Long EMA Strategy with Advanced Exit OptionsThis strategy is designed for traders seeking a trend-following system with a focus on precision and adaptability.
**Core Strategy Concept**
The essence of this strategy lies in use of Exponential Moving Averages (EMAs) to identify potential long (buy) positions based on the relative positions of short-term, medium-term, and long-term EMAs. The use of EMAs is a classic yet powerful approach to trend detection, as these indicators smooth out price data over time, emphasizing the direction of recent price movements and potentially signaling the beginning of new trends.
**Customizable Parameters**
- **EMA Periods**: Users can define the periods for three EMAs - long-term, medium-term, and short-term - allowing for a tailored approach to capture trends based on individual trading styles and market conditions.
- **Volatility Filter**: An optional Average True Range (ATR)-based volatility filter can be toggled on or off. When activated, it ensures that trades are only entered when market volatility exceeds a user-defined threshold, aiming to filter out entries during low-volatility periods which are often characterized by indecisive market movements.
- **Trailing Stop Loss**: A trailing stop loss mechanism, expressed as a percentage of the highest price achieved since entry, provides a dynamic way to manage risk by allowing profits to run while cutting losses.
- **EMA Exit Condition**: This advanced exit option enables closing positions when the short-term EMA crosses below the medium-term EMA, serving as a signal that the immediate trend may be reversing.
- **Close Below EMA Exit**: An additional exit condition, which is disabled by default, allows positions to be closed if the price closes below a user-selected EMA. This provides an extra layer of flexibility and risk management, catering to traders who prefer to exit positions based on specific EMA thresholds.
**Operational Mechanics**
Upon activation, the strategy evaluates the current price in relation to the set EMAs. A long position is considered when the current price is above the long-term EMA, and the short-term EMA is above the medium-term EMA. This setup aims to identify moments where the price momentum is strong and likely to continue.
The strategy's versatility is further enhanced by its optional settings:
- The **Volatility Filter** adjusts the sensitivity of the strategy to market movements, potentially improving the quality of the entries during volatile market conditions.
The Average True Range (ATR) is a key component of this filter, providing a measure of market volatility by calculating the average range between the high and low prices over a specified number of periods. Here's how you can adjust the volatility filter settings for various market conditions, focusing on filtering out low-volatility markets:
Setting Examples for Volatility Filter
1. High Volatility Markets (e.g., Cryptocurrencies, Certain Forex Pairs):
ATR Periods: 14 (default)
ATR Multiplier: Setting the multiplier to a lower value, such as 1.0 or 1.2, can be beneficial in high-volatility markets. This sensitivity allows the strategy to react to volatility changes more quickly, ensuring that you're entering trades during periods of significant movement.
2. Medium Volatility Markets (e.g., Major Equity Indices, Medium-Volatility Forex Pairs):
ATR Periods: 14 (default)
ATR Multiplier: A multiplier of 1.5 (default) is often suitable for medium volatility markets. It provides a balanced approach, ensuring that the strategy filters out low-volatility conditions without being overly restrictive.
3. Low Volatility Markets (e.g., Some Commodities, Low-Volatility Forex Pairs):
ATR Periods: Increasing the ATR period to 20 or 25 can smooth out the volatility measure, making it less sensitive to short-term fluctuations. This adjustment helps in focusing on more significant trends in inherently stable markets.
ATR Multiplier: Raising the multiplier to 2.0 or even 2.5 increases the threshold for volatility, effectively filtering out low-volatility conditions. This setting ensures that the strategy only triggers trades during periods of relatively higher volatility, which are more likely to result in significant price movements.
How to Use the Volatility Filter for Low-Volatility Markets
For traders specifically interested in filtering out low-volatility markets, the key is to adjust the ATR Multiplier to a higher level. This adjustment increases the threshold required for the market to be considered sufficiently volatile for trade entries. Here's a step-by-step guide:
Adjust the ATR Multiplier: Increase the ATR Multiplier to create a higher volatility threshold. A multiplier of 2.0 to 2.5 is a good starting point for very low-volatility markets.
Fine-Tune the ATR Periods: Consider lengthening the ATR calculation period if you find that the strategy is still entering trades in undesirable low-volatility conditions. A longer period provides a more averaged-out measure of volatility, which might better suit your needs.
Monitor and Adjust: Volatility is not static, and market conditions can change. Regularly review the performance of your strategy in the context of current market volatility and adjust the settings as necessary.
Backtest in Different Conditions: Before applying the strategy live, backtest it across different market conditions with your adjusted settings. This process helps ensure that your approach to filtering low-volatility conditions aligns with your trading objectives and risk tolerance.
By fine-tuning the volatility filter settings according to the specific characteristics of the market you're trading in, you can enhance the performance of this strategy
- The **Trailing Stop Loss** and **EMA Exit Conditions** provide two layers of exit strategies, focusing on capital preservation and profit maximization.
**Visualizations**
For clarity and ease of use, the strategy plots the three EMAs and, if enabled, the ATR threshold on the chart. These visual cues not only aid in decision-making but also help in understanding the market's current trend and volatility state.
**How to Use**
Traders can customize the EMA periods to fit their trading horizon, be it short, medium, or long-term trading. The volatility filter and exit options allow for further customization, making the strategy adaptable to different market conditions and personal risk tolerance levels.
By offering a blend of trend-following principles with advanced risk management features, this strategy aims to cater to a wide range of trading styles, from cautious to aggressive. Its strength lies in its flexibility, allowing traders to fine-tune settings to their specific needs, making it a potentially valuable tool in the arsenal of any trader looking for a disciplined approach to navigating the markets.
Tìm kiếm tập lệnh với "英国央行降息25个基点"
VWAP 8EMA Crossover Scalping IndicatorWhy?
Everybody, especially in Indian context, from 9:15 AM to 3:30 PM, wants to trade in BankNifty.
And even 15m is Too Big timeframe for The Great Indian Options buyers. Everyone knows how potentially BankNifty (& FinNifty on Tuesday and Sensex on Friday) can show dance within 15m.
So there always been an overarching longing among traders to have something in shorter timeframes. And this 5m timeframe, looks like a universally (sic) accepted Standard Timeframe for Indian Options traders.
So here is this.
What?
The time we are publishing this public indicator Indian market (Nifty) is in ATH at ~22200.
In any such super trending market it's always good to wait for a dip and then in suitable time, enter the trade in the direction of the larger trend. The reversal trading systems, in such a situation, proves to be ineffective.
Of course there are time when market is sideways and keeps on oscillating between +/2 standard deviation of the 20 SMA. In such a situation the reversal play works perfectly. But not so in such a trending market.
So the question comes up - after a dip what's the right point to enter.
Hence comes the importance of such a crossover based trading system.
In this indicator, it's a well-known technique (nothing originally from ours, it's taken from social media, exact one we forgot) to find out the 8EMA and VWAP crossover.
So we learned from social media, practice in our daily trading a bit, actuate it and now publishing it.
A few salient points
It does not make sense to jump into the trade just on the crossover (or crossunder).
So we added some more sugar to it, e.g. we check the color the candle. Also the next candle if crosses and closes above (or below) the breakout candle's high/low.
The polarity (color) of both the alert (breakout/breakdown) and confirmation candle to be same (green for crossover, red from crossunder).
Of course, it does provider BUY and SELL alerts separately.
These all we have found out doing backtesting and forward testing with 1/2 lots and saw this sort of approaches works.
Hence all of these are added to this script.
Nomenclature
Here green line is the 8EMA and the red line is the VWAP.
Also there is a black dotted line. That's 50 EMA. It's to show you the trend.
The recent trade is shown in the top right of the chart as green (for buy) or red (for sell) with SL and 1:1 target.
How to trade using this system?
This is roughly we have found the best possible use of this indicator.
Lets explain with a bullish BUY positive crossover (means 8EMA is crossing over the daily VWAP)
Keep timeframe as 5m
Check the direction/slope of the black dotted line (50 EMA). If it's upwards, only take bullish positions.
Open the chart which has the VWAP. (e.g. FinNifty spot or MidcapNifty spot does not have vwap). So in those cases Future is the way to go.
Wait for a breakout crossover and let the indicator gives a green, triangular UP arrow.
Draw a horizontal line to the close of that candle for next few (say 6 candles i.e. 30m) candles.
Wait for the price first to retest the 8EMA or even better the VWAP (or near to the 8EMA, VWAP)
Let the price moves and closes above the horizontal line drawn in the 4th step.
Take a bullish trade, keeping VWAP as the SL and 1:1 as the target.
Additionally, Options buyer can consult ADX also to see if the ADX is more than 25 and moving up for the bullish trade. (This has to be added seperately in the chart, it's not a part of the indicator).
Mention
The concept we have taken from some social media. Forget exactly where we heard this first time. We just coded it with some additional steps.
Statutory Disclaimer
There is no silver bullet / holy grail in trading. Nothing works 100% time. One has to be careful about the loss (s)he can bear in case of the trade goes against.
We, as the author of this script, is not responsible for any trading or position decision one is taken based on the outcome of this.
It is our sole discretion to change, add, delete the portion or withdraw the whole script without any prior notice or intimation.
In Indian Context: We are not SEBI registered.
RSI Volatility Bands [QuantraSystems]RSI Volatility Bands
Introduction
The RSI Volatility Bands indicator introduces a unique approach to market analysis by combining the traditional Relative Strength Index (RSI) with dynamic, volatility adjusted deviation bands. It is designed to provide a highly customizable method of trend analysis, enabling investors to analyze potential entry and exit points in a new and profound way.
The deviation bands are calculated and drawn in a manner which allows investors to view them as areas of dynamic support and resistance.
Legend
Upper and Lower Bands - A dynamic plot of the volatility-adjusted range around the current price.
Signals - Generated when the RSI volatility bands indicate a trend shift.
Case Study
The chart highlights the occurrence of false signals, emphasizing the need for caution when the bands are contracted and market volatility is low.
Juxtaposing this, during volatile market phases as shown, the indicator can effectively adapt to strong trends. This keeps an investor in a position even through a minor drawdown in order to exploit the entire price movement.
Recommended Settings
The RSI Volatility Bands are highly customisable and can be adapted to many assets with diverse behaviors.
The calibrations used in the above screenshots are as follows:
Source = close
RSI Length = 8
RSI Smoothing MA = DEMA
Bandwidth Type = DEMA
Bandwidth Length = 24
Bandwidth Smooth = 25
Methodology
The indicator first calculates the RSI of the price data, and applies a custom moving average.
The deviation bands are then calculated based upon the absolute difference between the RSI and its moving average - providing a unique volatility insight.
The deviation bands are then adjusted with another smoothing function, providing clear visuals of the RSI’s trend within a volatility-adjusted context.
rsiVal = ta.rsi(close, rsiLength)
rsiEma = ma(rsiMA, rsiVal, bandLength)
bandwidth = ma(bandMA, math.abs(rsiVal - rsiEma), bandLength)
upperBand = ma(bandMA, rsiEma + bandwidth, smooth)
lowerBand = ma(bandMA, rsiEma - bandwidth, smooth)
long = upperBand > 50 and not (lowerBand < lowerBand and lowerBand < 50)
short= not (upperBand > 50 and not (lowerBand < lowerBand and lowerBand < 50))
By dynamically adjusting to market conditions, the RSI trend bands offer a unique perspective on market trends, and reversal zones.
Clustered Asset Moving Average @shrilssThe Clustered Asset Moving Average script is designed to provide traders with a unique perspective on a cluster of multiple assets. By combining the closing prices and volumes of 12 specified assets, this indicator calculates a Clustered Moving Average to reveal potential trends and market sentiment within this asset cluster.
Key Features:
- Asset Cluster Analysis:
The script considers 12 assets, including well-known names such as Google (GOOG), Microsoft (MSFT), Apple (AAPL), Tesla (TSLA), and others.
It calculates the price and volume of each asset to form a comprehensive view of the asset cluster.
- Clustered Moving Average Calculation:
The Asset Price and Volume are combined to calculate the Clustered Moving Average
This moving average reflects the relationship between the aggregated price and volume of the specified assets.
- Multiple Exponential Moving Averages (EMA):
The script includes three EMAs (10, 25, and 100) applied to the Clustered Moving Average, providing different time perspectives.
Users can customize the visibility of each EMA based on their trading preferences.
- Visual Representation:
The indicator offers a visual representation of the Clustered Moving Average, allowing traders to quickly identify trends and potential reversal points.
Different EMAs are color-coded, enhancing visual clarity.
Ticker Screener by Volume Heatmap [SS]Fun little screener that creates a heatmap by daily volume trend.
The numbers expressed are the Sell to Buy ratio (Selling volume / buying volume). The % is the % change over the lookback period.
The default lookback period is 25 days, but you can adjust it as you see fit. The brightness of the green and red will change based on the extent of buying / selling.
Anything 1 or over means there is a lot of selling. A percent change in the negatives is good, it means that selling is decreasing and buying is increasing. Vice versa for a percent change in the positives.
It will accomodate up to 12 tickers, there are some pre-set but you can obviously customize it with your own tickers of interest.
And that's pretty much the indicator, pretty simple indicator but I hope you enjoy!
Safe trades everyone!
COT Index by NielsThe COT index is an indicator for determining trend reversals based on the net positions of commercials from the CFTC COT report.
A time frame of 26 weeks is selected as the basis. If the value is greater than or equal to 75, this is a bullish sign; if it is less than or equal to 25, this is a bearish sign.
You can select the number of weeks to be used for the calculation.
As the CFTC data is only published on Fridays at 21:30, the value of the current week is hidden until the market closes.
In addition, the background changes color when the index reaches an extreme range.
Both functions can be deactivated in the settings.
ADX and DI (Colored Candles Open-Source)The "ADX and DI (Colored Candles Open-Source)" indicator is a technical analysis tool used in trading. It utilizes the Average Directional Index (ADX) and the Directional Movement Indicators (+DI and -DI) to assess the strength and direction of a price trend. The ADX is calculated based on a 14-period lookback and is displayed as a histogram.
The color of the ADX histogram varies depending on the ADX value and the relative positions of +DI and -DI. Green and purple colors represent bullish and bearish trends respectively, with variations in shades indicating trend strength. Yellow and red colors indicate potential trend exhaustion for bullish and bearish trends, respectively, when ADX is above 50. Gray color is used when ADX is below 10, indicating a neutral trend.
Additionally, the script plots +DI and -DI lines with a fill between them to visually represent their crossover. Horizontal dotted lines are drawn at key ADX levels (0, 10, 25, 50) for reference. The candles on the chart are also colored to match the ADX histogram, providing a clear visual representation of the market trend.
RSI Market Regime FinderThe Relative Strength Index Market Regime
Imagine the RSI as a tool that helps you figure out if a stock or any other asset is overbought or oversold. It’s like trying to see if a party is too crowded or too empty.
The RSI measures the speed and change of price movements. When it’s high, like above 70, it suggests that the asset might be overbought. Think of it like everyone rushing in to buy the latest cool thing, and maybe it’s getting a bit too popular. On the flip side, if the RSI is low, below 30, it implies that the asset might be oversold. This is like when nobody wants to go to a party, and it might be a good time to check it out because things could pick up.
Now, why does this matter? Well, it gives you a hint about potential reversals in the market. If something is overbought, it might be time for a cool-down, and if it’s oversold, there might be a chance for a comeback. Traders often use RSI to get a sense of whether an asset is in a strong trend or if it’s about to change direction. So, in a nutshell, RSI is like a party meter for the market. It helps you gauge if things are getting too wild or if it’s a bit quiet, giving you a heads-up on potential changes in the market vibe.
Creating the Regime Detection Indicator
A market regime is essentially the prevailing state or condition of the financial markets at a given time. It’s like saying the market can have different modes or phases, just like a person can be happy, sad, or somewhere in between.
Now, these market regimes can be broadly categorized based on trends. Imagine a market in a strong upward trend — everyone’s feeling optimistic, prices are going up, and it’s like a bull (that’s the term for a rising market) is running around.
On the flip side, if the market is in a downtrend, it’s like a bear (that’s the term for a falling market) is dominating. People might be a bit more cautious, prices are dropping, and it’s generally a less optimistic atmosphere.
The tricky part is that markets aren’t always in a clear-cut bull or bear state. Sometimes they’re just moving sideways, not going up or down much. That’s another market regime, often called a “sideways” or “range-bound” market.
The conditions of the creation of the indicator follow these assumptions:
A bullish regime is taking place whenever the RSI is above 50 but below 75 while the last three RSI values were above 46.
A bearish regime is taking place whenever the RSI is below 50 but above 25 while the last three RSI values were below 54.
The script is super simple to use. Basically, whenever the green line is in progress, a bullish regime is taking place, and whenever the red line is in progress, a bearish regime is taking place.
Long strategies fit well within a bullish regime while short strategies fit well within a bearish regime.
All the credit for this script goes to Sofien Kaabar. He graciously provided the code and I'm passing along his work.
ADX Thrust Reversal & Trend
Created by Love Sharma, CMT, CFTe
the idea is simple. there needs to be thrust in prices before adx goes above any barrier or level say 25/10 or even 10/ The Di plus or Di minus should be above ADX. This indicates the change in direction or change in underlying price and obviously followed by ADX indicator which is dependent on user which level it exceed.
The ADX - Shows Trend Strength
The =/- Di show Thrust or reversal in prices.
it helps in entering the directional change in prices early rather than waiting for ADX
SentinelsSentinels is a playful variation on combining different mean averages (MA).
A cross of 2 user-defined MA's (MA 1 & MA 2) initiates the drawing of a sentinel with tentacles, which, on its turn can provide potential support/resistance or entry/stop-loss/take profit zones.
The type of each MA (MA 1, MA 2 and tentacles) can be chosen from following options:
SMA
EMA
SMMA (RMA)
HullMA
WMA
VWMA
DEMA
TEMA
🔹 Examples
Fast & slow MA: HullMA, Tentacles: TEMA
Fast & slow MA: SMA, Tentacles: WMA
Fast & slow MA: WMA, Tentacles: WMA
Fast & slow MA: TEMA, Tentacles: TEMA
🔶 DETAILS
🔹 Head-Body
The head-body is formed by:
the slow MA when there is a crossunder.
the fast MA when there is a crossover.
The color of the head-body is a gradient which can be set. The color of the tentacles (non-gradient) can be set as well.
The head-body of the sentinel will be visible for maximum 60 bars after a cross has occured.
🔹 Tentacles
The length of the 'Tentacles' is calculated by taking the difference between the length of MA 1 and MA 2 , and dividing this by 6 -> diff .
The length of each tentacle is MA 1 + a multiple of diff .
The tentacles will only begin to show from 2 bars after a cross.
Each tentacle will be shown maximum x bars after the cross:
Tentacle 1: 15 bars
Tentacle 2: 20 bars
Tentacle 3: 25 bars
Tentacle 4: 30 bars
Tentacle 5: 35 bars
Tentacle 6: 40 bars
🔹 Switch lengths
By switching lengths the colors get switched too.
Note that the tentacles act differently though.
In that way, this can be an extra option to visualize the tentacles .
🔶 Happy Holidays
Merry Christmas and a Happy New Year!
Logarithmic CVD [IkkeOmar]The LCVD is another Mean-Reversion Indicator. it doesn't detect trends and does not give a signal per se. However the logarithmic transformation is made to visualize the direction of the trend for the volume. This allows you to see if money is flowing in or out of an asset.
What it does is tell you if we have a flashcrash based on the difference in volume.
Think of this indicator like a form of a volatility index.
Smoothing input:
The only input is an input for the smoothing length of the logDelta.
Volume Calculation:
// @IkkeOmar
//@version=5
indicator('Logarithmic CVD', shorttitle='CVD', overlay=false)
smooth = input.int(defval = 25, title = "Smoothing Distance")
// Calculate buying and selling volume
askVolume = volume * (close > open ? 1 : 0) // Assuming higher close than open indicates buying
bidVolume = volume * (close < open ? 1 : 0) // Assuming lower close than open indicates selling
// Delta is the difference between buying and selling volume
delta = askVolume - bidVolume
// Apply logarithmic transformation to delta
// Adding a check to ensure delta is not zero as log(0) is undefined
logDelta = delta > 0 ? math.log(math.abs(delta)) * math.sign(delta) : - math.log(math.abs(delta)) * math.sign(delta)
// use the the ta lib for calculating the sma of the logDelta
smoothLogDelta = ta.sma(logDelta, smooth)
// Create candlestick plot
plot(logDelta, color= color.green, title='Logarithmic CVD')
plot(smoothLogDelta, color= color.rgb(145, 37, 1), title='Smooth CVD')
These lines calculate the buying and selling volumes. askVolume is calculated as the total volume when the closing price is higher than the opening price, assuming this indicates buying pressure. bidVolume is calculated as the total volume when the closing price is lower than the opening price, assuming selling pressure.
The Delta is simply the difference between buying and selling volumes.
Logarithmic Transformation:
logDelta = delta > 0 ? math.log(math.abs(delta)) * math.sign(delta) : - math.log(math.abs(delta)) * math.sign(delta)
Applies a logarithmic transformation to delta. The math.log function is used to calculate the natural logarithm of the absolute value of delta. The sign of delta is preserved to differentiate between positive and negative values. This transformation helps in scaling the delta values, especially useful when dealing with large numbers.
This script essentially provides a visual representation of the buying and selling pressures in a market, transformed logarithmically for better scaling and smoothed for trend analysis.
Hope it makes sense!
Stay safe everyone!
Don't hesitate to ask any questions if you have any!
EUR/USD 45 MIN Strategy - FinexBOTThis strategy uses three indicators:
RSI (Relative Strength Index) - It indicates if a stock is potentially overbought or oversold.
CCI (Commodity Channel Index) - It measures the current price level relative to an average price level over a certain period of time.
Williams %R - It is a momentum indicator that shows whether a stock is at the high or low end of its trading range.
Long (Buy) Trades Open:
When all three indicators suggest that the stock is oversold (RSI is below 25, CCI is below -130, and Williams %R is below -85), the strategy will open a buy position, assuming there is no current open trade.
Short (Sell) Trades Open:
When all three indicators suggest the stock is overbought (RSI is above 75, CCI is above 130, and Williams %R is above -15), the strategy will open a sell position, assuming there is no current open trade.
SL (Stop Loss) and TP (Take Profit):
SL (Stop Loss) is 0.45%.
TP (Take Profit) is 1.2%.
The strategy automatically sets these exit points as a percentage of the entry price for both long and short positions to manage risks and secure profits. You can easily adopt these inputs according to your strategy. However, default settings are recommended.
Ultimate Seasonality Indicator [SS]Hello everyone,
This is my seasonality indicator. I have been working on it for like 2 months, so hope you like it!
What it does?
The Ultimate Seasonality indicator is designed to provide you, the trader, an in-depth look at seasonality. The indicator gives you the ability to do the following functions:
View the most bearish and bullish months over a user defined amount of years back.
View the average daily change for each respective months over a user defined amount of years back.
See the most closely correlated month to the current month to give potential insights of likely trend.
Plot out areas of High and Low Seasonality.
Create a manual seasonal forecast model by selecting the desired month you would like to model the current month data after.
Have the indicator develop an autoregressive seasonal model based on seasonally lagged variables, using principles of machine learning.
I will go over these functions 1 by 1, its a whopper of an indicator so I will try to be as clear and concise as possible.
Viewing Bullish vs Bearish Months, Average Daily Change & Correlation to Current Month
The indicator will break down the average change, as well as the number of bullish and bearish days by month. See the image below as an example:
In the table to the right, you will see a breakdown of each month over the past 3 years.
In the first column, you will see the average daily change. A negative value, means it was a particularly bearish month, a positive value means it was a particularly bullish month.
The next column over shows the correlation to the current dataset. How this works is the indicator takes the size of the monthly data for each month, and compares it to the last X number of days up until the last trading day. It will then perform a correlation assessment to see how closely similar the past X number of trading days are to the various monthly data.
The last 2 columns break down the number of Bullish and Bearish days, so you can see how many red vs green candles happened in each respective month over your set timeframe. In the example above, it is over the pats 3 years.
Plot areas of High and Low Seasonality
In the chart above, you will see red and green highlighted zones.
Red represents areas of HIGH Seasonality .
Green represents areas of LOW Seasonality .
For this function, seasonality is measured by the autocorrelation function at various lags (12 lags). When there is an average autocorrelation of greater than 0.85 across all seasonal lags, it is considered likely the result of high seasonality/trend.
If the lag is less than or equal to 0.05, it is indicative of very low seasonality, as there is no predominate trend that can be found by the autocorrelation functions over the seasonally lagged variables.
Create Manual Seasonal Forecasts
If you find a month that has a particularly high correlation to the current month, you can have the indicator create a seasonal model from this month, and fit it onto the current dataset (past X days of trading).
If we look at the example below:
We can see that the most similar month to the current data is September. So, we can ask the indicator to create a seasonal forecast model from only September data and fit it to our current month. This is the result:
You will see, using September data, our most likely close price for this month is 450 and our model is y= 1.4305x + -171.67.
We can accept the 450 value but we can use the equation to model the data ourselves manually.
For example, say we have a target price on the month of 455 based on our own analysis. We can calculate the likely close price, should this target be reached, by substituting this target for x. So y = 1.4305x + -171.67 becomes
y = 1.4305(455) +- 171.67
y = 479.20
So the likely close price would be 479.20. No likely, and thus its not likely we are to see 455.
HOWEVER, in this current example, the model is far too statistically insignificant to be used. We can see the correlation is only 0.21 and the R squared is 0.04. Not a model you would want to use!
You want to see a correlation of at least 0.5 or higher and an R2 of 0.5 or higher.
We can improve the accuracy by reducing the number of years we look back. This is what happens when we reduce the lookback years to 1:
You can see reducing to 1 year gives December as the most similar month. However, our R2 value is still far too low to really rely on this data whole-heartedly. But it is a good reference point.
Automatic Autoregressive Model
So this is my first attempt at using some machine learning principles to guide statistical analysis.
In the main chart above, you will see the indicator making an autoregressive model of seasonally lagged variables. It does this in steps. The steps include:
1) Differencing the data over 12, seasonally lagged variables.
2) Determining stationarity using DF test.
3) Determining the highest, autocorrelated lags that fall within a significant stationary result.
4) Creating a quadratic model of the two identified lags that best represents a stationary model with a high autocorrelation.
What are seasonally lagged variables?
Seasonally lagged variables are variables that represent trading months. So a lag of 25 would be 1 month, 50, 2 months, 75, 3 months, etc.
When it displays this model, it will show us what the results of the t-statistic are for the DF test, whether the data is stationary, and the result of the autocorrelation assessment.
It will then display the model detail in the tip table, which includes the equation, the current lags being used, the R2 and the correlation value.
Concluding Remarks
That's the indicator in a nutshell!
Hope you like it!
One final thing, you MUST have your chart set to daily, otherwise you will get a runtime error. This can ONLY be used on the daily timeframe!
Feel free to leave your questions, comments and suggestions below.
Note:
My "ultimate" indicators are made to give the functionality of multiple indicators in one. If you like this one, you may like some of my others:
Ultimate P&L Indicator
Ultimate Customizable EMA/SMA
Thanks for checking out the indicator!
Double RSI 00 1.0This script creates a custom indicator, visualizes two RSI values (RSI1 and RSI2) on the chart and generates alerts based on different RSI-related conditions, which can be used for technical analysis and trading strategies. Users can customize the RSI parameters and alert levels according to their preferences.
It includes several input parameters that allow the user to customize the RSI calculations and overbought/oversold levels. These parameters include:
length_1: RSI1 Length (default: 7)
length_2: RSI2 Length (default: 12)
overbought_1: Overbought Signal level for RSI1 (default: 75)
oversold_1: Oversold Signal level for RSI1 (default: 25)
overbought_2: High Overbought Signal level for RSI1 (default: 85)
oversold_2: High Oversold Signal level for RSI1 (default: 15)
The script calculates two RSI values: rsi_1 and rsi_2, based on the high and low prices averaged (hl2) and the specified RSI lengths.
It plots these RSI values on the chart using different colors and line widths.
Several horizontal lines are drawn on the chart to represent key levels:
h0: 0 (Lower Band)
h1: 50 (Middle Band)
h2: 100 (Upper Band)
h3: The Oversold level (customizable)
h4: The Overbought level (customizable)
h5: The High Oversold level (customizable)
h6: The High Overbought level (customizable)
The script defines alert conditions for various signals, including overbought, oversold, high overbought, high oversold, long (crossover between RSI1 and RSI2), and short (crossunder between RSI1 and RSI2).
It sends alerts when these conditions are met, indicating potential trading signals.
Please note that this script is meant for educational purposes and should be used cautiously in a real trading environment. It's important to have a thorough understanding of technical analysis and risk management when using such indicators in actual trading.
Support and Resistance: Triangles [YinYangAlgorithms]Overview:
Triangles have always been known to be the strongest shape. Well, why wouldn’t that likewise apply to trading? This Indicator will create Upwards and Downwards Triangles which in turn create Support and Resistance locations. For example, we find 2 highs that meet the criteria (within deviation %, Minimum Distance and Lookback Distance). We calculate the distance between these two and create an Equilateral Triangle Downwards (You can adjust the % if you want more of an Isosceles Triangle). The midpoint (tip) of this triangle is the Support and the bottom (base) of it is the Resistance. The exact opposite applies for an Upwards Triangle.
The reason why Triangles may make for good Support and Resistance locations is the % 's used, much like the fibonacci, use ratios relevant in nature and everywhere in the world around us, so why not for trading too?
Tutorial:
If you look at the locations we’ve circled above, all of them exhibit strong rejections are predictive Support and Resistance locations plotted by the triangles created. There can only ever be 1 Upward and 1 Downward Triangle at a time, so when a new one is created, the Support and Resistance locations are moved.
If you scroll back far enough you’ll notice the Triangles disappear but their Support and Resistance locations are still plotted. This has to do with the fact you are allowed only so many Lines plotted and when a new Triangle is created, an old one will be removed. The Support and Resistance locations however will stay.
If we look at the example above, you can see the Support and Resistance locations the Triangles made here may have helped predict where the price would struggle to surpass.
By default the Look Back Distance is set to 50 and the Min Distance is 10 (settings used in all previous examples). However, you can modify these to make Triangles more ‘Rare’ and therefore the Support and Resistance locations change less. In the example above for Instance we left Look Back Distance to 50 but changed Min Distance from 10 to 25. This results in Support and Resistance locations that may hold better in the long term.
If we scroll back a bit, we can see the settings ‘Look Back Distance’ 50 and ‘Minimum Distance’ 25 had done a decent job at predicting the ATH resistance and many Support and Resistance locations around it. Keep in mind, previous results don’t mean future results, but Triangles may create ratios which apply well to trading.
We will conclude our Tutorial here. Hopefully you can see the benefit to the ratio Triangles make when predicting Support and Resistance locations.
Settings:
Show Triangles: If all you want to know is the Support and Resistance locations, there’s no need to draw the Triangles.
Triangle Zones: What types of triangles should we create our zones for? Options are Upward, Downward, Both, None.
Max Deviation Allowed: Maximum Deviation up or down from the last bars High/Low for potential to create a Triangle.
Lookback Distance: How far back we look to see for potential of a High/Low within Deviation range.
Min Distance: This is so triangles are spaced properly and not from 2 bars beside each other. Min distance allocated between 2 points to create a Triangle.
Bar Percent Increase: How much % multiplier do we apply for each bar spacing of the triangle. 0.005 creates a close to Equilateral Triangle, but other values like 0.004 and 0.006 seem to work well too.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Williams %R with EMA'sThe provided Pine Script code presents a comprehensive technical trading strategy on the TradingView platform, incorporating the Williams %R indicator, exponential moving averages (EMAs), and upper bands for enhanced decision-making. This strategy aims to help traders identify potential buy and sell signals based on various technical indicators, thereby facilitating more informed trading decisions.
The key components of this strategy are as follows:
**Williams %R Indicator:** The Williams %R, also known as the "Willy," is a momentum oscillator that measures overbought and oversold conditions. In this code, the Williams %R is calculated with a user-defined period (default 21) and smoothed using an exponential moving average (EMA).
**Exponential Moving Averages (EMAs):** Two EMAs are computed on the Williams %R values. The "Fast" EMA (default 8) responds quickly to price changes, while the "Slow" EMA (default 21) provides a smoother trend-following signal. Crossovers and divergences between these EMAs can indicate potential buy or sell opportunities.
**Candle Color Detection:** The code also tracks the color of candlesticks, distinguishing between green (bullish) and red (bearish) candles. This information is used in conjunction with other indicators to identify specific trading conditions.
**Additional Upper Bands:** The script introduces upper bands at various levels (-5, -10, -20, -25) to create zones for potential buy and sell signals. These bands are visually represented on the chart and can help traders gauge the strength of a trend.
**Alert Conditions:** The code includes several alert conditions that trigger notifications when specific events occur, such as %R crossing certain levels, candle color changes within predefined upper bands, and EMA crossovers.
**Background Highlighting:** The upper bands and the zero line are visually highlighted with different colors, making it easier for traders to identify critical price levels.
This code is valuable for traders seeking a versatile technical strategy that combines multiple indicators to improve trading decisions. By incorporating the Williams %R, EMAs, candlestick analysis, and upper bands, it offers a holistic approach to technical analysis. Traders can customize the parameters to align with their trading preferences and risk tolerance. The use of alerts ensures that traders are promptly notified of potential trade setups, allowing for timely execution and risk management. Overall, this code serves as a valuable tool for traders looking to make more informed decisions in the dynamic world of financial markets.
Fib TSIFib TSI = Fibonacci True Strength Index
The Fib TSI indicator uses Fibonacci numbers input for the True Strength Index moving averages. Then it is converted into a stochastic 0-100 scale.
The Fibonacci sequence is the series of numbers where each number is the sum of the two preceding numbers. 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610...
TSI uses moving averages of the underlying momentum of a financial instrument.
Stochastic is calculated by a formula of high and low over a length of time on a scale of 0-100.
How to use Fib TSI:
100 = overbought
0 = oversold
Rising = bullish
Falling = bearish
crossover 50 = bullish
crossunder 50 = bearish
The default input settings are:
2 = Stoch D smoothing
3 = TSI signal
TSI uses 2 moving averages compared with each other.
5 = TSI fastest
TSI uses 2 moving averages compared with each other.
Default value is 3/5.
color = white
8 = TSI fast
TSI uses 2 moving averages compared with each other.
Default value is 5/8.
color = blue
13 = TSI mid
TSI uses 2 moving averages compared with each other.
Default value is 8/13.
color = orange
21 = TSI slow
TSI uses 2 moving averages compared with each other.
Default value is 13/21.
color = purple
34 = TSI slowest
TSI uses 2 moving averages compared with each other.
Default value is 21/34.
color = yellow
55 = Stoch K length
All total / 5 = All TSI
color rising above 50 = bright green
color falling above 50 = mint green
color falling below 50 = bright red
color rising below 50 = pink
Up bullish reversal = green arrow up
bullish trend = green dots
Down bearish reversal = red arrow down
bearish trend = red dots
Horizontal lines:
100
75
50
25
0
2 different visual options example snapshot:
Bullish Divergence Short-term Long Trade FinderThis script is a Bullish divergence trade finder built to find small periods where Bitcoin will likely rise from. It looks for bullish divergence followed by a higher low as long as the hour RSI value is below the 40 mark, if then it will enter an long. It marks out Buy signals on the RSI if the value dips below 'RSI Bull Condition Minimum' (Default 40) on the current time frame in view. It also marks out Sell signals found when the RSI is above the 'RSI Bearish Condition Minimum' (Default 50). The sell signals are bearish divergence that has occurred recently on the RSI. When a long is in play it will sell if it finds bearish divergence or the time frame in view reaches RSI value higher than the 'RSI Sell Value'(Default 75). You can set your stop loss value with the 'Stop loss Percentage' (default 5).
Available inputs:
RSI Period: relative strength measurement length(Typically 14)
RSI Oversold Level: the bottom bar of the RSI (Typically 30)
RSI Overbought Level: the top bar of the RSI (Typically 70)
RSI Bearish Condition Minimum: The minimum value the script will use to look for a pivot high that starts the Bearish condition to Sell (Default 50)
RSI Bearish Condition Sell Min: the minimum value the script will accept a bearish condition (Default 60)
RSI Bull Condition Minimum: the minimum value it will consider a pivot low value in the RSI to find a divergence buy (Default 40)
Look Back this many candles: the amount of candles thee script will look back to find a low value in the RSI (Default 25)
RSI Sell Value: The RSI value of the exit condition for a long when value is reached (Default 75)
Stop loss Percentage: Percentage value for amount to lose (Default 5)
The formula to enter a long is stated below:
If price finds a lower low and there is a higher low found following a lower low and price has just made another dip and price closes lower than the last divergence and Relative strength index hour value is less than 40 enter a long.
The formula to exit a long is stated below:
If the value drops below the stop loss percentage OR (the RSI value is greater than the value of the parameter 'RSI Sell Value' or bearish divergence is found greater than the parameter 'RSI Bearish Condition Minimum' )
This script was built from much strategy testing on BTC but works with alts (occasionally) also. It is most successful to my knowledge using the 15 min and 7 min time frames with default values. Hope it helps! Follow for further possible updates to this script or other entry or exit strategies.
snapshot:
I only have a Pro trading view account so I cannot share a larger data set about this script because the buy signals happen pretty rarely. The most amount that I could find within a view for me was 40 trades within a viewable time. The suggested/default parameters that I have do not occur very often so it limits the data set. Adjustments can be made to the parameters so that trades can be entered more often. The scripts success is dependent on the values of the parameters set by the user. This script was written to be used for BTC/USD or BTC/USDT trading. I am unable to share a larger dataset without putting out results that are intended to fail or having a premium account so reaching the 100 trade minimum is not possible with my account.
Indian Market Sessions for BacktestingThis indicator is designed to increase the quality of your backtesting in the Indian Market.
NSE & BSE run from 9:15 am IST to 3:30 pm IST.
Naturally different times have different kinds of volatility.
On your chart you will find premarked -
Saffron - 9:15 am to 10:30 am - Opening Session - High Volatility Observed Historically
White - 10:35 am to 2:25 pm - Middle Session - Lower Volatility Observed Historically
Green - 2:30 pm to 3:30 pm - Closing Session - Medium to High Volatility Observed Historically
You will also find the start of each session marked with an arrow.
Feel free to change the times from the input settings and the color and visibility from the style settings.
_______________
Usage:
When you backtest any strategies, say moving average crossovers, also mark the sessions in your sheet which will help you further increase accuracy.
Feel free to drop your doubts in the comments.
The Z-score The Z-score, also known as the standard score, is a statistical measurement that describes a value's relationship to the mean of a group of values. It's measured in terms of standard deviations from the mean. If a Z-score is 0, it indicates that the data point's score is identical to the mean score. Z-scores may be positive or negative, with a positive value indicating the score is above the mean and a negative score indicating it is below the mean.
The concept of Z-score was introduced by statistician Carl Friedrich Gauss as part of his "method of the least squares," which was an important step in the development of the normal distribution and Z-score tables. It's a key concept in statistics and is used in various statistical tests.
In financial analysis, Z-scores are used to determine whether a data point is usual or unusual. You can think of it as a measure of how many standard deviations an element is from the mean. For instance, a Z-score of 1.0 would denote a value that is one standard deviation from the mean. Z-scores are also used to predict probabilities, with Z-scores having a distribution that is expected to be normal.
In trading, a Z-score is used to determine how often a trading system may produce a string of winners or losers. It can help a trader to understand whether the losses or profits they see are something that the system would most likely produce, or if it's a once in a blue moon situation. This helps traders make decisions about when to start or stop a system.
I just wanted to play a bit with the Z-score I guess.
Feel free to share your findings if you discover additional applications for this strategy or identify timeframes where it appears to perform more optimally.
How it works:
This strategy is based on a statistical concept called Z-score, which measures the number of standard deviations a data point is from the mean. In other words, it helps determine how unusual or usual a data point is.
In the context of this strategy, Z-score is applied to a 10-period EMA (Exponential Moving Average) of Heikin-Ashi candlestick close prices. The Z-score is calculated over a look-back period of 25 bars.
The EMA of the Z-score is then calculated over a 20-bar period, and the upper and lower thresholds (bounds for buy and sell signals) are defined using the 90th and 10th percentiles of this EMA score.
Long positions are taken when the Z-score crosses above the lower threshold or crosses above the mid-line (50th percentile). An additional long entry is made when the Z-score crosses above the highest value the EMA has been in the past 100 periods.
Short positions are initiated when the EMA crosses below the upper threshold, lower threshold or the highest value the EMA has been in the past 100 periods.
Positions are closed when opposing entry conditions are met, for example, a long position is closed when the short entry condition is true, and vice versa.
Set your desired start date for the strategy. This can be modified in the timestamp("YYYY MM DD") function at the top of the script.
MTF SuperTrends Nexus [DarkWaveAlgo]🧾 Description:
A nexus is a connection, link, or neuronal junction where signals and information are transmitted between different elements.
The MTF SuperTrends Nexus indicator serves as a nexus between MTF SuperTrends by facilitating the visualization of up to eight multi-timeframe SuperTrends, each with its own customizable timeframe, period, factor, and coloring customization. By combining these various SuperTrends, it helps you create a comprehensive view of MTF trend dynamics and cross-timeframe confluence according to the SuperTrend indicator.
It acts as a utility/control center that brings together multiple MTF SuperTrends and allows you to visualize the interactions between them with exceptional ease-of-use and customizability, helping to provide you with valuable insights into potential trend reversals, momentum shifts, and trading opportunities.
💡 Originality and Usefulness:
While there are other multi-timeframe SuperTrend indicators available, MTF SuperTrends Nexus' semi-transparent fills create a compounding opaqueness when SuperTrends from multiple timeframes coalesce - making visual assessment of cross-timeframe confluence extremely easy. We also believe it stands above the rest with its sheer quantity and quality of settings, features, and usability.
✔️ Re-Published to Avoid Misleading Values
This script has been re-published to ensure that it does not use `request.security()` calls using lookahead_on to access future data when referencing SuperTrend calculations from other timeframes. This decreases the likelihood that the indicator will provide deceiving values. This change has been made in accordance with the PineScript documentation: "Using barmerge.lookahead_on at timeframes higher than the chart's without offsetting the `expression` argument like in `close [ ]` will introduce future leak in scripts, as the function will then return the `close` price before it is actually known in the current context" and the Publishing Rule: "Do not use `request.security()` calls using lookahead to access future data". Historical and real-time values may differ when referencing timeframes other than the chart's.
💠 Features:
8 toggleable MTF SuperTrends with customizable timeframes, periods, and factors
Compounding filled areas for easy MTF SuperTrend confluence analysis
Aesthetic and flexible coloring and color theme styling options
End-of chart labels and options for ease-of-use and legibility
⚙️ Settings:
Use a Color Theme: When this setting is enabled, all manual 'Bullish and Bearish Colors' are overridden. All plots will use the colors from your selected Color Theme - excepting those plots set to use the 'Single Color' coloring method.
Color Theme: When 'Use a Color Theme' is enabled, this setting allows you to select the color theme you wish to use.
Fill SuperTrend Areas: When enabled, the area between any MTF SuperTrend and the price bars will be filled with semi-transparent coloring.
Hide SuperTrends on Timeframes Lower Than the Chart: When this setting is enabled, any MTF SuperTrend with a timeframe smaller than that of the chart the indicator is applied to will be hidden from view.
Enable: Show/hide a specific MTF SuperTrend.
Timeframe: Set the timeframe for a specific MTF SuperTrend.
Period: Set the lookback period for a specific MTF SuperTrend.
Factor: Set the multiplier factor used for a specific MTF SuperTrend's calculation.
Bullish Color: When 'Use a Color Theme' is disabled, this will set the 'bullish color' for this specific MTF SuperTrend.
Bearish Color: When 'Use a Color Theme' is disabled, this will set the 'bearish color' for this specific MTF SuperTrend.
Enable Label: When enabled, a label will show at the end of the chart displaying the timeframe, period, factor, and current price value of this specific MTF SuperTrend.
Size: Sets the font size of this specific MTF SuperTrend's label.
Label Offset (in Bars): Sets the distance from the latest bar, in bars, at which this specific MTF SuperTrend's label is displayed.
Show Label Line: When enabled, this specific MTF SuperTrend's label will be accommodated by a dashed line connecting it to its plot.
📈 Chart:
The chart shown in this original publication displays the 5 minute chart on BTCUSDT. Displayed on the chart are 6 MTF SuperTrends: the 5m 50-period/3-factor SuperTrend, 15m 50-period/3-factor SuperTrend, 30m 50-period/3-factor SuperTrend, 1h 50-period/3-factor SuperTrend, 4h 50-period/3-factor SuperTrend, and the 1D 25-period/1.5-factor SuperTrend - offering an exemplary view of how you can easily use these MTF SuperTrends to your advantage in analyzing SuperTrend relationships across multiple timeframes.
Scalp Tool
This script is primarily intended as a scalping tool.
The theory of the tool is based on the fact that the price always returns to its mean.
Elements used:
1. VWMA as a moving average. VWMA is calculated once based on source close and once based on source open.
2. the bands are not calculated like the Bollinger Band, but only a settlement is calculated for the lower bands based on the Lows and for the upper bands based on the Highs. Thus the bands do not become thicker or thinner, but remain in the same measure to the mean value above or below the price.
3. a volume filter on simple calculation of a MA with deviation. Therefore, it can be identified if a volume breakout has occurred.
4. support and resistance zones which are calculated based on the highs and lows over a certain length.
5. RSI to determine oversold and overbought zones. It also tries to capture the momentum by using a moving average (variable selectable) to filter the signals. The theory is that in an uptrend the RSI does not go below 50 and in a downtrend it does not go above 50.
However, this can be very different depending on the financial instrument.
Explanation of the signals:
The main signal in this indicator Serves for pure short-term trading and is generated purely on the basis of the bands and the RSI.
Only the first bands are taken into account.
Buy signal is generated when the price opens below the lower band 1 and closes above the lower band 1 or the RSI crosses a value of 25 from bottom to top.
Sell signal is generated when the price opens above the Upper Band 1 and closes below the Upper Band 1 or the RSI crosses a value of 75 from top to bottom.
The position should be closed when the price hits the opposite band. Alternatively, it can also be closed at the mean.
Other side signals:
1. breakouts:
The indicator includes 2 support and resistance zones, which differ only in length. For the breakout signals, the short version of the R/S is used. A signal is generated when the price breaks through the zones with increased volume. It is then assumed that the price will continue to follow the breakout.
The values of the S/R are adjustable and marked with "BK".
The value under Threshold 2 defines the volume breakout. 4 is considered as the highest value. The smaller the value, the smaller the volume must be during a breakout.
2. bounce
If the price hits a S/R (here the long variant is used with the designation "Support" or "Resistance") and makes a wick with small volume, the script assumes a bounce and generates a Sell or Buy signal accordingly.
The volume can be defined under "Threshold".
The S/R according to the designation as well.
Combined signals:
If the value of the S/R BK and the S/R is the same and the bounce logic of the S/R BK applies and an RSI signal is also generated, a signal is also plotted.
Here the idea was to get very strong signals for possible swing entries.
4. RSI Signals
The script contains two RSI.
RSI 1:
Bullish signal is generated when the set value is crossed from the bottom to the top.
Bearish signal is generated when the set value is crossed from the top to the bottom.
RSI 2:
Bullish signal is generated when the set value is crossed from the top to the bottom.
Bearish signal is generated when the set value is crossed from bottom to top.
For RSI 2 the theory is taken into account according to the description under Used elements point 5
Optical trend filter:
Also an optical trend filter was generated which fills the bands accordingly.
For this the VWMA is used and the two average values of the band.
Color definition:
Gray = Neutral
Red = Bearish
Green = Bullish
If the mean value is above the VWMA and the mean value based on the closing price is above the mean value based on the open price, the band is colored green. It is a bullish trend
If the mean value is below the VWMA and the mean value based on the closing price is below the mean value based on the open price, the band is colored red.
The band is colored gray if the mean value is correspondingly opposite. A sideways phase is assumed.
The script was developed on the basis of the pair BTCUSD in the 15 minute chart and the settings were defined accordingly on it. The display of S/R for forex pairs does not work correctly and should be hidden. The logic works anyway.
When using the script, all options should first be set accordingly to the asset and tested before trading afterwards. It applies of course also here that there is no 100% guarantee.
Also, a strong breakout leads to false signals and overheating of the indicator.
P/E RatioPlots the P/E Ratio with highest, lowest and average, as well as two ranges, 25-20 & 20-0 considered as the regular P/E Range
