Effort Versus ResultsThis indicator, named "Effort Versus Results" (CCB), is designed to visually highlight price bars on a TradingView chart based on user-defined criteria. The purpose of this indicator is to identify potential trading opportunities or signal areas of interest for further analysis.
Once the inputs are specified, the indicator calculates the ratio of the first ATR to the average volume and compares it to the product of the multiplier and the ratio of the second ATR to the average volume. If the calculated condition is met, indicating that the first ATR relative to volume is greater than the second ATR relative to volume multiplied by the specified multiplier, the indicator colors the corresponding price bars red.
By customizing the parameters, traders can adapt the indicator to suit their trading strategies, risk tolerance, and market conditions. The highlighted bars may signify potential areas of increased volatility or trading activity, prompting traders to further investigate potential trading opportunities. However, as with any technical indicator, it is essential to use this tool in conjunction with other analysis techniques and risk management strategies for informed decision-making.
The indicator utilizes three main inputs that users can customize:
1. **ATR Length 1 (`atr_length_1`)**: This parameter allows users to specify the length of the first Average True Range (ATR) period. ATR is a measure of market volatility and represents the average range of price movement over a specified period.
2. **ATR Length 2 (`atr_length_2`)**: Users can set the length of the second ATR period, allowing for comparison between two different ATR values.
3. **Volume Length (`volume_length`)**: This input enables users to define the length of the volume period. Volume is a measure of the number of shares or contracts traded during a given period and is often used to confirm price movements.
4. **Multiplier (`multiplier`)**: Users can specify a multiplier value to adjust the threshold for comparison between the two ATR values divided by volume. This parameter allows for flexibility in setting the sensitivity of the indicator.
Cerca negli script per "Volatility"
Volatility Adjusted EMA - by CrunchsterApplies recent volatility adjustment to the exponential moving average, where the smoothing factor is 2/(N + 1) - N being the lookback period or span
Volatility of recent 30 days returns is calculated using standard deviation with a thirty day lookback.
Increased smoothing compared to a standard EMA, which also adjusts to market conditions, as first described by Chande in 1991.
Exponentially Weighted Moving Average Oscillator [BackQuant]Exponentially Weighted Moving Average (EWMA)
The Exponentially Weighted Moving Average (EWMA) is a quantitative or statistical measure used to model or describe a time series. The EWMA is widely used in finance, the main applications being technical analysis and volatility modeling.
The moving average is designed as such that older observations are given lower weights. The weights fall exponentially as the data point gets older – hence the name exponentially weighted.
Applications of the EWMA
The EWMA is widely used in technical analysis. It may not be used directly, but it is used in conjunction with other indicators to generate trading signals. A well-known example is the Negative Volume Index (NVI), which is used in conjunction with its EWMA.
Why is it different from the In-Built TradingView EWMA
Adaptive Algorithms: If your strategy requires the alpha parameter to change adaptively based on certain conditions (for example, based on market volatility), a for loop can be used to adjust the weights dynamically within the loop as opposed to the fixed decay rate in the standard EWMA.
Customization: A for loop allows for more complex and nuanced calculations that may not be directly supported by built-in functions. For example, you might want to adjust the weights in a non-standard way that the typical EWMA calculation doesn't allow for.
Use of the Oscillator
This mainly comes from 3 main premises, this is something I like to do personally since it is easier to work with them in the context of my system. E.g. Using them to spot clear trends without noise on longer timeframes.
Clarity: Plotting the EWMA as an oscillator provides a clear visual representation of the momentum or trend strength. It allows traders to see overbought or oversold conditions relative to a normalized range.
Comparison: An oscillator can make it easier to compare different securities or timeframes on a similar scale, especially when normalized. This is because the oscillator values are typically bounded within a range (like -1 to 1 or 0 to 100), whereas the actual price series can vary significantly.
Focus on Change: When plotted as an oscillator, the focus is on the rate of change or the relative movement of the EWMA, not on the absolute price levels. This can help traders spot divergences or convergences that may not be as apparent when the EWMA is plotted directly on the price chart. This is also one reason there is a conditional plotting on the chart.
Trend Strength: When normalized, the distance of the oscillator from its midpoint can be interpreted as the strength of the trend, providing a quantitative measure that can be used to make systematic trading decisions.
Here are the backtests on the 1D Timeframe for
BITSTAMP:BTCUSD
BITSTAMP:ETHUSD
COINBASE:SOLUSD
When using this script the user is able to define a source and period, which by extension calculates the alpha. An option to colour the bars accord to trend.
This makes it super easy to use in a system.
I recommend using this as above the midline (0) for a positive trend and below the midline for negative trend.
Hence why I put a label on the last bar to ensure it is easier for traders to read.
Lastly, The decreasing colour relative to RoC, this also helps traders to understand the strength of the indicator and gain insight into when to potentially reduce position size.
This indicator is best used in the medium timeframe.
Sessions Lite [TradingFinder] New York, London, Asia, NYSE Forex🔵 Introduction
A trading session is one of the basic concepts in the financial market that refers to specific time periods. In fact, a session means hours during the day and night, during which traders in a certain part of the world conduct their transactions.
Although the "Forex" and "CFDs" market is open 24 hours a day and it is possible to trade in it, but in some hours the activity in this market decreases so much that many traders prefer not to trade and only watch the market. On the other hand, there are specific times when the market is very busy and dynamic, and many traders tend to trade during these hours of the day and night.
Trading sessions are usually divided into three main categories, which are "Asian", "European" and "North American" sessions. These trading sessions are also called the "Tokyo", "London" and "New York" sessions, respectively. But they also categorized these sessions in more detailed ways such as "Sydney session", "Shanghai session" or "NYSE session".
🔵 Tokyo trading session (Asian session)
After the weekend that happens on Saturday and Sunday, the Forex market starts with the Asian session. In this continent, most of the transactions are done in the Tokyo session, and for this reason, it is usually called the Asian session or the Tokyo session. However, other countries such as Australia, China and Singapore also do a lot of trading in this session.
The Tokyo session has a lower volume of transactions compared to the London and New York sessions, and therefore the liquidity is lower. In this session, most of the Forex currency pairs move in a price range. For this reason, different people use the ups and downs with the trading strategy in the range and get profit.
The low liquidity of the Tokyo session means that trading spreads are also higher during these hours. Besides, most of the transactions of this session are done in the early hours and at the same time as the planned news release.
In the Tokyo or Asia session, the best currency pairs to trade are the "Japanese yen", the "Australian dollar", and the "New Zealand dollar".
"Nikkei" index is also a good option for trading. If you trade in the Tokyo session, you should also be aware of the release of economic news and data from Australian, New Zealand and Japanese financial institutions.
🔵 London trading session (European session)
After the Asian session, it is time for the European session. In this period of time, transactions are very large and many European markets are involved. However, the European session is usually known as the London session.
Because of its specific time zone, London is not only known as the Forex trading center in Europe, but it is also known as the Forex trading center in the world. The London session overlaps with two other major trading sessions in the world, Asia and America. This means that most of the Forex transactions are done in this session. According to the latest statistics, 32% of Forex transactions are related to the London session, which shows that about a third of the activity performed in Forex takes place during this period.
This will increase the volume of Forex transactions and increase liquidity. An event that causes the spread of transactions to decrease. Of course, high liquidity also leads to greater volatility, which is desirable for many traders.
In the European session, the pound and euro currencies and the "DAX", "FTSE100", and "CAC40" indices are known as the best tradable assets. Also, traders of this session should pay attention to the news and data published by the "European Central Bank" and the "Bank of England". The news of countries like Germany, France and Italy are also very important.
🔵 American trading session (New York session)
When the New York session begins, several hours have passed since the end of the Tokyo session, but the European session is in the middle. In this session, they usually affect the financial activities carried out in America, but they also affect other countries such as Canada, Mexico and several South American countries.
The "US dollar" and stock indices such as "S&P", "Dow Jones" and "Nasdaq" are the most important assets that are traded in this session.
The early hours of the American session have a lot of liquidity and volatility due to the overlap with the European session, but with the end of the European session, the activity in the American session also decreases.
You can trade all major Forex currency pairs in the New York trading session. In this session, the "Federal Reserve", as the most important central bank in the world, is the institution that you should pay attention to its news and data.
The trading session indicator is an analytical tool in the financial markets that is used to display and analyze specific trading periods during a day. These indicators are generally useful for determining support and resistance levels during any trading session and for detecting different trading patterns.
For example, usually these indicators display the open and close price levels, the highest and lowest prices during a trading session. Also, you may notice various price patterns such as price channels, price phase phases and market trend changes during different trading sessions using these indicators.
🔵 cause of construction
In particular, the session light indicator version is designed and built for those traders who use many different tools on their chart at the same time. These traders can include "Volume Traders", "ICT traders", "Day Traders" and... These individuals can use "Session Lite" without disturbing the display of their other trading tools such as "Order Blocks", "Liquidity", "Zigzag", "FVG" etc.
But in general, there are several reasons for making tools like trading session indicators in financial markets, some of which include the following :
1. Analysis of specific time frames : Some traders and investors like to consider specific time frames for price analysis and review. For example, analyzing price changes during each trading session can help analyze trading patterns and identify trading opportunities.
2. Recognize different price patterns : Different price patterns may be observed during trading sessions. Trading session indicators can help to make better trading decisions by analyzing these patterns and their strengths and weaknesses.
3. Identifying Support and Resistance Levels : These tools may help to identify support and resistance levels during any trading session which can be helpful in deciding whether to enter or exit the market.
🔵 How to use
The Session Lite indicator displays 8 sessions by default. Asia session, Sydney session, Tokyo session, Shanghai session, Europe session, London session, New York session and New York Stock Exchange (NYSE) session are the sessions that are displayed.
You can activate or deactivate the display of each session by using the tick button next to the name of each session.
Two gray vertical dashes are also displayed by default, which indicate the beginning of the European session and the New York session. This feature is available for all sessions, but it is enabled by default only for these two sessions, and you can activate it for the rest of the session. You can enable or disable the display of this line by using the Start Session tick key.
Likewise, the information table is displayed by default, which includes the open or closed information of each session and the start and end times of each session. These timings are based on the UTC time zone.
Accordingly, the schedule of trading sessions is as follows :
Asia session from 23:00 to 06:00
Sydney session from 23:00 to 05:00
Tokyo session from 00:00 to 00:06
Shanghai session from 01:30 to 06:57
European session from 07:00 to 16:30
London session from 08:00 to 16:30
New York session from 13:00 to 22:00
New York Stock Exchange (NYSE) session from 14:30 to T 22:00
Important note : the beginning of the European session coincides with the opening of the Frankfurt market.
🔵 Settings
• In the settings section, there are customization capabilities according to the type of use of each user. The settings related to showing or not showing the box of each session, the start indicator of each session, setting the start and end time of the session and choosing the desired color to display each session are among the things that can be set from this section.
• At the end of the settings, you will see the "Info Table" option; By disabling this option, the "sessions" clock table displayed on the upper right side will be disabled.
IU Average move How The Script Works :
1. This script calculate the average movement of the price in a user defined custom session and plot the data in a table from on top left corner of the chart.
2. The script takes highest and lowest value of that custom session and store their difference into an array.
3. Then the script average the array thus gets the average price.
4. Addition to that the script converter the price pip change into percentage in order to calculate the value in percentage form.
5. This script is pure price action based the script only take price value and doesn't take any indicator for calculation.
6. The script works on every type of market.
7. If the session is invalid it returns nothing
8. The background color, text color and transparency is changeable.
How User Can Benefit From This Script:
1. User can understand the volatility of any session that he/she wish to trade.
2. It can be helpful for understanding the average price moment of any tradeble asset.
3. It will give the average price movement both in percentage and points bases.
4. By understanding the volatility user can adjust his stop loss or take profit with respect his risk management.
Supertrend Targets [ChartPrime]The Supertrend Targets indicator combines the concepts of trend-following with dynamic volatility-based target levels. It takes core simple and classical concepts and provides actionable insights. The core of this indicator revolves around the "Supertrend" algorithm, which essentially uses the Average True Range (ATR) and a multiplier to determine if the price of a financial instrument is in an uptrend or downtrend. The indicator generates various plot points on the trading chart, which traders can use to make informed trading decisions.
Users can set several input parameters such as the source price, custom levels, multiplier scale, length of the average true range, and the window length. Traders can also opt to enable a table that shows numeric target data by percentiles, risk ratio, take profit and stop loss points.
The generated plots and fills on the chart represent various levels of potential gains and drawdowns, acting as potential targets for taking profit or stopping losses. These include the 25th, 50th, 75th, 90th, and 100th percentiles, which are adjustable by scale. There are also plots for average gain and drawdown levels, enhanced by standard deviation curves if enabled.
The Supertrend line indicators are color-coded for ease of understanding: blue for bullish performance and orange for bearish performance. The "Center Line" represents the point at which traders might consider entering a position.
Lastly, the script presents a summary table (when enabled) at the right side of the chart displaying numeric data of the plotted targets. This data provides additional insights on the risk-reward balance for each percentile, helping traders to execute their strategies more effectively.
Here's a comprehensive breakdown of its functionalities and features:
Inputs:
Source: Determines the price series type (e.g., Close, Open, High, Low, etc.).
Show Trailing Stop: Option to display the trailing stop on the chart.
Levels: Sets the number of target levels you want to display. Can range from -5 to 5.
Scale: A scaling factor for adjusting targets, can be between 1 to 100.
Window Length: Length for the target computation, determines how many bars will be considered.
Unique: Ensures every data point used in calculations is unique.
Multiplier: Multiplier for the ATR (Average True Range) to compute the SuperTrend.
ATR Length: Period for the ATR computation.
Custom Level: Allows users to set their own levels using various statistics like Average, Average + STDEV, Percentile, or can be disabled.
Percent Rank: Determines the percentile rank for targeting.
Enable Table: Enables or disables a table display.
Methods:
Flag: Identifies bullish and bearish trend reversals.
Target Percent: Determines the expected price movement (both gains and drawdowns) based on historical trend reversals.
Value Percent: Computes the percentage difference between the current price and the entry price during trend reversals.
Plots:
Multiple target lines are plotted on the chart to visualize potential gain and drawdown levels. These levels are adjusted based on user settings. Additionally, the main Supertrend line is plotted to indicate the prevailing trend direction.
Gain Levels: Target levels which show potential upside from the current price.
Drawdown Levels: Target levels which represent potential downside from the current price.
SuperTrend Line: A line that adjusts based on price volatility and trend direction, acting as a dynamic support or resistance.
In conclusion, the "Supertrend Targets " indicator is a powerful tool that combines the principle of trend-following with dynamic targets, providing traders with insights into potential future price movements. The range of customization options allows traders to adapt the indicator to different trading strategies and market conditions.
ATR InfoWhat Is the Average True Range (ATR)?
The average true range (ATR) is a technical analysis indicator, introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems, that measures market volatility by decomposing the entire range of an asset price for that period.
Each instrument per unit of time passes its average value of the true range, but there are moments when the volatility explodes or abruptly decays, these phenomena introduce large distortions into the average value of the true range.
The ATR_WPB function calculates the average value of the true range for the specified number of bars, while excluding paranormally large and paranormally small bars from the calculation of the average.
For example, if the instrument has passed a small ATR value, then it has many chances to continue moving, but if the instrument has passed its ATR value, then the chances of continuing to move are extremely low.
Volatility Capture RSI-Bollinger - Strategy [presentTrading]- Introduction and how it is different
The 'Volatility Capture RSI-Bollinger - Strategy ' is a trading strategy that combines the concepts of Bollinger Bands (BB), Relative Strength Index (RSI), and Simple Moving Average (SMA) to generate trading signals. The uniqueness of this strategy is it calculates which is a dynamic level between the upper and lower Bollinger Bands based on the closing price. This unique feature allows the strategy to adapt to market volatility and price movements.
The market in Crypto and Stock are highly volatile, making them suitable for a strategy that uses Bollinger Bands. The RSI can help identify overbought or oversold conditions in this often speculative market.
BTCUSD 4hr chart
(700.hk) 3hr chart
Remember, the effectiveness of a trading strategy also depends on other factors such as the timeframe used, the specific settings of the indicators, and the overall market conditions. It's always recommended to backtest and paper trade a strategy before using it in live trading.
- Strategy, How it Works
Dynamic Bollinger Band: The strategy works by first calculating the upper and lower Bollinger Bands based on the user-defined length and multiplier. It then uses the Bollinger Bands and the closing price to dynamically adjust the presentBollingBand value. In the end, it generates a long signal when the price crosses over the present Bolling Band and a short signal when the price crosses under the present Bolling Band.
RSI: If the user has chosen to use RSI for signals, the strategy also calculates the RSI and its SMA, and uses these to generate additional long and short signals. The RSI-based signals are only used if the 'Use RSI for signals' option is set to true.
The strategy then checks the chosen trading direction and enters a long or short position accordingly. If the trading direction is set to 'Both', the strategy can enter both long and short positions.
Finally, the strategy exits a position when the close price crosses under the present Bolling Band for a long position, or crosses over the present Bolling Band for a short position.
- Trade direction
The strategy also includes a trade direction parameter, allowing the user to choose whether to enter long trades, short trades, or both. This makes the strategy adaptable to different market conditions and trading styles.
- Usage
1. Set the input parameters as per your trading preferences. You can choose the price source, the length of the moving average, the multiplier for the ATR, whether to use RSI for signals, the RSI and SMA periods, the bought and sold range levels, and the trading direction.
2. The strategy will then generate buy and sell signals based on these parameters. You can use these signals to enter and exit trades.
- Default settings
1. Source: hlc3
2. Length: 50
3. Multiplier: 2.7183
4. Use RSI for signals: True
5. RSI Period: 10
6. SMA Period: 5
7. Bought Range Level: 55
8. Sold Range Level: 50
9. Trade Direction: Both
- Strategy's default Properties
1. Default Quantity Type: 'strategy.percent_of_equity'
2. commission_value= 0.1, commission_type=strategy.commission.percent, slippage= 1: These parameters set the commission and slippage for the strategy. The commission is set to 0.1% of the trade value, and the slippage (the difference between the expected price of a trade and the price at which the trade is executed) is set to 1.
3. default_qty_type = strategy.percent_of_equity, default_qty_value = 15: These parameters set the default quantity for trades. The default_qty_type is set to strategy.percent_of_equity, which means that the size of each trade will be a percentage of the account equity. The default_qty_value is set to 15, which means that each trade will be 15% of the account equity.
4. initial_capital= 10000: This parameter sets the initial capital for the strategy to $10,000.
StdDev ChannelsThis script draws two sets of standard deviation channels on the price chart, providing a nuanced view of price volatility over different lengths.
The script starts by declaring a set of user-defined inputs allowing traders to customize the tool according to their individual requirements. The price input sets the source of the price data, defaulting to the closing price but customizable to use open, high, or low prices. The deviations parameter defines the width of the channels, with larger numbers resulting in wider channels. The length and length2 inputs represent the number of periods (in bars) that the script considers when calculating the regression line and standard deviation. Traders can also personalize the visual aspects of the indicator on the chart using the color, linewidth, and linestyle parameters.
Calculation of Standard Deviation:
The core of this script lies in calculating the regression line and standard deviation. This is where the InertiaAll function comes into play. This function calculates the linear regression line, which serves as the middle line of each channel. The function takes in two parameters: y (price data) and n (length for calculation). It returns an array containing the values for the regression line (InertiaTS), counter variable (x), slope of the line (a), and y-intercept (b). The standard deviation is then calculated using the built-in function ta.stdev, which measures the amount of variation or dispersion from the average.
After the calculation, the script proceeds to draw the channels. It creates two sets of lines (upper, middle, and lower) for each channel. These lines are initialized at the lowest price point on the chart (low). The coordinates for these lines get updated in the last section of the script, which runs only on the last bar on the chart (if barstate.islast). The functions line.set_xy1 and line.set_xy2 are used to adjust the starting and ending points for each line, forming the channels.
If the "full range" toggle is enabled, the script uses the maximum number of bars available on the chart to calculate the regression and standard deviation. This can give a broader perspective of the price's volatility over the entire available data range.
A Basic Strategy
The channels generated by this script may inform your trading decisions. If the price hits the upper line of a channel, it could suggest an 'overbought' condition indicating a potential selling opportunity. Conversely, if the price hits the lower line, it might signal an 'oversold' condition, suggesting a buying opportunity. The second channel, calculated over a different length, may serve to confirm these signals or identify longer-term trends.
Typical Price Difference - TPD © with reversal zones and signalsv1.0 NOTE: The maths have been tested only for BTC and weekly time frame.
This is a concept that I came through after long long hours of VWAP trading and scalping.
The idea is pretty simple:
1) Typical Price is calculated by (h+l+c) / 3. If we take this price and adjust it to volume we get the VWAP value. The difference between this value and the close value, i call it " Typical Price Difference - TPD ".
2) We get the Historical Volatility as calculated by TradingView script and we add it up to TPD and divide it by two (average). This is what I call " The Source - TS ".
3) We apply the CCI formula to TS .
4) We calculate the Rate of Change (roc) of the CCI formula.
5) We apply the VIX FIX of Larry Williams (script used is from ChrisMoody - CM_Williams_Vix_Fix Finds Market Bottoms) *brilliant script!!!
How to use it:
a) When the (3) is over the TPD we have a bullish bias (green area). When it's under we have a bearish bias (red area).
b) If the (1) value goes over or under a certain value (CAUTION!!! it varies in different assets or timeframes) we get a Reversal Zone (RZ). Red/Green background.
c) If we are in a RZ and the VIX FIX gives a strong value (look for green bars in histogram) and roc (4) goes in the opposite direction, we get a reversal signal that works for the next week(s).
I applied this to BTC on a weekly time frame and after some corrections, it gives pretty good reversal zones and signals. Especially bottoms. Also look for divergences in the zones/signals.
As I said I have tested and confirmed it only on BTC/weekly. I need more time with the maths and pine to automatically adjust it to other time frames. You can play with it in different assets or time frames to find best settings by hand.
Feel free to share your thoughts or ideas on this.
P.S. I realy realy realy try to remember when or how or why I came up with the idea to combine typical price with historical volatility and CCI. I can't! It doesn't make any sense LOL
Volatility Adjusted EMA (VAEMA) The pine script shown in the code is an indicator that calculates the volatility-adjusted exponential moving average (VAEMA) of a given data series. The VAEMA indicator uses a variable alpha value in the EMA calculation, with the alpha value being inversely proportional to the volatility of the data. This allows the VAEMA indicator to provide a more accurate representation of the data's trend. The user can specify the length of the data series, the alpha value, and whether to invert the proportionality of the alpha value in the calculation. The resulting VAEMA line is plotted on the chart.
inverted alpha proportions
long lookback regular
long lookback inverted
Elevated Leverage index System - ELiSELEVATED LEVERAGE index SYSTEM (ELiS) tries to solve the problem of adjusting meaningful leverage in futures and margin trading.
The biggest problem for traders is adjusting the leverage level manually.
Concerning about the volatilities it's very hard to set a meaningful leverage level.
ELiS includes 4 different volatility component which are:
1- nATR: Normalized Average True Range which is actually ATR/price to stabilize ATR's value differences when price changes are high on long term periods.
2- Standard Deviation
3- Kairi based nATR
4- Bollinger %B
which are scaled from 0 to 100 and takes different averages with different combinations & ratios and combines them as an index.
This index calculates an average volatility to set the true leverage level when trading futures especially in Crypto and FX markets.
There are 5 risk levels of "GEARS" like on automobiles to set the max leverage for risk management.
Gear 1 - CONSERVATIVE: max leverage level can be 20 for swing traders and beginners
Gear 2 - STANDARD: max leverage level can be 25 (default) for day traders
Gear 3 - AVERAGE: max leverage level can be 33 for day traders
Gear 4 - RISKY: max leverage level can be 50 for scalpers
Gear 5 - AGRESSIVE: max leverage level can be 100 for advanced scalpers
default length for ATR, Standard Deviation and %B are all 50
Simply:
When markets aren't volatile: ELiS indicateshigher leverage values to maximize profits.
When markets are volatile enough: ELiS indicates lower values to reduce risk level.
hope you all enjoy ELiS on profitable trades.
Keltner Channel With User Selectable Moving AvgKeltner Channel with user options to calculate the moving average basis and envelopes from a variety of different moving averages.
The user selects their choice of moving average, and the envelopes automatically adjust. The user may select a MA that reacts faster to volatility or slower/smoother.
Added additional options to color the envelopes or basis based on the current trend and alternate candle colors for envelope touches. The script has a rainbow gradient by default based on RSI.
Options (generally from slower/smoother to faster/more responsive to volatility):
SMMA,
SMA,
Donchian, (Note: Selecting Donchian will just convert this indicator to a regular Donchian Channel)
Tillson T3,
EMA,
VWMA,
WMA,
EHMA,
ALMA,
LSMA,
HMA,
TEMA
Value Added:
Allows Keltner Channel to be calculated from a variety of moving averages other than EMA/SMA, including ones that are well liked by traders such as Tillson T3, ALMA, Hull MA, and TEMA.
Glossary:
The Hull Moving Average ( HMA ), developed by Alan Hull, is an extremely fast and smooth moving average . In fact, the HMA almost eliminates lag altogether and manages to improve smoothing at the same time.
The Exponential Hull Moving Average is similar to the standard Hull MA, but with superior smoothing. The standard Hull Moving Average is derived from the weighted moving average ( WMA ). As other moving average built from weighted moving averages it has a tendency to exaggerate price movement.
Weighted Moving Average: A Weighted Moving Average ( WMA ) is similar to the simple moving average ( SMA ), except the WMA adds significance to more recent data points.
Arnaud Legoux Moving Average: ALMA removes small price fluctuations and enhances the trend by applying a moving average twice, once from left to right, and once from right to left. At the end of this process the phase shift (price lag) commonly associated with moving averages is significantly reduced. Zero-phase digital filtering reduces noise in the signal. Conventional filtering reduces noise in the signal, but adds a delay.
Least Squares: Based on sum of least squares method to find a straight line that best fits data for the selected period. The end point of the line is plotted and the process is repeated on each succeeding period.
Triple EMA (TEMA) : The triple exponential moving average (TEMA) was designed to smooth price fluctuations, thereby making it easier to identify trends without the lag associated with traditional moving averages (MA). It does this by taking multiple exponential moving averages (EMA) of the original EMA and subtracting out some of the lag.
Running (SMoothed) Moving Average: A Modified Moving Average (MMA) (otherwise known as the Running Moving Average (RMA), or SMoothed Moving Average (SMMA)) is an indicator that shows the average value of a security's price over a period of time. It works very similar to the Exponential Moving Average, they are equivalent but for different periods (e.g., the MMA value for a 14-day period will be the same as EMA-value for a 27-days period).
Volume-Weighted Moving Average: The Volume-weighted Moving Average (VWMA) emphasizes volume by weighing prices based on the amount of trading activity in a given period of time. Users can set the length, the source and an offset. Prices with heavy trading activity get more weight than prices with light trading activity.
Tillson T3: The Tillson moving average a.k.a. the Tillson T3 indicator is one of the smoothest moving averages and is both composite and adaptive.
SD Lines for options [Nischay]Annual volatility is found from the NSE website in derivative section, select appropriate annualized volatility for selected instrument.
Nischay Rana
Jeges JigsThis is a combination of all my old indicators, with an added feature for trend lines (inspiration for this came from Wedge Maker script thanks to veryfid, I hope he doesn't mind).
This script looks for a period with increased volatility , as measured by ATR ( Average True Range ), then it looks for a high or a low in that area.
When price is above EMA (400 is default, can be changed), it looks for the highs and adds multiples of ATR to the high. Default values for multipliers are 3,9 and 27, meaning that the script will show 3xATR level above the high, 9xATR above the high and 27xATR above the high.
When price is below EMA it looks for the lows and subtracts multiples of ATR from the low.The script will show 3xATR level below the low, 9xATR below the low and 27xATR below the low.
Multipliers values can be changed as well, making it a versatile tool that shows potential levels of suppport/resistance based on the volatility .
Possible use cases:
Breakout trading, when price crosses a certain level, it may show potential profit targets for trades opened at a breakout.
Stoploss helper. Many traders use ATR for their stoplosses, 1 ATR below the swing low for long trades and 1 ATR above the swing high for short trades are common values used by many traders. In this case, the Lookback value comes handy, if we want to look maybe at a more recent value for swing high/low point.
It highlights ATR peaks, it also displays Bollinger bands of SMA400 (or Ema), breakouts for upper/lower bands.
Another thing you get is Parabolic SAR and Zigzag based on SAR.
[KL] Mean Reversion (ATR) StrategyThis strategy will enter into a position when price volatility is relative high, betting that price will subsequently trend in a favourable direction.
Hypothesis : During periods of high price volatility, ATR will divert from its moving average by at least +/- one standard deviation. Eventually, ATR will revert back to the mean. However, just knowing the magnitude of increase/decrease of ATR does not give a trend signal, so we need to introduce a model in this script to predict whether the next bars will be up/down.
Trend Prediction : This strategy calculates the expected logarithmic return of the security (the "Drift") and considers prices to be moving in uptrend if the drift curve is upward sloping or if the drift value is positive.
Entry Conditions : Long position is entered when:
(a) ATR has diverted from mean by one standard deviation, and
(b) trend is predicted to move in our favor.
Exit Condition : When trailing stop loss is hit.
Results from backtesting against VOO (1H timeframe):
- approx 46% win rate over 491 trades, on average holding for 20 hours per trade
- price at the beginning of backtest (Jan. 2015) was $187.52, giving holding period return of ~120% had we not sold in between ("HPR of HODL'ing")
- this strategy gained ~159%, exceeding ~120% HPR of HODL'ing
MACD-RSI With @LuckyNickVAMACD & RSi Confluence. Great for those who are looking for RSI & macd signals. Highlights volatility & structure points for entering & exiting the market. You have to understand market volatility to understand this concept. So please research more on those subjects before using. But The RSI is the relative strength index it helps you understand the increase in interest in price great for trend trading along with the momentum based indicator. Macd Developed by Gerald Appel, the Moving Average Convergence-Divergence, or MACD, is an oscillator that measures price momentum. The indicator also measures the strength, direction and duration of a trend. Forex traders can use the MACD to confirm an entry price or exit point.
HYE Trend Hunter [Strategy]*** Stratejinin Türkçe ve İngilizce açıklaması aşağıya eklenmiştir.
HYE Trend Hunter
In this strategy, two of the most basic data (price and volume) necessary for detecting trends as early as possible and entering the trade on time are used. In this context, the approaches of some classical and new generation indicators using price and volume have been taken into account.
The strategy is prepared to generate buy signals only. The following steps were followed to generate the buy and exit signals.
1-) First of all, the two most basic data of the strategy, “slow leading line” and “fast leading line” need to be calculated. For this, we use the formula of the “senkou span A” line of the indicator known as the Ichimoku Cloud. We also need to calculate lines known as tenkan sen and kijun sen in ichimoku because they are used in the calculation of this formula.
The high and low values of the candles are taken into account when calculating the Tenkansen, Kijunsen and Senkou Span A lines in the Ichimoku cloud. In this strategy, the highest and lowest values of the periodic VWAP are taken into account when calculating the "slow leading line" and "fast leading line". (The periodic vwap formula was coded and made available by @neolao on tradingviev). Also, in the ichimoku cloud, while the Senkou Span A line is plotted 26 periods into the future, we consider the values of the fast and slow leading lines in the last candle in this strategy.
ORIGINAL ICHIMOKU SPAN A FORMULA
Tenkansen = (Highest high of the last 9 candles + Lowest low of the last 9 candles) / 2
Kijunsen = (Highest high of the last 26 candles + Lowest low of the last 26 candles) / 2
Senkou Span A = Tenkansen + Kijunsen / 2
HYE TREND HUNTER SPAN A FORMULA*
Tenkansen = (Highest VWAP of the last 9 candles + Lowest VWAP of the last 9 candles) / 2
Kijunsen = (Highest VWAP of the last 26 candles + Lowest VWAP of the last 26 candles) / 2
Senkou Span A = Tenkansen + Kijunsen / 2
* We use the original ichimoku values 9 and 26 for the slow line, and 5 and 13 for the fast line. These settings can be changed from the strategy settings.
2-) At this stage, we have 2 lines that we obtained by using the formula of the ichimoku cloud, one of the most classical trend indicators, and by including the volume-weighted average price.
a-) Fast Leading Line (5-13)
b-) Slow Leading Line (9-26)
For the calculation we will do soon, we get a new value by taking the average of these two lines. Using this value, which is the average of the fast and slow leading lines, we plot the Bollinger Bands indicator, which is known as one of the most classic volatility indicators of technical analysis. Thus, we are trying to understand whether there is a volatility change in the market, which may mean the presence of a trend start. We will use this data in the calculation of buy-sell signals.
In the classical Bollinger Bands calculation, the standard deviation is calculated by applying a multiplier at the rate determined by the user (2 is used in the original settings) to the moving average calculated with the “closing price”, and this value is added or subtracted from the moving average and upper band and lower band lines are drawn.
In the HYE Trend Hunter Strategy, instead of the moving average calculated with the closing price in the Bollinger Band calculation, we consider the average of the fast and slow leading lines calculated in the 1st step and draw the Bollinger upper and lower bands accordingly. We use the values of 2 and 20 as the standard deviation and period, as in the original settings. These settings can also be changed from the strategy settings.
3-) At this stage, we have fast and slow leading lines trying to understand the trend direction using VWAP, and Bollinger lower and upper bands calculated by the average of these lines.
In this step, we will use another tool that will help us understand whether the invested market (forex, crypto, stocks) is gaining momentum in volume. The Time Segmented Volume indicator was created by the Worden Brothers Inc. and coded by @liw0 and @vitelot on tradingview. The TSV indicator segments the price and volume of an investment instrument according to certain time periods and makes calculations on comparing these price and volume data to reveal the buying and selling periods.
To trade in the buy direction on the HYE Trend Hunter Strategy, we look for the TSV indicator to be above 0 and above its exponential moving average value. TSV period and exponential moving average period settings (13 and 7) can also be changed in the strategy settings.
BUY SIGNAL
1-) Fast Leading Line value should be higher than the Fast Leading Line value in the previous candle.
2-) Slow Leading Line value should be higher than the Slow Leading Line value in the previous candle.
3-) Candle Closing value must be higher than the Upper Bollinger Band.
4-) TSV value must be greater than 0.
5-) TSV value must be greater than TSVEMA value.
EXIT SIGNAL
1-) Fast Leading Line value should be lower than the Fast Leading Line value in the previous candle.
2-) Slow Leading Line value should be lower than the Slow Leading Line value in the previous candle.
TIPS AND WARNINGS
1-) The standard settings of the strategy work better in higher timeframes (4-hour, daily, etc.). For lower timeframes, you should change the strategy settings and find the best value for yourself.
2-) All lines (fast and slow leading lines and Bollinger bands) except TSV are displayed on the strategy. For a simpler view, you can hide these lines in the strategy settings.
3-) You can see the color changes of the fast and slow leading lines as well as you can specify a single color for these lines in the strategy settings.
4-) It is an strategy for educational and experimental purposes. It cannot be considered as investment advice. You should be careful and make your own risk assessment when opening real market trades using this strategy.
_______________________________________________
HYE Trend Avcısı
Bu stratejide, trendlerin olabildiğince erken tespit edilebilmesi ve zamanında işleme girilebilmesi için gerekli olan en temel iki veriden (fiyat ve hacim) yararlanılmaktadır. Bu kapsamda, fiyat ve hacim kullanan bazı klasik ve yeni nesil indikatörlerin yaklaşımları dikkate alınmıştır.
Strateji yalnızca alış yönlü sinyaller üretecek şekilde hazırlanmıştır. Alış ve çıkış sinyallerinin üretilmesi için aşağıdaki adımlar izlenmiştir.
1-) Öncelikle, stratejinin en temel iki verisi olan “yavaş öncü çizgi” ve “hızlı öncü çizgi” hesaplamasının yapılması gerekiyor. Bunun için de Ichimoku Bulutu olarak bilinen indikatörün “senkou span A” çizgisinin formülünü kullanıyoruz. Bu formülün hesaplamasında kullanılmaları nedeniyle ichimoku’da tenkan sen ve kijun sen olarak bilinen çizgileri de hesaplamamız gerekiyor.
Ichimoku bulutunda Tenkansen, Kijunsen ve Senkou Span A çizgileri hesaplanırken mumların yüksek ve düşük değerleri dikkate alınıyor. Bu stratejide ise “yavaş öncü çizgi” ve “hızlı öncü çizgi” hesaplanırken periyodik VWAP’ın en yüksek ve en düşük değerleri dikkate alınıyor. (Periyodik vwap formülü, tradingviev’de @neolao tarafından kodlanmış ve kullanıma açılmış). Ayrıca, ichimoku bulutunda Senkou Span A çizgisi geleceğe yönelik çizilirken (26 mum ileriye dönük) biz bu stratejide öncü çizgilerin son mumdaki değerlerini dikkate alıyoruz.
ORJİNAL ICHIMOKU SPAN A FORMÜLÜ
Tenkansen = (Son 9 mumun en yüksek değeri + Son 9 mumun en düşük değeri) / 2
Kijunsen = (Son 26 mumun en yüksek değeri + Son 26 mumun en düşük değeri) / 2
Senkou Span A = Tenkansen + Kijunsen / 2
HYE TREND HUNTER SPAN A FORMÜLÜ*
Tenkansen = (Son 9 mumun en yüksek VWAP değeri + Son 9 mumun en düşük VWAP değeri) / 2
Kijunsen = (Son 26 mumun en yüksek VWAP değeri + Son 26 mumun en düşük VWAP değeri) / 2
Senkou Span A = Tenkansen + Kijunsen / 2
* Yavaş çizgi için orijinal ichimoku değerleri olan 9 ve 26’yı kullanırken, hızlı çizgi için 5 ve 13’ü kullanıyoruz. Bu ayarlar, strateji ayarlarından değiştirilebiliyor.
2-) Bu aşamada, elimizde en klasik trend indikatörlerinden birisi olan ichimoku bulutunun formülünden faydalanarak, işin içinde hacim ağırlıklı ortalama fiyatı da sokmak suretiyle elde ettiğimiz 2 çizgimiz var.
a-) Hızlı Öncü Çizgi (5-13)
b-) Yavaş Öncü Çizgi (9-26)
Birazdan yapacağımız hesaplama için bu iki çizginin de ortalamasını alarak yeni bir değer elde ediyoruz. Hızlı ve yavaş öncü çizgilerin ortalaması olan bu değeri kullanarak, teknik analizin en klasik volatilite indikatörlerinden birisi olarak bilinen Bollinger Bantları indikatörünü çizdiriyoruz. Böylelikle piyasada bir trend başlangıcının varlığı anlamına gelebilecek volatilite değişikliği var mı yok mu anlamaya çalışıyoruz. Bu veriyi al-sat sinyallerinin hesaplamasında kullanacağız.
Klasik Bollinger Bantları hesaplamasında, “kapanış fiyatıyla” hesaplanan hareketli ortalamaya, kullanıcı olarak belirlenen oranda (orijinal ayarlarında 2 kullanılır) bir çarpan uygulanarak standart sapma hesaplanıyor ve bu değer hareketli ortalamaya eklenip çıkartılarak üst bant ve alt bant çizgileri çiziliyor.
HYE Trend Avcısı stratejisinde, Bollinger Bandı hesaplamasında kapanış fiyatıyla hesaplanan hareketli ortalama yerine, 1. adımda hesapladığımız hızlı ve yavaş öncü çizgilerin ortalamasını dikkate alıyoruz ve buna göre bollinger üst ve alt bantlarını çizdiriyoruz. Standart sapma ve periyot olarak yine orijinal ayarlarında olduğu gibi 2 ve 20 değerlerini kullanıyoruz. Bu ayarlar da strateji ayarlarından değiştirilebiliyor.
3-) Bu aşamada, elimizde VWAP kullanarak trend yönünü anlamaya çalışan hızlı ve yavaş öncü çizgilerimiz ile bu çizgilerin ortalaması ile hesaplanan bollinger alt ve üst bantlarımız var.
Bu adımda, yatırım yapılan piyasanın (forex, kripto, hisse senedi) hacimsel olarak ivme kazanıp kazanmadığını anlamamıza yarayacak bir araç daha kullanacağız. Time Segmented Volume indikatörü, Worden Kardeşler şirketi tarafından oluşturulmuş ve tradingview’de @liw0 ve @vitelot tarafından kodlanarak kullanıma açılmış. TSV indikatörü, bir yatırım aracının fiyatını ve hacmini belirli zaman aralıklarına göre bölümlere ayırarak, bu fiyat ve hacim verilerini, alış ve satış dönemlerini ortaya çıkarmak için karşılaştırmak üzerine hesaplamalar yapar.
HYE Trend Avcısı stratejisinde alış yönünde işlem yapmak için, TSV indikatörünün 0’ın üzerinde olmasını ve kendi üstel hareketli ortalama değerinin üzerinde olmasını arıyoruz. TSV periyodu ve üstel hareketli ortalama periyodu ayarları da (13 ve 7) strateji ayarlarından değiştirilebiliyor.
ALIŞ SİNYALİ
1-) Hızlı Öncü Çizgi değeri bir önceki mumdaki Hızlı Öncü Çizgi değerinden yüksek olmalı.
2-) Yavaş Öncü Çizgi değeri bir önceki mumdaki Yavaş Öncü Çizgi değerinden yüksek olmalı.
3-) Kapanış Değeri, Üst Bollinger Bandı değerinden yüksek olmalı.
4-) TSV değeri 0’dan büyük olmalı.
5-) TSV değeri TSVEMA değerinden büyük olmalı.
ÇIKIŞ SİNYALİ
1-) Hızlı Öncü Çizgi değeri bir önceki mumdaki Hızlı Öncü Çizgi değerinden düşük olmalı.
2-) Yavaş Öncü Çizgi değeri bir önceki mumdaki Yavaş Öncü Çizgi değerinden düşük olmalı.
İPUÇLARI VE UYARILAR
1-) Stratejinin standart ayarları, yüksek zaman dilimlerinde (4 saatlik, günlük vs.) daha iyi çalışıyor. Düşük zaman dilimleri için strateji ayarlarını değiştirmeli ve kendiniz için en iyi değeri bulmalısınız.
2-) Stratejide tüm çizgiler (hızlı ve yavaş öncü çizgiler ile bollinger bantları) -TSV dışında- açık olarak gelmektedir. Daha sade bir görüntü için bu çizgilerin görünürlüğünü strateji ayarlarından gizleyebilirsiniz.
3-) Hızlı ve yavaş öncü çizgilerin renk değişimlerini görebileceğiniz gibi bu çizgiler için tek bir renk olarak da strateji ayarlarında belirleme yapabilirsiniz.
4-) Eğitim ve deneysel amaçlı bir stratejidir. Yatırım tavsiyesi olarak değerlendirilemez. Bu stratejiyi kullanarak gerçek piyasa işlem açarken dikkatli olmalı ve kendi risk değerlendirmenizi yapmalısınız.
HYE Trend Hunter [Indicator]*** İndikatörün Türkçe ve İngilizce açıklaması aşağıya eklenmiştir.
HYE Trend Hunter
In this indicator, two of the most basic data (price and volume) necessary for detecting trends as early as possible and entering the trade on time are used. In this context, the approaches of some classical and new generation indicators using price and volume have been taken into account.
The indicator is prepared to generate buy signals only. The following steps were followed to generate the buy and exit signals.
1-) First of all, the two most basic data of the indicator, “slow leading line” and “fast leading line” need to be calculated. For this, we use the formula of the “senkou span A” line of the indicator known as the Ichimoku Cloud. We also need to calculate lines known as tenkan sen and kijun sen in ichimoku because they are used in the calculation of this formula.
The high and low values of the candles are taken into account when calculating the Tenkansen, Kijunsen and Senkou Span A lines in the Ichimoku cloud. In this indicator, the highest and lowest values of the periodic VWAP are taken into account when calculating the "slow leading line" and "fast leading line". (The periodic vwap formula was coded and made available by @neolao on tradingviev). Also, in the ichimoku cloud, while the Senkou Span A line is plotted 26 periods into the future, we consider the values of the fast and slow leading lines in the last candle in this indicator.
ORIGINAL ICHIMOKU SPAN A FORMULA
Tenkansen = (Highest high of the last 9 candles + Lowest low of the last 9 candles) / 2
Kijunsen = (Highest high of the last 26 candles + Lowest low of the last 26 candles) / 2
Senkou Span A = Tenkansen + Kijunsen / 2
HYE TREND HUNTER SPAN A FORMULA*
Tenkansen = (Highest VWAP of the last 9 candles + Lowest VWAP of the last 9 candles) / 2
Kijunsen = (Highest VWAP of the last 26 candles + Lowest VWAP of the last 26 candles) / 2
Senkou Span A = Tenkansen + Kijunsen / 2
* We use the original ichimoku values 9 and 26 for the slow line, and 5 and 13 for the fast line. These settings can be changed from the indicator settings.
2-) At this stage, we have 2 lines that we obtained by using the formula of the ichimoku cloud, one of the most classical trend indicators, and by including the volume-weighted average price.
a-) Fast Leading Line (5-13)
b-) Slow Leading Line (9-26)
For the calculation we will do soon, we get a new value by taking the average of these two lines. Using this value, which is the average of the fast and slow leading lines, we plot the Bollinger Bands indicator, which is known as one of the most classic volatility indicators of technical analysis. Thus, we are trying to understand whether there is a volatility change in the market, which may mean the presence of a trend start. We will use this data in the calculation of buy-sell signals.
In the classical Bollinger Bands calculation, the standard deviation is calculated by applying a multiplier at the rate determined by the user (2 is used in the original settings) to the moving average calculated with the “closing price”, and this value is added or subtracted from the moving average and upper band and lower band lines are drawn.
In the HYE Trend Hunter indicator, instead of the moving average calculated with the closing price in the Bollinger Band calculation, we consider the average of the fast and slow leading lines calculated in the 1st step and draw the Bollinger upper and lower bands accordingly. We use the values of 2 and 20 as the standard deviation and period, as in the original settings. These settings can also be changed from the indicator settings.
3-) At this stage, we have fast and slow leading lines trying to understand the trend direction using VWAP, and Bollinger lower and upper bands calculated by the average of these lines.
In this step, we will use another tool that will help us understand whether the invested market (forex, crypto, stocks) is gaining momentum in volume. The Time Segmented Volume indicator was created by the Worden Brothers Inc. and coded by @liw0 and @vitelot on tradingview. The TSV indicator segments the price and volume of an investment instrument according to certain time periods and makes calculations on comparing these price and volume data to reveal the buying and selling periods.
To trade in the buy direction on the HYE Trend Hunter indicator, we look for the TSV indicator to be above 0 and above its exponential moving average value. TSV period and exponential moving average period settings (13 and 7) can also be changed in the indicator settings.
BUY SIGNAL
1-) Fast Leading Line value should be higher than the Fast Leading Line value in the previous candle.
2-) Slow Leading Line value should be higher than the Slow Leading Line value in the previous candle.
3-) Candle Closing value must be higher than the Upper Bollinger Band.
4-) TSV value must be greater than 0.
5-) TSV value must be greater than TSVEMA value.
EXIT SIGNAL
1-) Fast Leading Line value should be lower than the Fast Leading Line value in the previous candle.
2-) Slow Leading Line value should be lower than the Slow Leading Line value in the previous candle.
TIPS AND WARNINGS
1-) The standard settings of the indicator work better in higher timeframes (4-hour, daily, etc.). For lower timeframes, you should change the indicator settings and find the best value for yourself.
2-) All lines (fast and slow leading lines and Bollinger bands) except TSV are displayed on the indicator. For a simpler view, you can hide these lines in the indicator settings.
3-) You can see the color changes of the fast and slow leading lines as well as you can specify a single color for these lines in the Indicator settings.
4-) Alarms have been added for Buy and Exit. When setting up the alarm, you should set it to be triggered at "every bar close". Otherwise it may repaint. There is no repaint after the candle closes.
5-) It is an indicator for educational and experimental purposes. It cannot be considered as investment advice. You should be careful and make your own risk assessment when opening real market trades using this indicator.
_______________________________________________
HYE Trend Avcısı
Bu indikatörde, trendlerin olabildiğince erken tespit edilebilmesi ve zamanında işleme girilebilmesi için gerekli olan en temel iki veriden (fiyat ve hacim) yararlanılmaktadır. Bu kapsamda, fiyat ve hacim kullanan bazı klasik ve yeni nesil indikatörlerin yaklaşımları dikkate alınmıştır.
İndikatör yalnızca alış yönlü sinyaller üretecek şekilde hazırlanmıştır. Alış ve çıkış sinyallerinin üretilmesi için aşağıdaki adımlar izlenmiştir.
1-) Öncelikle, indikatörün en temel iki verisi olan “yavaş öncü çizgi” ve “hızlı öncü çizgi” hesaplamasının yapılması gerekiyor. Bunun için de Ichimoku Bulutu olarak bilinen indikatörün “senkou span A” çizgisinin formülünü kullanıyoruz. Bu formülün hesaplamasında kullanılmaları nedeniyle ichimoku’da tenkan sen ve kijun sen olarak bilinen çizgileri de hesaplamamız gerekiyor.
Ichimoku bulutunda Tenkansen, Kijunsen ve Senkou Span A çizgileri hesaplanırken mumların yüksek ve düşük değerleri dikkate alınıyor. Bu indikatörde ise “yavaş öncü çizgi” ve “hızlı öncü çizgi” hesaplanırken periyodik VWAP’ın en yüksek ve en düşük değerleri dikkate alınıyor. (Periyodik vwap formülü, tradingviev’de @neolao tarafından kodlanmış ve kullanıma açılmış). Ayrıca, ichimoku bulutunda Senkou Span A çizgisi geleceğe yönelik çizilirken (26 mum ileriye dönük) biz bu indikatörde öncü çizgilerin son mumdaki değerlerini dikkate alıyoruz.
ORJİNAL ICHIMOKU SPAN A FORMÜLÜ
Tenkansen = (Son 9 mumun en yüksek değeri + Son 9 mumun en düşük değeri) / 2
Kijunsen = (Son 26 mumun en yüksek değeri + Son 26 mumun en düşük değeri) / 2
Senkou Span A = Tenkansen + Kijunsen / 2
HYE TREND HUNTER SPAN A FORMÜLÜ*
Tenkansen = (Son 9 mumun en yüksek VWAP değeri + Son 9 mumun en düşük VWAP değeri) / 2
Kijunsen = (Son 26 mumun en yüksek VWAP değeri + Son 26 mumun en düşük VWAP değeri) / 2
Senkou Span A = Tenkansen + Kijunsen / 2
* Yavaş çizgi için orijinal ichimoku değerleri olan 9 ve 26’yı kullanırken, hızlı çizgi için 5 ve 13’ü kullanıyoruz. Bu ayarlar, indikatör ayarlarından değiştirilebiliyor.
2-) Bu aşamada, elimizde en klasik trend indikatörlerinden birisi olan ichimoku bulutunun formülünden faydalanarak, işin içinde hacim ağırlıklı ortalama fiyatı da sokmak suretiyle elde ettiğimiz 2 çizgimiz var.
a-) Hızlı Öncü Çizgi (5-13)
b-) Yavaş Öncü Çizgi (9-26)
Birazdan yapacağımız hesaplama için bu iki çizginin de ortalamasını alarak yeni bir değer elde ediyoruz. Hızlı ve yavaş öncü çizgilerin ortalaması olan bu değeri kullanarak, teknik analizin en klasik volatilite indikatörlerinden birisi olarak bilinen Bollinger Bantları indikatörünü çizdiriyoruz. Böylelikle piyasada bir trend başlangıcının varlığı anlamına gelebilecek volatilite değişikliği var mı yok mu anlamaya çalışıyoruz. Bu veriyi al-sat sinyallerinin hesaplamasında kullanacağız.
Klasik Bollinger Bantları hesaplamasında, “kapanış fiyatıyla” hesaplanan hareketli ortalamaya, kullanıcı olarak belirlenen oranda (orijinal ayarlarında 2 kullanılır) bir çarpan uygulanarak standart sapma hesaplanıyor ve bu değer hareketli ortalamaya eklenip çıkartılarak üst bant ve alt bant çizgileri çiziliyor.
HYE Trend Avcısı indikatöründe, Bollinger Bandı hesaplamasında kapanış fiyatıyla hesaplanan hareketli ortalama yerine, 1. adımda hesapladığımız hızlı ve yavaş öncü çizgilerin ortalamasını dikkate alıyoruz ve buna göre bollinger üst ve alt bantlarını çizdiriyoruz. Standart sapma ve periyot olarak yine orijinal ayarlarında olduğu gibi 2 ve 20 değerlerini kullanıyoruz. Bu ayarlar da indikatör ayarlarından değiştirilebiliyor.
3-) Bu aşamada, elimizde VWAP kullanarak trend yönünü anlamaya çalışan hızlı ve yavaş öncü çizgilerimiz ile bu çizgilerin ortalaması ile hesaplanan bollinger alt ve üst bantlarımız var.
Bu adımda, yatırım yapılan piyasanın (forex, kripto, hisse senedi) hacimsel olarak ivme kazanıp kazanmadığını anlamamıza yarayacak bir araç daha kullanacağız. Time Segmented Volume indikatörü, Worden Kardeşler şirketi tarafından oluşturulmuş ve tradingview’de @liw0 ve @vitelot tarafından kodlanarak kullanıma açılmış. TSV indikatörü, bir yatırım aracının fiyatını ve hacmini belirli zaman aralıklarına göre bölümlere ayırarak, bu fiyat ve hacim verilerini, alış ve satış dönemlerini ortaya çıkarmak için karşılaştırmak üzerine hesaplamalar yapar.
HYE Trend Avcısı indikatöründe alış yönünde işlem yapmak için, TSV indikatörünün 0’ın üzerinde olmasını ve kendi üstel hareketli ortalama değerinin üzerinde olmasını arıyoruz. TSV periyodu ve üstel hareketli ortalama periyodu ayarları da (13 ve 7) indikatör ayarlarından değiştirilebiliyor.
ALIŞ SİNYALİ
1-) Hızlı Öncü Çizgi değeri bir önceki mumdaki Hızlı Öncü Çizgi değerinden yüksek olmalı.
2-) Yavaş Öncü Çizgi değeri bir önceki mumdaki Yavaş Öncü Çizgi değerinden yüksek olmalı.
3-) Kapanış Değeri, Üst Bollinger Bandı değerinden yüksek olmalı.
4-) TSV değeri 0’dan büyük olmalı.
5-) TSV değeri TSVEMA değerinden büyük olmalı.
ÇIKIŞ SİNYALİ
1-) Hızlı Öncü Çizgi değeri bir önceki mumdaki Hızlı Öncü Çizgi değerinden düşük olmalı.
2-) Yavaş Öncü Çizgi değeri bir önceki mumdaki Yavaş Öncü Çizgi değerinden düşük olmalı.
İPUÇLARI VE UYARILAR
1-) İndikatörün standart ayarları, yüksek zaman dilimlerinde (4 saatlik, günlük vs.) daha iyi çalışıyor. Düşük zaman dilimleri için indikatör ayarlarını değiştirmeli ve kendiniz için en iyi değeri bulmalısınız.
2-) İndikatörde tüm çizgiler (hızlı ve yavaş öncü çizgiler ile bollinger bantları) -TSV dışında- açık olarak gelmektedir. Daha sade bir görüntü için bu çizgilerin görünürlüğünü indikatör ayarlarından gizleyebilirsiniz.
3-) Hızlı ve yavaş öncü çizgilerin renk değişimlerini görebileceğiniz gibi bu çizgiler için tek bir renk olarak da İndikatör ayarlarında belirleme yapabilirsiniz.
4-) Alış ve Çıkış için alarmlar eklenmiştir. Alarm kurulumu yaparken “Her çubuk kapanışında” tetiklenecek şekilde ayarlama yapmalısınız. Aksi takdirde repaint yapabilir. Mum kapanışından sonra repaint söz konusu değildir.
5-) Eğitim ve deneysel amaçlı bir indikatördür. Yatırım tavsiyesi olarak değerlendirilemez. Bu indikatörü kullanarak gerçek piyasa işlem açarken dikkatli olmalı ve kendi risk değerlendirmenizi yapmalısınız.
Scalping Screener - 15minSCALPING SCREENER - 15 mins (Indicator Tool)
TIME FRAME to use - 15 mins
DURATION OF TRADE - Using this indicator, Trade must be taken only during market hours and must be closed before market close (must not be carried forrward for next day).
SCALPING - This is a scalping strategy that is intended to make small profits in intraday trading
ENTRY CONCEPT -
- There must be 2 bulish candles and the 2nd candle's high should be greater than first candle's high.
- And If the latest candle high breaks high of the 2nd candle (prev candle), BUY signal is generated.
- Additional filters are added to reduce non-performaing trades.
- visa versa for SHORT signal
EXIT CONCEPT -
- 2nd candles low is the stop loss.
- Difference between 2nd candle high and 2nd candle low is target.
- The script will indicate when to BUY / SHORT and when to EXIT the trade.
INSTRUMENTS TO TRADE -
- High volatility instruments are best to be traded
- Nifty 50 stocks have been added to this indicator for the sake of screener. User can change these stocks with high volatility ones
- There is a limitation to add upto 40 scripts.
SCREENER FUNCTION -
- Right side of the chart has screener section which shows the list of stocks that qualify as per the BUY / SELL signal
NOTE -
The purpose of the scipt is for self learning / improvement and analysis.
Trading is a risky business and a trader must take any trade at their own RISK.
The author shall not be held responsible for Losses / Profits
Candle Volatilty IndicatorThis script helps to get a better view on the volatility of the price.
Each bar represents the high and low of the candle calculated derived from the open price.
It can help to get an insight on the volatility .
DEMA/EMA & VOL (Short strategy)Hello,
I am trying to build a short momentum strategy that is based off of the DEMA crossing under the EMA, but because many momentum strategies send too many signals, I have also implemented a volatility condition based on the average true range percentage (ATRP). Essentially, as momentum moves downwards + volatility (ATRP) moves upwards, it shorts the security. However, I am having an issue with exiting trades. I think this would be a great strategy if I could simply get the strategy to exit the trades. Does anyone mind looking through the source code and tell me what I might be doing wrong? In return, I would hope that this strategy could be useful to you in same way! Thank you for looking!
Monte Carlo Range Forecast [DW]This is an experimental study designed to forecast the range of price movement from a specified starting point using a Monte Carlo simulation.
Monte Carlo experiments are a broad class of computational algorithms that utilize random sampling to derive real world numerical results.
These types of algorithms have a number of applications in numerous fields of study including physics, engineering, behavioral sciences, climate forecasting, computer graphics, gaming AI, mathematics, and finance.
Although the applications vary, there is a typical process behind the majority of Monte Carlo methods:
-> First, a distribution of possible inputs is defined.
-> Next, values are generated randomly from the distribution.
-> The values are then fed through some form of deterministic algorithm.
-> And lastly, the results are aggregated over some number of iterations.
In this study, the Monte Carlo process used generates a distribution of aggregate pseudorandom linear price returns summed over a user defined period, then plots standard deviations of the outcomes from the mean outcome generate forecast regions.
The pseudorandom process used in this script relies on a modified Wichmann-Hill pseudorandom number generator (PRNG) algorithm.
Wichmann-Hill is a hybrid generator that uses three linear congruential generators (LCGs) with different prime moduli.
Each LCG within the generator produces an independent, uniformly distributed number between 0 and 1.
The three generated values are then summed and modulo 1 is taken to deliver the final uniformly distributed output.
Because of its long cycle length, Wichmann-Hill is a fantastic generator to use on TV since it's extremely unlikely that you'll ever see a cycle repeat.
The resulting pseudorandom output from this generator has a minimum repetition cycle length of 6,953,607,871,644.
Fun fact: Wichmann-Hill is a widely used PRNG in various software applications. For example, Excel 2003 and later uses this algorithm in its RAND function, and it was the default generator in Python up to v2.2.
The generation algorithm in this script takes the Wichmann-Hill algorithm, and uses a multi-stage transformation process to generate the results.
First, a parent seed is selected. This can either be a fixed value, or a dynamic value.
The dynamic parent value is produced by taking advantage of Pine's timenow variable behavior. It produces a variable parent seed by using a frozen ratio of timenow/time.
Because timenow always reflects the current real time when frozen and the time variable reflects the chart's beginning time when frozen, the ratio of these values produces a new number every time the cache updates.
After a parent seed is selected, its value is then fed through a uniformly distributed seed array generator, which generates multiple arrays of pseudorandom "children" seeds.
The seeds produced in this step are then fed through the main generators to produce arrays of pseudorandom simulated outcomes, and a pseudorandom series to compare with the real series.
The main generators within this script are designed to (at least somewhat) model the stochastic nature of financial time series data.
The first step in this process is to transform the uniform outputs of the Wichmann-Hill into outputs that are normally distributed.
In this script, the transformation is done using an estimate of the normal distribution quantile function.
Quantile functions, otherwise known as percent-point or inverse cumulative distribution functions, specify the value of a random variable such that the probability of the variable being within the value's boundary equals the input probability.
The quantile equation for a normal probability distribution is μ + σ(√2)erf^-1(2(p - 0.5)) where μ is the mean of the distribution, σ is the standard deviation, erf^-1 is the inverse Gauss error function, and p is the probability.
Because erf^-1() does not have a simple, closed form interpretation, it must be approximated.
To keep things lightweight in this approximation, I used a truncated Maclaurin Series expansion for this function with precomputed coefficients and rolled out operations to avoid nested looping.
This method provides a decent approximation of the error function without completely breaking floating point limits or sucking up runtime memory.
Note that there are plenty of more robust techniques to approximate this function, but their memory needs very. I chose this method specifically because of runtime favorability.
To generate a pseudorandom approximately normally distributed variable, the uniformly distributed variable from the Wichmann-Hill algorithm is used as the input probability for the quantile estimator.
Now from here, we get a pretty decent output that could be used itself in the simulation process. Many Monte Carlo simulations and random price generators utilize a normal variable.
However, if you compare the outputs of this normal variable with the actual returns of the real time series, you'll find that the variability in shocks (random changes) doesn't quite behave like it does in real data.
This is because most real financial time series data is more complex. Its distribution may be approximately normal at times, but the variability of its distribution changes over time due to various underlying factors.
In light of this, I believe that returns behave more like a convoluted product distribution rather than just a raw normal.
So the next step to get our procedurally generated returns to more closely emulate the behavior of real returns is to introduce more complexity into our model.
Through experimentation, I've found that a return series more closely emulating real returns can be generated in a three step process:
-> First, generate multiple independent, normally distributed variables simultaneously.
-> Next, apply pseudorandom weighting to each variable ranging from -1 to 1, or some limits within those bounds. This modulates each series to provide more variability in the shocks by producing product distributions.
-> Lastly, add the results together to generate the final pseudorandom output with a convoluted distribution. This adds variable amounts of constructive and destructive interference to produce a more "natural" looking output.
In this script, I use three independent normally distributed variables multiplied by uniform product distributed variables.
The first variable is generated by multiplying a normal variable by one uniformly distributed variable. This produces a bit more tailedness (kurtosis) than a normal distribution, but nothing too extreme.
The second variable is generated by multiplying a normal variable by two uniformly distributed variables. This produces moderately greater tails in the distribution.
The third variable is generated by multiplying a normal variable by three uniformly distributed variables. This produces a distribution with heavier tails.
For additional control of the output distributions, the uniform product distributions are given optional limits.
These limits control the boundaries for the absolute value of the uniform product variables, which affects the tails. In other words, they limit the weighting applied to the normally distributed variables in this transformation.
All three sets are then multiplied by user defined amplitude factors to adjust presence, then added together to produce our final pseudorandom return series with a convoluted product distribution.
Once we have the final, more "natural" looking pseudorandom series, the values are recursively summed over the forecast period to generate a simulated result.
This process of generation, weighting, addition, and summation is repeated over the user defined number of simulations with different seeds generated from the parent to produce our array of initial simulated outcomes.
After the initial simulation array is generated, the max, min, mean and standard deviation of this array are calculated, and the values are stored in holding arrays on each iteration to be called upon later.
Reference difference series and price values are also stored in holding arrays to be used in our comparison plots.
In this script, I use a linear model with simple returns rather than compounding log returns to generate the output.
The reason for this is that in generating outputs this way, we're able to run our simulations recursively from the beginning of the chart, then apply scaling and anchoring post-process.
This allows a greater conservation of runtime memory than the alternative, making it more suitable for doing longer forecasts with heavier amounts of simulations in TV's runtime environment.
From our starting time, the previous bar's price, volatility, and optional drift (expected return) are factored into our holding arrays to generate the final forecast parameters.
After these parameters are computed, the range forecast is produced.
The basis value for the ranges is the mean outcome of the simulations that were run.
Then, quarter standard deviations of the simulated outcomes are added to and subtracted from the basis up to 3σ to generate the forecast ranges.
All of these values are plotted and colorized based on their theoretical probability density. The most likely areas are the warmest colors, and least likely areas are the coolest colors.
An information panel is also displayed at the starting time which shows the starting time and price, forecast type, parent seed value, simulations run, forecast bars, total drift, mean, standard deviation, max outcome, min outcome, and bars remaining.
The interesting thing about simulated outcomes is that although the probability distribution of each simulation is not normal, the distribution of different outcomes converges to a normal one with enough steps.
In light of this, the probability density of outcomes is highest near the initial value + total drift, and decreases the further away from this point you go.
This makes logical sense since the central path is the easiest one to travel.
Given the ever changing state of markets, I find this tool to be best suited for shorter term forecasts.
However, if the movements of price are expected to remain relatively stable, longer term forecasts may be equally as valid.
There are many possible ways for users to apply this tool to their analysis setups. For example, the forecast ranges may be used as a guide to help users set risk targets.
Or, the generated levels could be used in conjunction with other indicators for meaningful confluence signals.
More advanced users could even extrapolate the functions used within this script for various purposes, such as generating pseudorandom data to test systems on, perform integration and approximations, etc.
These are just a few examples of potential uses of this script. How you choose to use it to benefit your trading, analysis, and coding is entirely up to you.
If nothing else, I think this is a pretty neat script simply for the novelty of it.
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How To Use:
When you first add the script to your chart, you will be prompted to confirm the starting date and time, number of bars to forecast, number of simulations to run, and whether to include drift assumption.
You will also be prompted to confirm the forecast type. There are two types to choose from:
-> End Result - This uses the values from the end of the simulation throughout the forecast interval.
-> Developing - This uses the values that develop from bar to bar, providing a real-time outlook.
You can always update these settings after confirmation as well.
Once these inputs are confirmed, the script will boot up and automatically generate the forecast in a separate pane.
Note that if there is no bar of data at the time you wish to start the forecast, the script will automatically detect use the next available bar after the specified start time.
From here, you can now control the rest of the settings.
The "Seeding Settings" section controls the initial seed value used to generate the children that produce the simulations.
In this section, you can control whether the seed is a fixed value, or a dynamic one.
Since selecting the dynamic parent option will change the seed value every time you change the settings or refresh your chart, there is a "Regenerate" input built into the script.
This input is a dummy input that isn't connected to any of the calculations. The purpose of this input is to force an update of the dynamic parent without affecting the generator or forecast settings.
Note that because we're running a limited number of simulations, different parent seeds will typically yield slightly different forecast ranges.
When using a small number of simulations, you will likely see a higher amount of variance between differently seeded results because smaller numbers of sampled simulations yield a heavier bias.
The more simulations you run, the smaller this variance will become since the outcomes become more convergent toward the same distribution, so the differences between differently seeded forecasts will become more marginal.
When using a dynamic parent, pay attention to the dispersion of ranges.
When you find a set of ranges that is dispersed how you like with your configuration, set your fixed parent value to the parent seed that shows in the info panel.
This will allow you to replicate that dispersion behavior again in the future.
An important thing to note when settings alerts on the plotted levels, or using them as components for signals in other scripts, is to decide on a fixed value for your parent seed to avoid minor repainting due to seed changes.
When the parent seed is fixed, no repainting occurs.
The "Amplitude Settings" section controls the amplitude coefficients for the three differently tailed generators.
These amplitude factors will change the difference series output for each simulation by controlling how aggressively each series moves.
When "Adjust Amplitude Coefficients" is disabled, all three coefficients are set to 1.
Note that if you expect volatility to significantly diverge from its historical values over the forecast interval, try experimenting with these factors to match your anticipation.
The "Weighting Settings" section controls the weighting boundaries for the three generators.
These weighting limits affect how tailed the distributions in each generator are, which in turn affects the final series outputs.
The maximum absolute value range for the weights is . When "Limit Generator Weights" is disabled, this is the range that is automatically used.
The last set of inputs is the "Display Settings", where you can control the visual outputs.
From here, you can select to display either "Forecast" or "Difference Comparison" via the "Output Display Type" dropdown tab.
"Forecast" is the type displayed by default. This plots the end result or developing forecast ranges.
There is an option with this display type to show the developing extremes of the simulations. This option is enabled by default.
There's also an option with this display type to show one of the simulated price series from the set alongside actual prices.
This allows you to visually compare simulated prices alongside the real prices.
"Difference Comparison" allows you to visually compare a synthetic difference series from the set alongside the actual difference series.
This display method is primarily useful for visually tuning the amplitude and weighting settings of the generators.
There are also info panel settings on the bottom, which allow you to control size, colors, and date format for the panel.
It's all pretty simple to use once you get the hang of it. So play around with the settings and see what kinds of forecasts you can generate!
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ADDITIONAL NOTES & DISCLAIMERS
Although I've done a number of things within this script to keep runtime demands as low as possible, the fact remains that this script is fairly computationally heavy.
Because of this, you may get random timeouts when using this script.
This could be due to either random drops in available runtime on the server, using too many simulations, or running the simulations over too many bars.
If it's just a random drop in runtime on the server, hide and unhide the script, re-add it to the chart, or simply refresh the page.
If the timeout persists after trying this, then you'll need to adjust your settings to a less demanding configuration.
Please note that no specific claims are being made in regards to this script's predictive accuracy.
It must be understood that this model is based on randomized price generation with assumed constant drift and dispersion from historical data before the starting point.
Models like these not consider the real world factors that may influence price movement (economic changes, seasonality, macro-trends, instrument hype, etc.), nor the changes in sample distribution that may occur.
In light of this, it's perfectly possible for price data to exceed even the most extreme simulated outcomes.
The future is uncertain, and becomes increasingly uncertain with each passing point in time.
Predictive models of any type can vary significantly in performance at any point in time, and nobody can guarantee any specific type of future performance.
When using forecasts in making decisions, DO NOT treat them as any form of guarantee that values will fall within the predicted range.
When basing your trading decisions on any trading methodology or utility, predictive or not, you do so at your own risk.
No guarantee is being issued regarding the accuracy of this forecast model.
Forecasting is very far from an exact science, and the results from any forecast are designed to be interpreted as potential outcomes rather than anything concrete.
With that being said, when applied prudently and treated as "general case scenarios", forecast models like these may very well be potentially beneficial tools to have in the arsenal.
