XLibrary "X"
a collection of 'special' methods/functions ('special' at the time of conception)
Initial functions includes:
• count of a given number in a given array
• array.get() but option added to use negative index
• sum of all digits until the output < 10
• slope/angle calculation of lines
method count_num_in_array(arr, num)
counts how many times a given number is present in a given array (0 when not present)
Namespace types: int
Parameters:
arr (int ) : Array (int, float )
num (int) : Number that needs to be counted (int, float)
Returns: count of number in array (0 when not present)
method count_num_in_array(arr, num)
Namespace types: float
Parameters:
arr (float )
num (float)
method get_(arr, idx)
array.get() but you can use negative index (-1 is last of array, -2 is second last,...)
Namespace types: int
Parameters:
arr (int ) : Array (int, float, string, bool, label, line, box, color )
idx (int) : Index
Returns: value/object at index, 'na' if index is outside array
method get_(arr, idx)
Namespace types: float
Parameters:
arr (float )
idx (int)
method get_(arr, idx)
Namespace types: string
Parameters:
arr (string )
idx (int)
method get_(arr, idx)
Namespace types: bool
Parameters:
arr (bool )
idx (int)
method get_(arr, idx)
Namespace types: label
Parameters:
arr (label )
idx (int)
method get_(arr, idx)
Namespace types: line
Parameters:
arr (line )
idx (int)
method get_(arr, idx)
Namespace types: box
Parameters:
arr (box )
idx (int)
method get_(arr, idx)
Namespace types: color
Parameters:
arr (color )
idx (int)
method sumAllNumbers_till_under_10(num)
sums all separate digit numbers, it repeats the process until sum < 10
Namespace types: series int, simple int, input int, const int
Parameters:
num (int) : Number (int, float)
Returns: value between 0 and 9
method sumAllNumbers_till_under_10(num)
Namespace types: series float, simple float, input float, const float
Parameters:
num (float)
method XYaxis(width)
Global function to calculate Yaxis, which is used in calculate_slope() method
Namespace types: series int, simple int, input int, const int
Parameters:
width (int) : Amount of bars for reference X-axis
Returns: Yaxis
method calculate_slope(width, XYratio, Yaxis, x1, y1, x2, y2)
Returns a normalised slope
Namespace types: series int, simple int, input int, const int
Parameters:
width (int) : Amount of bars to calculate height
XYratio (float) : Ratio to calculate height (from width) normalised_slope calculation
Yaxis (float) : Y-axis from XYaxis() method
x1 (int) : x1 of line
y1 (float) : y1 of line
x2 (int) : x2 of line
y2 (float) : y2 of line
Returns: Tuple of -> slope = price difference per bar
스크립트에서 "10年期国债收益率+曲线图+数据来源"에 대해 찾기
Seasonality and Presidential cycleAn incredibly useful indicator that shows seasonality and presidential cycles by indices, stocks and industries. Just type in a ticker and trade according to seasonal patterns
Blue line - seasonality excluding presidential cycles
Green line - seasonality taking into account presidential cycles
*Seasonal patterns over the last 10 years
This indicator uses the request.seed() function.
Requests data from a GitHub repository maintained by our team and returns it as a series.
Pine Seeds is a service to import custom data and access it via TradingView.
Use TradingView as frontend and use a GitHub repository as backend.
github.com
...
Rus: Невероятно полезный индикатор, который показывает сезонность и президентские циклы по индексам, акциям и отраслям. Просто вбейте тикер и торгуйте согласно сезонным паттернам
Синяя линия - сезонность без учета президентских циклов
Зеленая линия - сезонность с учетом президентских циклов
*Сезонные паттерны за последние 10 лет
Grospector DCA V.4This is system for DCA with strategy and can trade on trend technique "CDC Action Zone".
We upgrade Grospector DCA V.3 by minimizing unnecessary components and it is not error price predictions.
This has 5 zone Extreme high , high , normal , low , Extreme low. You can dynamic set min - max percent every zone.
Extreme zone is derivative short and long which It change Extreme zone to Normal zone all position will be closed.
Every Zone is splitted 10 channel. and this strategy calculate contribution.
and now can predict price in future.
Idea : Everything has average in its life. For bitcoin use 4 years for halving. I think it will be interesting price.
Default : I set MA is 365*4 days and average it again with 365 days.
Input :
len: This input represents the length of the moving average.
strongLen: This input represents the length of the moving average used to calculate the strong buy and strong sell zone.
shortMulti: This input represents the multiplier * moveing average used to calculate the short zone.
strongSellMulti: This input represents the multiplier used to calculate the strong sell signal.
sellMulti: This input represents the multiplier * moveing average used to calculate the sell zone.
strongBuyMulti: This input represents the multiplier used to calculate the strong sell signal.
longMulti: This input represents the multiplier * moveing average used to calculate the long zone.
*Diff sellMulti and strongBuyMulti which is normal zone.
useDerivative: This input is a boolean flag that determines whether to use the derivative display zone. If set to true, the derivative display zone will be used, otherwise it will be hidden.
zoneSwitch: This input determines where to display the channel signals. A value of 1 will display the signals in all zones, a value of 2 will display the signals in the chart pane, a value of 3 will display the signals in the data window, and a value of 4 will hide the signals.
price: Defines the price source used for the indicator calculations. The user can select from various options, with the default being the closing price.
labelSwitch: Defines whether to display assistive text on the chart. The user can select a boolean value (true/false), with the default being true.
zoneSwitch: Defines which areas of the chart to display assistive zones. The user can select from four options: 1 = all, 2 = chart only, 3 = data only, 4 = none. The default value is 2.
predictFuturePrice: Defines whether to display predicted future prices on the chart. The user can select a boolean value (true/false), with the default being true.
DCA: Defines the dollar amount to use for dollar-cost averaging (DCA) trades. The user can input an integer value, with a default value of 5.
WaitingDCA: Defines the amount of time to wait before executing a DCA trade. The user can input a float value, with a default value of 0.
Invested: Defines the amount of money invested in the asset. The user can input an integer value, with a default value of 0.
strategySwitch: Defines whether to turn on the trading strategy. The user can select a boolean value (true/false), with the default being true.
seperateDayOfMonth: Defines a specific day of the month on which to execute trades. The user can input an integer value from 1-31, with the default being 28.
useReserve: Defines whether to use a reserve amount for trading. The user can select a boolean value (true/false), with the default being true.
useDerivative: Defines whether to use derivative data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
useHalving: Defines whether to use halving data for the indicator calculations. The user can select a boolean value (true/false), with the default being true.
extendHalfOfHalving: Defines the amount of time to extend the halving date. The user can input an integer value, with the default being 200.
Every Zone: It calculate percent from top to bottom which every zone will be splited 10 step.
To effectively make the DCA plan, I recommend adopting a comprehensive strategy that takes into consideration your mindset as the best indicator of the optimal approach. By leveraging your mindset, the task can be made more manageable and adaptable to any market
Dollar-cost averaging (DCA) is a suitable investment strategy for sound money and growth assets which It is Bitcoin, as it allows for consistent and disciplined investment over time, minimizing the impact of market volatility and potential risks associated with market timing
Market Performance TableThe Market Performance Table displays the performance of multiple tickers (up to 5) in a table format. The tickers can be customized by selecting them through the indicator settings.
The indicator calculates various metrics for each ticker, including the 1-day change percentage, whether the price is above the 50, 20, and 10-day simple moving averages (SMA), as well as the relative strength compared to the 10/20 SMA and 20/50 SMA crossovers. It also calculates the price deviation from the 50-day SMA.
The table is displayed on the chart and can be positioned in different locations.
Credits for the idea to @Alex_PrimeTrading ;)
Support and Resistance: Triangles [YinYangAlgorithms]Overview:
Triangles have always been known to be the strongest shape. Well, why wouldn’t that likewise apply to trading? This Indicator will create Upwards and Downwards Triangles which in turn create Support and Resistance locations. For example, we find 2 highs that meet the criteria (within deviation %, Minimum Distance and Lookback Distance). We calculate the distance between these two and create an Equilateral Triangle Downwards (You can adjust the % if you want more of an Isosceles Triangle). The midpoint (tip) of this triangle is the Support and the bottom (base) of it is the Resistance. The exact opposite applies for an Upwards Triangle.
The reason why Triangles may make for good Support and Resistance locations is the % 's used, much like the fibonacci, use ratios relevant in nature and everywhere in the world around us, so why not for trading too?
Tutorial:
If you look at the locations we’ve circled above, all of them exhibit strong rejections are predictive Support and Resistance locations plotted by the triangles created. There can only ever be 1 Upward and 1 Downward Triangle at a time, so when a new one is created, the Support and Resistance locations are moved.
If you scroll back far enough you’ll notice the Triangles disappear but their Support and Resistance locations are still plotted. This has to do with the fact you are allowed only so many Lines plotted and when a new Triangle is created, an old one will be removed. The Support and Resistance locations however will stay.
If we look at the example above, you can see the Support and Resistance locations the Triangles made here may have helped predict where the price would struggle to surpass.
By default the Look Back Distance is set to 50 and the Min Distance is 10 (settings used in all previous examples). However, you can modify these to make Triangles more ‘Rare’ and therefore the Support and Resistance locations change less. In the example above for Instance we left Look Back Distance to 50 but changed Min Distance from 10 to 25. This results in Support and Resistance locations that may hold better in the long term.
If we scroll back a bit, we can see the settings ‘Look Back Distance’ 50 and ‘Minimum Distance’ 25 had done a decent job at predicting the ATH resistance and many Support and Resistance locations around it. Keep in mind, previous results don’t mean future results, but Triangles may create ratios which apply well to trading.
We will conclude our Tutorial here. Hopefully you can see the benefit to the ratio Triangles make when predicting Support and Resistance locations.
Settings:
Show Triangles: If all you want to know is the Support and Resistance locations, there’s no need to draw the Triangles.
Triangle Zones: What types of triangles should we create our zones for? Options are Upward, Downward, Both, None.
Max Deviation Allowed: Maximum Deviation up or down from the last bars High/Low for potential to create a Triangle.
Lookback Distance: How far back we look to see for potential of a High/Low within Deviation range.
Min Distance: This is so triangles are spaced properly and not from 2 bars beside each other. Min distance allocated between 2 points to create a Triangle.
Bar Percent Increase: How much % multiplier do we apply for each bar spacing of the triangle. 0.005 creates a close to Equilateral Triangle, but other values like 0.004 and 0.006 seem to work well too.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Abz US Real ratesThis indicator shows Fed Funds Rate vs US inflation. It also shows the US 10 year bond yield and provides a color indication that aims to indicate if this is a period where owning TLT is a good idea or not. It is not investment advice and it is only aiming to indicate whether the trend is supportive or not for long dated US bonds in comparison with short dated treasury bills and versus inflation.
Recessions: Recessions are indicated by a grey background.
Yield inversion: Periods where the Fed Funds Rate is above the US 10 year bond yield are shown as a maroon background and frequently are macro indicators of an upcoming recession. Like other macro signals, this can't be relied upon as a timing tool.
This is intended to be used as an indictor on a long term chart. Minimum would be weekly but could be even more valid to focus on a chart with monthly candles.
Median of Means Estimator Median of Means (MoM) is a measure of central tendency like mean (average) and median. However, it could be a better and robust estimator of central tendency when the data is not normal, asymmetric, have fat tails (like stock price data) and have outliers. The MoM can be used as a robust trend following tool and in other derived indicators.
Median of means (MoM) is calculated as follows, the MoM estimator shuffles the "n" data points and then splits them into k groups of m data points (n= k*m). It then computes the Arithmetic Mean of each group (k). Finally, it calculate the median over the resulting k Arithmetic Means. This technique diminishes the effect that outliers have on the final estimation by splitting the data and only considering the median of the resulting sub-estimations. This preserves the overall trend despite the data shuffle.
Below is an example to illustrate the advantages of MoM
Set A Set B Set C
3 4 4
3 4 4
3 5 5
3 5 5
4 5 5
4 5 5
5 5 5
5 5 5
6 6 8
6 6 8
7 7 10
7 7 15
8 8 40
9 9 50
10 100 100
Median 5 5 5
Mean 5.5 12.1 17.9
MoM 5.7 6.0 17.3
For all three sets the median is the same, though set A and B are the same except for one outlier in set B (100) it skews the mean but the median is resilient. However, in set C the group has several high values despite that the median is not responsive and still give 5 as the central tendency of the group, but the median of means is a value of 17.3 which is very close to the group mean 17.9. In all three cases (set A, B and C) the MoM provides a better snapshot of the central tendency of the group. Note: The MoM is dependent on the way we split the data initially and the value might slightly vary when the randomization is done sevral time and the resulting value can give the confidence interval of the MoM estimator.
Tops & Bottoms by Volume [SS]Hey everyone,
Releasing this indicator that helps you time entries by alerting to potential tops and bottoms in the market.
Background to the indicator:
I was playing around with things that signalled reversals / tops and bottoms in SPSS and R using Pivot Points to mark tops and bottoms. Happened to come across a generally statistically significant relationship between sell to buy volume that was tracked over 10 to 50 candles back and pivot highs and pivot lows.
So I put it into a beta version of an indicator to see how it looked and was a bit surprised.
Since then, I have went back and narrowed down the details of what works/what doesn't work and this is the tentative result!
What it does / How to Use:
It tracks the cumulative buy vs sell volume. Buy volume is cumulated as close > open (or green candles) and sell is open > close (or red candles).
It then cumulates this over a user-defined period (defaulted to 14). It then looks back to see the highest vs lowest areas of sell and buy volume and makes determinations based on this relationship.
The relationship was determined by me using my own analysis and programmed into the indicators algorithm (using highest vs lowest function in pine).
It will plot areas of potential reversal to the upside as green on the histogram or red for a downside reversal. Once this becomes significant enough to signal an actual bottom or top, it will then change the SMA colour from white to green (for bottom) or red (for top).
Your entries generally should be once the SMA turns back to white. So from green to white, you would enter long or inverse for red to white (enter short).
Settings and Customizability:
Here are the key points to keep in mind if you are using this indicator:
Your lookback length should be between 10 to 50. I have left it open for you to modify it below and above this lookback period; however, this is the major periods deemed to be significant in identifying tops and bottoms. Thus, I advise against operating outside of those parameters.
You can toggle between smoothed look or historgram with SMA. The strength in this indicator comes from using the SMA and watching the SMA for signals of reversals, so if you want to filter out the background noise, you can simply look at the plotted SMA. If you want a more responsive indication of impending reversals, leave the smoothed option off and view the histogram in conjunction with the SMA.
The indicator will change the candle colour to red for bearish reversal and green to bullish reversal. This is based on the SMA. You can toggle this off and/or on as desired.
It is recommended to leave ETH (extended trading hours) turned off and RTH turned on.
Please read the instructions carefully.
If you require further assistance, I have posted a tutorial video.
Please be sure you are reading and/or watching carefully.
If you have questions, please feel free to post them below. But bear in mind I likely will not respond if it is already addressed in the description above (this happens often).
Also, feel free to leave your comments or suggestions below as well.
Thanks for checking this out. If you are interested in volume based trading, I suggest also checking out my Buyer to Seller volume indicator which cumulates total buying vs selling volume over a designated lookback period. Both of these used in conjunction are very powerful tools for volume based traders! ( Available here )
NOTE:
The boxes drawn in the chart are my own for demonstration purposes. I unfortunately cannot get the indicator to overlay the boxes on the chart in a separate viewing pane. That is why I opted to use the barcolor function to change the candle color instead :-).
Thanks again everyone and safe trades!
Cross Correlation [Kioseff Trading]Hello!
This script "Cross Correlation" calculates up to ~10,000 lag-symbol pair cross correlation values simultaneously!
Cross correlation calculation for 20 symbols simultaneously
+/- Lag Range is theoretically infinite (configurable min/max)
Practically, calculate up to 10000 lag-symbol pairs
Results can be sorted by greatest absolute difference or greatest sum
Ability to "isolate" the symbol on your chart and check for cross correlation against a list of symbols
Script defaults to stock pairs when on a stock, Forex pairs when on a Forex pair, crypto when on a crypto coin, futures when on a futures contract.
A custom symbol list can be used for cross correlation checking
Can check any number of available historical data points for cross correlation
Practical Assessment
Ideally, we can calculate cross correlation to determine if, in a list of assets, any of the assets frequently lead or lag one another.
Example
Say we are comparing the log returns for the previous 10 days for SPY and XLU.
*A single time-interval corresponds to the timeframe of your chart i.e. 1-minute chart = 1-minute time interval. We're using days for this example.
(Example Results)
A lag value (k) +/-3 is used.
The cross correlation (normalized) for k = +3 is -0.787
The cross correlation (normalized) for k = -3 is 0.216
A positive "k" value indicates the correlation when Asset A (SPY) leads Asset B (XLU)
A negative "k" value indicates the correlation when Asset B (XLU) leads Asset A (SPY)
A normalized cross correlation of -0.787 for k = +3 indicates an "adequately strong" negative relationship when SPY leads XLU by 3 days.
When SPY increases or decreases - XLU frequently moves in the opposite direction 3 days later.
A cross correlation value of 0.216 at k = −3 indicates a "weak" positive correlation when XLU leads SPY by 3 days.
There's a slight tendency for SPY to move in the same direction as XLU 3 days later.
After the cross-correlation score is normalized it will fall between -1 and 1.
A cross-correlation score of 1 indicates a perfect directional relationship between asset A and asset B at the corresponding lag (k).
A cross correlation of -1 indicates a perfect inverse relationship between asset A and asset B at the corresponding lag (k).
A cross correlation of 0 indicates no correlation at the corresponding lag (k).
The image above shows the primary usage for the script!
The image above further explains the data points located in the table!
The image above shows the script "isolating" the symbol on my chart and checking the cross correlation between the symbol and a list of symbols!
Wrapping Up
With this information, hopefully you can find some meaningful lead-lag relationships amongst assets!
Thank you for checking this out (:
JK - Q SuiteThis indicator is primarily for identifying pauses in Stage 2 uptrends, modelled on Qullamaggie's style of trading, but fits well with many traders including William O' Neil. or Mark Minervini.
I built this for my own purposes, and have gradually added range of tools into a single suite. My goal has also to be as clean as possible, while providing clear, actionable information.
This suite includes all of the following:
Moving averages (10, 20, 50, 200)
Coloured bars showing tightening price (blue under 75% of ADR, orange under 50% of ADR)
A 'markets' dashboard (top-right), showing the major indexes. Red if 10<20MA, or price <20MA
A 'sectors' dashboard (top-right, below markets). Red if 5<10MA, or price <10MA - see note below
Strength / Weakness information - two cells at the top, bottom-right. See below
Stock information - glanceable stock info as quick filters. The thresholds for ADR, Average volume, and Dollar Volume can be customised.
NOTE - if the 'tightening coloured candles' are not showing, the indicator needs to be at the top of the stack. Click the triple squares at the very bottom-right of the TradingView interface, and drag the indicator to the top, should work then!
=============
Sectors
These are based on the 11 official Sectors, tracked using index funds (XLY, XLK etc). HOWEVER, TradingView does NOT use the official 11 sectors - therefore I've done my best to match TradingViews ones to the official ones, but doesn't always work... e.g. 'Electronic Technology' is typically semiconductors, which are classes as 'Industrials', but Apple is the same sector in TV, but classed as 'Technology' using the official 11 Sectors.
If TradingView move to use the official 11 I'll update this, but for now it's a best guess and will sometimes be wrong, sorry!
Strength / Weakness information
This was an experiment in trying not to give too much back to the market! Typically the strategy would be to sell if price closes below 10MA (Weakness), however there may be large pops that can be advantageous to sell into.
The 'Strength' information (top cell, bottom-right), checks how far the price is extended above 10MA - this is customisable as a multiple of ADR. You may find that in weak markets (like now), it can be best to take profits quickly - in good markets, you could increase this as stocks make bigger or more sustained moves.
=============
While I'm not the best coder - and I've hacked and tried and changed different things - this has been a labour of love and essential for me.
If you have any suggestions, while I may or may not be able to implement them, I'm certainly open to ideas!
Strategy:Reversal-CatcherWhat
This is a plain and vanilla reversal based strategy for intraday (15m) timeframe on Futures prices of the assets.
Now what all it comprises of?
It finds out the dynamic support & resistance from Bollinger Band (20 period, 1.5 std dev).
It finds out the potential divergence of price deviation from 5 period exponential moving average (EMA).
If the previous candle (N-1) shows a divergence it confirms the reversal by checking the present candle (N) to be closed inside the Bollinger Band.
It confirms the momentum by checking RSI shows a crossover/crossunder to oversold (30) / overbought (70) region.
It also confirms whether the trend is up (then only reversal trade to short) or down (then only reversal trade to long). The trend is checked with EMA-21 and EMA-50.
Re-affirmation Condition : It re-affirms the position of two successive candles called as `hhLLong` and `hhLLShort` in the script.
Why
In Indian context, retail participants are pre-dominantly (yes- 80% of Indian daily volume) Options buyers mainly in weekly indices (Nifty, BankNifty, FinNifty, CNXMidcap, Sensex, Bankx .. well everyday is expiry now in India, except -- Thank God -- Saturday & Sunday).
And in Index Options the momentum plays a big role.
If one can catch a good reversal point the potential of high Risk-to-Reward trade (hence earn handsomely) is very likely (please note: there is no holy grail in trading. Nothing works 100%).
So this is the attempt to catch a reversal.
Re-affirmation of Reversal
hhLLong : It's a reversal point after an uptrend. It checks the relative positioning of current candle compared to that of previous candle. [The details are in the script. Check for variable hhLLong in script.
hhLLShort : It's a reversal point after a downtrend. It checks the relative positioning of current candle compared to that of previous candle. [The details are in the script. Check for variable hhLLShort in script.
Unique-ness
What's unique in it? Why we decided to publicly share this:
Already given the context of The Great Indian Options Buyers community. It should be helpful to them, we believe.
It takes Very Less Number of Trades with High Accuracy . Please check the result in NSE:NIFTY1! in 15m timeframe. 71% accuracy with roughly a trade in a month.
There is no point giving brokers' the brokerages taking 10 trades a day and ending not-so-good EoD. Better lets take less trades with better result possibility. .
Mention
There are many people uses this variation of Bolling Band, 5EMA
Many people use RSI, trends and relative positioning of candles.
--> We are grateful to all of them. It's really difficult to mention everyone's name. But all people somehow influence the thought process. Thanks for all of them.
Statutory Disclaimer
There is no silver bullet / holy grail in trading. Nothing works 100% time. One has to be careful about the loss (s)he can bear in case of the trade goes against.
We, as the author of this script, is not responsible for any trading or position decision one is taken based on the outcome of this.
It is our sole discretion to change, add, delete the portion or withdraw the whole script without any prior notice or intimation.
In Indian Context : We are not SEBI registered, will never be SEBI registered.
Dynamic Liquidity Map [Kioseff Trading]Hello!
Just a quick/fun project here: "Dynamic Heatmap".
This script draws a volume delta or open interest delta heatmap for the asset on your chart.
The adjective "Dynamic" is used for two reasons (:
1: Self-Adjusting Lower Timeframe Data
The script requests ~10 lower timeframe volume and open interest data sets.
When using the fixed range feature the script will, beginning at the start time, check the ~10 requested lower timeframes to see which of the lower timeframes has available data.
The script will always use the lowest timeframe available during the calculation period. As time continues, the script will continue to check if new lower timeframe data (lower than the currently used lowest timeframe) is available. This process repeats until bar time is close enough to the current time that 1-minute data can be retrieved.
The image above exemplifies the process.
Incrementally lower timeframe data will be used as it becomes available.
1: Fixed range capabilities
The script features a "fixed range" tool, where you can manually set a start time (or drag & drop a bar on the chart) to determine the interval the heatmap covers.
From the start date, the script will calculate the calculate the sub-intervals necessary to draw a rows x columns heatmap. Consequently, setting the start time further back will draw a heat map with larger rows x columns, whereas, a start time closer to the current bar time will draw a more "precise" heatmap with smaller rows x columns.
Additionally, the heatmap can be calculated using open interest data.
The image above shows the heatmap displaying open interest delta.
The image above shows alternative settings for the heatmap.
Delta values have been hidden alongside grid border colors. These settings can be replicated to achieve a more "traditional" feel for the heatmap.
Thanks for checking this out!
[OKX Signal Bot] Indicator Script Set Up TemplateDiscover the power of the Turtle Trade Channels Indicator (TUTCI), an innovative tool that integrates the time-tested principles of the legendary Turtle Trade system. This groundbreaking system shattered the belief that successful traders are born, not made, by transforming ordinary individuals into profitable traders.
The Turtle Trade Experiment, which achieved a remarkable 80% annual return over four years and amassed a staggering $150 million, showcased the immense potential of this trend-following strategy. Unlike the conventional "buy low and sell high" approach, the Turtle Trade system embraces a different philosophy—one of capturing substantial profits by following prevailing trends.
At the heart of the Turtle Trade Channels Indicator lies the concept of Donchian Channels, a powerful technical indicator developed by Richard Donchian. Building upon this foundation, the main rule of TUTCI is to identify 20-day breakouts and capitalize on them, while simultaneously utilizing a profit-taking strategy based on breaching 10-day highs or lows.
For long trades, the indicator signals a buying opportunity when the price breaks above the 20-day high. Conversely, for short trades, a selling opportunity arises when the price falls below the 20-day low. This systematic approach allows traders to align themselves with the prevailing momentum, capturing significant price movements.
To further enhance trading precision, TUTCI incorporates two key lines. The red line represents the trading line, indicating the direction of the trend. Price bars above the trend line suggest an uptrend, while those below indicate a downtrend. The dotted blue line serves as the exit line, guiding traders to close their positions when price action breaches the 10-day high or low. This rule safeguards profits and helps traders avoid potential trend reversals.
The Turtle Trade Channels Indicator (TUTCI) is a versatile tool applicable to various financial markets, including stocks, commodities, and forex. By harnessing the power of breakouts and integrating profit-taking rules, this indicator empowers traders to capitalize on favorable trading opportunities while managing risk effectively.
As with any trading strategy, it is crucial to conduct thorough backtesting and evaluation of the TUTCI system before implementing it in live trading. Traders can customize the indicator's parameters to align with their trading preferences and adapt to changing market conditions. Employing sound risk management techniques, such as position sizing and stop-loss orders, is paramount to protect capital and minimize potential losses.
Experience the transformational potential of the Turtle Trade Channels Indicator (TUTCI) and embark on a journey of trend following, capturing significant profits, and achieving trading success.
These scripts are only functioning as sample script templates to support okx alert standards. It is not intended to provide any investment, tax, or legal advice, nor should it be considered an offer to purchase, sell, hold or offer any services relating to digital assets. Digital assets, including stablecoins, involve a high degree of risk, can fluctuate greatly, and can even become worthless. You should carefully consider whether trading or holding digital assets is suitable for you in light of your financial condition and risk tolerance. OKX does not provide investment or asset recommendations. You are solely responsible for your investment decisions, and OKX is not responsible for any potential losses. Past performance is not indicative of future results. Please consult your legal/tax/investment professional for questions about your specific circumstances.
Volume Delta Compare [Ticks ~ LTF data]
The "Volume Delta Compare " publication shows 2 different techniques to show into-depth details of Volume, using Tick and Lower-Time-Frame (LTF) data.
🔶 USAGE
Check for divergences between price and volume movement
Check details (why and when a ΔV developed)
Or if you want to see a lot of data stacked on each other )
🔶 CONCEPTS
🔹 Tick vs. LTF data
a Tick is an measure of (upward or downward) movement in price OR volume.
We can use this data by using varip in the code.
Advantage:
• Detail, detail, detail
• Accurate, per tick
Disadvantage:
• Only realtime
• Can reset 'easily' -> loss of data
• Will reset when settings are changed
LTF data, through the request.security_lower_tf() function, measures the OHLCV data per LTF bar
Advantage:
• Access to history when loading a chart
• No 'loss' of data when chart resets
Disadvantage:
• Less detailed
• Less accurate
This script makes it possible to compare the 2 techniques and enables you to show different values.
🔹 Values
There are mainly 3 important values:
• UP volume (uV): volume when price rises
• DOWN volume (dV): volume when price falls
• NEUTRAL volume (nV): volume when price stays the same
From this, additional data is calculated:
• Volume Delta (ΔV): uV minus dV
• Cumulative Delta Volume (cΔV): sum of ΔV
One typical nV is at open: at that moment there isn't a base price to compare with,
so when the first trade doesn't fully fill the first supply (up or down), volume will rise, but price just is 'open', no movement -> no uV or dV.
• Tick data: every volume changement per tick will be added to the concerning variable (uV, dV or nV)
• LTF data: every volume changement of each bar will be added to the concerning variable (uV, dV or nV)
-> this can easily give a difference, for example (Tick vs. 1 minute LTF), when most of the ticks caused a rise of price, but at the last few seconds, a few ticks causes the close to come below open, with Tick data this could give more UP Volume, while LTF data will show 1 value of DOWN Volume.
🔶 EXAMPLES
🔹 Details
In these examples you can see:
• grey line: Total volume (higher precision)
• UP/DOWN/NEUTRAL Volume
• green columns: uV
• orange columns: dV
• blue pillars: nV
• coloured stepline: reflects ΔV
• close > open and positive ΔV -> green
• close > open but negative ΔV -> fuchsia
• close < open and negative ΔV -> orange
• close < open but positive ΔV -> bright lime green
• Right side -> indication of used data (Tick/LTF data) + last ΔV
• labels (can be disabled)
Above 0 (only with Tick data): data from EVERY tick (ΔV ):
• first the amount of Volume (0 when the amount is very minimal)
• between brackets: price movement
Below 0:
• Σ V: sum of uV, dV and nV, for that bar
• Σ up: sum of uV for that bar
• Σ dn: sum of dV for that bar
• Σ nt: sum of nV for that bar
• Σ P: sum of price movement, for that bar (only at Tick data)
(At the right you'll see a new bar just started)
Here is a detail of the first second at opening:
🔹 Cumulative Volume Delta (CVD)
Difference CVD based on Tick vs. LTF data :
(horizontal lines added for reference)
🔶 FEATURES
🔹 Minimal plotting of na values
Data window and status line only show what is applicable (tick or LTF data) to diminish clutter of data values:
The Tick option has a label above 0 which includes details of every Tick.
If data is added every tick, that label on a 10 minute chart will be filled beyond limitations pretty quickly (string max_length = 4096 limit).
To prevent the script stopping to execute, at a certain limit, this label will stop updating and show the message "Too much data".
The label below the 0-line won't reach that limit, so it will keep on updating.
Timeframes closer to 1 second will have less risk to reach that 4096 limit. Details will remain to show in this case.
🔹 Automatic label colour adaption when changing between dark/light mode values
Label background/text-colour will adapt according to the dark/light-mode by using chart.fg_color / chart.bg_color
🔶 SETTINGS
🔹 Data from: Ticks vs. LTF data
🔹 LTF: Lower Time-Frame for when LTF option is chosen: 1, 5, 10, 15, 30 Seconds or 1 minute
🔹 Also start when bar already has data: only for tick data -> when disabled calculations only start on a new bar.
🔹 CVD, Only show Cumulative Delta Volume: enable to just display CVD
🔹 Colours: colour at the right is for price/volume direction divergences
🔹 Label: choose what you want to display + size labels
🔹 0-line: The label under the 0-line sometimes goes below the chart. this can be adjusted with this setting.
TrendGuard Flag Finder - Strategy [presentTrading]
Introduction and How It Is Different
In the vast world of trading strategies, the TrendGuard Flag Finder stands out as a unique blend of traditional flag pattern detection and the renowned SuperTrend indicator.
- A significant portion of the Flag Pattern detection is inspired by the "Flag Finder" code by @Amphibiantrading, which serves as one of foundational element of this strategy.
- While many strategies focus on either trend-following or pattern recognition, this strategy harmoniously combines both, offering traders a more holistic view of the market.
- The integration of the SuperTrend indicator not only provides a clear direction of the prevailing trend but also offers potential stop-loss levels, enhancing the strategy's risk management capabilities.
AAPL 1D chart
ETHBTC 6hr chart
Strategy: How It Works
The TrendGuard Flag Finder is primarily built on two pillars:
1. Flag Pattern Detection : At its core, the strategy identifies flag patterns, which are continuation patterns suggesting that the prevailing trend will resume after a brief consolidation. The strategy meticulously detects both bullish and bearish flags, ensuring traders can capitalize on opportunities in both rising and falling markets.
What is a Flag Pattern? A flag pattern consists of two main components:
1.1 The Pole : This is the initial strong price move, which can be either upwards (for bullish flags) or downwards (for bearish flags). The pole represents a strong surge in price in a particular direction, driven by significant buying or selling momentum.
1.2 The Flag : Following the pole, the price starts consolidating, moving against the initial trend. This consolidation forms a rectangular shape and is characterized by parallel trendlines. In a bullish flag, the consolidation will have a slight downward tilt, while in a bearish flag, it will have a slight upward tilt.
How the Strategy Detects Flags:
Identifying the Pole: The strategy first identifies a strong price movement over a user-defined number of bars. This movement should meet a certain percentage change to qualify as a pole.
Spotting the Flag: After the pole is identified, the strategy looks for a consolidation phase. The consolidation should be counter to the prevailing trend and should be contained within parallel lines. The depth (for bullish flags) or rally (for bearish flags) of this consolidation is calculated to ensure it meets user-defined criteria.
2. SuperTrend Integration : The SuperTrend indicator, known for its simplicity and effectiveness, is integrated into the strategy. It provides a dynamic line on the chart, signaling the prevailing trend. When prices are above the SuperTrend line, it's an indication of an uptrend, and vice versa. This not only confirms the flag pattern's direction but also offers a potential stop-loss level for trades.
When combined, these components allow traders to identify potential breakout (for bullish flags) or breakdown (for bearish flags) scenarios, backed by the momentum indicated by the SuperTrend.
Usage
To use the SuperTrend Enhanced Flag Finder:
- Inputs : Begin by setting the desired parameters. The strategy offers a range of user-controlled settings, allowing for customization based on individual trading preferences and risk tolerance.
- Visualization : Once the parameters are set, the strategy will identify and visually represent flag patterns on the chart. Bullish flags are represented in green, while bearish flags are in red.
- Trade Execution : When a breakout or breakdown is identified, the strategy provides entry signals. It also offers exit signals based on the SuperTrend, ensuring that traders can capitalize on the momentum while managing risk.
Default Settings
The strategy comes with a set of default settings optimized for general use:
- SuperTrend Parameters: Length set to 10 and Factor set to 5.0.
- Bull Flag Criteria: Max Flag Depth at 7, Max Flag Length at 10 bars, Min Flag Length at 3 bars, Prior Uptrend Minimum at 9%, and Flag Pole Length between 7 to 13 bars.
- Bear Flag Criteria: Similar settings adjusted for bearish patterns.
- Display Options: By default, both bullish and bearish flags are displayed, with breakout and breakdown points highlighted.
Liquidity Breakout - Strategy [presentTrading]- Introduction and How It Is Different
The Liquidity Breakout Strategy is a unique trading strategy that focuses on identifying and leveraging patterns in market price data. This strategy, mainly inspired by the script "Master Pattern" by LuxAlgo, takes a different approach from many traditional strategies that rely on technical indicators or fundamental analysis. Instead, the Liquidity Breakout is based on the concept of contraction detection and liquidity levels. This approach allows traders to identify potential trading opportunities that other strategies might miss.
BTCUSDT 6h
The strategy is different from other trading strategies because it uses a unique combination of pattern detection, liquidity levels, and user-defined trading direction. This combination allows the strategy to adapt to various market conditions and trading styles, making it a versatile tool for traders.
- Strategy: How It Works
1. Contraction Detection: The strategy uses a lookback period defined by the user (default is 10 bars) to identify contractions in the market. A contraction is a period where the market is consolidating, often followed by a significant price movement. The strategy identifies contractions by finding pivot highs and pivot lows within the lookback period. If a pivot high is lower than the previous pivot high and a pivot low is higher than the previous pivot low, a contraction is detected.
2. liquidity Levels:
What are Liquidity levels? Liquidity levels, also known as liquidity pools or zones, are price levels at which there is a significant amount of trading activity. They are often areas where large institutional traders (like banks or hedge funds) have placed orders. These levels are important because they can act as support or resistance levels, and price often reacts at these levels.
In the context of this strategy, liquidity levels are used to identify potential entry and exit points for trades. When the price reaches a liquidity level, it could indicate a potential trading opportunity. For example, if the price breaks through a liquidity level, it could signal the start of a new trend. On the other hand, if the price approaches a liquidity level and then reverses, it could signal a potential reversal.
The strategy uses these two elements to identify potential trading opportunities. When a contraction is detected, the strategy will look for a breakout in the direction of the trend. If the breakout occurs at a liquidity level, the strategy will execute a trade.
The strategy also allows traders to set their stop loss based on either the Average True Range (ATR) or a fixed percentage. This flexibility allows traders to manage their risk according to their personal risk tolerance and trading style.
- Trade Direction
One of the unique features of the Master Pattern Strategy is the ability to choose the trading direction. Traders can choose to trade in the "Long" direction, the "Short" direction, or "Both". This feature allows traders to adapt the strategy to their personal trading style and market outlook.
For example, if a trader believes that the market is in an uptrend, they can choose to trade only in the "Long" direction. Conversely, if the market is in a downtrend, they can choose to trade only in the "Short" direction. If the trader believes that the market is volatile and there are opportunities in both directions, they can choose to trade in "Both" directions.
- Usage
To use the strategy, traders need to input their preferred settings, including the contraction detection lookback period, liquidity levels, stop loss type, and trading direction. Once these settings are input, the strategy will automatically detect potential trading opportunities and execute trades according to the defined parameters.
- Default Settings
The default settings for the Master Pattern Strategy are as follows:
Contraction Detection Lookback: 10
Liquidity Levels: 20
Stop Loss Type: ATR
ATR Length: 20
ATR Multiplier: 3.0
Fixed Percentage: 0.01
Trading Direction: Both
These settings can be adjusted according to the trader's personal preferences and market conditions. It's recommended that traders experiment with different settings to find the ones that work best for their trading style and goals.
