GBPJPY SELLAs in our previous anylisis we had told that price will go for previous high to be touched and price had done the same and as market sentiment has changed price is moving in to bearish movment and we predict that price will return to its support level of 196 and lower than that so we are at a bearish run for today and tomorrow
Blackcat1402
How-to Use L1 Dynamic Multi-Layer Bollinger BandsEver wondered if there's a magic formula that can help you navigate the choppy waters of the financial market? Well, look no further than the L1 Dynamic Multi-Layer Bollinger Bands! This powerful tool is like a trading wizard's secret weapon, designed to keep you one step ahead of the game.
## What Are Special Points of These Bollinger Bands?
These Bollinger Bands are a technical analysis tool that was invented by John Bollinger. They're a volatility indicator, meaning they can help you understand the market's volatility and predict future price movements. However, Here, the bands are composed of a middle band being a simple moving average (SMA) of the close price, and an upper and lower band that are respectively 1.382 and 2.56 times the standard deviation of the close price over a 21-day period.
## The L1 Dynamic Multi-Layer Bollinger Bands
Now, meet the L1 Dynamic Multi-Layer Bollinger Bands. This isn't your average Bollinger Bands. No, this is a high-tech, state-of-the-art version that's been upgraded with a touch of L1 magic!
### Dynamic Layer:
The "L1" in L1 Dynamic Multi-Layer Bollinger Bands stands for "Level 1" which means this indicator is free to use and open sourced. This indicator may provides the foundation for your trading strategy. It's the 21-day SMA of the close price, acting as the central nervous system of the trading operation.
### Multi-Layer Structure:
But that's not all! The L1 Dynamic Multi-Layer Bollinger Bands also calculates two additional bands, `up2` and `loow2`, which are respectively 2.56 times the standard deviation above and below the middle band. These additional layers give us a layered perspective on the volatility of the price, providing a more comprehensive view of market dynamics.
### Color Coding:
And let's not forget the color coding! The area between the upper and lower bands is filled with a color that indicates the direction of the price movement. Green, as in "Go Green!" is our signal for an upward trend, while red, as in "Red Alert!", is our signal for a downward trend. It's like our eyes, guiding us through the trading maze.
## How to Use L1 Dynamic Multi-Layer Bollinger Bands
1. **Add the Indicator to Your Chart**: Click on the "Add to Chart" button in the Pine-Script editor. This is like planting the L1 Dynamic Multi-Layer Bollinger Bands in your trading chart.
2. **Interpreting the Bands**: The middle band is the 21-day SMA of the close price. The upper band is 1.382 times the standard deviation above the middle band, and the lower band is 1.382 times the standard deviation below the middle band. These bands are like the safety zones in a wild animal's territory. When the price moves outside these bands, it's like a wild animal crossing the territory.
3. **Multi-Layer Structure**: The script also calculates two additional bands, `up2` and `loow2`, which are respectively 2.56 times the standard deviation above and below the middle band. These bands are like the wild animals' offspring, providing a more layered perspective on the volatility of the price.
4. **Color Coding**: The area between the upper and lower bands is filled with a color that indicates the direction of the price movement. Green is like the "Go Green!" signal for an upward trend, while red is like the "Red Alert!" signal for a downward trend. It's like our eyes guiding us through the trading maze.
## The Power of L1 Dynamic Multi-Layer Bollinger Bands
The L1 Dynamic Multi-Layer Bollinger Bands is like a supercharged trading machine. It can help you identify potential support and resistance levels, and it can also provide insights into the market's volatility. It's like having a trading wizard on your side, always one step ahead.
But remember, like any tool, it's not a silver bullet. It's just a tool to help you make more informed decisions. It's up to you to use it wisely and make the most out of it.
So, why wait? Go ahead, add the L1 Dynamic Multi-Layer Bollinger Bands to your chart, and start trading like a boss! After all, the L1 Dynamic Multi-Layer Bollinger Bands are here to help you navigate the choppy waters of the financial market with style and panache. Happy trading!
*Please note that this article is for educational purposes only and should not be used as the sole basis for any trading decisions. Trading involves risk, and it is possible to lose money when trading stocks and other financial instruments. Use this information at your own risk.*
How to use L3 Ultimate Market SentinelScript Introduction
The L3 Ultimate Market Sentinel (UMS) is a technical indicator specifically designed to capture market turning points. This indicator incorporates the principles of the Stochastic Oscillator and provides a clear view of market dynamics through four key boundary lines — the Alert Line, Start Line, Safe Line, and Divider Line. The UMS indicator not only focuses on the absolute movement of prices but also visually displays subtle changes in market sentiment through color changes (green for rise, red for fall), helping traders quickly identify potential buy and sell opportunities.
In the above image, you can see how the UMS indicator labels different market conditions on the chart. Green candlestick charts indicate price increases, while red candlestick charts indicate price decreases. The Alert Line (Alert Line) is typically set at a higher level to warn of potential overheating in the market; the Start Line (Start Line) is in the middle, marking the beginning of market momentum; the Safe Line (Safe Line) is at a lower level, indicating a potential oversold state in the market; the Divider Line (Divider Line) helps traders identify whether the market is in an overbought or oversold area.
Script Usage
1. **Identifying Turning Points**: Traders should pay close attention to the Alert Line and Safe Line in the UMS indicator. When the indicator approaches or touches the Alert Line, it may signal an imminent market reversal; when the indicator touches the Safe Line, it may indicate that the market is oversold and there is a chance for a rebound.
2. **Color Changes**: By observing the color changes in the histogram, traders can quickly judge market trends. The transition from green to red may indicate a weakening of upward momentum, while the shift from red to green could suggest a slowdown in downward momentum.
3. **Trading Strategy**: The UMS indicator is suitable for a variety of trading timeframes, ranging from 1 minute to 1 hour. Short-term traders can use the UMS indicator to capture rapid market fluctuations, while medium-term traders can combine it with other analytical tools to confirm the sustainability of trends.
Advantages and Limitations of the Indicator
**Advantages**:
- Intuitive color coding that is easy to understand and use.
- Multiple boundary lines provide comprehensive market analysis.
- Suitable for a variety of trading timeframes, offering high flexibility.
**Limitations**:
- As a single indicator, it may not cover all market dynamics.
- For novice traders, it may be necessary to use the UMS indicator in conjunction with other indicators to improve accuracy.
- The indicator may lag in extreme market conditions.
Special Note
The L3 Ultimate Market Sentinel (UMS) indicator is a powerful analytical tool, but it is not omnipotent. The market has its inherent risks and uncertainties, so it is recommended that traders use the UMS indicator in conjunction with their own trading strategies and risk management rules. Additionally, it is always recommended to fully test and verify any indicator in a simulated environment before actual application.
New York Community Bank's Hair-Raising Ride and Gold's ShiningAfter returning from a European trip, I have found themselves out of sorts, with no desire to write articles or code, preferring instead to lounge on the sofa in a state of contemplation. It seems that our moods and states of mind have their own cycles; sometimes, things we once loved can lose their appeal, and our attention gets drawn to other matters. Only when the next cycle comes around can we make up for lost time. So, please allow this cat to take things slow and easy.
In this world full of uncertainties, the American banking industry seems to have started a "collapse relay race." Recently, New York Community Bank's performance has been like playing a game of "who falls to the bottom first," and it has inadvertently become the leader. Let's discuss what's going on.
Imagine a bank as a giant piggy bank where people deposit their money, and the bank lends it out to others. If the borrowed money isn't returned, the bank runs into trouble. That's the case with New York Community Bank, whose commercial real estate loans resemble a stack of IOUs that might never be paid back, accounting for a significant portion of its total loans. Commercial real estate refers to buildings used for business, such as office buildings and shops. However, many of these properties now stand empty because, post-pandemic, people prefer working from home, reducing the need for offices.
New York Community Bank's financial report is like a report card that everyone expected to be an A but turned out to be an F. With this result, the bank's stock plummeted like a rollercoaster, its market value plummeting from billions to mere scraps, akin to a millionaire turned pauper.
Now, let's simplify this complex situation with a story. Imagine you have a massive piggy bank filled with gold coins. You lend these coins to your friends, who use them to buy a bunch of toys that might not sell. As a result, these toys fill up the warehouse, and your friends can't repay the coins. Your piggy bank empties, and your friends lose trust in you. That's the current state of New York Community Bank.
The Federal Reserve, like a bank's parent, seeing the children (banks) in trouble, quickly brings out the printing press to create money, hoping to help them overcome their difficulties. However, this solution is like giving children candy; while it temporarily makes them happy, it could lead to long-term problems like cavities (inflation).
Now, the market price of gold has reached a new high, as if everyone is saying, "We don't want this paper money; we want real gold and silver!" Gold is like the superhero that always provides a sense of security during crises. When people doubt the reliability of paper money (the US dollar), gold shines brightly, capturing everyone's attention.
Lastly, let's talk about the Federal Reserve's interest rate hike policy. Raising interest rates is like a parent telling their children, "You can't borrow money so freely anymore; you need to learn to save." This policy makes borrowing more expensive, so people are less inclined to take out loans. However, this policy also has side effects; it can put immense pressure on those who have already borrowed a lot (like New York Community Bank).
So, the story ends here, and we can see that the "collapse relay race" in the American banking industry is ongoing. New York Community Bank is just one example, teaching us that even large banks can fall into trouble due to seemingly minor issues. As observers, we might learn a lesson: whether it's individuals or banks, managing finances wisely is always crucial.
Market Tango: Unveiling the Mystery of the "Twisted Pair" Dance
On the grand stage of the financial market, every trader is looking for a partner who can lead them to dance the tango well. The "Twisted Pair" indicator is that partner who dances gracefully in the market fluctuations. It weaves the rhythm of the market with two lines, helping traders to find the rhythm in the market's dance floor.
Imagine when the market is as calm as water, the "Twisted Pair" is like two ribbons tightly intertwined. They almost overlap on the chart, as if whispering: "Now, let's enjoy these quiet dance steps." This is the market consolidation period, the price fluctuation is not significant, traders can relax and slowly savor every detail of the market.
However, the maestro of the market always likes to change the melody unexpectedly. When volatility suddenly increases, it's like the rhythm of the music speeding up, and the originally quiet dance floor suddenly becomes lively. At this point, the two lines of the "twisted pair" start to separate, they are like dancers ignited by passion, each showing their unique dance moves. The moment these two lines separate, it's like telling the traders: "Are you ready? The market is about to dance, it's time to show off your dancing skills!”
The changes in the "Twisted Pair" indicator are like a barometer of market sentiment. When the two lines are closely connected, the market sentiment is stable, and traders can observe calmly and wait for opportunities. However, when they separate, the market sentiment is high, and traders need to react quickly to capture those moments that could bring profits.
The calculation method of this indicator is like a carefully choreographed dance. It captures the dynamics of the market by calculating the average price, the weighted moving average of the trading volume, and the short-term deviation of the price. These calculations are like the steps of the dancers, each step precise and powerful, ensuring that traders can keep up with the market rhythm.
In practical application, the "Twisted Pair" indicator is not just a static chart line, it is more like a living dance partner. It can sense changes in the market and guide traders to respond flexibly in the market dance floor. Whether in the calm period of the market or during volatility, it can provide clear signals to help traders make wise decisions.
Now, let's describe the market logic of this code in natural language:
- **HJ_1**: This is the foundation of the market dance steps, by calculating the average price and trading volume, setting the tone for the market rhythm.
- **HJ_2** and **HJ_3**: These two lines are the arms of the dance partner, they help traders identify the long-term trend of the market through smoothing.
- **HJ_4**: This is a magnifying glass for market sentiment, it reveals the tension and excitement of the market by calculating the short-term deviation of the price.
- **A7** and **A9**: These two lines are the guide to the dance steps, they separate when the market volatility increases, guiding the traders in the right direction.
- **WATCH**: This is the signal light of the dance, when the two lines overlap, the market is calm; when they separate, the market is active.
The "Twisted Pair" indicator is like a carefully choreographed dance, it allows traders to find their own rhythm in the market dance floor, whether in a calm slow dance or a passionate tango. Remember, the market is always changing, and the "Twisted Pair" is the perfect dance partner that can lead you to dance out brilliant steps. Next, this cat will introduce the TradingView code for this indicator:
// ____ __ ___ ________ ___________ ___________ __ ____ ___
// / __ )/ / / | / ____/ //_/ ____/ |/_ __< / // / / __ |__ \
// / __ / / / /| |/ / / ,< / / / /| | / / / / // /_/ / / __/ /
// / /_/ / /___/ ___ / /___/ /| / /___/ ___ |/ / / /__ __/ /_/ / __/
// /_____/_____/_/ |_\____/_/ |_\____/_/ |_/_/ /_/ /_/ \____/____/
// This source code is subject to the terms of the Mozilla Public License 2.0 at mozilla.org
// © blackcat1402
//@version=5
indicator(title=" L2 Twisted Pair Indicator", shorttitle="TPI", overlay=true)
//define DEMA
DEMA_function(src, length) =>
ema1 = ta.ema(src, length)
ema2 = ta.ema(ema1, length)
2 * ema1 - ema2
//define TEMA
TEMA_function(src, length) =>
ema1 = ta.ema(src, length)
ema2 = ta.ema(ema1, length)
ema3 = ta.ema(ema2, length)
3 * (ema1 - ema2) + ema3
//input
swi = input.string(title="Switch", options= , defval="EMA")
ma(src, length) =>
out = swi == "DEMA" ? DEMA_function(src, length) : swi == "TEMA" ? TEMA_function(src, length) : ta.ema(src, length)
out
//Twisted Pair algorithm
HJ_1 = (high + low + close) / 3 * volume
HJ_2 = ma((ma(HJ_1, 3) / ma(volume, 3) + ma(HJ_1, 6) / ma(volume, 6) + ma(HJ_1, 12) / ma(volume, 12) + ma(HJ_1, 24) / ma(volume, 24)) / 4, 13)
HJ_3 = 1.08 * HJ_2
HJ_4 = ma(HJ_3 - (ma(close, 3) - HJ_3), 5)
A7 = HJ_4 <= HJ_3 ? HJ_4 : HJ_3
HJ_5 = 2 * HJ_3 - A7
A9 = HJ_5 >= HJ_3 ? HJ_5 : HJ_3
WATCH = A7 == A9 ? A7 : na
plot(A7, color=color.yellow, linewidth=2)
plot(A9, color=color.yellow, linewidth=2)
plot(WATCH, color=color.green, linewidth=2, style = plot.style_steplinebr)
HJ_6 = close * 1.1 - close < 0.01 and high == close
HJ_7 = HJ_3 >= HJ_3 and A7 < A7 and close > HJ_3 and open > HJ_3
// plot candle color indications
plotcandle(open, (open + close) / 2, open, (open + close) / 2, color=HJ_7 ? color.yellow : na)
plotcandle(close, (open + close) / 2, close, (open + close) / 2, color=HJ_7 ? color.red : na)
The script of this "Twisted Pair" uses three different types of moving averages: EMA (Exponential Moving Average), DEMA (Double EMA), and TEMA (Triple EMA). These types can be selected by the user through exchange input.
Here are the main functions of this code:
1. Defined the DEMA and TEMA functions: These two functions are used to calculate the corresponding moving averages. EMA is the exponential moving average, which is a special type of moving average that gives more weight to recent data. In the first paragraph, ema1 is the EMA of "length", and ema2 is the EMA of ema1. DEMA is 2 times of ema1 minus ema2.
2. Let users choose to use EMA, DEMA or TEMA: This part of the code provides an option for users to choose which type of moving average they want to use.
3. Defined an algorithm called "Twisted Pair algorithm": This part of the code defines a complex algorithm to calculate a value called "HJ". This algorithm involves various complex calculations and applications of EMA, DEMA, TEMA.
4. Plotting charts: The following code is used to plot charts on Tradingview. It uses the plot function to draw lines, the plotcandle function to draw candle (K-line) charts, and yellow and red to represent different conditions.
5. Specify colors: The last two lines of code use yellow and red K-line charts to represent the conditions of HJ_7. If the conditions of HJ_7 are met, the color of the K-line chart will change to the corresponding color.
HOW-TO use L3 Emotion LineI. Overview
The Emotion Line is an innovative technical indicator designed to capture market sentiment by analyzing price dynamics. This indicator calculates the average of opening, high, low, and closing prices over the past three days and combines the concepts of Dynamic Moving Average (DMA) and Exponential Moving Average (EMA) to generate a value reflecting market sentiment. The Emotion Line is implemented in Pine Script on the TradingView platform, providing users with an intuitive tool for market sentiment analysis.
II. Calculation Method
Ray: Calculate the average of the past three days' prices, i.e., (2 * C + H + L) / 4, where C represents the closing price, H the highest price, and L the lowest price. Then, take the Simple Moving Average (SMA) of this average over 3 days with a smoothing factor of 2.
CL (Close Line): Assign the value of Ray to CL as the basis for subsequent calculations.
DIR1 (Directional Change): Calculate the absolute difference between CL and the CL of the previous two days, indicating the magnitude of price movement.
VIR1 (Volume in Range): Calculate the sum of the absolute differences between CL and the previous day's CL over the past two days, measuring the accumulation of price fluctuations.
ER1 (Efficiency Ratio): The ratio of DIR1 to VIR1, measuring the efficiency of price movement.
CS1 (Cumulative Strength): Apply a weighted process to ER1 to obtain CS1.
CQ1 (Cumulative Quotient): The square of CS1, further strengthening the cumulative effect of price movement.
AMA5 (Adjusted Moving Average): Calculate the Dynamic Moving Average (DMA) of CL with the dynamic factor CQ1, then apply a 2-day Exponential Moving Average (EMA) to the result.
Cost: Calculate the 7-day Simple Moving Average (SMA) of AMA5.
CLX (Composite Line): Calculate the average of AMA5 and Cost to obtain CLX.
Emotion Line: Calculate the proportion of CLX increasing continuously for N days, with N defaulting to 7 days. Multiply the result by 100 to get the Emotion Line value.
MA_emotionLine (Moving Average Emotion Line): Calculate the M-day moving average of the Emotion Line, with M defaulting to 6 days.
III. Market Logic
By analyzing the cumulative effect and efficiency of price movement, the Emotion Line attempts to reveal the strength of market sentiment. When the Emotion Line rises, it indicates a positive market sentiment, and investors may have an optimistic attitude towards the stock; a falling Emotion Line may signal a weakening market sentiment. The absolute value and trend changes of the Emotion Line can provide investors with references for buying, holding, or selling.
IV. Usage
Attention Signal: When the Emotion Line exceeds 20%, the market sentiment may begin to be positive, and investors should pay attention to related stocks.
Entry Signal: When the Emotion Line exceeds 40%, the market sentiment is relatively strong, and investors may consider entering the market.
Reduce Position Signal: When the Emotion Line exceeds 80%, the market may be overly optimistic, and investors should consider reducing their positions to avoid risk.
Exit Signal: When the Emotion Line breaks below its M-day moving average, it may signal a shift in market sentiment, and investors should consider exiting the market.
V. Notes
The Emotion Line is an auxiliary tool, and investors should make comprehensive judgments based on other technical analysis and fundamental analysis.
Market sentiment is influenced by various factors, and the Emotion Line may have lag, so investors should use it cautiously.
Investors should adjust the parameters of the Emotion Line according to their risk tolerance and investment strategy.
VI. Conclusion
The Emotion Line is an intuitive indicator that reflects market sentiment through quantitative methods, providing a new perspective for investors to observe market dynamics. However, no technical indicator is foolproof, and investors should remain cautious when using it, combining their personal experience and market conditions to make decisions. Through the TradingView platform, investors can easily add the Emotion Line indicator to their charts to assist in their trading decision-making process.
[blackcat] L5 ALGOLD: Trend Mastery UnleashedThe " L5 Alchemy Gold (ALGOLD)" is a comprehensive trend-following indicator for trading. It combines volume and price data to create a MACD-like oscillator with reduced lag. The indicator includes adaptive and volatility filters, an ALMA for further filtering, and a divergence detector. It offers customizable settings and visual effects, such as color changes and shapes. ALGOLD provides entry and exit signals based on crossovers of fast and slow lines. It is a versatile tool for traders of all levels, helping decode market trends and tailor trading strategies.
Welcome to the world of trading, where the charts speak, and the indicators are the translators! Today, we're diving into the realm of the " L5 Alchemy Gold (ALGOLD)" - not your average indicator, but a trend-following maestro that dances to the rhythm of the markets.
**The Birth of ALGOLD:**
Born in the digital alleys of TradingView, ALGOLD is the brainchild of blackcat1402 who decided that 'lag' is a three-letter word not welcome in its vocabulary. This trend-following indicator isn't just another line on your chart; it's a fusion reactor of volume and price information. Imagine a MACD oscillator but with less lag and more swagger. That's ALGOLD for you! It's a trend-following indicator that blends volume and price data to create a MACD-like oscillator, aiming to address the lagging issue typical in price-only indicators. The integration of leading volume information with lagging price data is a smart approach to create more timely signals. Additionally, incorporating a volatility filter to reduce false signals during sideways markets is a thoughtful enhancement.
" L5 Alchemy Gold (ALGOLD)" indicator is shaping up to be quite comprehensive. It includes:
1. An adaptive filter for smoothing price and volume data.
2. A volatility filter based on Average True Range (ATR).
3. A trigger moving average for generating smoothed price information.
4. An ALMA (Arnaud Legoux Moving Average) for further filtering of price and volume.
5. A divergence detector to identify potential trend reversals.
" L5 Alchemy Gold (ALGOLD)" indicator input setting parameters, categorized into three groups:
1. **Alchemy Setting**:
- Alchemy Sharpness (Default: 7) - Controls the sharpness of the adaptive filter.
- Alchemy Period (Default: 55) - Determines the smoothness of the oscillator.
2. **DVATR Setting**:
- DVATR Length (Default: 11) - Sets the period length for the DVATR, similar to ATR's Length.
- DVATR Threshold (Default: 0.07) - Adjusts sensitivity for sideways market detection.
- Smooth Length (Default: 21) - Smoothens the DVATR output, balancing with volatility detection.
3. **Divergence Setting**:
- Parameters like Pivot Lookback, Max/Min of Lookback Range - Sets the sensitivity for divergence detection.
- Options to enable or disable plots for various types of divergence (Bullish, Hidden Bullish, Bearish, Hidden Bearish).
**Alchemy Meets Trading:**
At the heart of ALGOLD lies the 'Alchemy Setting'. Think of it as the secret sauce that gives this indicator its edge. With the 'Alchemy Sharpness' and 'Alchemy Period' knobs, you're not just smoothing data; you're crafting financial art. The sharpness sets the mood, and the period decides the tempo.
**Taming the Market's Roar with DVATR:**
Sideways markets? ALGOLD laughs in the face of these with its DVATR Setting. Using the ATR as a base, this feature filters the market's whispers and roars, distinguishing between a lion's charge and a cat's stroll. It's like having a market mood ring on your chart!
**Diving for Divergence:**
The 'Divergence Setting' is where ALGOLD plays detective. It's on the lookout for those sneaky market reversals. With a range of lookback settings and the option to plot different divergence types, it's like giving your chart a pair of detective glasses.
**A Visual Symphony:**
Now, let's talk visuals. If ALGOLD was a movie, it'd win an Oscar for best visual effects. " L5 Alchemy Gold (ALGOLD)" indicator are vivid and intuitive:
1. **Candle Bar Color**: Gradient color changes to indicate trend strength, with warmer colors for bullish and cooler colors for bearish trends.
2. **Line Colors and Shapes**:
- Green color represents the fast line, red for the slow line.
- Crosses of these lines signal entries (triangles) and exits (cross shapes).
- A band is created between these lines, filled with green for uptrends and red for downtrends.
3. **Histogram**:
- Red histogram for above 0 and uptrend.
- Blue histogram for above 0 and retracement.
- Green histogram for below 0 and downtrend.
- Yellow histogram for below 0 and bounce-up.
Candle bars change colors like chameleons, adapting to the market's mood. The fast line (in green) and the slow line (in red) waltz on your screen, creating a visual feast. When they cross, it's not just a signal; it's a declaration!
**The Histogram That Speaks Volumes:**
The ALGOLD histogram is a story teller in its own right. Imagine a bar chart that not only shows the market's direction but also its mood swings. Red bars for the uptrends, blue for those sneaky retracements, green for the downtrends, and yellow for the bounces. It's like having a market weather forecast at your fingertips!
**Entry and Exit: The Dance of the Bulls and Bears:**
- **Entry Criteria**: A composite crossover and crossunder of the fast and slow lines of the ALGOLD oscillator.
- **Exit Criteria**: A crossover and crossunder of the fast and slow lines of the ALGOLD oscillator, but using a lower time frame for more sensitivity.
When it comes to entering and exiting trades, ALGOLD is like a seasoned dance instructor. The entry signals are a harmonious crossover and crossunder of the fast and slow lines, telling you when to step in. And when it's time to bow out? A similar crossover and crossunder on a lower time frame gives you the nudge. It's like having a dance partner that knows exactly when to lead and when to follow.
**Customization: Your Personal Trading Tailor:**
What's more? ALGOLD is not a one-size-fits-all indicator. With its customizable settings, you can tailor it to fit your trading style. Whether you like your trading smooth and slow or sharp and fast, ALGOLD adapts to you. It's the bespoke suit of trading indicators!
**Bringing it All Together:**
So, there you have it, traders. The " L5 Alchemy Gold (ALGOLD)" is not just an indicator; it's your market compass, your trend translator, and your trading tailor, all rolled into one sleek package. Whether you're a seasoned trader or just starting, ALGOLD is your ally in decoding the market's mysteries.
As we wrap up this tour of ALGOLD, remember that the markets are a dance floor, and with ALGOLD, you're always ready to dance. Test it, tweak it, and make it your own. And who knows, with ALGOLD by your side, you might just become the trading legend you were meant to be!
Happy trading, and may the trends always be in your favor!
HOW-TO use[blackcat] L5 KDJ with Whale Pump DetectorOne of the biggest differences between cryptocurrency and traditional financial markets lies in the foundational technology that underpins cryptocurrency, known as blockchain. This revolutionary technology enables individual investors to gain insights into the flow of large funds through on-chain transfers, thus providing a unique advantage in the market. These significant funds, often referred to as "Whales," have the ability to exert considerable influence over the price movements of cryptocurrencies, particularly Bitcoin. As a result, monitoring and analyzing Whale trends holds immense importance, both in terms of understanding the fundamental dynamics and leveraging technical aspects of the market.
Let's delve into the KDJ oscillator display, a powerful tool for cryptocurrency traders. Comprising three lines, namely K, D, and J, the KDJ display draws parallels with the stochastic oscillator. The K and D lines are identical to those seen in the stochastic oscillator, while the J line represents the deviation of the D value from the K value. By observing the convergence of these lines, traders can identify potential trading opportunities and capitalize on them. Moreover, similar to the Stochastic Oscillator, the KDJ display also highlights oversold and overbought levels, indicating moments when the ongoing trend is likely to reverse.
In the realm of cryptocurrency trading, the L2 KDJ with Whale Pump Detector emerges as a composite indicator that seamlessly integrates the KDJ display with the Whale Pump Detector. This integration imparts an additional layer of sophistication to the analysis process, allowing traders to filter out false signals that may arise from the KDJ display. Consequently, traders can make more informed decisions by leveraging the power of this composite indicator.
For further information and access to the L2 KDJ with Whale Pump Detector script, you can visit the following link: (). However, it is important to exercise caution while using any script and ensure that you fully trust the author and comprehend the script's functionality. If you are uncertain, consider exploring open-source alternatives available within the (www.tradingview.com) section.
This article introduces the advanced version of L2 KDJ, called L5 KDJ. The L5 KDJ indicator is mainly composed of three parts.
The first part is the color band of KDJ, which changes color based on the strength of the market trend. The closer the color is to cool colors, the market tends to be bearish; if the color leans towards warm colors, it indicates a bullish market. This color change can provide valuable market information to help traders assess the current market trend and situation.
In addition, the fluctuation range of the KDJ color band is between 0 and 100. To better utilize this indicator, I set 0 to 20 as the oversold zone and 80 to 100 as the overbought zone. When the oscillator oscillates within this range, the color of the band changes, indicating the current position of the market. This setting can help traders more accurately determine overbought and oversold conditions, enabling them to make wiser trading decisions.
It should be noted that in some extreme market conditions, the color band may exhibit special color changes. In a trending market, if the color band leans towards warm colors, it indicates that the market may be in an overbought state; whereas if the color band leans towards cool colors, it may indicate an oversold market. These special color changes can help traders better understand the market conditions and take appropriate trading strategies in a timely manner.
In summary, L5 KDJ is an advanced version of L2 KDJ, which integrates the KDJ color band and the color changes of the market trend, providing traders with more useful market information. Proper use of the L5 indicator can help traders more accurately assess the market trend and position, enabling them to make wiser trading decisions.
Part 2. This is the KDJ candle in yellow and purple. These candles are key signals for generating entry and exit signals. They are generated through multiple high-order filters. The candles are divided into yellow and purple parts, where yellow represents long positions and purple represents short positions. There are also yellow and purple labels for opening and closing signals. The yellow label 'L' represents long entry, and the yellow label 'TP' represents closing long positions. Similarly, the purple label 'S' represents short entry, and the purple label 'TP' represents closing short positions. Each label is followed by an '@' symbol, followed by a percentage. This percentage represents the dynamic candle's deviation from the mean deviation value. The mean deviation value indicates whether the current market is in an extreme condition. It is not only used to determine overbought and oversold conditions and closing signals, but also to identify opportunities for short-term rebounds. This rebound strategy can be used in conjunction with the BNF. Overall, the yellow and purple candles will fluctuate above and below the KDJ color band. When the candles are far away from the color band, there is a tendency to regress. In this case, it is advisable to consider entering for a rebound or to take timely profits and exit.
In addition, the third major characteristic is the whale jump indicator. For whale departure, this is the same as my classic whale jump algorithm. Of course, here it is defined that the starting point for bullish whales is 0, and the starting point for bearish whales is 100. The color bars generated by bullish whales are purple and red, with purple indicating that bullish whales are actively buying long positions, and red indicating that bullish funds are starting to pause or relay. Bearish funds are represented by yellow and green colors, with yellow bars indicating strong bearish selling pressure and green indicating situations where bearish intensity pauses or relays.
Finally, this indicator will generate alert signals for long entry, short entry, short take profit, and long take profit, which can be implemented through the alert function. Overall, the L5 KDJ indicator has significant improvements compared to the L2 KDJ indicator. These advantages are mainly reflected in the stability of the signals, noise filtering, and accurate generation of long and short entry signals, as well as the generation of closing signals. Additionally, it also displays the deviation rate (used for BNF rebound strategy). I hope this will bring more convenience to traders.
HOW-TO indicate turbulent market : TEMA ChannelHey, friends! blackcat is here to bring you an interesting and professional article today, talking about the "Triple Exponential Moving Average (TEMA) Channel" - a powerful tool as a trend indicator in volatile markets.
First of all, let's delve into the origins of the TEMA indicator. It was invented by Patrick Mulloy in the mid-90s with the aim to address the lagging issue encountered when using oscillators or Exponential Moving Averages (EMA). The TEMA indicator smooths out short-term fluctuations by utilizing multiple moving averages. What sets it apart is its unique approach of continuously using the EMA's EMA and adjusting for lag in its formula.
In this article, we will primarily focus on the functionality of the TEMA channel as a trend indicator. However, it's worth noting that its effectiveness is diminished in choppy or sideways markets. Instead, the TEMA indicator shines brightest in long-term trend trading. By utilizing TEMA, analysts can easily filter out and disregard periods of volatility, allowing them to focus on the overall trend.
To gain a comprehensive understanding of market trends, it is often recommended to combine TEMA with other oscillators or technical indicators. This combination can help traders and analysts interpret sharp price movements and assess the level of volatility. For example, some analysts suggest combining the Moving Average Convergence Divergence (MACD) with the TEMA channel to evaluate market trends more accurately.
Now, let's explore how the TEMA channel can be used as a tool to showcase interesting features of price support and resistance. In this script, the TEMA channel is represented by three bands: the upper band, the middle band, and the lower band. The upper band is depicted in white, the middle band in yellow, and the lower band in magenta.
So, let's dive deep into the world of the TEMA channel and enjoy the benefits it brings to understanding market trends. Join us on this exciting journey!
" L1 Triple EMA Channel" requires the overlay parameter set to true. This means that the indicator will be plotted on top of the price chart.
The variable N is defined as an input integer with a default value of 21 and a label "Period". This allows users to change the period value when adding this indicator to their chart.
The variables MAH, MAL, RRANGE, and RANGEMA are calculated using exponential moving averages (EMAs) applied multiple times to either high, low, or range values based on the specified period (N). These calculations help determine upper and lower channel levels for plotting.
The variable UPPER represents the upper channel level by adding twice the RANGEMA value to MAH. It is then plotted using plot() function with parameters like color, linewidth etc.
Similarly, The variable LOWER represents the lower channel level by subtracting twice RANGEMA from MAL. It is also plotted using plot() function with different color than UPPER line.
Finally, The MID variable calculates midpoint between UPPER and LOWER channels by taking their average. It too gets plotted using plot() function but has different color than both UPPER & LOWER lines.
How to use [blackcat] L3 Fibonacci Bands With ATRToday, what I'm going to introduce is a technical indicator that I think is quite in line with the indicator displayed by Tang - Fibonacci Bands with ATR. This indicator combines Bollinger Bands and Average True Range (ATR) to provide insights into market volatility and potential price reversals. Sounds complicated, right? Don't worry, I will explain it to you in the simplest way.
First, let's take a look at how Fibonacci Bands are constructed. They are similar to Bollinger Bands and consist of three lines: upper band, middle band (usually a 20-period simple moving average), and lower band. The difference is that Fibonacci Bands use ATR to calculate the distance between the upper and lower bands and the middle band.
Next is a key factor - ATR multiplier. We need to smooth the ATR using Welles Wilder's method. Then, by multiplying the ATR by a Fibonacci multiplier (e.g., 1.618), we get the upper band, called the upper Fibonacci channel. Similarly, multiplying the ATR by another Fibonacci multiplier (e.g., 0.618 or 1.0) gives us the lower band, called the lower Fibonacci channel.
Now, let's see how Fibonacci Bands can help us assess market volatility. When the channel widens, it means that market volatility is high, while a narrow channel indicates low market volatility. This way, we can determine the market's activity level based on the width of the channel.
In addition, when the price touches or crosses the Fibonacci channel, it may indicate a potential price reversal, similar to Bollinger Bands. Therefore, using Fibonacci Bands in trading can help us capture potential buy or sell signals.
In summary, Fibonacci Bands with ATR is an interesting and practical technical indicator that provides information about market volatility and potential price reversals by combining Bollinger Bands and ATR. Remember, make good use of these indicators and apply them flexibly in trading!
This code is a TradingView indicator script used to plot L3 Fibonacci Bands With ATR.
First, the indicator function is used to define the title and short title of the indicator, and whether it should be overlaid on the main chart.
Then, the input function is used to define three input parameters: MA type (maType), MA length (maLength), and data source (src). There are four options for MA type: SMA, EMA, WMA, and HMA. The default values are SMA, 55, and hl2 respectively.
Next, the moving average line is calculated based on the user's selected MA type. If maType is 'SMA', the ta.sma function is called to calculate the simple moving average; if maType is 'EMA', the ta.ema function is called to calculate the exponential moving average; if maType is 'WMA', the ta.wma function is called to calculate the weighted moving average; if maType is 'HMA', the ta.hma function is called to calculate the Hull moving average. The result is then assigned to the variable ma.
Then, the _atr variable is used to calculate the ATR (Average True Range) value using ta.atr, and multiplied by different coefficients to obtain four Fibonacci bias values: fibo_bias4, fibo_bias3, fibo_bias2, and fibo_bias1.
Finally, the prices of the upper and lower four Fibonacci bands are calculated by adding or subtracting the corresponding Fibonacci bias values from the current price, and plotted on the chart using the plot function.
HOW-TO use Fibonacci Bands make a strategyThe concept of the Fibonacci Bands indicator was described by Suri Dudella in his book "Trade Chart Patterns Like the Pros" (Section 8.3, page 149). These bands are derived from Fibonacci expansions based on a fixed moving average, and they display potential areas of support and resistance. Traders can utilize the Fibonacci Bands indicator to identify key price levels and anticipate potential reversals in the market.
To calculate the Fibonacci Bands indicator, three Keltner Channels are applied. These channels help in determining the upper and lower boundaries of the bands. The default Fibonacci expansion levels used are 1.618, 2.618, and 4.236. These levels act as reference points for traders to identify significant areas of support and resistance.
When analyzing the price action, traders can focus on the extreme Fibonacci Bands, which are the upper and lower boundaries of the bands. If prices trade outside of the bands for a few bars and then return inside, it may indicate a potential reversal. This pattern suggests that the price has temporarily deviated from its usual range and could be due for a correction.
To enhance the accuracy of the Fibonacci Bands indicator, traders often use multiple time frames. By aligning short-term signals with the larger time frame scenario, traders can gain a better understanding of the overall market trend. It is generally advised to trade in the direction of the larger time frame to increase the probability of success.
In addition to identifying potential reversals, traders can also use the Fibonacci Bands indicator to determine entry and exit points. Short-term support and resistance levels can be derived from the bands, providing valuable insights for trade decision-making. These levels act as reference points for placing stop-loss orders or taking profits.
Another useful tool for analyzing the trend is the slope of the midband, which is the middle line of the Fibonacci Bands indicator. The midband's slope can indicate the strength and direction of the trend. Traders can monitor the slope to gain insights into the market's momentum and make informed trading decisions.
The Fibonacci Bands indicator is based on the concept of Fibonacci levels, which are support or resistance levels calculated using the Fibonacci sequence. The Fibonacci sequence is a mathematical pattern that follows a specific formula. A central concept within the Fibonacci sequence is the Golden Ratio, represented by the numbers 1.618 and its inverse 0.618. These ratios have been found to occur frequently in nature, architecture, and art.
The Italian mathematician Leonardo Fibonacci (1170-1250) is credited with introducing the Fibonacci sequence to the Western world. Fibonacci noticed that certain ratios could be calculated and that these ratios correspond to "divine ratios" found in various aspects of life. Traders have adopted these ratios in technical analysis to identify potential areas of support and resistance in financial markets.
In conclusion, the Fibonacci Bands indicator is a powerful tool for traders to identify potential reversals, determine entry and exit points, and analyze the overall trend. By combining the Fibonacci Bands with other technical indicators and using multiple time frames, traders can enhance their trading strategies and make more informed decisions in the market.
How-To Use Bollinger Bands Width CrossToday, this article will introduce the last member of the Bollinger Bands trio - **Bollinger Bands Width (BBW)**. This indicator is derived from the famous Bollinger Bands and is used to measure price volatility and identify trading signals.
First, let's take a look at what Bollinger Bands are. It consists of three lines that are associated with the price of a security. The middle line is usually a 20-day simple moving average (SMA), while the upper and lower bands are two standard deviations above and below the middle band. The Bollinger Bands Width is a method used to measure the width between the upper and lower bands.
```markdown
Bollinger Bands Width = (Upper Band - Lower Band) / Middle Band
```
So how do we calculate BBW? It's simple! Just subtract the lower band from the upper band and divide it by the middle band to get the BBW value.
However, it's important to note that we cannot simply determine whether it is in a narrow or wide state based on the BBW value alone. Different tools or securities may have different definitions of narrowness, and it can also change over different time ranges. Therefore, to accurately assess the importance of band narrowing, we need to analyze the past BBW fluctuations and price performance together.
Next, let's talk about one of the most famous theories about Bollinger Bands - the "squeeze". The squeeze setup consists of two steps: first, a period of low volatility where the bands narrow and prices move relatively horizontally; then, an increase in volatility where prices break above the upper band or below the lower band, signaling the start of a new trend.
In a squeeze setup during a bull market, BBW decreases, and when prices break above the upper band, a new uptrend begins. In a squeeze setup during a bear market, BBW also decreases, and when prices fall below the lower band, a new downtrend begins.
To summarize, Bollinger Bands Width (BBW) is a very useful technical analysis tool that performs well in identifying squeezes. However, traders should use it with caution! Sometimes, even though a squeeze setup occurs, a strong market trend may not actually emerge. Therefore, determining whether a breakout is valid still requires traders to decide for themselves.
Finally, let's introduce some parameters and options: Length represents the time period used for calculating the base SMA, with a default of 20 days; Source represents the determination of the data used for each candlestick in the calculation, with a default of the closing price; Standard Deviation represents the number of standard deviations away from the SMA that the upper and lower bands are, with a default of 2.
How-to use L3 Six-color Divine DragonNOTE: this indicator is optimized for stocks which include financial data, for forex and crypto, it may not work as well as stocks.
**L3 Six-color Divine Dragon** Indicator consists of red profit holders, yellow floating chips, and green trapped holders, along with their 10-day moving averages, totaling six colors, hence the name Six Color Dragon. The dynamic chips reflect the trading and movement of the main chips within a certain range. Purple represents the stock price entering the oversold zone, and yellow represents the stock price in a normal trend. The Six Color Dragon Indicator calculates the price and volume data over a period of time to display the buyer/seller activity. It analyzes the possible behavior of institutional funds based on the price and volume data of each trading day.
- Deep red bars: the current proportion of profitable holders.
- Red line: the moving average of the red bars.
- Deep green bars: the current proportion of losing holders.
- Light green line: the moving average of the green bars.
- Yellow bars: the proportion of daily traders (buying and selling on that day).
- Yellow line: the moving average of the yellow bars.
When the deep red bars > 50%, it indicates strong control of institutional funds and an easier continuation of the uptrend. When the deep green bars < 50%, it indicates retail investors are trapped inside, making it easier for the downtrend to continue.
The intersection of moving averages indicates a trend reversal signal:
1. Red line crossing above the green line: uptrend.
2. Green line crossing above the red line: downtrend.
The process of major manipulation of stock prices can be roughly divided into the following stages:
1. Accumulation stage: before the start of the main uptrend, the main players repeatedly clean up the chips to obtain more cheap chips; trial actions before the rise are also essential. When the selling pressure from external sources exceeds the expectations of the main players, they will continue to clean up the chips until their desired goal is achieved. After breaking through the platform, they choose to rise. During the rise, the main players will choose to lift, clean up, lift again, clean up again... When most investors feel that every pullback of this stock is a buying opportunity, often the top of this stock is not far away, and the main players have quietly started to exit.
By using the Six Color Dragon Indicator and dynamic chips together, we can effectively grasp the various stages of the main manipulation of stock prices:
1. Accumulation - initial rise: in this stage, the typical features of the Six Color Dragon Indicator are a decrease in trapped holders (green bars), an increase in floating chips (yellow bars), and occasional appearance of profit holders. The dynamic chips show that the stock price always fluctuates around the dense peak area of the chips. This stage is more difficult to operate, so it is recommended to wait for the appearance of a buying signal.
Buying signal: the stock price breaks through the consolidation pattern with increased volume, the 10-day moving average of the profit holders in the Six Color Dragon Indicator is moving upward, and the red bars of the profit holders break through the purple moving average of the profit holders; the stock price is more than 10% away from the dense peak area.
2. Trial trading, chip cleaning: after the main accumulation is completed, before a significant rise, there is often a trial trading phase. If a large amount of selling pressure is observed, it is usually necessary to clean up the floating chips, which is called chip cleaning. The chip cleaning is manifested in the stock price as significant fluctuations.
The main features of this stage are: the 10-day moving average of the profit holders in the Six Color Dragon Indicator changes from an upward trend to a flat or smaller angle, indicating a decrease in profit holders, and the stock price experiences a certain amount of decline. However, the dense peak of the dynamic chips remains unchanged, and the stock price usually fluctuates above the corresponding price level of the dense chip area, rarely falling below the dense peak or quickly recovering after falling below.
At this time, we can choose to buy a portion of the stock near the dense peak of the dynamic chips when the stock price stabilizes. We can then add more positions when there is another significant volume breakthrough of the previous high point, and the dense peak of the dynamic chips does not shift upward.
3. Main rise stage: this stage is the main profit-making stage of significant rise.
- The main features in the early stage of the rise are steadily increasing red bars in the Six Color Dragon Indicator and a steady upward trend of the 10-day moving average of the profit holders.
- In the later stage of the rise, the red bars are mostly above the 10-day moving average of the profit holders or around it. The dense peak of the dynamic chips does not clearly shift upward, or even after the shift, the stock price continues to run above the new dense peak, indicating that the stock still has upside potential and can be held.
4. Distribution stage: the main features of this stage are a slow decrease in profit holders, red bars retracting within the 10-day moving average, accompanied by a decline in the stock price and the emergence of trapped holders; the dense peak of the dynamic chips shifts upward, and the stock price falls below the newly formed dense peak, leading to an increase in trapped holders and profit-taking.
Note: when analyzing weak rebounds, the selected range, the time span on the x-axis, and the turnover statistics may vary, resulting in different effects in dynamic chip analysis. Specifically, the range from the most recent point to the highest point within 3 weeks or more is usually a reasonable range. Remember to identify the high point of a rebound that lasted for 3 weeks or more, otherwise, the accuracy of the analysis will be reduced.
In addition, when using the Six Color Dragon Indicator and dynamic chip analysis, it is necessary to combine other technical analysis tools and market conditions for comprehensive judgment in order to improve the accuracy and reliability of the analysis.
Why does physics still exist in blackcat's eyes?The story of this cat and the subject of physics can be described as ups and downs, making people laugh. During my undergraduate years, this cat actually scored a perfect 100 in two semesters of college physics, shining like the sun in the cat world! Several years later, while continuing my graduate studies at the same school, I encountered the young female teacher who had taught physics back then. Ah, time flies, she is no longer the youthful beauty she once was. After exchanging pleasantries, she sighed and said, "Since you, no one has been able to score a perfect grade in both semesters of college physics." In that moment, a sense of pride welled up in my heart. Yes, I have truly turned physics into a supreme art, feeling invincible!
Similarly, I was enthusiastic about digital signal processing (DSP) during my college years. I scored 98 on the undergraduate exam, making me feel invincible and believing that the world of DSP is my cat's backyard. Unfortunately, a few years later, I discovered that I had to take this subject again for my graduate studies, and I was at a loss. But, being resourceful, I immediately found a solution - borrowing DSP review materials from my junior classmates.
On those photocopies, which had been copied numerous times and had some faded handwriting, I saw a familiar handwriting. To my delight, it turned out to be the review materials I had helped my classmates prepare for the exam back in my undergraduate years! Over the years, this treasure had not been lost, but had been passed down from junior to junior! The feeling at that time was truly indescribable, as if this cat was a legend in the Department of Automation. Haha, it seems that this cat's academic torch has been burning for a long time, unconsciously influencing one batch of students after another. In summary, my academic career is like a dinosaur, completely extinct, but my skills are like a torch, illuminating the path for others. This cat's aura of academic excellence is probably irresistible!
In my trading experience, my deep involvement with physics began with John Ehlers' four English textbooks. When faced with complex market conditions, my scientific background required me to trust conclusions based on solid theoretical foundations rather than those based on experience or hearsay "Holy Grails". Ehlers' theories, although profound, were greatly aided by the accumulation of my physics knowledge during school, allowing me to quickly translate many concepts into code. So, if you want to find the most comprehensive collection of Ehlers' technical indicators on the internet, you can search for "Ehlers" on my TradingView page, and you'll find a bunch. Those are all the technical indicators I have translated from Ehlers' book into TradingView scripts. Even now, this cat admires its own dedication and perseverance.
In trading, delving into physics is not an easy task. Starting with John F. Ehlers' four English textbooks, I immersed myself in the ocean of physics. Facing the complex market environment, as a science student, I tend to trust conclusions based on solid theoretical foundations rather than those based on experience or hearsay "Holy Grails".
Ehlers' theories are indeed profound, but fortunately, during my school years, I accumulated a lot of physics knowledge, which greatly helped me in trading. Not only do I understand the principles behind many things, but I can also quickly convert them into executable code. So, if you're interested in finding the most comprehensive collection of Ehlers' technical indicators on the internet, you can go to my TradingView page and search for "Ehlers," and you'll see a bunch of relevant results. Those are all the technical indicators I have translated from Ehlers' book into TradingView scripts. Ah, even now, this cat has to admire its own dedication and perseverance! Hehe, surprised, aren't you? This cat is not only a physics genius, but also a master at translating theory into practical applications! In China, this cat is considered a representative of the feline world who has taken his theoretical research to the extreme! But no matter what, this cat will always cherish this special ability, continue to explore and utilize the wonders of physics in trading. Who knows?
The previous paragraphs were all introductions. Now let's get back to the main topic and talk about what the market and technical indicators look like after studying Ehlers' theory. First of all, Ehlers is an expert in the field of digital signal processing (DSP), and he introduced this method into technical analysis. Here are his main reasons and viewpoints for using this method:
1. **Market prices as time series data**: JFE believes that the price data of financial markets can be viewed as a discrete time series system. This means that market prices are similar to digital signals (such as audio signals), consisting of a series of data points that change over time.
2. **Market periodicity**: JFE observed that financial markets often exhibit periodicity, and digital signal processing is used to analyze the periodicity and other components in signals. By appropriately applying DSP techniques, we can more accurately determine market cycles and predict future price movements.
3. **Noise filtering**: Digital signal processing techniques help analysts filter out random noise in price data, allowing clearer observation of true market trends and patterns.
4. **Adaptation to cycles**: Unlike traditional fixed-period indicators, indicators developed using DSP techniques can adapt to the current market cycle, providing more accurate and timely trading signals.
5. **Filters and transforms**: He designed a series of filters and transforms, such as MESA, Fisher transform, etc., to help identify and utilize market periodicity.
6. **Nonlinear systems**: He also believes that since the market is a nonlinear system, traditional linear methods may not always be effective. Therefore, his techniques often take into account this nonlinear nature of the market.
Regarding the question of whether this methodology is correct, like all technical analysis methods, there is no one method that is absolutely correct. However, JFE's methods and indicators have been accepted by many traders and analysts and are considered to be very effective tools under certain market conditions. But like all trading tools, they should be used in conjunction with other analysis methods and strategies, always considering risk management.
JFE views market prices as discrete time series systems because price data is usually reported at fixed time intervals (such as daily, hourly, or minute-by-minute), with each time point having a specific value. This is very similar to discrete signals in digital signal processing, where signals are also composed of a series of data points with a fixed interval in time.
If the above was too profound, let's explain Ehlers' market physics with a simple concept: Do you think the essence of moving averages and oscillators in technical indicators is the same?
According to Ehlers' viewpoint, moving averages and oscillators are essentially similar. His view is that all technical indicators, whether moving averages or oscillators, are filters that extract certain information from market data. In some of his work, JFE points out that oscillators can be seen as a variation of moving averages, or more specifically, they are different types of filters. For example, a simple moving average (SMA) is a low-pass filter that allows low-frequency price movements to pass while filtering out high-frequency noise. Oscillators, such as RSI or MACD, can be seen as band-pass filters that extract signals in specific frequency ranges. Therefore, JFE's view is that different technical indicators only apply different mathematical methods to process and interpret market data, but they are essentially filters. This is why he uses advanced signal processing techniques, such as Hilbert transforms, in designing indicators.
Therefore, according to John F. Ehlers (JFE), filters can be classified. He believes that all technical indicators in the market are some form of filters. According to his classification method, filters can be divided into the following types:
1. **Low Pass Filter (LPF)**: This type of filter allows low-frequency components to pass through while filtering out high-frequency components. The Simple Moving Average (SMA) is an example of a low pass filter.
2. **High Pass Filter (HPF)**: In contrast to the low pass filter, it allows high-frequency components to pass through while filtering out low-frequency components.
3. **Band Pass Filter (BPF)**: This filter only allows components within a specific frequency range to pass through. Many oscillators, such as RSI or MACD, can be considered as some form of band pass filter as they typically focus on price movements within a specific range.
4. **Band Stop Filter (BRF)**: This filter blocks components within a specific frequency range while allowing signals of other frequencies to pass through.
Here are some common low pass filter technical indicators:
**Simple Moving Average (SMA)**
**Exponential Moving Average (EMA)**
**Weighted Moving Average (WMA)**
**Triple Exponential Moving Average (TEMA)**
**Double Exponential Moving Average (DEMA)**
**Hull Moving Average (HMA)**
These indicators work by averaging or weighted averaging the price or other indicator's historical data in some form, hence they are all referred to as low pass filters. The goal of a low pass filter is to allow low-frequency (long-term) price trends to pass through while filtering out high-frequency (short-term) noise or volatility.
In technical analysis, high pass filters (HPF) are not as common as low pass filters like moving averages because they primarily focus on quick, short-term changes in price, which are often considered market "noise". However, in some applications, this "noise" or short-term changes can be valuable. Here are some indicators that can be considered high pass filters or at least have high pass filter characteristics:
**Rate of Change (ROC)**: ROC is an indicator that measures the rate of price change and focuses on quick price changes.
**Momentum**: Similar to ROC, the momentum indicator measures the change in price relative to a past period.
**First Derivative**: Although not a common indicator, calculating the first derivative of price or other indicators can be considered a high pass filter. This is an interesting fusion of mathematics and physics, and I plan to write a separate article about it. Learning about trading can definitely enhance your application of mathematical and physical knowledge, haha.
It should be noted that the above indicators may not be true high pass filters, but they focus on quick and temporary changes in price, hence they have high pass filter characteristics to some extent.
Band pass filters (BPF) are not as evident in technical analysis as low pass and high pass filters, but they do exist. Band pass filters only allow signals within a specific frequency range to pass through while filtering out others. This can help analysts focus more on specific market cycles. Many technical indicators, although not entirely band pass filters (not 100% conforming to the physics definition of a band pass filter), have similar characteristics because they focus on specific price change periods or ranges. Here are some technical indicators that may have band pass filter characteristics:
**Stochastic Oscillator**: This indicator measures the current price relative to its past range. Although it is not a pure band pass filter, it does focus on a specific price change range.
**Relative Strength Index (RSI)**: RSI measures the relative strength of price increases and decreases and typically ranges from 0 to 100.
**Moving Average Convergence Divergence (MACD)**: Although based on the difference between two moving averages, MACD focuses on the specific relationship between these two averages, thereby having some band pass characteristics.
**Commodity Channel Index (CCI)**: CCI measures the deviation of commodity or stock prices from their average prices.
The above-listed indicators may not be pure band pass filters, but to some extent, they all emphasize a specific range or period of price data. These band pass filter indicators are often used to identify overbought or oversold market conditions or to identify potential market turning points. Overbought and oversold signals are often signs to identify them.
Band stop filters (also known as notch filters) are not commonly used directly in technical analysis. The purpose of this filter is to suppress or filter out signals within a specific frequency range while allowing signals of other frequencies to pass through. 99% of indicators do not possess the characteristics of pure band stop filters. However, considering the working principle of band stop filters, there are some similar indicators, such as:
**High-Low Difference**: Some strategies and indicators may use the difference between the high and low prices to measure intra-day price changes. This method can filter out intra-day noise to some extent, especially when the market trading range is narrow.
However, the above-mentioned indicators are not truly designed as band stop filters. In practical financial market analysis, pure band stop filters are less common, and there are more applications of low pass, high pass, or band pass filters. If you have specific needs or purposes, you may need customized strategies or indicators to achieve similar effects to band stop filters.
The reason why I consider the high-low difference to some extent as a band stop filter is that it removes specific price movements within the day and retains a broader range of fluctuations. However, this analogy is relative because in traditional signal processing, band stop filters are usually based on frequency rather than time, as high-low difference does. In summary, although the high-low difference is not a band stop filter in the traditional sense, it does provide similar effects to some extent, namely filtering out specific intra-day price dynamics and retaining their range of fluctuations.
Based on our previous discussion and the typical characteristics of technical indicators, the technical indicators seen by me can be classified as follows:
**Low Pass Filters**: These filters allow long-term (low-frequency) trends to pass through while suppressing short-term (high-frequency) noise.
- Moving Averages (e.g., SMA, EMA, WMA, etc.)
- Bollinger Bands
**High Pass Filters**: These filters allow short-term (high-frequency) fluctuations to pass through while reducing long-term (low-frequency) trends.
- Some difference or rate of change indicators, such as Momentum or Rate of Change (these indicators can be considered as emphasizing short-term price changes)
**Band Pass Filters**: These filters emphasize price changes within a specific time range or period while suppressing changes that are too long or too short.
- Stochastic Oscillator (focuses on a specific price change range)
- RSI (considers price dynamics within a specific time window)
- MACD (although its core is based on the difference between two EMAs, it emphasizes price dynamics within a specific time range to some extent)
**Band Stop Filters**: Within commonly used technical indicators, true band stop filters are not common. However, the high-low difference can be approximated as having band stop characteristics as it aims to remove long-term trends to better analyze short-term or periodic fluctuations in price.
It should be noted that these classifications are a broad interpretation based on the concept of filters, combined with the common uses and characteristics of technical indicators. Many technical indicators were not designed with filtering as their primary purpose, so strictly classifying them as a certain type of filter may have some ambiguity. However, regardless, did today's article provide you with a different perspective? If so, give me a thumbs up.
How-to use Ichimoku Cloud to find out swing entries?The Ichimoku Cloud is a technical analysis indicator used to identify potential trend reversals, support and resistance levels, and generate entry and exit signals in financial markets. It was developed by a Japanese journalist named Goichi Hosoda, who went by the pen name Ichimoku Sanjin.
The Ichimoku Cloud consists of several components, including the Tenkan-sen (Conversion Line), Kijun-sen (Base Line), Senkou Span A (Leading Span A), Senkou Span B (Leading Span B), and the Cloud. The Tenkan-sen and Kijun-sen lines are calculated based on the average of the highest high and lowest low over a specific period of time. The Senkou Span A is the average of the Tenkan-sen and Kijun-sen, plotted ahead of the current price. The Senkou Span B is calculated based on the average of the highest high and lowest low over a longer period of time, also plotted ahead of the current price. The Cloud is the area between Senkou Span A and Senkou Span B and is often used to identify potential support and resistance levels.
The Ichimoku Cloud with Entry Signals script provided above is a TradingView Pine script that plots the Ichimoku Cloud on a chart, along with entry signals. The entry signals are generated based on the crossover and crossunder of the Tenkan-sen and Kijun-sen lines, as well as the relationship of the closing price with Senkou Span A and Senkou Span B. When the conditions for a long entry signal are met, a green triangle-up shape is plotted below the price bars. Conversely, when the conditions for a short entry signal are met, a red triangle-down shape is plotted above the price bars.
It's important to note that the Ichimoku Cloud is a versatile indicator that can be used in various ways, including identifying trends, determining support and resistance levels, and generating entry and exit signals. Traders and investors often use it in conjunction with other technical analysis tools and indicators to make informed trading decisions.
This piece of code is a TradingView indicator script used to plot Ichimoku Cloud and display entry signals. It is written in Pine Script language.
First, the `indicator` function is used to set the title and short title of the indicator and overlay it on the main chart.
Next, two parameters `tenkanPeriod` and `kijunPeriod` are defined to represent the calculation period of Tenkan-sen (Conversion Line) and Kijun-sen (Base Line) respectively. Then, the `ta.sma` function is used to calculate the values of Tenkan-sen and Kijun-sen, and they are plotted on the chart using the `plot` function.
After that, the value of Senkou Span A (Leading Span A) is calculated using the `math.avg` function, and it is plotted on the chart using the `plot` function. Similarly, the value of Senkou Span B (Leading Span B) is calculated and plotted.
Then, the `fill` function is used to fill the area between Senkou Span A and Senkou Span B with color, forming the cloud.
Finally, entry signals are determined based on certain conditions. If the conditions are met, the `plotshape` function is called to plot arrow shapes at the corresponding positions to represent entry points.
HOW-TO develop a MartinGale Scalping Strategy**MartinGale Strategy** is a popular money management strategy used in trading. It is commonly applied in situations where the trader aims to recover from a losing streak by increasing the position size after each loss.
In the MartinGale Strategy, after a losing trade, the trader doubles the position size for the next trade. This is done in the hopes that a winning trade will eventually occur, which will not only recover the previous losses but also generate a profit.
The idea behind the MartinGale Strategy is to take advantage of the law of averages. By increasing the position size after each loss, the strategy assumes that eventually, a winning trade will occur, which will not only cover the previous losses but also generate a profit. This can be especially appealing for traders looking for a quick recovery from a losing streak.
However, it is important to note that the MartinGale Strategy carries significant risks. If a trader experiences a prolonged losing streak or lacks sufficient capital, the strategy can lead to substantial losses. The strategy's reliance on the assumption of a winning trade can be dangerous, as there is no guarantee that a winning trade will occur within a certain timeframe.
Traders considering implementing the MartinGale Strategy should carefully assess their risk tolerance and thoroughly understand the potential drawbacks. It is crucial to have a solid risk management plan in place to mitigate potential losses. Additionally, traders should be aware that the strategy may not be suitable for all market conditions and may require adjustments based on market volatility.
In summary, the MartinGale Strategy is a money management strategy that involves increasing the position size after each loss in an attempt to recover from a losing streak. While it can offer the potential for quick recovery, it also comes with significant risks that traders should carefully consider before implementing it in their trading approach.
The MartinGale Scalping Strategy is a trading strategy designed to generate profits through frequent trades. It utilizes a combination of moving average crossovers and crossunders to generate entry and exit signals. The strategy is implemented in TradingView's Pine Script language.
The strategy begins by defining input variables such as take profit and stop loss levels, as well as the trading mode (long, short, or bidirectional). It then sets a rule to allow only long entries if the trading mode is set to "Long".
The strategy logic is defined using SMA (Simple Moving Average) crossover and crossunder signals. It calculates a short-term SMA (SMA3) and a longer-term SMA (SMA8), and plots them on the chart. The crossoverSignal and crossunderSignal variables are used to track the occurrence of the crossover and crossunder events, while the crossoverState and crossunderState variables determine the state of the crossover and crossunder conditions.
The strategy execution is based on the current position size. If the position size is zero (no open positions), the strategy checks for crossover and crossunder events. If a crossover event occurs and the trading mode allows long entries, a long position is entered. The entry price, stop price, take profit price, and stop loss price are calculated based on the current close price and the SMA8 value. Similarly, if a crossunder event occurs and the trading mode allows short entries, a short position is entered with the corresponding price calculations.
If there is an existing long position and the current close price reaches either the take profit price or the stop loss price, and a crossunder event occurs, the long position is closed. The entry price, stop price, take profit price, and stop loss price are reset to zero.
Likewise, if there is an existing short position and the current close price reaches either the take profit price or the stop loss price, and a crossover event occurs, the short position is closed and the price variables are reset.
The strategy also plots entry and exit points on the chart using plotshape function. It displays a triangle pointing up for a buy entry, a triangle pointing down for a buy exit, a triangle pointing down for a sell entry, and a triangle pointing up for a sell exit.
Overall, the MartinGale Scalping Strategy aims to capture small profits by taking advantage of short-term moving average crossovers and crossunders. It incorporates risk management through take profit and stop loss levels, and allows for different trading modes to accommodate different market conditions.
HOW-TO combine CCI and RSI?CCI-RSI Combo indicator is a combination indicator that includes CCI and RSI. It uses some parameters to calculate the values of CCI and RSI, and generates corresponding charts based on these values. On the chart, when CCI exceeds 100 or falls below -100, yellow or magenta filling areas are displayed. Additionally, gradient colors are used on the RSI chart to represent different value ranges. Based on the values of CCI and RSI, buying or selling signals can be identified and "B" or "S" labels are displayed at the corresponding positions. It utilizes some technical indicators and logic to generate buying and selling signals, and displays the corresponding labels on the chart.
Here are the main parts of the code:
1. Definition of some variables:
- `N`, `M`, `N1`: Parameters used to calculate CCI and RSI.
- `xcn(cond, len)` and `xex(cond, len)`: Two functions used to calculate the number of times a condition is met.
2. Calculation of CCI (Commodity Channel Index):
- Calculate the CCI value based on the formula `(TYP - ta.sma(TYP, M)) / (0.015 * ta.stdev(TYP, M))`.
- Use the `plot()` function to plot CCI on the chart and set the color based on its value.
3. Calculation of RSI (Relative Strength Index):
- First calculate RSI1 by taking the average of positive differences between closing prices and the average of all absolute differences, and then multiplying by 100.
- Then use the ALMA function to transform RSI1 into a smoother curve.
- Use the `plot()` function to plot RSI on the chart and select gradient colors for shading based on its value.
4. Setting up the gradient color array:
- Create a color array using `array.new_color()` and add a series of color values to it.
5. Generating buying and selling signals based on conditions:
- Use logical operators and technical indicator functions to determine the conditions for buying and selling.
- Use the `label.new()` function to draw the corresponding labels on the chart to represent buying or selling signals.
How-to use SuperJThe SuperJ indicator is a powerful tool that utilizes VWMA (Volume Weighted Moving Average) and ALMA (Arnaud Legoux Moving Average) to filter and enhance the KDJ indicator, resulting in a smoother J line and the creation of the SuperJ indicator. By incorporating TVMA (Triggered Volume Moving Average), the SuperJ indicator can generate trigger signals that can form bullish and bearish crossovers with the J line, creating an oscillating pattern.
The combination of VWMA and ALMA helps to remove noise from the market and provides clearer trading signals. This is particularly useful when the market is highly volatile or the trend is ambiguous. The oscillations of the J line can help traders identify the true trend and avoid being misled by false signals.
Furthermore, by considering the values and trends of the J line in conjunction with other technical analysis tools, traders can make more accurate assessments of market trends and price movements. For example, when combined with moving averages, the SuperJ indicator can enhance the ability to identify price reversal points.
The SuperJ indicator also offers benefits in assessing overbought and oversold conditions in the market. By observing the values and trends of the J line, traders can more accurately evaluate market sentiment and strength. When the J line is above 80, it may indicate an overly optimistic market with a risk of overbought conditions. Conversely, when the J line is below 20, it may indicate an overly pessimistic market with an opportunity for oversold conditions. These signals can assist traders in determining when to buy or sell.
In summary, the SuperJ indicator, derived from the combination of VWMA, ALMA, and TVMA, provides traders with a valuable tool for identifying overbought and oversold conditions, predicting price reversals, and generating high-quality trading signals. Its application as a "buy low, sell high" strategy element is highly effective in maximizing trading opportunities and optimizing profitability.
HOW-TO use RAVI as a volatility filter?The Range Action Verification Index (RAVI) is a technical indicator used in trading to measure the strength of a trend. It compares two simple moving averages (SMAs) to determine the market's momentum.
To calculate RAVI, we subtract the shorter SMA from the longer SMA, and then divide the result by the longer SMA. This value is then multiplied by 100 to express it as a percentage.
The RAVI indicator helps traders identify whether the market is in a trending or range-bound phase. When the RAVI value is positive, it indicates a bullish trend, suggesting that the market is in an uptrend. Conversely, a negative RAVI value indicates a bearish trend or a downtrend.
Traders can use the RAVI indicator in several ways. Here are a few common strategies:
1. **Trend confirmation**: Traders can use RAVI to confirm the strength of a trend identified by other indicators or price patterns. If the RAVI value aligns with the direction of the trend, it provides additional confirmation.
2. **Overbought and oversold conditions**: Traders can use extreme RAVI values to identify overbought or oversold conditions in the market. When the RAVI value reaches high positive or negative levels, it suggests that the market may be due for a reversal or a retracement.
3. **Divergence**: Traders can look for divergences between the RAVI indicator and the price action. For example, if the price makes a higher high, but the RAVI value makes a lower high, it could indicate a weakening trend and a potential reversal.
As with any technical indicator, it is essential to use RAVI in conjunction with other tools and analysis techniques to make informed trading decisions. Traders should also consider factors such as market conditions, risk management, and other supporting indicators to validate their trading strategies.
In this indicator, an additional simple moving average (SMA) is introduced to consider long-term bias. This modification allows the Range Action Verification Index (RAVI) to be used as a volatility filter. By comparing the shorter SMA with this longer SMA, traders can gain insights into the market's volatility and adjust their trading strategies accordingly. This longer SMA helps provide a broader perspective on the market's trend and can be particularly useful for identifying and filtering out periods of high volatility. It is called "L2 Range Action Verification Index (RAVI) with 3 SMA". It calculates the RAVI value based on three simple moving averages (SMA). The code also includes calculations for the upper and lower bands, as well as color gradient settings. Finally, it plots the RAVI values and a midline.
It calculates the Range Action Verification Index (RAVI) using three Simple Moving Averages (SMA). The RAVI measures the difference between two SMAs divided by a third SMA, and then multiplied by 100.
The code starts with defining input parameters such as length, multiplier, and lengths for the three SMAs. Then it assigns the closing price to a variable called "price".
Next, it calculates the three SMAs using the "ta.sma" function from TradingView's built-in technical analysis library. The first SMA uses "sma1Length", the second SMA uses "sma2Length", and the third SMA uses "sma3Length".
After that, it calculates the RAVI by subtracting sma2 from sma1, dividing it by sma3, and multiplying it by 100.
Then it calculates additional values like basis (using another SMA), deviation (using standard deviation), upper band (basis + dev), and lower band (basis - dev).
Finally, it plots these values on a chart using different colors for each line. It also creates an array of gradient colors based on RSI values calculated from another indicator called ALMA. This gradient color is used to colorize the RAVI line.
Overall, this script helps visualize and analyze market trends based on moving averages and their relationship with price movements.
HOW-TO use My Ninja ChannelNinjaTrader is a popular charting software widely used for trading analysis and execution in financial markets such as stocks, futures, and forex. It provides rich features and tools to assist traders in technical analysis, trade strategy development, and trade execution. When I discovered a built-in channel technical indicator in NinjaTrader and became interested in it but didn't understand its principles, I utilized my extensive development experience to simulate a similar version based on its characteristics, naming it "Ninja Channel" for reference only. First, I observed the characteristics and behavior of the built-in channel indicator. Pay attention to how it calculates and plots the channels, as well as its parameter settings and usage methods. This information can help me better understand the principles and functions of this indicator. Then, I attempted to simulate a similar channel indicator using my existing knowledge of technical analysis tools. I used charting tools and indicators to plot and calculate the upper and lower boundaries of the channel according to my needs and preferences. Please remember that this simulated version is for reference only; there is no guarantee that it will be exactly identical to the built-in channel indicator in NinjaTrader. The original built-in indicator may have more complex calculation methods with more precise results. Therefore, before engaging in actual trading activities, it is recommended that you carefully study and understand the principles and usage methods of the original indicator.
The Ninja Channel belongs to a type of technical indicator used for analyzing price range fluctuations and trends. It constructs an upper-lower boundary channel based on high-low points or moving average line fluctuations of prices to assist traders in determining overbought/oversold zones, trend strength/weaknesses,and price reversal points.
The main uses of Ninja Channel include:
1.Trend determination: The Ninja Channel helps traders determine price trends.When prices are located above half partofthechannel,it indicates an uptrend; when prices are located below half partofthechannel,it indicates adowntrend. Traders can formulate corresponding trading strategies based on trend analysis.
2.Overbought/oversold zones: The upper and lower boundaries of the Ninja Channel can be used to determine overbought and oversold zones.When prices touch or exceed the upper boundary of the channel, it may indicate an overbought market condition with a potential price pullback or reversal; when prices touch or fall below the lower boundary of the channel, it may indicate an oversold market condition with a potential price rebound or reversal.Traders can develop counter-trend or reversal trading strategies based on these overbought/oversold zones.
3.Dynamic support and resistance: The upper and lower boundaries of the Ninja Channel can be seen as dynamic support and resistance levels.When prices approach the upper boundary ofthechannel,theupperboundarymay act asresistance, limiting upward price movement; when prices approachthelowerboundaryofthechannel,thelowerboundarymayactassupport,limiting downward price movement.Traderscanmake trading decisions based on these dynamic supportandresistancelevels.
Of course, for this newly created indicator,some aspects are still unfamiliar.However,the learning process can refer to some common channel-type technical indicators including Bollinger Bands,Keltner Channels,and Donchian Channels. Each indicator has its unique calculation method and parameter settings.Traderscan choose suitable indicators according to their own needsandpreferences.
In summary,NinjaChannel is a type of technical indicator used for analyzingprice range fluctuationsandtrends.It helps traders determine trends,overbought/oversoldzones,anddynamic support/resistance levels in order to formulate appropriate trading strategies.However,technicalindicatorsareonly auxiliary tools.Traderstill needsto consider other factorsandsrisk managementstrategiesinorder tomakemore informedtradingdecisions.
HOW-TO use Market Facilitation Index (MFI) capture trends?The Market Facilitation Index (MFI) is a technical indicator that measures the ease with which the market is able to move based on the volume traded. It was developed by Dr. Bill Williams as part of his trading system.
The MFI is calculated by taking into account the difference between the current typical price (average of high, low, and close) and the previous typical price, multiplied by the volume. This difference is then divided by the sum of volume over a specified period.
The MFI helps traders to identify periods of high or low market facilitation. High MFI values indicate that the market is facilitating trade and moving with ease, suggesting increased activity and potential trading opportunities. Conversely, low MFI values suggest a lack of market facilitation, indicating decreased activity and potential consolidation or sideways movement.
Traders can use the MFI in conjunction with other technical indicators and price analysis techniques to make informed trading decisions. It can be used to confirm trends, identify potential reversals, and assess the strength of market movements.
The Market Facilitation Index provides valuable insights into market dynamics, as it focuses on the relationship between price movement and trading volume. By incorporating volume data into its calculations, the MFI captures the impact of volume on market activity.
This indicator is particularly useful in identifying periods of market consolidation or range-bound trading. When the MFI shows low values, it suggests that market participants are hesitant and there may be a lack of clear trends. Traders can interpret this as a potential signal to avoid entering new positions or to tighten their stop-loss levels.
Conversely, when the MFI indicates high values, it signifies that the market is experiencing high levels of activity and price movement. This can be an indication of a strong trend, and traders may look for opportunities to enter positions in line with the prevailing market direction.
In addition to identifying market trends and potential reversals, the MFI can also help traders gauge the strength of price movements. By comparing the MFI values during different price swings or trends, traders can assess whether the market is experiencing increasing or decreasing levels of facilitation. This information can be valuable in determining the overall momentum and sustainability of a trend.
It's important to note that while the Market Facilitation Index can be a useful tool in technical analysis, it should not be used in isolation. Like any indicator, it has its limitations and may not always accurately reflect market conditions. Therefore, it is advisable to combine the MFI with other technical indicators, chart patterns, and fundamental analysis to gain a more comprehensive understanding of the market.
In conclusion, the Market Facilitation Index is a powerful technical indicator that measures the ease with which the market is able to move based on trading volume. It helps traders identify periods of high or low market facilitation, confirm trends, identify potential reversals, and assess the strength of market movements. However, it should be used in conjunction with other analysis methods for comprehensive market evaluation.
HOW-TO Use Nadaraya-Watson Envelope Improve SupertrendThe Nadaraya-Watson Envelope is a statistical technique used in finance and time series analysis. It is derived from the Nadaraya-Watson estimator, which is a non-parametric regression method.
In the context of the tradingview pine script provided, the Nadaraya-Watson Envelope is calculated based on the Volume Weighted Exponential Moving Average (VWEMA). The VWEMA is a type of moving average that takes into account both the price and volume of an asset. It is calculated by multiplying the closing price of the asset by its volume, then applying an exponential moving average to the result. This weighted moving average gives more importance to periods with higher trading volume.
The Nadaraya-Watson Envelope consists of an upper and lower envelope, which are calculated by applying a smoothing factor (alpha) to the standard deviation of the VWEMA. The standard deviation measures the volatility of the VWEMA, and the smoothing factor determines the width of the envelope. By adjusting the smoothing factor, traders can customize the sensitivity of the envelope to market conditions.
The Nadaraya-Watson Envelope can be used to identify potential overbought and oversold conditions in the market. When the price of an asset moves close to or beyond the upper envelope, it may indicate that the asset is overbought and due for a price correction. Conversely, when the price moves close to or below the lower envelope, it may indicate that the asset is oversold and due for a price rebound. Traders can use these signals to make informed decisions about buying or selling assets.
Additionally, the Nadaraya-Watson Envelope can be used to generate trading signals. For example, when the price crosses above the upper envelope, it may indicate a buy signal, suggesting that the price will continue to rise. Conversely, when the price crosses below the lower envelope, it may indicate a sell signal, suggesting that the price will continue to decline. Traders can use these signals in conjunction with other technical indicators and analysis to make well-informed trading decisions.
In summary, the Nadaraya-Watson Envelope is a powerful tool in technical analysis that combines the Volume Weighted Exponential Moving Average with upper and lower envelopes. It helps traders identify potential overbought and oversold conditions in the market and generate trading signals. By incorporating this technique into their analysis, traders can gain valuable insights into market dynamics and improve their trading strategies.
Supertrend is a popular technical indicator used to identify market trends and potential buy/sell signals. It combines the Nadaraya-Watson Envelope with other technical indicators to determine optimal entry and exit points in the market.
The principle behind the Supertrend indicator is to calculate the volatility and trend of prices using the Nadaraya-Watson Envelope. The Nadaraya-Watson Envelope creates upper and lower bands based on the statistical characteristics of price fluctuations. When the price touches or crosses the upper band, it suggests that the market may be overbought and a potential sell signal. Conversely, when the price touches or crosses the lower band, it indicates that the market may be oversold and a potential buy signal.
The advantage of using the Nadaraya-Watson Envelope to create the Supertrend indicator is its ability to capture long-term market trends while filtering out short-term noise. By considering the volatility of prices and statistical characteristics, the Nadaraya-Watson Envelope provides more accurate identification of overbought and oversold conditions, resulting in more reliable buy/sell signals.
The Supertrend indicator is widely applicable across various markets and timeframes. By combining the features of the Nadaraya-Watson Envelope with other technical indicators, traders can develop more effective trading strategies, improving their success rate and profitability.
In summary, the Nadaraya-Watson Envelope-based Supertrend indicator helps traders identify market trends and potential entry/exit points while filtering out short-term noise. It is a statistical analysis tool suitable for trading in various markets and timeframes.
HOW-TO evaluate volatility quality?The Volatility Quality Index (VQI) is an indicator used to measure the quality of market volatility. Volatility refers to the extent of price changes in the market. VQI helps traders assess market stability and risk levels by analyzing price volatility. This introduction may be a bit abstract, so let me help you understand it with a comparative metaphor if you're not immersed in various technical indicators.
Imagine you are playing a jump rope game, and you notice that sometimes the rope moves fast and other times it moves slowly. This is volatility, which describes the speed of the rope. VQI is like an instrument specifically designed to measure rope speed. It observes the movement of the rope and provides a numerical value indicating how fast or slow it is moving. This value can help you determine both the stability of the rope and your difficulty level in jumping over it. With this information, you know when to start jumping and when to wait while skipping rope.
In trading, VQI works similarly. It observes market price volatility and provides a numerical value indicating market stability and risk levels for traders. If VQI has a high value, it means there is significant market volatility with relatively higher risks involved. Conversely, if VQI has a low value, it indicates lower market volatility with relatively lower risks involved as well. The calculation involves dividing the range by values obtained from calculating Average True Range (ATR) multiplied by a factor/multiple.
The purpose of VQI is to assist traders in evaluating the quality of market volatility so they can develop better trading strategies accordingly.
Therefore, VQI helps traders understand the quality of market volatility for better strategy formulation and risk management—just like adjusting your jumping style based on rope speed during jump-rope games; traders can adjust their trading decisions based on VQI values.
The calculation of VQI indicator depends on given period length and multiple factors: Period length is used to calculate Average True Range (ATR), while the multiple factor adjusts the range of volatility. By dividing the range by values and multiplying it with a multiple, VQI numerical value can be obtained.
VQI indicator is typically presented in the form of a histogram on price charts. Higher VQI values indicate better quality of market volatility, while lower values suggest poorer quality of volatility. Traders can use VQI values to assess the strength and reliability of market volatility, enabling them to make wiser trading decisions.
It should be noted that VQI is just an auxiliary indicator; traders should consider other technical indicators and market conditions comprehensively when making decisions. Additionally, parameter settings for VQI can also be adjusted and optimized based on individual trading preferences and market characteristics.