Connors RSI with Down GapThe Connors RSI with Down Gap indicator is a technical tool designed to support Larry Connors' Terror Gap Strategy, which is part of his broader framework outlined in the book "Buy the Fear, Sell the Greed: 7 Behavioral Quant Strategies for Traders." This specific indicator integrates the ConnorsRSI calculation with a focus on detecting down gaps in price, providing insights into moments when panic selling may occur.
The ConnorsRSI
ConnorsRSI is a composite indicator developed by Larry Connors that combines three core components:
RSI: A short-term relative strength index measuring the speed and magnitude of price changes.
Streak RSI: Tracks consecutive up or down closes to assess momentum.
Percent Rank: Evaluates how the current close ranks in relation to past prices.
When combined, these three elements provide a nuanced view of short-term overbought or oversold conditions. ConnorsRSI readings below a certain threshold (commonly 30 or lower) suggest that the asset has been heavily sold, indicating potential exhaustion of selling pressure.
Behavioral Finance Insights
The Terror Gap Strategy is grounded in principles from behavioral finance, which studies how psychological factors affect market participants' decision-making. Specifically, the indicator exploits the fear and irrational behavior that often arise when traders face persistent losses, especially after a down gap. According to behavioral finance theories like prospect theory (Kahneman & Tversky, 1979), people tend to overreact to losses, leading to panic selling. This creates opportunities for contrarian traders who understand the psychology behind these market movements.
The ConnorsRSI with Down Gap indicator works because it identifies:
Overextended selling through the ConnorsRSI, where persistent price declines result in low RSI values (indicating panic).
Gap down days, where the opening price is below the previous day’s close, typically amplifying the sense of loss and fear for traders already in losing positions.
Why This Indicator Works
The psychology of losses makes traders more prone to selling during periods of fear, especially when confronted with a gap down after sustained price declines. This indicator, by combining ConnorsRSI with down gaps, offers a quantitative way to spot these moments of panic. Traders can take advantage of these signals to enter positions when the market is in a state of fear, often when there is potential for a reversion to the mean.
Indicator Mechanics
In the current implementation:
The ConnorsRSI is calculated using three components: a short-term RSI, streak RSI, and percent rank.
When the ConnorsRSI drops below a user-defined lower threshold, the indicator highlights oversold conditions.
If there is a down gap (open price lower than the previous close) and the ConnorsRSI is below the threshold, a label is displayed, signaling a potential opportunity to buy.
Practical Use and Application
For traders looking to implement the Terror Gap Strategy, this indicator provides a clear visual cue (via background coloring and labels) when conditions are ripe for a contrarian trade. It can be particularly useful for traders who thrive on taking advantage of fear-driven sell-offs.
However, to fully understand and apply this strategy effectively, it is recommended to purchase Larry Connors' book "Buy the Fear, Sell the Greed." The book provides detailed explanations of how to execute the strategy with precision, including insights into exit conditions, scaling into positions, and managing risk.
Conclusion
The ConnorsRSI with Down Gap indicator combines quantitative analysis with behavioral finance principles to exploit fear-driven market behavior. By utilizing this tool within a disciplined trading strategy, traders can potentially profit from temporary market inefficiencies caused by panic selling.
References
Kahneman, D., & Tversky, A. (1979). Prospect theory: An analysis of decision under risk. Econometrica, 47(2), 263-291.
Connors, L. (2013). Buy the Fear, Sell the Greed: 7 Behavioral Quant Strategies for Traders.
This indicator can be a valuable asset, but understanding its proper use within a broader strategy framework is essential. Purchasing Connors' book is a recommended step toward mastering the approach.
Oscillators
Median Kijun-Sen [InvestorUnknown]The Median Kijun-Sen is a versatile technical indicator designed for both trend-following strategies and long-term market valuation. It incorporates various display modes and includes a backtest mode to simulate its performance on historical price action.
Key Features:
1. Trend-Following and Long-Term Valuation:
The indicator is ideal for trend-following strategies, helping traders identify entry and exit points based on the relationship between price and the Kijun-Sen calculated from median price (customizable price source).
With longer-term settings, it can also serve as a valuation tool (in oscillator display mode), assisting in identifying potential overbought or oversold conditions over extended timeframes.
2. Display Modes:
The indicator can be displayed in three main modes, each serving a different purpose:
Overlay Mode : Plots the Median Kijun-Sen directly over the price chart, useful for visualizing trends relative to price action.
Oscillator Mode : Displays the oscillator that compares the current price to the Median Kijun-Sen, providing a clearer signal of trend strength and direction
Backtest Mode : Simulates the performance of the indicator with different settings on historical data, offering traders a way to evaluate its reliability and effectiveness without needing TradingView's built-in strategy tool
3. Backtest Functionality:
The inbuilt backtest mode enables users to evaluate the indicator's performance across historical data by simulating long and short trades. Users can customize the start and end dates for the backtest, as well as specify whether to allow long & short, long only, or short only signals.
This backtest functionality mimics TradingView's strategy feature, allowing users to test the effectiveness of their chosen settings before applying them to live markets.
equity(series int sig, series float r, startDate, string signals, bool endDate_bool) =>
if time >= startDate and endDate_bool
float a = 0
if signals == "Long & Short"
if sig > 0
a := r
else
a := -r
else if signals == "Long Only"
if sig > 0
a := r
else if signals == "Short Only"
if sig < 0
a := -r
else
runtime.error("No Signal Type found")
var float e = na
if na(e )
e := 1
else
e := e * (1 + a)
float r = 0.0
bool endDate_bool = use_endDate ? (time <= endDate ? true : false) : true
float eq = 1.0
if disp_mode == "Backtest Mode"
r := (close - close ) / close
eq := equity(sig, r, startDate, signals, endDate_bool)
4. Hint Table for Pane Suggestions:
An inbuilt hint table guides users on how to best visualize the indicator in different display modes:
For Overlay Mode, it is recommended to use the same pane as the price action.
For Oscillator and Backtest Modes, it is advised to plot them in a separate pane for better clarity.
This table also provides step-by-step instructions on how to move the indicator to a different pane and adjust scaling, making it user-friendly.
Potential Weakness
One of the key drawbacks is the indicator’s tendency to produce false signals during price consolidations, where price action lacks clear direction and may trigger unnecessary trades. This is particularly noticeable in markets with low volatility.
Alerts
The indicator includes alert conditions for when it crosses above or below key levels, enabling traders to receive notifications of LONG or SHORT signals.
Summary
The Median Kijun-Sen is a highly adaptable tool that serves multiple purposes, from trend-following to long-term valuation. With its customizable settings, backtest functionality, and built-in hints, it provides traders with valuable insights into market trends while allowing them to optimize the indicator to their specific strategy.
This versatility, however, comes with the potential weakness of false signals during consolidation phases, so it's most effective in trending markets.
Larry Conners SMTP StrategyThe Spent Market Trading Pattern is a strategy developed by Larry Connors, typically used for short-term mean reversion trading. This strategy takes advantage of the exhaustion in market momentum by entering trades when the market is perceived as "spent" after extended trends or extreme moves, expecting a short-term reversal. Connors uses indicators like RSI (Relative Strength Index) and price action patterns to identify these opportunities.
Key Elements of the Strategy:
Overbought/Oversold Conditions: The strategy looks for extreme overbought or oversold conditions, often indicated by low RSI values (below 30 for oversold and above 70 for overbought).
Mean Reversion: Connors believed that markets, especially in short-term scenarios, tend to revert to the mean after periods of strong momentum. The "spent" market is assumed to have expended its energy, making a reversal likely.
Entry Signals:
In an uptrend, a stock or market index making a significant number of consecutive up days (e.g., 5-7 consecutive days with higher closes) indicates overbought conditions.
In a downtrend, a similar number of consecutive down days indicates oversold conditions.
Reversal Anticipation: Once an extreme in price movement is identified (such as consecutive gains or losses), the strategy places trades anticipating a reversion to the mean, which is usually the 5-day or 10-day moving average.
Exit Points: Trades are exited when prices move back toward their mean or when the extreme conditions dissipate, usually based on RSI or moving average thresholds.
Why the Strategy Works:
Human Psychology: The strategy capitalizes on the fact that markets, in the short term, often behave irrationally due to the emotions of traders—fear and greed lead to overextended moves.
Mean Reversion Tendency: Financial markets often exhibit mean-reverting behavior, where prices temporarily deviate from their historical norms but eventually return. Short-term exhaustion after a strong rally or sell-off offers opportunities for quick profits.
Overextended Moves: Markets that rise or fall too quickly tend to become overextended, as buyers or sellers get exhausted, making reversals more probable. Connors’ approach identifies these moments when the market is "spent" and ripe for a reversal.
Risks of the Spent Market Trading Pattern Strategy:
Trend Continuation: One of the key risks is that the market may not revert as expected and instead continues in the same direction. In trending markets, mean-reversion strategies can suffer because strong trends can last longer than anticipated.
False Signals: The strategy relies heavily on technical indicators like RSI, which can produce false signals in volatile or choppy markets. There can be times when a market appears "spent" but continues in its current direction.
Market Timing: Mean reversion strategies often require precise market timing. If the entry or exit points are mistimed, it can lead to losses, especially in short-term trades where small price movements can significantly impact profitability.
High Transaction Costs: This strategy requires frequent trades, which can lead to higher transaction costs, especially in markets with wide bid-ask spreads or high commissions.
Conclusion:
Larry Connors’ Spent Market Trading Pattern strategy is built on the principle of mean reversion, leveraging the concept that markets tend to revert to a mean after extreme moves. While effective in certain conditions, such as range-bound markets, it carries risks—especially during strong trends—where price momentum may not reverse as quickly as expected.
For a more in-depth explanation, Larry Connors’ books such as "Short-Term Trading Strategies That Work" provide a comprehensive guide to this and other strategies .
Dynamic Volume RSI (DVRSI) [QuantAlgo]Introducing the Dynamic Volume RSI (DVRSI) by QuantAlgo 📈✨
Elevate your trading and investing strategies with the Dynamic Volume RSI (DVRSI) , a powerful tool designed to provide clear insights into market momentum and trend shifts. This indicator is ideal for traders and investors who want to stay ahead of the curve by using volume-responsive calculations and adaptive smoothing techniques to enhance signal clarity and reliability.
🌟 Key Features:
🛠 Customizable RSI Settings: Tailor the indicator to your strategy by adjusting the RSI length and price source. Whether you’re focused on short-term trades or long-term investments, DVRSI adapts to your needs.
🌊 Adaptive Smoothing: Enable adaptive smoothing to filter out market noise and ensure cleaner signals in volatile or choppy market conditions.
🎨 Dynamic Color-Coding: Easily identify bullish and bearish trends with color-coded candles and RSI plots, offering clear visual cues to track market direction.
⚖️ Volume-Responsive Adjustments: The DVRSI reacts to volume changes, giving greater significance to high-volume price moves and improving the accuracy of trend detection.
🔔 Custom Alerts: Stay informed with alerts for key RSI crossovers and trend changes, allowing you to act quickly on emerging opportunities.
📈 How to Use:
✅ Add the Indicator: Set up the DVRSI by adding it to your chart and customizing the RSI length, price source, and smoothing options to fit your specific strategy.
👀 Monitor Visual Cues: Watch for trend shifts through the color-coded plot and candles, signaling changes in momentum as the RSI crosses key levels.
🔔 Set Alerts: Configure alerts for critical RSI crossovers, such as the 50 line, ensuring you stay on top of potential market reversals and opportunities.
🔍 How It Works:
The Dynamic Volume RSI (DVRSI) is a unique indicator designed to provide more accurate and responsive signals by incorporating both price movement and volume sensitivity into the RSI framework. It begins by calculating the traditional RSI values based on a user-defined length and price source, but unlike standard RSI tools, the DVRSI applies volume-weighted adjustments to reflect the strength of market participation.
The indicator dynamically adjusts its sensitivity by factoring in volume to the RSI calculation, which means that price moves backed by higher volumes carry more weight, making the signal more reliable. This method helps identify stronger trends and reduces the risk of false signals in low-volume environments. To further enhance accuracy, the DVRSI offers an adaptive smoothing option that allows users to reduce noise during periods of market volatility. This adaptive smoothing function responds to market conditions, providing a cleaner signal by reducing erratic movements or price spikes that could lead to misleading signals.
Additionally, the DVRSI uses dynamic color-coding to visually represent the strength of bullish or bearish trends. The candles and RSI plots change color based on the RSI values crossing critical thresholds, such as the 50 level, offering an intuitive way to recognize trend shifts. Traders can also configure alerts for specific RSI crossovers (e.g., above 50 or below 40), ensuring that they stay informed of potential trend reversals and significant market shifts in real-time.
The combination of volume sensitivity, adaptive smoothing, and dynamic trend visualization makes the DVRSI a robust and versatile tool for traders and investors looking to fine-tune their market analysis. By incorporating both price and volume data, this indicator delivers more precise signals, helping users make informed decisions with greater confidence.
Disclaimer:
The Dynamic Volume RSI is designed to enhance your market analysis but should not be used as a sole decision-making tool. Always consider multiple factors before making any trading or investment decisions. Past performance is not indicative of future results.
RishiMoney RSIRishiMoney RSI
The "RishiMoney RSI" indicator is designed for traders who want to leverage the power of the Relative Strength Index (RSI) across multiple timeframes.
In addition to regular RSI, this script allows the users to select custom timeframes for two additional RSI calculations, making it easier to identify trends, reversals, and potential entry or exit points.
USAGE
While Returning the same information as a regular RSI the RishiMoney RSI provides two more RSI calculations One for Lagrgest Timeframe and one for middle Timeframe so that the users need not to check for higher timeframes separately Which is very Time consuming. This script solves the problem of time taking process of checking different timeframes RSI calculations.
This script is ideal for traders who want to confirm their analysis across multiple timeframes. By comparing the main RSI with larger and intermediate timeframes, traders can better understand the market's momentum and make more informed decisions.
The RishiMoney RSI crossing above the overbought level can be indicative of a strong uptrend which is highlighted as a green gradient area, while when RishiMoney RSI is crossing under the oversold level can be indicative of a strong downtrend which is highlighted as a red area.
Key Features:
Customizable RSI Period: Set your preferred RSI period for precise calculation and analysis.
Multi-Timeframe RSI:
Largest RSI Timeframe: Choose the largest timeframe for your analysis (Monthly, Weekly, Daily, Hourly, 15 minutes, or 5 minutes).
Middle RSI Timeframe: Select an intermediate timeframe for comparison with the main RSI.
Overbought and Oversold Levels: The indicator includes customizable overbought and oversold levels, which are clearly marked on the chart with dynamic bands.
Alerts: Set up alerts for when the RSI crosses into overbought or oversold territory, so you never miss a potential trading opportunity.
Visual Clarity: The script plots the RSI for your selected timeframes with distinct colors, helping you quickly identify trends across different timeframes.
This script is provided for educational purposes only and should not be considered financial advice. Always conduct your own research and consult with a financial advisor before making any trading decisions.
Ultra Money FlowIntroduction
The Ultra Money Flow script is a technical indicator for analyzing stock trends. It highlights buying and selling power, helping you identify bullish (rising) or bearish (falling) market trends.
Detailed Description
The Ultra Money Flow script calculates and visually displays two main components: Fast and Slow money flow. These components represent short-term and long-term trends, respectively.
Here's how it works:
.........
Inputs
You can adjust the speed of analysis (Fast Length and Slow Length) and the type of smoothing applied (e.g., Simple Moving Average, Exponential Moving Average).
Choose colors for visualizing the trends, with blue for bullish (positive) and orange for bearish (negative) movements.
.....
Money Flow Calculation
The script analyzes price changes (delta) over specified periods.
It separates upward price movements (buying power) from downward ones (selling power).
It then calculates the difference between these powers for both Fast and Slow components.
The types of smoothing methods range from traditional ones like the Simple Moving Average (SMA) to advanced ones like the Double Expotential Moving Average (DEMA) or the Triple Exponential Moving Average (TEMA) or the Recursive Moving Average (RMA) or the Weigthend Moving Average (WMA) or the Volume Weigthend Moving Average (VWMA) or Hull Moving Average (HMA).
Very Special ones are the Triple Weigthend Moving Average (TWMA) wich created RedKTrader .
I created the Multi Weigthend Moving Average (MWMA) wich is a simple signal line to the TWMA.
.....
Divergence
This indicator can show divergence by comparing the direction of price movements with the indicator value.
If the price and the indicator move in opposite directions, you can use these signals to help decide when to buy or sell.
.....
Auto Scaling
The script adjusts its calculations based on the time frame you are viewing, whether it's minutes, hours, or days, ensuring accurate representation across different time scales.
.....
Plotting
The script plots the Fast component as a histogram and the Slow component as a line, using the chosen colors to indicate bullish or bearish trends.
The thickness and transparency of these plots give additional clues about the strength of the trend.
.........
By using this indicator, traders can easily spot shifts in buying and selling power, allowing for better-informed decisions in the market.
Special Thanks
I use the TWMA-Function created from RedKTrader to smooth the values.
Special thanks to him for creating and sharing this function!
RSI Buy/Sell SignalsThis Pine Script is designed to plot Buy and Sell signals based on the Relative Strength Index (RSI) for both 15-minute and hourly timeframes. It calculates the RSI values for the current 15-minute chart and requests the hourly RSI data for comparison. Buy signals are generated when the RSI crosses above 60 in either timeframe, while sell signals occur when the RSI crosses below 40. The script also plots visual markers on the chart, indicating buy signals with green labels below the price bars and sell signals with red labels above the price bars. Additionally, it allows for alert conditions, notifying the user when a buy or sell signal is triggered.
RSI 15/60 and ADX PlotIn this script, the buy and sell criteria are based on the Relative Strength Index (RSI) values calculated for two different timeframes: the 15-minute RSI and the hourly RSI. These timeframes are used together to check signals when certain thresholds are crossed, providing confirmation across both short-term and longer-term momentum.
Buy Criteria:
Condition 1:
Hourly RSI > 60: This means the longer-term momentum shows strength.
15-minute RSI crosses above 60: This shows that the shorter-term momentum is catching up and confirms increasing strength.
Condition 2:
15-minute RSI > 60: This indicates that the short-term trend is already strong.
Hourly RSI crosses above 60: This confirms that the longer-term trend is also gaining strength.
Both conditions aim to capture the moments when the market shows increasing strength across both short and long timeframes, signaling a potential buy opportunity.
Sell Criteria:
Condition 1:
Hourly RSI < 40: This indicates that the longer-term trend is weakening.
15-minute RSI crosses below 40: The short-term momentum is also turning down, confirming the weakening trend.
Condition 2:
15-minute RSI < 40: The short-term trend is already weak.
Hourly RSI crosses below 40: The longer-term trend is now confirming the weakness, indicating a potential sell.
These conditions work to identify when the market is showing weakness in both short-term and long-term timeframes, signaling a potential sell opportunity.
ADX Confirmation :
The Average Directional Index (ADX) is a key tool for measuring the strength of a trend. It can be used alongside the RSI to confirm whether a buy or sell signal is occurring in a strong trend or during market consolidation. Here's how ADX can be integrated:
ADX > 25: This indicates a strong trend. Using this threshold, you can confirm buy or sell signals when there is a strong upward or downward movement in the market.
Buy Example: If a buy signal (RSI > 60) is triggered and the ADX is above 25, this confirms that the market is in a strong uptrend, making the buy signal more reliable.
Sell Example: If a sell signal (RSI < 40) is triggered and the ADX is above 25, it confirms a strong downtrend, validating the sell signal.
ADX < 25: This suggests a weak or non-existent trend. In this case, RSI signals might be less reliable since the market could be moving sideways.
Final Approach:
The RSI criteria help identify potential overbought and oversold conditions in both short and long timeframes.
The ADX confirmation ensures that the signals generated are happening during strong trends, increasing the likelihood of successful trades by filtering out weak or choppy market conditions.
This combination of RSI and ADX can help traders make more informed decisions by ensuring both momentum and trend strength align before entering or exiting trades.
Bull Bear Power With EMA FilterDescription of Indicator:
This Pine Script indicator colors price bars based on the open price in relation to custom moving averages (EMA/SMA), Bull/Bear Power (BBPower), and an optional VWAP filter. The bar colors help identify bullish and bearish conditions with added visual cues for price positioning relative to VWAP.
Key Features:
Customizable Moving Averages (EMA/SMA):
The user can select between EMA or SMA for both short-term and long-term moving averages.
Default moving averages are set to 5 (short-term) and 9 (long-term) but can be adjusted by the user.
Bullish Condition (Blue or Purple Bars):
A bar is colored blue if the following conditions are met:
The open price is above both the short-term and long-term moving averages.
The short-term moving average (MA 1) is above the long-term moving average (MA 2).
BBPower (open price minus the 13-period EMA) is positive, indicating bullish strength.
If the VWAP filter is enabled and the price opens below VWAP, the bullish bars will turn purple.
Bearish Condition (Yellow or Orange Bars):
A bar is colored yellow if the following conditions are met:
The open price is below both the short-term and long-term moving averages.
The short-term moving average (MA 1) is below the long-term moving average (MA 2).
BBPower is negative or zero, indicating bearish market conditions.
If the VWAP filter is enabled and the price opens above VWAP, the bearish bars will turn orange.
VWAP Filter (Optional):
An optional filter allows the user to add VWAP (Volume-Weighted Average Price) to the bar coloring logic.
When the VWAP filter is enabled, it provides additional information about price positioning relative to VWAP, turning bullish bars purple and bearish bars orange depending on whether the price opens above or below VWAP.
Usage:
Bullish Trend: Look for blue or purple bars to identify potential bullish momentum.
Bearish Trend: Look for yellow or orange bars to spot bearish conditions in the market.
The indicator allows users to customize the length and type of moving averages (EMA or SMA), as well as decide whether to apply the VWAP filter.
This indicator provides traders with clear visual signals to quickly assess the strength of bullish or bearish conditions based on the price's position relative to custom moving averages, BBPower, and VWAP, helping with trend identification and potential trade setups.
RCYC Bullish Bearish Indicator
Summary: The RCYC Bullish Bearish Indicator is a custom trading tool designed to help traders identify potential bullish and bearish conditions in the market using a combination of KDJ and RSI indicators. This indicator uses color-coded candles to visually represent bullish and bearish signals, making it easy to identify trend changes on the chart. The script is particularly useful for traders who prefer visual signals and want to incorporate both trend momentum (KDJ) and relative strength (RSI) in their analysis.
Description:
The RCYC Bullish Bearish Indicator is a unique mashup of the KDJ and RSI indicators, optimized to provide a clear visual representation of market conditions through color-coded candles. This indicator not only identifies the potential trend shifts but also provides alerts for significant crossover points, enhancing a trader's ability to make informed decisions.
How It Works:
KDJ Calculation:
The KDJ is a variation of the Stochastic Oscillator that includes the %J line, which can go beyond the typical 0-100 range of %K and %D.
The KDJ component of this indicator calculates the highest high and lowest low over a specified period (KDJ Length), using these values to derive the %K line.
The %D line is a smoothed version of %K, and the %J line is derived from %K and %D using the formula: J = 3 * %K - 2 * %D.
This indicator focuses on the behavior of the %J line in relation to a mid-point level (50), identifying crossovers and crossunders that signal potential shifts in market sentiment.
RSI Calculation:
The Relative Strength Index (RSI) is a momentum oscillator that measures the speed and change of price movements. It is widely used to identify overbought or oversold conditions.
In this indicator, RSI values are adjusted and plotted to align visually with the KDJ values, providing a complementary momentum analysis.
Crossover Logic and Candle Coloring:
The indicator tracks two main events:
CrossOver50: When the %J line crosses above the 50 level, indicating potential bullish momentum.
CrossUnder50: When the %J line crosses below the 50 level, indicating potential bearish momentum.
Depending on the crossover events, the script changes the color of the candles on the chart:
Red candles on the initial crossover above 50, followed by dark blue candles to maintain bullish sentiment.
Yellow candles on the initial crossover below 50, followed by light blue candles to maintain bearish sentiment.
Alerts:
The indicator includes alert conditions for both bullish and bearish signals:
Red Candle Alert: Notifies the trader when the %J line crosses above 50.
Yellow Candle Alert: Notifies the trader when the %J line crosses below 50.
These alerts allow traders to react promptly to key market signals without continuously monitoring the chart.
Usage and Benefits:
This indicator is designed for traders looking to combine momentum and trend analysis into a single visual tool. It is particularly useful for those trading in trending markets or looking for entry/exit signals based on momentum shifts.
The color-coded candles provide an intuitive way to assess market conditions at a glance, reducing the complexity associated with analyzing multiple indicators separately.
By integrating both KDJ and RSI, the RCYC Bullish Bearish Indicator offers a balanced approach to trend detection and momentum confirmation, making it versatile for various trading styles, including scalping, swing trading, and position trading.
Originality and Usefulness:
While the indicator builds upon the familiar concepts of KDJ and RSI, it uniquely merges them into a cohesive visual tool with distinct crossover-based alerts and candle coloring.
This approach makes the indicator original, as it simplifies the interpretation of complex signals into straightforward visual cues, enhancing the decision-making process for traders who prefer chart-based analysis.
Color Coded RSI [Phantom]Color Coded RSI
The Color Coded RSI enhances the standard RSI (Relative Strength Index) by applying dynamic color coding to the price bars, making it easier to visualize RSI levels directly on the chart.
Key Feature:
RSI-Based Color Coding: Price bars change color based on RSI values. High RSI values (above 70) show warm colors (red/orange), signaling potential overbought conditions, while low RSI values (below 30) display cool colors (blue), indicating possible oversold levels.
How to Trade with Color Coded RSI:
Overbought (Red/Orange Bars):
When the bars turn red or orange (RSI above 70), the market might be overbought. This could be a signal to sell or exit long positions, expecting a pullback.
Oversold (Blue Bars):
Blue bars (RSI below 30) suggest the market is oversold. Look for buying opportunities or consider exiting short positions, anticipating a rebound.
Neutral (Gray/Green Bars):
Gray or green bars (RSI near 50) indicate neutral conditions. You may want to wait for a clearer trend before taking action.
RSI is best used with other indicators to provide confirmations.
Stochastic RSI Average Overlay Stochastic Average Overlay is an advanced technical indicator designed to enhance your trading strategy by combining the power of stochastic averages with multiple smoothing techniques. This overlay indicator provides a comprehensive view of market momentum and potential reversal points, integrating features for both trend analysis and signal generation.
Key Features:
Stochastic Average:
Customizable Length: Adjust the length parameter to define the period over which the stochastic average is calculated. This flexibility allows you to tailor the indicator to different market conditions and trading styles.
Pre-Smoothing and Post-Smoothing: The indicator offers pre-smoothing and post-smoothing options to reduce noise and enhance signal clarity. Choose from various smoothing methods, including Simple Moving Average (SMA), Triangular Moving Average (TMA), and Least Squares Moving Average (LSMA).
Normalized Average Calculation:
Normalized Values: The stochastic average is calculated using normalized values to provide a clear view of market extremes. This approach helps in identifying overbought and oversold conditions more effectively.
Trend Detection:
Dynamic Coloring: The indicator uses color-coded plots to indicate bullish or bearish trends. The plot color changes dynamically based on whether the stochastic average is rising (bullish) or falling (bearish).
Upper and Lower Bounds: Includes horizontal lines at the upper (95) and lower (5) bounds to visually represent extreme levels and potential reversal zones.
Signal Generation:
Overbought/Oversold Conditions: Circles are plotted above or below the bars to highlight overbought (crossunder 95) and oversold (crossover 5) conditions.
Buy/Sell Labels: Buy and sell signals are plotted directly on the price chart. A "BUY" label appears below the bar when the stochastic average crosses above the lower bound, and a "SELL" label appears above the bar when it crosses below the upper bound.
Overlay Functionality:
Price Chart Integration: As an overlay indicator, it is plotted on the price chart, allowing you to analyze market conditions in conjunction with price movements.
Usage Tips:
Combine with Other Indicators: Use the Multi-Length Stochastic Average in conjunction with other technical indicators to confirm signals and enhance decision-making.
Adjust Parameters: Tailor the length and smoothing options to fit your trading style and market conditions.
Monitor Signal Strength: Pay attention to the strength of buy and sell signals in conjunction with the trend direction indicated by the color of the plot.
The Stochastic Average Overlay provides traders with a powerful tool to analyze market momentum, identify potential reversal points, and make informed trading decisions based on comprehensive technical analysis.
Disclaimer:
This indicator is designed for informational purposes only and should not be construed as financial advice. Always perform your own research and consider your individual financial situation before making trading decisions.
Tian Di Grid Merge Version 6.0
Strategy Introduction:
1. We know that the exchange can only set a maximum of 100 grids. However, our grid strategy can set a maximum of 350 grids.
2. We have added the modes of proportional and differential warehousing.
3. It should be noted that we have not set any filtering conditions, which means that when the price falls below the grid, we will execute a buy action at the closing price, and when the price falls above the grid, we will execute a sell action;
4. We suggest limiting the trading time cycle to 5 meters, as sometimes errors may appear on TV due to the dense grid or the inability to draw so many grids;
5. Please ensure that the minimum spacing between each grid is not less than 0.1%, as this is extremely difficult to profit from, and on the other hand, it may not function due to excessively dense spacing;
6. The maximum number of grids is 350, and the minimum number is currently 3;
matters needing attention:
Don't choose to go long or short together, and don't choose to go even short or short;
Closing position setting: It is recommended to select it to avoid order accumulation;
Unable to trade: If unable to trade normally, switch to a 1m cycle;
Number of cells: Calculate it yourself, 350 is just the maximum number of cells that can be adjusted;
Grid spacing: minimum 0.1%, below which no profit can be made;
Position value: default is 100u, which is the amount already leveraged;
Multiple investment: The order amount for each order is the same, and there is no need for multiple investment;
Open both long and short positions: You can open multiple positions for one account and open one position for one account. Do not open both long and short positions for the same target at the same time
Advanced Stochastic ForLoopAdvanced Stochastic ForLoop
OVERVIEW
Advanced Stochastic ForLoop is an improved version of Stochastic it is designed to calculate an array of values 1 or -1 depending if soruce for calculations is above or below basis.
It takes avereage of values over a range of lengths, providing trend signals smothed based on various moving averages in order to get rid of noise.
It offers flexibility with different signal modes and visual customizations.
TYPE OF SIGNALS
-FAST (MA > MA or MA > 0.99)
-SLOW (MA > 0)
-THRESHOLD CROSSING (set by user treshold for both directions)
-FAST THRESHOLD (when theres an change in signal by set margin e.g 0.4 -> 0.2 means bearsih when FT is set to 0.1, when MA is > 0.99 it will signal bullish, when MA < -0.99 it will signal bearish)
Generaly Lime color of line indicates Bullish, Fuchsia indicates Bearish.
This colors are not set in stone so you can change them in settings.
Alerts included when line color is:
-Bullish Trend, line color is lime
-Bearish Trend, line color is fuchsia
Credit
Idea for this script was from one of indicators created by www.tradingview.com
Warning
This indicator can be really noisy depending on the settings, signal mode so it should be used preferably as a part of an strategy not as a stand alone indicator
Remember the lower the timeframe you use the more noise there is.
No single indicator should be used alone when making investment decisions.
Bollinger Bands with RSI Buy/Sell Signals (15 min) Bollinger Bands with RSI Buy/Sell Signals (15 Min)
Description:
The Bollinger Bands with RSI Buy/Sell Signals (15 Min) indicator is designed to help traders identify potential reversal points in the market using two popular technical indicators: Bollinger Bands and the Relative Strength Index (RSI).
How It Works:
Bollinger Bands:
Bollinger Bands consist of an upper band, lower band, and a middle line (Simple Moving Average). These bands adapt to market volatility, expanding during high volatility and contracting during low volatility.
This indicator monitors the 15-minute Bollinger Bands. If the price moves completely outside the bands, it signals that the market is potentially overextended.
Relative Strength Index (RSI):
RSI is a momentum indicator that measures the strength of price movements. RSI readings above 70 indicate an overbought condition, while readings below 30 suggest an oversold condition.
This indicator uses the RSI on the 15-minute time frame to further confirm overbought and oversold conditions.
Buy/Sell Signal Generation:
Buy Signal:
A buy signal is triggered when the market price crosses above the lower Bollinger Band on the 15-minute time frame, indicating that the market may be oversold.
Additionally, the RSI must be below 30, confirming an oversold condition.
A "Buy" label appears below the price when this condition is met.
Sell Signal:
A sell signal is triggered when the market price crosses below the upper Bollinger Band on the 15-minute time frame, indicating that the market may be overbought.
The RSI must be above 70, confirming an overbought condition.
A "Sell" label appears above the price when this condition is met.
Dynamic Jurik RSX w/ Fisher Transform█ Introduction
The Dynamic Jurik RSX with Fisher Transform is a powerful and adaptive momentum indicator designed for traders who seek a non-laggy view of price movements. This script is based on the classic Jurik RSX (Relative Strength Index). It also includes features such as the dynamic overbought and oversold limits, the Inverse Fisher Transform, trend display, slope calculations, and the ability to color extremes for better clarity.
█ Key Features:
• RSX: The Relative Strength Index (RSX) in this script is based on Jurik’s RSX, which is smoother than the traditional RSI and aims to reduce noise and lag. This script calculates the RSX using an exponential smoothing technique and adaptive adjustments.
• Inverse Fisher Transform: This script can optionally apply the Inverse Fisher Transform to the RSX, which helps to normalize the RSX values, compressing them between -1 and 1. The inverse transformation makes it easier to spot extreme values (overbought and oversold conditions) by enhancing the visual clarity of those extremes. It also smooths the curve over a user-defined period in hopes of providing a more consistent signal.
• Dynamic Limits: The dynamic overbought and oversold limits are calculated based on the RSX's recent high and low values. The limits adjust dynamically depending on market conditions, making them more relevant to current price action.
• Slope Display: The slope of the RSX is calculated as the rate of change between the current and previous RSX value. The slope is displayed as dots when the slope exceeds the threshold designated by the user, providing visual cues for momentum shifts.
• Trend Coloring: Optionally, the user can also enable a trend-based display. It is simply based on current value of RSX versus the previous one. If RSX is rising then the trend is bullish, if not, then the trend is bearish.
• Coloring Extremes: Users can configure the RSX to color the chart when prices enter extreme conditions, such as overbought or oversold zones, providing visual cues for market reversals.
█ Attached Chart Notes:
• Top Panel: Enabled dynamic limits, Trend display, standard Jurik RSX with 20 lookback period, and Slope display.
• Middle Panel: Enabled dynamic limits, Extremes display, and standard Jurik RSX with 20 lookback period.
• Bottom Panel: Enabled dynamic limits, Trend display, Inverse Fisher Transform with 14 lookback period and 9 smoothing period. and Slope display.
█ Credits:
Special thanks to Everget for providing the original script. The script was also slightly modified based on updates from outside sources.
█ Disclaimer:
This script is for educational purposes only and should not be considered financial advice. Always conduct your own research and consult a professional before making any trading decisions.
Adaptive RSI-Stoch with Butterworth Filter [UAlgo]The Adaptive RSI-Stoch with Butterworth Filter is a technical indicator designed to combine the strengths of the Relative Strength Index (RSI), Stochastic Oscillator, and a Butterworth Filter to provide a smooth and adaptive momentum-based trading signal. This custom-built indicator leverages the RSI to measure market momentum, applies Stochastic calculations for overbought/oversold conditions, and incorporates a Butterworth Filter to reduce noise and smooth out price movements for enhanced signal reliability.
By utilizing these combined methods, this indicator aims to help traders identify potential market reversal points, momentum shifts, and overbought/oversold conditions with greater precision, while minimizing false signals in volatile markets.
🔶 Key Features
Adaptive RSI and Stochastic Oscillator: Calculates RSI using a configurable period and applies a dual-smoothing mechanism with Stochastic Oscillator values (K and D lines).
Helps in identifying momentum strength and potential trend reversals.
Butterworth Filter: An advanced signal processing filter that reduces noise and smooths out the indicator values for better trend identification.
The filter can be enabled or disabled based on user preferences.
Customizable Parameters: Flexibility to adjust the length of RSI, the smoothing factors for Stochastic (K and D values), and the Butterworth Filter period.
🔶 Interpreting the Indicator
RSI & Stochastic Calculations:
The RSI is calculated based on the closing price over the user-defined period, and further smoothed to generate Stochastic Oscillator values.
The K and D values of the Stochastic Oscillator provide insights into short-term overbought or oversold conditions.
Butterworth Filter Application:
What is Butterworth Filter and How It Works?
The Butterworth Filter is a type of signal processing filter that is designed to have a maximally flat frequency response in the passband, meaning it doesn’t distort the frequency components of the signal within the desired range. It is widely used in digital signal processing and technical analysis to smooth noisy data while preserving the important trends in the underlying data. In this indicator, the Butterworth Filter is applied to the trigger value, making the resulting signal smoother and more stable by filtering out short-term fluctuations or noise in price data.
Key Concepts Behind the Butterworth Filter:
Filter Design: The Butterworth filter works by calculating weighted averages of current and past inputs (price or indicator values) and outputs to produce a smooth output. It is characterized by the absence of ripple in the passband and a smooth roll-off after the cutoff frequency.
Cutoff Frequency: The period specified in the indicator acts as a control for the cutoff frequency. A higher period means the filter will remove more high-frequency noise and retain longer-term trends, while a lower period means it will respond more to short-term fluctuations in the data.
Smoothing Process: In this script, the Butterworth Filter is calculated recursively using the following formula,
butterworth_filter(series float input, int period) =>
float wc = math.tan(math.pi / period)
float k1 = 1.414 * wc
float k2 = wc * wc
float a0 = k2 / (1 + k1 + k2)
float a1 = 2 * a0
float a2 = a0
float b1 = 2 * (k2 - 1) / (1 + k1 + k2)
float b2 = (1 - k1 + k2) / (1 + k1 + k2)
wc: This is the angular frequency, derived from the period input.
k1 and k2: These are intermediate coefficients used in the filter calculation.
a0, a1, a2: These are the feedforward coefficients, which determine how much of the current and past input values will contribute to the filtered output.
b1, b2: These are feedback coefficients, which determine how much of the past output values will contribute to the current output, effectively allowing the filter to "remember" past behavior and smooth the signal.
Recursive Calculation: The filter operates by taking into account not only the current input value but also the previous two input values and the previous two output values. This recursive nature helps it smooth the signal by blending the recent past data with the current data.
float filtered_value = a0 * input + a1 * prev_input1 + a2 * prev_input2
filtered_value -= b1 * prev_output1 + b2 * prev_output2
input: The current input value, which could be the trigger value in this case.
prev_input1, prev_input2: The previous two input values.
prev_output1, prev_output2: The previous two output values.
This means the current filtered value is determined by the combination of:
A weighted sum of the current input and the last two inputs.
A correction based on the last two output values to ensure smoothness and remove noise.
In conclusion when filter is enabled, the Butterworth Filter smooths the RSI and Stochastic values to reduce market noise and highlight significant momentum shifts.
The filtered trigger value (post-Butterworth) provides a cleaner representation of the market's momentum.
Cross Signals for Trade Entries:
Buy Signal: A bullish crossover of the K value above the D value, particularly when the values are below 40 and when the Stochastic trigger is below 1 and the filtered trigger is below 35.
Sell Signal: A bearish crossunder of the K value below the D value, particularly when the values are above 60 and when the Stochastic trigger is above 99 and the filtered trigger is above 90.
These signals are plotted visually on the chart for easy identification of potential trading opportunities.
Overbought and Oversold Zones:
The indicator highlights the overbought zone when the filtered trigger surpasses a specific threshold (typically above 100) and the oversold zone when it drops below 0.
The color-coded fill areas between the Stochastic and trigger lines help visualize when the market may be overbought (likely a reversal down) or oversold (potential reversal up).
🔶 Disclaimer
Use with Caution: This indicator is provided for educational and informational purposes only and should not be considered as financial advice. Users should exercise caution and perform their own analysis before making trading decisions based on the indicator's signals.
Not Financial Advice: The information provided by this indicator does not constitute financial advice, and the creator (UAlgo) shall not be held responsible for any trading losses incurred as a result of using this indicator.
Backtesting Recommended: Traders are encouraged to backtest the indicator thoroughly on historical data before using it in live trading to assess its performance and suitability for their trading strategies.
Risk Management: Trading involves inherent risks, and users should implement proper risk management strategies, including but not limited to stop-loss orders and position sizing, to mitigate potential losses.
No Guarantees: The accuracy and reliability of the indicator's signals cannot be guaranteed, as they are based on historical price data and past performance may not be indicative of future results.
Dema EFI Volume | viResearchDema EFI Volume | viResearch
Conceptual Foundation and Innovation
The "Dema EFI Volume" indicator from viResearch integrates the Double Exponential Moving Average (DEMA) with the Elder Force Index (EFI), providing a dynamic approach to analyzing both price trends and volume strength. The DEMA is applied to smooth out price fluctuations while minimizing lag, which enhances the ability to detect trend direction. The EFI, developed by Dr. Alexander Elder, measures the power behind price movements by incorporating both price change and volume. This indicator, when combined with DEMA smoothing, gives traders a more accurate understanding of whether the current price movements are supported by significant volume, helping them make more informed trading decisions. The combination of DEMA and EFI allows traders to track trend strength while assessing the market’s volume dynamics, offering a more reliable method for identifying potential trend continuations or reversals.
Technical Composition and Calculation
The "Dema EFI Volume" script consists of two key components: the Double Exponential Moving Average (DEMA) and the Elder Force Index (EFI). The DEMA is applied to the selected source price over a user-defined length, providing a smoothed representation of price movements while reducing the noise that can occur with traditional moving averages. The EFI is calculated by multiplying the change in the DEMA by the volume over a user-defined period, which indicates whether the price movement is being driven by strong or weak volume. The script monitors the EFI values and volume data to generate trend signals. If the EFI is positive and volume increases, this indicates bullish pressure, while a negative EFI with decreasing volume suggests bearish conditions. The combination of these signals helps traders determine whether a price move is backed by sufficient volume, making it easier to identify trend continuations or potential reversals.
Features and User Inputs
The "Dema EFI Volume" script offers several customizable inputs, allowing traders to adapt the indicator to their specific strategies. The DEMA Length controls the smoothing applied to the price data, while the EFI Length defines the period over which the force index is calculated. Additionally, traders can set alert conditions for when a bullish or bearish EFI signal occurs, enabling them to react quickly to changing market conditions.
Practical Applications
The "Dema EFI Volume" indicator is designed for traders who want to combine price trend analysis with volume dynamics in a single tool. This makes it particularly effective for identifying trend continuations, as rising volume alongside a positive EFI suggests that the market move is supported by strong momentum. Conversely, decreasing volume and a negative EFI may indicate a weakening trend, giving traders early warning of potential reversals. The combination of DEMA and EFI also makes this indicator valuable for detecting trend strength by measuring whether price movements are backed by strong volume, confirming trend reversals by comparing price changes with volume activity, and improving trade entries and exits by analyzing both price and volume for more robust signals.
Advantages and Strategic Value
The "Dema EFI Volume" script offers significant advantages by combining the DEMA’s smoothing power with the EFI’s volume analysis. This integration allows traders to filter out noise in price data while ensuring that trend signals are backed by meaningful volume. The result is a more reliable tool for trend-following and reversal detection, making it easier for traders to stay aligned with strong market moves while avoiding false signals caused by low-volume fluctuations. The dual focus on price and volume makes the "Dema EFI Volume" an ideal tool for traders who value a comprehensive approach to market analysis.
Alerts and Visual Cues
The script includes alert conditions that notify traders when a significant EFI signal occurs. The "EFI Volume Long" alert is triggered when the EFI is positive and volume increases, indicating a potential upward trend. The "EFI Volume Short" alert signals a possible downward trend when the EFI turns negative and volume decreases. Visual cues, such as the color and direction of the plotted EFI line, help traders quickly identify trend shifts and make timely decisions.
Summary and Usage Tips
The "Dema EFI Volume | viResearch" indicator provides traders with a powerful tool for analyzing both price trends and volume strength. By incorporating this script into your trading strategy, you can improve your ability to detect trend continuations and reversals, making more informed decisions based on a combination of price movement and volume dynamics. Whether you are focused on identifying trend strength or looking for early reversal signals, the "Dema EFI Volume" offers a reliable and customizable solution for traders of all levels.
Note: Backtests are based on past results and are not indicative of future performance.
RSI TreeRSI Tree is a simple way to compare the strength of several different instruments against each other.
The default is to compare MSFT, NVDA, TSLA, GOOG, META, AMZN, AAPL and NASDAQ. You could do the same for currency pairs and any other instruments available in Trading View. However, it makes the most sense to compare seven instruments to an eighth underlying instrument. As you can see in the default values, we included the NASDAQ as the eighth instrument since the other seven are part of the NASDAQ composite index. If you were to trade major currency pairs, then your eighth instrument would most likely be the U.S. Dollar (DXY).
The chart setup is important as well. You need to split your chart horizontally into 4 plots. Each plot would be at a different timing interval. The example shows 4 hr, 1 hr, 15 min and 5 min (left to right) charts. Now not only can we compare the instruments against each other, but we can do it across time to get an idea of the motion of each instrument.
Note, the instrument used on the chart is somewhat important. If the chart is set to a currency pair, but you have the RSI Tree setup for equities (as in the default) then you will get some odd behavior due to the times when these are open. Equities are 0930 to 1600 EST, whereas something like a currency would be open 24 hours a day.
Layout for default settings: www.tradingview.com
Bugs?
Kindly report any issues and I'll try to fix them promptly.
Thank you!
DCA, Support and Resistance with RSI and Trend FilterThis script is based on
script from Kieranj with added pyramiding and DCA
The buy condition (buyCondition) is triggered when the RSI crosses above the oversold threshold (ta.crossover(rsi, oversoldThreshold)), the trend filter confirms an uptrend (isUptrend is true), and the close price is greater than or equal to the support level (close >= supportLevel).
The partial sell condition (sellCondition) is triggered when the RSI crosses below the overbought threshold (ta.crossunder(rsi, overboughtThreshold)) and profit goal is reached, the trend filter confirms a downtrend (isUptrend is false), and the close price is less than or equal to the resistance level (close <= resistanceLevel).
Full sell will be triggered if trend is broken and profit goal is reached
With this implementation, the signals will only be generated in the direction of the trend on the 4-hour timeframe. The trend is considered up when the 50-period SMA is below the 200-period SMA (ta.sma(trendFilterSource, 50) < ta.sma(trendFilterSource, 200)).
Pyramiding should be activated, values like 100, so every DCA step should be around 1%
i have best results on 5 min charts
Bitcoin Thermocap [InvestorUnknown]The Bitcoin Thermocap indicator is designed to analyze Bitcoin's market data using a variant of the "Thermocap Multiple" concept from BitBo. This indicator offers several modes for interpreting Bitcoin's historical block and price data, aiding investors and analysts in understanding long-term market dynamics and generating potential investing signals.
Key Features:
1. Thermocap Calculation
The core of the indicator is based on the Thermocap Multiple, which evaluates Bitcoin's value relative to its cumulative historical blocks mined.
Thermocap Formula:
Source: Bitbo
btc_price = request.security("INDEX:BTCUSD", "1D", close)
BTC_BLOCKSMINED = request.security("BTC_BLOCKSMINED", "D", close)
// Variable to store the cumulative historical blocks
var float historical_blocks = na
// Initialize historical blocks on the first bar
if (na(historical_blocks))
historical_blocks := 0.0
// Update the cumulative blocks for each day
historical_blocks += BTC_BLOCKSMINED * btc_price
// Calculate the Thermocap
float thermocap = ((btc_price / historical_blocks) * 1000000) // the multiplication is just for better visualization
2. Multiple Display Modes:
The indicator can display data in four different modes, offering flexibility in interpretation:
RAW: Displays the raw Thermocap value.
LOG: Applies the logarithm of the Thermocap to visualize long-term trends more effectively, especially for large-value fluctuations.
MA Oscillator: Shows the ratio between the Thermocap and its moving average (MA). Users can choose between Simple Moving Average (SMA) or Exponential Moving Average (EMA) for smoothing.
Normalized MA Oscillator: Provides a normalized version of the MA Oscillator using a dynamic min-max rescaling technique.
3. Normalization and Rescaling
The indicator normalizes the Thermocap Oscillator values between user-defined limits, allowing for easier interpretation. The normalization process decays over time, with values shrinking towards zero, providing more relevance to recent data.
Negative values can be allowed or restricted based on user preferences.
f_rescale(float value, float min, float max, float limit, bool negatives) =>
((limit * (negatives ? 2 : 1)) * (value - min) / (max - min)) - (negatives ? limit : 0)
f_max_min_normalized_oscillator(float x) =>
float oscillator = x
var float min = na
var float max = na
if (oscillator > max or na(max)) and time >= normalization_start_date
max := oscillator
if (min > oscillator or na(min)) and time >= normalization_start_date
min := oscillator
if time >= normalization_start_date
max := max * decay
min := min * decay
normalized_oscillator = f_rescale(x, min, max, lim, neg)
Usage
The Bitcoin Thermocap indicator is ideal for long-term market analysis, particularly for investors seeking to assess Bitcoin's relative value based on mining activity and price dynamics. The different display modes and customization options make it versatile for a variety of market conditions, helping users to:
Identify periods of overvaluation or undervaluation.
Generate potential buy/sell signals based on the MA Oscillator and its normalized version.
By leveraging this Thermocap-based analysis, users can gain a deeper understanding of Bitcoin's historical and current market position, helping to inform investment strategies.
RSItrendsThis is to my friends and to my sons to use.
What Is the Relative Strength Index (RSI)?
The relative strength index (RSI) is a momentum indicator used in technical analysis. RSI measures the speed and magnitude of a security's recent price changes to evaluate overvalued or undervalued conditions in the price of that security.
The RSI is displayed as an oscillator (a line graph) on a scale of zero to 100. The indicator was developed by J. Welles Wilder Jr. and introduced in his seminal 1978 book, New Concepts in Technical Trading Systems.
1
The RSI can do more than point to overbought and oversold securities. It can also indicate securities that may be primed for a trend reversal or corrective pullback in price. It can signal when to buy and sell. Traditionally, an RSI reading of 70 or above indicates an overbought situation. A reading of 30 or below indicates an oversold condition.
Adaptive LSMA Regression OscillatorOverview:
The Adaptive LSMA Regression Oscillator is an open-source technical analysis tool designed to reflect market price deviations from an adaptive least squares moving average (LSMA). The adaptive length of the LSMA changes dynamically based on the volatility of the market, making the indicator responsive to different market conditions.
Key Features:
Adaptive Length Adjustment : The base length of the LSMA is adjusted based on market volatility, measured by the Average True Range (ATR). The more volatile the market, the longer the adaptive length, and vice versa.
Oscillator : The indicator calculates the difference between the closing price and the adaptive LSMA. This difference is plotted as a histogram, showing whether prices are above or below the LSMA.
Color-Coded Histogram:
Positive values (where price is above the LSMA) are colored green.
Negative values (where price is below the LSMA) are colored red.
Debugging Information: The adaptive length is plotted for transparency, allowing users to see how the length changes based on the multiplier and ATR.
How It Works:
Inputs:
Base Length : This defines the starting length of the LSMA. It is adjusted based on market conditions.
Multiplier : A customizable multiplier is used to control how much the adaptive length responds to changes in volatility.
ATR Period : This determines the lookback period for the Average True Range calculation, a measure of market volatility.
Dynamic Adjustment:
The length of the LSMA is dynamically adjusted by multiplying the base length by a factor derived from ATR and the average close price.
This helps the indicator adapt to different market conditions, staying shorter during low volatility and longer during high volatility.
Example Use Cases:
Trend Analysis: By observing the oscillator, traders can see when prices deviate from a dynamically adjusted LSMA. This can be used to evaluate potential trend direction or changes in market behavior.
Volatility-Responsive Indicator: The adaptive length ensures that the indicator responds appropriately in both high and low volatility environments.
