Equity Curve Trading with EMAWhat Is Equity Curve Trading?
In equity curve trading, traders apply a moving average to the curve. The idea is when the equity curve drops below the moving average, the strategy is put on hold. This is done to stop losses when either the hopes of the plan working start dimming or when the trader knows he cannot afford more losses on a strategy. The trader can resume trading this particular strategy when the equity curve is above the moving average.
Equity Curve Trading puts an investor at the ease of knowing that his investment is covered even when he is not actively tracking his strategy. When the equity curve dips below a level investor is comfortable with, it can be paused until such time that the equity curve is back above the determined moving average.
Example:
Equity Curve Trading Example
Trading Strategy
I choosed the SuperTrend strategy for BTCUSDT on 4 hour time frame. That shows nice equity curve with default settings. Let's find out and check can we improve the equity curve with this modern money management trade method?
Some shift is exist in original equity curve relatively to filtered equity curve, because of array usage, but it is not affected on calculations.
Conclusion
I tested a different time frames, settings and equity curves shapes, but it not gives advantages in equity curve. You can look at the table on the top right corner of the strategy with equity curve and you will see some statistic information for the original strategy and for the modified equity curve trade strategy. In most cases we have lower Win Rate and lower Net Profit after turning on Equity curve trading method. In some cases this can be help if you have the equity curve looks like at the picture above, but this equity curve is really bad for choosing this strategy to trade. I found that EMA works better than SMA, and RMA works better then EMA applied to Equity Curve. You can test your strategy with this trade method if you want, I make the source code opened for it. Please share your results, I hope it will helps.
Conclusion 2
Equity Curve Trading definitely has its proponents in the industry, some of them quite vocal. But, the overall efficacy of the approach is certainly not crystal clear. In fact, what is clear is that it is relatively easy to take a good strategy, and significantly degrade its performance by employing equity curve trading. While the overall objective of equity curve trading is unquestionable – cease trading poor performing strategies - it is probable that there are better ways of accomplishing that goal. From this study, the conclusion is equity curve trading with simple indicators has more downside than upside.
Rata-Rata Pergerakan / Moving Averages
SA 2.0The 100/200 EMA crossover strategy is a popular trend-following strategy used in technical analysis. It aims to identify potential buy and sell signals based on the crossover of two exponential moving averages (EMAs), specifically the 100-period EMA and the 200-period EMA. This strategy is designed to capture the momentum of the market and take advantage of sustained trends in the price of US30. This strategy can also work on other instruments, just backtest the winrate.
How it Works:
Timeframe Selection: The strategy is optimized for the US30 index and is implemented on both the 5-minute and 3-minute charts. These shorter timeframes provide more frequent trading opportunities and allow for quicker decision-making.
EMA Crossover: The strategy focuses on the crossover of the 100-period EMA and the 200-period EMA. When the 100 EMA crosses above the 200 EMA, it generates a bullish signal, indicating a potential upward trend. Conversely, when the 100 EMA crosses below the 200 EMA, it generates a bearish signal, suggesting a potential downward trend.
Rejection Confirmation: To filter out false signals and increase the reliability of the strategy, it incorporates a rejection confirmation. After the initial crossover, the strategy looks for price rejections near the 100 EMA. A rejection occurs when the price briefly moves below the 100 EMA and then quickly bounces back above it, indicating potential support and a possible continuation of the trend. It is during this rejection that the strategy generates the buy or sell signal.
Buy and Sell Signals: When a rejection occurs after the crossover, the strategy generates a buy signal if the rejection is above the 100 EMA. This suggests that the price is likely to continue its upward momentum. On the other hand, a sell signal is generated if the rejection occurs below the 100 EMA, indicating a potential continuation of the downward trend. These signals help traders identify favorable entry points for long or short positions.
Risk Management: As with any trading strategy, proper risk management is crucial. Traders can use stop-loss orders to limit potential losses in case the market moves against their positions. Additionally, setting profit targets or trailing stops can help secure profits as the trend progresses.
It's important to note that no trading strategy guarantees success, and it's recommended to test the strategy on historical data or in a demo trading environment before applying it with real funds. Furthermore, regular monitoring and adjustment may be necessary to adapt to changing market conditions.
Disclaimer: This description is for informational purposes only and should not be considered as financial advice. Trading carries risks, and individuals should exercise caution and consult with a qualified financial professional before making any investment decisions.
EMA ProHi Traders!
This Improved EMA Cross Pro Indicator does a few things that Ease Up Our Charting.
Personally it Saved me Tons of Time searching for structure highs / lows, measuring ranges and distances from my entry to stop or take profit.
It's like having most of your trade in front of you, charted for you.
Works Across Assets & Time Frames.
The Functions
1. Signals EMA Crosses - green for Bull Cross & Red for Bear Cross
2. Signals Touches to the 55 EMA
a. In a Bull Cross it will only signal touches and closes Above the 55
b. In a Bear Cross it will only signal touches and closes Under the 55
3. Plots Current Horizontals:
a. The current position of the 55
b. The last High & Low
4. Calculation:
a. % from the 55 to the High & Low
b. Risk / Reward Ratio ("Bad Risk Management" message appears if ratio is not favorable)
c. Over Range between the Low and the High
5. Labels - Current prices for all horizontals marked as Entry, Exit & Stop
Notes:
* This Indicator is Interchanging between bull and bear crosses, it recognizes the trend and adapts its high and low output.
* You Can and Should make your personal changes. everything can be changed in the settings inputs.
* You can Turn On & Off most functions in the settings inputs.
BYBIT:BTCUSDT.P
AggBands (v1) [qrsq]The "AggBands" indicator is a custom trading indicator designed to provide a consolidated view of the price action across multiple assets or trading pairs. It combines the price data from multiple tickers and calculates an aggregated price using user-defined weights for each ticker.
The indicator starts by defining the tickers to be included in the aggregation. You can choose from predefined configurations such as "BTC PAIRS," "CRYPTO TOTAL MARKET CAP," "TOP 5 PAIRS," "TOP 5 MEMECOINS," "SPX," "DXY," or "FANG." Each configuration includes specific tickers or indices relevant to the chosen category.
The indicator then fetches the closing, high, and low prices for each ticker and applies the user-defined weights to calculate the aggregated prices. The aggregated prices are normalized within a specified length to provide a consistent scale across different assets or pairs.
Next, the indicator calculates the midpoint, which is the average of the highest high and lowest low of the aggregated prices over a specified aggregation period.
To assess the volatility, the indicator calculates the price range and applies the Average True Range (ATR) indicator to determine the volatility value. The standard deviation is then computed using the price range and aggregation period, with an additional scaling factor applied to the volatility value.
Based on the standard deviation, the indicator generates multiple bands above and below the midpoint. By default, three standard deviation bands are calculated, but the user can choose between one and five bands. The upper and lower bands are smoothed using various moving average (MA) types, such as Simple Moving Average (SMA), Exponential Moving Average (EMA), Smoothed Moving Average (SMMA/RMA), Weighted Moving Average (WMA), Volume Weighted Moving Average (VWMA), Volume Weighted Average Price (VWAP), or Arnaud Legoux Moving Average (ALMA). The user can also adjust the length, offset, and sigma parameters for the moving averages.
The indicator can optionally smooth the midpoint, upper bands, and lower bands using a separate set of moving average parameters.
The indicator can be useful for traders and analysts who want to gain a consolidated view of price movements across multiple assets or trading pairs. It helps identify trends, volatility, and potential support and resistance levels based on the aggregated price and standard deviation bands. Traders can use this information to make informed decisions about trading strategies, risk management, and market analysis.
EMA orderly stacked or notThis script plots a green circle on top of the chart when the EMAs are stacked positively, a red circle if they are stacked negatively and gray if neither positively nor negatively stacked.
The EMAs used are:
8 EMA
21 EMA
34 EMA
55 EMA
89 EMA
Useful when you look for a quick and easy way to see if these EMAs are stacked positively or negatively as a confirmation to the Squeeze Pro indicator if going long or short (Squeeze Pro is developed by John Carter at SimplerTrading.com and can be purchased there).
Default 100 bars back, but that can be adjusted.
Remember to do your own research.
Feel free to adjust the script to your liking.
The script is not meant to be, and do not constitute, financial, investment, trading, or other types of advice or recommendations supplied or endorsed by me.
Have fun!
Recursive Moving Average DifferenceThe relative difference between a moving average and the price can be a useful tool for interpreting trend direction and identifying pullbacks or breakdowns. This indicator recursively finds all the relative moving average differences between two simple moving averages of your choosing and weighs them by their lengths. It then returns a value that represents the weighted average of all the moving average differences. This can represent the gradient of motion between moving averages, or the path of least resistance, which the price may revert to in certain situations.
For the settings: minimum MA represents the minimum simple moving average to consider for the total weighted average. Maximum MA represents the maximum simple moving average to consider. "Move By" is the increment that you want to move between these two moving averages.
A positive moving average difference indicates that the price is above the moving average difference (i.e. the weighted average of all moving average differences between your two selected moving averages). A negative moving average difference indicates that the price is below the moving average difference. I have added a signal with a configurable length input as well to smooth out trends.
You can configure colors and lengths, as well as the counting increment. Future updates may include different ways to calculate weights, perhaps on overlay or strategy.
ADW - MomentumADW - Momentum is a trading indicator based on the Relative Momentum Index (RMI) and Exponential Moving Averages (EMAs). This indicator plots the RMI along with its EMAs and highlights regions where RMI crosses its slow EMA. Additionally, it provides alerts when the momentum flips bullish or bearish.
Key Features:
The RMI helps to identify momentum in the market.
Three EMAs (Fast, Standard, and Slow) were calculated on the RMI. These can be utilized to analyze the momentum trend over different periods.
Highlighted regions and colour coding to indicate when RMI crosses its Slow EMA, signalling potential momentum shifts.
Customizable parameters: Users can specify the lengths of the RMI and EMAs, boundaries for RMI, and colours for various components of the plot.
Alerts: The script can alert users when the momentum has flipped bullish or bearish.
The script is organized into several sections:
Inputs: The user can customize several parameters including the RMI averaging length, momentum lookback, RMI boundaries, and the EMA lengths. In addition, users can also specify the colours for the RMI line, Slow EMA line, and the fill colour.
RMI Calculation: The script calculates the RMI based on the user-provided length and momentum lookback. This is done by first calculating two EMAs - one for the positive differences between closing prices (emaInc), and one for the negative differences (emaDec). Then, the RMI is computed using these EMAs.
Plotting: The script plots the RMI line, Slow EMA line, and two horizontal lines indicating the RMI boundaries. In addition, it also fills the region between the RMI and Slow EMA lines.
Conditions: The script computes the conditions for bullish and bearish momentum flips. These are defined as when the RMI crosses above or below the Slow EMA respectively.
Alerts: Finally, the script sets up two alert conditions based on the bullish and bearish conditions. These alert the user when the momentum has flipped bullish or bearish, with a message that includes the current RMI value.
ADW - Colour TrendColour Trend is an indicator that will give you a visual representation of the trend in a selected market, and alert you when the trend changes. The green colour represents a bullish trend (prices are going up), the red colour represents a bearish trend (prices are going down), and silver represents a neutral trend (prices are relatively stable). The script calculates these trends based on the relative price levels and their moving averages.
Below is a breakdown of the script so you can better understand how these trends are defined.
Function f_p(_length, price) : This function calculates the price relative to its highest and lowest point over the given `_length` of time. This calculation is normalized by multiplying it by 100, giving us a percentage-like measure.
User Inputs : The length of the period (default 12), you can choose to show or hide bar colours (default is true).
Variables cycle_avg, cycle_counter, cycle_count, cycle_trend, cycle_col : These variables are used to calculate the trend cycles. The `cycle_avg` is the average trend cycle, `cycle_counter` keeps track of the current trend cycle, `cycle_count` counts the total number of cycles, `cycle_trend` keeps track of the direction of the cycle (1 for up, -1 for down), and `cycle_col` defines the colour of the current cycle.
Variables ph, pl, avg, mean : These variables calculate the price level relative to the highest and lowest prices (`ph` and `pl`), the average of these two levels (`avg`), and the cumulative average of the price level (`mean`).
Conditionals for cycle trend : The if-statements are checking whether the price level has reached a trend extreme and then updating the trend cycle, colour, count, and average accordingly.
Variable col and bar color : The variable `col` is used to define the colour of the bars based on the average price level. If the `show_barcolor` is true, the colour is determined based on the `avg` value.
Alert Conditions : These are conditions that will send alerts to the user when the trend changes. Specifically, the alerts occur when the colour changes from non-green to green (bull trend), from non-red to red (bear trend), or from non-silver to silver (no trend).
RSI of Zero Lag MA (ValueRay)The RSI of a Zero Lag Moving Average a powerful tool for for reliable exit signals.
The Relative Strength Index (RSI) is a widely recognized momentum oscillator that measures the speed and change of price movements. It provides valuable insights into overbought and oversold conditions, enabling traders to identify potential reversal points and take advantage of market inefficiencies.
The RSI of a Zero Lag Indicator takes this concept a step further by incorporating the Zero Lag Moving Average. The Zero Lag Moving Average is a cutting-edge indicator that minimizes lag and provides a smoother representation of price action, allowing for quicker and more precise responses to market movements.
By combining the RSI with the Zero Lag Moving Average, this indicator offers traders a superior exit strategy. When the RSI reaches extreme levels of overbought or oversold conditions, it indicates a potential reversal in the market. The Zero Lag Moving Average further enhances this signal by reducing delays and providing timely exit points.
Moreover, the RSI of a Zero Lag Indicator is not limited to mean reversion strategies. While it excels in identifying mean reversion opportunities, it can also be used in conjunction with other trading approaches. Traders can take advantage of its objective signals to exit trades profitably, regardless of their chosen strategy.
With its ability to accurately pinpoint overbought and oversold conditions, the RSI of a Zero Lag Indicator offers traders a competitive edge in the market. By providing timely exit signals and minimizing lag, it helps traders optimize their trading decisions and increase their chances of success.
Multi-Divergence Buy/Sell IndicatorThe "Multi-Divergence Buy/Sell Indicator" is a technical analysis tool that combines multiple divergence signals from different indicators to identify potential buy and sell opportunities in the market. Here's a breakdown of how the indicator works and how to use it:
Input Parameters:
RSI Length: Specifies the length of the RSI (Relative Strength Index) calculation.
MACD Short Length: Specifies the short-term length for the MACD (Moving Average Convergence Divergence) calculation.
MACD Long Length: Specifies the long-term length for the MACD calculation.
MACD Signal Smoothing: Specifies the smoothing length for the MACD signal line calculation.
Stochastic Length: Specifies the length of the Stochastic oscillator calculation.
Stochastic Overbought Level: Defines the overbought level for the Stochastic oscillator.
Stochastic Oversold Level: Defines the oversold level for the Stochastic oscillator.
Calculation of Indicators:
RSI: Calculates the RSI based on the specified RSI Length.
MACD: Calculates the MACD line, signal line, and histogram based on the specified MACD parameters.
Stochastic: Calculates the Stochastic oscillator based on the specified Stochastic parameters.
Divergence Detection:
RSI Divergence: Identifies a bullish divergence when the RSI crosses above its 14-period simple moving average (SMA).
MACD Divergence: Identifies a bullish divergence when the MACD line crosses above the signal line.
Stochastic Divergence: Identifies a bullish divergence when the Stochastic crosses above its 14-period SMA.
Buy and Sell Conditions:
Buy Condition: Triggers a buy signal when all three divergences (RSI, MACD, and Stochastic) occur simultaneously.
Sell Condition: Triggers a sell signal when both RSI and MACD divergences occur, but Stochastic divergence does not occur.
Plotting Buy/Sell Signals:
The indicator plots green "Buy" labels below the price bars when the buy condition is met.
It plots red "Sell" labels above the price bars when the sell condition is met.
Usage:
The indicator can be used on any timeframe and for any trading instrument.
Look for areas where all three divergences (RSI, MACD, and Stochastic) align to generate stronger buy and sell signals.
Consider additional technical analysis and risk management strategies to validate the signals and manage your trades effectively.
Remember, no indicator guarantees profitable trades, so it's essential to use this indicator in conjunction with other tools and perform thorough analysis before making trading decisions.
Feel free to ask any questions
Price Action (ValueRay)With this indicator, you gain access to up to 5 moving averages from a selection of 15 different types. This flexibility allows you to customize your trading strategy based on your preferences and market conditions. Whether you're a fan of simple moving averages, exponential moving averages, or weighted moving averages, our indicator has got you covered! Additionally, all the MAs are Multi-Time-Frame!
The indicator also provides trading signals. By analyzing market trends and price movements, it generates accurate buy and sell signals, providing you with clear entry and exit points. You can choose between Fast, Mid, and Slow signal speeds.
Trendlines are another crucial aspect of effective trading, and our indicator seamlessly integrates them, helping you visualize the market's direction.
Furthermore, the indicator empowers you with recent highs and lows. By highlighting these key levels, it becomes easier than ever to spot support and resistance areas, aiding you in making well-informed trading choices.
Additionally, you can switch the ADR% (Average Daily Range as a Percentage) on and off. This number instantly provides you with information on how much the stock usually moves per day as a percentage.
Key Features:
Up to 5 Moving Averages, each with its own timeframe.
SMA, EMA, WMA, RMA, Triangular, Volume Weighted, Elastic Volume Weighted, Least Squares, ZLEMA, Hull, Double EMA, Triple EMA, T3, ALMA, KAMA (more to come in future versions).
Recent High and Low Pivot Points acting as support/resistance.
Trendline indicating the current trend.
Buy/Sell Signals (recommended for use as exit points, stop loss, or take profit levels).
Signals can have three different speeds: Fast, Mid, and Slow. You can switch them anytime depending on how quickly or slowly you want to exit a trade.
The predefined colors are best suited for a dark background, and the predefined settings provide a solid starting point that many traders use in their daily work.
Unlock the full potential of your trading strategy with our comprehensive indicator and start making informed trading decisions today!
Moving Averages + BB & R.VWAP StDev (multi-tf)█ Moving Averages + Bollinger Bands and Rolling Volume Weighted Average Price with Standard Deviation Bands (Multi Timeframe)
Multiple moving averages can be independently applied.
The length , type and timeframe of each moving average are configurable .
The lines and colors are customizable too.
This script can display:
Moving Averages
Bollinger Bands
Rolling VWAP and Standard Deviation Bands
Types of Moving Averages:
Simple Moving Average (SMA)
Exponential Moving Average (EMA)
Smoothed Moving Average (SMMA)
Weighted Moving Average (WMA)
Volume Weighted Moving Average (VWMA)
Least Squares Moving Average (LSMA)
Hull Moving Average (HMA)
Arnaud Legoux Moving Average (ALMA)
█ Moving Average
Moving Averages are price based, lagging (or reactive) indicators that display the average price of a security over a set period of time.
A Moving Average is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance.
█ Bollinger Bands
Bollinger Bands consist of a band of three lines which are plotted in relation to security prices.
The line in the middle is usually a Simple Moving Average (SMA) set to a period of 20 days (the type of trend line and period can be changed by the trader, a 20 day moving average is by far the most popular).
The SMA then serves as a base for the Upper and Lower Bands which are used as a way to measure volatility by observing the relationship between the Bands and price.
█ Rolling VWAP
The typical VWAP is designed to be used on intraday charts, as it resets at the beginning of the day.
Such VWAPs cannot be used on daily, weekly or monthly charts. Instead, this rolling VWAP uses a time period that automatically adjusts to the chart's timeframe.
You can thus use the rolling VWAP on any chart that includes volume information in its data feed.
Because the rolling VWAP uses a moving window, it does not exhibit the jumpiness of VWAP plots that reset.
Based on the previous script :
Discrete Fourier Transform Overlay [wbburgin]The discrete Fourier transform (DFT) overlay uses a discrete Fourier transform algorithm to identify trend direction. This is a simpler interpretation that only uses the magnitude of the first frequency component obtained from the DFT algorithm, but can be useful for visualization purposes. I haven't seen many Fourier scripts on TradingView that actually have the magnitude plotted on the chart (some have lines, for instance, but that makes it difficult to look into the past or to see previous lines).
About the Discrete Fourier Transform
The DFT is a mathematical transformation that decomposes a time-domain signal into its constituent frequency components. By applying the DFT to OHLC data, we can interpret the periodicities and trends present in the market. I've designed the overlay so that you can choose your source for the Fourier transform, as well as the length.
Settings and Configuration
The "Fourier Period" is the transform length of the DFT algorithm. This input indicates the number of data points considered for the DFT calculation. For example, if this input is set to 20, the DFT will be performed on the most recent 20 data points of the input series. The transform length affects the resolution and accuracy of the frequency analysis. A shorter transform length may provide a broader frequency range but with less detail, while a longer transform length can provide finer frequency resolution but may be computationally more intensive (I recommend using under 100 - anything above that might take too much time to load on the platform).
The "Fourier X Series" is the source you want the Fourier transform to be applied to. I have it set in default to the close.
"Kernel Smoothing" is the bar-start of the rational quadratic kernel used to smooth the frequency component. Think of it just like a normal moving average if you are unfamiliar with the concept, it functions similarly to the "length" value of a moving average.
TTP NVT StudioNVT Studio is an indicator that aims to find areas of reversal of the Bitcoin price based on the extreme areas of Network Value Transaction.
Instructions:
- We recommend using it on INDEX:BTCUSD
- Use the daily or weekly timeframe
The indicator works as an oscillator and offers to visualisation modes.
1) Showing the short term oscillations of NVT showing signals in potential areas of reversal.
2) The actual value of NVT displayed. When in green is an area of value and in red when its overextended.
This indicator can be used based on the signals or based on breakouts of trend lines drawn in the oscillator mode.
Red/green dots: signal type 1 - extremes with confirmation, these might trigger late
Yellow/Orange: signal type 2 - extremes without confirmation, might trigger too soon
Moving Average Contrarian IndicatorThis indicator is designed to identify potential turning points in the market. By measuring the distance between the price and a moving average, and normalizing it, the MACI provides valuable insights into market sentiment and potential reversals. In this article, we will explore the calculation, interpretation, and practical applications of the MACI, along with its potential limitations.
The MACI is calculated in several steps. First, a moving average is computed using a user-defined length, representing the average price over the specified period. The distance between the current price and the moving average is then determined. This distance is normalized using the highest and lowest distances observed within the chosen length, resulting in a value between 0 and 100. Higher MACI values indicate that the price is relatively far from the moving average, potentially signaling an overextension, while lower values suggest price consolidation or convergence with the moving average.
Altering the parameters of the Moving Average Contrarian Indicator can provide traders with additional flexibility and adaptability to suit different market conditions and trading styles. By adjusting the length parameter, traders can customize the sensitivity of the indicator to price movements. A shorter length may result in more frequent and responsive signals, which can be useful for short-term traders aiming to capture quick price reversals. On the other hand, a longer length may provide smoother signals, suited for traders who prefer to focus on longer-term trends and are less concerned with minor fluctuations. Experimenting with different parameter values allows traders to fine-tune the indicator to align with their preferred trading timeframes and risk tolerance. However, it is essential to strike a balance and avoid excessive parameter adjustments that may lead to over-optimization or curve fitting. Regular evaluation and optimization based on historical data and real-time market observations can help identify the most suitable parameter values for optimal performance.
The coloration of the Moving Average Contrarian Indicator provides visual cues that assist traders in interpreting its signals. The background color, set based on the indicator's values, adds an additional layer of context to the chart. When the indicator is indicating bullish conditions, the background color is set to lime, suggesting a favorable environment for long positions. Conversely, when the indicator signals bearish conditions, the background color is set to fuchsia, indicating a potential advantage for short positions. In neutral or transitional periods, the background color is set to yellow, indicating caution and the absence of a clear bias.
The bar color complements the histogram and provides additional visual clarity. When the MACI value is greater than the MACI SMA value and exceeds the threshold of 30, the bars are colored lime, signaling potential bullish conditions. Conversely, when the MACI value is below the MACI SMA value and falls below the threshold of 70, the bars are colored fuchsia, indicating potential bearish conditions. For values that fall between these thresholds, the bars are colored yellow, highlighting a neutral or transitional state.
Practical Uses and Strategies:
The MACI offers traders and analysts valuable insights into market dynamics and potential reversal points. When the MACI is above its moving average and above a predefined threshold (e.g., 30), it suggests that prices have deviated significantly from the average and may be overbought. This could serve as an early indication for potential short-selling opportunities or taking profits on existing long positions. Conversely, when the MACI is below its moving average and below a predefined threshold (e.g., 70), it suggests oversold conditions, potentially signaling a buying opportunity. Traders can combine MACI with other technical indicators or price patterns to further refine their trading strategies.
The MACI can be a powerful tool for identifying potential market reversals. When the MACI reaches extreme levels, such as above 70 or below 30, it indicates overbought or oversold conditions, respectively. Traders can use these signals to anticipate price reversals and adjust their trading strategies accordingly. For example, when the MACI enters the overbought zone, traders may consider initiating short positions or tightening stop-loss levels on existing long positions. Conversely, when the MACI enters the oversold zone, it may indicate a buying opportunity, prompting traders to consider initiating long positions or loosening stop-loss levels.
The MACI can also be used in conjunction with price action to identify potential divergence patterns. Divergence occurs when the MACI and price move in opposite directions. For instance, if the price is making higher highs while the MACI is making lower highs, it suggests a bearish divergence, indicating a potential trend reversal. Conversely, if the price is making lower lows while the MACI is making higher lows, it suggests a bullish divergence, signaling a potential trend reversal to the upside. Traders can use these divergence patterns as additional confirmation signals when making trading decisions.
Limitations:
-- Sideways and Choppy Markets : The MACI performs best in trending markets where price movements are more pronounced. In sideways or choppy markets with limited directional bias, the MACI may generate false signals or provide less reliable indications. Traders should exercise caution when relying solely on the MACI in such market conditions and consider incorporating additional analysis techniques or filters to confirm potential signals.
-- Lagging Indicator : The MACI is a lagging indicator, as it relies on moving averages and historical price data. It may not provide timely signals for very short-term trading or capturing rapid price movements. Traders should be aware that there may be a delay between the occurrence of a signal and its confirmation by the MACI.
-- False Signals : Like any technical indicator, the MACI is not immune to false signals. It is essential to use the MACI in conjunction with other technical indicators, chart patterns, or fundamental analysis to increase the probability of accurate predictions. Combining multiple confirmation signals can help filter out false signals and enhance the overall reliability of trading decisions.
-- Market Conditions : It's important to consider that the effectiveness of the MACI may vary across different markets and asset classes. Each market has its own characteristics, and what works well in one market may not work as effectively in another. Traders should evaluate the performance of the MACI within their specific trading environment and adapt their strategies accordingly.
This indicator can be a valuable addition to a trader's toolkit, offering insights into potential entry and exit points. However, it should be used in conjunction with other analysis techniques and should not be relied upon as a standalone trading signal. Understanding its calculation, interpreting its values, and considering its limitations will empower traders to make more informed decisions in their pursuit of trading success.
Moving Average Reversals [QuantVue]Moving Average Reversals
Description:
The Moving Average Reversals indicator gives a quick visual representation of when a stock gets extended up or down from a user selected moving average.
The color of the histogram dynamically changes as price becomes extended or within it’s normal trading range.
The indicator also highlights the largest extensions over the past year or 252 bars if using intraday.
Lastly a simple moving average of the extensions is calculated and used to confirm a change of character.
Settings:
🔹Use different MA types - EMA, SMA, HMA, WMA, VWMA
🔹Adjustable MA length
🔹Change distance measurement source - open, close, high, low, hl2, hlc3, ohlc4, hlcc4
🔹Extension highlighting
🔹Toggle MA extensions
Don't hesitate to reach out with any questions or concerns. We hope you enjoy!
Cheers.
MADI(Moving average deviation rate index)This script is "Moving average deviation rate" to Indexing.
index = average deviation rate / (Sigma * (input:SIgma)) * 100
It's for people who like simplicity.
Biddles OIWAP-Price SpreadThis indicator is the companion to my OIWAP (Open Interested-Weighted Average price) open source indicator.
In observing the OIWAP, what seemed most interesting was the distance between price and OIWAP.
This indicator plots that spread in a histogram.
It seems when price is too high above all OIWAPs, it's locally overbought (sentiment is overly bullish), and vice versa when it's too far below all OIWAPs (sentiment is overly bearish).
But I think there are more unique observations to be made beyond that - I am still in discovery phase myself.
For example: Looking at the SPX while using the ticker override to display BINANCE:BTCUSDT.P OI-Price spread data.
It works on any asset that Tradingview has OI data for. But it's also interesting to view correlated assets by using ticker override in the indicator settings (open the correlated asset w/o OI data in your chart, then set ticker override to a symbol with OI data, like the SPX example above).
>> If you find any interesting observations using it, have suggestions for improving the script, etc., hit me up on Twitter!
>>> @thalamu_
Wyckoff Range StrategyThe Wyckoff Range Strategy is a trading strategy that aims to identify potential accumulation and distribution phases in the market using the principles of Wyckoff analysis. It also incorporates the detection of spring and upthrust patterns.
Here's a step-by-step explanation of how to use this strategy:
Understanding Accumulation and Distribution Phases:
Accumulation Phase: This is a period where smart money (large institutional traders) accumulates a particular asset at lower prices. It is characterized by a sideways or consolidating price action.
Distribution Phase: This is a period where smart money distributes or sells a particular asset at higher prices. It is also characterized by a sideways or consolidating price action.
Input Variables:
crossOverLength: This variable determines the length of the moving average crossover used to identify accumulation and distribution phases. You can adjust this value based on the market you are trading and the time frame you are analyzing.
stopPercentage: This variable determines the percentage used to calculate the stop loss level. It helps you define a predefined level at which you would exit a trade if the price moves against your position.
Strategy Conditions:
Enter Long: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength and a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the start of an accumulation phase and a potential buying opportunity.
Exit Long: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength or a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the end of an accumulation phase and a potential exit signal for long positions.
Enter Short: The strategy looks for a crossunder of the close price below the SMA of the close price with a length of crossOverLength and a crossunder of the high price below the SMA of the high price with a length of 20. This combination suggests the start of a distribution phase and a potential selling opportunity.
Exit Short: The strategy looks for a crossover of the close price above the SMA of the close price with a length of crossOverLength or a crossover of the low price above the SMA of the low price with a length of 20. This combination suggests the end of a distribution phase and a potential exit signal for short positions.
Stop Loss:
The strategy sets a stop loss level for both long and short positions. The stop loss level is calculated based on the stopPercentage variable, which represents the percentage of the current close price. If the price reaches the stop loss level, the strategy will automatically exit the position.
Plotting Wyckoff Schematics:
The strategy plots different shapes on the chart to indicate the identified phases and patterns. Green and red labels indicate the accumulation and distribution phases, respectively. Blue triangles indicate spring patterns, and orange triangles indicate upthrust patterns.
To use this strategy, you can follow these steps:
Jim Forte — Anatomy of a Trading Range
robertbrain.com/Bull...+a+Trading+Range.pdf
Adaptive Gaussian Moving AverageThe Adaptive Gaussian Moving Average (AGMA) is a versatile technical indicator that combines the concept of a Gaussian Moving Average (GMA) with adaptive parameters based on market volatility. The indicator aims to provide a smoothed trend line that dynamically adjusts to different market conditions, offering a more responsive analysis of price movements.
Calculation:
The AGMA is calculated by applying a weighted moving average based on a Gaussian distribution. The length parameter determines the number of bars considered for the calculation. The adaptive parameter enables or disables the adaptive feature. When adaptive is true, the sigma value, which represents the standard deviation, is dynamically calculated using the standard deviation of the closing prices over the volatilityPeriod. When adaptive is false, a user-defined fixed value for sigma can be input.
Interpretation:
The AGMA generates a smoothed line that follows the trend of the price action. When the AGMA line is rising, it suggests an uptrend, while a declining line indicates a downtrend. The adaptive feature allows the indicator to adjust its sensitivity based on market volatility, making it more responsive during periods of high volatility and less sensitive during low volatility conditions.
Potential Uses in Strategies:
-- Trend Identification : Traders can use the AGMA to identify the direction of the prevailing trend. Buying opportunities may arise when the price is above the AGMA line during an uptrend, while selling opportunities may be considered when the price is below the AGMA line during a downtrend.
-- Trend Confirmation : The AGMA can be used in conjunction with other technical indicators or trend-following strategies to confirm the strength and sustainability of a trend. A strong and steady AGMA line can provide additional confidence in the prevailing trend.
-- Volatility-Based Strategies : Traders can utilize the adaptive feature of the AGMA to build volatility-based strategies. By adjusting the sigma value based on market volatility, the indicator can dynamically adapt to changing market conditions, potentially improving the accuracy of entry and exit signals.
Limitations:
-- Lagging Indicator : Like other moving averages, the AGMA is a lagging indicator that relies on historical price data. It may not provide timely signals during rapidly changing market conditions or sharp price reversals.
-- Whipsaw in Sideways Markets : During periods of low volatility or when the market is moving sideways, the AGMA may generate false signals or exhibit frequent crossovers around the price, leading to whipsaw trades.
-- Subjectivity of Parameters : The choice of length, adaptive parameters, and volatility period requires careful consideration and customization based on individual preferences and trading strategies. Traders need to adjust these parameters to suit the specific market and timeframe they are trading.
Overall, the Adaptive Gaussian Moving Average can be a valuable tool in trend identification and confirmation, especially when combined with other technical analysis techniques. However, traders should exercise caution, conduct thorough analysis, and consider the indicator's limitations when incorporating it into their trading strategies.
Chilllax Moving Averages with Qullamaggie colors// Display 2 Moving Averages. Default is 10d sma and 20d sma. You can choose any length. Choose sma, or ema. Choose ma of Open, High, Low, or Close
// Color code is based on Qullamaggie's idea:
// Dark green = 10d ma > 20d ma, and both trending up
// Light green = 10d ma > 20d ma, but only 10d ma trending up
// Yellow = 10d ma > 20d ma, but neither trending up
// You can change the color
// You can hide the colors, then it will simply show 2 moving averages of your choice
// Trend is comparing the ma from X trendlen days ago. Default to 5 days ago. So, if today's ma is > 5 days ago, it is trending up
Nonlinear Regression, Zero-lag Moving Average [Loxx]Nonlinear Regression and Zero-lag Moving Average
Technical indicators are widely used in financial markets to analyze price data and make informed trading decisions. This indicator presents an implementation of two popular indicators: Nonlinear Regression and Zero-lag Moving Average (ZLMA). Let's explore the functioning of these indicators and discuss their significance in technical analysis.
Nonlinear Regression
The Nonlinear Regression indicator aims to fit a nonlinear curve to a given set of data points. It calculates the best-fit curve by minimizing the sum of squared errors between the actual data points and the predicted values on the curve. The curve is determined by solving a system of equations derived from the data points.
We define a function "nonLinearRegression" that takes two parameters: "src" (the input data series) and "per" (the period over which the regression is calculated). It calculates the coefficients of the nonlinear curve using the least squares method and returns the predicted value for the current period. The nonlinear regression curve provides insights into the overall trend and potential reversals in the price data.
Zero-lag Moving Average (ZLMA)
Moving averages are widely used to smoothen price data and identify trend directions. However, traditional moving averages introduce a lag due to the inclusion of past data. The Zero-lag Moving Average (ZLMA) overcomes this lag by dynamically adjusting the weights of past values, resulting in a more responsive moving average.
We create a function named "zlma" that calculates the ZLMA. It takes two parameters: "src" (the input data series) and "per" (the period over which the ZLMA is calculated). The ZLMA is computed by first calculating a weighted moving average (LWMA) using a linearly decreasing weight scheme. The LWMA is then used to calculate the ZLMA by applying the same weight scheme again. The ZLMA provides a smoother representation of the price data while reducing lag.
Combining Nonlinear Regression and ZLMA
The ZLMA is applied to the input data series using the function "zlma(src, zlmaper)". The ZLMA values are then passed as input to the "nonLinearRegression" function, along with the specified period for nonlinear regression. The output of the nonlinear regression is stored in the variable "out".
To enhance the visual representation of the indicator, colors are assigned based on the relationship between the nonlinear regression value and a signal value (sig) calculated from the previous period's nonlinear regression value. If the current "out" value is greater than the previous "sig" value, the color is set to green; otherwise, it is set to red.
The indicator also includes optional features such as coloring the bars based on the indicator's values and displaying signals for potential long and short positions. The signals are generated based on the crossover and crossunder of the "out" and "sig" values.
Wrapping Up
This indicator combines two important concepts: Nonlinear Regression and Zero-lag Moving Average indicators, which are valuable tools for technical analysis in financial markets. These indicators help traders identify trends, potential reversals, and generate trading signals. By combining the nonlinear regression curve with the zero-lag moving average, this indicator provides a comprehensive view of the price dynamics. Traders can customize the indicator's settings and use it in conjunction with other analysis techniques to make well-informed trading decisions.
Volatility SpeedometerThe Volatility Speedometer indicator provides a visual representation of the rate of change of volatility in the market. It helps traders identify periods of high or low volatility and potential trading opportunities. The indicator consists of a histogram that depicts the volatility speed and an average line that smoothes out the volatility changes.
The histogram displayed by the Volatility Speedometer represents the rate of change of volatility. Positive values indicate an increase in volatility, while negative values indicate a decrease. The height of the histogram bars represents the magnitude of the volatility change. A higher histogram bar suggests a more significant change in volatility.
Additionally, the Volatility Speedometer includes a customizable average line that smoothes out the volatility changes over the specified lookback period. This average line helps traders identify the overall trend of volatility and its direction.
To enhance the interpretation of the Volatility Speedometer, color zones are used to indicate different levels of volatility speed. These color zones are based on predefined threshold levels. For example, green may represent high volatility speed, yellow for moderate speed, and fuchsia for low speed. Traders can customize these threshold levels based on their preference and trading strategy.
By monitoring the Volatility Speedometer, traders can gain insights into changes in market volatility and adjust their trading strategies accordingly. For example, during periods of high volatility speed, traders may consider employing strategies that capitalize on price swings, while during low volatility speed, they may opt for strategies that focus on range-bound price action.
Adjusting the inputs of the Volatility Speedometer indicator can provide valuable insights and flexibility to traders. By modifying the inputs, traders can customize the indicator to suit their specific trading style and preferences.
One input that can be adjusted is the "Lookback Period." This parameter determines the number of periods considered when calculating the rate of change of volatility. Increasing the lookback period can provide a broader perspective of volatility changes over a longer time frame. This can be beneficial for swing traders or those focusing on longer-term trends. On the other hand, reducing the lookback period can provide more responsiveness to recent volatility changes, making it suitable for day traders or those looking for short-term opportunities.
Another adjustable input is the "Volatility Measure." In the provided code, the Average True Range (ATR) is used as the volatility measure. However, traders can choose other volatility indicators such as Bollinger Bands, Standard Deviation, or custom volatility measures. By experimenting with different volatility measures, traders can gain a deeper understanding of market dynamics and select the indicator that best aligns with their trading strategy.
Additionally, the "Thresholds" inputs allow traders to define specific levels of volatility speed that are considered significant. Modifying these thresholds enables traders to adapt the indicator to different market conditions and their risk tolerance. For instance, increasing the thresholds may highlight periods of extreme volatility and help identify potential breakout opportunities, while lowering the thresholds may focus on more moderate volatility shifts suitable for range trading or trend-following strategies.
Remember, it is essential to combine the Volatility Speedometer with other technical analysis tools and indicators to make informed trading decisions.
