TPO Letters [Kioseff Trading]Hello!
"TPO Letters" functions similarly to the script "Realtime TPO Profile"; however, TPO characters are appended to a developing bar. Simply, TPO characters display on the bar that formed them.
All colors are configurable.
The image above emphasizes functionality; TPO letters are colored on a gradient . Additionally, the value area range is shaded; characters that form within the range are gradient colored. Gray-colored characters extend beyond the value area.
The columned data displayed right of the TPO letters shows tick levels. Tick levels are shaded various colors, each color indicative of some occurrence.
Tick Levels
Red: Single Print
Yellow: POC
Lime Green: VAH or VAL
Lighter Green: Value Area Inclusive Level
Left of the TPO horizontal-axis, the aqua-colored line (blue-line inclusive) reflects the high-low range of the session; the blue-colored line reflects the initial-balance range (IBR).
You can select to color TPO letters within the IBR blue (any color).
Additionally, you can select to shade the IBR.
The image above shows auxiliary features.
Unfortunately, I'm unable to orient TPO letters at their intended tick levels using one label per bar, a contrasting feature of the "Realtime TPO Profile" script.
This means only 1000 TPO letters can be displayed simultaneously. If the number of TPO letters exceeds 1000, early-session and middle-session characters will begin to disappear. This isn't an issue for the "Realtime TPO Profile" script, as each tick level comprised one label, to which additional TPO characters were appended to the label as necessary and extended horizontally. Using this same method proved fallible for this indicator - vertical scaling is an issue. While I could append all letters formed for a bar to one label, the letters wouldn't superimpose atop their corresponding tick level (using " " didn't suffice).
Consequently, you'll have to, at times, rely on the label & box count oriented in the bottom-right table to see whether the number of labels & boxes transcends the upper threshold. You can hide this table at anytime (:
The image above exemplifies the "Fixed Range" portion of the indicator. A useful inclusion for the "Realtime TPO Profile" script however, while still useful for "TPO Letters", can only display 1000 TPO letters concurrently.
You can also reset the TPO profile at user-defined time intervals.
The indicator hosts an auto-calculate tick levels option; however, there will be times you'll need to manually adjust the tick levels to achieve digestible results (:
That's all! If the script would benefit from an excluded feature, or you notice an error, please let me know! Thank you (:
Shoutout to @kaigouthro for creating an exceptional library for gradient colors!! It was used in this script (:
Statistics
YOY[TV1]Year-to-year comparison is a popular and effective way to evaluate a company's financial performance and investment performance.
Any measurable event that repeats yearly can be compared based on YoY.
As a rule, the indicator YoY (year to year) is the number of percentages indicating an increase or regression in relation to the future or past period.
For example, you can compare WM2NS using the YOY (Year to Year) method.
The Offset argument sets the data comparison period. For daily, weekly and monthly timeframes, if Offset is set to 0, it will be determined automatically.
Сравнение Год к году - популярный и эффективный способ оценки финансовых показателей компании и эффективность инвестиций.
Любое измеримое событие, которое повторяется ежегодно можно сравнить на основе YoY.
Как правило, показателем YoY (year to year) является количество процентов указывающее на прирост или регресс по отношению к будущему или прошлому периоду.
Например, вы можете сравнить WM2NS (эмиссию доллара) с помощью метода YOY (Год к году).
Допустим, в 2021 году вы эмитировали А долларов, а в 2022 вы эмитировали Б долларов
Итак итоговой формулой будет: ((Б - А) / А) * 100
Аргумент Offset устанавливает период сравнения данных. Для дневного, недельного и месячного таймфрейма, если Offset установлен в 0, будет определен автоматически.
Historical Crypto Conference DatesJust a basic list date script to display various conference dates from the crypto sector. Updates to add more conferences.
Red - BTC Miami
Blue - Consensus
VPT Timeleft v.10Timeleft counter for candle in minutes. It will countdown the time left for a candle to close and display near the running candle.
TradersCustomLibraryLibrary "TradersCustomLibrary"
TODO: add library description here
SelectOptimalTimeframeTrendlineSettings()
calculateShortStopLoss()
calculateLongStopLoss()
werdygerTrend()
trendLines()
stoch()
timeToString()
ETH Dominance Excluding BTCThe indicator shows when ETH is undervalued or overvalued with regard to other alts. BTC capitalization is not taken into account.
Range-AnalysisMarkets usually tend to stay within a range during a specific time frame (for example first hour of the regular trading session, the whole regular trading session). For traders before initiating a trade it can be helpful to determine the range potential left for the targeted time frame. So they can decide to either try to ride the current trend further or fade the current trend in the case there is no range potential left for the specific time frame. This could be especially helpful for example in the E-Mini S&P future during the first hour.
The script calculates the average range for the last x days of the session defined and plots a line at the expected range extremes based on that average (for example: RangeExtremeHigh would be currentSessionLow+average Range of the last x days.
Any feedback is appreciated.
BTC Profitable Wallets StrategyBTC Profitable Wallets Strategy - plots the percentage of profitable BTC wallets and places long orders when the profitable wallet share crosses above 50%, historically a very accurate point to catch the next Bull Run early.
The only setting is a smoothing option using the Moving Average method and length of your choice.
On Chain Data is queried from IntoTheBlock.
This is a 'HODL' strategy, with no exit given. If you'd like to see the historical performance check the Open Profit or place a sell order at the current date.
TALibrary "TA"
General technical analysis functions
div_bull(pS, iS, cp_length_after, cp_length_before, pivot_length, lookback, no_broken, pW, iW, hidW, regW)
Test for bullish divergence
Parameters:
pS : Price series (float)
iS : Indicator series (float)
cp_length_after : Bars after current (divergent) pivot low to be considered a valid pivot (optional int)
cp_length_before : Bars before current (divergent) pivot low to be considered a valid pivot (optional int)
pivot_length : Bars before and after prior pivot low to be considered valid pivot (optional int)
lookback : Bars back to search for prior pivot low (optional int)
no_broken : Flag to only consider divergence valid if the pivot-to-pivot trendline is unbroken (optional bool)
pW : Weight of change in price, used in degree of divergence calculation (optional float)
iW : Weight of change in indicator, used in degree of divergence calculation (optional float)
hidW : Weight of hidden divergence, used in degree of divergence calculation (optional float)
regW : Weight of regular divergence, used in degree of divergence calculation (optional float)
Returns:
flag = true if divergence exists (bool)
degree = degree (strength) of divergence (float)
type = 1 = regular, 2 = hidden (int)
lx1 = x coordinate 1 (int)
ly1 = y coordinate 1 (float)
lx2 = x coordinate 2 (int)
ly2 = y coordinate 2 (float)
div_bear(pS, iS, cp_length_after, cp_length_before, pivot_length, lookback, no_broken, pW, iW, hidW, regW)
Test for bearish divergence
Parameters:
pS : Price series (float)
iS : Indicator series (float)
cp_length_after : Bars after current (divergent) pivot high to be considered a valid pivot (optional int)
cp_length_before : Bars before current (divergent) pivot highto be considered a valid pivot (optional int)
pivot_length : Bars before and after prior pivot high to be considered valid pivot (optional int)
lookback : Bars back to search for prior pivot high (optional int)
no_broken : Flag to only consider divergence valid if the pivot-to-pivot trendline is unbroken (optional bool)
pW : Weight of change in price, used in degree of divergence calculation (optional float)
iW : Weight of change in indicator, used in degree of divergence calculation (optional float)
hidW : Weight of hidden divergence, used in degree of divergence calculation (optional float)
regW : Weight of regular divergence, used in degree of divergence calculation (optional float)
Returns:
flag = true if divergence exists (bool)
degree = degree (strength) of divergence (float)
type = 1 = regular, 2 = hidden (int)
lx1 = x coordinate 1 (int)
ly1 = y coordinate 1 (float)
lx2 = x coordinate 2 (int)
ly2 = y coordinate 2 (float)
PipMotionFXHi guys,
If you are looking to add some watermark into your charts. You can use this indicator.
You can add add a title and a subtitle, if you want to write in diferents lines, you can use as you can see in the script.
All the features are customizable: position, text size, text color, background.
Enjoy it.
Opening Range Breakout with Price TargetsJust publishing a version of the script amitgandhinz already created, which is amazing.
Added fib levels that amitgandhinz already started but commented out
Added mid point that is often found effective as a starting point, SL, etc
Price ProfileThe indicator shows number of candles present in the horizontal box areas for the given time window. You can set up:
1) Start time
2) Stop time
3) Number of horizontal bars
Machine Learning: kNN (New Approach)Description:
kNN is a very robust and simple method for data classification and prediction. It is very effective if the training data is large. However, it is distinguished by difficulty at determining its main parameter, K (a number of nearest neighbors), beforehand. The computation cost is also quite high because we need to compute distance of each instance to all training samples. Nevertheless, in algorithmic trading KNN is reported to perform on a par with such techniques as SVM and Random Forest. It is also widely used in the area of data science.
The input data is just a long series of prices over time without any particular features. The value to be predicted is just the next bar's price. The way that this problem is solved for both nearest neighbor techniques and for some other types of prediction algorithms is to create training records by taking, for instance, 10 consecutive prices and using the first 9 as predictor values and the 10th as the prediction value. Doing this way, given 100 data points in your time series you could create 10 different training records. It's possible to create even more training records than 10 by creating a new record starting at every data point. For instance, you could take the first 10 data points and create a record. Then you could take the 10 consecutive data points starting at the second data point, the 10 consecutive data points starting at the third data point, etc.
By default, shown are only 10 initial data points as predictor values and the 6th as the prediction value.
Here is a step-by-step workthrough on how to compute K nearest neighbors (KNN) algorithm for quantitative data:
1. Determine parameter K = number of nearest neighbors.
2. Calculate the distance between the instance and all the training samples. As we are dealing with one-dimensional distance, we simply take absolute value from the instance to value of x (| x – v |).
3. Rank the distance and determine nearest neighbors based on the K'th minimum distance.
4. Gather the values of the nearest neighbors.
5. Use average of nearest neighbors as the prediction value of the instance.
The original logic of the algorithm was slightly modified, and as a result at approx. N=17 the resulting curve nicely approximates that of the sma(20). See the description below. Beside the sma-like MA this algorithm also gives you a hint on the direction of the next bar move.
Impulse Strategy Signals V2This is a low timeframe strategy based on SMMAs and RSI, shared by Investishare.
This script turns the indicator into a strategy and allows for several variables to be customized.
TPO Profile with Day StatFirst of all I want to Thank @noop42 for creating this wonderful Market Profile chart in Pine script
I have made some changes to this scripts
This Script can auto calculate the TPO Size for NSE Symbols and MCX Crude oil.
This Script Will only calculate the TPO's for visible range only so that the script use less heap size.
I have added some of the day Statistics to enhance your visualization.
Limitations of this Script
Currently This Script can Plot Market Profile Chart only for Historical Data.
It Can only Plot Market Profile Charts in 30-Mins Time Frame only so that you can't use it for Composite Profile Analysis.
To plot Market Profile Chart in Real Time and Historical please use "Market Profile With TPO by Drother"
