Best of Option Indicator - Manoj WadekarPlot this indicator for both CALL and PUT options and buy only when color of candle is YELLOW and above BLACK line.
Educational
Candle 1 2 3 on XAUUSD (by Veronica)Description
Discover the Candle 1 2 3 Strategy, a simple yet effective trading method tailored exclusively for XAUUSD on the 15-minute timeframe. Designed by Veronica, this strategy focuses on identifying key reversal and continuation patterns during the London and New York sessions, making it ideal for traders who prioritise high-probability entries during these active market hours.
Key Features:
1. Session-Specific Trading:
The strategy operates strictly during London (03:00–06:00 UTC) and New York (08:30–12:30 UTC) sessions, where XAUUSD tends to show higher volatility and clearer price movements.
Pattern Criteria:
- Works best if the first candle is NOT a pin bar or a doji.
- Third candle should either:
a. Be a marubozu (large body with minimal wicks).
a. Have a significant body with wicks, ensuring the close of the third candle is above Candle 2 (for Buy) or below Candle 2 (for Sell).
Callout Labels and Alerts:
Automatic Buy and Sell labels are displayed on the chart during qualifying sessions, ensuring clarity for decision-making.
Integrated alerts notify you of trading opportunities in real-time.
Risk Management:
Built-in Risk Calculator to estimate lot sizes based on your account size, risk percentage, and stop-loss levels.
Customizable Table:
Displays your calculated lot size for various stop-loss pip values, making risk management seamless and efficient.
How to Use:
1. Apply the indicator to XAUUSD (M15).
2. Focus on setups appearing within the London and New York sessions only.
3. Ensure the first candle is neither a pin bar nor a doji.
4. Validate the third candle's body placement:
For a Buy, the third candle’s close must be above the second candle.
For a Sell, the third candle’s close must be below the second candle.
5. Use the generated alerts to streamline your entry process.
Notes:
This strategy is meant to complement your existing knowledge of market structure and price action.
Always backtest thoroughly and adjust parameters to fit your personal trading style and risk tolerance.
Credit:
This strategy is the intellectual property of Veronica, developed specifically for XAUUSD (M15) traders seeking precision entries during high-volume sessions.
Fusion Signal ProFusion Signal Pro
Your All-in-One Trading Powerhouse
Say goodbye to cluttered charts and hello to precision trading. Fusion Signal Pro is the ultimate tool for traders who want to simplify their strategy without sacrificing accuracy. By combining the power of RSI, Parabolic SAR, MACD, Stochastic Oscillator, and EMAs, this indicator delivers crystal-clear signals and actionable insights—all in one sleek package.
What’s Under the Hood?
Fusion Signal Pro integrates 5 powerhouse indicators into a single, easy-to-use tool:
Relative Strength Index (RSI)
Spot overbought and oversold conditions like a pro.
Get buy signals when RSI crosses above the oversold zone and sell signals when it drops below overbought.
Parabolic SAR
Track trends and reversals with precision.
Visualized directly on your chart for seamless trend analysis.
MACD (Moving Average Convergence Divergence)
Master momentum and trend strength.
Buy/Sell signals trigger on crossovers between the MACD line and signal line.
Stochastic Oscillator
Gauge momentum and overbought/oversold levels.
Toggle this feature on or off to keep your chart clean and focused.
Exponential Moving Averages (EMAs)
Short and long EMAs for trend confirmation.
Use crossover signals for long-term strategies or trend-following setups.
Why Fusion Signal Pro?
Customizable AF: Tweak every setting to match your trading style—whether you’re a scalper, swing trader, or long-term investor.
Clean & Focused: Enable or disable components to declutter your chart and focus on what matters.
Flexible Display: Plot RSI, MACD, and Stochastic in a separate pane or keep them off the chart entirely.
Pro-Level Precision: Designed to work seamlessly with Heikin-Ashi candles for smoother trends and sharper signals.
Pro Tips for Maximum Gains
Pair with Heikin-Ashi: For next-level trend clarity, use Fusion Signal Pro with Heikin-Ashi candles. They smooth out price action, making it easier to spot reversals and ride trends.
Adjust for Timeframes: Shorter settings for scalping, longer settings for swing trading.
Tweak for Volatility: Fine-tune overbought/oversold levels and EMA lengths to match market conditions.
Key Settings Explained
RSI Settings
Length: Shorter = more sensitive; Longer = smoother.
Overbought/Oversold Levels: Lower thresholds = earlier signals (but more noise).
Parabolic SAR Settings
Start, Increment, Maximum: Control sensitivity. Smaller values = less reactive; larger values = more responsive to trends.
MACD Settings
Fast/Slow Lengths: Shorter = faster signals (scalping); Longer = smoother signals (swing trading).
Signal Length: Higher values = less noise but delayed signals.
Stochastic Settings
K & D Lengths: Shorter = faster signals; Longer = smoother signals.
Overbought/Oversold Levels: Adjust for volatile markets.
EMA Settings
Short/Long Lengths: Short EMAs = quick reactions; Long EMAs = trend confirmation.
Disclaimer
Fusion Signal Pro is a powerful tool, but it’s not a crystal ball. Always combine it with solid risk management, additional analysis, and your trading instincts. Trade smart, stay sharp, and let Fusion Signal Pro guide your way.
High Volatility Crypto StrategyThis strategy indicatore use for high volatile market like crypto for 1 min, 5 min and 15 min interval chart
15 Min Breakout of Previous 75 Min Candle with SMMA and VWAPBreakout Candle finder with Signals & Long term EMAs Trend direction
Multi Moving Averagesbrief description
Labeled Multi-Moving Average Cloud with Cross Signals
Overview
This Trading View indicator is crafted to enhance the learning of trading strategies by integrating seven distinct types of moving averages (SMA, EMA, WMA, RMA, HMA, VWMA). Each moving average line is clearly labeled with its calculation length, and the indicator features a cloud that visually represents the area between two selected moving average lines, highlighting crossovers and crossdowns.
Features
Diverse Moving Averages: The indicator includes SMA, EMA, WMA, RMA, HMA, and VWMA to provide a comprehensive analysis of price trends.
Calculation Length Labels: Each moving average displays its calculation length directly on the chart for easy reference. If a fixed time frame differs from the chart's time frame, this is also indicated.
Cloud Visualization: A colored cloud appears between two selected moving average lines, offering a visual representation of market dynamics.
Cross Markers: The indicator marks crossovers between two selected moving averages, helping traders identify potential change in trend.
How to Use This Indicator
Select Your Moving Averages: Customize which moving averages you want to display and set the calculation lengths according to your trading strategy.
Choose a Fixed Time frame: Determine the fixed time frame for your analysis and decide whether to label each moving average line on the chart.
Analyze the Cloud: Use the cloud to assess market sentiment and identify potential trend reversals.
Monitor Cross Signals: Keep an eye on crossovers for timely entry and exit points in your trades.
Conclusion
This indicator combines multiple moving averages with cloud visualization and crossover signals, making it an invaluable tool for traders looking to enhance their analysis and decision-making processes. By leveraging these features, you can better navigate market trends and optimize your trading strategies.
INFINITE 2M ADX ( POLICKY )Always shows 2m ADX this helps to be on different time frames and still be able to see what exactly the 2m is doing
4EMAs+OpenHrs+FOMC+CPIThis script displays 4 custom EMAs of your choice based on the Pine script standard ema function.
Additionally the following events are shown
1. Opening hours for New York Stock exchange
2. Opening Time for London Stock exchange
3. US CPI Release Dates
4. FOMC press conference dates
5. FOMC meeting minutes release dates
I have currently added FOMC and CPI Dates for 2025 but will keep updating in January of every year (at least as long as I stay in the game :D)
Moving Average Convergence Divergence 3 lineThis adds an additional line to the traditional MACD. The goal is to better identify entry and exit times. I am going to adjust the time frame for optimal on a 1hr chart and 4hr chart. Primary Goal is the identify low risk entry for swing trades lasting one day to two weeks.
Enhanced Support Level StrategyEnhanced Support Level Strategy. Testing the strategy to confirm if it works according to plan. This is a strategy in test. You are fully responsible for the outcome of your trades should you use this strategy.
Indicators Table[Robinson0707]
I try to make a table for simple indicator. I hope you lile it. For now I just add classic, fibonacci and wodie pivont point. And ı use Exponanctal moving avera. If you want you can open it as a plot. Also I ad Benjamin GRAHAM's valuation formula
Combined Multi-Timeframe EMA OscillatorThis script aims to visualize the strength of bullish or bearish trends by utilizing a mix of 200 EMA across multiple timeframes. I've observed that when the multi-timeframe 200 EMA ribbon is aligned and expanding, the uptrend usually lasts longer and is safer to enter at a pullback for trend continuation. Similarly, when the bands are expanding in reverse order, the downtrend holds longer, making it easier to sell the pullbacks.
In this script, I apply a purely empirical and experimental method: a) Ranking the position of each of the above EMAs and turning it into an oscillator. b) Taking each 200 EMA on separate timeframes, turning it into a stochastic-like oscillator, and then averaging them to compute an overall stochastic.
To filter a bullish signal, I use the bullish crossover between these two aggregated oscillators (default: yellow and blue on the chart) which also plots a green shadow area on the screen and I look for buy opportunities/ ignore sell opportunities while this signal is bullish. Similarly, a bearish crossover gives us a bearish signal which also plots a red shadow area on the screen and I only look for sell opportunities/ ignore any buy opportunities while this signal is bearish.
Note that directly buying the signal as it prints can lead to suboptimal entries. The idea behind the above is that these crossovers point on average to a stronger trend; however, a trade should be initiated on the pullbacks with confirmation from momentum and volume indicators and in confluence with key areas of support and resistance and risk management should be used in order to protect your position.
Disclaimer: This script does not constitute certified financial advice, the current work is purely experimental, use at your own discretion.
TTZConcept Currency Lot Calculator
The TTZConcept Currency Pair Lot Size Calculator is a must-have tool for traders looking to optimize their lot sizes based on their risk management strategy. By simply inputting the entry price and stop loss from your trading setup, this calculator automatically generates the ideal lot size, helping you control your risk while ensuring your trade size fits your account balance and preferred risk percentage.
Key Features:
Automatic Lot Size Calculation: Enter your entry price and stop loss directly from your trading setup, and the tool will automatically calculate the ideal lot size for your trade.
Precise Risk Management: Based on your account balance and risk percentage (e.g., 1%, 2%), the tool helps you size your position accurately to stay within your risk limits.
Customizable Inputs: Adjust your account balance, leverage, and risk percentage settings to ensure the lot size generated is in line with your trading profile.
Manual Take Profit: While the tool focuses on lot size calculation and risk, you can manually set your take profit levels to match your trading strategy.
Works with Any Currency Pair: Whether you're trading EUR/USD, GBP/JPY, or any other pair, this tool will provide the precise lot size for your trade based on the pip value of your selected pair.
User-Friendly Interface: Easily input your entry and stop loss, and let the tool handle the calculations. With just a few adjustments, you get the perfect lot size in seconds.
How It Works:
1. Open the TTZConcept Currency Lot Size Calculator on TradingView.
2. Set the Entry: Enter the entry price from your trading setup. This is the price where you plan to open the trade.
3. Set the Stop Loss: Enter the stop loss level from your trading setup. This is the price level where you’ll close the trade if the market moves against you.
4. Let the Tool Calculate the Lot Size: Based on your entry price, stop loss, and account balance, the calculator will automatically generate the ideal lot size to match your risk profile.
5. **Adjust Your Risk & Balance: Modify your account balance, risk percentage (e.g., 1%, 2%), and leverage to fit your trading plan. The tool will update the lot size accordingly.
6. Manual Take Profit: You can manually set your take profit level based on your strategy. The tool will focus on lot size and risk, while you control your profit targets.
Why Use This Tool?
Precise Risk Management: This tool ensures that each trade’s position size is tailored to your desired risk, protecting your account from overexposure.
Simple and Fast: Forget about complicated calculations. Just input your entry and stop loss, and let the tool handle the rest.
Customizable for Your Needs: You can adjust the account balance, risk percentage, and leverage settings to match your unique trading style.
Manual Control of TP: While the tool handles position sizing, you can still set your own take profit levels manually, keeping full control over your trade.
Versatile for Any Currency Pair: Works with any currency pair, giving you flexibility no matter which market you're trading.
Perfect for:
- Forex traders who want precise position sizing
- Beginners seeking a reliable way to manage risk and understand lot sizing
- Experienced traders who need a quick and accurate lot size calculation tool
- Traders who prefer manually setting stop loss and take profit targets
India VIXThe VIX chart represents the Volatility Index, commonly referred to as the "Fear Gauge" of the stock market. It measures the market's expectations of future volatility over the next 30 days, based on the implied volatility of NSE index options. The VIX is often used as an indicator of investor sentiment, reflecting the level of fear or uncertainty in the market.
Here’s a breakdown of what you might observe on a typical VIX chart:
VIX Value: The y-axis typically represents the VIX index value, with higher values indicating higher levels of expected market volatility (more fear or uncertainty), and lower values signaling calm or stable market conditions.
VIX Spikes: Large spikes in the VIX often correspond to market downturns or periods of heightened uncertainty, such as during financial crises or major geopolitical events. A high VIX is often associated with a drop in the stock market.
VIX Drops: A decline in the VIX indicates a reduction in expected market volatility, usually linked with periods of market calm or rising stock prices.
Trend Analysis: Technical traders might use moving averages or other indicators on the VIX chart to assess the potential for future market movements.
Inverse Relationship with the Stock Market: Typically, there is an inverse correlation between the VIX and the stock market. When stocks fall sharply, volatility increases, and the VIX tends to rise. Conversely, when the stock market rallies or remains stable, the VIX tends to fall.
A typical interpretation would be that when the VIX is low, the market is relatively stable, and when the VIX is high, the market is perceived to be uncertain or volatile.
Market Turn Breakout Strategy OptimizerThis is a script made for a friend of mine. It is intended to be used as a visual tool to see which combination of RR is best for a Breakout Strategy he made.
Trend-Based Signals (NASDAQ) - LA CLAVE ESTÁ EN NO RENDIRSEOrlando Pereira
// Highlight Time Zones
in_zone1 = (hour == 8 and minute >= 30 and minute <= 35) // 8:30 am to 8:36 am EST
in_zone2 = (hour == 8 and minute > 35) or (hour == 9) or (hour == 10 and minute == 0) // 8:36 am to 10:00 am EST
bgcolor(in_zone1 ? color_zone1 : na, title="Zone 1 Background")
bgcolor(in_zone2 ? color_zone2 : na, title="Zone 2 Background")
// Display motivational message
if bar_index == na
label.new(bar_index, high, "LA CLAVE ESTÁ EN NO RENDIRSE",
style=label.style_label_center,
color=color.orange,
textcolor=color.black,
size=size.large)
Buy and Sell SignalInputs:
lengthMA: Moving average length for trend detection.
lengthRSI: RSI period for momentum analysis.
volumeMultiplier: Multiplier for identifying volume spikes.
atrMultiplier: Multiplier for determining stop-loss levels using ATR.
Buy Conditions:
A bullish crossover is detected when:
The price is above the moving average.
RSI crosses above 50 (bullish momentum).
A volume spike is present.
Sell Conditions:
A bearish crossover is detected when:
The price is below the moving average.
RSI crosses below 50 (bearish momentum).
A volume spike is present.
Stop Loss Levels:
For buy signals, a stop loss is set at close - (ATR × ATR multiplier).
For sell signals, a stop loss is set at close + (ATR × ATR multiplier).
Visual Signals:
Buy signals are plotted as green triangles below bars.
Sell signals are plotted as red triangles above bars.
A moving average line is plotted for trend reference.
Alerts:
Alerts notify when buy or sell conditions are met.
Crypto Market Trend Analysis This indicator is a multi-asset market analysis tool that evaluates trends, RSI, and confluence across various assets, providing actionable insights into the current market conditions. It calculates a score and trend signals for multiple assets, including DXY, USDT dominance, BTC, BTC dominance, TOTAL market cap, and specific altcoins like HBAR and its pairings.
Key Features:
Multi-Asset Analysis:
Analyzes multiple metrics such as DXY, BTC, TOTAL market caps, and specific altcoins.
Provides a clear breakdown of trend directions (Bull/Bear), RSI values, and previous conditions for each asset.
Custom Scoring System:
Calculates a score for each asset using a weighted system based on:
Moving averages (37 and 200-period).
RSI thresholds (e.g., >60 for bullish, <40 for bearish).
Relative Volume (RVOL).
ADX values for trend strength.
Bullish and bearish divergences detected using RSI and price.
The score categorizes the trend into five levels:
Strong Bull: High bullish confidence.
Bull: Moderately bullish conditions.
Neutral: Mixed or undecided market state.
Bear: Moderately bearish conditions.
Strong Bear: High bearish confidence.
RSI-Based Trend Insights:
Evaluates whether RSI is trending higher or lower, combining this with price and volume metrics to strengthen trend detection.
Divergence Detection:
Identifies bullish divergences when prices make lower lows while RSI makes higher lows.
Identifies bearish divergences when prices make higher highs while RSI makes lower highs.
Confluence Across Metrics:
Combines individual asset scores to provide a comprehensive view of market sentiment and strength across key assets.
For example:
If BTC and TOTAL both show bullish trends with rising RSI, the market-wide confluence suggests stronger confidence in the bullish scenario.
Visualization:
Displays clear metrics such as trend direction, RSI values, and their corresponding previous states in a visually organized table format.
Color coding (e.g., green for bullish, red for bearish) enhances readability.
Accurate Bollinger Bands mcbw_ [True Volatility Distribution]The Bollinger Bands have become a very important technical tool for discretionary and algorithmic traders alike over the last decades. It was designed to give traders an edge on the markets by setting probabilistic values to different levels of volatility. However, some of the assumptions that go into its calculations make it unusable for traders who want to get a correct understanding of the volatility that the bands are trying to be used for. Let's go through what the Bollinger Bands are said to show, how their calculations work, the problems in the calculations, and how the current indicator I am presenting today fixes these.
--> If you just want to know how the settings work then skip straight to the end or click on the little (i) symbol next to the values in the indicator settings window when its on your chart <--
--------------------------- What Are Bollinger Bands ---------------------------
The Bollinger Bands were formed in the 1980's, a time when many retail traders interacted with their symbols via physically printed charts and computer memory for personal computer memory was measured in Kb (about a factor of 1 million smaller than today). Bollinger Bands are designed to help a trader or algorithm see the likelihood of price expanding outside of its typical range, the further the lines are from the current price implies the less often they will get hit. With a hands on understanding many strategies use these levels for designated levels of breakout trades or to assist in defining price ranges.
--------------------------- How Bollinger Bands Work ---------------------------
The calculations that go into Bollinger Bands are rather simple. There is a moving average that centers the indicator and an equidistant top band and bottom band are drawn at a fixed width away. The moving average is just a typical moving average (or common variant) that tracks the price action, while the distance to the top and bottom bands is a direct function of recent price volatility. The way that the distance to the bands is calculated is inspired by formulas from statistics. The standard deviation is taken from the candles that go into the moving average and then this is multiplied by a user defined value to set the bands position, I will call this value 'the multiple'. When discussing Bollinger Bands, that trading community at large normally discusses 'the multiple' as a multiplier of the standard deviation as it applies to a normal distribution (gaußian probability). On a normal distribution the number of standard deviations away (which trades directly use as 'the multiple') you are directly corresponds to how likely/unlikely something is to happen:
1 standard deviation equals 68.3%, meaning that the price should stay inside the 1 standard deviation 68.3% of the time and be outside of it 31.7% of the time;
2 standard deviation equals 95.5%, meaning that the price should stay inside the 2 standard deviation 95.5% of the time and be outside of it 4.5% of the time;
3 standard deviation equals 99.7%, meaning that the price should stay inside the 3 standard deviation 99.7% of the time and be outside of it 0.3% of the time.
Therefore when traders set 'the multiple' to 2, they interpret this as meaning that price will not reach there 95.5% of the time.
---------------- The Problem With The Math of Bollinger Bands ----------------
In and of themselves the Bollinger Bands are a great tool, but they have become misconstrued with some incorrect sense of statistical meaning, when they should really just be taken at face value without any further interpretation or implication.
In order to explain this it is going to get a bit technical so I will give a little math background and try to simplify things. First let's review some statistics topics (distributions, percentiles, standard deviations) and then with that understanding explore the incorrect logic of how Bollinger Bands have been interpreted/employed.
---------------- Quick Stats Review ----------------
.
(If you are comfortable with statistics feel free to skip ahead to the next section)
.
-------- I: Probability distributions --------
When you have a lot of data it is helpful to see how many times different results appear in your dataset. To visualize this people use "histograms", which just shows how many times each element appears in the dataset by stacking each of the same elements on top of each other to form a graph. You may be familiar with the bell curve (also called the "normal distribution", which we will be calling it by). The normal distribution histogram looks like a big hump around zero and then drops off super quickly the further you get from it. This shape (the bell curve) is very nice because it has a lot of very nifty mathematical properties and seems to show up in nature all the time. Since it pops up in so many places, society has developed many different shortcuts related to it that speed up all kinds of calculations, including the shortcut that 1 standard deviation = 68.3%, 2 standard deviations = 95.5%, and 3 standard deviations = 99.7% (these only apply to the normal distribution). Despite how handy the normal distribution is and all the shortcuts we have for it are, and how much it shows up in the natural world, there is nothing that forces your specific dataset to look like it. In fact, your data can actually have any possible shape. As we will explore later, economic and financial datasets *rarely* follow the normal distribution.
-------- II: Percentiles --------
After you have made the histogram of your dataset you have built the "probability distribution" of your own dataset that is specific to all the data you have collected. There is a whole complicated framework for how to accurately calculate percentiles but we will dramatically simplify it for our use. The 'percentile' in our case is just the number of data points we are away from the "middle" of the data set (normally just 0). Lets say I took the difference of the daily close of a symbol for the last two weeks, green candles would be positive and red would be negative. In this example my dataset of day by day closing price difference is:
week 1:
week 2:
sorting all of these value into a single dataset I have:
I can separate the positive and negative returns and explore their distributions separately:
negative return distribution =
positive return distribution =
Taking the 25th% percentile of these would just be taking the value that is 25% towards the end of the end of these returns. Or akin the 100%th percentile would just be taking the vale that is 100% at the end of those:
negative return distribution (50%) = -5
positive return distribution (50%) = +4
negative return distribution (100%) = -10
positive return distribution (100%) = +20
Or instead of separating the positive and negative returns we can also look at all of the differences in the daily close as just pure price movement and not account for the direction, in this case we would pool all of the data together by ignoring the negative signs of the negative reruns
combined return distribution =
In this case the 50%th and 100%th percentile of the combined return distribution would be:
combined return distribution (50%) = 4
combined return distribution (100%) = 10
Sometimes taking the positive and negative distributions separately is better than pooling them into a combined distribution for some purposes. Other times the combined distribution is better.
Most financial data has very different distributions for negative returns and positive returns. This is encapsulated in sayings like "Price takes the stairs up and the elevator down".
-------- III: Standard Deviation --------
The formula for the standard deviation (refereed to here by its shorthand 'STDEV') can be intimidating, but going through each of its elements will illuminate what it does. The formula for STDEV is equal to:
square root ( (sum ) / N )
Going back the the dataset that you might have, the variables in the formula above are:
'mean' is the average of your entire dataset
'x' is just representative of a single point in your dataset (one point at a time)
'N' is the total number of things in your dataset.
Going back to the STDEV formula above we can see how each part of it works. Starting with the '(x - mean)' part. What this does is it takes every single point of the dataset and measure how far away it is from the mean of the entire dataset. Taking this value to the power of two: '(x - mean) ^ 2', means that points that are very far away from the dataset mean get 'penalized' twice as much. Points that are very close to the dataset mean are not impacted as much. In practice, this would mean that if your dataset had a bunch of values that were in a wide range but always stayed in that range, this value ('(x - mean) ^ 2') would end up being small. On the other hand, if your dataset was full of the exact same number, but had a couple outliers very far away, this would have a much larger value since the square par of '(x - mean) ^ 2' make them grow massive. Now including the sum part of 'sum ', this just adds up all the of the squared distanced from the dataset mean. Then this is divided by the number of values in the dataset ('N'), and then the square root of that value is taken.
There is nothing inherently special or definitive about the STDEV formula, it is just a tool with extremely widespread use and adoption. As we saw here, all the STDEV formula is really doing is measuring the intensity of the outliers.
--------------------------- Flaws of Bollinger Bands ---------------------------
The largest problem with Bollinger Bands is the assumption that price has a normal distribution. This is assumption is massively incorrect for many reasons that I will try to encapsulate into two points:
Price return do not follow a normal distribution, every single symbol on every single timeframe has is own unique distribution that is specific to only itself. Therefore all the tools, shortcuts, and ideas that we use for normal distributions do not apply to price returns, and since they do not apply here they should not be used. A more general approach is needed that allows each specific symbol on every specific timeframe to be treated uniquely.
The distributions of price returns on the positive and negative side are almost never the same. A more general approach is needed that allows positive and negative returns to be calculated separately.
In addition to the issues of the normal distribution assumption, the standard deviation formula (as shown above in the quick stats review) is essentially just a tame measurement of outliers (a more aggressive form of outlier measurement might be taking the differences to the power of 3 rather than 2). Despite this being a bit of a philosophical question, does the measurement of outlier intensity as defined by the STDEV formula really measure what we want to know as traders when we're experiencing volatility? Or would adjustments to that formula better reflect what we *experience* as volatility when we are actively trading? This is an open ended question that I will leave here, but I wanted to pose this question because it is a key part of what how the Bollinger Bands work that we all assume as a given.
Circling back on the normal distribution assumption, the standard deviation formula used in the calculation of the bands only encompasses the deviation of the candles that go into the moving average and have no knowledge of the historical price action. Therefore the level of the bands may not really reflect how the price action behaves over a longer period of time.
------------ Delivering Factually Accurate Data That Traders Need------------
In light of the problems identified above, this indicator fixes all of these issue and delivers statistically correct information that discretionary and algorithmic traders can use, with truly accurate probabilities. It takes the price action of the last 2,000 candles and builds a huge dataset of distributions that you can directly select your percentiles from. It also allows you to have the positive and negative distributions calculated separately, or if you would like, you can pool all of them together in a combined distribution. In addition to this, there is a wide selection of moving averages directly available in the indicator to choose from.
Hedge funds, quant shops, algo prop firms, and advanced mechanical groups all employ the true return distributions in their work. Now you have access to the same type of data with this indicator, wherein it's doing all the lifting for you.
------------------------------ Indicator Settings ------------------------------
.
---- Moving average ----
Select the type of moving average you would like and its length
---- Bands ----
The percentiles that you enter here will be pulled directly from the return distribution of the last 2,000 candles. With the typical Bollinger Bands, traders would select 2 standard deviations and incorrectly think that the levels it highlights are the 95.5% levels. Now, if you want the true 95.5% level, you can just enter 95.5 into the percentile value here. Each of the three available bands takes the true percentile you enter here.
---- Separate Positive & Negative Distributions----
If this box is checked the positive and negative distributions are treated indecently, completely separate from each other. You will see that the width of the top and bottom bands will be different for each of the percentiles you enter.
If this box is unchecked then all the negative and positive distributions are pooled together. You will notice that the width of the top and bottom bands will be the exact same.
---- Distribution Size ----
This is the number of candles that the price return is calculated over. EG: to collect the price return over the last 33 candles, the difference of price from now to 33 candles ago is calculated for the last 2,000 candles, to build a return distribution of 2000 points of price differences over 33 candles.
NEGATIVE NUMBERS(<0) == exact number of candles to include;
EG: setting this value to -20 will always collect volatility distributions of 20 candles
POSITIVE NUMBERS(>0) == number of candles to include as a multiple of the Moving Average Length value set above;
EG: if the Moving Average Length value is set to 22, setting this value to 2 will use the last 22*2 = 44 candles for the collection of volatility distributions
MORE candles being include will generally make the bands WIDER and their size will change SLOWER over time.
I wish you focus, dedication, and earnest success on your journey.
Happy trading :)
Average Daily Range (ADR)This indicator just shows a simple text box with average daily range (in ticks) for the past 20, 40, and 60 days. It also includes the range of the current day, and the % of the different ADR values. Other indicators all plotted lines or had sub-charts and I just wanted a simple text box with the values. Hence, this indicator.
Bull Market ScreenerPrice above 50-day SMA True
50-day SMA above 200-day SMA True
RSI Between 50 and 70
ADX Above 20
Volume Above 20-day average
Earnings Growth (Quarterly) > 10%
Revenue Growth (Yearly) > 10%
P/E Ratio (optional) < 30
Parabolic SAR CustomПараболик со значением 0.02;0,02;0,02 когда цена пересекает с верху вниз покупай, когда когда пересекает с низу вверх продавай
