Interval Vertical Line DrawerIntroduction
The Interval Vertical Line Drawer is an indicator that assists traders in visualizing specific intervals on the chart. This script enables traders to conduct more accurate analyses across various time frames.
How It Works
This script operates by drawing vertical lines at intervals defined by the user. Users can select the interval for the vertical lines in minutes, and the script automatically places vertical lines at each interval on the chart. For instance, if a 15-minute interval is selected, vertical lines will appear at the start and end times of every 15-minute candle on the chart.
Additionally, this script includes a feature that allows drawing horizontal lines representing the open price of the candles at each vertical line. This is crucial for traders observing price action around specific times and evaluating market conditions at regular intervals.
This script is operative across diverse time frames and can be adjusted to fit various trading styles and analyses. It is efficient, user-friendly, and adaptable to the diverse needs of traders.
The open price of a candle often serves as a support or resistance, and there is a high possibility of significant movement occurring when these S/R levels are breached.
How to Use
VLInterval: Users can input the interval for the vertical lines in minutes and select from 5, 15, 30, 60, 120, 240, 1440.
visibleTimeframe: Users can select the desired time frame where the vertical lines will be visible.
Color and Style: Users can freely modify the color and style of the lines.
Apply the indicator to the chart.
Select the desired interval for the vertical lines.
Adjust the visibility and style of the lines as needed.
By adhering to these steps, traders can effectively incorporate this tool into their analysis, maximizing the utility of interval-based evaluations and observations.
소개
간격 수직 선 그리기 도구는 트레이더가 차트에서 특정 간격을 시각화할 수 있도록 도와주는 지표입니다. 이 스크립트는 트레이더들이 다양한 시간 프레임에서 더 정확한 분석을 수행할 수 있게 해줍니다.
작동 원리
이 스크립트는 사용자가 정의한 간격에서 수직선을 그리는 방식으로 작동합니다. 사용자는 분 단위로 수직선 간격을 선택할 수 있고, 스크립트는 자동으로 차트의 각 간격에 수직선을 배치합니다. 예를 들어, 15분 간격이 선택되면, 차트에는 15분봉의 시작, 종료 시간마다 수직선이 나타납니다.
더불어, 이 스크립트는 각 수직선에서의 캔들의 시가를 나타내는 수평선을 그릴 수 있는 기능도 포함하고 있습니다. 이는 트레이더가 특정 시간 주변의 가격 행동을 관찰하고 정기적인 간격으로 시장 상황을 평가하는데 중요합니다.
이 스크립트는 다양한 시간 프레임에서 작동하며, 다양한 거래 스타일과 분석에 맞게 조정할 수 있습니다. 이는 효율적이고 사용자 친화적이며, 트레이더의 다양한 필요에 적응할 수 있습니다.
캔들의 시작가는 종종 지지 또는 저항의 역할을 하며, S/R이 깨질 때 큰 움직임이 일어날 가능성이 높습니다.
사용 방법
VLInterval: 사용자는 분 단위로 수직선 간격을 입력할 수 있으며, 5, 15, 30, 60, 120, 240, 1440 중에서 선택할 수 있습니다.
visibleTimeframe: 사용자는 수직선이 보이게 될 원하는 시간 프레임을 선택할 수 있습니다.
색상과 스타일: 사용자는 선의 색상과 스타일을 자유롭게 수정할 수 있습니다.
지표를 차트에 적용합니다.
수직선의 원하는 간격을 선택합니다.
선의 가시성과 스타일을 필요에 맞게 조정합니다.
在脚本中搜索"涨幅超过60日均线的股票"
Cycles: 4x dual inputs: Swing / Time Cycles projected forward//Purpose/Premise:
To project forward vertical 'cycle' lines based on user-input anchor points, and to search for confluence.
The idea being that if several well-anchored cycles agree (i.e. we see multiple bunched vertical line confluence in the future), then this may add support to an already existing trade idea, or may indicate an increased likelihood of a shift in direction.
//Usage & notes:
~In the above chart I've anchored to obvious swing lows and swing highs in Btc/Usd from 2020-2022. You could also use fixed time-based cycles from a favored start anchor point. Bars per cycle are printed at the top of each cycle box if your're interested in time cycles. I.e. for 1, 2, 3 month cycles: for BTC you could use 30, 60, 90 bars on daily; for S&P you could use 20, 40, 60 bars on daily.
~On first loading the indicator you will be asked select 'start date', and 'end date' for each of 4 sessions (8x clicks on chart). After this you can easily reset points by clicking the indicator display line three dots>> reset points. Or you can simply drag the vertical box edges (purple lines) to change your cycle anchor points.
~Be sure the start anchor point is before the end anchor point or box/lines won't appear.
~When you drop down to low timeframes you might get bar_index error due to history available: you need then to click the three dots on indicator display line >> reset points >> 8x clicks on the chart.
~Vertical projected lines will match the color of the cycle box they origninate from.
~Lines will project into the future as far as is allowed by tradingview (500 bars max)
//Inputs:
~Time start and end dates for each cycle (change these as described above, or input manually)
~Show/hide each cycle (default is show all 4)
~Formatting options: color of forward projected lines, line width, line style, line / box / text color.
~Box transparancy: Set to 100 to make boxes invisible & declutter the chart. Set to 0 for maximum opacity. Default is 80.
thanks to @Sathyamurthie for his ideas on cycle confluence which caused me to write this.
libHTF[without request.security()]Library "libHTF"
libHTF: use HTF values without request.security()
This library enables to use HTF candles without request.security().
Basic data structure
Using to access values in the same manner as series variable.
The last member of HTF array is always latest current TF's data.
If new bar in HTF(same as last bar closes), new member is pushed to HTF array.
2nd from the last member of HTF array is latest fixed(closed) bar.
HTF: How to use
1. set TF
tf_higher() function selects higher TF. TF steps are ("1","5","15","60","240","D","W","M","3M","6M","Y").
example:
tfChart = timeframe.period
htf1 = tf_higher(tfChart)
2. set HTF matrix
htf_candle() function returns 1 bool and 1 matrix.
bool is a flag for start of new candle in HTF context.
matrix is HTF candle data(0:open,1:time_open,2:close,3:time_close,4:high,5:time:high,6:low,7:time_low).
example:
=htf_candle(htf1)
3. how to access HTF candle data
you can get values using .lastx() method.
please be careful, return value is always float evenif it is "time". you need to cast to int time value when using for xloc.bartime.
example:
htf1open=m1.lastx("open")
htf1close=m1.lastx("close")
//if you need to use histrical value.
lastopen=open
lasthtf1open=m1.lastx("open",1)
4. how to store Data of HTF context
you have to use array to store data of HTF context.
array.htf_push() method handles the last member of array. if new_bar in HTF, it push new member. otherwise it set value to the last member.
example:
array a_close=array.new(1,na)
a_close.htf_push(b_new_bar1,m1.lastx("close"))
HTFsrc: How to use
1. how to setup src.
set_src() function is set current tf's src from string(open/high/low/close/hl2/hlc3/ohlc4/hlcc4).
set_htfsrc() function returns src array of HTF candle.
example:
_src="ohlc4"
src=set_src(_src)
htf1src=set_htfsrc(_src,b_new_bar1,m1)
(if you need to use HTF src in series float)
s_htf1src=htf1src.lastx()
HighLow: How to use
1. set HTF arrays
highlow() and htfhighlow() function calculates high/low and return high/low prices and time.
the functions return 1 int and 8arrays.
int is a flag for new high(1) or new low(-1).
arrays are high/low and return high/low data. float for price, int for time.
example
=
highlow()
=
htfhighlow(m1)
2. how to access HighLow data
you can get values using .lastx() method.
example:
if i_renew==1
myhigh=a_high.lastx()
//if you need to use histrical value.
myhigh=a_high.lastx(1)
other functions
functions for HTF candle matrix or HTF src array in this script are
htf_sma()/htf_ema()/htf_rma()
htf_rsi()/htf_rci()/htf_dmi()
method lastx(arrayid, lastindex)
method like array.last. it returns lastindex from the last member, if parameter is set.
Namespace types: float
Parameters:
arrayid (float )
lastindex (int) : (int) default value is "0"(the last member). if you need to access historical value, increment it(same manner as series vars).
Returns: float value of lastindex from the last member of the array. returns na, if fail.
method lastx(arrayid, lastindex)
method like array.last. it returns lastindex from the last member, if parameter is set.
Namespace types: int
Parameters:
arrayid (int )
lastindex (int) : (int) default value is "0"(the last member). if you need to access historical value, increment it(same manner as series vars).
Returns: int value of lastindex from the last member of the array. returns na, if fail.
method lastx(m, _type, lastindex)
method for handling htf matrix.
Namespace types: matrix
Parameters:
m (matrix) : (matrix) matrix for htf candle.
_type (string) : (string) value type of htf candle:
lastindex (int) : (int) default value is "0"(the last member).
Returns: (float) value of htf candle. (caution: need to cast float to int to use time values!)
method set_last(arrayid, val)
method to set a value of the last member of the array. it sets value to the last member.
Namespace types: float
Parameters:
arrayid (float )
val (float) : (float) value to set.
Returns: nothing
method htf_push(arrayid, b, val)
method to push new member to htf context. if new bar in htf, it works as push. else it works as set_last.
Namespace types: float
Parameters:
arrayid (float )
b (bool) : (bool) true:push,false:set_last
val (float) : (float) _f the value to set.
Returns: nothing
method tf_higher(tf)
method to set higher tf from tf string. TF steps are .
Namespace types: series string, simple string, input string, const string
Parameters:
tf (string) : (string) tf string
Returns: (string) string of higher tf.
htf_candle(_tf, _TZ)
build htf candles
Parameters:
_tf (string) : (string) tf string.
_TZ (string) : of timezone. default value is "GMT+3".
Returns: bool for new bar@htf and matrix for snapshot of htf candle
set_src(_src_type)
set src.
Parameters:
_src_type (string) : (string) type of source:
Returns: (series float) src value
set_htfsrc(_src_type, _nb, _m)
set htf src.
Parameters:
_src_type (string) : (string) type of source:
_nb (bool) : (bool) flag of new bar
_m (matrix) : (matrix) matrix for htf candle.
Returns: (array) array of src value
is_up()
last_is_up()
peak_bottom(_latest, _last)
Parameters:
_latest (bool)
_last (bool)
htf_is_up(_m)
Parameters:
_m (matrix)
htf_last_is_up(_m)
Parameters:
_m (matrix)
highlow(_b_bartime_price)
Parameters:
_b_bartime_price (bool)
htfhighlow(_m, _b_bartime_price)
Parameters:
_m (matrix)
_b_bartime_price (bool)
htf_sma(_a_src, _len)
Parameters:
_a_src (float )
_len (int)
htf_rma(_a_src, _new_bar, _len)
Parameters:
_a_src (float )
_new_bar (bool)
_len (int)
htf_ema(_a_src, _new_bar, _len)
Parameters:
_a_src (float )
_new_bar (bool)
_len (int)
htf_rsi(_a_src, _new_bar, _len)
Parameters:
_a_src (float )
_new_bar (bool)
_len (int)
rci(_src, _len)
Parameters:
_src (float)
_len (int)
htf_rci(_a_src, _len)
Parameters:
_a_src (float )
_len (int)
htf_dmi(_m, _new_bar, _len, _ma_type)
Parameters:
_m (matrix)
_new_bar (bool)
_len (int)
_ma_type (string)
Bull and Bear Market '20% IndicatorThis indicator uses the somewhat crude method of calculating bear/bull markets using the following popular ' 20% rule ':
A bear market begins when an asset trades 20% below its recent high for more than two months, a bear market ends when an asset trades 20% above its recent low for one month or more.
The 1d time-frame should be used, here's why:
"A bear market begins when an asset trades 20% below its recent high for more than two months."
If we take the standard trading month to be around 20-22 days (excluding weekends), then two months would be approximately 40-44 days. This is why we set the `bearDuration` to 60 days in the script to capture the "more than two months" criteria. Using a daily timeframe, 60 bars represent roughly 3 months (since markets are not open every day due to weekends and holidays).
"...a bear market ends when an asset trades 20% above its recent low for one month or more."
This is why the `bullDuration` is set to 20 days in the script, which represents roughly one trading month on a daily timeframe.
So, to capture the mentioned bear and bull market definitions, you'd want to apply the script on a daily (1d/1D) chart.
Expected Move from RSI [SS]Publishing this experimental indicator.
What it does:
The indicator uses a user-defined lookback period on a user-defined timeframe to lookback at all instances of RSI. It breaks RSI down as follows:
RSI between
0 - 10
10 - 20
20 - 30
30 - 40
40 - 50
50 - 60
60 - 70
70 - 80
80 - 90
90 - 100
From there, it stores the ticker's move from open to high and open to low. It will then use this data to look at the current RSI based on the specified timeframe and plot the expected move based on the average move the ticker does with a similar RSI reading.
It will plot the expected range, with the high range being plotted in green and the low range being plotted in red.
It will also display an infographic that dictates the current RSI based on the selected time frame, the anticipated up move and the anticipated down move. This infographic will also tell you the strength of the relationship (correlation) RSI has with the ticker's high or low price:
From there the user can determine whether this RSI reading is traditionally bullish or bearish for the ticker. A greater down move indicates that the RSI traditionally elicits a bearish response. A greater up move indicates the inverse.
The user can also view a chart of a breakdown of the anticipated moves based on RSI. If the option to "Show Expected Move Table" is select in the settings menu, the following table will appear:
From here you can see the average up move and down move a ticker does based on its corresponding RSI reading.
NOTE: When using the table, please adjust your chart timeframe to the selected timeframe on the indicator. Thus, if you are looking at the 1 hour levels, please adjust your chart to the 1 hour timeframe to use the chart.
Additional Note: When using the table, an "NaN" means that there are no instances of the ticker being at that RSI level within the designated timeframe period. You can extend your lookback period to up to 500 candles to see if it finds additional instances of similar RSI. Otherwise, you can adjust the selected timeframe.
Uses:
The indicator can be used on all timeframes. It can help give you an idea as to whether the RSI indicates a bearish or bullish sentiment.
It can signal a potential reversal or continuation. It can also help you with determining target prices for day trades and scalp trades.
And that is the indicator. Its pretty straight forward. It is experimental and new, so feel free to play around with it and let me know your thoughts.
Safe trades everyone and thank you for reading!
RD Opening Range/Initial BalanceIntroducing the RD Opening Range/Initial Balance indicator. The opening range is the first 60 minutes of trading action for a given day (High, Mid, and Low).
The market tends to put significance in these levels, that's why we use them in our trade system.
There is also a data panel:
Today - Today's opening range value
W-Avg - This weeks average
20D CA-OH - the total number of closes above the opening range over the last 20 days (above high)
20D CA-OL - the total number of closes below the opening range over the last 20 days (below low)
* We do plan to add additional data points.
* Only the last OR has labels, we will not be adding them or an option in the future.
* Full customization in setting panel. Color of lines, background, no display of data panel and more.
How to Use
These levels act as dual magnets. They both attract price and repel price.
You use price action and rules to decipher if price is being attracted or repelled.
You will notice as you use this indicator that price respects these levels. Often when answering the 3Qs one of these levels is in play.
During the cash market these levels play a significant role in price action. Even during the Globex/Overnight session these levels are a factor.
Circle areas are examples of price reactions at OR key levels:
If you trade with the RDTS you already know how to use these levels as reaction and target zones.
For clues on which level price is being repelled or attracted I'd suggest you utilize bias and momentum indicators like the RDA.
Initial Balance vs Opening Range
Before we move on and discuss how to use this indicator I want to mention what I consider the difference between the Opening Range and the Initial Balance.
I've adopted the Opening Range verbiage for the first 60 minutes of trading even though the Opening Range is often defined as the first 15m or first 30m.
The more accurate term for the first 60m should be Initial Balance. I'm not sure exactly where this originated but I learned this term when I was heavily trading TPO-- the IB is the first 2 30m blocks of trading.
Any questions or improvements just comment below.
This script was created in by both Bhangerang (an Alpha member of the RDTS) with help by @RexDogActual as well as permission to publish.
Liquidation Levels on OIThis indicator is used to display estimated contract liquidation prices. When there are dense liquidation areas on the chart, it indicates that there may be a lot of liquidity at that price level. The horizontal lines of different colors on the chart represent different leverage ratios. See below for details.
Let me introduce the principle behind this indicator:
1. When position trading volume increases or decreases significantly higher than usual levels in a specific candlestick chart, it indicates that a large number of contracts were opened during that period. We use the 60-day moving average change as a benchmark line. If the position trading volume changes more than 1.2x, 2x or 3x its MA60 value, it is considered small, medium or large abnormal increase or decrease.
2. This indicator takes an approximate average between high, open, low and close prices of that candlestick as opening price.
3. Since contracts involve liquidity provided by both buyers and sellers with equal amounts of long and short positions corresponding to each contract respectively; since we cannot determine actual settlement prices for contract positions; therefore this indicator estimates settlement prices instead which marks five times (5x), ten times (10x), twenty-five times (25x), fifty times (50x) and one hundred times (100x) long/short settlement prices corresponding to each candlestick chart generating liquidation lines with different colors representing different leverage levels.
4. We can view areas where dense liquidation lines appear as potential liquidation zones which will have high liquidity.
5. We can adjust orders based on predicted liquidation areas because most patterns in these areas will be quickly broken.
6. We provide a density histogram to display the liquidation density of each price range.
Special thanks to the following TradingView community members for providing open-source indicators and contributing to the development of this indicator!
Liquidation - @Mysterysauce
Open Interest Delta - By Leviathan - @LeviathanCapital
Regarding the relationship with the above-mentioned open source indicators:
1. Indicator Liquidation - @Mysterysauce can also draw a liquidation line in the chart, but:
(1) Our indicator generates a liquidation line based on abnormal changes in open interest; their indicator generates a liquidation line based on trading volume.
(2) Our indicator will generate both long and short liquidation lines at the same time; their indicator will only generate a liquidation line in a single direction.
We refer to their method of drawing liquidation lines when drawing our own.
2. Indicator Open Interest Delta - By Leviathan - @LeviathanCapital obtained OI data for Binance USDT perpetual contracts in the code. We refer to their method of obtaining OI data in our code.
============= 中文版本 =============
此指标用于显示估计合约清算价格。当图表上有密集的清算区域时，表示该价格水平可能存在大量流动性。图表上不同颜色的水平线代表不同杠杆比率。详情请参见下面的说明。
让我介绍一下这个指标背后的原理：
1. 当特定蜡烛图对应的合约仓位增加量（OI Delta）显著高于通常水平时，表示在那段时间有大量合约开仓。我们使用OI Delta的60日移动均线作为基准线。如果OI Delta超过其MA60值的1.2倍、2倍或3倍，则认为是小型、中型或大型的异常OI Delta。
2. 该指标将上述蜡烛图高、开、低和收盘价的平均值作为近似的合约开仓价。
3. 由于合约涉及买方和卖方之间相互提供流动性，每个合约对应相等数量的多头和空头头寸。由于我们无法确定合约头寸的实际清算价格，因此该指标估计了清算价格。它标记了与该蜡烛图相对应的多头和空头5倍、10倍、25倍、50倍和100倍的清算价格，生成清算线。不同杠杆水平用不同颜色表示。
4. 我们可以将出现密集清算线的区域视为潜在的清算区域。这些区域将具有高流动性。
5. 我们可以根据预测到的清算区域调整自己的订单，因为根据规律，这些清算区域大部分都会很快被击穿。
6. 我们提供了密度直方图来显示每个价格范围的清算密度
特别感谢以下TradingView社区成员提供开源指标并为该指标的开发做出贡献！
Liquidation - @Mysterysauce
Open Interest Delta - By Leviathan - @LeviathanCapital
与上述开源指标的关系：
1. 指标Liquidation - @Mysterysauce也可以在图中绘制清算线，但是：
（1）我们的指标是基于open interest的异常变化生成的清算线；他们的指标是基于成交量生成的清算线
（2）我们的指标会同时生成多头和空头清算线；他们的指标仅会在单一方向生成清算线
我们的指标在绘制清算线上参考了他们绘制清算线的方式
2. 指标Open Interest Delta - By Leviathan - @LeviathanCapital在代码中获取了Binance USDT永续合约的OI数据。我们在代码中参考他们获取OI数据的方式
Automated Option Price - Black-Scholes modelPlease make sure you are plotting this indicator on DAILY bars, not doing so will lead to unintended results. Also, make sure that you keep up to date the Risk-free interest rate, which you can consult (for U.S.) on ycharts.com.
This is an indicator that is meant to be used for Options Day Trading, but it can be useful for mid-term or leaps for I also enabled the possibility for user to input manually the Strike and Expiration date. I based the calculation on the Black-Scholes model. Variables included in the calculation are:
-Stock price (S): The current price of the underlying asset (e.g., a stock).
-Strike price (K): The predetermined price at which the option can be exercised.
-Time to expiration (T): The time remaining until the option expires, expressed as a fraction of a year.
-Volatility (σ): The annualized standard deviation of the stock's returns, which is a measure of the stock's price fluctuations.
-Risk-free interest rate (r): The annualized return on a risk-free investment, often approximated by the yield on a government bond.
The only variable I excluded from the original model was the Dividend yield (q).
U S E R I N P U T S:
1. AUTOMATIC calculations enabled:
i) Strike price (K):
Automatically calculate the strike price for both call and put options based on the stock's closing price. The logic follows a set of rules to determine the strike prices which will usually be Out-of-the-Money (OTM):
-If the stock's closing price is between 1 and 60, the call strike price is rounded up to the nearest whole number, while the put strike price is rounded down to the nearest whole number.
-If the stock's closing price is between 60 and 90, the call strike price is rounded up to the nearest whole number and increased by 1, while the put strike price is rounded down to the nearest whole number and decreased by 1.
-If the stock's closing price is between 90 and 120, the call strike price is rounded up to the nearest whole number and increased by 2, while the put strike price is rounded down to the nearest whole number and decreased by 2.
-If the stock's closing price is above 120, the call strike price is rounded up to the nearest multiple of 5, while the put strike price is rounded down to the nearest multiple of 5.
By applying these rules, I just tried to ensure that the automatically calculated strike prices are tailored to the stock's price range, allowing for more accurate option pricing calculations.
ii) Time to expiration (T):
The indicator will consider this week’s expiration contracts (Friday) only when the current day/bar = Monday. If Tuesday or older it will consider the expiration date of the next week’s Friday (because we are not Theta gamblers, right?).
If you are not comfortable with above for whatever reason, you can always…
2. Enter inputs MANUALLY
First make sure you UNTICK the boxes for automatic calculation.
i) Strike price (K) – Self-explanatory
ii) Time to expiration (T) – Just make sure that the horizon you are inputting matches with the next parameter (e.g. you would not input a Monthly risk-free interest rate for a Leap).
iii) Risk-free interest rate (r) – You can pull this data from the web. Here’s the link I used to define the value that this indicator was launched with:
ycharts.com
Don’t get obsessed with updating this daily if you are using this for day trading, you will notice that weekly may be more than enough.
V O L A T I L I T Y
Not option to manually input Volatility so I’ll explain how it is calculated in this script:
I considered two measures of volatility; one is derived calculating the annualized volatility using the standard deviation of daily returns and the second one is the ATR-based annualized volatility. I then used a ‘combined’ approach with the harmonic mean and the arithmetic mean of these results which can help account for the variability in the option prices calculated with different volatility estimates, which can be more robust when dealing with outliers or skewed data. I back tested with some samples of actual option prices and found that this approach is the one that got results closer to the actual bids.
T A B L E
Nomenclature to read rows is:
Option Strike Price | Type of Option (Put or Call) @ The current Close or at 50% level of bar | Estimated Price
*The Option expiration Date showed as dd-MMM as part of the headers.
Second and third row (color 1): These will show the calculated value for the Put/Call, assuming you are buying at the CURRENT price of the stock.
Third and Fifth row (color2): These will show the calculated value for the Put/Call, assuming you buy at the 50% level of the current bar (this is the value that the contract WOULD HAVE at the 50% level of the bar).
If you plot the indicator during market hours it will obviously update as price moves, this is an intended feature.
L I M I T A T I O N S
The Black-Scholes model, like many other models, has its limitations and will oftentimes provide inaccurate option prices in all market conditions. High volatility events, such as earnings announcements, can lead to significant price fluctuations that are not fully captured by the model.
The model assumes that the stock price follows a continuous random walk with constant volatility, but in reality, volatility can change over time, and stock prices can exhibit jumps, especially around significant events like earnings announcements. This can cause the model to underestimate the true option price in such situations.
Please make sure that you first back test on the symbols you trade to ensure the information presented by this indicator will suit your trading strategy. You will find that the delta between the proposed price of the indicator versus the actual price may differ significantly in some symbols while for others it will be very close. For instance, today (13APR23), the prices for AMD, DIS, AAPL (puts only), were very close to actual bids, whereas TSLA differ significantly (but then again, take a look at the calendar and this last symbol is having earnings next week which may add a premium to the contracts)… I am sure you will get your own conclusions and applicable use cases based on the data you test with.
As always, be wise and methodical on the investment or trading decisions you make!
Acceleration-Based MA Slope PredictionHello traders,
I developed this indicator while working on a trading strategy using moving average slope and acceleration, and I found the concept interesting enough to share it.
Let me briefly explain this indicator.
----About White Plot----
1. Calculate the first derivative approximation at the current point of the Moving Average, and then calculate the second derivative approximation to obtain the 'Acceleration'.
2. Where the acceleration is 0, it signifies a change in the force of the moving average.
3. Therefore, by drawing a parabola based on the acceleration at that time, can depict the parabolic shape of the moving average.
This is represented as a white circle on the indicator.
4. These circles are reset at the next point where the acceleration is 0, indicating a change in the parabolic force.
If the moving average rises more sharply than the predicted value of the rising parabola, a more drastic increase is expected.
5. In this case, you can start risk management around the time the drawn parabola breaks.
(The actual MA is represented by green/red lines)
6. Before the trend changes, i.e., before the direction of the moving average changes, there is a section where the acceleration is 0, and this is represented on the chart as follows.
(The lower indicator shows the acceleration of the corresponding parabola)
----About Red Plot----
1. Calculate the first derivative approximation of the moving average value, the 'slope'.
2. Where the slope is 0, it represents the extreme point of the parabola.
3. Therefore, by using the acceleration at that point as the coefficient of the quadratic function and setting the extreme point as a vertex, we can draw a quadratic function. This is represented as a red circle on the indicator.
(Keep in mind that the actual moving average is not a quadratic function; this is a "forced" quadratic function assuming the parabola is maintained)
4. These circles are reset at the next extreme point where the slope is 0, and a new quadratic function is created.
Based on the formula obtained in the above process, you can predict the future moving average through 'offset'.
5. That is, if the x value at the current point is 'k', you can predict the moving average one candle ahead by substituting (k+1) into the quadratic function.
The predicted value at the past position is shown as a red circle.
6. The smoother the chosen moving average, the fewer extreme points will appear, and the higher the likelihood of the parabola fitting.
For the T3 set as the default value, it shows very high accuracy even when predicting about 20 candles ahead.
On the other hand, rough moving averages like SMA have limited prediction value.
(SMA 60, offset = 10)
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The moving average with a very high level of accuracy is JMA (Jurik Moving Average). However, since the code for this moving average is not public, I recommend those interested to check it through my code.
Additionally, I believe the code of this indicator I've uploaded has significant utility.
As an example, you can use the breaking point of the parabola predicted by the acceleration to determine when the force changes again for entries/losses. There are many other possible applications as well.
I look forward to seeing more excellent results from this indicator.
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안녕하세요 트레이더여러분.
이 지표는, 제가 이동평균선의 기울기와 가속도를 이용하여 매매를 하기 위한 지표를 개발하다가, 흥미로운 내용이라고 판단하여 만들게 되었습니다.
이 지표에 대해 간단히 설명드리겠습니다.
----하얀색 플롯에 대해----
1. 이동평균선이 진행되는 현재 시점에서 미분의 근사값을 구하고, 다시 한 번 미분의 근사값을 구해서 '가속도'를 얻습니다.
2. 가속도가 0이 되는 곳은, 곧 해당 이동평균선의 힘이 바뀌는 곳을 의미합니다.
3. 따라서, 그 당시 시점 기준으로 포물선을 그려낸다면, 가속도를 이용하여 해당 이동평균선의 포물선을 그려낼 수 있습니다. 이것은 지표의 하얀색점로서 표기됩니다.
4. 이 때, 이러한 점들은 다음의 가속도가 0이 되는 지점, 즉 포물선의 힘이 바뀌는 곳에서 다시 초기화됩니다.
5. 올라가고 있던 포물선에서의 예측치보다 이동평균선이 더 급하게 올라간다면, 더욱 급격한 상승이 예상됩니다. 이 경우, 그려지고있는 포물선이 깨질 때쯤부터 리스크 관리를 시작할 수 있습니다.
(녹색/빨간색의 선으로 실제 MA를 표현했습니다. 거슬리시면 '모습'가셔서 끄셔도 좋습니다. )
6. 추세가 변경되기 전, 즉 이동평균선의 방향이 바뀌기 전에는 가속도가 0이 되는 구간이 존재하고, 그것이 차트 위에 다음과같이 표현됩니다.
(하단의 지표는, 해당 포물선의 가속도을 나타냅니다)
----붉은색 플롯에 대해----
1. 이동평균선 값을 미분 근사값 즉, '기울기'를 구합니다.
2. 기울기가 0이 되는 곳은, 포물선이 극점이 되는 곳을 뜻합니다.
3. 따라서, 해당 시점의 가속도를 2차함수의 계수로 하여, 또한 해당 극점을 하나의 꼭지점으로 설정하여,이차함수를 그려낼 수 있습니다. 이것은 지표의 빨간색점으로서 표현됩니다.
(실제 이동평균선은 2차함수가 아니기에, 포물선이 유지된다는 가정 하에 "억지로"만들어낸 이차함수입니다)
4. 이 때, 이러한 점은 다음 극점이 0이 되는 곳에서 초기화되고 이차함수가 만들어집니다.
5. 위의 과정에서 얻은 식을 바탕으로 'offset'을 통해 미래의 이동평균선을 예측할 수 있습니다.
즉, 현재시점의 x값을 'k'라고 한다면, (k+1)을 이차함수에 대입하여 1캔들 앞의 이동평균선을 예측할 수 있습니다.
해당 예측치가 지나간 자리는, 빨간색점을 통해 보여집니다.
6. 선택한 이동평균선이 스무스할수록 극점은 덜 등장하게되고, 포물선의 위치가 맞아들어갈 가능성이 높습니다.
현재 디폴트값으로 설정된 T3의 경우, 약 20캔들 앞을 예측해도 매우 높은 정확도를 보여줍니다.
반면에, SMA와 같이 울퉁불퉁한 이동평균선은 가능한 예측치가 크지 않습니다.
(SMA 60, offset=10)
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매우 높은 수준의 정확도를 보여준 이동평균선은 JMA(Jurik Moving Average)입니다. 다만 이 이동평균선은 코드가 공개되지 않았기때문에, 관심있으신 분은 저의 코드를 통해 한번 확인해보시길 권장드립니다.
추가로, 제가 올린 이 지표의 코드는 이용가치가 높다고 생각합니다.
하나의 예시로서, 가속도로 예측한 포물선이 깨지는 곳을 기준으로, 힘이 다시 한 번 바뀌는 것을 이용해 진입/로스를 할 수 있습니다. 그 외에도 매우 다양한 활용이 가능합니다.
이 지표를 통해 더욱 좋은 새로운 결과물이 나오길 기대해봅니다.
The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)
Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits.
Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend.
The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines.
Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits.
Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels.
The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading.
Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now!
General Comments
This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts.
Detailed Description
The “Flash” script considers the following indicators for the generation of trading signals:
1. Momentum-RSI
2. ‘Super-Trend’-Analysis
3. EMA-Strategy
1. Momentum-RSI
• This indicator signals the strength of the underlying upward- or downward-trend.
• The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend.
• The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals).
• This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend.
Graph 1 shows this concept:
• The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods.
Example (graph 2):
2. Super-Trend Analysis
• The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively).
• If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered.
• The vice-versa approach can be considered for short entries.
Graph 3 explains this concept:
3. Exponential Moving Average / EMA-Strategy
The functionality of this EMA-element of the strategy has been programmed as follows:
• The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals.
• Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line.
• Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line.
An example is shown in graph 4 below:
We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement.
4. Bringing it all together
This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy.
The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met:
1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5):
2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively.
3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively.
The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success.
Example for Long-Entry (graph 6):
When these conditions are met, our Long position is opened.
Example for Short-Entry (graph 7):
Trade Management Options (graph 8)
Option 1
In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters.
The following settings of the supertrend-indicator can be changed and optimized (graph 9):
The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment.
Option 2 (graph 10):
Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart.
Settings options (graph 11):
The following settings can be changed for the three elements of this strategy:
1. (Length Mom-Rsi): Length of our Mom-RSI indicator.
2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals.
3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend
4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind
5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind
6. The backtesting period can be adjusted: Start and End time of BackTest
7. Dollar cost per position: this is relevant for 100% fully automated trading.
8. Trade direction can be adjusted: LONG, SHORT or BOTH
9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 )
Display options on the charts graph 12):
1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts.
2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend.
Other comments
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
TOMMAR#TOMMAR #MultiMovingAverages #MMAR
Dear fellow traders, this is Tommy, and today I'd like to introduce you to the Multi-Moving Averages Ribbon (MMAR) indicator, which I believe to be one of the best MMAR indicators available on TradingView. Moving Averages is a popular technical analysis tool used to smooth out price data by creating an average of past price data points over a specified time period. They can be used to identify trends and provide a clearer view of price action, as well as generate buy and sell signals by observing crossovers between different moving average lines.
In the MMAR indicator, we have incorporated 12 different types of Moving Averages, including Simple Moving Averages (SMA), Exponential Moving Averages (EMA), Weighted Moving Averages (WMA), Hull Moving Averages (HMA), and Smoothed Moving Averages (SMMA), among others. This allows traders to choose the optimal type for their preferred trading commodities.
One common technique in technical analysis is using multiple Moving Averages with varying lengths, which provides a more comprehensive view of price action. By analyzing multiple Moving Averages with different timeframes, traders can better understand both short- and long-term trends and make more informed trading decisions. Some of the well-known combinations of multiple moving averages used by traders are (5, 9, 14, 21, 45), (6, 11, 16, 22, 51), [8, 13, 21, 55), (50, 100, 200), and (60, 120, 240).
Another way to gauge the strength of the market trend is to look for the arrangement of the Moving Averages. If they are in a sequential order, with the shortest on top and the longest on the bottom, it is most likely a bullish trend. On the other hand, if they are arranged in reverse order, with the shortest on the bottom and the longest on top, it is most likely a bearish trend. The 'Trend Light' in the indicator settings will automatically signal when the Moving Averages are in either an orderly or reverse arrangement.
Lastly, I have added a useful feature to the indicator: the 'MA Projection'. This feature projects and forecasts the Moving Averages in the future, allowing traders to easily identify confluence zones in future candlesticks. Please note that the projection levels may change in the case of extreme price action that significantly affects the Moving Averages.
This is free so any Tradingview users can use this indicator. Just search TOMMAR in the indicator section located on top of the chart.
#TOMMAR #MultiMovingAverages #MMAR
안녕하세요 트레이더 여러분, 토미입니다. 오늘 여러분들에게 소개드릴 지표는 다양한 길이의 이동평균선 조합을 사용할 수 있는 MMAR (Multiple Moving Averages Ribbon)입니다. 아마 제가 만든 MMAR 지표가 트레이딩뷰에서 가장 쓸만할 겁니다. 이동평균선, 줄여서 이평선은 말 그대로 특정 기간 범위 내의 주가들을 평균한 값들로 이루어진 선입니다. 제가 이평선 관련된 강의 자료는 예전에 올려드린 바 있으니 더 자세한 내용이 궁금하신 분들은 아래 링크/이미지 클릭하시길 바랍니다.
본 지표는 Simple Moving Averages (SMA), Exponential Moving Averages (EMA), Weighted Moving Averages (WMA), Hull Moving Averages (HMA), 그리고 Smoothed Moving Averages (SMMA) 등을 포함해 총 12개 종류의 이평선 지표를 사용할 수 있습니다. 또한 각 이평선의 길이들도 하나하나 일일이 설정하실 수 있습니다. 예를 들어 요즘에 자주 보이는 이평선들의 조합이 , , , , 그리고 등등이 존재하는데 여러분의 취향에 맞게 설정하여 사용하시면 됩니다.
몇 가지 주요 기능에 대해서 설명 드리겠습니다. 설정에서 ‘Trend Light’를 키면 이평선들의 정배열 혹은 역배열 여부를 쉽게 볼 수 있습니다. 이평선이 정배열일때는 맨 아래의 이평선에 초록불이, 역배열일때는 맨 위의 이평선에 빨간불이 켜지며 둘 다 아닐 땐 아무 불도 켜지지 않습니다. 또한 ‘MA Projection’을 키면 이평선들의 미래 예측 값들을 확장해줍니다. 당연히 가격 변동이 갑자기 크게 나오면 이평선 예측 확장 레벨들이 확 바뀌겠죠.
지표창에 TOMMAR 검색하시거나 아래 즐겨찾기 인디케이터에 넣기 클릭하시면 누구나 사용하실 수 있습니다~ 여러분의 구독, 좋아요, 댓글은 저에게 큰 힘이 됩니다.
RSI Multi Symbol/Time Frame DetectorThis code is an implementation of the Relative Strength Index (RSI) indicator, which is a popular momentum indicator used in technical analysis. The RSI measures the strength of an asset's price action and provides information on whether the asset is overbought or oversold. The code also calculates a moving average of the RSI and allows the user to choose the type of moving average to be calculated (SMA, EMA, SMMA, WMA, or VWMA).
The user can select from different time frames (5, 15, 60, or 240), symbols (SP:SPX, OANDA:EURUSD, or OANDA:NZDUSD), RSI lengths, and moving average types and lengths.
The code starts by defining a function called "ma" for calculating different types of moving averages. This function takes as input the source data for the moving average calculation (the RSI), the length of the moving average, and the type of moving average. The function uses a switch statement to return the appropriate calculation based on the inputted moving average type.
Next, the code calculates the RSI and its moving average. The RSI is calculated using the well-known formula for the RSI, which involves calculating the average gains and losses over a specified period of time and then dividing the average gains by the average losses. The moving average is calculated using the "ma" function defined earlier.
Finally, the code allows the user to choose the symbol and time frame to be used in the RSI calculation, as well as the length of the RSI and the moving average, and the type of moving average. The user can choose from three symbols (SP:SPX, OANDA:EURUSD, OANDA:NZDUSD) and four time frames (5, 15, 60, and 240 minutes). The code then uses the "request.security" function to retrieve the RSI calculation for the selected symbol and time frame.
Note: This code is example for you to use multi timeframe/symbol in your indicator or Strategy , also prevent Repainting Calculation
Setup Max e Min Larry WilliansLarry Williams used this system to win the trading championship
Hello friends, I bring a script with a trading strategy to be used in futures such as Index, Forex and Commodities. Developed by famous trader Larry Williams.
In them we use two 3-period Simple Moving Averages (Arithmetic) (one with the high price, the other with the low price), and a 21-period Moving Average (Arithmetic) to determine the trend. This will form an average channel with the prices of the maximums and minimums of the last three candles.
Best time charts use the strategy: from 5 minutes to 60 minutes.
This strategy is quite simple. The 21 Moving Average will color according to the trend (Green for bullish, Red for bearish and Gray for transitions). The Script will signal the entry according to the trend by the colors of the candles and also by the signal:
When green, the buy will be on the crossing of the lower Moving Average crossing the candlestick, and the exit will be on the crossing of the candlestick on the next Upper Moving Average.
When red, the sell will be at the crossing of the Upper Moving Average crossing the candlestick, and the exit will be at the crossing of the candlestick on the next Lower Moving Average.
When the Script signals the candle with a purple X, it means that the trend is changing and the entire open operation must be closed.
This system has no Stop, so be careful when using it.
Na linguagem do autor:
Larry Williams usou esse sistema ganhar campeonato de trade
Olá amigos, trago um script com uma estratégia de trade pra ser usada em futuros como Índice, Forex e Commodities. Desenvolvido pelo famoso trader Larry Willians.
Neles usamos duas Médias Móveis Simples (Aritmética) de 3 períodos (uma com o preço da máxima, outra com o preço da mínima), e uma Média Móvel (Aritmética) de 21 períodos para determinar a tendência. Nisso vai formar uma canal de médias com os preços das máximas e mínimas dos últimos três candles.
Melhores tempos gráficos usar a estratégia: de 5 minutos até 60 minutos.
Essa estratégia é bem simples. A Média Móvel de 21 irá colorir de acordo com a tendência (Green pra alta, Red para baixa e Gray para transições). O Script irá sinalizar a entrada de acordo com a tendência pela cores dos candles e também pela sinalização:
Quando green, a compra será no cruzamento da Média Móvel inferior cruzando o candle, e a saida será no cruzamento do candle na Média Móvel Superior seguinte.
Quando red, a venda será no cruzamento da Média Móvel Superior cruzando o candle, e a saida será no cruzamento do candle na Média Móvel Inferior seguinte.
Quando o Script sinaliza o candle com X purple, significa que a tendência está em mudança e deve ser fechada toda a operação em aberto.
Este sistema não possui Stop, portando cuidado quanto a seu uso.
Delta Ladder [Kioseff Trading]Hello!
This script presents volume delta data in various forms!
Features
Classic mode: Volume delta boxes oriented to the right of the bar (sell closer / buy further)
On Bar mode: Volume delta boxes oriented on the bar (sell left / buy right)
Pure Ladder mode: Pure volume delta ladder
PoC highlighting
Color-coordinated delta boxes. Marginal volume differences are substantially shaded while large volume differences are lightly shaded.
Volume delta boxes can be merged and delta values removed to generate a color-only canvas reflecting vol. delta differences in price blocks.
Price bars can be split up to 497 times - allowing for greater precision.
Total volume delta for the bar and timestamp included
The image above shows Classic mode - delta blocks are oriented left/right contingent on positive/negative values!
The image above shows the same price sequence; however, delta blocks are superimposed on the price bar. Left-side blocks reflect negative delta while right-side blocks reflect positive delta! To apply this display method - select "On Bar" for the "Data Display Method" setting!
The image above shows "Pure Ladder" mode. Delta blocks remain color-coordinated; however, all delta blocks retain the same x-axis as the price bar they were calculated for!
Additionally, you can select to remove the delta values and merge the delta boxes to generate a color-based canvas indicative of volume delta at traded price levels!
The image above shows the same price sequence; however, the "Volume Assumption" setting is activated.
When active, the indicator assumes a 60/ 40 split when a level is traded at and only one metric - "buy volume" or "sell volume" is recorded. This means there shouldn't be any levels recorded where "buy volume" is greater than 0 and "sell volume" equals 0 and vice versa. While this assumption was performed arbitrarily, it may help better replicate volume delta and OI delta calculations seen on other charting platforms.
This option is configurable; you can select to have the script not assume a 60/ 40 split and instead record volume "as is" at the corresponding price level!
I plan to roll out additional features for the indicator - particularly tick-based price blocks! Stay tuned (:
Thank you!
Expected Move Plotter IntradayHello everyone!
I am releasing my Intra-day expected move plotter indicator.
About the indicator:
This indicator looks at 3 differing time frames, the 15, 30 and 60 minute time frames.
It calculates the average move from high to low over the past 5 candle period and then plots out the expected move based on that average.
It also attempts to determine the sentiment. How it does this is by taking the average of the High, Low and Close of the previous 5 minute candle and comparing it in relation to the close of the current 5 minute candle. It essentially is the premise of pivot points.
Each time frame can be shut off or selected based on your preference, as well as the sentiment fills.
How to use:
Please play around with it and determine how you feel you could best use it, but I can share with you some tips that I have picked up from using this.
Wait for a clear rejection of respect of a level:
Once you have confirmed rejection or support, you can scalp to the next support level:
As well, you can switch between the 30 and 60 minute time frames as reference
30 Minute:
And that's it!
Its a very simplistic indicator, but it is quite helpful to help identify potential areas of reversal.
There really isn't much to it!
Also, it can be used on any stock!
As always, I have provided a quick tutorial video for your reference, linked below:
Let me know if you have any questions or recommendations for modification to make the indicator more useful and helpful.
Thanks so much for checking it out and trying it out everyone!
As always, safe trades and green days!
BankNifty_Bullish_Intraday
The script uses following mechanism to give a signal of BUY if multiple parameters evaluated are all passed.
ENTRY-
1. 5 min MACD should be more than its previous tick
2. 15 min MACD should be more than its previous tick
3. 60 min MACD should be more than its previous tick
4. ADX should be more than 12
5. RSI should be more than 60
6. Stochastic %k should have cross over with %d
7. Bollinger band upper band value should be more than previous tick
EXIT
If the 5 min bar price closes below 5 min EMA , it gives an exit signal.
Volume Profile Volume Delta OI Delta [Kioseff Trading]Hello!
This script serves to distinguish volume delta for any asset and open interest delta for Binance perpetual futures.
The image above provides further explanation of functionality and color correspondence.
The image above shows the indicator calculating volume at each tick level and displaying the metric.
The label color outline (neon effect) is configurable; the image above is absent the feature.
The image above shows Open Interest (OI) Delta calculated - similar to how the script calculates volume delta - for a Binance Perpetual Future pair.
This feature only works for Binance Futures pairs; the script will not load when trying to calculate OI Delta on other assets.
Additionally, a heatmap is displayable should you configure the indicator to calculate it.
The image above shows a heatmap using volume delta calculations.
The image above shows a heatmap using OI delta calculations.
Of course, these calculations - when absent requisite data - require some assumptions to better replicate calculations with access to requisite data.
The indicator assumes a 60/40 split when a tick level is traded at and only one metric - "buy volume" or "sell volume" is recorded. This means there shouldn't be any levels recorded where "buy volume" is greater than 0 and "sell volume" equals 0 and vice versa. While this assumption was performed arbitrarily, it may help better replicate volume delta and OI delta calculations seen on other charting platforms.
This option is configurable; you can select to have the script not assume a 60/40 split and instead record volume "as is" at the corresponding tick level.
The script also divides volume and open interest if a one-minute bar violates multiple tick levels. The volume or open interest generated on the one-minute bar will be divided by the number of tick levels it exceeds. The results are, subsequently, appended to the violated tick levels.
Further, the script can be set to recalculate after a user-defined time threshold is exceeded. You can also define the percentage or tick distance between levels.
Also, it'd be great if this indicator can nicely replicate volume delta indicators on other charting platforms. If you've any ideas on how price action can be used to better assume volume at the corresponding price area please let me know!
Thank you (:
ICT IPDA Look BackThis script automatically calculates and updates ICT's daily IPDA look back time intervals and their respective discount / equilibrium / premium, so you don't have to :)
IPDA stands for Interbank Price Delivery Algorithm. Said algorithm appears to be referencing the past 20, 40, and 60 days intervals as points of reference to define ranges and related PD arrays.
Intraday traders can find most value in the 20 Day Look Back box, by observing imbalances and points of interest.
Longer term traders can reference the 40 and 60 Day Look Back boxes for a clear indication of current market conditions.
Ichimoku Breakout Kumo SWING TRADER (By Insert Cheese)A simple strategy for long spot or long futures (swing traders) based on a basic method of Ichimoku Kinko Hyo strategies.
The strategy is simple:
- Buy when the price breaks the cloud
- Close the trade when the price closes again inside the cloud.
The parameters that work best on this strategy are 10,30,60,30 and 1 for Senkou-Span A
but you can try classic Ichimoku parameters (9,26,52,26,26) or whatever you want like (7,22,44,22,22), (10,30,60,30,30) and others.
-1D chart
I have removed everything from the interface except the cloud to make it visually more aesthetic :D (but if you want to see all the ichimoku indicator you can put in again into the chart)
I have also added several functions for you to do your own backtesting:
- Date range
- TP AND SL method
- Includes long or short trades
The strategy starts with 500 $ and use 100% for trade to make the power of the compounding :P
Remember that this is for only educational porpouse and you must to do your own research and backtested on your usually market..
I hope you like it enjoy and support this indicator :)
Donate (BEP20) 0xC118f1ffB3ac40875C13B3823C182eA2Af344c6d
Scalping The Bull - BTC Chart for Trend AnalysisName: BTC Chart for Trend Analysis
Category: Scalping, Trend Analysis .
Timeframe: 1M, 5M, 30M, 1D depending on the specific technique.
Technical Analysis: The indicator supports the operations of the trader named "Scalping The Bull" who uses BTC as an Index for Crypto trading.
Suggested usage: When trading on altcoins, to check whether or not they are trending with Bitcoin and whether those anticipate its movements.
It is therefore possible to see Bitcoin specifically if it makes red or green candles and how it is positioned with respect to the EMA 5, 10, 60, 223, however configurable from the panel.
Used in conjunction with Scalping The Bull Indicator or PRO Indicator, on the main panel.
Configuration:
EMA Length:
- EMA 1: by default 5, configurable
- EMA 2: by default 10, configurable
- EMA 3: by default 60, configurable
- EMA 4: by default 223, configurable
Colors can be modified from "Settings" > "Style"
Designed to be used with the following the indicator:
lower_tf█ OVERVIEW
This library is a Pine programmer’s tool containing functions to help those who use the request.security_lower_tf() function. Its `ltf()` function helps translate user inputs into a lower timeframe string usable with request.security_lower_tf() . Another function, `ltfStats()`, accumulates statistics on processed chart bars and intrabars.
█ CONCEPTS
Chart bars
Chart bars , as referred to in our publications, are bars that occur at the current chart timeframe, as opposed to those that occur at a timeframe that is higher or lower than that of the chart view.
Intrabars
Intrabars are chart bars at a lower timeframe than the chart's. Each 1H chart bar of a 24x7 market will, for example, usually contain 60 intrabars at the LTF of 1min, provided there was market activity during each minute of the hour. Mining information from intrabars can be useful in that it offers traders visibility on the activity inside a chart bar.
Lower timeframes (LTFs)
A lower timeframe is a timeframe that is smaller than the chart's timeframe. This framework exemplifies how authors can determine which LTF to use by examining the chart's timeframe. The LTF determines how many intrabars are examined for each chart bar; the lower the timeframe, the more intrabars are analyzed.
Intrabar precision
The precision of calculations increases with the number of intrabars analyzed for each chart bar. As there is a 100K limit to the number of intrabars that can be analyzed by a script, a trade-off occurs between the number of intrabars analyzed per chart bar and the chart bars for which calculations are possible.
█ `ltf()`
This function returns a timeframe string usable with request.security_lower_tf() . It calculates the returned timeframe by taking into account a user selection between eight different calculation modes and the chart's timeframe. You send it the user's selection, along with the text corresponding to the eight choices from which the user has chosen, and the function returns a corresponding LTF string.
Because the function processes strings and doesn't require recalculation on each bar, using var to declare the variable to which its result is assigned will execute the function only once on bar zero and speed up your script:
var string ltfString = ltf(ltfModeInput, LTF1, LTF2, LTF3, LTF4, LTF5, LTF6, LTF7, LTF8)
The eight choices users can select from are of two types: the first four allow a selection from the desired amount of chart bars to be covered, the last four are choices of a fixed number of intrabars to be analyzed per chart bar. Our example code shows how to structure your input call and then make the call to `ltf()`. By changing the text associated with the `LTF1` to `LTF8` constants, you can tailor it to your preferences while preserving the functionality of `ltf()` because you will be sending those string constants as the function's arguments so it can determine the user's selection. The association between each `LTFx` constant and its calculation mode is fixed, so the order of the arguments is important when you call `ltf()`.
These are the first four modes and the `LTFx` constants corresponding to each:
Covering most chart bars (least precise) — LTF1
Covers all chart bars. This is accomplished by dividing the current timeframe in seconds by 4 and converting that number back to a string in timeframe.period format using secondsToTfString() . Due to the fact that, on premium subscriptions, the typical historical bar count is between 20-25k bars, dividing the timeframe by 4 ensures the highest level of intrabar precision possible while achieving complete coverage for the entire dataset with the maximum allowed 100K intrabars.
Covering some chart bars (less precise) — LTF2
Covering less chart bars (more precise) — LTF3
These levels offer a stepped LTF in relation to the chart timeframe with slightly more, or slightly less precision. The stepped lower timeframe tiers are calculated from the chart timeframe as follows:
Chart Timeframe Lower Timeframe
Less Precise More Precise
< 1hr 1min 1min
< 1D 15min 1min
< 1W 2hr 30min
> 1W 1D 60min
Covering the least chart bars (most precise) — LTF4
Analyzes the maximum quantity of intrabars possible by using the 1min LTF, which also allows the least amount of chart bars to be covered.
The last four modes allow the user to specify a fixed number of intrabars to analyze per chart bar. Users can choose from 12, 24, 50 or 100 intrabars, respectively corresponding to the `LTF5`, `LTF6`, `LTF7` and `LTF8` constants. The value is a target; the function will do its best to come up with a LTF producing the required number of intrabars. Because of considerations such as the length of a ticker's session, rounding of the LTF to the closest allowable timeframe, or the lowest allowable timeframe of 1min intrabars, it is often impossible for the function to find a LTF producing the exact number of intrabars. Requesting 100 intrabars on a 60min chart, for example, can only produce 60 1min intrabars. Higher chart timeframes, tickers with high liquidity or 24x7 markets will produce optimal results.
█ `ltfStats()`
`ltfStats()` returns statistics that will be useful to programmers using intrabar inspection. By analyzing the arrays returned by request.security_lower_tf() in can determine:
• intrabarsInChartBar : The number of intrabars analyzed for each chart bar.
• chartBarsCovered : The number of chart bars where intrabar information is available.
• avgIntrabars : The average number of intrabars analyzed per chart bar. Events like holidays, market activity, or reduced hours sessions can cause the number of intrabars to vary, bar to bar.
The function must be called on each bar to produce reliable results.
█ DEMONSTRATION CODE
Our example code shows how to provide users with an input from which they can select a LTF calculation mode. If you use this library's functions, feel free to reuse our input setup code, including the tooltip providing users with explanations on how it works for them.
We make a simple call to request.security_lower_tf() to fetch the close values of intrabars, but we do not use those values. We simply send the returned array to `ltfStats()` and then plot in the indicator's pane the number of intrabars examined on each bar and its average. We also display an information box showing the user's selection of the LTF calculation mode, the resulting LTF calculated by `ltf()` and some statistics.
█ NOTES
• As in several of our recent publications, this script uses secondsToTfString() to produce a timeframe string in timeframe.period format from a timeframe expressed in seconds.
• The script utilizes display.data_window and display.status_line to restrict the display of certain plots.
These new built-ins allow coders to fine-tune where a script’s plot values are displayed.
• We implement a new recommended best practice for tables which works faster and reduces memory consumption.
Using this new method, tables are declared only once with var , as usual. Then, on bar zero only, we use table.cell() calls to populate the table.
Finally, table.set_*() functions are used to update attributes of table cells on the last bar of the dataset.
This greatly reduces the resources required to render tables. We encourage all Pine Script™ programmers to do the same.
Look first. Then leap.
█ FUNCTIONS
The library contains the following functions:
ltf(userSelection, choice1, choice2, choice3, choice4, choice5, choice6, choice7, choice8)
Selects a LTF from the chart's TF, depending on the `userSelection` input string.
Parameters:
userSelection : (simple string) User-selected input string which must be one of the `choicex` arguments.
choice1 : (simple string) Input selection corresponding to "Least precise, covering most chart bars".
choice2 : (simple string) Input selection corresponding to "Less precise, covering some chart bars".
choice3 : (simple string) Input selection corresponding to "More precise, covering less chart bars".
choice4 : (simple string) Input selection corresponding to "Most precise, 1min intrabars".
choice5 : (simple string) Input selection corresponding to "~12 intrabars per chart bar".
choice6 : (simple string) Input selection corresponding to "~24 intrabars per chart bar".
choice7 : (simple string) Input selection corresponding to "~50 intrabars per chart bar".
choice8 : (simple string) Input selection corresponding to "~100 intrabars per chart bar".
Returns: (simple string) A timeframe string to be used with `request.security_lower_tf()`.
ltfStats()
Returns statistics about analyzed intrabars and chart bars covered by calls to `request.security_lower_tf()`.
Parameters:
intrabarValues : (float [ ]) The ID of a float array containing values fetched by a call to `request.security_lower_tf()`.
Returns: A 3-element tuple: [ (series int) intrabarsInChartBar, (series int) chartBarsCovered, (series float) avgIntrabars ].
Higher Time Frame EMAs and 1% volatility indicatorSet the "higher time frame" (HTF) from which the EMAs will be calculated in all timeframes.
Example: I chose timeframe 1D and I will see the EMAs from TF 1D also in smaller TF as 1, 5, 30, 60 minutes.
There are 4 EMAs. The default values are 5, 10, 60 and 223 periods from "Scalping the Bull" indicator.
You can change the periods of each EMA.
The indicator have also a volatility indication, showing -1% and +1% price levels.
RSI ModifiedThe RSI is an excellent indicator for determining when equities are overbought/oversold. Though I believe there is a shortcoming in using the 70/30 levels since they are static and do not adjust for when an equity is trending. It stands to reason that in a downtrend, the overbought might be less than 70 and the oversold less than 30—Vice versa for a bull trend. Using the built-in function of pivots, I have attempted to create overbought/oversold lines that adjust with the trend. Leaving the 70/30 lines on the indicator also helps visualize the equity trend. All pivot settings are adjustable in the input menu. The pivot limits serve as a filter for recording pivot points. For example, with an upper pivot limit of 60, only pivots greater than 60 will be recorded into the array used to determine overbought. The crosses represent which values are used to determine overbought/oversold and do not provide timely indications.
