Unbounded RSIIntroducing the concept of "Unbounded RSI".
Instead of indexing the average gain and average loss, over the time period of interest, we leave the average gain and loss unbounded. Instead we "bound" them by difference of each and smoothen out this difference in an envelope using exponential average. See code.
What this does to traditional RSI concept?
No concept of "overbought", "oversold"
No concept of "60-40", "70-30" bands and arguments over it
No concept of "Range Shifts"
...
How to use it?
I am generally a positional long trader. So I present my version. Of course, I expect each individual who decide to use this concept, to come up with their ideas, based on their style and temperament.
The points below, I apply on a Weekly Timeframe Chart.
Once, we see a long consolidation and price breakout, we should be able to see "Green" histogram bars. These appear, once we have the stock at least 20% up from the 52WL and the "Unbounded RSI" has turned positive. This can be a good time to "enter" into the scrip.
The height of the bars are significant, since they essentially show, that the "gap" between the avg. gain and avg. loss is widening, indicating momentum. Swing trading can thrive in these environments I guess.
Falling heights indicate that gaps to close, though, the "gap can still be green". This means, momentum is now falling. Swing traders and "quick buck makers", would ideally book profits here. If the color of the bars still remain "Green" it indicates that momentum has reduced but still the gains are "more" than loss on the timeperiod selected.
Once the histogram turns red, it means that the gain is now lower than loss. An increasing height underground, means this loss is widening. Generally, this will corelate with price action (not necessarily volume).
At this time, exits should be looked for, may be also check other factors/indicators to decide, but surely the momentum and the gain% over the timeperiod selected has now gone.
Note for Pine Coders:
The source code can easily be modified to develop this concept further.
For example:
Use different smoothing algorithms
Remove 52WL condition and introduce new additional conditions
Instead of price change of the stock for gain/loss calculations, we use the concept of Relative Strength (RS, not RSI) and measuere the gain/loss based on a benchmark index . I intend to work on this concept, soon.
You shall see a variable "unboundedRSI" which is actually a ratio of the Avg. Gain / Avg. Loss. This ratio is not plotted. It is kept there, for future use.
Many more
Центральные осцилляторы
Test - Most correlated assetThis is a simple test to find the most and least correlated assets in a list.
Risk Metric combinedAttempt at replicating a simplified Risk-Metric for BTC.
Original code written by user Oakley Wood.
Based on 3 different approaches:
- deviation from 4 year sma
- ln(btc / 20 wma)
- 50D MA / 50W MA
[blackcat] L2 Double EMA Convergence and Diverence (DEMACD)Introduction:
The " L2 Double EMA Convergence and Divergence (DEMACD)" is a custom technical indicator designed for use in TradingView. It's based on the concept of Double Exponential Moving Averages (DEMA) and incorporates elements from the well-known Moving Average Convergence Divergence (MACD). This guide aims to provide an understanding of its definition, history, calculation, operations, usage, input settings, and style.
1. Definition:
The DEMACD indicator is designed to detect changes in price trends using a modified approach of the traditional MACD, with a focus on reducing lag. It does this by comparing two DEMAs of different lengths, providing traders with signals of converging and diverging trends.
2. History:
The concept of DEMA was introduced by Patrick Mulloy in 1994 to reduce the lag inherent in traditional EMAs. MACD, developed by Gerald Appel in the 1970s, is a trend-following momentum indicator that shows the relationship between two moving averages of a security's price. The DEMACD combines the quick response feature of DEMA with the reliable trend analysis of MACD.
3. Calculation Method:
DEMACD is calculated through several steps:
Smoothed price S is first computed as (3 * close + high + low + open) / 6.
DAYLINE is calculated as 2 * EMA(S, len_ema) - EMA(EMA(S, 5), len_ema).
The mainTrendLine is the EMA of the EMA of the closing price over len_dema periods.
DIF is the difference between the DAYLINE and mainTrendLine.
DEA is the EMA of DIF over len_smooth periods.
Finally, DEMACD is calculated as (DIF - DEA) * 2.
4. Basic Operations and Comparison with MACD:
DEMACD's key feature is its reduced lag compared to the traditional MACD. While MACD uses EMA, DEMACD uses DEMA, providing a faster and more accurate response to price changes. This makes it particularly useful in volatile market conditions where traditional MACD may lag.
5. Usage:
Similar to MACD, DEMACD is used for trend confirmation, crossover signals, and divergences:
Trend confirmation is observed when the DIF line is above or below the DEA line.
Crossover signals are generated when the DIF line crosses the DEA line.
Divergences between the DEMACD and price action can signal potential trend reversals.
6. Input Settings:
Users can configure the following settings in TradingView:
len_ema: Length of the EMA for DAYLINE.
len_dema: Length of the EMA for the main trend line.
len_smooth: Smoothing length for DEA.
Adjusting these settings allows traders to tailor the indicator to different trading styles and market conditions.
7. Style:
The DEMACD in TradingView is represented with different colors and line thicknesses:
DIF is plotted in red with a line thickness of 2.
DEA is plotted in gray, also with a line thickness of 2.
DEMACD histogram changes color based on its value relative to its previous value and zero.
Conclusion:
The " L2 Double EMA Convergence and Divergence (DEMACD)" is a versatile indicator that combines the rapid response of DEMA with the trend-following abilities of MACD. Its reduced lag makes it a valuable tool for traders looking for timely market signals. Proper understanding and application of its settings can enhance its effectiveness in various trading strategies.
Monitor XThe Monitor X Indicator is a dynamic tool designed for any trading symbol, providing a quick and intuitive snapshot of price action relative to the latest closing level. With a user-friendly interface, this indicator allows traders to effortlessly gauge price movement and key levels.
Key Features:
1. Symbol Agnosticism:
Universally applicable to any trading symbol, the Monitor X Indicator ensures versatility and adaptability across various financial instruments.
2. Instant Price Insight:
Obtain immediate clarity on current market dynamics with a single glance. The indicator prominently displays the price line, facilitating swift analysis.
3. Last Close Comparison:
Easily assess the price's relationship to the most recent closing level. This feature provides valuable context for understanding market sentiment and potential support/resistance areas.
4. Customizable Display:
Tailor the indicator to your preferences with adjustable settings for line color, width, and opacity. This customization empowers traders to align the indicator with their unique trading strategies.
5. Intuitive Interface:
The clean and intuitive interface ensures a seamless user experience. Access crucial information effortlessly, allowing for quick decision-making.
How to Use:
1. Symbol Selection:
Apply the Monitor X Indicator to any trading symbol of your choice, ensuring a versatile tool for your entire portfolio.
2. Last Close Analysis:
Quickly assess how the current price relates to the previous close. This instant comparison aids in identifying potential entry and exit points.
3. Customization for Precision:
Fine-tune the indicator's appearance to suit your preferences. Adjust line colors, widths, and opacity settings for a personalized and efficient trading experience.
4. Swift Decision-Making:
Utilize the Monitor X Indicator for rapid decision-making. Gain insights into market movements at a glance, allowing you to stay ahead in dynamic trading environments.
Instant MACD (IMACD)The "Instant MACD" is a tailored version of the traditional Moving Average Convergence Divergence indicator, specifically designed to begin plotting with minimal data, such as in cases of high timeframe charts or newly listed trading instruments. Unlike the standard MACD that requires a substantial amount of data to provide accurate readings, the Instant MACD can deliver insights with as few as two candlesticks.
This iteration of the MACD utilizes the Chebyshev filter for the computation of both the fast and slow moving averages as well as for the signal line. The Chebyshev filter is known for its effectiveness in smoothing data series and reducing ripple effects, which is particularly advantageous when working with limited datasets.
The Instant MACD comprises several components. The histogram, which illustrates the difference between the MACD line and the signal line, adjusts its color based on the directional momentum; it transitions between shades of green and red as the histogram moves above or below the zero line and increases or decreases in value. The MACD line, depicted in blue, represents the disparity between the fast and slow Chebyshev moving averages. Complementing it is the signal line in orange, which is a Chebyshev-filtered mean of the MACD line and serves as an indicator of potential momentum shifts.
Additionally, the indicator includes a zero line for reference, aiding in the visualization of the convergence or divergence of the MACD and signal lines. To enhance its utility, the script encompasses alert conditions to notify users when there is a change in the trend of the histogram—specifically, when it transitions from a rising to a falling state and vice versa, potentially indicating shifts in market momentum.
Overall, the Instant MACD is an innovative tool for traders who require early trend signals in scenarios where traditional MACD analysis might be hampered by the lack of extensive historical data.
tl;dr this is identical to the regular macd but it starts working almost instantly.
CCI based support and resistance strategy
WARNING:
Commissions and slippage has not been considered! Don’t take it easy adding commissions and slippage could turns a fake-profitable strategy to a real disaster.
We consider account size as 10k and we enter 1000 for each trade.
Less than 100 trades is too small sample community and it’s not reliable, Also the performance of the past do not guarantee future performance. This result was handpicked by author and will differ by other timeframes, instruments and settings.
*PLEASE SHARE YOUR SETTINGS THAT WORK WITH THE COMMUNITY.
Introduction:
The CCI-based dynamic support and resistance is a "Bands and Channels" kind of indicator consisting an upper and lower band. This is a strategy which uses CCI-based (Made by me) indicator to execute trades.
SL and TP are calculated based on max ATR during last selected time period. You can edit strategy settings using "Ksl", "Ktp" and the other button for time period. “KSL” and “KTP” are 2.5 and 5 by default.
Bands are calculated regarding CCI previous high and low pivot. CCI length, right pivot length and left pivot length are 50.
A dynamic support and resistance has been calculated using last upper-cci minus a buffer and last lower-cci plus the buffer. The buffer is 10.
If "Trend matter?" button is on you can detect trend by color of the upper and lower line. Green is bullish and red is bearish! "Trend matter?" is on.
The "show mid?" button makes mid line visible, which is average of upper and lower lines, visible. The button is not active by default.
Reaction to the support could be a buy signal while a reaction to the resistance could interpreted as a sell signal.
How this strategy work?
Donald Lambert, a technical analyst, created the CCI, or Commodity Channel Index, which he first published in 1980. CCI is calculated regarding CCI can be used both as trend-detector or an oscillator. As an oscillator most traders believe in static predefined levels. Overbought and oversold candles which are clear in the chart could be used as sell and buy signals.
During my trading career I’ve noticed that there might be some reversal points for the CCI. I believe CCI could have to potential to reverse more from lately reversal point. Of course, just like other trading strategies we are talking about probabilities. We do not expect a win trade each time.
On price chart
Now this the question! What price should the instrument reach that CCI turns to be equal to our reversing aim for CCI? Imagine we have found last important bearish reversal of CCI in 200. Now, if we need the CCI to be 200 what price should we wait for?
How to calculate?
This is the CCI formula:
CCI = (Typical Price - SMA of TP) / (0.015 x Mean Deviation)
Where, Typical Price (TP) = (High + Low + Close)/3
For probable reversing points, high and low pivots of 50 bars have been used.
So we do have an Upper CCI and a Lower CCI. They are valid until the next pivot is available.
By relocating factors in CCI formula you can reach the “Typical Price”.
“
Typical Price = CCI (0.015 * Mean Deviation) + SMA of TP
So we could have a Support or Resistance by replacing CCI with Upper and Lower CCI.
A buy signal is valid if the trend is bullish (or “trend matter” is off) and lowest low of last 2 candles is lower than support and close is greater than both support and open.
A Sell signal is produced in opposite situation.
There are 2+1 options for trend!
Trend matter box is on by default, which means we’ll just open trades in direction of the trend. It’s available to turn it off.
Other 2 options are cross and slope. Cross calculated by comparing fast SMA and slow SMA. The slope one differentiate slow SMA to last “n” one.
Considering last day and today highest ATR as the ATR to calculating SL and TP is our unique technique.
Divergence AnalyzerUnlock the potential of your trading strategy with the Divergence Analyzer, a sophisticated indicator designed to identify divergence patterns between two financial instruments. Whether you're a seasoned trader or just starting, this tool provides valuable insights into market trends and potential trading opportunities.
Key Features:
1. Versatility in Symbol Selection:
- Choose from a wide range of symbols for comparison, including popular indices like XAUUSD and SPX.
- Seamlessly toggle between symbols to analyze divergences and make informed trading decisions.
2. Flexible Calculation Options:
- Customizable options allow you to use a different symbol for calculation instead of the chart symbol.
- Fine-tune your analysis by selecting specific symbols for comparison based on your trading preferences.
3. Logarithmic Scale Analysis:
- Utilizes logarithmic scales for accurate representation of price movements.
- Linear regression coefficients are calculated on the logarithmic scale, providing a comprehensive view of trend strength.
4. Dynamic Length and Smoothing:
- Adjust the length parameter to adapt the indicator to different market conditions.
- Smoothed linear regression with exponential moving averages enhances clarity and reduces noise.
5. Standard Deviation Normalization:
- Normalizes standard deviations over 200 periods, offering a standardized view of price volatility.
- Easily compare volatility levels across different symbols for effective divergence analysis.
6. Color-Coded Divergence Visualization:
- Clearly distinguish positive and negative divergences with customizable color options.
- Visualize divergence deltas with an intuitive color scheme for quick and effective interpretation.
7. Symbol Information Table:
- An included table provides at-a-glance information about the selected symbols.
- Identify Symbol 1 and Symbol 2, along with their corresponding positive and negative divergence colors.
How to Use:
1. Select symbols for analysis using the user-friendly inputs.
2. Customize calculation options based on your preferences.
3. Analyze the divergence delta plot for clear visual indications.
4. Refer to the symbol information table for a quick overview of selected instruments.
Empower your trading strategy with the Divergence Analyzer and gain a competitive edge in the dynamic world of financial markets. Start making more informed decisions today!
Instant RSI (IRSI)
Instant RSI is tailored for users seeking an effective RSI indicator for charts with limited historical data, such as new symbols or very high time frame charts. Its distinctiveness lies in employing a Chebyshev filter, an innovative approach that allows the RSI to initiate calculations with just two data points. The Chebyshev filter, traditionally used in signal processing, helps in smoothing data while minimizing lag, a critical aspect in fast-moving financial markets.
Key Features:
Chebyshev Filter Integration: The Chebyshev filter is fine-tuned to mimic a 14-period RMA's behavior, enhancing the RSI's responsiveness and accuracy with minimal data.
Customizable RSI and MA Settings: Users can modify the RSI's source, length, ripple effect, and style. An optional moving average overlay, also based on Chebyshev filtering, tuned to mimic an EMA set to 14.
Divergence Detection: I have also included the ability to adjust the divergence settings to allow for more flexibility over the built in RSI.
The script operates by applying the Chebyshev filter to the price movement's up and down components, forming the basis of the RSI calculation. When the moving average feature is activated, it further processes the RSI value through the Chebyshev filter for additional smoothing. This dual application of the Chebyshev filter is central to the script's design, offering a unique solution for situations where traditional RSI calculations might be less reliable due to data scarcity.
The divergence detection feature enhances the script's utility by signaling potential trend reversals, critical for strategic decision-making in trading. These features are visually represented on the chart, ensuring that users can easily interpret and react to the indicators.
In general this indicator should produce the exact same output as the built in RSI. This indicator is specifically designed to be used in conditions where the built in RSI will not work due to limited data.
In summary, the "Instant RSI" script is a practical option for those dealing with limited data scenarios, offering a unique blend of Chebyshev filter application for more responsive market analysis.
MACD Crossover with +/- FilterThis is to directly target when MACD crosses the Signal line. The purpose of this script is to target a +/- change of 3 in the MACD value after the most recent cross. It uses the value of the MACD line and holds it until a value of 3.00 + or - a crossover or crossunder happens. That's the significance of the red and green circles that appear on the chart. This is not financial advice, but I wanted to recreate what a friend of mine was doing manually and automate it for him.
The first circle that appears after MACD/SIGNAL lines cross would represent a potential trade idea. The circles after the first one match the intention of the first dot as they meet the condition of more than a value of -3 or +3 as the previous dot.
Inputs:
Standard Inputs as normal MACD (Moving Average Converging Divergence) within TradingView
Fast Length: User can change it to any value they want
Slow Length: User can change it to any value they want
Standard 12, 26, 9 as normal MACD // 9 being signal smoothing
Oscillator and Signal Line moving average type is using EMA's
Timeframe is dependent on user chart.
Circles are used for signaling the change in values. Red indicates a short-term bearish trend. Green indicates a short-term bullish trend.
Tested on lower timeframes:
1m, 3m, 5m, 15m, 60m
Not used as much on higher timeframes. Used for trading futures. This is what I use it for. It can be used for other futures than just NQ or ES, but those 2 are the ones that I've tested. Code it shown below for users to tinker with.
Style of indication symbol can be changed via settings within the indicator in the "Style" tab, as well as location of the symbol(s). Additionally, color can be changed as well, if you prefer different colors.
Not financial advice. Just trade ideas.
Relative Strength Trend Indicator (RSTI)This indicator is called the "Relative Strength Trend Indicator" (RSTI), designed to assess the relative strength of a trend.
Here is a detailed explanation of how it works and how traders can interpret it:
Indicator Operation:
1. Data Source (src): The indicator considers a data source, typically the closing price (close), but this can be adjusted according to the trader's preferences.
2. Period Length (Length): This determines the period used to calculate the simple moving average (SMA) of the data source. A longer period smoothes the indicator, while a shorter period makes it more responsive.
3. Multiplier (Multiplier): This is a multiplication factor applied to the Average True Range (ATR), adjusting the width of the bands.
4. Signal Length (Signal Length): This period is used to calculate the simple moving average of the relative strength (l_strength). It determines the sensitivity of the signal to changes in relative strength.
Interpretation of the Indicator:
1. Upper Strength Band (Upper Level): This line is drawn at 80 and represents a high strength level. When relative strength exceeds this value, it may indicate a potential overbought market.
2. Lower Strength Band (Lower Level): This line is drawn at 20 and represents a low strength level. When relative strength is below this value, it may indicate a potential oversold market.
3. RSTI Strength: The main line of the indicator, representing the calculated relative strength. When this line exceeds 50, it may indicate an uptrend, while a value below 50 may indicate a downtrend.
4. Filling Zones: These colored zones between levels 80 and 50, and between 50 and 20, can help quickly visualize relative strength. A colored zone above 50 indicates positive strength, while a colored zone below 50 indicates negative strength.
Qualities of the Indicator:
1. Adaptability: The use of ATR and the flexibility of parameters (length, multiplier, signal_length) allow the indicator to adapt to different market conditions.
2. Visual Clarity: Colored filling zones and horizontal lines make it easy to visualize relative strength levels.
3. Strength Signal: The signal line (RSTI Strength) allows traders to quickly spot changes in relative strength, facilitating decision-making.
4. Responsiveness: The combination of smoothed moving averages and relative strength indicators allows responsiveness to trend changes while reducing false signals.
It is essential to note that while this indicator can provide valuable insights, it is always recommended to use it in conjunction with other technical analysis tools for informed decision-making.
ROC & EMAIn summary, this allows you to plot the ROC, its EMA, and dynamically display the value of this EMA on the chart.
You can configure different lengths and colors.
Unpretentious code, just for the pleasure of sharing.
Thank you for sharing your comments with me, which will be welcome.
Ultimate Momentum"Ultimate Momentum" – Elevating Your Momentum Analysis
Experience a refined approach to momentum analysis with "Ultimate Momentum," a sophisticated indicator seamlessly combining the strengths of RSI and CCI. This tool offers a nuanced understanding of market dynamics with the following features:
1. Harmonious Fusion: Witness the dynamic interplay between RSI and CCI, providing a comprehensive understanding of market nuances.
2. Optimized CCI Dynamics: Delve confidently into market intricacies with optimized CCI parameters, enhancing synergy with RSI for a nuanced perspective on trends.
3. Standardized Readings: "Ultimate Momentum" standardizes RSI and CCI, ensuring consistency and reliability in readings for refined signals.
4. Native TradingView Integration: Immerse yourself in the reliability of native TradingView codes for RSI and CCI, ensuring stability and compatibility.
How RSI and CCI Work Together:
RSI (Relative Strength Index): Captures price momentum with precision, measuring the speed and change of price movements.
CCI (Commodity Channel Index): Strategically integrated to complement RSI, offering a unique perspective on price fluctuations and potential trend reversals.
Why "Ultimate Momentum"?
In a crowded landscape, "Ultimate Momentum" stands out, redefining how traders interpret momentum. Gain a profound understanding of market dynamics, spot trend reversals, and make informed decisions.
Your Insights Matter:
Share your suggestions to enhance "Ultimate Momentum" in the comments. Your feedback is crucial as we strive to deliver an unparalleled momentum analysis tool.
The Flash-Strategy with Minervini Stage Analysis QualifierThe Flash-Strategy (Momentum-RSI, EMA-crossover, ATR) with Minervini Stage Analysis Qualifier
Introduction
Welcome to a comprehensive guide on a cutting-edge trading strategy I've developed, designed for the modern trader seeking an edge in today's dynamic markets. This strategy, which I've honed through my years of experience in the trading arena, stands out for its unique blend of technical analysis and market intuition, tailored specifically for use on the TradingView platform.
As a trader with a deep passion for the financial markets, my journey began several years ago, driven by a relentless pursuit of a trading methodology that is both effective and adaptable. My background in trading spans various market conditions and asset classes, providing me with a rich tapestry of experiences from which to draw. This strategy is the culmination of that journey, embodying the lessons learned and insights gained along the way.
The cornerstone of this strategy lies in its ability to generate precise long signals in a Stage 2 uptrend and equally accurate short signals in a Stage 4 downtrend. This approach is rooted in the principles of trend following and momentum trading, harnessing the power of key indicators such as the Momentum-RSI, EMA Crossover, and Average True Range (ATR). What sets this strategy apart is its meticulous design, which allows it to adapt to the ever-changing market conditions, providing traders with a robust tool for navigating both bullish and bearish scenarios.
This strategy was born out of a desire to create a trading system that is not only highly effective in identifying potential trade setups but also straightforward enough to be implemented by traders of varying skill levels. It's a reflection of my belief that successful trading hinges on clarity, precision, and disciplined execution. Whether you are a seasoned trader or just beginning your journey, this guide aims to provide you with a comprehensive understanding of how to harness the full potential of this strategy in your trading endeavors.
In the following sections, we will delve deeper into the mechanics of the strategy, its implementation, and how to make the most out of its features. Join me as we explore the nuances of a strategy that is designed to elevate your trading to the next level.
Stage-Specific Signal Generation
A distinctive feature of this trading strategy is its focus on generating long signals exclusively during Stage 2 uptrends and short signals during Stage 4 downtrends. This approach is based on the widely recognized market cycle theory, which divides the market into four stages: Stage 1 (accumulation), Stage 2 (uptrend), Stage 3 (distribution), and Stage 4 (downtrend). By aligning the signal generation with these specific stages, the strategy aims to capitalize on the most dynamic and clear-cut market movements, thereby enhancing the potential for profitable trades.
1. Long Signals in Stage 2 Uptrends
• Characteristics of Stage 2: Stage 2 is characterized by a strong uptrend, where prices are consistently rising. This stage typically follows a period of accumulation (Stage 1) and is marked by increased investor interest and bullish sentiment in the market.
• Criteria for Long Signal Generation: Long signals are generated during this stage when the technical indicators align with the characteristics of a Stage 2 uptrend.
• Rationale for Stage-Specific Signals: By focusing on Stage 2 for long trades, the strategy seeks to enter positions during the phase of strong upward momentum, thus riding the wave of rising prices and investor optimism. This stage-specific approach minimizes exposure to less predictable market phases, like the consolidation in Stage 1 or the indecision in Stage 3.
2. Short Signals in Stage 4 Downtrends
• Characteristics of Stage 4: Stage 4 is identified by a pronounced downtrend, with declining prices indicating prevailing bearish sentiment. This stage typically follows the distribution phase (Stage 3) and is characterized by increasing selling pressure.
• Criteria for Short Signal Generation: Short signals are generated in this stage when the indicators reflect a strong bearish trend.
• Rationale for Stage-Specific Signals: Targeting Stage 4 for shorting capitalizes on the market's downward momentum. This tactic aligns with the natural market cycle, allowing traders to exploit the downward price movements effectively. By doing so, the strategy avoids the potential pitfalls of shorting during the early or late stages of the market cycle, where trends are less defined and more susceptible to reversals.
In conclusion, the strategy’s emphasis on stage-specific signal generation is a testament to its sophisticated understanding of market dynamics. By tailoring the long and short signals to Stages 2 and 4, respectively, it leverages the most compelling phases of the market cycle, offering traders a clear and structured approach to aligning their trades with dominant market trends.
Strategy Overview
At the heart of this trading strategy is a philosophy centered around capturing market momentum and trend efficiency. The core objective is to identify and capitalize on clear uptrends and downtrends, thereby allowing traders to position themselves in sync with the market's prevailing direction. This approach is grounded in the belief that aligning trades with these dominant market forces can lead to more consistent and profitable outcomes.
The strategy is built on three foundational components, each playing a critical role in the decision-making process:
1. Momentum-RSI (Relative Strength Index): The Momentum-RSI is a pivotal element of this strategy. It's an enhanced version of the traditional RSI, fine-tuned to better capture the strength and velocity of market trends. By measuring the speed and change of price movements, the Momentum-RSI provides invaluable insights into whether a market is potentially overbought or oversold, suggesting possible entry and exit points. This indicator is especially effective in filtering out noise and focusing on substantial market moves.
2. EMA (Exponential Moving Average) Crossover: The EMA Crossover is a crucial component for trend identification. This strategy employs two EMAs with different timeframes to determine the market trend. When the shorter-term EMA crosses above the longer-term EMA, it signals an emerging uptrend, suggesting a potential long entry. Conversely, a crossover below indicates a possible downtrend, hinting at a short entry opportunity. This simple yet powerful tool is key in confirming trend directions and timing market entries.
3. ATR (Average True Range): The ATR is instrumental in assessing market volatility. This indicator helps in understanding the average range of price movements over a given period, thus providing a sense of how much a market might move on a typical day. In this strategy, the ATR is used to adjust stop-loss levels and to gauge the potential risk and reward of trades. It allows for more informed decisions by aligning trade management techniques with the current volatility conditions.
The synergy of these three components – the Momentum-RSI, EMA Crossover, and ATR – creates a robust framework for this trading strategy. By combining momentum analysis, trend identification, and volatility assessment, the strategy offers a comprehensive approach to navigating the markets. Whether it's capturing a strong trend in its early stages or identifying a potential reversal, this strategy aims to provide traders with the tools and insights needed to make well-informed, strategically sound trading decisions.
Detailed Component Analysis
The efficacy of this trading strategy hinges on the synergistic functioning of its three key components: the Momentum-RSI, EMA Crossover, and Average True Range (ATR). Each component brings a unique perspective to the strategy, contributing to a well-rounded approach to market analysis.
1. Momentum-RSI (Relative Strength Index)
• Definition and Function: The Momentum-RSI is a modified version of the classic Relative Strength Index. While the traditional RSI measures the velocity and magnitude of directional price movements, the Momentum-RSI amplifies aspects that reflect trend strength and momentum.
• Significance in Identifying Trend Strength: This indicator excels in identifying the strength behind a market's move. A high Momentum-RSI value typically indicates strong bullish momentum, suggesting the potential continuation of an uptrend. Conversely, a low Momentum-RSI value signals strong bearish momentum, possibly indicative of an ongoing downtrend.
• Application in Strategy: In this strategy, the Momentum-RSI is used to gauge the underlying strength of market trends. It helps in filtering out minor fluctuations and focusing on significant movements, providing a clearer picture of the market's true momentum.
2. EMA (Exponential Moving Average) Crossover
• Definition and Function: The EMA Crossover component utilizes two exponential moving averages of different timeframes. Unlike simple moving averages, EMAs give more weight to recent prices, making them more responsive to new information.
• Contribution to Market Direction: The interaction between the short-term and long-term EMAs is key to determining market direction. A crossover of the shorter EMA above the longer EMA is an indicator of an emerging uptrend, while a crossover below signals a developing downtrend.
• Application in Strategy: The EMA Crossover serves as a trend confirmation tool. It provides a clear, visual representation of the market's direction, aiding in the decision-making process for entering long or short positions. This component ensures that trades are aligned with the prevailing market trend, a crucial factor for the success of the strategy.
3. ATR (Average True Range)
• Definition and Function: The ATR is an indicator that measures market volatility by calculating the average range between the high and low prices over a specified period.
• Role in Assessing Market Volatility: The ATR provides insights into the typical market movement within a given timeframe, offering a measure of the market's volatility. Higher ATR values indicate increased volatility, while lower values suggest a calmer market environment.
• Application in Strategy: Within this strategy, the ATR is instrumental in tailoring risk management techniques, particularly in setting stop-loss levels. By accounting for the market's volatility, the ATR ensures that stop-loss orders are placed at levels that are neither too tight (risking premature exits) nor too loose (exposing to excessive risk).
In summary, the combination of Momentum-RSI, EMA Crossover, and ATR in this trading strategy provides a comprehensive toolkit for market analysis. The Momentum-RSI identifies the strength of market trends, the EMA Crossover confirms the market direction, and the ATR guides in risk management by assessing volatility. Together, these components form the backbone of a strategy designed to navigate the complexities of the financial markets effectively.
1. Signal Generation Process
• Combining Indicators: The strategy operates by synthesizing signals from the Momentum-RSI, EMA Crossover, and ATR indicators. Each indicator serves a specific purpose: the Momentum-RSI gauges trend momentum, the EMA Crossover identifies the trend direction, and the ATR assesses the market’s volatility.
• Criteria for Signal Validation: For a signal to be considered valid, it must meet specific criteria set by each of the three indicators. This multi-layered approach ensures that signals are not only based on one aspect of market behavior but are a result of a comprehensive analysis.
2. Conditions for Long Positions
• Uptrend Confirmation: A long position signal is generated when the shorter-term EMA crosses above the longer-term EMA, indicating an uptrend.
• Momentum-RSI Alignment: Alongside the EMA crossover, the Momentum-RSI should indicate strong bullish momentum. This is typically represented by the Momentum-RSI being at a high level, confirming the strength of the uptrend.
• ATR Consideration: The ATR is used to fine-tune the entry point and set an appropriate stop-loss level. In a low volatility scenario, as indicated by the ATR, the stop-loss can be set tighter, closer to the entry point.
3. Conditions for Short Positions
• Downtrend Confirmation: Conversely, a short position signal is indicated when the shorter-term EMA crosses below the longer-term EMA, signaling a downtrend.
• Momentum-RSI Confirmation: The Momentum-RSI should reflect strong bearish momentum, usually seen when the Momentum-RSI is at a low level. This confirms the bearish strength of the market.
• ATR Application: The ATR again plays a role in determining the stop-loss level for the short position. Higher volatility, as indicated by a higher ATR, would warrant a wider stop-loss to accommodate larger market swings.
By adhering to these mechanics, the strategy aims to ensure that each trade is entered with a high probability of success, aligning with the market’s current momentum and trend. The integration of these indicators allows for a holistic market analysis, providing traders with clear and actionable signals for both entering and exiting trades.
Customizable Parameters in the Strategy
Flexibility and adaptability are key features of this trading strategy, achieved through a range of customizable parameters. These parameters allow traders to tailor the strategy to their individual trading style, risk tolerance, and specific market conditions. By adjusting these parameters, users can fine-tune the strategy to optimize its performance and align it with their unique trading objectives. Below are the primary parameters that can be customized within the strategy:
1. Momentum-RSI Settings
• Period: The lookback period for the Momentum-RSI can be adjusted. A shorter period makes the indicator more sensitive to recent price changes, while a longer period smoothens the RSI line, offering a broader view of the momentum.
• Overbought/Oversold Thresholds: Users can set their own overbought and oversold levels, which can help in identifying extreme market conditions more precisely according to their trading approach.
2. EMA Crossover Settings
• Timeframes for EMAs: The strategy uses two EMAs with different timeframes. Traders can modify these timeframes, choosing shorter periods for a more responsive approach or longer periods for a more conservative one.
• Source Data: The choice of price data (close, open, high, low) used in calculating the EMAs can be varied depending on the trader’s preference.
3. ATR Settings
• Lookback Period: Adjusting the lookback period for the ATR impacts how the indicator measures volatility. A longer period may provide a more stable but less responsive measure, while a shorter period offers quicker but potentially more erratic readings.
• Multiplier for Stop-Loss Calculation: This parameter allows traders to set how aggressively or conservatively they want their stop-loss to be in relation to the ATR value.
Here are the standard settings:
Triple Confirmation Kernel Regression Base [QuantraSystems]Kernel Regression Oscillator - BASE
Introduction
The Kernel Regression Oscillator (ᏦᏒᎧ) represents an advanced tool for traders looking to capitalize on market trends.
This Indicator is valuable in identifying and confirming trend directions, as well as probabilistic and dynamic oversold and overbought zones.
It achieves this through a unique composite approach using three distinct Kernel Regressions combined in an Oscillator. The additional Chart Overlay Indicator adds confidence to the signal.
This methodology helps the trader to significantly reduce false signals and offers a more reliable indication of market movements than more widely used indicators can.
Legend
The upper section is the Overlay. It features the Signal Wave to display the current trend.
Its Overbought and Oversold zones start at 50% and end at 100% of the selected Standard Deviation (default σ = 3), which can indicate extremely rare situations which can lead to either a softening momentum in the trend or even a mean reversion situation.
The lower one is the Base Chart - This Indicator.
It features the Kernel Regression Oscillator to display a composite of three distinct regressions, also displaying current trend.
Its Overbought and Oversold zones start at 50% and end at 100% of the selected Standard Deviation (default σ = 2), which can indicate extremely rare situations.
Case Study
To effectively utilize the ᏦᏒᎧ, traders should use both the additional Overlay and the Base
Chart at the same time. Then focus on capturing the confluence in signals, for example:
If the 𝓢𝓲𝓰𝓷𝓪𝓵 𝓦𝓪𝓿𝓮 on the Overlay and the ᏦᏒᎧ on the Base Chart both reside near the extreme of an Oversold zone the probability is higher than normal that momentum in trend may soften or the token may even experience a reversion soon.
If a bar is characterized by an Oversold Shading in both the Overlay and the Base Chart, then the probability is very high to experience a reversion soon.
In this case the trader may want to look for appropriate entries into a long position, as displayed here.
If a bar is characterized by an Overbought Shading in either Overlay or Base Chart, then the probability is high for momentum weakening or a mean reversion.
In this case the trade may have taken profit and closed his long position, as displayed here.
Please note that we always advise to find more confluence by additional indicators.
Recommended Settings
Swing Trading (1D chart)
Overlay
Bandwith: 45
Width: 2
SD Lookback: 150
SD Multiplier: 2
Base Chart
Bandwith: 45
SD Lookback: 150
SD Multiplier: 2
Fast-paced, Scalping (4min chart)
Overlay
Bandwith: 75
Width: 2
SD Lookback: 150
SD Multiplier: 3
Base Chart
Bandwith: 45
SD Lookback: 150
SD Multiplier: 2
Notes
The Kernel Regression Oscillator on the Base Chart is also sensitive to divergences if that is something you are keen on using.
For maximum confluence, it is recommended to use the indicator both as a chart overlay and in its Base Chart.
Please pay attention to shaded areas with Standard Deviation settings of 2 or 3 at their outer borders, and consider action only with high confidence when both parts of the indicator align on the same signal.
This tool shows its best performance on timeframes lower than 4 hours.
Traders are encouraged to test and determine the most suitable settings for their specific trading strategies and timeframes.
The trend following functionality is indicated through the "𝓢𝓲𝓰𝓷𝓪𝓵 𝓦𝓪𝓿𝓮" Line, with optional "Up" and "Down" arrows to denote trend directions only (toggle “Show Trend Signals”).
Methodology
The Kernel Regression Oscillator takes three distinct kernel regression functions,
used at similar weight, in order to calculate a balanced and smooth composite of the regressions. Part of it are:
The Epanechnikov Kernel Regression: Known for its efficiency in smoothing data by assigning less weight to data points further away from the target point than closer data points, effectively reducing variance.
The Wave Kernel Regression: Similarly assigning weight to the data points based on distance, it captures repetitive and thus wave-like patterns within the data to smoothen out and reduce the effect of underlying cyclical trends.
The Logistic Kernel Regression: This uses the logistic function in order to assign weights by probability distribution on the distance between data points and target points. It thus avoids both bias and variance to a certain level.
kernel(source, bandwidth, kernel_type) =>
switch kernel_type
"Epanechnikov" => math.abs(source) <= 1 ? 0.75 * (1 - math.pow(source, 2)) : 0.0
"Logistic" => 1/math.exp(source + 2 + math.exp(-source))
"Wave" => math.abs(source) <= 1 ? (1 - math.abs(source)) * math.cos(math.pi * source) : 0.
kernelRegression(src, bandwidth, kernel_type) =>
sumWeightedY = 0.
sumKernels = 0.
for i = 0 to bandwidth - 1
base = i*i/math.pow(bandwidth, 2)
kernel = kernel(base, 1, kernel_type)
sumWeightedY += kernel * src
sumKernels += kernel
(src - sumWeightedY/sumKernels)/src
// Triple Confirmations
Ep = kernelRegression(source, bandwidth, 'Epanechnikov' )
Lo = kernelRegression(source, bandwidth, 'Logistic' )
Wa = kernelRegression(source, bandwidth, 'Wave' )
By combining these regressions in an unbiased average, we follow our principle of achieving confluence for a signal or a decision, by stacking several edges to increase the probability that we are correct.
// Average
AV = math.avg(Ep, Lo, Wa)
The Standard Deviation bands take defined parameters from the user, in this case sigma of ideally between 2 to 3,
to help the indicator detect extremely improbable conditions and thus take an inversely probable signal from it to forward to the user.
The parameter settings and also the visualizations allow for ample customizations by the trader. The indicator comes with default and recommended settings.
For questions or recommendations, please feel free to seek contact in the comments.
BDC - Bitcoin (BTC) Dominance Change [Logue]Bitcoin Dominance Change. Interesting things tend to happen when the Bitcoin dominance increases or decreases rapidly. Perhaps because there is overexuberance in the market in either BTC or the alts. In back testing, I found a rapid 13-day change in dominance indicates interesting switches in the BTC trends. Prior to 2019, the indicator doesn't work as well to signal trend shifts (i.e., local tops and bottoms) likely based on very few coins making up the crypto market.
The BTC dominance change is calculated as a percentage change of the daily dominance. You are able to change the upper bound, lower bound, and the period (daily) of the indicator to your own preferences. The indicator going above the upper bound or below the lower bound will trigger a different background color.
Use this indicator at your own risk. I make no claims as to its accuracy in forecasting future trend changes of Bitcoin.
Price PressureDescription:
The Price Pressure Indicator, developed by OmegaTools, is a robust and versatile tool designed to assist traders in analyzing market dynamics and identifying potential trend shifts. This open-source script, offers a unique approach to understanding price pressure over specified periods, enhancing the user's ability to make informed trading decisions.
Key Features:
1. Dynamic Length Configuration: The indicator allows users to customize the length parameter, ranging from 9 to 100, providing flexibility in adapting to different market conditions.
2. Extensions Control: Traders can fine-tune the extension levels (ob) between 50 and 90, allowing for precise adjustments based on their risk tolerance and trading preferences.
3. Normalization and Oscillation: The script employs a normalization function to standardize price data, offering a clearer representation of market pressure. The resulting oscillator visualizes the normalized pressure, highlighting potential market trends.
4. Pressure Calculation: The indicator calculates price pressure by considering the difference between the previous high and the current close, as well as the difference between the current close and the previous low. This innovative approach enhances the accuracy of pressure analysis.
5. Smoothing Option: While the script currently uses a simple moving average for smoothing, traders have the option to explore other smoothing methods by uncommenting the "smt" input line.
6. Visual Clarity: The indicator provides a visually intuitive representation of pressure and signal lines, aiding traders in quickly interpreting market conditions. The color-coded display enhances user experience, with the ability to discern bullish and bearish pressures.
7. Premium and Discount Zones: The script identifies premium and discount areas, assisting traders in spotting potential buying or selling opportunities. The premium and discount lines can be adjusted based on individual risk tolerance and strategy.
How to Use:
1. Adjust the length and extension parameters based on your trading preferences.
2. Interpret the oscillator and signal lines for insights into market pressure.
3. Utilize premium and discount zones to identify potential entry or exit points.
4. Experiment with different smoothing options for a customized analysis.
Concepts and Methodology:
The Price Pressure Indicator utilizes a normalization function and oscillation to quantify market pressure. By calculating the difference between highs and lows, the script provides a nuanced understanding of current market conditions. The smoothing option further refines the analysis, offering traders a comprehensive tool for trend identification.
Explore, experiment, and leverage the power of the Price Pressure Indicator to enhance your trading strategy on TradingView.
Chaos CypherOverview
Technically a smooth linear rate transformation, the "Chaos Cypher" drew some inspiration from the principles of Markov and chaos. Aside from price action, this combination provides a different lens through which to observe and interpret market movements. Markov models are based on the principle that future states depend only on the current state, not on the sequence of events that preceded it. Chaos theory deals with systems that are highly sensitive to initial conditions, a concept popularly referred to as the butterfly effect.
Efficient with Minimal Data: Designed to perform efficiently, the CC indicator is particularly useful in situations regardless of extensive historical data, except for obvious back testing, while still providing strength at identifying potential overbought/oversold zones and critical divergences.
Simplified Momentum Analysis: With further inspiration from the triple smoothed exponential rate, the CC actually uses linear regression for its calculations. This approach allows for a clear and more straightforward identification of deviations in momentum. The smoothing helps allow it to provide details while still operating at a fast pace due to the regression speed.
Adaptable to Various Timeframes: The transformation calculation then employed effectively narrows its scope in relation to the pace, enhancing its applicability across multiple timeframes and periods. This flexibility makes it a versatile tool suitable for various strategies and market conditions.
Fisher Transform Style Presentation: The indicator is presented in a style reminiscent of the Fisher Transform. However, this method of the script recalculates based on every individual dataset. To maintain efficiency, the adjustable length only applies to the regression rate.
The Chaos Cypher when compared to the Fisher Transform
Inversion Option for Leads: Lastly, an intriguing find when testing this script is the potential of the inversion option. This aspect proved particularly useful when searching for pullbacks on a trending market.
Conclusion
This indicator is designed to be forward-thinking and attempts to combine theoretical concepts with practicality. It has the ability to work with minimal data, adapt to various timeframes, and provide clear views of market movements. It back tested very well even when unrealistically used as a sole instrument.
"Two states differing by imperceptible amounts may eventually evolve into two considerably different states ... If, then, there is any error whatever in observing the present state—and in any real system such errors seem inevitable—an acceptable prediction of an instantaneous state in the distant future may well be impossible....In view of the inevitable inaccuracy and incompleteness of weather observations, precise very-long-range forecasting would seem to be nonexistent." -Edward Norton Lorenz
Dynamic Volume-Volatility Adjusted MomentumThis Indicator in a refinement of my earlier script PC*VC Moving average Old with easier to follow color codes, overbought and oversold zones. This script has converted the previous script into a standardized measure by converting it into Z-scores and also incorporated a volatility based dynamic length option. Below is a detailed Explanation.
The "Dynamic Volume-Volatility Adjusted Momentum" or "Nasan Momentum Oscillator" is designed to capture market momentum while accounting for volume and volatility fluctuations. It leverages the Typical Price (TP), calculated as the average of high, low, and close prices, and introduces the Price Coefficient (PC) based on deviations from the simple moving average (SMA) across various time frames. Additionally, the Volume Coefficient (VC) compares current volume to SMA, and calculates Intraday Volatility (IDV) which gauges the daily price range relative to the close. Then intraday volatility ratio is calculated ( IDV Ratio) as the ratio of current Intraday Volatility (IDV) to the average of IDV for three different length periods, which provides a relative measure of current intraday volatility compared to its recent historical average. An inter-day ATR based Relative Volatility (RV) is calculated to adjusts for changing market volatility based on which the dynamic length adjustment adapts the moving average (standard length is 14). The PC *VC/IDV Ratio integrates price, volume, and volatility information which provides a volume and volatility adjusted momentum. This volume and volatility adjusted momentum is converted into a standardized Z-Score. The Z-Score measures deviations from the mean. Color-coded plots visually represent momentum, and thresholds aid in identifying overbought or oversold conditions.
The indicator incorporates a nuanced approach to emphasize the joint impact of price and volume while considering the stabilizing effect of lower intraday volatility. Placing the volume ratio (VC) in the numerator means that higher volume positively contributes to the overall ratio, aligning with the observation that increased volumes often accompany robust price movements. Simultaneously, the decision to include the inverse of intraday volatility (1/IDV) in the denominator acts as a dampener, reducing the impact of extreme intraday volatility on the momentum indicator. This design choice aims to filter out noise, giving more weight to significant price changes supported by substantial trading activity. In essence, the indicator's design seeks to provide a more robust momentum measure that balances the influence of price, volume, and volatility in the analysis of market dynamics.
OneThingToRuleThemAll [v1.4]This script was created because I wanted to be able to display a contextual chart of commonly used indicators for scalping and swing traders, with the ability to control the visual representation on the charts as their cross-overs, cross-unders, or changes of state happen in real time. Additionally, I wanted the ability to control how or when they are displayed. While looking through other community projects, I found they lacked the ability to full customize the output controls and values used for these indicators.
The script leverages standard RSI/MACD/VWAP/MVWAP/EMA calculations to help a trader visually make more informed decisions on entering or exiting a trade, depending on their understanding on what the indicators represent. Paired with a table directly on the chart, it allows a trader to quickly reference values to make more informed decisions without having to look away from the price action or look through multiple indicator outputs.
The main functionality of the indicator is controlled within the settings directly on the chart. There a user can enable the visual representations, or disable, and configure how they are displayed on the charts by altering their values or style types.
Users have the ability to enable/disable visual representations of:
The indicator chart
RSI Cross-over and RSI Reversals
MACD Uptrends and Downtrends
VWAP Cross-overs and Cross-unders
VWAP Line
MVWAP Cross-overs and Cross-unders
MVWAP Line
EMA Cross-overs and Cross-unders
EMA Line
Some traders like to use these visual indications as thresholds to enter or exit trades. Its best to find out which ones work the best with the security you are trying to trade. Personally, I use the table as a reference in conjunction with the RSI chart indicators to help me decide a logical trailing stop if I am scalping. Some users might like the track EMA200 crossovers, and have visual representations on the chart for when that happens. However, users may use the other indicators in other methods, and this script provides the ability to be able to configure those both visually and by value.
The pine script code is open source and itself is fairly straightforward, it is mostly written to provide the ultimate level of control the the user of the various indicators. Please reach out to me directly if you would like a further understanding of the code and an explanation on anything that may be unclear.
Enjoy :)
-dead1.
MACD of Relative Strenght StrategyMACD Relative Strenght Strategy :
INTRODUCTION :
This strategy is based on two well-known indicators: MACD and Relative Strenght (RS). By coupling them, we obtain powerful buy signals. In fact, the special feature of this strategy is that it creates an indicator from an indicator. Thus, we construct a MACD whose source is the value of the RS. The strategy only takes buy signals, ignoring SHORT signals as they are mostly losers. There's also a money management method enabling us to reinvest part of the profits or reduce the size of orders in the event of substantial losses.
RELATIVE STRENGHT :
RS is an indicator that measures the anomaly between momentum and the assumption of market efficiency. It is used by professionals and is one of the most robust indicators. The idea is to own assets that do better than average, based on their past performance. We calculate RS using this formula :
RS = close/highest_high(RS_Length)
Where highest_high(RS_Length) = highest value of the high over a user-defined time period (which is the RS_Length).
We can thus situate the current price in relation to its highest price over this user-defined period.
MACD (Moving Average Convergence - Divergence) :
This is one of the best-known indicators, measuring the distance between two exponential moving averages : one fast and one slower. A wide distance indicates fast momentum and vice versa. We'll plot the value of this distance and call this line macdline. The MACD uses a third moving average with a lower period than the first two. This last moving average will give a signal when it crosses the macdline. It is therefore constructed using the values of the macdline as its source.
It's important to note that the first two MAs are constructed using RS values as their source. So we've just built an indicator of an indicator. This kind of method is very powerful because it is rarely used and brings value to the strategy.
PARAMETERS :
RS Length : Relative Strength length i.e. the number of candles back to find the highest high and compare the current price with this high. Default is 300.
MACD Fast Length : Relative Strength fast EMA length used to plot the MACD. Default is 14.
MACD Slow Length : Relative Strength slow EMA length used to plot the MACD. Default is 26.
MACD Signal Smoothing : Macdline SMA length used to plot the MACD. Default is 10.
Max risk per trade (in %) : The maximum loss a trade can incur (in percentage of the trade value). Default is 8%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. Default is 400, meaning that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:ETHUSD in 8h timeframe with the parameters set by default.
ENTER RULES :
The entry rules are very simple : we open a long position when the MACD value turns positive. You are therefore LONG when the MACD is green.
EXIT RULES :
We exit a position (whether losing or winning) when the MACD becomes negative, i.e. turns red.
RISK MANAGEMENT :
This strategy can incur losses, so it's important to manage our risks well. If the position is losing and has incurred a loss of -8%, our stop loss is activated to limit losses.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
Enjoy the strategy and don't forget to take the trade :)
TSI Market Timer + Volatility MeterThis is the TSI Market Timer. It is years in the making and it is comprised of four indicators in one. The stock (or source) is run through an indicator called the True Strength Indicator with settings(5,15) , then the TSI is run on both the Index(SPY) by default and what I call a Trigger line which is basically the TSI applied to the DXY (US Dollar Index).
Midline Volatility Indicator:
Lastly, we have a volatility indicator on the midline. The colors of the midline indicate levels of volatility. For the lowest volatility in the last 100 days, the dot turns dark blue. For the lowest volatility in 30 days, the dot turns aqua. For regular volatility, it remains orange. And last, for higher volatility of the last 100 days, it turns red. These are more or less arbitrary but they do come in handy.
Settings for Green/Red Shading:
Next on the indicator are the settings. You can toggle a color change between the stock/source and the index(spy). If the stock/source is greater than the index, it will color the area in between a green and if it is below the index, it will be red.
There is also a toggle for the stock/source and the trigger/DXY. This will also show green when the stock is above the trigger and red if it is below the trigger.
By turning on both of these, you get light green and dark green areas as well as red and darker red areas. The lighter green represent when the stock is above both the index and the trigger and conversely for the red areas.
Settings for vertical line crossings:
When the stock crosses the trigger/dxy line, it shows a green vertical line signal. When the stock crosses below the trigger/dxy, a red vertical line is shown.
You can turn these off by toggling them in the settings.
Stacked Condition:
Lastly, we have a "stacked condition" which shows up as a white triangle at the bottom when the condition of the stock being above the index and the trigger below the zero line.
New Highs:
If you see the stock line turn lime green, this indicates a new high was reached for the last 255 days/periods. This is like a new 52 week high signal.
Note:
This indicator is made mostly for the stock market. It may work ok during the week for crypto but using the trigger/dxy and index lines on the weekends doesn't work too well as they will be flat.
Also note that this indicator is not a recommendation to buy or sell any stock/instrument. It is only a study of market conditions. Any analysis should be followed up with volume analysis or other confirming indicators.
Fisher Transform RevisitedFisher Transform developped by Ehlers is used mostly to detect peaks and troughs, which it does with little lag, but there are many false signals. Looking at its formula and construction, we can revisit it for the purpose of detecting trends and flat market.
How do we want to do that? There are 3 different actions:
Increase the default value from usual 9 or 10 to 30
Show the indicator as seen from upper time frame with synthetic rolling candles
Change the weights in first formula in order to saturate the input signal, push the trend data to the limits, so therefore leaving a good view when market is flat
As can be seen from the chart above, the revisited Fisher is above 2 for uptrend markets, below -2 for downtrending markets and in-between when the market is flat.
Notes
Weights for Fisher transform formula can be changed as parameters. Recommended valeus are 0.6 and 0.6 to saturate signal. You may come back to original formula by setting 0.33 and 0.66.
Parameter n allows view from upper time, a multiple of current time frame. n = 1 for current chart, n = 5 for 5 minutes view on the 1 min chart
Usage
Of course, it should be not be used in standalone mode. Indicator is for trend traders who can stay away when market is flat. Trend start when indicator goes above 2 but like all trade indicators, it will be late; it is therefore a good idea to change n back to 1 to get a timely entry, to be confirmed of course with other elements of technical analysis.
