Price and Volume Stochastic Divergence [MW]Introduction
This indicator creates signals of interest for entering and exiting long and short positions on equities. It primarily uses up and down trends defined by the change in cumulative volume with some filtering provided by a short period exponential moving average (9 EMA by default).
Settings
Moving Average Period : The moving average over which the cumulative volume delta is calculated. Default: 14
Short Period EMA : The EMA used to represent price action, and is used to generate the EMA Delta line. Default: 27 (3*3*3)
Long Period EMA : The second EMA used to calculate the EMA Delta line. Default: 108 (2*2*3*3*3)
Stochastic K Value : The value used for stochastic curve smoothing. Default: 3
Dot Size : The diameter of the larger indicator. Default: 10
Dot Transparency : The transparency level of the outer ring of the primary BUY/SELL signal. Default: 50 (0 is opaque, 100 is transparent)
Band Distance from 0 to 100 : The upper and lower band distance. Default: 20
Calculations
The cumulative volume delta (CVD) is calculated using candle bodies and wicks. For a red candle, buying volume is calculated by multiplying the volume by the spread percentage of the average of the top and bottom wicks, while Selling Volume is calculated multiplying the volume by the spread percentage of the average of the top and bottom wicks - in addition to the spread percentage of the candle body.
For a green candle, buying volume is calculated by multiplying the volume by the spread percentage of the average of the top and bottom wicks - plus the spread percentage of the candle body - while Selling Volume is calculated using only the spread percentage average of the top and bottom wicks.
Once we have the CVD, we can then perform a stochastic calculation of the CVD value.
stochastic calculation = (current value - lowest value in period) / (highest value in period - lowest value in period)
We’ll do the same stochastic calculation for the short term EMA (27 EMA default) as well as for the difference between the short term and long term EMA.
When the stochastic CVD value is rising from zero and the short term EMA stochastic value equals 100, then it’s a major bullish signal. When the stochastic CVD value is falling from 100 and the short term EMA stochastic value equals 0, then it’s a major bearish signal.
Sometimes, after a bullish or bearish signal, the stochastic CVD will reverse direction triggering a new opposing signal.
How to Interpret
The CVD indicates when there is either more buying than selling or vice versa. A value over 50 for the stochastic CVD curve represents more buying taking place. A value below 50 represents more selling. One might intuitively believe that when there is more buying volume than selling volume that the price would follow suit. This is not always the case.
Most of the time buying volume will precede consistent price movement upwards, and selling volume will precede consistent price movement downwards. When this divergence occurs, the indicator generates a signal. When this divergence begins to fail, and buying or selling volume reverses, then another signal is generated indicating that the buying/selling impulse is headed back into the direction of price action.
These interactions are visually represented on the chart with the coral line that represents CVD, and the yellow line that represents the EMA, or the average price. When the coral line goes up and the yellow line stays down, that’s the BUY signal. When the coral line goes down and the yellow line stays up, that’s the sell signal. When the coral line switches direction, the chart generates another signal showing that volume is moving in a direction that supports the price.
The orange line represents the stochastic representation of the difference between the short EMA (27 by default) and the long EMA (108 by default). EMA differences is a method that can be used to define a trend. When a short term EMA is above a longer term EMA, that may represent a bullish trend. When it is below, that may represent a bearish trend. When all 3 lines are rising or falling in the same direction at the same time, it tends to indicate a movement that has the potential to continue.
Other Usage Notes and Limitations
It's important for traders to be aware of the limitations of any indicator and to use them as part of a broader, well-rounded trading strategy that includes risk management, fundamental analysis, and other tools that can help with reducing false signals, determining trend direction, and providing additional confirmation for a trade decision. Diversifying strategies and not relying solely on one type of indicator or analysis can help mitigate some of these risks.
This indicator can be paired with the MW Volume Impulse indicator if it is desired to see the actual buying and selling cumulative volume deltas. Also, in many cases, the BUY and SELL signals tend to correspond with Keltner Bands (ATR Bands) becoming extended. Lastly, volume weighted average price (VWAP) along with other macro events can impact price and negate signals. To view VWAP lines, you may choose to use the Multi VWAP or Multi VWAP for Gaps indicator to help ensure that the signals you see in this indicator are not being affected by VWAP lines.
Cerca negli script per "科创50成分股"
Kshitij Malve - Minervini Trend Criteria (MTC)Purpose:
This indicator is designed to assist traders in identifying stocks that potentially meet the bullish Stage 2 trend criteria outlined by renowned stock trader Mark Minervini. It analyzes price movement in relation to moving averages and calculates certain price thresholds to provide visual signals.
Key Features:
Minervini Stage 2 Focus: Specifically targets trend characteristics highlighted in Minervini's trading methodology.
Adjustable Moving Averages: The script includes inputs for 150-day, 200-day, and 50-day moving average lengths, allowing users to customize their analysis.
Visual Trend Criteria: Each core Stage 2 trend condition is plotted below the chart as green or red dots for quick visual assessment.
Stage 2 Uptrend Signal: When all key trend conditions are met, a purple up-arrow appears beneath the price chart.
Alerts: Customizable alerts can be set up to notify the user when all conditions are met, signaling a potential Stage 2 uptrend.
Conditions Evaluated:
Price Position: Current price is above the 50-day, 150-day, and 200-day simple moving averages.
Moving Average Alignment: 50-day MA is above the 150-day MA, which is above the 200-day MA.
Uptrending 200-day MA: The 200-day MA is demonstrating an upward trend over the specified period.
30% Above 52-Week Low: Current price is at least 30% higher than the 52-week low.
Within 25% of 52-Week High: Current price is no more than 25% below the 52-week high.
Important Notes:
This indicator does not directly plot lines for conditions 4 and 5 (52-week high/low comparisons). Consider incorporating these into your chart in some way for full technical analysis in line with the Minervini method.
For additional depth, study Mark Minervini's books to fully understand the context and strategies built around these criteria.
How to Use:
Add the "Kshitij Malve - Minervini Trend Criteria" indicator to a stock chart.
Observe the placement of colored dots below the chart. A series of green dots suggests the stock is within Minervini's Stage 2 criteria.
Look for the purple up-arrow signal for confirmation that all conditions are met.
Customize alerts if you would like real-time signals of potential Stage 2 uptrends.
Moving Average Dispersion Index w/ Z-Score (Adjusted MADI-Z)Overview
The Adjusted MADI-Z indicator is a custom indicator that looks to decipher trends and consolidations based on the clustering and dispersion of Moving Averages. It calculates a z-score based on the dispersion of various exponentially weighted moving averages to identify trends and consolidation. The z-score is then adjusted using a logistic function to map it between 0-100.
How can it be used?
- Identify trends and consolidation - Values above 80 indicate a strong trend while values below 20 show consolidation
- Gauge trend strength - Higher positive values suggest a stronger uptrend while lower negative values indicate a stronger downtrend
- Generate trading signals - Crossovers of key levels can act as entry/exit triggers
- Smooth noise in price action - The adjusted z-score filters out market noise
Default Values
- ma5_len = 5
- ma10_len = 10
- ma50_len = 50
- ma200_len = 200
- lookback_period = 100
Strategies
The Adjusted MADI-Z can be used for trend-following strategies across various timeframes. Specific strategies include:
- Trend trading - Enter long on crossover above 80, exit on crossover below 80. Reverse for short trades.
- Range trading - Enter short on crossover below 20, exit on crossover above 20. Reverse for long trades.
- Identifying pullbacks - Temporary moves below 80 during uptrends and above 20 during downtrends can act as retracement entry points.
Rationale
By adjusting the z-score output of the standard MADI using a logistic function, the indicator becomes bounded and easier to interpret for trading purposes. The customized moving average lengths also allow tuning the indicator to particular assets and timeframes.
Interpretation
- Above 80 - Strong uptrend
- 70 to 80 - Moderate uptrend
- 50 to 70 - Weak uptrend
- 30 to 50 - Range-bound consolidation
- 20 to 30 - Weak downtrend
- Below 20 - Strong downtrend
Values below 15 or above 85 represent extremes outside two standard deviations.
Leveraged Share Decay Tracker [SS]Releasing this utility tool for leveraged share traders and investors.
It is very difficult to track the amount of decay and efficiency that is associated with leveraged shares and since not all leveraged shares are created equally, I developed this tool to help investors/traders ascertain:
1. The general risk, in $$, per share associated with investing in a particular leveraged ETF
2. The ability of a leveraged share to match what it purports to do (i.e. if it is a 3X Bull share, is it actually returning consistently 3X the underlying or is there a large variance?)
3. The general decay at various timepoints expressed in $$$
How to use:
You need to be opened on the chart of the underlying. In the example above, the chart is on DIA, the leveraged share being tracked is UDOW (3X bull share of the DOW).
Once you are on the chart of the underlying, you then put in the leveraged share of interest. The indicator will perform two major assessments:
1. An analysis of the standard error between the underlying and the leveraged share. This is accomplished through linear regression, but instead of creating a linreg equation, it simply uses the results to ascertain the degree of error associated at various time points (the time points are 10, 20, 30, 40, 50, 100, 252).
2. An analysis of the variance of returns. The indicator requires you to put in the leverage amount. So if the leverage amount is 3% (i.e. SPXL or UPRO is 3 X SPY), be sure that you are putting that factor in the settings. It will then modify the underlying to match the leverage amount, and perform an assessment of variance over 10, 20, 30, 40, 50, 100, 252 days to ensure stability. This will verify whether the leveraged ETF is actually consistently performing how it purports to perform.
Here are some examples, and some tales of caution so you can see, for yourself, how not all leveraged shares are created equal.
SPY and SPXL:
SPY and UPRO:
XBI and LABU (3 x bull share):
XBI and LABD (3 x bear share):
SOX and SOXL:
AAPL and AAPU:
It is VERY pivotal you remember to check and adjust the Leveraged % factor.
For example, AAPU is leveraged 1.5%. You can see above it tracks this well. However, if you accidently leave it at 3%, you will get an erroneous result:
You can also see how some can fail to track the quoted leveraged amount, but still produce relatively lower risk decay.
And, as a final example, let's take a look at the worst leveraged share of life, BOIL:
Trainwreck that one. Stay far away from it!
The chart:
The chart will show you the drift (money value over time) and the variance (% variance between the expected and actual returns) over time. From here, you can ascertain the general length you feel comfortable holding a leveraged share. In general, for most stable shares, <= 50 trading days tends to be the sweet spot, but always check the chart.
There are also options to plot the variances and the drifts so you can see them visually.
And that is the indicator! Kind of boring, but there are absolutely 0 resources out there for doing this job, so hopefully you see the use for it!
Safe trades everyone!
Session Breakout Scalper Trading BotHi Traders !
Introduction:
I have recently been exploring the world of automated algorithmic trading (as I prefer more objective trading strategies over subjective technical analysis (TA)) and would like to share one of my automation compatible (PineConnecter compatible) scripts “Session Breakout Scalper”.
The strategy is really simple and is based on time conditional breakouts although has more ”relatively” advanced optional features such as the regime indicators (Regime Filters) that attempt to filter out noise by adding more confluence states and the ATR multiple SL that takes into account volatility to mitigate the down side risk of the trade.
What is Algorthmic Trading:
Firstly what is algorithmic trading? Algorithmic trading also known as algo-trading, is a method of using computer programs (in this case pine script) to execute trades based on predetermined rules and instructions (this trading strategy). It's like having a robot trader who follows a strict set of commands to buy and sell assets automatically, without any human intervention.
Important Note:
For Algorithmic trading the strategy will require you having an essential TV subscription at the minimum (so that you can set alerts) plus a PineConnecter subscription (scroll down to the .”How does the strategy send signals” headings to read more)
The Strategy Explained:
Is the Time input true ? (this can be changed by toggling times under the “TRADE MEDIAN TIMES” group for user inputs).
Given the above is true the strategy waits x bars after the session and then calculates the highest high (HH) to lowest low (LL) range. For this box to form, the user defined amount of bars must print after the session. The box is symmetrical meaning the HH and LL are calculated over a lookback that is equal to the sum of user defined bars before and after the session (+ 1).
The Strategy then simultaneously defines the HH as the buy level (green line) and the LL as the sell level (red line). note the strategy will set stop orders at these levels respectively.
Enter a buy if price action crosses above the HH, and then cancel the sell order type (The opposite is true for a stop order).
If the momentum based regime filters are true the strategy will check for the regime / regimes to be true, if the regime if false the strategy will exit the current trade, as the regime filter has predicted a slowing / reversal of momentum.
The image below shows the strategy executing these trading rules ( Regime filters, "Trades on chart", "Signal & Label" and "Quantity" have been omitted. "Strategy label plots" has been switched to true)
Other Strategy Rules:
If a new session (time session which is user defined) is true (blue vertical line) and the strategy is currently still in a trade it will exit that trade immediately.
It is possible to also set a range of percentage gain per day that the strategy will try to acquire, if at any point the strategy’s profit is within the percentage range then the position / trade will be exited immediately (This can be changed in the “PERCENT DAY GAIN” group for user inputs)
Stops and Targets:
The strategy has either static (fixed) or variable SL options. TP however is only static. The “STRAT TP & TP” group of user inputs is responsible for the SL and TP values (quoted in pips). Note once the ATR stop is set to true the SL values in the above group no longer have any affect on the SL as expected.
What are the Regime Filters:
The Larry Williams Large Trade Index (LWLTI): The Larry Williams Large Trade Index (LWTI) is a momentum-based technical indicator developed by iconic trader Larry Williams. It identifies potential entries and exits for trades by gauging market sentiment, particularly the buying and selling pressure from large market players. Here's a breakdown of the LWTI:
LWLTI components and their interpretation:
Oscillator: It oscillates between 0 and 100, with 50 acting as the neutral line.
Sentiment Meter: Values above 75 suggest a bearish market dominated by large selling, while readings below 25 indicate a bullish market with strong buying from large players.
Trend Confirmation: Crossing above 75 during an uptrend and below 25 during a downtrend confirms the trend's continuation.
The Andean Oscillator (AO) : The Andean Oscillator is a trend and momentum based indicator designed to measure the degree of variations within individual uptrends and downtrends in the prices.
Regime Filter States:
In trading, a regime filter is a tool used to identify the current state or "regime" of the market.
These Regime filters are integrated within the trading strategy to attempt to lower risk (equity volatility and/or draw down). The regime filters have different states for each market order type (buy and sell). When the regime filters are set to true, if these regime states fail to be true the trade is exited immediately.
For Buy Trades:
LWLTI positive momentum state: Quotient of the lagged trailing difference and the ATR > 50
AO positive momentum state: Bull line > Bear line (signal line is omitted)
For Sell Trades:
LWLTI negative momentum stat: Quotient of the lagged trailing difference and the ATR < 50
AO negative momentum state: Bull line < Bear line (signal line is omitted)
How does the Strategy Send Signals:
The strategy triggers a TV alert (you will neet to set a alert first), TV then sends a HTTP request to the automation software (PineConnecter) which receives the request and then communicates to an MT4/5 EA to automate the trading strategy.
For the strategy to send signals you must have the following
At least a TV essential subscription
This Script added to your chart
A PineConnecter account, which is paid and not free. This will provide you with the expert advisor that executes trades based on these strategies signals.
For more detailed information on the automation process I would recommend you read the PineConnecter documentation and FAQ page.
Dashboard:
This Dashboard (top right by defualt) lists some simple trading statistics and also shows when a trade is live.
Important Notice:
- USE THIS STRATEGY AT YOUR OWN RISK AND ALWAYS DO YOUR OWN RESEARCH & MANUAL BACKTESTING !
- THE STRATEGY WILL NOT EXHIBIT THE BACKTEST PERFORMANCE SEEN BELOW IN ALL MARKETS !
Advanced Dynamic Threshold RSI [Elysian_Mind]Advanced Dynamic Threshold RSI Indicator
Overview
The Advanced Dynamic Threshold RSI Indicator is a powerful tool designed for traders seeking a unique approach to RSI-based signals. This indicator combines traditional RSI analysis with dynamic threshold calculation and optional Bollinger Bands to generate weighted buy and sell signals.
Features
Dynamic Thresholds: The indicator calculates dynamic thresholds based on market volatility, providing more adaptive signal generation.
Performance Analysis: Users can evaluate recent price performance to further refine signals. The script calculates the percentage change over a specified lookback period.
Bollinger Bands Integration: Optional integration of Bollinger Bands for additional confirmation and visualization of potential overbought or oversold conditions.
Customizable Settings: Traders can easily customize key parameters, including RSI length, SMA length, lookback bars, threshold multiplier, and Bollinger Bands parameters.
Weighted Signals: The script introduces a unique weighting mechanism for signals, reducing false positives and improving overall reliability.
Underlying Calculations and Methods
1. Dynamic Threshold Calculation:
The heart of the Advanced Dynamic Threshold RSI Indicator lies in its ability to dynamically calculate thresholds based on multiple timeframes. Let's delve into the technical details:
RSI Calculation:
For each specified timeframe (1-hour, 4-hour, 1-day, 1-week), the Relative Strength Index (RSI) is calculated using the standard 14-period formula.
SMA of RSI:
The Simple Moving Average (SMA) is applied to each RSI, resulting in the smoothing of RSI values. This smoothed RSI becomes the basis for dynamic threshold calculations.
Dynamic Adjustment:
The dynamically adjusted threshold for each timeframe is computed by adding a constant value (5 in this case) to the respective SMA of RSI. This dynamic adjustment ensures that the threshold reflects changing market conditions.
2. Weighted Signal System:
To enhance the precision of buy and sell signals, the script introduces a weighted signal system. Here's how it works technically:
Signal Weighting:
The script assigns weights to buy and sell signals based on the crossover and crossunder events between RSI and the dynamically adjusted thresholds. If a crossover event occurs, the weight is set to 2; otherwise, it remains at 1.
Signal Combination:
The weighted buy and sell signals from different timeframes are combined using logical operations. A buy signal is generated if the product of weights from all timeframes is equal to 2, indicating alignment across timeframe.
3. Experimental Enhancements:
The Advanced Dynamic Threshold RSI Indicator incorporates experimental features for educational exploration. While not intended as proven strategies, these features aim to offer users a glimpse into unconventional analysis. Some of these features include Performance Calculation, Volatility Calculation, Dynamic Threshold Calculation Using Volatility, Bollinger Bands Module, Weighted Signal System Incorporating New Features.
3.1 Performance Calculation:
The script calculates the percentage change in the price over a specified lookback period (variable lookbackBars). This provides a measure of recent performance.
pctChange(src, length) =>
change = src - src
pctChange = (change / src ) * 100
recentPerformance1H = pctChange(close, lookbackBars)
recentPerformance4H = pctChange(request.security(syminfo.tickerid, "240", close), lookbackBars)
recentPerformance1D = pctChange(request.security(syminfo.tickerid, "1D", close), lookbackBars)
3.2 Volatility Calculation:
The script computes the standard deviation of the closing price to measure volatility.
volatility1H = ta.stdev(close, 20)
volatility4H = ta.stdev(request.security(syminfo.tickerid, "240", close), 20)
volatility1D = ta.stdev(request.security(syminfo.tickerid, "1D", close), 20)
3.3 Dynamic Threshold Calculation Using Volatility:
The dynamic thresholds for RSI are calculated by adding a multiplier of volatility to 50.
dynamicThreshold1H = 50 + thresholdMultiplier * volatility1H
dynamicThreshold4H = 50 + thresholdMultiplier * volatility4H
dynamicThreshold1D = 50 + thresholdMultiplier * volatility1D
3.4 Bollinger Bands Module:
An additional module for Bollinger Bands is introduced, providing an option to enable or disable it.
// Additional Module: Bollinger Bands
bbLength = input(20, title="Bollinger Bands Length")
bbMultiplier = input(2.0, title="Bollinger Bands Multiplier")
upperBand = ta.sma(close, bbLength) + bbMultiplier * ta.stdev(close, bbLength)
lowerBand = ta.sma(close, bbLength) - bbMultiplier * ta.stdev(close, bbLength)
3.5 Weighted Signal System Incorporating New Features:
Buy and sell signals are generated based on the dynamic threshold, recent performance, and Bollinger Bands.
weightedBuySignal = rsi1H > dynamicThreshold1H and rsi4H > dynamicThreshold4H and rsi1D > dynamicThreshold1D and crossOver1H
weightedSellSignal = rsi1H < dynamicThreshold1H and rsi4H < dynamicThreshold4H and rsi1D < dynamicThreshold1D and crossUnder1H
These features collectively aim to provide users with a more comprehensive view of market dynamics by incorporating recent performance and volatility considerations into the RSI analysis. Users can experiment with these features to explore their impact on signal accuracy and overall indicator performance.
Indicator Placement for Enhanced Visibility
Overview
The design choice to position the "Advanced Dynamic Threshold RSI" indicator both on the main chart and beneath it has been carefully considered to address specific challenges related to visibility and scaling, providing users with an improved analytical experience.
Challenges Faced
1. Differing Scaling of RSI Results:
RSI values for different timeframes (1-hour, 4-hour, and 1-day) often exhibit different scales, especially in markets like gold.
Attempting to display these RSIs on the same chart can lead to visibility issues, as the scaling differences may cause certain RSI lines to appear compressed or nearly invisible.
2. Candlestick Visibility vs. RSI Scaling:
Balancing the visibility of candlestick patterns with that of RSI values posed a unique challenge.
A single pane for both candlesticks and RSIs may compromise the clarity of either, particularly when dealing with assets that exhibit distinct volatility patterns.
Design Solution
Placing the buy/sell signals above/below the candles helps to maintain a clear association between the signals and price movements.
By allocating RSIs beneath the main chart, users can better distinguish and analyze the RSI values without interference from candlestick scaling.
Doubling the scaling of the 1-hour RSI (displayed in blue) addresses visibility concerns and ensures that it remains discernible even when compared to the other two RSIs: 4-hour RSI (orange) and 1-day RSI (green).
Bollinger Bands Module is optional, but is turned on as default. When the module is turned on, the users can see the upper Bollinger Band (green) and lower Bollinger Band (red) on the main chart to gain more insight into price actions of the candles.
User Flexibility
This dual-placement approach offers users the flexibility to choose their preferred visualization:
The main chart provides a comprehensive view of buy/sell signals in relation to candlestick patterns.
The area beneath the chart accommodates a detailed examination of RSI values, each in its own timeframe, without compromising visibility.
The chosen design optimizes visibility and usability, addressing the unique challenges posed by differing RSI scales and ensuring users can make informed decisions based on both price action and RSI dynamics.
Usage
Installation
To ensure you receive updates and enhancements seamlessly, follow these steps:
Open the TradingView platform.
Navigate to the "Indicators" tab in the top menu.
Click on "Community Scripts" and search for "Advanced Dynamic Threshold RSI Indicator."
Select the indicator from the search results and click on it to add to your chart.
This ensures that any future updates to the indicator can be easily applied, keeping you up-to-date with the latest features and improvements.
Review Code
Open TradingView and navigate to the Pine Editor.
Copy the provided script.
Paste the script into the Pine Editor.
Click "Add to Chart."
Configuration
The indicator offers several customizable settings:
RSI Length: Defines the length of the RSI calculation.
SMA Length: Sets the length of the SMA applied to the RSI.
Lookback Bars: Determines the number of bars used for recent performance analysis.
Threshold Multiplier: Adjusts the multiplier for dynamic threshold calculation.
Enable Bollinger Bands: Allows users to enable or disable Bollinger Bands integration.
Interpreting Signals
Buy Signal: Generated when RSI values are above dynamic thresholds and a crossover occurs.
Sell Signal: Generated when RSI values are below dynamic thresholds and a crossunder occurs.
Additional Information
The indicator plots scaled RSI lines for 1-hour, 4-hour, and 1-day timeframes.
Users can experiment with additional modules, such as machine-learning simulation, dynamic real-life improvements, or experimental signal filtering, depending on personal preferences.
Conclusion
The Advanced Dynamic Threshold RSI Indicator provides traders with a sophisticated tool for RSI-based analysis, offering a unique combination of dynamic thresholds, performance analysis, and optional Bollinger Bands integration. Traders can customize settings and experiment with additional modules to tailor the indicator to their trading strategy.
Disclaimer: Use of the Advanced Dynamic Threshold RSI Indicator
The Advanced Dynamic Threshold RSI Indicator is provided for educational and experimental purposes only. The indicator is not intended to be used as financial or investment advice. Trading and investing in financial markets involve risk, and past performance is not indicative of future results.
The creator of this indicator is not a financial advisor, and the use of this indicator does not guarantee profitability or specific trading outcomes. Users are encouraged to conduct their own research and analysis and, if necessary, consult with a qualified financial professional before making any investment decisions.
It is important to recognize that all trading involves risk, and users should only trade with capital that they can afford to lose. The Advanced Dynamic Threshold RSI Indicator is an experimental tool that may not be suitable for all individuals, and its effectiveness may vary under different market conditions.
By using this indicator, you acknowledge that you are doing so at your own risk and discretion. The creator of this indicator shall not be held responsible for any financial losses or damages incurred as a result of using the indicator.
Kind regards,
Ely
Supertrend Advance Pullback StrategyHandbook for the Supertrend Advance Strategy
1. Introduction
Purpose of the Handbook:
The main purpose of this handbook is to serve as a comprehensive guide for traders and investors who are looking to explore and harness the potential of the Supertrend Advance Strategy. In the rapidly changing financial market, having the right tools and strategies at one's disposal is crucial. Whether you're a beginner hoping to dive into the world of trading or a seasoned investor aiming to optimize and diversify your portfolio, this handbook offers the insights and methodologies you need. By the end of this guide, readers should have a clear understanding of how the Supertrend Advance Strategy works, its benefits, potential pitfalls, and practical application in various trading scenarios.
Overview of the Supertrend Advance Pullback Strategy:
At its core, the Supertrend Advance Strategy is an evolution of the popular Supertrend Indicator. Designed to generate buy and sell signals in trending markets, the Supertrend Indicator has been a favorite tool for many traders around the world. The Advance Strategy, however, builds upon this foundation by introducing enhanced mechanisms, filters, and methodologies to increase precision and reduce false signals.
1. Basic Concept:
The Supertrend Advance Strategy relies on a combination of price action and volatility to determine the potential trend direction. By assessing the average true range (ATR) in conjunction with specific price points, this strategy aims to highlight the potential starting and ending points of market trends.
2. Methodology:
Unlike the traditional Supertrend Indicator, which primarily focuses on closing prices and ATR, the Advance Strategy integrates other critical market variables, such as volume, momentum oscillators, and perhaps even fundamental data, to validate its signals. This multidimensional approach ensures that the generated signals are more reliable and are less prone to market noise.
3. Benefits:
One of the main benefits of the Supertrend Advance Strategy is its ability to filter out false breakouts and minor price fluctuations, which can often lead to premature exits or entries in the market. By waiting for a confluence of factors to align, traders using this advanced strategy can increase their chances of entering or exiting trades at optimal points.
4. Practical Applications:
The Supertrend Advance Strategy can be applied across various timeframes, from intraday trading to swing trading and even long-term investment scenarios. Furthermore, its flexible nature allows it to be tailored to different asset classes, be it stocks, commodities, forex, or cryptocurrencies.
In the subsequent sections of this handbook, we will delve deeper into the intricacies of this strategy, offering step-by-step guidelines on its application, case studies, and tips for maximizing its efficacy in the volatile world of trading.
As you journey through this handbook, we encourage you to approach the Supertrend Advance Strategy with an open mind, testing and tweaking it as per your personal trading style and risk appetite. The ultimate goal is not just to provide you with a new tool but to empower you with a holistic strategy that can enhance your trading endeavors.
2. Getting Started
Navigating the financial markets can be a daunting task without the right tools. This section is dedicated to helping you set up the Supertrend Advance Strategy on one of the most popular charting platforms, TradingView. By following the steps below, you'll be able to integrate this strategy into your charts and start leveraging its insights in no time.
Setting up on TradingView:
TradingView is a web-based platform that offers a wide range of charting tools, social networking, and market data. Before you can apply the Supertrend Advance Strategy, you'll first need a TradingView account. If you haven't set one up yet, here's how:
1. Account Creation:
• Visit TradingView's official website.
• Click on the "Join for free" or "Sign up" button.
• Follow the registration process, providing the necessary details and setting up your login credentials.
2. Navigating the Dashboard:
• Once logged in, you'll be taken to your dashboard. Here, you'll see a variety of tools, including watchlists, alerts, and the main charting window.
• To begin charting, type in the name or ticker of the asset you're interested in the search bar at the top.
3. Configuring Chart Settings:
• Before integrating the Supertrend Advance Strategy, familiarize yourself with the chart settings. This can be accessed by clicking the 'gear' icon on the top right of the chart window.
• Adjust the chart type, time intervals, and other display settings to your preference.
Integrating the Strategy into a Chart:
Now that you're set up on TradingView, it's time to integrate the Supertrend Advance Strategy.
1. Accessing the Pine Script Editor:
• Located at the top-center of your screen, you'll find the "Pine Editor" tab. Click on it.
• This is where custom strategies and indicators are scripted or imported.
2. Loading the Supertrend Advance Strategy Script:
• Depending on whether you have the script or need to find it, there are two paths:
• If you have the script: Copy the Supertrend Advance Strategy script, and then paste it into the Pine Editor.
• If searching for the script: Click on the “Indicators” icon (looks like a flame) at the top of your screen, and then type “Supertrend Advance Strategy” in the search bar. If available, it will show up in the list. Simply click to add it to your chart.
3. Applying the Strategy:
• After pasting or selecting the Supertrend Advance Strategy in the Pine Editor, click on the “Add to Chart” button located at the top of the editor. This will overlay the strategy onto your main chart window.
4. Configuring Strategy Settings:
• Once the strategy is on your chart, you'll notice a small settings ('gear') icon next to its name in the top-left of the chart window. Click on this to access settings.
• Here, you can adjust various parameters of the Supertrend Advance Strategy to better fit your trading style or the specific asset you're analyzing.
5. Interpreting Signals:
• With the strategy applied, you'll now see buy/sell signals represented on your chart. Take time to familiarize yourself with how these look and behave over various timeframes and market conditions.
3. Strategy Overview
What is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is a refined version of the classic Supertrend Indicator, which was developed to aid traders in spotting market trends. The strategy utilizes a combination of data points, including average true range (ATR) and price momentum, to generate buy and sell signals.
In essence, the Supertrend Advance Strategy can be visualized as a line that moves with the price. When the price is above the Supertrend line, it indicates an uptrend and suggests a potential buy position. Conversely, when the price is below the Supertrend line, it hints at a downtrend, suggesting a potential selling point.
Strategy Goals and Objectives:
1. Trend Identification: At the core of the Supertrend Advance Strategy is the goal to efficiently and consistently identify prevailing market trends. By recognizing these trends, traders can position themselves to capitalize on price movements in their favor.
2. Reducing Noise: Financial markets are often inundated with 'noise' - short-term price fluctuations that can mislead traders. The Supertrend Advance Strategy aims to filter out this noise, allowing for clearer decision-making.
3. Enhancing Risk Management: With clear buy and sell signals, traders can set more precise stop-loss and take-profit points. This leads to better risk management and potentially improved profitability.
4. Versatility: While primarily used for trend identification, the strategy can be integrated with other technical tools and indicators to create a comprehensive trading system.
Type of Assets/Markets to Apply the Strategy:
1. Equities: The Supertrend Advance Strategy is highly popular among stock traders. Its ability to capture long-term trends makes it particularly useful for those trading individual stocks or equity indices.
2. Forex: Given the 24-hour nature of the Forex market and its propensity for trends, the Supertrend Advance Strategy is a valuable tool for currency traders.
3. Commodities: Whether it's gold, oil, or agricultural products, commodities often move in extended trends. The strategy can help in identifying and capitalizing on these movements.
4. Cryptocurrencies: The volatile nature of cryptocurrencies means they can have pronounced trends. The Supertrend Advance Strategy can aid crypto traders in navigating these often tumultuous waters.
5. Futures & Options: Traders and investors in derivative markets can utilize the strategy to make more informed decisions about contract entries and exits.
It's important to note that while the Supertrend Advance Strategy can be applied across various assets and markets, its effectiveness might vary based on market conditions, timeframe, and the specific characteristics of the asset in question. As always, it's recommended to use the strategy in conjunction with other analytical tools and to backtest its effectiveness in specific scenarios before committing to trades.
4. Input Settings
Understanding and correctly configuring input settings is crucial for optimizing the Supertrend Advance Strategy for any specific market or asset. These settings, when tweaked correctly, can drastically impact the strategy's performance.
Grouping Inputs:
Before diving into individual input settings, it's important to group similar inputs. Grouping can simplify the user interface, making it easier to adjust settings related to a specific function or indicator.
Strategy Choice:
This input allows traders to select from various strategies that incorporate the Supertrend indicator. Options might include "Supertrend with RSI," "Supertrend with MACD," etc. By choosing a strategy, the associated input settings for that strategy become available.
Supertrend Settings:
1. Multiplier: Typically, a default value of 3 is used. This multiplier is used in the ATR calculation. Increasing it makes the Supertrend line further from prices, while decreasing it brings the line closer.
2. Period: The number of bars used in the ATR calculation. A common default is 7.
EMA Settings (Exponential Moving Average):
1. Period: Defines the number of previous bars used to calculate the EMA. Common periods are 9, 21, 50, and 200.
2. Source: Allows traders to choose which price (Open, Close, High, Low) to use in the EMA calculation.
RSI Settings (Relative Strength Index):
1. Length: Determines how many periods are used for RSI calculation. The standard setting is 14.
2. Overbought Level: The threshold at which the asset is considered overbought, typically set at 70.
3. Oversold Level: The threshold at which the asset is considered oversold, often at 30.
MACD Settings (Moving Average Convergence Divergence):
1. Short Period: The shorter EMA, usually set to 12.
2. Long Period: The longer EMA, commonly set to 26.
3. Signal Period: Defines the EMA of the MACD line, typically set at 9.
CCI Settings (Commodity Channel Index):
1. Period: The number of bars used in the CCI calculation, often set to 20.
2. Overbought Level: Typically set at +100, denoting overbought conditions.
3. Oversold Level: Usually set at -100, indicating oversold conditions.
SL/TP Settings (Stop Loss/Take Profit):
1. SL Multiplier: Defines the multiplier for the average true range (ATR) to set the stop loss.
2. TP Multiplier: Defines the multiplier for the average true range (ATR) to set the take profit.
Filtering Conditions:
This section allows traders to set conditions to filter out certain signals. For example, one might only want to take buy signals when the RSI is below 30, ensuring they buy during oversold conditions.
Trade Direction and Backtest Period:
1. Trade Direction: Allows traders to specify whether they want to take long trades, short trades, or both.
2. Backtest Period: Specifies the time range for backtesting the strategy. Traders can choose from options like 'Last 6 months,' 'Last 1 year,' etc.
It's essential to remember that while default settings are provided for many of these tools, optimal settings can vary based on the market, timeframe, and trading style. Always backtest new settings on historical data to gauge their potential efficacy.
5. Understanding Strategy Conditions
Developing an understanding of the conditions set within a trading strategy is essential for traders to maximize its potential. Here, we delve deep into the logic behind these conditions, using the Supertrend Advance Strategy as our focal point.
Basic Logic Behind Conditions:
Every strategy is built around a set of conditions that provide buy or sell signals. The conditions are based on mathematical or statistical methods and are rooted in the study of historical price data. The fundamental idea is to recognize patterns or behaviors that have been profitable in the past and might be profitable in the future.
Buy and Sell Conditions:
1. Buy Conditions: Usually formulated around bullish signals or indicators suggesting upward price momentum.
2. Sell Conditions: Centered on bearish signals or indicators indicating downward price momentum.
Simple Strategy:
The simple strategy could involve using just the Supertrend indicator. Here:
• Buy: When price closes above the Supertrend line.
• Sell: When price closes below the Supertrend line.
Pullback Strategy:
This strategy capitalizes on price retracements:
• Buy: When the price retraces to the Supertrend line after a bullish signal and is supported by another bullish indicator.
• Sell: When the price retraces to the Supertrend line after a bearish signal and is confirmed by another bearish indicator.
Indicators Used:
EMA (Exponential Moving Average):
• Logic: EMA gives more weight to recent prices, making it more responsive to current price movements. A shorter-period EMA crossing above a longer-period EMA can be a bullish sign, while the opposite is bearish.
RSI (Relative Strength Index):
• Logic: RSI measures the magnitude of recent price changes to analyze overbought or oversold conditions. Values above 70 are typically considered overbought, and values below 30 are considered oversold.
MACD (Moving Average Convergence Divergence):
• Logic: MACD assesses the relationship between two EMAs of a security’s price. The MACD line crossing above the signal line can be a bullish signal, while crossing below can be bearish.
CCI (Commodity Channel Index):
• Logic: CCI compares a security's average price change with its average price variation. A CCI value above +100 may mean the price is overbought, while below -100 might signify an oversold condition.
And others...
As the strategy expands or contracts, more indicators might be added or removed. The crucial point is to understand the core logic behind each, ensuring they align with the strategy's objectives.
Logic Behind Each Indicator:
1. EMA: Emphasizes recent price movements; provides dynamic support and resistance levels.
2. RSI: Indicates overbought and oversold conditions based on recent price changes.
3. MACD: Showcases momentum and direction of a trend by comparing two EMAs.
4. CCI: Measures the difference between a security's price change and its average price change.
Understanding strategy conditions is not just about knowing when to buy or sell but also about comprehending the underlying market dynamics that those conditions represent. As you familiarize yourself with each condition and indicator, you'll be better prepared to adapt and evolve with the ever-changing financial markets.
6. Trade Execution and Management
Trade execution and management are crucial aspects of any trading strategy. Efficient execution can significantly impact profitability, while effective management can preserve capital during adverse market conditions. In this section, we'll explore the nuances of position entry, exit strategies, and various Stop Loss (SL) and Take Profit (TP) methodologies within the Supertrend Advance Strategy.
Position Entry:
Effective trade entry revolves around:
1. Timing: Enter at a point where the risk-reward ratio is favorable. This often corresponds to confirmatory signals from multiple indicators.
2. Volume Analysis: Ensure there's adequate volume to support the movement. Volume can validate the strength of a signal.
3. Confirmation: Use multiple indicators or chart patterns to confirm the entry point. For instance, a buy signal from the Supertrend indicator can be confirmed with a bullish MACD crossover.
Position Exit Strategies:
A successful exit strategy will lock in profits and minimize losses. Here are some strategies:
1. Fixed Time Exit: Exiting after a predetermined period.
2. Percentage-based Profit Target: Exiting after a certain percentage gain.
3. Indicator-based Exit: Exiting when an indicator gives an opposing signal.
Percentage-based SL/TP:
• Stop Loss (SL): Set a fixed percentage below the entry price to limit potential losses.
• Example: A 2% SL on an entry at $100 would trigger a sell at $98.
• Take Profit (TP): Set a fixed percentage above the entry price to lock in gains.
• Example: A 5% TP on an entry at $100 would trigger a sell at $105.
Supertrend-based SL/TP:
• Stop Loss (SL): Position the SL at the Supertrend line. If the price breaches this line, it could indicate a trend reversal.
• Take Profit (TP): One could set the TP at a point where the Supertrend line flattens or turns, indicating a possible slowdown in momentum.
Swing high/low-based SL/TP:
• Stop Loss (SL): For a long position, set the SL just below the recent swing low. For a short position, set it just above the recent swing high.
• Take Profit (TP): For a long position, set the TP near a recent swing high or resistance. For a short position, near a swing low or support.
And other methods...
1. Trailing Stop Loss: This dynamic SL adjusts with the price movement, locking in profits as the trade moves in your favor.
2. Multiple Take Profits: Divide the position into segments and set multiple TP levels, securing profits in stages.
3. Opposite Signal Exit: Exit when another reliable indicator gives an opposite signal.
Trade execution and management are as much an art as they are a science. They require a blend of analytical skill, discipline, and intuition. Regularly reviewing and refining your strategies, especially in light of changing market conditions, is crucial to maintaining consistent trading performance.
7. Visual Representations
Visual tools are essential for traders, as they simplify complex data into an easily interpretable format. Properly analyzing and understanding the plots on a chart can provide actionable insights and a more intuitive grasp of market conditions. In this section, we’ll delve into various visual representations used in the Supertrend Advance Strategy and their significance.
Understanding Plots on the Chart:
Charts are the primary visual aids for traders. The arrangement of data points, lines, and colors on them tell a story about the market's past, present, and potential future moves.
1. Data Points: These represent individual price actions over a specific timeframe. For instance, a daily chart will have data points showing the opening, closing, high, and low prices for each day.
2. Colors: Used to indicate the nature of price movement. Commonly, green is used for bullish (upward) moves and red for bearish (downward) moves.
Trend Lines:
Trend lines are straight lines drawn on a chart that connect a series of price points. Their significance:
1. Uptrend Line: Drawn along the lows, representing support. A break below might indicate a trend reversal.
2. Downtrend Line: Drawn along the highs, indicating resistance. A break above might suggest the start of a bullish trend.
Filled Areas:
These represent a range between two values on a chart, usually shaded or colored. For instance:
1. Bollinger Bands: The area between the upper and lower band is filled, giving a visual representation of volatility.
2. Volume Profile: Can show a filled area representing the amount of trading activity at different price levels.
Stop Loss and Take Profit Lines:
These are horizontal lines representing pre-determined exit points for trades.
1. Stop Loss Line: Indicates the level at which a trade will be automatically closed to limit losses. Positioned according to the trader's risk tolerance.
2. Take Profit Line: Denotes the target level to lock in profits. Set according to potential resistance (for long trades) or support (for short trades) or other technical factors.
Trailing Stop Lines:
A trailing stop is a dynamic form of stop loss that moves with the price. On a chart:
1. For Long Trades: Starts below the entry price and moves up with the price but remains static if the price falls, ensuring profits are locked in.
2. For Short Trades: Starts above the entry price and moves down with the price but remains static if the price rises.
Visual representations offer traders a clear, organized view of market dynamics. Familiarity with these tools ensures that traders can quickly and accurately interpret chart data, leading to more informed decision-making. Always ensure that the visual aids used resonate with your trading style and strategy for the best results.
8. Backtesting
Backtesting is a fundamental process in strategy development, enabling traders to evaluate the efficacy of their strategy using historical data. It provides a snapshot of how the strategy would have performed in past market conditions, offering insights into its potential strengths and vulnerabilities. In this section, we'll explore the intricacies of setting up and analyzing backtest results and the caveats one must be aware of.
Setting Up Backtest Period:
1. Duration: Determine the timeframe for the backtest. It should be long enough to capture various market conditions (bullish, bearish, sideways). For instance, if you're testing a daily strategy, consider a period of several years.
2. Data Quality: Ensure the data source is reliable, offering high-resolution and clean data. This is vital to get accurate backtest results.
3. Segmentation: Instead of a continuous period, sometimes it's helpful to backtest over distinct market phases, like a particular bear or bull market, to see how the strategy holds up in different environments.
Analyzing Backtest Results:
1. Performance Metrics: Examine metrics like the total return, annualized return, maximum drawdown, Sharpe ratio, and others to gauge the strategy's efficiency.
2. Win Rate: It's the ratio of winning trades to total trades. A high win rate doesn't always signify a good strategy; it should be evaluated in conjunction with other metrics.
3. Risk/Reward: Understand the average profit versus the average loss per trade. A strategy might have a low win rate but still be profitable if the average gain far exceeds the average loss.
4. Drawdown Analysis: Review the periods of losses the strategy could incur and how long it takes, on average, to recover.
9. Tips and Best Practices
Successful trading requires more than just knowing how a strategy works. It necessitates an understanding of when to apply it, how to adjust it to varying market conditions, and the wisdom to recognize and avoid common pitfalls. This section offers insightful tips and best practices to enhance the application of the Supertrend Advance Strategy.
When to Use the Strategy:
1. Market Conditions: Ideally, employ the Supertrend Advance Strategy during trending market conditions. This strategy thrives when there are clear upward or downward trends. It might be less effective during consolidative or sideways markets.
2. News Events: Be cautious around significant news events, as they can cause extreme volatility. It might be wise to avoid trading immediately before and after high-impact news.
3. Liquidity: Ensure you are trading in assets/markets with sufficient liquidity. High liquidity ensures that the price movements are more reflective of genuine market sentiment and not due to thin volume.
Adjusting Settings for Different Markets/Timeframes:
1. Markets: Each market (stocks, forex, commodities) has its own characteristics. It's essential to adjust the strategy's parameters to align with the market's volatility and liquidity.
2. Timeframes: Shorter timeframes (like 1-minute or 5-minute charts) tend to have more noise. You might need to adjust the settings to filter out false signals. Conversely, for longer timeframes (like daily or weekly charts), you might need to be more responsive to genuine trend changes.
3. Customization: Regularly review and tweak the strategy's settings. Periodic adjustments can ensure the strategy remains optimized for the current market conditions.
10. Frequently Asked Questions (FAQs)
Given the complexities and nuances of the Supertrend Advance Strategy, it's only natural for traders, both new and seasoned, to have questions. This section addresses some of the most commonly asked questions regarding the strategy.
1. What exactly is the Supertrend Advance Strategy?
The Supertrend Advance Strategy is an evolved version of the traditional Supertrend indicator. It's designed to provide clearer buy and sell signals by incorporating additional indicators like EMA, RSI, MACD, CCI, etc. The strategy aims to capitalize on market trends while minimizing false signals.
2. Can I use the Supertrend Advance Strategy for all asset types?
Yes, the strategy can be applied to various asset types like stocks, forex, commodities, and cryptocurrencies. However, it's crucial to adjust the settings accordingly to suit the specific characteristics and volatility of each asset type.
3. Is this strategy suitable for day trading?
Absolutely! The Supertrend Advance Strategy can be adjusted to suit various timeframes, making it versatile for both day trading and long-term trading. Remember to fine-tune the settings to align with the timeframe you're trading on.
4. How do I deal with false signals?
No strategy is immune to false signals. However, by combining the Supertrend with other indicators and adhering to strict risk management protocols, you can minimize the impact of false signals. Always use stop-loss orders and consider filtering trades with additional confirmation signals.
5. Do I need any prior trading experience to use this strategy?
While the Supertrend Advance Strategy is designed to be user-friendly, having a foundational understanding of trading and market analysis can greatly enhance your ability to employ the strategy effectively. If you're a beginner, consider pairing the strategy with further education and practice on demo accounts.
6. How often should I review and adjust the strategy settings?
There's no one-size-fits-all answer. Some traders adjust settings weekly, while others might do it monthly. The key is to remain responsive to changing market conditions. Regular backtesting can give insights into potential required adjustments.
7. Can the Supertrend Advance Strategy be automated?
Yes, many traders use algorithmic trading platforms to automate their strategies, including the Supertrend Advance Strategy. However, always monitor automated systems regularly to ensure they're operating as intended.
8. Are there any markets or conditions where the strategy shouldn't be used?
The strategy might generate more false signals in markets that are consolidative or range-bound. During significant news events or times of unexpected high volatility, it's advisable to tread with caution or stay out of the market.
9. How important is backtesting with this strategy?
Backtesting is crucial as it allows traders to understand how the strategy would have performed in the past, offering insights into potential profitability and areas of improvement. Always backtest any new setting or tweak before applying it to live trades.
10. What if the strategy isn't working for me?
No strategy guarantees consistent profits. If it's not working for you, consider reviewing your settings, seeking expert advice, or complementing the Supertrend Advance Strategy with other analysis methods. Remember, continuous learning and adaptation are the keys to trading success.
Other comments
Value of combining several indicators in this script and how they work together
Diversification of Signals: Just as diversifying an investment portfolio can reduce risk, using multiple indicators can offer varied perspectives on potential price movements. Each indicator can capture a different facet of the market, ensuring that traders are not overly reliant on a single data point.
Confirmation & Reduced False Signals: A common challenge with many indicators is the potential for false signals. By requiring confirmation from multiple indicators before acting, the chances of acting on a false signal can be significantly reduced.
Flexibility Across Market Conditions: Different indicators might perform better under different market conditions. For example, while moving averages might excel in trending markets, oscillators like RSI might be more useful during sideways or range-bound conditions. A mashup strategy can potentially adapt better to varying market scenarios.
Comprehensive Analysis: With multiple indicators, traders can gauge trend strength, momentum, volatility, and potential market reversals all at once, providing a holistic view of the market.
How do the different indicators in the Supertrend Advance Strategy work together?
Supertrend: This is primarily a trend-following indicator. It provides traders with buy and sell signals based on the volatility of the price. When combined with other indicators, it can filter out noise and give more weight to strong, confirmed trends.
EMA (Exponential Moving Average): EMA gives more weight to recent price data. It can be used to identify the direction and strength of a trend. When the price is above the EMA, it's generally considered bullish, and vice versa.
RSI (Relative Strength Index): An oscillator that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. By cross-referencing with other indicators like EMA or MACD, traders can spot potential reversals or confirmations of a trend.
MACD (Moving Average Convergence Divergence): This indicator identifies changes in the strength, direction, momentum, and duration of a trend in a stock's price. When the MACD line crosses above the signal line, it can be a bullish sign, and when it crosses below, it can be bearish. Pairing MACD with Supertrend can provide dual confirmation of a trend.
CCI (Commodity Channel Index): Initially developed for commodities, CCI can indicate overbought or oversold conditions. It can be used in conjunction with other indicators to determine entry and exit points.
In essence, the synergy of these indicators provides a balanced, comprehensive approach to trading. Each indicator offers its unique lens into market conditions, and when they align, it can be a powerful indication of a trading opportunity. This combination not only reduces the potential drawbacks of each individual indicator but leverages their strengths, aiming for more consistent and informed trading decisions.
Backtesting and Default Settings
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
• Default properties: RSI on (length 14, RSI buy level 50, sell level 50), EMA, RSI, MACD on, type of strategy pullback, SL/TP type: ATR (length 10, factor 3), trade direction both, quantity 5, take profit swing hl 5.1, highest / lowest lookback 2, enable ATR trail (ATR length 10, SL ATR multiplier 1.4, TP multiplier 2.1, lookback = 4, trade direction = both).
Machine Learning: Optimal RSI [YinYangAlgorithms]This Indicator, will rate multiple different lengths of RSIs to determine which RSI to RSI MA cross produced the highest profit within the lookback span. This ‘Optimal RSI’ is then passed back, and if toggled will then be thrown into a Machine Learning calculation. You have the option to Filter RSI and RSI MA’s within the Machine Learning calculation. What this does is, only other Optimal RSI’s which are in the same bullish or bearish direction (is the RSI above or below the RSI MA) will be added to the calculation.
You can either (by default) use a Simple Average; which is essentially just a Mean of all the Optimal RSI’s with a length of Machine Learning. Or, you can opt to use a k-Nearest Neighbour (KNN) calculation which takes a Fast and Slow Speed. We essentially turn the Optimal RSI into a MA with different lengths and then compare the distance between the two within our KNN Function.
RSI may very well be one of the most used Indicators for identifying crucial Overbought and Oversold locations. Not only that but when it crosses its Moving Average (MA) line it may also indicate good locations to Buy and Sell. Many traders simply use the RSI with the standard length (14), however, does that mean this is the best length?
By using the length of the top performing RSI and then applying some Machine Learning logic to it, we hope to create what may be a more accurate, smooth, optimal, RSI.
Tutorial:
This is a pretty zoomed out Perspective of what the Indicator looks like with its default settings (except with Bollinger Bands and Signals disabled). If you look at the Tables above, you’ll notice, currently the Top Performing RSI Length is 13 with an Optimal Profit % of: 1.00054973. On its default settings, what it does is Scan X amount of RSI Lengths and checks for when the RSI and RSI MA cross each other. It then records the profitability of each cross to identify which length produced the overall highest crossing profitability. Whichever length produces the highest profit is then the RSI length that is used in the plots, until another length takes its place. This may result in what we deem to be the ‘Optimal RSI’ as it is an adaptive RSI which changes based on performance.
In our next example, we changed the ‘Optimal RSI Type’ from ‘All Crossings’ to ‘Extremity Crossings’. If you compare the last two examples to each other, you’ll notice some similarities, but overall they’re quite different. The reason why is, the Optimal RSI is calculated differently. When using ‘All Crossings’ everytime the RSI and RSI MA cross, we evaluate it for profit (short and long). However, with ‘Extremity Crossings’, we only evaluate it when the RSI crosses over the RSI MA and RSI <= 40 or RSI crosses under the RSI MA and RSI >= 60. We conclude the crossing when it crosses back on its opposite of the extremity, and that is how it finds its Optimal RSI.
The way we determine the Optimal RSI is crucial to calculating which length is currently optimal.
In this next example we have zoomed in a bit, and have the full default settings on. Now we have signals (which you can set alerts for), for when the RSI and RSI MA cross (green is bullish and red is bearish). We also have our Optimal RSI Bollinger Bands enabled here too. These bands allow you to see where there may be Support and Resistance within the RSI at levels that aren’t static; such as 30 and 70. The length the RSI Bollinger Bands use is the Optimal RSI Length, allowing it to likewise change in correlation to the Optimal RSI.
In the example above, we’ve zoomed out as far as the Optimal RSI Bollinger Bands go. You’ll notice, the Bollinger Bands may act as Support and Resistance locations within and outside of the RSI Mid zone (30-70). In the next example we will highlight these areas so they may be easier to see.
Circled above, you may see how many times the Optimal RSI faced Support and Resistance locations on the Bollinger Bands. These Bollinger Bands may give a second location for Support and Resistance. The key Support and Resistance may still be the 30/50/70, however the Bollinger Bands allows us to have a more adaptive, moving form of Support and Resistance. This helps to show where it may ‘bounce’ if it surpasses any of the static levels (30/50/70).
Due to the fact that this Indicator may take a long time to execute and it can throw errors for such, we have added a Setting called: Adjust Optimal RSI Lookback and RSI Count. This settings will automatically modify the Optimal RSI Lookback Length and the RSI Count based on the Time Frame you are on and the Bar Indexes that are within. For instance, if we switch to the 1 Hour Time Frame, it will adjust the length from 200->90 and RSI Count from 30->20. If this wasn’t adjusted, the Indicator would Timeout.
You may however, change the Setting ‘Adjust Optimal RSI Lookback and RSI Count’ to ‘Manual’ from ‘Auto’. This will give you control over the ‘Optimal RSI Lookback Length’ and ‘RSI Count’ within the Settings. Please note, it will likely take some “fine tuning” to find working settings without the Indicator timing out, but there are definitely times you can find better settings than our ‘Auto’ will create; especially on higher Time Frames. The Minimum our ‘Auto’ will create is:
Optimal RSI Lookback Length: 90
RSI Count: 20
The Maximum it will create is:
Optimal RSI Lookback Length: 200
RSI Count: 30
If there isn’t much bar index history, for instance, if you’re on the 1 Day and the pair is BTC/USDT you’ll get < 4000 Bar Indexes worth of data. For this reason it is possible to manually increase the settings to say:
Optimal RSI Lookback Length: 500
RSI Count: 50
But, please note, if you make it too high, it may also lead to inaccuracies.
We will conclude our Tutorial here, hopefully this has given you some insight as to how calculating our Optimal RSI and then using it within Machine Learning may create a more adaptive RSI.
Settings:
Optimal RSI:
Show Crossing Signals: Display signals where the RSI and RSI Cross.
Show Tables: Display Information Tables to show information like, Optimal RSI Length, Best Profit, New Optimal RSI Lookback Length and New RSI Count.
Show Bollinger Bands: Show RSI Bollinger Bands. These bands work like the TDI Indicator, except its length changes as it uses the current RSI Optimal Length.
Optimal RSI Type: This is how we calculate our Optimal RSI. Do we use all RSI and RSI MA Crossings or just when it crosses within the Extremities.
Adjust Optimal RSI Lookback and RSI Count: Auto means the script will automatically adjust the Optimal RSI Lookback Length and RSI Count based on the current Time Frame and Bar Index's on chart. This will attempt to stop the script from 'Taking too long to Execute'. Manual means you have full control of the Optimal RSI Lookback Length and RSI Count.
Optimal RSI Lookback Length: How far back are we looking to see which RSI length is optimal? Please note the more bars the lower this needs to be. For instance with BTC/USDT you can use 500 here on 1D but only 200 for 15 Minutes; otherwise it will timeout.
RSI Count: How many lengths are we checking? For instance, if our 'RSI Minimum Length' is 4 and this is 30, the valid RSI lengths we check is 4-34.
RSI Minimum Length: What is the RSI length we start our scans at? We are capped with RSI Count otherwise it will cause the Indicator to timeout, so we don't want to waste any processing power on irrelevant lengths.
RSI MA Length: What length are we using to calculate the optimal RSI cross' and likewise plot our RSI MA with?
Extremity Crossings RSI Backup Length: When there is no Optimal RSI (if using Extremity Crossings), which RSI should we use instead?
Machine Learning:
Use Rational Quadratics: Rationalizing our Close may be beneficial for usage within ML calculations.
Filter RSI and RSI MA: Should we filter the RSI's before usage in ML calculations? Essentially should we only use RSI data that are of the same type as our Optimal RSI? For instance if our Optimal RSI is Bullish (RSI > RSI MA), should we only use ML RSI's that are likewise bullish?
Machine Learning Type: Are we using a Simple ML Average, KNN Mean Average, KNN Exponential Average or None?
KNN Distance Type: We need to check if distance is within the KNN Min/Max distance, which distance checks are we using.
Machine Learning Length: How far back is our Machine Learning going to keep data for.
k-Nearest Neighbour (KNN) Length: How many k-Nearest Neighbours will we account for?
Fast ML Data Length: What is our Fast ML Length? This is used with our Slow Length to create our KNN Distance.
Slow ML Data Length: What is our Slow ML Length? This is used with our Fast Length to create our KNN Distance.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
Fiboborsa+BistTitle: "Fiboborsa+Bist Indicator for TradingView"
Description: The "Fiboborsa+Bist" indicator is a powerful tool designed for TradingView users. This indicator offers a comprehensive set of technical indicators to assist you in your technical analysis and trading decisions.
Features:
Simple Moving Averages (SMA): You can enable or disable SMA with different periods (20, 50, 100, 200) to observe different timeframes and trends.
SMA Strategy: Use SMA crossovers to determine trends. Watch for the 20-period SMA crossing above the 50-period SMA for a bullish signal. For a bearish signal, observe the 50-period SMA crossing below the 100-period SMA.
Exponential Moving Averages (EMA): Similar to SMA, you can enable or disable EMA with different periods (5, 8, 14, 21, 34, 55, 89, 144, 233) for more precise trend analysis.
EMA Strategy: Use EMA crossovers and crossunders for short-term trend changes. A buy signal may occur when the 5-period EMA crosses above the 14-period EMA, while a crossunder suggests a selling opportunity.
Weighted Moving Averages (WMA): Customize WMA settings with various periods (5, 13, 21, 34, 89, 144, 233, 377, 610, 987) to suit your trading style.
WMA Strategy: Use WMA crossovers to verify trends. When the 13-period WMA crosses above the 34-period WMA, it may indicate an uptrend.
Buy and Sell Signals: The indicator provides buy and sell signals based on EMA crossovers and crossunders. Strong signals are also highlighted.
EMA Buy and Sell Strategy: Make informed trading decisions using buy and sell signals generated by EMA crossovers and crossunders.
Ichimoku Cloud: You can enable the Ichimoku Cloud for a clear visual representation of support and resistance levels.
Ichimoku Strategy: Use the Ichimoku Cloud to determine trend direction. Entering long positions is common when the price is above the cloud and considering short positions when it's below the cloud. Verify the trend with the Chikou Span.
Bollinger Bands: Easily visualize price volatility by enabling the Bollinger Bands feature.
Bollinger Bands Strategy: Bollinger Bands help you visualize price volatility. Look for potential reversal points when the price touches or crosses the upper or lower bands.
Use the "Fiboborsa+Bist" indicator to enhance your trading strategies and make informed decisions in the dynamic world of financial markets.
Additional Information:
Bollinger Bands: Bollinger Bands are a technical analysis tool used to monitor price volatility and determine overbought or oversold conditions. This indicator consists of three components:
Middle Moving Average (SMA): Typically, a 20-day SMA is used.
Upper Band: Calculated by adding two times the standard deviation to the SMA.
Lower Band: Calculated by subtracting two times the standard deviation from the SMA.
As the price moves between these two bands, it becomes possible to identify potential buying or selling points by comparing its height or low with these bands.
Ichimoku Cloud: The Ichimoku Cloud is a comprehensive indicator used for trend identification, defining support and resistance levels, and measuring trend strength. The Ichimoku Cloud comprises five key components:
Tenkan Sen (Conversion Line): Used to identify short-term trends.
Kijun Sen (Base Line): Used to identify medium-term trends.
Senkou Span A (Leading Span A): Calculated as (Tenkan Sen + Kijun Sen) / 2 and shows future support and resistance levels.
Senkou Span B (Leading Span B): Calculated as (highest high + lowest low) / 2 and indicates future support and resistance levels.
Chikou Span (Lagging Line): Enables tracking the price backward.
The Ichimoku Cloud interprets a price above the cloud as an uptrend and below the cloud as a downtrend. The Chikou Span assists in verifying the current trend.
ADDITIONAL STRATEGY WITH RSI AND MACD INDICATORS
**Strategy: Two-Stage Trading Strategy Using RSI, MACD, and Fiboborsa+Bist Indicators**
**Stage 1: Determining the Trend and Selecting the Trading Direction**
1. **Trend Identification with Fiboborsa+Bist Indicator:**
- Analyze the simple moving averages (SMA), exponential moving averages (EMA), and weighted moving averages (WMA) used with the Fiboborsa+Bist indicator. These indicators will provide information about the direction of the market trend.
2. **Identifying Overbought and Oversold Conditions with RSI:**
- Use the RSI indicator to identify overbought (70 and above) and oversold (30 and below) conditions. This helps in measuring the strength of the trend. If RSI enters the overbought zone, a downward correction is likely. If RSI enters the oversold zone, an upward correction is probable.
3. **Evaluating Momentum with MACD:**
- Examine price momentum using the MACD indicator. When the MACD line crosses above the signal line, it may indicate an increasing upward momentum. Conversely, a downward cross can suggest an increasing downward momentum.
**Stage 2: Generating Buy and Sell Signals**
4. **Combining RSI, MACD, and Fiboborsa+Bist Indicators:**
- To generate a buy signal, wait for RSI to move out of the oversold region into an uptrend and for the MACD line to cross above the signal line.
- To generate a sell signal, wait for RSI to move out of the overbought region into a downtrend and for the MACD line to cross below the signal line.
5. **Confirmation with Fiboborsa+Bist Indicator:**
- When you receive a buy or sell signal, use the Fiboborsa+Bist indicator to confirm the market trend. Confirming the trend can strengthen your trade signals.
6. **Setting Stop-Loss and Take-Profit Levels:**
- Remember to manage risk when opening buy or sell positions. Set stop-loss and take-profit levels to limit your risk.
7. **Monitor and Adjust Your Trades:**
- Continuously monitor your trade positions and adjust your strategy as per market conditions.
This two-stage trading strategy offers the ability to determine trends and generate trade signals using different indicators. However, every trading strategy involves risks, so risk management and practical application are essential. Also, it's recommended to test this strategy in a demo account before using it in a real trading account.
Market Performance TableThe Market Performance Table displays the performance of multiple tickers (up to 5) in a table format. The tickers can be customized by selecting them through the indicator settings.
The indicator calculates various metrics for each ticker, including the 1-day change percentage, whether the price is above the 50, 20, and 10-day simple moving averages (SMA), as well as the relative strength compared to the 10/20 SMA and 20/50 SMA crossovers. It also calculates the price deviation from the 50-day SMA.
The table is displayed on the chart and can be positioned in different locations.
Credits for the idea to @Alex_PrimeTrading ;)
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!
NSDT Average 6This is a pretty simple concept that we were asked to put together. It uses 6 Moving Averages, and takes the average of each one, then averages them all together.
If you don't want to use 6, and only 3 for example, then just enter the same length in two of the input fields as pairs.
Example:
For 6, you could use 10, 20, 30, 40, 50, 60
For 3, you could use 10, 10, 50, 50, 100, 100
It doesn't ploy 6 MA's, it only plots one - the result of the average of an average of an average, etc..
Publishing open source so other can modify as needed.
Statistical Package for the Trading Sciences [SS]
This is SPTS.
It stands for Statistical Package for the Trading Sciences.
Its a play on SPSS (Statistical Package for the Social Sciences) by IBM (software that, prior to Pinescript, I would use on a daily basis for trading).
Let's preface this indicator first:
This isn't so much an indicator as it is a project. A passion project really.
This has been in the works for months and I still feel like its incomplete. But the plan here is to continue to add functionality to it and actually have the Pinecoding and Tradingview community contribute to it.
As a math based trader, I relied on Excel, SPSS and R constantly to plan my trades. Since learning a functional amount of Pinescript and coding a lot of what I do and what I relied on SPSS, Excel and R for, I use it perhaps maybe a few times a week.
This indicator, or package, has some of the key things I used Excel and SPSS for on a daily and weekly basis. This also adds a lot of, I would say, fairly complex math functionality to Pinescript. Because this is adding functionality not necessarily native to Pinescript, I have placed most, if not all, of the functionality into actual exportable functions. I have also set it up as a kind of library, with explanations and tips on how other coders can take these functions and implement them into other scripts.
The hope here is that other coders will take it, build upon it, improve it and hopefully share additional functionality that can be added into this package. Hence why I call it a project. Okay, let's get into an overview:
Current Functions of SPTS:
SPTS currently has the following functionality (further explanations will be offered below):
Ability to Perform a One-Tailed, Two-Tailed and Paired Sample T-Test, with corresponding P value.
Standard Pearson Correlation (with functionality to be able to calculate the Pearson Correlation between 2 arrays).
Quadratic (or Curvlinear) correlation assessments.
R squared Assessments.
Standard Linear Regression.
Multiple Regression of 2 independent variables.
Tests of Normality (with Kurtosis and Skewness) and recognition of up to 7 Different Distributions.
ARIMA Modeller (Sort of, more details below)
Okay, so let's go over each of them!
T-Tests
So traditionally, most correlation assessments on Pinescript are done with a generic Pearson Correlation using the "ta.correlation" argument. However, this is not always the best test to be used for correlations and determine effects. One approach to correlation assessments used frequently in economics is the T-Test assessment.
The t-test is a statistical hypothesis test used to determine if there is a significant difference between the means of two groups. It assesses whether the sample means are likely to have come from populations with the same mean. The test produces a t-statistic, which is then compared to a critical value from the t-distribution to determine statistical significance. Lower p-values indicate stronger evidence against the null hypothesis of equal means.
A significant t-test result, indicating the rejection of the null hypothesis, suggests that there is statistical evidence to support that there is a significant difference between the means of the two groups being compared. In practical terms, it means that the observed difference in sample means is unlikely to have occurred by random chance alone. Researchers typically interpret this as evidence that there is a real, meaningful difference between the groups being studied.
Some uses of the T-Test in finance include:
Risk Assessment: The t-test can be used to compare the risk profiles of different financial assets or portfolios. It helps investors assess whether the differences in returns or volatility are statistically significant.
Pairs Trading: Traders often apply the t-test when engaging in pairs trading, a strategy that involves trading two correlated securities. It helps determine when the price spread between the two assets is statistically significant and may revert to the mean.
Volatility Analysis: Traders and risk managers use t-tests to compare the volatility of different assets or portfolios, assessing whether one is significantly more or less volatile than another.
Market Efficiency Tests: Financial researchers use t-tests to test the Efficient Market Hypothesis by assessing whether stock price movements follow a random walk or if there are statistically significant deviations from it.
Value at Risk (VaR) Calculation: Risk managers use t-tests to calculate VaR, a measure of potential losses in a portfolio. It helps assess whether a portfolio's value is likely to fall below a certain threshold.
There are many other applications, but these are a few of the highlights. SPTS permits 3 different types of T-Test analyses, these being the One Tailed T-Test (if you want to test a single direction), two tailed T-Test (if you are unsure of which direction is significant) and a paired sample t-test.
Which T is the Right T?
Generally, a one-tailed t-test is used to determine if a sample mean is significantly greater than or less than a specified population mean, whereas a two-tailed t-test assesses if the sample mean is significantly different (either greater or less) from the population mean. In contrast, a paired sample t-test compares two sets of paired observations (e.g., before and after treatment) to assess if there's a significant difference in their means, typically used when the data points in each pair are related or dependent.
So which do you use? Well, it depends on what you want to know. As a general rule a one tailed t-test is sufficient and will help you pinpoint directionality of the relationship (that one ticker or economic indicator has a significant affect on another in a linear way).
A two tailed is more broad and looks for significance in either direction.
A paired sample t-test usually looks at identical groups to see if one group has a statistically different outcome. This is usually used in clinical trials to compare treatment interventions in identical groups. It's use in finance is somewhat limited, but it is invaluable when you want to compare equities that track the same thing (for example SPX vs SPY vs ES1!) or you want to test a hypothesis about an index and a leveraged share (for example, the relationship between FNGU and, say, MSFT or NVDA).
Statistical Significance
In general, with a t-test you would need to reference a T-Table to determine the statistical significance of the degree of Freedom and the T-Statistic.
However, because I wanted Pinescript to full fledge replace SPSS and Excel, I went ahead and threw the T-Table into an array, so that Pinescript can make the determination itself of the actual P value for a t-test, no cross referencing required :-).
Left tail (Significant):
Both tails (Significant):
Distributed throughout (insignificant):
As you can see in the images above, the t-test will also display a bell-curve analysis of where the significance falls (left tail, both tails or insignificant, distributed throughout).
That said, I have not included this function for the paired sample t-test because that is a bit more nuanced. But for the one and two tailed assessments, the indicator will provide you the P value.
Pearson Correlation Assessment
I don't think I need to go into too much detail on this one.
I have put in functionality to quickly calculate the Pearson Correlation of two array's, which is not currently possible with the "ta.correlation" function.
Quadratic (Curvlinear) Correlation
Not everything in life is linear, sometimes things are curved!
The Pearson Correlation is great for linear assessments, but tends to under-estimate the degree of the relationship in curved relationships. There currently is no native function to t-test for quadratic/curvlinear relationships, so I went ahead and created one.
You can see an example of how Quadratic and Pearson Correlations vary when you look at CME_MINI:ES1! against AMEX:DIA for the past 10 ish months:
Pearson Correlation:
Quadratic Correlation:
One or the other is not always the best, so it is important to check both!
R-Squared Assessments:
The R-squared value, or the square of the Pearson correlation coefficient (r), is used to measure the proportion of variance in one variable that can be explained by the linear relationship with another variable. It represents the goodness-of-fit of a linear regression model with a single predictor variable.
R-Squared is offered in 3 separate forms within this indicator. First, there is the generic R squared which is taking the square root of a Pearson Correlation assessment to assess the variance.
The next is the R-Squared which is calculated from an actual linear regression model done within the indicator.
The first is the R-Squared which is calculated from a multiple regression model done within the indicator.
Regardless of which R-Squared value you are using, the meaning is the same. R-Square assesses the variance between the variables under assessment and can offer an insight into the goodness of fit and the ability of the model to account for the degree of variance.
Here is the R Squared assessment of the SPX against the US Money Supply:
Standard Linear Regression
The indicator contains the ability to do a standard linear regression model. You can convert one ticker or economic indicator into a stock, ticker or other economic indicator. The indicator will provide you with all of the expected information from a linear regression model, including the coefficients, intercept, error assessments, correlation and R2 value.
Here is AAPL and MSFT as an example:
Multiple Regression
Oh man, this was something I really wanted in Pinescript, and now we have it!
I have created a function for multiple regression, which, if you export the function, will permit you to perform multiple regression on any variables available in Pinescript!
Using this functionality in the indicator, you will need to select 2, dependent variables and a single independent variable.
Here is an example of multiple regression for NASDAQ:AAPL using NASDAQ:MSFT and NASDAQ:NVDA :
And an example of SPX using the US Money Supply (M2) and AMEX:GLD :
Tests of Normality:
Many indicators perform a lot of functions on the assumption of normality, yet there are no indicators that actually test that assumption!
So, I have inputted a function to assess for normality. It uses the Kurtosis and Skewness to determine up to 7 different distribution types and it will explain the implication of the distribution. Here is an example of SP:SPX on the Monthly Perspective since 2010:
And NYSE:BA since the 60s:
And NVDA since 2015:
ARIMA Modeller
Okay, so let me disclose, this isn't a full fledge ARIMA modeller. I took some shortcuts.
True ARIMA modelling would involve decomposing the seasonality from the trend. I omitted this step for simplicity sake. Instead, you can select between using an EMA or SMA based approach, and it will perform an autogressive type analysis on the EMA or SMA.
I have tested it on lookback with results provided by SPSS and this actually works better than SPSS' ARIMA function. So I am actually kind of impressed.
You will need to input your parameters for the ARIMA model, I usually would do a 14, 21 and 50 day EMA of the close price, and it will forecast out that range over the length of the EMA.
So for example, if you select the EMA 50 on the daily, it will plot out the forecast for the next 50 days based on an autoregressive model created on the EMA 50. Here is how it looks on AMEX:SPY :
You can also elect to plot the upper and lower confidence bands:
Closing Remarks
So that is the indicator/package.
I do hope to continue expanding its functionality, but as of now, it does already have quite a lot of functionality.
I really hope you enjoy it and find it helpful. This. Has. Taken. AGES! No joke. Between referencing my old statistics textbooks, trying to remember how to calculate some of these things, and wanting to throw my computer against the wall because of errors in the code, this was a task, that's for sure. So I really hope you find some usefulness in it all and enjoy the ability to be able to do functions that previously could really only be done in external software.
As always, leave your comments, suggestions and feedback below!
Take care!
Ultimate RSI [LuxAlgo]The Ultimate RSI indicator is a new oscillator based on the calculation of the Relative Strength Index that aims to put more emphasis on the trend, thus having a less noisy output. Opposite to the regular RSI, this oscillator is designed for a trend trading approach instead of a contrarian one.
🔶 USAGE
While returning the same information as a regular RSI, the Ultimate RSI puts more emphasis on trends, and as such can reach overbought/oversold levels faster as well as staying longer within these areas. This can avoid the common issue of an RSI regularly crossing an overbought or oversold level while the trend makes new higher highs/lower lows.
The Ultimate RSI crossing above the overbought level can be indicative of a strong uptrend (highlighted as a green area), while an Ultimate RSI crossing under the oversold level can be indicative of a strong downtrend (highlighted as a red area).
The Ultimate RSI crossing the 50 midline can also indicate trends, with the oscillator being above indicating an uptrend, else a downtrend. Unlike a regular RSI, the Ultimate RSI will cross the midline level less often, thus generating fewer whipsaw signals.
For even more timely indications users can observe the Ultimate RSI relative to its signal line. An Ultimate RSI above its signal line can indicate it is increasing, while the opposite would indicate it is decreasing.
🔹 Smoothing Methods
Users can return more reactive or smoother results depending on the selected smoothing method used for the calculation of the Ultimate RSI. Options include:
Exponential Moving Average (EMA)
Simple Moving Average (SMA)
Wilder's Moving Average (RMA)
Triangular Moving Average (TMA)
These are ranked by the degree of reactivity of each method, with higher ones being more reactive (but less smooth).
Users can also select the smoothing method used by the signal line.
🔶 DETAILS
The RSI returns a normalized exponential average of price changes in the range (0, 100), which can be simply calculated as follows:
ema(d) / ema(|d|) × 50 + 50
where d represent the price changes. In order to put more emphasis on trends we can put higher weight on d . We can perform this on the occurrence of new higher highs/lower lows, and by replacing d with the rolling range instead (the rolling period used to detect the higher highs/lower lows is equal to the length setting).
🔶 SETTINGS
Length: Calculation period of the indicator
Method: Smoothing method used for the calculation of the indicator.
Source: Input source of the indicator
🔹 Signal Line
Smooth: Degree of smoothness of the signal line
Method: Smoothing method used to calculation the signal line.
Anit Momentum IndicatorAnit Momentum Indicator: A Powerful Trend Continuation Tool for Long-Only Strategies
The "Anit Momentum Indicator" (AMI) is a powerful technical analysis tool designed to assist traders in identifying potential trend continuation opportunities in the financial markets. Unlike traditional trend reversal indicators, AMI is specifically crafted for long-only strategies, making it an ideal tool for traders seeking to capture sustained uptrends.
Concepts and Functionality:
1. Momentum Calculation:
The Anit Momentum Indicator begins by calculating the momentum of the closing price over a specified period. Momentum represents the rate of price change, offering clues about the strength and direction of price movements during the chosen duration.
2. RSI for Trend Continuation:
The script then applies the RSI to the previously computed momentum values. The RSI is a well-known oscillator used to measure the speed and magnitude of price changes. By utilizing the RSI on momentum data, the Anit Momentum Indicator gains a distinct advantage in gauging the strength of price momentum, leading to more accurate trend evaluations.
3. Rescaling for Better Visualization:
To enhance visual clarity and maintain consistent representation, the RSI on Momentum is rescaled to range from 0 to 100. This normalization ensures that the indicator's values remain within a fixed range, making it easier for traders to identify crucial overbought and oversold regions.
How to Use the Indicator:
Long-Only Strategy:
The AMI is most effective in long-only strategies. Traders can deploy the indicator to identify promising opportunities to go long on a stock or asset. A long position is established when the AMI crosses above 50, signaling a robust upward momentum.
Trend Continuation Confirmation:
The AMI's ability to capture trend continuation opportunities allows traders to stay invested in an uptrend for an extended period. As long as the AMI remains above 50, the uptrend is considered intact, and traders may continue to hold the position.
Higher Timeframe Advantage:
The AMI's effectiveness is further enhanced on higher timeframes. Longer timeframes provide a more reliable and sustained view of the underlying trend, giving traders greater confidence in their long-only strategies.
Conclusion:
The Anit Momentum Indicator is a valuable tool for traders pursuing trend continuation strategies, specifically long-only approaches. By leveraging the concept of momentum and RSI, the AMI helps traders identify and participate in sustained uptrends. With its focus on trend continuation rather than reversals, the AMI can be a key component in building successful long-only trading strategies, especially on higher timeframes. Traders can use this indicator to stay invested in robust uptrends, maximizing their profit potential while minimizing exposure to counter-trend moves by staying long till AMI value is greater than 50,it is better to stay away or exit from the asst class when AMI value is less than 50.
Stochastic Zone Strength Trend [wbburgin](This script was originally invite-only, but I'd vastly prefer contributing to the TradingView community more than anything else, so I am making it public :) I'd much rather share my ideas with you all.)
The Stochastic Zone Strength Trend indicator is a very powerful momentum and trend indicator that 1) identifies trend direction and strength, 2) determines pullbacks and reversals (including oversold and overbought conditions), 3) identifies divergences, and 4) can filter out ranges. I have some examples below on how to use it to its full effectiveness. It is composed of two components: Stochastic Zone Strength and Stochastic Trend Strength.
Stochastic Zone Strength
At its most basic level, the stochastic Zone Strength plots the momentum of the price action of the instrument, and identifies bearish and bullish changes with a high degree of accuracy. Think of the stochastic Zone Strength as a much more robust equivalent of the RSI. Momentum-change thresholds are demonstrated by the "20" and "80" levels on the indicator (see below image).
Stochastic Trend Strength
The stochastic Trend Strength component of the script uses resistance in each candlestick to calculate the trend strength of the instrument. I'll go more into detail about the settings after my description of how to use the indicator, but there are two forms of the stochastic Trend Strength:
Anchored at 50 (directional stochastic Trend Strength):
The directional stochastic Trend Strength can be used similarly to the MACD difference or other histogram-like indicators : a rising plot indicates an upward trend, while a falling plot indicates a downward trend.
Anchored at 0 (nondirectional stochastic Trend Strength):
The nondirectional stochastic Trend Strength can be used similarly to the ADX or other non-directional indicators : a rising plot indicates increasing trend strength, and look at the stochastic Zone Strength component and your instrument to determine if this indicates increasing bullish strength or increasing bearish strength (see photo below):
(In the above photo, a bearish divergence indicated that the high Trend Strength predicted a strong downwards move, which was confirmed shortly after. Later, a bullish move upward by the Zone Strength while the Trend Strength was elevated predicated a strong upwards move, which was also confirmed. Note the period where the Trend Strength never reached above 80, which indicated a ranging period (and thus unprofitable to enter or exit)).
How to Use the Indicator
The above image is a good example on how to use the indicator to determine divergences and possible pivot points (lines and circles, respectively). I recommend using both the stochastic Zone Strength and the stochastic Trend Strength at the same time, as it can give you a robust picture of where momentum is in relation to the price action and its trajectory. Every color is changeable in the settings.
Settings
The Amplitude of the indicator is essentially the high-low lookback for both components.
The Wavelength of the indicator is how stretched-out you want the indicator to be: how many amplitudes do you want the indicator to process in one given bar.
A useful analogy that I use (and that I derived the names from) is from traditional physics. In wave motion, the Amplitude is the up-down sensitivity of the wave, and the Wavelength is the side-side stretch of the wave.
The Smoothing Factor of the settings is simply how smoothed you want the stochastic to be. It's not that important in most circumstances.
Trend Anchor was covered above (see my description of Trend Strength). The "Trend Transform MA Length" is the EMA length of the Trend Strength that you use to transform it into the directional oscillator. Think of the EMA being transformed onto the 50 line and then the Trend Strength being dragged relative to that.
Trend Transform MA Length is the EMA length you want to use for transforming the nondirectional Trend Strength (anchored at 0) into the directional Trend Strength (anchored at 50). I suggest this be the same as the wavelength.
Trend Plot Type can transform the Nondirectional Trend Strength into a line plot so that it doesn't murk up the background.
Finally, the colors are changeable on the bottom.
Explanation of Zone Strength
If you're knowledgeable in Pine Script, I encourage you to look at the code to try to understand the concept, as it's a little complicated. The theory behind my Zone Strength concept is that the wicks in every bar can be used create an index of bullish and bearish resistance, as a wick signifies that the price crossed above a threshold before returning to its origin. This distance metric is unique because most indicators/formulas for calculating relative strength use a displacement metric (such as close - open) instead of measuring how far the price actually moved (up and down) within a candlestick. This is what the Zone Strength concept represents - the hesitation within the bar that is not typically represented in typical momentum indicators.
In the script's code I have step by step explanations of how the formula is calculated and why it is calculated as such. I encourage you to play around with the amplitude and wavelength inputs as they can make the zone strength look very different and perform differently depending on your interests.
Enjoy!
Walker
[FC] Multi EMA Cross Alerts Fltered with RSI and StochThis script prints Green Dots and Red Dots on candle close using Faster EMA ( 5 ) and Slower EMA (10 ) filtering with RSI (50)+ Stochastic %K ( 20 to 80 ) Smoothning(3).
The idea behind is to you use dots for scalping on smaller timeframe(5) ,(10) etc but you can modify all values to better fit your needs.
Explaination for Green Dots and Red Dots:
---> Green dot : 5 Ema crosses above 10 Ema ( i.e faster EMA crosses above slower EMA which signals price is trying to move up
RSI value > 50 (filtering for quick move)
stoch %k value between 20 and 80 ( filtering to know there is leg left in the move and all movement is already not done)
---> Red dot : 5 Ema crosses below 10 Ema ( i.e faster EMA crosses above slower EMA which signals price is trying to move down
RSI value < 50 (filtering for quick move)
stoch %k value between 20 and 80 ( filtering to know there is leg left in the move and all movement is already not done)
Engulfing Pattern BUY and SELL SystemThis indicator is based on multiple parameters such as the Open, High, Low, and Close of candles. We add confluences such as SMMA crossovers, engulfing candles, and the number of pips that it has moved from it.
The main parameter is the DFS (Distance from SMMA). This will adjust the number of signals you'll get. This parameter is calculated based on the Open price of the signal bar and the 50 SMMA price. If the difference between these two values is greater than the input value, it will not be considered a signal.
The buy/sell signal consists of the following conditions:
1. Engulfing Candle based on conditions
2. SMMA crossover (21 and 50 periods)
3. For BUYS, the RSI value is greater than 49. For SELLS, the RSI value is less than 51.
4. Open price of the signal bar is less/greater than the 50 SMMA for SELLS/BUYS respectively.
5. DFS value is less than or equal to the input value
We recommend backtesting this on FX Pairs, and metals such as Gold. It is not well suited for Crypto or Indices.
Relative Trend Index (RTI) by Zeiierman█ Overview
The Relative Trend Index (RTI) developed by Zeiierman is an innovative technical analysis tool designed to measure the strength and direction of the market trend. Unlike some traditional indicators, the RTI boasts a distinctive ability to adapt and respond to market volatility, while still minimizing the effects of minor, short-term market fluctuations.
The Relative Trend Index blends trend-following and mean-reverting characteristics, paired with a customizable and intuitive approach to trend strength, and its sensitivity to price action makes this indicator stand out.
█ Benefits of using this RTI instead of RSI
The Relative Strength Index (RSI) and the Relative Trend Index (RTI) are both powerful technical indicators, each with its own unique strengths.
However, there are key differences that make the RTI arguably more sophisticated and precise, especially when it comes to identifying trends and overbought/oversold (OB/OS) areas.
The RSI is a momentum oscillator that measures the speed and change of price movements and is typically used to identify overbought and oversold conditions in a market. However, its primary limitation lies in its tendency to produce false signals during extended trending periods.
On the other hand, the RTI is designed specifically to identify and adapt to market trends. Instead of solely focusing on price changes, the RTI measures the relative positioning of the current closing price within its recent range, providing a more comprehensive view of market conditions.
The RTI's adaptable nature is particularly valuable. The user-adjustable sensitivity percentage allows traders to fine-tune the indicator's responsiveness, making it more resilient to sudden market fluctuations and noise that could otherwise produce false signals. This feature is advantageous in various market conditions, from trending to choppy and sideways-moving markets.
Furthermore, the RTI's unique method of defining OB/OS zones takes into account the prevailing trend, which can provide a more precise reflection of the market's condition.
While the RSI is an invaluable tool in many traders' toolkits, the RTI's unique approach to trend identification, adaptability, and enhanced definition of OB/OS zones can provide traders with a more nuanced understanding of market conditions and potential trading opportunities. This makes the RTI an especially powerful tool for those seeking to ride long-term trends and avoid false signals.
█ Calculations
In summary, while simple enough, the math behind the RTI indicator is quite powerful. It combines the quantification of price volatility with the flexibility to adjust the trend sensitivity. It provides a normalized output that can be interpreted consistently across various trading scenarios.
The math behind the Relative Trend Index (RTI) indicator is rooted in some fundamental statistical concepts: Standard Deviation and Percentiles.
Standard Deviation: The Standard Deviation is a measure of dispersion or variability in a dataset. It quantifies the degree to which each data point deviates from the mean (or average) of the data set. In this script, the standard deviation is computed on the 'close' prices over a specified number of periods. This provides a measure of the volatility in the price over that period. The higher the standard deviation, the more volatile the price has been.
Percentiles: The percentile is a measure used in statistics indicating the value below which a given percentage of observations in a group falls. After calculating the upper and lower trends for the last 'length' periods and sorting these values, the script uses the 'Sensitivity ' parameter to extract percentiles from these sorted arrays. This is a powerful concept because it allows us to adjust the sensitivity of our signals. By choosing different percentiles (controlled through the 'Sensitivity' parameter), we can decide whether we want to react only to extreme events (high percentiles) or be more reactive and consider smaller deviations from the norm as significant (lower percentiles).
Finally, the script calculates the Relative Trend Index value, which is essentially a normalized measure indicating where the current price falls between the upper and lower trend values. This simple ratio is incredibly powerful as it provides a standardized measure that can be used across different securities and market conditions to identify potential trading signals.
Core Components
Trend Data Count: This parameter denotes the number of data points used in the RTI's calculation, determining the trend length. A higher count captures a more extended market view (long-term trend), providing smoother results that are more resistant to sudden market changes. In contrast, a lower count focuses on more recent data (short-term trend), yielding faster responses to market changes, albeit at the cost of increased susceptibility to market noise.
Trend Sensitivity Percentage: This parameter is employed to select the indices within the trend arrays used for upper and lower trend definitions. By adjusting this value, users can affect the sensitivity of the trend, with higher percentages leading to a less sensitive trend.
█ How to use
The RTI plots a line that revolves around a mid-point of 50. When the RTI is above 50, it implies that the market trend is bullish (upward), and when it's below 50, it indicates a bearish (downward) trend. Furthermore, the farther the RTI deviates from the 50 line, the stronger the trend is perceived to be.
Bullish
Bearish
The RTI includes user-defined Overbought and Oversold levels. These thresholds suggest potential trading opportunities when they are crossed, serving as a cue for traders to possibly buy or sell. This gives the RTI an additional use case as a mean-reversion tool, in addition to being a trend-following indicator.
In short
Trend Confirmation and Reversals: If the percentage trend value is consistently closer to the upper level, it can indicate a strong uptrend. Similarly, if it's closer to the lower level, a downtrend may be in play. If the percentage trend line begins to move away from one trend line towards the other, it could suggest a potential trend reversal.
Identifying Overbought and Oversold Conditions: When the percentage trend value reaches the upper trend line (signified by a value of 1), it suggests an overbought condition - i.e., the price has been pushed up, perhaps too far, and could be due for a pullback, or indicating a strong positive trend. Conversely, when the percentage trend value hits the lower trend line (a value of 0), it indicates an oversold condition - the price may have been driven down and could be set to rebound, or indicate a strong negative trend. Traders often use these overbought and oversold signals as contrarian indicators, considering them potential signs to sell (in overbought conditions) or buy (in oversold conditions). If the RTI line remains overbought or oversold for an extended period, it indicates a strong trend in that direction.
█ Settings
One key feature of the RTI is its configurability. It allows users to set the trend data length and trend sensitivity.
The trend data length represents the number of data points used in the trend calculation. A longer trend data length will reflect a more long-term trend, whereas a shorter trend data length will capture short-term movements.
Trend sensitivity refers to the threshold for determining what constitutes a significant trend. High sensitivity levels will deem fewer price movements as significant, hence making the trend less sensitive. Conversely, low sensitivity levels will deem more price movements as significant, hence making the trend more sensitive.
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
Selective Moving Average: DemoThis indicator produces a conditional moving average based off of your chosen inputs. For example, you can create an EMA that only takes into account closing prices when the 14 period RSI is greater than 50, or a VWMA that tracks hl2 values when the hl2 value is within one standard deviation from the mean. The possibilities are highly configurable to your liking. Please comment below additional conditions you might like me to add to the moving average and I will try my best to get to your feedback.
The following parameters are configurable:
--> Source: This is the source of the moving average that you want to create. You can use external sources if you have another indicator on your chart.
--> Condition: This is the condition that you want to take into account when the moving average is calculating itself. For instance, I have the following conditions pre-built (more to come): Source within 1 standard deviation of the mean (of the source), Source within 2 standard deviations of the mean (of the source), Positive volume, Negative volume, RSI greater than 50, RSI less than 50, Candlestick length greater than body.
--> Length: The length of the selective moving average. For conditions that occur infrequently, a larger length may be necessary to improve accuracy.
--> Average type: The type of moving average (SMA, EMA, RMA, etc.) that you wish to create
--> Condition length: An optional parameter if you are using a condition that depends on a length itself, i.e. the RSI - here you can change the RSI length. The RSI source will be the moving average source, but future updates may separate the two.
Bollinger Bands, RSI, and MA StrategyThe "Bollinger Bands, RSI and MA Strategy" is a trend-following strategy that combines the Bollinger Bands indicator, the Relative Strength Index (RSI), and a moving average (MA). It aims to identify potential entry and exit points in the market based on price volatility, momentum, and trend.
The strategy uses two Bollinger Bands with different standard deviations to create price channels. The default settings for the Bollinger Bands are a length of 20 periods and a standard deviation of 2.0. The upper and lower bands of the Bollinger Bands serve as dynamic resistance and support levels, respectively.
The RSI indicator is employed to gauge the strength of price momentum.
The strategy also incorporates a 50-period moving average (MA) to help identify the overall trend direction. When the price is above the MA, it suggests an uptrend, and when the price is below the MA, it suggests a downtrend.
The entry conditions for long trades are when the RSI is above the overbought level and there is no contraction in the Bollinger Bands. For short trades, the entry conditions are when the RSI is below the oversold level and there is no contraction in the Bollinger Bands.
The exit conditions for long trades are when the RSI drops below the overbought level or when the price closes below the 50-period MA.
For short trades, the exit conditions are when the RSI goes above the oversold level or when the price closes above the 50-period MA.
The strategy generates alerts for potential long and short entry signals, as well as for exit signals when the specified conditions are met. These alerts can be used to receive notifications or take further actions, such as placing trades manually or using automated trading systems.
It is important to note that this strategy serves as a starting point and should be thoroughly backtested and validated with historical data before applying it to live trading. Additionally, it is recommended to consider risk management techniques, including setting appropriate stop-loss and take-profit levels, to effectively manage trades.
FibonRSI / ErkOziHello,
This software is a technical analysis script written in the TradingView Pine language. The script creates a trading indicator based on Fibonacci retracement levels and the RSI indicator, providing information about price movements and asset volatility by using Bollinger Bands.
There are many different scripts in the market that draw RSI and Fibonacci retracement levels. However, this script was originally designed by me and shared publicly on TradingView.
***The indicator uses RSI (Relative Strength Index) and Bollinger Bands (BB) as the basis for the FibonRSI strategy. RSI measures the strength of a price movement, and BB measures the volatility of an asset. The FibonRSI strategy is based on the idea that the Fibonacci ratios and RSI can be used to predict a asset's price retracement levels.
***The script allows for various parameters to be adjusted. Users can specify the price source type and adjust the periods for RSI and Bollinger Bands. The standard deviation number for Bollinger Bands can also be customized.
***The script calculates the current RSI indicator position and the basic, upper, and lower levels of Bollinger Bands. It then calculates and draws the Fibonacci retracement levels. The color of the RSI line is determined by the upper and lower distribution levels of Bollinger Bands. Additionally, the color of the Fibonacci retracement levels can also be customized by the user.
***This script can be used to determine potential buy and sell signals using Fibonacci retracement levels and RSI. For example, when the RSI is oversold and the price is close to a Fibonacci retracement level, it can be interpreted as a buying opportunity. Similarly, when the RSI is overbought and the price is close to a Fibonacci retracement level, it can be interpreted as a selling opportunity.
***The script takes input parameters such as the price source used for calculation, the period for the RSI indicator, the period for the Moving Average in Bollinger Bands, and the number of standard deviations used in Bollinger Bands.
***The script's conditions include elements such as calculating the current position of the RSI indicator, calculating the upper and lower Bollinger Bands, calculating the dispersion factor, and calculating Fibonacci levels.
***The parameters in the code can be adjusted for calculation, including the price type used, the RSI period, the Moving Average period for BB, and the standard deviation count for BB. After this, the current position of the RSI, Moving Average, and standard deviation for BB are calculated. After calculating the upper and lower BB, the levels above and below the average are calculated using a specific dispersion constant.
CONDITIONS FOR THE SCRIPT
current_rsi = ta.rsi(src, for_rsi) // Current position of the RSI indicator
basis = ta.ema(current_rsi, for_ma)
dev = for_mult * ta.stdev(current_rsi, for_ma)
upper = basis + dev
lower = basis - dev
dispersion = 1
disp_up = basis + (upper - lower) * dispersion
disp_down = basis - (upper - lower) * dispersion
// Fibonacci Levels
f100 = basis + (upper - lower) * 1.0
f78 = basis + (upper - lower) * 0.78
f65 = basis + (upper - lower) * 0.65
f50 = basis
f35 = basis - (upper - lower) * 0.65
f23 = basis - (upper - lower) * 0.78
f0 = basis - (upper - lower) * 1.0
***When calculating Fibonacci levels, the distance between the average of BB and the upper and lower BB is used. These levels are 0%, 23.6%, 35%, 50%, 65%, 78.6%, and 100%. Finally, the RSI line that changes color according to a specific RSI position, Fibonacci levels, and BB are visualized. Additionally, the levels of 70, 30, and 50 are also shown.
The script then sets the color of the RSI position according to the EMA and draws Bollinger Bands, RSI, Fibonacci levels, and the 70, 30, and 50 levels.
In conclusion, this script enables traders to analyze market trends and make informed decisions. It can also be customized to suit individual trading strategies.
This script analyzes the RSI indicator using Bollinger Bands and Fibonacci levels. The default settings are 14 periods for RSI, 233 periods and 2 standard deviations for BB. The MA period inside BB is selected as the BB period and is used when calculating Fibonacci levels.
***The reason for selecting these settings is to provide enough time for BB period to confirm a possible trend. Additionally, the MA period inside BB is matched with the BB period and used when calculating Fibonacci levels.
***Fibonacci levels are calculated from the distance between the upper and lower bands of BB and show how RSI movement is related to these levels. Better results can be achieved when RSI periods are set to Fibonacci numbers such as 21, 55, and 89. Therefore, the use of Fibonacci numbers is recommended when adjusting RSI periods. Fibonacci numbers are among the technical analysis tools that can capture the reflection of naturally occurring movements in the market. Therefore, the use of Fibonacci numbers often helps to better track fluctuations in the market.
Finally, the indicator also displays the 70 and 30 levels and the middle level (50) with Fibonacci levels drawn in circles. Changing these settings can help optimize the Fibonacci levels and further improve the indicator.
Thank you in advance for your suggestions and opinions......
EMA bridge and dashboard with color coding.
Summary:
This is a custom moving average indicator script that calculates and plots different Exponential Moving Averages (EMAs) based on user-defined input values. The script also displays MACD and RSI, and provides a table that displays the current trend of the market in a color-coded format.
Explanation:
- The script starts by defining the name of the indicator and the different inputs that the user can customize.
- The inputs include bridge values for three different EMAs (high, close, and low), and four other EMAs (5, 50, 100, and 200).
- The script assigns values to these inputs using the `ta.ema()` function.
- Additionally, the script calculates EMAs for higher timeframes (3m, 5m, 15m, and 30m).
- The script then plots the EMAs on the chart using different colors and line widths.
- The script defines conditions for going long or short based on the crossover of two EMAs.
- It plots triangles above or below bars to indicate the crossover events.
- The script also calculates and displays the RSI and MACD of the asset.
- Finally, the script creates a table that displays the current trend of the market in a color-coded format. The table can be positioned on the top, middle, or bottom of the chart and on the left, center, or right side of the chart.
Parameters:
- i_ema_h: Bridge value for high EMA (default=34)
- i_ema_c: Bridge value for close EMA (default=34)
- i_ema_l: Bridge value for low EMA (default=34)
- i_ema_5: Value for 5-period EMA (default=5)
- i_ema_50: Value for 50-period EMA (default=50)
- i_ema_100: Value for 100-period EMA (default=100)
- i_ema_200: Value for 200-period EMA (default=200)
- i_f_ema: Value for fast EMA used in MACD calculation (default=9)
- i_s_ema: Value for slow EMA used in MACD calculation (default=21)
- fastInput: Value for fast length used in MACD calculation (default=7)
- slowInput: Value for slow length used in MACD calculation (default=14)
- tableYposInput: Vertical position of the table (options: top, middle, bottom; default=middle)
- tableXposInput: Horizontal position of the table (options: left, center, right; default=right)
- bullColorInput: Color of the table cell for a bullish trend (default=green)
- bearColorInput: Color of the table cell for a bearish trend (default=red)
- neutColorInput: Color of the table cell for a neutral trend (default=white)
- neutColorLabelInput: Color of the label for neutral trend in the table (default=fuchsia)
Usage:
To use this script, simply copy and paste it into the Pine Editor on TradingView. You can then customize the input values to your liking or leave them at their default values. Once you have added the script to your chart, you can view the EMAs, MACD, RSI, and trend table on the chart. The trend table provides a quick way to assess the current trend of the market at a glance.
