FVGs plotted on M1 chart and you can see price respecting them. Mitigations can also be shown as lines (as you can see in the chart).
You can also setup alerts for formation and mitigation of such inversion FVGs.
ICT Concepts [LuxAlgo]The ICT Concepts indicator regroups core concepts highlighted by trader and educator "The Inner Circle Trader" (ICT) into an all-in-one toolkit. Features include Market Structure (MSS & BOS), Order Blocks, Imbalances, Buyside/Sellside Liquidity, Displacements, ICT Killzones, and New Week/Day Opening Gaps.
🔶 SETTINGS
🔹 Mode
When Present is selected, only data of the latest 500 bars are used/visualized, except for NWOG/NDOG
🔹 Market Structure
Enable/disable Market Structure.
Length: will set the lookback period/sensitivity.
In Present Mode only the latest Market Structure trend will be shown, while in Historical Mode, previous trends will be shown as well:
You can toggle MSS/BOS separately and change the colors:
🔹 Displacement
Enable/disable Displacement.
🔹 Volume Imbalance
Enable/disable Volume Imbalance.
# Visible VI's: sets the amount of visible Volume Imbalances (max 100), color setting is placed at the side.
🔹 Order Blocks
Enable/disable Order Blocks.
Swing Lookback: Lookback period used for the detection of the swing points used to create order blocks.
Show Last Bullish OB: Number of the most recent bullish order/breaker blocks to display on the chart.
Show Last Bearish OB: Number of the most recent bearish order/breaker blocks to display on the chart.
Color settings.
Show Historical Polarity Changes: Allows users to see labels indicating where a swing high/low previously occurred within a breaker block.
Use Candle Body: Allows users to use candle bodies as order block areas instead of the full candle range.
Change in Order Blocks style:
🔹 Liquidity
Enable/disable Liquidity.
Margin: sets the sensitivity, 2 points are fairly equal when:
'point 1' < 'point 2' + (10 bar Average True Range / (10 / margin)) and
'point 1' > 'point 2' - (10 bar Average True Range / (10 / margin))
# Visible Liq. boxes: sets the amount of visible Liquidity boxes (max 50), this amount is for Sellside and Buyside boxes separately.
Colour settings.
Change in Liquidity style:
🔹 Fair Value Gaps
Enable/disable FVG's.
Balance Price Range: this is the overlap of latest bullish and bearish Fair Value Gaps.
By disabling Balance Price Range only FVGs will be shown.
Options: Choose whether you wish to see FVG or Implied Fair Value Gaps (this will impact Balance Price Range as well)
# Visible FVG's: sets the amount of visible FVG's (max 20, in the same direction).
Color settings.
Change in FVG style:
🔹 NWOG/NDOG
Enable/disable NWOG; color settings; amount of NWOG shown (max 50).
Enable/disable NDOG ; color settings; amount of NDOG shown (max 50).
🔹 Fibonacci
This tool connects the 2 most recent bullish/bearish (if applicable) features of your choice, provided they are enabled.
3 examples (FVG, BPR, OB):
Extend lines -> Enabled (example OB):
🔹 Killzones
Enable/disable all or the ones you need.
Time settings are coded in the corresponding time zones.
🔶 USAGE
By default, the indicator displays each feature relevant to the most recent price variations in order to avoid clutter on the chart & to provide a very similar experience to how a user would contruct ICT Concepts by hand.
Users can use the historical mode in the settings to see historical market structure/imbalances. The ICT Concepts indicator has various use cases, below we outline many examples of how a trader could find usage of the features together.
In the above image we can see price took out Sellside liquidity, filled two bearish FVGs, a market structure shift, which then led to a clean retest of a bullish FVG as a clean setup to target the order block above.
Price then fills the OB which creates a breaker level as seen in yellow.
Broken OBs can be useful for a trader using the ICT Concepts indicator as it marks a level where orders have now been filled, indicating a solidified level that has proved itself as an area of liquidity. In the image above we can see a trade setup using a broken bearish OB as a potential entry level.
We can see the New Week Opening Gap (NWOG) above was an optimal level to target considering price may tend to fill / react off of these levels according to ICT.
In the next image above, we have another example of various use cases where the ICT Concepts indicator hypothetically allow traders to find key levels & find optimal entry points using market structure.
In the image above we can see a bearish Market Structure Shift (MSS) is confirmed, indicating a potential trade setup for targeting the Balanced Price Range imbalance (BPR) below with a stop loss above the buyside liquidity.
Although what we are demonstrating here is a hindsight example, it shows the potential usage this toolkit gives you for creating trading plans based on ICT Concepts.
Same chart but playing out the history further we can see directly after price came down to the Sellside liquidity & swept below it...
Then by enabling IFVGs in the settings, we can see the IFVG retests alongside the Sellside & Buyside liquidity acting in confluence.
Which allows us to see a great bullish structure in the market with various key levels for potential entries.
Here we can see a potential bullish setup as price has taken out a previous Sellside liquidity zone and is now retesting a NWOG + Volume Imbalance.
Users also have the option to display Fibonacci retracements based on market structure, order blocks, and imbalance areas, which can help place limit/stop orders more effectively as well as finding optimal points of interest beyond what the primary ICT Concepts features can generate for a trader.
In the above image we can see the Fibonacci extension was selected to be based on the NWOG giving us some upside levels above the buyside liquidity.
🔶 DETAILS
Each feature within the ICT Concepts indicator is described in the sub sections below.
🔹 Market Structure
Market structure labels are constructed from price breaking a prior swing point. This allows a user to determine the current market trend based on the price action.
There are two types of Market Structure labels included:
Market Structure Shift (MSS)
Break Of Structure (BOS)
A MSS occurs when price breaks a swing low in an uptrend or a swing high in a downtrend, highlighting a potential reversal. This is often labeled as "CHoCH", but ICT specifies it as MSS.
On the other hand, BOS labels occur when price breaks a swing high in an uptrend or a swing low in a downtrend. The occurrence of these particular swing points is caused by retracements (inducements) that highlights liquidity hunting in lower timeframes.
🔹 Order Blocks
More significant market participants (institutions) with the ability of placing large orders in the market will generally place a sequence of individual trades spread out in time. This is referred as executing what is called a "meta-order".
Order blocks highlight the area where potential meta-orders are executed. Bullish order blocks are located near local bottoms in an uptrend while bearish order blocks are located near local tops in a downtrend.
When price mitigates (breaks out) an order block, a breaker block is confirmed. We can eventually expect price to trade back to this breaker block offering a new trade opportunity.
🔹 Buyside & Sellside Liquidity
Buyside / Sellside liquidity levels highlight price levels where market participants might place limit/stop orders.
Buyside liquidity levels will regroup the stoploss orders of short traders as well as limit orders of long traders, while Sellside liquidity levels will regroup the stoploss orders of long traders as well as limit orders of short traders.
These levels can play different roles. More informed market participants might view these levels as source of liquidity, and once liquidity over a specific level is reduced it will be found in another area.
🔹 Imbalances
Imbalances highlight disparities between the bid/ask, these can also be defined as inefficiencies, which would suggest that not all available information is reflected by the price and would as such provide potential trading opportunities.
It is common for price to "rebalance" and seek to come back to a previous imbalance area.
ICT highlights multiple imbalance formations:
Fair Value Gaps: A three candle formation where the candle shadows adjacent to the central candle do not overlap, this highlights a gap area.
Implied Fair Value Gaps: Unlike the fair value gap the implied fair value gap has candle shadows adjacent to the central candle overlapping. The gap area is constructed from the average between the respective shadow and the nearest extremity of their candle body.
Balanced Price Range: Balanced price ranges occur when a fair value gap overlaps a previous fair value gap, with the overlapping area resulting in the imbalance area.
Volume Imbalance: Volume imbalances highlight gaps between the opening price and closing price with existing trading activity (the low/high overlap the previous high/low).
Opening Gap: Unlike volume imbalances opening gaps highlight areas with no trading activity. The low/high does not reach previous high/low, highlighting a "void" area.
🔹 Displacement
Displacements are scenarios where price forms successive candles of the same sentiment (bullish/bearish) with large bodies and short shadows.
These can more technically be identified by positive auto correlation (a close to open change is more likely to be followed by a change of the same sign) as well as volatility clustering (large changes are followed by large changes).
Displacements can be the cause for the formation of imbalances as well as market structure, these can be caused by the full execution of a meta order.
🔹 Kill Zones
Killzones represent different time intervals that aims at offering optimal trade entries. Killzones include:
- New York Killzone (7:9 ET)
- London Open Killzone (2:5 ET)
- London Close Killzone (10:12 ET)
- Asian Killzone (20:00 ET)
🔶 Conclusion & Supplementary Material
This script aims to emulate how a trader would draw each of the covered features on their chart in the most precise representation to how it's actually taught by ICT directly.
There are many parallels between ICT Concepts and Smart Money Concepts that we released in 2022 which has a more general & simpler usage:
ICT Concepts, however, is more specifically aligned toward the community's interpretation of how to analyze price 'based on ICT', rather than displaying features to have a more classic interpretation for a technical analyst.
Regression Channel Alternative MTF V2█ OVERVIEW
This indicator is a predecessor to Regression Channel Alternative MTF , which is coded based on latest update of type, object and method.
█ IMPORTANT NOTES
This indicator is NOT true Multi Timeframe (MTF) but considered as Alternative MTF which calculate 100 bars for Primary MTF, can be refer from provided line helper.
The timeframe scenarios are defined based on Position, Swing and Intraday Trader.
Suppported Timeframe : W, D, 60, 15, 5 and 1.
Channel drawn based on regression calculation.
Angle channel is NOT supported.
█ INSPIRATIONS
These timeframe scenarios are defined based on Harmonic Trading : Volume Three written by Scott M Carney.
By applying channel on each timeframe, MW or ABCD patterns can be easily identified manually.
This can also be applied on other chart patterns.
█ CREDITS
Scott M Carney, Harmonic Trading : Volume Three (Reaction vs. Reversal)
█ TIMEFRAME EXPLAINED
Higher / Distal : The (next) longer or larger comparative timeframe after primary pattern has been identified.
Primary / Clear : Timeframe that possess the clearest pattern structure.
Lower / Proximate : The (next) shorter timeframe after primary pattern has been identified.
Lowest : Check primary timeframe as main reference.
█ FEATURES
Color is determined by trend or timeframe.
Some color is depends on chart contrast color.
Color is determined by trend or timeframe.
█ EXAMPLE OF USAGE / EXPLAINATION
Zigzag Array ExperimentalThis is experimental script for zigzag which uses type, method and array. Not recommend for actual usage, for pine script study maybe useful.
In this experiment, I use type as coded below. It seems have limitation as specially when push as array. As Trading View recommendation, pushing float and int into array especially for type not guarantee to work. I agree with that. Preferred to push array as line or label especially for types.
// @type Used for point especially for array
// @field x int value for bar_index
// @field y float value for price
// @field sty label style
// @field col color for text label
// @field str high or low string
type point
int x = na
float y = na
string sty = na
color col = na
string str = na
I simulate the arrays as below.
var dirLine = array.new()
var dirLabel = array.new()
var dirPoint = array.new()
....
dirPoint.unshift(zigzag.createPoint(0))
dirLabel.unshift(zigzag.createLabel(fontSize, 0, true))
dirLine.unshift(zigzag.createLine(width, switchLine, 0, true))
Here are some results.
Watermark° (Quote, Name, Timeframe, Date)I have been asked for this a lot, so here it is!
It's an easy script to read, and for all you aspiring Pinescript coders out there it might serve as a little introduction on Tables , switch operator, and a bit of UI/UX!
Description:
This is just a watermark, which follows my personal style an aesthetic when it comes to Pinescript tools. I like to keep my charts clean to focus on Time and price, and I love to have a reminder to remain disciplined.
Homo Faber Fortunae Suae is a Latin maxim which loosely translates to: Humans Are The Makers Of Their Own Destiny.
So make your own destiny, master yourself and the charts!
Indicator Features:
– Display symbol ticker, timeframe and date all in one place.
– Make it look nice 🤗
– Protect your TV username ID, by having your chart show a custom username (if you are sharing charts outside of Tradingview, and are known under a different alias there)
Note: no matter what, by exporting images from TV (copy image/copy link to chart) your TV username will appear in the top left corner of the image
👇👁
Strategy Template + Performance & Returns table + ExtrasA script I've been working on since summer 2022. A template for any strategy so you just have to write or paste the code and go straight into risk management settings
Features:
>Signal only Longs/only Shorts/Both
>Leverage system
>Proper fees calculation (even with leverage on)
>Different Stop Loss systems: Simple percentage, 4 different "move to Break Even" systems and Scaling SL after each TP order (read the disclaimer at the bottom regarding this and the TV % profitable metric)
>2 Take Profit systems: Simple percentages, or Risk/reward ratios based on SL level
>Additional option on TP so last one "rides free" until closure of position or Stoploss is hit (for more than 1 orders)
>Up to 5 TP orders
>Show or hide SL/TP levels on demand
>2 date filters. Manual filter is nothing new, enter two dates/hours and filter will turn on. BUT automatic filter is another thing (thanks to user @bfr_ for his help in codingthis feature)
>AUTOMATIC DATE FILTER. Allows you to split all historical data on the chart in X periods, then choose the range of periods used. Up to 10 but that can be changed, instructions included. Useful for WalkForward simulations, haven't seen a script in TradingView that allows you to do this and test your strategy on "unseen data" automatically
EXTRA SETTINGS
Besides, some additions I like to add to my codes:
>Returns table for monthly and weekly performance. Requires recalculation on every tick. This is a modified version of @QuantNomad's work. May add lower TF options later on
>Volume Based S/R system. Original work from @shtcoinr
>One feature that was made by me, the "portfolio table". Yields info and metrics of your strategy, current position and balance. You're able to turn it off and change its size
Should anyone find an error, or have any idea on how to improve this code, please contact me. Future updates could come, stay tuned
DISCLAIMER:
In order to have accurate StopLoss hit, I had to change the previous system, which was a "close position on candle close" instead at actual stoploss level. It was fixed, but resulted on inflation of the number of trading orders, thus reducing the percent profitable and making it strongly biased and unreal. Keep that in mind, that "real" profitability could be 2x or 3x the metric TradingView says. If your strategy has a really high trading frequency, resulting in 3000+ orders, might be a problem. Try to make use of the automatic/manual date filter as workaround, I have no means of changing this, seems it is not a bug but an intended design of the PineScript Code
ICT NWOG/NDOG & EHPDA [LuxAlgo]This indicator displays New Week/Day Opening Gaps alongside Event Horizon PD Arrays which were conceptualized by a trader, ICT.
🔶 SETTINGS
Show: Determines if new week opening gaps (NWOG) or new day opening gaps (NDOG) are shown.
Amount: Controls the amount of most recent NWOGs/NDOGs to display on the chart.
Show EHPDA: Displays Event Horizons PD arrays.
🔶 USAGE
New Week/Day Opening Gaps are generally used as potential support or resistance areas.
Trader ICT describes that under consolidating market conditions, price tends to revert towards the opening gap area. This is consistent with other analysis suggesting that price has a tendency to come back toward gaps, ultimately looking to fill them.
ICT also introduces a novel concept, the "Event Horizon PD Array" (EHPDA) which are intermediary levels constructed from the average between the neighboring NWOGs or NDOGs.
EHPDA's are described by ICT as levels that "will not allow price to escape to the NWOG that will create a surge towards the NWOG it got too "close" to but has not yet reached."
Double Trend Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed double trend scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a close price equal to or above the price it opened.
• A red candle is one that closes with a close price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
Muti-Part Upper and Lower Trends
• A multi-part return line uptrend begins with the formation of a new return line uptrend and continues until a new downtrend ends the trend.
• A multi-part downtrend begins with the formation of a new downtrend and continues until a new return line uptrend ends the trend.
• A multi-part uptrend begins with the formation of a new uptrend and continues until a new return line downtrend ends the trend.
• A multi-part return line downtrend begins with the formation of a new return line downtrend and continues until a new uptrend ends the trend.
Double Trends
• A double uptrend is formed when the current trough price is higher than the preceding trough price and the current peak price is higher than the preceding peak price.
• A double downtrend is formed when the current peak price is lower than the preceding peak price and the current trough price is lower than the preceding trough price.
Muti-Part Double Trends
• A multi-part double uptrend begins with the formation of a new uptrend that proceeds a new return line uptrend, and continues until a new downtrend or return line downtrend ends the trend.
• A multi-part double downtrend begins with the formation of a new downtrend that proceeds a new return line downtrend, and continues until a new uptrend or return line uptrend ends the trend.
█ FEATURES
Inputs
• Start Date
• End Date
• Position
• Text Size
Table
The table is colour coded, consists of seven columns and, as many as, fifteen rows. Blue cells denote the multi-part trend scenarios, green cells denote the corresponding double uptrend scenarios and red cells denote the corresponding double downtrend scenarios.
The double trend scenarios are listed in the first column with their corresponding total counts to the right, in the second and fifth columns. The last row in column one, displays the sample period which can be adjusted or hidden via indicator settings.
The third and sixth columns display the double trend scenarios as percentages of total 1-part double trends. And columns four and seven display the total double trend scenarios as percentages of the last, or preceding double trend part. For example, 4-part double trends as percentages of 3-part double trends and so on.
Plots
For a visual aid to this indicator please use in conjunction with my Double Trends indicator which can be found on my profile page under scripts, or in community scripts under the same name.
Green up-arrows, with the number of the double trend part, denote double uptrends. Red down-arrows, with the number of the double trend part, denote double downtrends.
█ HOW TO USE
This indicator is intended for research purposes, strategy development and strategy optimisation. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe.
It can, for example, give you an idea of whether the current double trend will continue or fail, based on the current double trend scenario and what has happened in the past under similar circumstances. Such information can be very useful when conducting top down analysis across multiple timeframes and making strategic decisions.
What you do with these statistics and how far you decide to take your research is entirely up to you, the possibilities are endless.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge.
It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
Variety MA Cluster Filter Crosses [Loxx]What is a Cluster Filter?
One of the approaches to determining a useful signal (trend) in stream data. Small filtering (smoothing) tests applied to market quotes demonstrate the potential for creating non-lagging digital filters (indicators) that are not redrawn on the last bars.
Standard Approach
This approach is based on classical time series smoothing methods. There are lots of articles devoted to this subject both on this and other websites. The results are also classical:
1. The changes in trends are displayed with latency;
2. Better indicator (digital filter) response achieved at the expense of smoothing quality decrease;
3. Attempts to implement non-lagging indicators lead to redrawing on the last samples (bars).
And whereas traders have learned to cope with these things using persistence of economic processes and other tricks, this would be unacceptable in evaluating real-time experimental data, e.g. when testing aerostructures.
The Main Problem
It is a known fact that the majority of trading systems stop performing with the course of time, and that the indicators are only indicative over certain intervals. This can easily be explained: market quotes are not stationary. The definition of a stationary process is available in Wikipedia:
A stationary process is a stochastic process whose joint probability distribution does not change when shifted in time.
Judging by this definition, methods of analysis of stationary time series are not applicable in technical analysis. And this is understandable. A skillful market-maker entering the market will mess up all the calculations we may have made prior to that with regard to parameters of a known series of market quotes.
Even though this seems obvious, a lot of indicators are based on the theory of stationary time series analysis. Examples of such indicators are moving averages and their modifications. However, there are some attempts to create adaptive indicators. They are supposed to take into account non-stationarity of market quotes to some extent, yet they do not seem to work wonders. The attempts to "punish" the market-maker using the currently known methods of analysis of non-stationary series (wavelets, empirical modes and others) are not successful either. It looks like a certain key factor is constantly being ignored or unidentified.
The main reason for this is that the methods used are not designed for working with stream data. All (or almost all) of them were developed for analysis of the already known or, speaking in terms of technical analysis, historical data. These methods are convenient, e.g., in geophysics: you feel the earthquake, get a seismogram and then analyze it for few months. In other words, these methods are appropriate where uncertainties arising at the ends of a time series in the course of filtering affect the end result.
When analyzing experimental stream data or market quotes, we are focused on the most recent data received, rather than history. These are data that cannot be dealt with using classical algorithms.
Cluster Filter
Cluster filter is a set of digital filters approximating the initial sequence. Cluster filters should not be confused with cluster indicators.
Cluster filters are convenient when analyzing non-stationary time series in real time, in other words, stream data. It means that these filters are of principal interest not for smoothing the already known time series values, but for getting the most probable smoothed values of the new data received in real time.
Unlike various decomposition methods or simply filters of desired frequency, cluster filters create a composition or a fan of probable values of initial series which are further analyzed for approximation of the initial sequence. The input sequence acts more as a reference than the target of the analysis. The main analysis concerns values calculated by a set of filters after processing the data received.
In the general case, every filter included in the cluster has its own individual characteristics and is not related to others in any way. These filters are sometimes customized for the analysis of a stationary time series of their own which describes individual properties of the initial non-stationary time series. In the simplest case, if the initial non-stationary series changes its parameters, the filters "switch" over. Thus, a cluster filter tracks real time changes in characteristics.
Cluster Filter Design Procedure
Any cluster filter can be designed in three steps:
1. The first step is usually the most difficult one but this is where probabilistic models of stream data received are formed. The number of these models can be arbitrary large. They are not always related to physical processes that affect the approximable data. The more precisely models describe the approximable sequence, the higher the probability to get a non-lagging cluster filter.
2. At the second step, one or more digital filters are created for each model. The most general condition for joining filters together in a cluster is that they belong to the models describing the approximable sequence.
3. So, we can have one or more filters in a cluster. Consequently, with each new sample we have the sample value and one or more filter values. Thus, with each sample we have a vector or artificial noise made up of several (minimum two) values. All we need to do now is to select the most appropriate value.
An Example of a Simple Cluster Filter
For illustration, we will implement a simple cluster filter corresponding to the above diagram, using market quotes as input sequence. You can simply use closing prices of any time frame.
1. Model description. We will proceed on the assumption that:
The aproximate sequence is non-stationary, i.e. its characteristics tend to change with the course of time.
The closing price of a bar is not the actual bar price. In other words, the registered closing price of a bar is one of the noise movements, like other price movements on that bar.
The actual price or the actual value of the approximable sequence is between the closing price of the current bar and the closing price of the previous bar.
The approximable sequence tends to maintain its direction. That is, if it was growing on the previous bar, it will tend to keep on growing on the current bar.
2. Selecting digital filters. For the sake of simplicity, we take two filters:
The first filter will be a variety filter calculated based on the last closing prices using the slow period. I believe this fits well in the third assumption we specified for our model.
Since we have a non-stationary filter, we will try to also use an additional filter that will hopefully facilitate to identify changes in characteristics of the time series. I've chosen a variety filter using the fast period.
3. Selecting the appropriate value for the cluster filter.
So, with each new sample we will have the sample value (closing price), as well as the value of MA and fast filter. The closing price will be ignored according to the second assumption specified for our model. Further, we select the МА or ЕМА value based on the last assumption, i.e. maintaining trend direction:
For an uptrend, i.e. CF(i-1)>CF(i-2), we select one of the following four variants:
if CF(i-1)fastfilter(i), then CF(i)=slowfilter(i);
if CF(i-1)>slowfilter(i) and CF(i-1)slowfilter(i) and CF(i-1)>fastfilter(i), then CF(i)=MAX(slowfilter(i),fastfilter(i)).
For a downtrend, i.e. CF(i-1)slowfilter(i) and CF(i-1)>fastfilter(i), then CF(i)=MAX(slowfilter(i),fastfilter(i));
if CF(i-1)>slowfilter(i) and CF(i-1)fastfilter(i), then CF(i)=fastfilter(i);
if CF(i-1)<slowfilter(i) and CF(i-1)<fastfilter(i), then CF(i)=MIN(slowfilter(i),fastfilter(i)).
Where:
CF(i) – value of the cluster filter on the current bar;
CF(i-1) and CF(i-2) – values of the cluster filter on the previous bars;
slowfilter(i) – value of the slow filter
fastfilter(i) – value of the fast filter
MIN – the minimum value;
MAX – the maximum value;
What is Variety MA Cluster Filter Crosses?
For this indicator we calculate a fast and slow filter of the same filter and then we run a cluster filter between the fast and slow filter outputs to detect areas of chop/noise. The output is the uptrend is denoted by green color, downtrend by red color, and chop/noise/no-trade zone by white color. As a trader, you'll likely want to avoid trading during areas of chop/noise so you'll want to avoid trading when the color turns white.
Extras
Bar coloring
Alerts
Loxx's Expanded Source Types, see here:
Loxx's Moving Averages, see here:
An example of filtered chop, see the yellow circles. The cluster filter identifies chop zones so you don't get stuck in a sideways market.
Wavemeter [theEccentricTrader]█ OVERVIEW
This indicator is a representation of my take on price action based wave cycle theory. The indicator counts the number of confirmed wave cycles, keeps a rolling tally of the average wave length, wave height and frequency, and displays the statistics in a table. The indicator also displays the current wave measurements as an optional feature.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Wave Cycles
A wave cycle is here defined as a complete two-part move between a swing high and a swing low, or a swing low and a swing high. As can be seen in the example above, the first swing high or swing low will set the course for the sequence of wave cycles that follow; a chart that begins with a swing low will form its first complete wave cycle upon the formation of the first complete swing high and vice versa.
Wave Length
Wave length is here measured in terms of bar distance between the start and end of a wave cycle. For example, if the current wave cycle ends on a swing low the wave length will be the difference in bars between the current swing low and current swing high. In such a case, if the current swing low completes on candle 100 and the current swing high completed on candle 95, we would simply subtract 95 from 100 to give us a wave length of 5 bars.
Average wave length is here measured in terms of total bars as a proportion as total waves. The average wavelength is calculated by dividing the total candles by the total wave cycles.
Wave Height
Wave height is here measured in terms of current range. For example, if the current peak price is 100 and the current trough price is 80, the wave height will be 20.
Amplitude
Amplitude is here measured in terms of current range divided by two. For example if the current peak price is 100 and the current trough price is 80, the amplitude would be calculated by subtracting 80 from 100 and dividing the answer by 2 to give us an amplitude of 10.
Frequency
Frequency is here measured in terms of wave cycles per second (Hertz). For example, if the total wave cycle count is 10 and the amount of time it has taken to complete these 10 cycles is 1-year (31,536,000 seconds), the frequency would be calculated by dividing 10 by 31,536,000 to give us a frequency of 0.00000032 Hz.
Range
The range is simply the difference between the current peak and current trough prices, generally expressed in terms of points or pips.
█ FEATURES
Inputs
Show Sample Period
Start Date
End Date
Position
Text Size
Show Current
Show Lines
Table
The table is colour coded, consists of two columns and, as many as, nine rows. Blue cells display the total wave cycle count and average wave measurements. Green cells display the current wave measurements. And the final row in column one, coloured black, displays the sample period. Both current wave measurements and sample period cells can be hidden at the user’s discretion.
Lines
For a visual aid to the wave cycles, I have added a blue line that traces out the waves on the chart. These lines can be hidden at the user’s discretion.
█ HOW TO USE
The indicator is intended for research purposes, strategy development and strategy optimisation. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe.
For example, the indicator can be used to compare the current range and frequency with the average range and frequency, which can be useful for gauging current market conditions versus historic and getting a feel for how different markets and timeframes behave.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge.
It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
Percent Change of Day [ilovealgotrading]
OVERVIEW:
This indicator aims to effectively show us the percentage change of the price within the time frame we have chosen.
What is the purpose of this indicator?
This indicator shows how the price changes for each bar at different time frames we have chosen. By examining the percentage change in different time periods, we can easily look at the change in the face of the market during the time interval. Also if the price is above or below the value of 0 during the specified time, the color of our percentage line changes.
IMPLEMENTATION DETAILS:
First of all, let's understand How to Calculate Percent Change?
The difference between the old and new value of a quantity given in percentages is known as a percent change. It's rather simple to calculate the % difference between two given quantities.
The formula is given by;
Example
The price of a kilo of rice went from 10$ to12.5$, what is the percentage change?
Explanation
• The old value of sugar = $ 10
• New value = $12.5
• Now apply the percent change formula;
• Percentage change = ×100%
= x 100%
= (2.5/10) x 100%
= 25%
In this case, the percent change is positive and therefore, it is an increase.
How Is Percentage Change Used in Finance?
In the world of finance, percentage change is frequently used to analyze changes in the value of stocks or major market indexes over time.
Percentage change is used for many purposes in finance, most notably to track the price change of stocks market and crypto market.
What can we change from the settings panel ?
We can set time frame setting of the percentage change from place number 1
We are able to adjust the changing color if the percentage change is above or below zero from place 2 and 3
ALSO:
Please do not open trades without properly managing your risk and psychology!!!
If you have any ideas what to add to my work to add more sources or make calculations cooler, suggest in DM .
Relative Performance of stock against nifty & bank niftyThe code calculates the relative performance of Nifty and Bank Nifty and plots it on a chart. It also calculates the 14-day RSI and a moving average of the relative performance.
First, the script retrieves the daily close prices for Nifty and Bank Nifty from the NSE using the request.security() function. It then calculates the daily returns for each index and the average returns over a specified lookback period. The relative performance is then calculated as the difference between the current close price and its moving average, expressed as a percentage of the moving average, minus the average daily returns of Nifty and Bank Nifty.
The script then calculates the 14-day RSI using the ta.rsi() function and plots the relative performance on the chart in green color. A signal line at zero is also plotted in black color. Additionally, the moving average of the relative performance is plotted on the chart using the ta.sma() function and an input variable called "interval" is used to specify the number of bars to use for the moving average.
Finally, the script sets the color of the chart bars based on the relative performance and RSI values. If the relative performance is above the moving average and the RSI is above 50, the color of the bars is set to yellow. If the relative performance is below the moving average and the RSI is below 50, the color of the bars is set to a shade of purple.
Kitchen [ilovealgotrading]
OVERVIEW:
Kitchen is a strategy that aims to trade in the direction of the trend by using supertrend and stochRsi data by calculating at different time values.
IMPLEMENTATION DETAILS – SETTINGS:
First of all, let's understand the supertrend and stocrsi indicators.
How do you read and use Super Trend for trading ?
The price is often going upwards when it breaks the super trend line while keeping its position above the indication level.
When the market is in a bullish trend, the indicator becomes green. The indicator level will act as trendline support in such a scenario. The color of the indicator changes to red to indicate a negative trend once the price crosses the support line. The price uses the super trend level as a trendline resistance during a bearish move.
In our strategy, if our 1-hour and 4-hour supertrend lines show the up or down train in the same direction at the same time, we can assume that a train is forming here.
Why do I use the time of 1 hour and 4 hours ?
When I did a backtest from the past to the present, I discovered that the most accurate and consistent time zones are the 1 hour and 4 hour time zones.
By the way we can change our short term timeframe(1H) and long term timeframe(4H) from settings panel.
How do you read and use the Stoch-RSI Indicator?
This indicator analyzes price dynamics automatically to detect overbought and oversold locations.
The indicator includes:
- The primary line, which typically has values between 0 and 100;
- Two dynamic levels for overbought and oversold conditions.
IF our stoch-rsi indicator value has fallen below our lower boundary line, the oversold event has been observed in the price, if our stoch-rsi value breaks up our bottom line after becoming oversold, we think that the price will start the recovery phase.(The case is also true for the opposite.)
However, this does not always apply and we need additional approvals, Therefore, our 1H and 4H supertrrend indicator provides us with additional confirmation.
Buy Condition:
Our 1H(short term) and 4H(long term) supertrrend indicator, has given the buy signal(green line and yellow line), and if our stochrsi indicator has broken our oversold line up on the past 15 bars, the buy signal is formed here.
Sell Condition:
Our 1H(short term) and 4H(long term) supertrrend indicator, has given the sell signal(red line and orange line), and if our stochrsi indicator has broken our overbuy line down on the past 15 bars, the sell signal is formed here.
Stop Loss or Take Profit Conditions:
Exit Long Senerio:
All conditions are completed, the buy signal has arrived and we have entered a LONG trade, the 1-hour supertrend line follows the price rise(yellow line), if the price breaks below the 1-hour super trend line and a sell condition occurs for 1H timeframe for supertrend indcator, LONG trade will exit here.
Exit Short Senerio:
All conditions are completed, the Sell signal has arrived and we have entered a SHORT trade, the 1-hour supertrend line follows the price down(orange line), if the price breaks up the 1-hour super trend line and a buy condition occurs for 1H timeframe for supertrend indcator, SHORT trade will exit here.
What can you change in the settings panel?
1-We can set Start and End date for backtest and future alarms
2-We can set ATR length and Factor for supertrend indicator
3-We can set our short term and long term timeframe value
4-We can set StochRsi Up and Low limit to confirm buy and sell conditions
5-We can set stochrsi retroactive approval length
6-We can set stochrsi values or the length
7-We can set Dollar cost for per position
8- We can choose the direction of our positions, we can set only LONG, only SHORT or both directions.
9-IF you want to place automatic buy and sell orders with this strategy, you can paste your codes into the Long open-close or Short open-close message sections.
For example
IF you write your alert window this code {{strategy.order.alert_message}}.
When trigger Long signal you will get dynamically what you pasted here for Long Open Message
ALSO:
Please do not open trades without properly managing your risk and psychology!!!
If you have any ideas what to add to my work to add more sources or make calculations cooler, suggest in DM .
Trading Checklist - SonarlabTrading Checklist is a customizable indicator designed for traders who want to stay disciplined and stick to their trading rules. Using this indicator, you can easily create and display your own personalized checklist of trading rules directly on your TradingView chart.
The Title and the Body are two different sections, so you can set two different styles.
This indicator allows you to customize:
Text color
Text size
Text alignment
FuriousFX Trading Confirmation ListThis is a simple script that allows user to define the confirmations, position them (pin them) to the top middle bottom left or right on the screen and check them off
Once the user checks the confirmation it changes from red or any other default color to green (indicating it has played out).
There are similar script out there but what makes this script unique is one how it is generated and more importantly the mechanism of changing color.. You also have the option to pick from a pick list in the options of how many (up to 10) confirmations you want to generate and you can define change them at any time..
To use this script simply do the following :
1) add it to your chart, double click on the default table
2)select the desired number of confirmations
3)Select the desired position and default colors (default is top right and dark red)
4)Define your criteria for confirmations in appropriate boxes by writing over the default values
5)Start using it, when you see your desired confirmation, double click on the table again and select "Confirmed?" check box.. Once selected the color of that confirmation will turn green...
This script is done to keep people disciplined and enter only according to their trading strategy, as we all know that the biggest reason why people lose in trading is impatience fear and greed...
This script attemps to solve problems of overtrading, entering too early or too late..
Hope you guys enjoy it..
Feel free to write comments for improvements or copy it for your needs.
Pivot Highs&lows: Short/Medium/Long-term + Spikeyness FilterShows Pivot Highs & Lows defined or 'Graded' on a fractal basis: Short-term, medium-term and long-term. Also applies 'Spikeyness' condition by default to filter-out weak/rounded pivots
ES1! 4hr chart (CME) shown above, with lookback = 15; clearly identifying the major highs & lows on the basis of how they are fractally 'nested' within lesser Pivots.
-- in the above chart Short term pivot highs (STH) are simply represented by green 'ʌ', and short-term pivot lows (STL) are simply represented by orange 'v'.
//Basics: (as applying to pivot highs, the following is reversed for pivot lows)
-Short term highs (STH) are simple pivot highs, albeit refined from standard with the 'spikeyness' filter.
-Medium-term highs (MTH) are defined as having a lower STH on either side of them.
-Long-term highs (LTH) are defined as having a lower MTH on either side of them.
//Purpose:
-Education: Quick and easy visualization of the strength or importance of a pivot high or low; a way of grading them based on their larger context.
-Backtesting: use in combination with other trading methods when backtesting to see the relative significance and price sensitivity of LTHs/LTLs compared to lower grade highs and lows.
//Settings:
-Choose Pivot lookback/lookforward bars: One setting, the basis from which all further pivot calculations are done.
-Toggle on/off 'Spikeyness' condition to filter-out weak/rounded/unimpressive pivot highs or lows (default is ON).
-Toggle on/off each of STH, MTH, LTH, STL, MTL, LTL; and choose label text-styles/colors/sizes independently.
-Set text Vertically, horizonally, or simply use 'ʌ' or 'v' symbols if you want to declutter your chart.
//Usage notes:
-Pivots take time to print (lookback bars must have elapsed before confirmation). Fractally nested pivots as here (i.e. a LTH), take even longer to print/confirm, so please be patient.
-Works across timeframes & Assets. Different timeframes may require slightly tweaked lookback/forward settings for optimal use; default is 15 bars.
Example usage with just symbolic labels short-term, med-term, long-term with 1x, 2x and 3x ʌ/v respectively:
RedK DIY ZLMA: Customizable Zero-Lag MA (Educational / Utility)This script is more of an educational / utility piece rather than a fully-fledged indicator - It provides an easy way to customize and produce a zero-lag Moving average that can then be used in various scenarios
What is DIY_ZLMA?
------------------------
The DIY ZLMA is for fans and enthusiasts of researching Moving Averages (like me) - the script enables the user to play around with one of the common approaches used to reduce lag in moving averages - which was explained in this old post below
Suggested uses of the DIY_ZLMA
---------------------------------------
* The Zero-lag approach here applies 3 moving average passes to a source data series - I'll refer to these 3 passes as Base MA Pass , De-lagging Pass, and Smoothing Pass - these "passes" can be customized from the indicator settings in terms of MA Length and type. The first pass allows the choice of a "source", and the second pass allows additional fine tuning by playing around with the magnification factor. The 3rd pass (smoothing) is optional and can be skipped altogether when needed. (as noted in the script, HMA and TEMA, which are very common low-lag MA's use slightly different approach in the calculation than the one used here .. so we can't get an equivalent of either of these MA's with the customization of DIY_ZLMA parameters)
* After the user experiments with the various settings for the 3 passes, and finds a "preferred combination", the script not only plots the resulting My_ZLMA - it also produces the "1-line Pine script formula" that the user can then use in any other script, maybe to smoothen some data series, or to combine with other types of moving averages to create multi-MA cross-over trading signals... and so on.
* The DIY_ZLMA can also be added to another indicator as a signal line using the Indicator-on-Indicator feature of TradingView (review this post for step-by-step -->
)
* the script also showcases couple of recent (and very neat) Pine features: the use of User-defined Types (UDT) and User-defined Methods - which are awesome and a lot of fun to work with :)
Since this is more of a utility piece, I added as many comments as possible to the script to explain the way it works - so it's more valuable if someone finds it by searching the "Add Indicator" feature in TradingView charts
Please feel free to play around with this new toy :) and share comments and feedback below if you find this useful. I truly hope you do.
Swing Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed swing high and swing low scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
• A green candle is one that closes with a high price equal to or above the price it opened.
• A red candle is one that closes with a low price that is lower than the price it opened.
Swing Highs and Swing Lows
• A swing high is a green candle or series of consecutive green candles followed by a single red candle to complete the swing and form the peak.
• A swing low is a red candle or series of consecutive red candles followed by a single green candle to complete the swing and form the trough.
Peak and Trough Prices (Basic)
• The peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the preceding green candle, depending on which is higher.
• The trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the preceding red candle, depending on which is lower.
Peak and Trough Prices (Advanced)
• The advanced peak price of a complete swing high is the high price of either the red candle that completes the swing high or the high price of the highest preceding green candle high price, depending on which is higher.
• The advanced trough price of a complete swing low is the low price of either the green candle that completes the swing low or the low price of the lowest preceding red candle low price, depending on which is lower.
Green and Red Peaks and Troughs
• A green peak is one that derives its price from the green candle/s that constitute the swing high.
• A red peak is one that derives its price from the red candle that completes the swing high.
• A green trough is one that derives its price from the green candle that completes the swing low.
• A red trough is one that derives its price from the red candle/s that constitute the swing low.
Historic Peaks and Troughs
The current, or most recent, peak and trough occurrences are referred to as occurrence zero. Previous peak and trough occurrences are referred to as historic and ordered numerically from right to left, with the most recent historic peak and trough occurrences being occurrence one.
Upper Trends
• A return line uptrend is formed when the current peak price is higher than the preceding peak price.
• A downtrend is formed when the current peak price is lower than the preceding peak price.
• A double-top is formed when the current peak price is equal to the preceding peak price.
Lower Trends
• An uptrend is formed when the current trough price is higher than the preceding trough price.
• A return line downtrend is formed when the current trough price is lower than the preceding trough price.
• A double-bottom is formed when the current trough price is equal to the preceding trough price.
█ FEATURES
Inputs
• Start Date
• End Date
• Position
• Text Size
• Show Sample Period
• Show Plots
• Show Lines
Table
The table is colour coded, consists of three columns and nine rows. Blue cells denote neutral scenarios, green cells denote return line uptrend and uptrend scenarios, and red cells denote downtrend and return line downtrend scenarios.
The swing scenarios are listed in the first column with their corresponding total counts to the right, in the second column. The last row in column one, row nine, displays the sample period which can be adjusted or hidden via indicator settings.
Rows three and four in the third column of the table display the total higher peaks and higher troughs as percentages of total peaks and troughs, respectively. Rows five and six in the third column display the total lower peaks and lower troughs as percentages of total peaks and troughs, respectively. And rows seven and eight display the total double-top peaks and double-bottom troughs as percentages of total peaks and troughs, respectively.
Plots
I have added plots as a visual aid to the swing scenarios listed in the table. Green up-arrows with ‘HP’ denote higher peaks, while green up-arrows with ‘HT’ denote higher troughs. Red down-arrows with ‘LP’ denote higher peaks, while red down-arrows with ‘LT’ denote lower troughs. Similarly, blue diamonds with ‘DT’ denote double-top peaks and blue diamonds with ‘DB’ denote double-bottom troughs. These plots can be hidden via indicator settings.
Lines
I have also added green and red trendlines as a further visual aid to the swing scenarios listed in the table. Green lines denote return line uptrends (higher peaks) and uptrends (higher troughs), while red lines denote downtrends (lower peaks) and return line downtrends (lower troughs). These lines can be hidden via indicator settings.
█ HOW TO USE
This indicator is intended for research purposes and strategy development. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe. It can, for example, give you an idea of any inherent biases such as a greater proportion of higher peaks to lower peaks. Or a greater proportion of higher troughs to lower troughs. Such information can be very useful when conducting top down analysis across multiple timeframes, or considering entry and exit methods.
What I find most fascinating about this logic, is that the number of swing highs and swing lows will always find equilibrium on each new complete wave cycle. If for example the chart begins with a swing high and ends with a swing low there will be an equal number of swing highs to swing lows. If the chart starts with a swing high and ends with a swing high there will be a difference of one between the two total values until another swing low is formed to complete the wave cycle sequence that began at start of the chart. Almost as if it was a fundamental truth of price action, although quite common sensical in many respects. As they say, what goes up must come down.
The objective logic for swing highs and swing lows I hope will form somewhat of a foundational building block for traders, researchers and developers alike. Not only does it facilitate the objective study of swing highs and swing lows it also facilitates that of ranges, trends, double trends, multi-part trends and patterns. The logic can also be used for objective anchor points. Concepts I will introduce and develop further in future publications.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY , do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge.
The sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
█ NOTES
I feel it important to address the mention of advanced peak and trough price logic. While I have introduced the concept, I have not included the logic in my script for a number of reasons. The most pertinent of which being the amount of extra work I would have to do to include it in a public release versus the actual difference it would make to the statistics. Based on my experience, there are actually only a small number of cases where the advanced peak and trough prices are different from the basic peak and trough prices. And with adequate multi-timeframe analysis any high or low prices that are not captured using basic peak and trough price logic on any given time frame, will no doubt be captured on a higher timeframe. See the example below on the 1H FOREXCOM:USDJPY chart (Figure 1), where the basic peak price logic denoted by the indicator plot does not capture what would be the advanced peak price, but on the 2H FOREXCOM:USDJPY chart (Figure 2), the basic peak logic does capture the advanced peak price from the 1H timeframe.
Figure 1.
Figure 2.
█ RAMBLINGS
“Never was there an age that placed economic interests higher than does our own. Never was the need of a scientific foundation for economic affairs felt more generally or more acutely. And never was the ability of practical men to utilize the achievements of science, in all fields of human activity, greater than in our day. If practical men, therefore, rely wholly on their own experience, and disregard our science in its present state of development, it cannot be due to a lack of serious interest or ability on their part. Nor can their disregard be the result of a haughty rejection of the deeper insight a true science would give into the circumstances and relationships determining the outcome of their activity. The cause of such remarkable indifference must not be sought elsewhere than in the present state of our science itself, in the sterility of all past endeavours to find its empirical foundations.” (Menger, 1871, p.45).
█ BIBLIOGRAPHY
Menger, C. (1871) Principles of Economics. Reprint, Auburn, Alabama: Ludwig Von Mises Institute: 2007.
Global GDPThis is the GlobalGDP of the richest and most populous countries
It is measured in USD
The countries included are the same than are included in my Global M2 indicator, as of to be able to compare them side to side.
Candle Counter [theEccentricTrader]█ OVERVIEW
This indicator counts the number of confirmed candle scenarios on any given candlestick chart and displays the statistics in a table, which can be repositioned and resized at the user's discretion.
█ CONCEPTS
Green and Red Candles
A green candle is one that closes with a high price equal to or above the price it opened.
A red candle is one that closes with a low price that is lower than the price it opened.
Upper Candle Trends
A higher high candle is one that closes with a higher high price than the high price of the preceding candle.
A lower high candle is one that closes with a lower high price than the high price of the preceding candle.
A double-top candle is one that closes with a high price that is equal to the high price of the preceding candle.
Lower Candle Trends
A higher low candle is one that closes with a higher low price than the low price of the preceding candle.
A lower low candle is one that closes with a lower low price than the low price of the preceding candle.
A double-bottom candle is one that closes with a low price that is equal to the low price of the preceding candle.
█ FEATURES
Inputs
Start Date
End Date
Position
Text Size
Show Sample Period
Show Plots
Table
The table is colour coded, consists of three columns and twenty-two rows. Blue cells denote all candle scenarios, green cells denote green candle scenarios and red cells denote red candle scenarios.
The candle scenarios are listed in the first column with their corresponding total counts to the right, in the second column. The last row in column one, row twenty-two, displays the sample period which can be adjusted or hidden via indicator settings.
Rows two and three in the third column of the table display the total green and red candles as percentages of total candles. Rows four to nine in column three, coloured blue, display the corresponding candle scenarios as percentages of total candles. Rows ten to fifteen in column three, coloured green, display the corresponding candle scenarios as percentages of total green candles. And lastly, rows sixteen to twenty-one in column three, coloured red, display the corresponding candle scenarios as percentages of total red candles.
Plots
I have added plots as a visual aid to the various candle scenarios listed in the table. Green up-arrows denote higher high candles when above bar and higher low candles when below bar. Red down-arrows denote lower high candles when above bar and lower low candles when below bar. Similarly, blue diamonds when above bar denote double-top candles and when below bar denote double-bottom candles. These plots can also be hidden via indicator settings.
█ HOW TO USE
This indicator is intended for research purposes and strategy development. I hope it will be useful in helping to gain a better understanding of the underlying dynamics at play on any given market and timeframe. It can, for example, give you an idea of any inherent biases such as a greater proportion of green candles to red. Or a greater proportion of higher low green candles to lower low green candles. Such information can be very useful when conducting top down analysis across multiple timeframes, or considering trailing stop loss methods.
What you do with these statistics and how far you decide to take your research is entirely up to you, the possibilities are endless.
This is just the first and most basic in a series of indicators that can be used to study objective price action scenarios and develop a systematic approach to trading.
█ LIMITATIONS
Some higher timeframe candles on tickers with larger lookbacks such as the DXY, do not actually contain all the open, high, low and close (OHLC) data at the beginning of the chart. Instead, they use the close price for open, high and low prices. So, while we can determine whether the close price is higher or lower than the preceding close price, there is no way of knowing what actually happened intra-bar for these candles. And by default candles that close at the same price as the open price, will be counted as green. You can avoid this problem by utilising the sample period filter.
The green and red candle calculations are based solely on differences between open and close prices, as such I have made no attempt to account for green candles that gap lower and close below the close price of the preceding candle, or red candles that gap higher and close above the close price of the preceding candle. I can only recommend using 24-hour markets, if and where possible, as there are far fewer gaps and, generally, more data to work with. Alternatively, you can replace the scenarios with your own logic to account for the gap anomalies, if you are feeling up to the challenge.
It is also worth noting that the sample size will be limited to your Trading View subscription plan. Premium users get 20,000 candles worth of data, pro+ and pro users get 10,000, and basic users get 5,000. If upgrading is currently not an option, you can always keep a rolling tally of the statistics in an excel spreadsheet or something of the like.
