Rule of 16 - LowerThe "Rule of 16" is a simple guideline used by traders and investors to estimate the expected annualized volatility of the S&P 500 Index (SPX) based on the level of the CBOE Volatility Index (VIX). The VIX, often referred to as the "fear gauge" or "fear index," measures the market's expectations for future volatility. It is calculated using the implied volatility of a specific set of S&P 500 options.
The Rule of 16 provides a rough approximation of the expected annualized percentage change in the S&P 500 based on the VIX level. Here's how it works:
Find the VIX level: Look up the current value of the VIX. Let's say it's currently at 20.
Apply the Rule of 16: Divide the VIX level by 16. In this example, 20 divided by 16 equals 1.25.
Result: The result of this calculation represents the expected annualized percentage change in the S&P 500. In this case, 1.25% is the estimated annualized volatility.
So, according to the Rule of 16, a VIX level of 20 suggests an expected annualized volatility of approximately 1.25% in the S&P 500.
Here's how you can use the Rule of 16:
Market Sentiment: The VIX is often used as an indicator of market sentiment. When the VIX is high (above its historical average), it suggests that investors expect higher market volatility, indicating potential uncertainty or fear in the markets. Conversely, when the VIX is low, it suggests lower expected volatility and potentially more confidence in the markets.
Risk Management: Traders and investors can use the Rule of 16 to estimate the potential risk associated with their portfolios. For example, if you have a portfolio of S&P 500 stocks and the VIX is at 20, you can use the Rule of 16 to estimate that the annualized volatility of your portfolio may be around 1.25%. This information can help you make decisions about position sizing and risk management.
Option Pricing: Options traders may use the Rule of 16 to get a quick estimate of the implied annualized volatility priced into S&P 500 options. It can help them assess whether options are relatively expensive or cheap based on the VIX level.
It's important to note that the Rule of 16 is a simplification and provides only a rough estimate of expected volatility. Market conditions and the relationship between the VIX and the S&P 500 can change over time. Therefore, it should be used as a guideline rather than a precise forecasting tool. Traders and investors should consider other factors and use additional analysis to make informed decisions.
Educational
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.
Average True Range (ATR) % KTSLSome traders calculate using percentages when trading. The original ATR indicator calculates using price movements, so it differs for each stock. To avoid this, I changed the ATR indicator to show price movement as a percentage. The red line is the percentage value of the volatility of the original ATR indicator. The white line is 1.6 times the original indicator. The green line is 2.5 times the white line. These values can be adjusted. I wish you good luck.
Position calculator [krazke]This indicator will help you calculate your position. This will automatically calculate potential liquidation price and select leverage for your stop loss and risk size.
How to use it:
1. Select position direction. (long checkmark - selected if it's long)
2. Select entry. If you want to use custom entry price select checkmark and set value. (Current price is default entry)
3. Enter stop loss.
4. Enter risk.
5. Enter max leverage for current ticker.
P.S. Liquidation price is not 100% correct but it almost.
Alxuse Supertrend 4EMA Buy and Sell for tutorialAll abilities of Supertrend, moreover :
Drawing 4 EMA band & the ability to change values, change colors, turn on/off show.
Sends Signal Sell and Buy in multi timeframe.
The ability used in the alert section and create customized alerts.
To receive valid alerts the replay section , the timeframe of the chart must be the same as the timeframe of the indicator.
Supertrend with a simple EMA Filter can improve the performance of the signals during a strong trend.
For detecting the continuation of the downward and upward trend we can use 4 EMA colors.
In the upward trend , the EMA lines are in order of green, blue, red, yellow from bottom to top.
In the downward trend, the EMA lines are in order of yellow, red, blue, green from bottom to top.
How it works:
x1 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA3, MA4)
x2 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA2, MA3)
x3 = MA1 < MA2 and MA2 < MA3 and MA3 < MA4 and ta.crossunder(MA1, MA2)
y1 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA3, MA4)
y2 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA2, MA3)
y3 = MA4 < MA3 and MA3 < MA2 and MA2 < MA1 and ta.crossover(MA1, MA2)
Red triangle = x1 or x2 or x3
Green triangle = y1 or y2 or y3
Long = BUY signal and followed by a Green triangle
Exit Long = SELL signal
Short = SELL signal and followed by a Red triangle
Exit Short = BUY signal
It is also possible to get help from the Stochastic RSI and MACD indicators for confirmation.
For receiving a signal with these two conditions or more conditions, i am making a video tutorial that I will release soon.
Supertrend
Definition
Supertrend is a trend-following indicator based on Average True Range (ATR). The calculation of its single line combines trend detection and volatility. It can be used to detect changes in trend direction and to position stops.
The basics
The Supertrend is a trend-following indicator. It is overlaid on the main chart and their plots indicate the current trend. A Supertrend can be used with varying periods (daily, weekly, intraday etc.) and on varying instruments.
The Supertrend has several inputs that you can adjust to match your trading strategy. Adjusting these settings allows you to make the indicator more or less sensitive to price changes.
For the Supertrend inputs, you can adjust atrLength and multiplier:
the atrLength setting is the lookback length for the ATR calculation;
multiplier is what the ATR is multiplied by to offset the bands from price.
When the price falls below the indicator curve, it turns red and indicates a downtrend. Conversely, when the price rises above the curve, the indicator turns green and indicates an uptrend. After each close above or below Supertrend, a new trend appears.
Summary
The Supertrend helps you make the right trading decisions. However, there are times when it generates false signals. Therefore, it is best to use the right combination of several indicators. Like any other indicator, Supertrend works best when used with other indicators such as MACD, Parabolic SAR, or RSI.
Exponential Moving Average
Definition
The Exponential Moving Average (EMA) is a specific type of moving average that points towards the importance of the most recent data and information from the market. The Exponential Moving Average is just like it’s name says - it’s exponential, weighting the most recent prices more than the less recent prices. The EMA can be compared and contrasted with the simple moving average.
Similar to other moving averages, the EMA is a technical indicator that produces buy and sell signals based on data that shows evidence of divergence and crossovers from general and historical averages. Additionally, the EMA tries to amplify the importance that the most recent data points play in a calculation.
It is common to use more than one EMA length at once, to provide more in-depth and focused data. For example, by choosing 10-day and 200-day moving averages, a trader is able to determine more from the results in a long-term trade, than a trader who is only analyzing one EMA length.
It’s best to use the EMA when for trending markets, as it shows uptrends and downtrends when a market is strong and weak, respectively. An experienced trader will know to look both at the line the EMA projects, as well as the rate of change that comes from each bar as it moves to the next data point. Analyzing these points and data streams correctly will help the trader determine when they should buy, sell, or switch investments from bearish to bullish or vice versa.
Short-term averages, on the other hand, is a different story when analyzing Exponential Moving Average data. It is most common for traders to quote and utilize 12- and 26-day EMAs in the short-term. This is because they are used to create specific indicators. Look into Moving Average Convergence Divergence (MACD) for more information. Similarly, the 50- and 200-day moving averages are most common for analyzing long-term trends.
Moving averages can be very useful for traders using technical analysis for profit. It is important to identify and realize, however, their shortcomings, as all moving averages tend to suffer from recurring lag. It is difficult to modify the moving average to work in your favor at times, often having the preferred time to enter or exit the market pass before the moving average even shows changes in the trend or price movement for that matter.
All of this is true, however, the EMA strives to make this easier for traders. The EMA is unique because it places more emphasis on the most recent data. Therefore, price movement and trend reversals or changes are closely monitored, allowing for the EMA to react quicker than other moving averages.
Limitations
Although using the Exponential Moving Average has a lot of advantages when analyzing market trends, it is also uncertain whether or not the use of most recent data points truly affects technical and market analysis. In addition, the EMA relies on historical data as its basis for operating and because news, events, and other information can change rapidly the indicator can misinterpret this information by weighting the current prices higher than when the event actually occurred.
Summary
The Exponential Moving Average (EMA) is a moving average and technical indicator that reflects and projects the most recent data and information from the market to a trader and relies on a base of historical data. It is one of many different types of moving averages and has an easily calculable formula.
The added features to the indicator are made for training, it is advisable to use it with caution in tradings.
Alxuse Stochastic RSI for tutorial All abilities of Stochastic RSI, moreover :
Drawing upper band and lower band & the ability to change values, change colors, turn on/off show.
Crossing K line and D line in multi timeframe & there are symbols (Circles) with green color (Buy) and red color (Sell) & the ability to change colors, turn on/off show.
Crossing K line and D line in multi timeframe according to the values of upper band and lower band & there are symbols (Triangles) with green color (Long) and red color (Short) & the ability to change colors, turn on/off show.
The ability used in the alert section and create customized alerts.
To receive valid alerts the replay section , the timeframe of the chart must be the same as the timeframe of the indicator.
Stochastic RSI (STOCH RSI)
Definition
The Stochastic RSI indicator (Stoch RSI) is essentially an indicator of an indicator. It is used in technical analysis to provide a stochastic calculation to the RSI indicator. This means that it is a measure of RSI relative to its own high/low range over a user defined period of time. The Stochastic RSI is an oscillator that calculates a value between 0 and 1 which is then plotted as a line. This indicator is primarily used for identifying overbought and oversold conditions.
The basics
It is important to remember that the Stoch RSI is an indicator of an indicator making it two steps away from price. RSI is one step away from price and therefore a stochastic calculation of the RSI is two steps away. This is important because as with any indicator that is multiple steps away from price, Stoch RSI can have brief disconnects from actual price movement. That being said, as a range bound indicator, the Stoch RSI's primary function is identifying crossovers as well as overbought and oversold conditions.
The basics
It is important to remember that the Stoch RSI is an indicator of an indicator making it two steps away from price. RSI is one step away from price and therefore a stochastic calculation of the RSI is two steps away. This is important because as with any indicator that is multiple steps away from price, Stoch RSI can have brief disconnects from actual price movement. That being said, as a range bound indicator, the Stoch RSI's primary function is identifying crossovers as well as overbought and oversold conditions.
Overbought/Oversold
Overbought and Oversold conditions are traditionally different than the RSI. While RSI overbought and oversold conditions are traditionally set at 70 for overbought and 30 for oversold, Stoch RSI are typically .80 and .20 respectively. When using the Stoch RSI, overbought and oversold work best when trading along with the underlying trend.
During an uptrend, look for oversold conditions for points of entry.
During a downtrend, look for overbought conditions for points of entry.
Summary
When using Stoch RSI in technical analysis, a trader should be careful. By adding the Stochastic calculation to RSI, speed is greatly increased. This can generate many more signals and therefore more bad signals as well as the good ones. Stoch RSI needs to be combined with additional tools or indicators in order to be at its most effective. Using trend lines or basic chart pattern analysis can help to identify major, underlying trends and increase the Stoch RSI's accuracy. Using Stoch RSI to make trades that go against the underlying trend is a dangerous proposition.
The added features to the indicator are made for training, it is advisable to use it with caution in tradings.
Alxuse MACD for tutorialAll abilities of MACD, moreover :
Drawing upper band and lower band & the ability to change values, change colors, turn on/off show.
Crossing MACD line and SIGNAL line in multi timeframe & there are symbols (Circles) with green color (Buy) and red color (Sell) & the ability to change colors, turn on/off show.
Crossing MACD line and SIGNAL line in multi timeframe according to the values of upper band and lower band & there are symbols (Triangles) with green color (Long) and red color (Short) & the ability to change colors, turn on/off show.
The ability used in the alert section and create customized alerts.
To receive valid alerts the replay section , the timeframe of the chart must be the same as the timeframe of the indicator.
MACD (Moving Average Convergence/Divergence)
Definition
MACD is an extremely popular indicator used in technical analysis. MACD can be used to identify aspects of a security's overall trend. Most notably these aspects are momentum, as well as trend direction and duration. What makes MACD so informative is that it is actually the combination of two different types of indicators. First, MACD employs two Moving Averages of varying lengths (which are lagging indicators) to identify trend direction and duration. Then, MACD takes the difference in values between those two Moving Averages (MACD Line) and an EMA of those Moving Averages (Signal Line) and plots that difference between the two lines as a histogram which oscillates above and below a center Zero Line. The histogram is used as a good indication of a security's momentum.
MACD Line is a result of taking a longer term EMA and subtracting it from a shorter term EMA.The most commonly used values are 26 days for the longer term EMA and 12 days for the shorter term EMA, but it is the trader's choice.
The Signal Line.
The Signal Line is an EMA of the MACD Line described in Component 1. The trader can choose what period length EMA to use for the Signal Line however 9 is the most common.
The MACD Histogram.
As time advances, the difference between the MACD Line and Signal Line will continually differ. The MACD histogram takes that difference and plots it into an easily readable histogram. The difference between the two lines oscillates around a Zero Line.
A general interpretation of MACD is that when MACD is positive and the histogram value is increasing, then upside momentum is increasing. When MACD is negative and the histogram value is decreasing, then downside momentum is increasing.
What to look for
The MACD indicator is typically good for identifying three types of basic signals; Signal Line Crossovers, Zero Line Crossovers, and Divergence.
SIGNAL LINE CROSSOVERS
A Signal Line Crossover is the most common signal produced by the MACD. First one must consider that the Signal Line is essentially an indicator of an indicator. The Signal Line is calculating the Moving Average of the MACD Line. Therefore the Signal Line lags behind the MACD line. That being said, on the occasions where the MACD Line crosses above or below the Signal Line, that can signify a potentially strong move.
The strength of the move is what determines the duration of Signal Line Crossover. Understanding and being able to analyze move strength, as well as being able to recognize false signals, is a skill that comes with experience.
The first type of Signal Line Crossover to examine is the Bullish Signal Line Crossover. Bullish Signal Line Crossovers occur when the MACD Line crosses above the Signal Line.
The second type of Signal Line Crossover to examine is the Bearish Signal Line Crossover. Bearish Signal Line Crossovers occur when the MACD Line crosses below the Signal Line.
Zero line crossovers
Zero Line Crossovers have a very similar premise to Signal Line Crossovers. Instead of crossing the Signal Line, Zero Line Crossovers occur when the MACD Line crossed the Zero Line and either becomes positive (above 0) or negative (below 0).
The first type of Zero Line Crossover to examine is the Bullish Zero Line Crossover. Bullish Zero Line Crossovers occur when the MACD Line crosses above the Zero Line and go from negative to positive.
The second type of Zero Line Crossover to examine is the Bearish Zero Line Crossover. Bearish Zero Line Crossovers occur when the MACD Line crosses below the Zero Line and go from positive to negative.
Divergence
Divergence is another signal created by the MACD. Simply put, divergence is when the MACD and actual price are not in agreement.
For example, Bullish Divergence occurs when price records a lower low, but the MACD records a higher low. The movement of price can provide evidence of the current trend, however changes in momentum as evidenced by the MACD can sometimes precede a significant reversal.
Bearish Divergence is, of course, the opposite. Bearish Divergence occurs when price records a higher high while the MACD records a lower high.
Summary
What makes the MACD such a valuable tool for technical analysis is that it is almost like two indicators in one. It can help to identify not just trends, but it can measure momentum as well. It takes two separate lagging indicators and adds the aspect of momentum which is much more active or predictive That kind of versatility is why it has been and is used by trader's and analysts across the entire spectrum of finance.
Despite MACD's obvious attributes, just like with any indicator, the trader or analyst needs to exercise caution. There are just some things that MACD doesn't do well which may tempt a trader regardless. Most notably, traders may be tempted into using MACD as a way to find overbought or oversold conditions. This is not a good idea. Remember, MACD is not bound to a range, so what is considered to be highly positive or negative for one instrument may not translate well to a different instrument.
With sufficient time and experience, almost anybody who wants to analyze chart data should be able to make good use out of the MACD.
The added features to the indicator are made for training, it is advisable to use it with caution in tradings.
MTF - Zigzag + Tech IndicatorsMTF - Zigzag + Tech Indicators
At high level the indicator can be a useful tool while analyzing the charts. It marks swing points (Zigzag) on 3 different timeframes along with capability to view key technical indicator values at each of the swing point.
Normally Zaizag indicators are useful for identifying primary trend and retracements. Zigzags also help in identifying key support and resistance areas. Traders develop various trading strategies based on Zigzags.
Most of the published Zigzag indicators use single timeframe / chart timeframe to draw the Zigzag lines but, many traders/chart analysts would like to analyze trends on multiple timeframes. Single timeframe Zigzags makes such analysis little difficult.
This indicator is an advanced version of Zigzag which allow users to draw Zigzag lines on multiple timeframes. It allows users to input 2 additional higher timeframes and in total it draws Zigzag on 3 timeframes i.e., on chart timeframe and 2 additional higher timeframes.
Once loaded on the chart, it draws Zigzag lines and plot labels (HH, LL, HL, LH) which denotes swing points. Each of the swing point label has a tooltip attached to it, which provide few additional data point, to view the additional data points, hover the mouse over the label.
Swing label tooltip shows these additional data points:
Tag: Swing type (HH, LL, HL, LH) + Bar time (in dd-mm-yyyy hh:mm format)
Price point: Swing price point
Price change: Price change since previous swing point along with change %
Swing volume: Volume since previous swing point in million
Key technical indicator values:
RSI (close, 14)
Stochastic (close, high, low, 14)
ADX (14, 14)
SMA20
SMA50
SMA100
SMA200
Use cases:
Support resistance: Though most of the swing points of a zigzag are treated as a support or resistance. This indicator allows to add more depth to the analysis. E.g., swing points based on lowest timeframe (chart timeframe) can be treated as weak support/resistance whereas swing points based on higher timeframe can treated as strong support/resistance and prices need to hit it multiple time to cross/break the same.
Trend identification: Trend on lowest timeframe (chart timeframe) can be a immediate term trend, trend on the mid-level higher timeframe can be a short term trend and trend on the highest level timeframe can be a long term trend.
Trade identification, entry, and exit: MTF Zigzag can also be creatively used while trading. Eg. One can identify a trend on highest level timeframe and use mid-level timeframe for trade entry and lowest level timeframe can be used for Take Profit levels (TP1, TP2, ..) and Stop loss. Alternatively, Trend can be identified on highest or mid-level timeframe and trade entry/exit can be based on lowest level timeframe.
Use of information displayed in tooltip: Analysts/traders look for confirmations from other indicators while initiating trades. These additional indicator values become handy/readily available source of information without specifically navigating through different indicators/charts. These indicator values can be creatively used in many ways. Some of the examples are:
Easy comparison of values of moving averages on all 3 timeframes
Better assessment of momentum and overbought/oversold based on value of stochastic and rsi
Use of ADX to determine the strength of the trend
Trade decision based on increasing or decreasing order of moving averages
Trade decision, based order of moving averages combined with overbought/oversold and strength of the trend
Chart examples: TCS on 60m/4h/1D
ITC 4h/1D
Input Parameters:
1. Chart timeframe zigzag setup: to plot zigzag based on chart timeframe
2. Higher timeframe zigzag setup: to plot zigzag based on higher timeframe
3. Higher timeframe zigzag setup 1: to plot zigzag based on another higher timeframe
Each of these have user selectable options:
1. Color/width of the zigzag line
2. plot zigzag line - select/unselect
3. plot HHLL labels - select/unselect
Both (2 and 3) Higher timeframe setups allow to select higher timeframe and offset. Offset can be 0 or 1. This setting normally used to avoid repainting. Select offset as 1 to avoid repainting.
For Pine script developers:
Script elements:
1. Input parameters
2. Type definition (UDT) for ohlc and ph, pl data elements
3. Map definition for visual properties
4. Type instances for chart_tf, higher_tf1, higher_tf2
5. Important variable – for indicator values
6. Methods –
a. get_ph_pl() – get ph, pl data for each of the tf along with indicator values
b. add_ph(), add_pl() – add ph, pl data to timeframe specific udt, plot the zigzag and labels, add tooltip to label
Script structure
1. Input parameters
2. Variable and type definitions
3. Methods and functions
4. For each of timeframe, call functions and methods
a. Check ph, pl (if swing point formed)
b. Plot ph, pl (if applicable) i.e. zigzag line, labels
KSMT Toolbox - MidTFThis tool allows you to quickly identify the macro and micro trend's direction and enter and exit position at a more favorable price.
When the pink lines are angled up you should look for a long position and enter only when the candles are colored green.
And when the pink lines are angled down you should look for a short position and enter only when the candles are colored red.
This tool is only meant to be a practice tool and should be used to train your eye on candle movements to gain a sense of when you should enter/exit.
Practice is what differentiates a good trader and a bad one.
#KSMT #KSMT_Armenia
Volume EntropyKey Components :
📍 Natural Logarithm Function : The script starts by employing a custom Taylor Series approximation for natural logarithms. This function serves to calculate entropy with higher accuracy than conventional methods, laying the foundation for further calculations.
📍 Entropy Calculation : The core of this indicator is its entropy function. It employs the custom natural log function to compute the randomness of the trading volume over a user-defined micro-pattern length, offering insights into market stability or volatility.
📍 Micro-Pattern Length : This is the parameter that sets the stage for the level of detail in the entropy calculation. Users can adjust it to suit different time frames or market conditions, thus customizing the indicator's sensitivity to randomness in trading volume.
Session CandlesThis indicator is designed to visually represent different trading sessions on a price chart, highlighting candlestick colors to distinguish between bullish (upward movement) and bearish (downward movement) trends during various market sessions. Here's an overview of how the indicator works:
1. Session Definition: The indicator defines four distinct trading sessions:
- London Session: Typically covering the European trading hours.
- New York AM Session: Representing the morning hours of the New York trading session.
- New York PM Session: Representing the afternoon hours of the New York trading session.
- Asia Session: Encompassing the trading hours of the Asian markets.
2. Configuration Options: Users can customize the behavior of the indicator through input options. For each session, users can enable or disable the display of session-specific candles.
3. Candle Coloring: The indicator determines the color of candles based on the following criteria:
- For each session, it checks whether the current candle's closing price is higher than its opening price.
- If the closing price is higher, the candle is considered bullish, and a user-defined green color is used for the candle.
- If the closing price is lower, the candle is considered bearish, and a user-defined red color is applied.
4. Display: The indicator then applies the calculated candle colors to the respective candles of each trading session on the price chart. This visual distinction helps traders quickly identify the prevailing trend during different market sessions.
To use the indicator, traders can overlay it on their price charts in TradingView. By enabling or disabling specific trading sessions, they can focus on the trends and price movements during those specific time periods.
Please note that the actual appearance of the indicator on the chart depends on the user's chosen settings for session enablement and color preferences.
Nitin Swing TradingThis is a CPR which indicates pivot points based on monthly price action.
The Orange line acts as a resistance area, blue lines act as pivot point/CPR and green one is support.
One can study retrospective chart to analyse how market has respected these Support and Resistance levels.
A guide on how to trade using this indicator?
1. If you see the resistance is broken after multiple attempt - We can Go Long
2.If you see price going down below CPR, We can Go Short
3.If you see price taking support at support level - We can Go Long.
Risk reward should always be 1:1 then gradually increase it to 1:2 & 1:3
It is advised to consult with your financial advisor before taking any trade just based on any indicator. You have to manage risk before entering any trade.
Inside Candle alert V1 By HARSH DEO SINGHA breakout long signal is generated when the current high crosses above the previous mother bar's high, and it's an inside bar.
A breakdown short signal is generated when the current low crosses below the previous mother bar's low, and it's an inside bar.
The script plots triangle shapes below breakout long signals and above breakdown short signals.
Alert conditions are added for inside bars, breakout long, and breakdown short.
Please note that this is a basic example, and you can further refine and optimize your strategy based on your specific trading rules and preferences. Always remember to backtest and paper trade any strategy before using it with real money.
Paytience DistributionPaytience Distribution Indicator User Guide
Overview:
The Paytience Distribution indicator is designed to visualize the distribution of any chosen data source. By default, it visualizes the distribution of a built-in Relative Strength Index (RSI). This guide provides details on its functionality and settings.
Distribution Explanation:
A distribution in statistics and data analysis represents the way values or a set of data are spread out or distributed over a range. The distribution can show where values are concentrated, values are absent or infrequent, or any other patterns. Visualizing distributions helps users understand underlying patterns and tendencies in the data.
Settings and Parameters:
Main Settings:
Window Size
- Description: This dictates the amount of data used to calculate the distribution.
- Options: A whole number (integer).
- Tooltip: A window size of 0 means it uses all the available data.
Scale
- Description: Adjusts the height of the distribution visualization.
- Options: Any integer between 20 and 499.
Round Source
- Description: Rounds the chosen data source to a specified number of decimal places.
- Options: Any whole number (integer).
Minimum Value
- Description: Specifies the minimum value you wish to account for in the distribution.
- Options: Any integer from 0 to 100.
- Tooltip: 0 being the lowest and 100 being the highest.
Smoothing
- Description: Applies a smoothing function to the distribution visualization to simplify its appearance.
- Options: Any integer between 1 and 20.
Include 0
- Description: Dictates whether zero should be included in the distribution visualization.
- Options: True (include) or False (exclude).
Standard Deviation
- Description: Enables the visualization of standard deviation, which measures the amount of variation or dispersion in the chosen data set.
- Tooltip: This is best suited for a source that has a vaguely Gaussian (bell-curved) distribution.
- Options: True (enable) or False (disable).
Color Options
- High Color and Low Color: Specifies colors for high and low data points.
- Standard Deviation Color: Designates a color for the standard deviation lines.
Example Settings:
Example Usage RSI
- Description: Enables the use of RSI as the data source.
- Options: True (enable) or False (disable).
RSI Length
- Description: Determines the period over which the RSI is calculated.
- Options: Any integer greater than 1.
Using an External Source:
To visualize the distribution of an external source:
Select the "Move to" option in the dropdown menu for the Paytience Distribution indicator on your chart.
Set it to the existing panel where your external data source is placed.
Navigate to "Pin to Scale" and pin the indicator to the same scale as your external source.
Indicator Logic and Functions:
Sinc Function: Used in signal processing, the sinc function ensures the elimination of aliasing effects.
Sinc Filter: A filtering mechanism which uses sinc function to provide estimates on the data.
Weighted Mean & Standard Deviation: These are statistical measures used to capture the central tendency and variability in the data, respectively.
Output and Visualization:
The indicator visualizes the distribution as a series of colored boxes, with the intensity of the color indicating the frequency of the data points in that range. Additionally, lines representing the standard deviation from the mean can be displayed if the "Standard Deviation" setting is enabled.
The example RSI, if enabled, is plotted along with its common threshold lines at 70 (upper) and 30 (lower).
Understanding the Paytience Distribution Indicator
1. What is a Distribution?
A distribution represents the spread of data points across different values, showing how frequently each value occurs. For instance, if you're looking at a stock's closing prices over a month, you may find that the stock closed most frequently around $100, occasionally around $105, and rarely around $110. Graphically visualizing this distribution can help you see the central tendencies, variability, and shape of your data distribution. This visualization can be essential in determining key trading points, understanding volatility, and getting an overview of the market sentiment.
2. The Rounding Mechanism
Every asset and dataset is unique. Some assets, especially cryptocurrencies or forex pairs, might have values that go up to many decimal places. Rounding these values is essential to generate a more readable and manageable distribution.
Why is Rounding Needed? If every unique value from a high-precision dataset was treated distinctly, the resulting distribution would be sparse and less informative. By rounding off, the values are grouped, making the distribution more consolidated and understandable.
Adjusting Rounding: The `Round Source` input allows users to determine the number of decimal places they'd like to consider. If you're working with an asset with many decimal places, adjust this setting to get a meaningful distribution. If the rounding is set too low for high precision assets, the distribution could lose its utility.
3. Standard Deviation and Oscillators
Standard deviation is a measure of the amount of variation or dispersion of a set of values. In the context of this indicator:
Use with Oscillators: When using oscillators like RSI, the standard deviation can provide insights into the oscillator's range. This means you can determine how much the oscillator typically deviates from its average value.
Setting Bounds: By understanding this deviation, traders can better set reasonable upper and lower bounds, identifying overbought or oversold conditions in relation to the oscillator's historical behavior.
4. Resampling
Resampling is the process of adjusting the time frame or value buckets of your data. In the context of this indicator, resampling ensures that the distribution is manageable and visually informative.
Resample Size vs. Window Size: The `Resample Resolution` dictates the number of bins or buckets the distribution will be divided into. On the other hand, the `Window Size` determines how much of the recent data will be considered. It's crucial to ensure that the resample size is smaller than the window size, or else the distribution will not accurately reflect the data's behavior.
Why Use Resampling? Especially for price-based sources, setting the window size around 500 (instead of 0) ensures that the distribution doesn't become too overloaded with data. When set to 0, the window size uses all available data, which may not always provide an actionable insight.
5. Uneven Sample Bins and Gaps
You might notice that the width of sample bins in the distribution is not uniform, and there can be gaps.
Reason for Uneven Widths: This happens because the indicator uses a 'resampled' distribution. The width represents the range of values in each bin, which might not be constant across bins. Some value ranges might have more data points, while others might have fewer.
Gaps in Distribution: Sometimes, there might be no data points in certain value ranges, leading to gaps in the distribution. These gaps are not flaws but indicate ranges where no values were observed.
In conclusion, the Paytience Distribution indicator offers a robust mechanism to visualize the distribution of data from various sources. By understanding its intricacies, users can make better-informed trading decisions based on the distribution and behavior of their chosen data source.
Time Session Filter - MACD exampleTime Session Filter in TradingView Strategy: A Comprehensive Guide
Welcome to this educational TradingView blog where we dive deep into the functionality and utility of the time session filter in trading strategies. It's interesting to note that the time session filter is a commonly overlooked feature in Pine Script, often not integrated into overall trading strategies. Yet, when used wisely, this tool can significantly enhance your trading approach. In essence, the session filter ensures that trades are only made within a specific, user-defined time frame. By incorporating this often-neglected building block, you can make your strategy more adaptable to various market conditions and trading preferences.
What is a Time Session Filter?
A time session filter is designed to:
Select Times of the Day to Trade: The filter allows you to choose specific hours during the day in which trades are allowed to be excecuted.
Toggle Days to Trade: You can decide which days of the week you want to trade, giving you the flexibility to avoid days that are historically not profitable for your strategy.
Close Trade When Session Ends: The filter can automatically close any open trade once the specified time session concludes, reducing the risk associated with holding positions outside your chosen time frame.
The user interface is streamlined, taking minimal space for the input sections, making it convenient to integrate with other indicators in your overall strategy script. In addition the script colors the background of the chart green when the timesession filter is on and makes the background red when the filter doesn't allow any trades. This helps you to visualise the selected timeframes in relation to chart patterns.
Best Practices for Time Selection
From my personal trading experience I share some input settings you can try to play around with:
Stocks: Trading stocks sometimes yield better results if you only trade in the mornings until lunchtime. This is the period when markets are generally more active, and traders are keenly participating.
Cryptocurrencies: For cryptocurrencies, it sometimes makes sense to avoid trading on Fridays, a day when futures contracts often expire. Various other market-moving events also typically occur on Fridays.
Random Selection: Interestingly, sometimes choosing a random selection of times and days can improve the script's performance, adding an element of unpredictability that might outperform more systematic approaches.
Strategy Overview
This strategy script incorporates various elements, including risk position size and MACD indicator, to provide a comprehensive trading strategy. For a detailed explanation of risk position sizing, please refer to this article:
For a complete understanding of the MACD indicator utilized, visit the following explanation:
Additionally, for high time frame trend filters, consult this resource for more info:
Educational Purposes and Risks
Please note that this script is for educational purposes and serves merely as an example of how to incorporate a time session filter into a trading strategy for pinescript. It is a simplified strategy without a fixed stop-loss, which can result in higher exposure to significant losses. The time session filter can be a powerful addition to your trading strategy, providing you with the tools to tailor your approach according to time-specific market conditions. By understanding its functionalities and best practices, you can make more informed trading decisions, but always remember that trading carries inherent risks.
Happy trading!
Equity Trade Risk ManagerEquity Trade Risk Manager is a simple indicator that helps you protect your portfolio by going into each trade risk first !
Equity Trade Risk Manager does this by calculating your ideal position size or ideal stop loss based on your account size, purchase price and risk tolerance. This ensures you are never risking more than your predetermined amount on each trade.
Unlike most position size calculators, that will only tell traders how many shares to purchase, Equity Trade Risk Manger allows the trader to choose whether they want to calculate the ideal number of shares to purchase or where to set the trades stop loss based on the number of shares owned. Not only that, but knowing traders need to act fast, the indicator also gives the option to quickly use the current price and low of the day as an entry and stop. Lastly, your stop loss will be plotted onto the chart for a visual aid.
Features:
Dynamic Risk Settings:
Account Customization: Input your account size to get metrics tailored to you.
Calculation Choices: Decide if you want the tool to calculate the number of shares you should buy or where to set your stop-loss.
Custom Risk Parameters: Use preset risk percentages or set your own to match your comfort level.
Price Point Flexibility:
Enter your entry and stop price or opt to use the current price and the low of the day.
Interactive Display Settings:
Customizable Interface: Adjust table positions, text size, and color schemes to match your trading dashboard aesthetic.
On-Chart Stop-Loss Indication: Visualize your stop loss on the chart itself.
Get a snapshot of your dollar risk, position size, shares to buy, and stop-loss.
Amols Magic LevelsThis Script showing Levels determined by previous day data. and its open for educational purpose.
IV Squeeze - Sunil Bhave This script calculates both Bollinger Bands and Keltner Channels on a 5-minute chart. It identifies IV squeeze conditions when the lower Bollinger Band is above the lower Keltner Channel and the upper Bollinger Band is below the upper Keltner Channel. When a squeeze is detected, it plots a red triangle below the chart bars and alerts you with a message.
Please note that this script is for educational purposes only.
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Label_Trades Enter your trade information to display on chartThis indicator is an overlay for your main chart. It will display your trade entry and trade close positions on your chart.
After you place the indicator on you shart you will need to enter the trade information that you want to display.
You can open thte input setting by clicking on the gear sprocket that appears when you hover your mouse over the indicator name. There are 7 seting you will want to fill in.
Date and Time Bought
Date and Time Sold
Trade Lot Size
Select whether the trades was 'long' or 'short'
The price for buying the Trade
The price for selling the Trade
On the third tab
The code is straightforward. Using a conditional based on whtehr the trade was 'long' or 'short' determines where the labels will be placed and whether they show a long trade or short trade. It also displays a tool tip when you hover over the label. The tooltip will display the number of lots bought or sold and the price.
The lable.new() function is the meat of the indicator. I will go over a line to explainthe options available.
Pinscript manual(www.tradingview.com)
The function parameters can be called out as in the example above or the values can be placed comma seperated. If you do the latter you must enter the parameters in order. I like anming the parameters as I place them so I can easily see what I did.
label.new(
x=t_bot, // x is the time the transaction occured
y=na, // y is the for the y-axis it is not used here so 'na' tells pinescript to ignore the parameter
xloc=xloc.bar_time, // x_loc is specifying that x is a time value
yloc=yloc.belowbar, // y-loc specifies to place the label under the bar. There are other locations to use. See language reference ((www.tradingview.com)
style=label.style_triangleup, // This parameter selects the lable style. There are many other style to use, see the manual.
color=color.green, // the Label fill color
size=size.small, // the label size
tooltip=str.tostring(lot_size) + " lots bought at $" + str.tostring(bot_val)) // Some parameters are tricky. This one needs to be a string but we are using an integer value(lot_size) and a float value(bol_val). They are all concatenated via the "+" sign. In oorder to do this the numeric values need to be cast or converted into strings. The string function str.tostring() does this.
Cynical Cold IndexThis TradingView indicator calculates the Cynical Cold Index, which is a weighted basket of commodity prices designed to track economic conditions. It compares the price of a given asset to the index value.
Weights the commodities as percentages:
Gold: 10%
Oil: 15%
Coffee: 5%
Natural Gas: 10%
Silver: 15%
Sugar: 5%
Corn: 5%
Wheat: 5%
Cotton: 10%
Copper: 10%
Iron Ore: 5%
Live Cattle: 5%
Urea: 5%
How To Input CSV List Of Symbol Data Used For ScreenerExample of how to input multiple symbols at once using a CSV list of ticker IDs. The input list is extracted into individual ticker IDs which are then each used within an example screener function that calculates their rate of change. The results for each of the rate of changes are then plotted.
For code brevity this example only demonstrates using up to 4 symbols, but the logic is annotated to show how it can easily be expanded for use with up to 40 ticker IDs.
The CSV list used for input may contain spaces or no spaces after each comma separator, but whichever format (space or no space) is used must be used consistently throughout the list. If the list contains any invalid symbols the script will display a red exclamation mark that when clicked will display those invalid symbols.
If more than 4 ticker IDs are input then only the first 4 are used. If less than 4 ticker IDs are used then the unused screener calls will return `float(na)`. In the published chart the input list is using only 3 ticker IDs so there are only 3 plots shown instead of 4.
NOTICE: This is an example script and not meant to be used as an actual strategy. By using this script or any portion thereof, you acknowledge that you have read and understood that this is for research purposes only and I am not responsible for any financial losses you may incur by using this script!
