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M-oscillator

Slope NormalizerBrief: This oscillator style indicator takes another indicator as its source and measures the change over time (the slope). It then isolates the positive slope values from the negative slope values to determine a 'normal' slope value for each. ** A 'normal' value of 1.0 is determined by the average slope plus the standard deviation of that slope. The Scale This indicator is not perfectly linear. The values are interpolated differently from 0.0 - 1.0 than values greater than 1.0. From values 0.0 to 1.0 (positive or negative): it means that the value of the slope is less than 'normal' **. Any value above 1.0 means the current slope is greater than 'normal' **. A value of 2.0 means the value is the average plus 2x the standard deviation. A value of 3.0 means the value is the average plus 3x the standard deviation. A value greater than 4.0 means the value is greater than the average plus 4x the standard deviation. Because the slope value is normalized, the meaning of these values can remain generally the same for different symbols. Potential Usage Examples/b] Using this in conjunction with an SMA or WMA may indicate a change in trend, or a change in trend-strength. Any values greater than 4 indicate a very strong (and unusual) trend that may not likely be sustainable. Any values cycling between +1.0 and -1.0 may mean indecision. A value that is decreasing below 0.5 may predict a change in trend (slope may soon invert).
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Electrified tarafından
7
Band Pass Normalized Suite (BPNS)Outlier-Free Normalization and Band Pass Filtering We present a technique for normalizing and filtering a given time series, source, in order to improve its stationarity and enhance its features. The technique includes two stages: outlier-free normalization and band pass filtering. Outlier-Free Normalization: In order to normalize source and reduce the impact of outliers, we first smooth the time series using an exponential moving average with a smoothing factor of alpha. The smoothed time series is then normalized by subtracting the minimum value within a given lookback period, dev_lookback, and dividing the result by the range (maximum - minimum) within the same lookback period. Outliers are detected and excluded from the normalization process by identifying values that are more than outlier_level standard deviations away from the exponentially smoothed average. Band Pass Filtering: After normalization, the time series is passed through a band pass filter to remove low and high frequency components. The specifics of the band pass filter implementation are not provided. Code snippet: bes(float source = close, float alpha = 0.7) => var float smoothed = na smoothed := na(smoothed) ? source : alpha * source + (1 - alpha) * nz(smoothed ) max(source, outlier_level, dev_lookback)=> var float max = na src = array.new() stdev = math.abs((source - bes(source, 0.1))/ta.stdev(source, dev_lookback)) array.push(src, stdev < outlier_level ? source : -1.7976931348623157e+308) max := math.max(nz(max ), array.get(src, 0)) min(source, outlier_level, dev_lookback) => var float min = na src = array.new() stdev = math.abs((source - bes(source, 0.1))/ta.stdev(source, dev_lookback)) array.push(src, stdev < outlier_level ? source : 1.7976931348623157e+308) min := math.min(nz(min ), array.get(src, 0)) min_max(src, outlier_level, dev_lookback) => (src - min(src, outlier_level, dev_lookback))/(max(src, outlier_level, dev_lookback) - min(src, outlier_level, dev_lookback)) * 100 To apply the outlier-free normalization and band pass filter to a given time series, source, the min_max() function can be called with the desired values for outlier_level and dev_lookback as arguments. For example: normalized_source = min_max(source, 2, 50) This will apply the outlier-free normalization and band pass filter to source, using an outlier_level of 2 standard deviations and a lookback period of 50 data points for both the normalization and outlier detection steps. The resulting normalized and filtered time series will be stored in normalized_source. It is important to note that the choice of values for outlier_level and dev_lookback will have a significant impact on the resulting normalized and filtered time series. These values should be chosen carefully based on the characteristics of the input time series and the desired properties of the normalized and filtered output. In conclusion, the outlier-free normalization and band pass filtering technique presented here provides a useful tool for preprocessing time series data and improving its stationarity and feature content. The flexibility of the method, through the choice of outlier_level and dev_lookback values, allows it to be tailored to the specific characteristics of the input time series.
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The_Peaceful_Lizard tarafından
11
Slope Normalized (SN)Introduction: The Normalized Slope script is a technical indicator that aims to measure the strength and direction of a trend in a financial market. It does this by calculating the slope of the source data series, which can be any type of data (such as price, volume, or an oscillator) over a specified length of time. The slope is then normalized, meaning it is transformed to a scale between -1 and 1, with 0 representing a flat trend. Methodology: The Normalized Slope script uses an exponential smoothing function to smooth the source data series. The smoothing factor, or alpha, can be adjusted by the user through the input parameter "Pre Smoothing". Next, the script calculates the slope of the smoothed data series by finding the average difference between the current value and the values of the previous "Length" periods. This slope is then normalized using a function that scales the data to a range of -1 to 1, with 0 representing a flat trend. The normalization function takes the minimum and maximum values of the slope, calculates the difference between them, and then scales the data to the range of -1 to 1. The normalized slope is then smoothed again using another exponential smoothing function with a user-adjustable smoothing factor (the "Post Smoothing" input parameter). A center line representing a flat trend can also be plotted on the chart by enabling the "Center Line" input parameter. Additionally, the user can choose to display bounds at the -1 and 1 levels by enabling the "Bounds" input parameter. Conclusion: The Normalized Slope script provides traders with a visual representation of the strength and direction of a trend in a financial market. It can be used as a standalone indicator or in combination with other technical analysis tools to help traders make informed trading decisions.
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The_Peaceful_Lizard tarafından
5
Regime Filter [CHE]About: A market regime filter is a tool used by traders and investors to identify the current state or "regime" of the market and adjust their investment strategies accordingly. This can involve identifying trends in market behavior, such as bullish or bearish trends, and using that information to make decisions about which assets to buy or sell. Market regime filters can be based on a variety of factors, including economic indicators, market sentiment, and technical analysis. They are often used in conjunction with other trading strategies and can help traders and investors manage risk and optimize their returns. It's important to note that market regime filters are not always accurate and can change over time, so it's important for traders and investors to regularly review and update their filters to ensure that they are relevant and effective. Understanding the use of a regime filter in trading: The importance of a trading filter cannot be overemphasized. As a matter of fact, the chances of any trading system making consistent returns over the long term depends on it trading in the right market environment — buying when the market is bullish and selling when the market is bearish. Some traders may want to stay out of the market when the conditions are unfavorable. The heard of this Regime Filter is the well kown Andean Oscillator. The proposed indicator aims to measure the degree of variations of individual up-trends and down-trends in the price, thus allowing to highlight the direction and amplitude of a current trend. Settings Length : Determines the significance of the trends degree of variations measured by the indicator. Signal Length : Moving average period of the signal line. The regime filter uses the color yellow and blue, yellow stands for bullish and blue for bearish. In daily use I have found that it makes sense to use it in different timeframes to identify meaningful trends. best regards and I hope you enjoy this new indicator Chervolino
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chervolino tarafından
7
Impulse Alerts - Riccardo Di GiacomoThis is the Impulse indicator that allows you to receive alerts in the case one of the following situation occurs: 1) Buy Setup - Price above Exponential Moving Average 260 - Moving Average 21 above Exponential Moving Average 260 - Moving Average 9 above Moving Average 21 - RSI(14) above 50 - Stochastic equal or below 20 2) Sell Setup - Price below Exponential Moving Average 260 - Moving Average 21 below Exponential Moving Average 260 - Moving Average 9 below Moving Average 21 - RSI(14) below 50 - Stochastic equal or above 80 The Bollinger Bands represents another useful information: - If the price is near the upper band when the first situation occurs, it is another green light, otherwise be careful - If the price is near the lower band when the second situation occurs, it is another green light, otherwise be careful
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riccardodigiacomo tarafından
Oscillator ExtremesThe Oscillator Extremes indicator plots the normalized positioning of the selected oscillator versus the Bollinger Bands' upper and lower boundaries. Currently, this indicator has four different oscillators to choose from; RSI, CMO, CCI, and ROC. When the oscillator pushes towards one extreme, it will bring the value of the prevailing line closer to zero. If the bullish or bearish line crosses the zero line, the oscillator is past the extreme of the Bollinger Band. Example: If the RSI crosses over the upper boundary of the Bollinger, the bullish(green) line will cross under the zero line. Crossovers of the bullish and bearish lines can indicate a shift in momentum and are a signal. Where the line crossing under, towards zero, is the prevailing trend. The plotted lines will highlight green(bullish) or red(bearish) to show the prevailing trend. This is similar to a DI+- crossover that is commonly associated with the ADX. We have included an optional normalized ADX to help validate signals. The ADX will change color based on the slope of the ADX. Purple indicates a positive slope and white for a negative slope.
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LeafAlgo tarafından
Vector MagnitudeThe pine indicator is a script for technical analysis of stock market data. It calculates the direction and magnitude of a moving average, and plots the result on a chart. The length of the moving average is specified by the user as an input parameter. The script uses the simple moving average (SMA) function from the TA-Lib library to calculate the average of the data. It then determines the direction of the vector by comparing the current value to the average. If the current value is greater than the average, the direction is set to 1. If it is less than the average, the direction is set to -1. Otherwise, the direction is set to 0. The magnitude of the vector is calculated using the Pythagorean theorem. The output is the magnitude of the vector, with the sign indicating the direction. A trader may use this pine script to help identify trends in the stock market. By plotting the direction and magnitude of the moving average on a chart, the trader can quickly see whether the market is trending up or down, and how strong the trend is. This can help the trader make informed decisions about when to buy and sell stocks. Additionally, the script allows the user to customize the length of the moving average, which can be useful for analyzing different time frames and making more accurate predictions.
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The_Peaceful_Lizard tarafından
LowHighFinderThis chart display how value change of (low,high,close,open) is considered as a factor for buying or selling. Each element take same weight when consider the final price. The price change over a certain threshold would be the decision point (buy/sell) Factors considered in this chart 1.Quotes: High,low,close,open,volume. If one of them higher than previous day, then it increase, otherwise decreases. 2. Multipler: If you think one quote is more important than other (High more important than close, you can set multipler higher) 3. EMA smoother: It is using to balance the price effect. Like if price increased dramatically, EMA would notify whether could be a good time to sell. (Because high deviation between MA and price suggest price increase too fast) 4. Length of line: set length of line for you need 5. Percentage change: how much percentage change is considered a significant change? 5%? or 10%? In which case should it count toward the final indicator? Adjust percentage change needed, smaller for minutes chart (less than 10) higher for hours chart (10-20), even higher for day chart Buy/Sell method: 1. When green dot appears, wait after price start to get close to moving average to find the low point and buy. 2. Reverse for red dot.
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xjtlumedia tarafından
5
True Momentum OscillatorThe True Momentum Oscillator (TMO) calculates the delta of the price using the open and close. We have taken the true momentum oscillator a step further and have added the momentum of the main signal (TMO) and the smooth signal line. We believe this helps give a clearer picture of price momentum and helps verify crossovers of the TMO and the smooth signal line. The momentum lines can also help confirm a divergence of the TMO. We have also added multiple moving average options so the user can customize the TMO to suit their needs. TMO- Green when above Smooth Signal Line, red when below Smooth Signal Line Smooth Signal- Gray Line Histogram- TMO-Smooth Signal TMO Momentum- Orange line Smooth Signal Momentum- Yellow line Overbought/Oversold regions- Gray highlighted boundaries The TMO has defined overbought and oversold regions where either a crossover signal or divergence in the oscillator itself can be taken as a signal. Similar to the MACD, a crossover of the zero line by the TMO can also be utilized as a signal.
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LeafAlgo tarafından
9
Divergence Strength OscillatorDetects divergence before it has formed a valid divergent pivot, across multiple indicators. After publishing my Strength of Divergence Across Multiple Indicators script, it seemed there were a lot of people who wanted to see the divergence signals before the divergent pivots were actually confirmed. Everyone complains about indicators repainting, yet in the next breath they complain about not wanting to wait for a signal to be confirmed before it appears on their chart! No matter how many times you ask, you can't have your cake and eat it too. While this isn't exactly cake, it's as close as you're gonna get. This oscillator will calculate the strength of divergence as it forms on any bar that could potentially be a pivot point (e.g. for a pivot low, the preceding bars must be higher than it) and track the net (bullish - bearish) value. For example: PLEASE NOTE that this is not intended to be a "Buy" or "Sell" signal, and it would be foolish to use it as such. The purpose of this script is to show you potential divergences as early as possible, so that you have more time to plan and evaluate confluent signals, etc. The Divergence Strength Calculation: The total divergence strength value is the sum of the divergence strengths of all indicators for which divergence was detected at a given bar. Each indicator's individual divergence strength is comprised of two basic components: (1) |ΔPrice| - the magnitude of the change in price over the divergence period (pivot-to-pivot), and (2) |ΔIndicator| - the magnitude of the change in indicator value over the divergence period. Because different indicators' scales and volatility can vary greatly, the Δ values are expressed in terms of standard deviation to ensure that the values are meaningful and equitable across all indicators and assets/instruments/currency pairs, etc: |ΔIndicator| = |indicator_value_1 - indicator_value_2| / 2 * StDev(indicator_series,100) Based on work for my Strength of Divergence Across Multiple Indicators script:
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reees tarafından
8
Extended Recursive Bands StrategyThe original indicator was created by alexgrover . All credit goes to alexgrover for creating the indicator that this strategy uses. This strategy was posted because there were multiple requests for it, and no strategy based on this indicator exists yet. The Recursive Bands Indicator, an indicator specially created to be extremely efficient, I think you already know that calculation time is extra important in algorithmic trading, and this is the principal motivation for the creation of the proposed indicator. Originally described in Alex's paper "Pierrefeu, Alex (2019): Recursive Bands - A New Indicator For Technical Analysis", the indicator framework has been widely used in his previous uploaded indicators, however it would have been a shame to not upload it, however user experience being a major concern for me, I decided to add extra options, which explain the term "extended". The Indicator The indicator displays one upper and one lower band, every common usages applied to bands indicators such as support/resistance , breakout, trailing stop, etc, can also be applied to this one. Length controls how reactive the bands are, higher values will make the bands cross the price less often. In order to provide more flexibility for the user alexgrover added the option to use various methods for the calculation of the indicator, therefore the indicator can use the average true range , standard deviation, average high-low range, and one totally exclusive method specially designed for this indicator. Added logic: We have implemented a logic that checks whether the bands have been following in the same direction for a set amount of bars. This logic must be true before it can enter trades. This is completely new code that was written by us entirely, and it makes a huge difference on strategy performance. Strategy Long conditions: 1 — Price low is below the the lower band. 2 — The lower band keeps increasing in value until the 'lookback' setting amount of bars is reached. Strategy Short conditions: 1 — Price high is above the upper band. 2 — The upper band keeps decreasing in value until the 'lookback' setting amount of bars is reached. Strategy Properties: We have set a default commission of 0.06% because these are Bybit's fees. The strategy uses an order size of 10% of equity, since drawdown is very low like this. We also use a 10 tick slippage to keep results realistic and account for this. All other settings were left as default apart from initial capital, just to decrease the size of the numbers.
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Adulari tarafından
4
Outliers Detector with N-Sigma Confidence Intervals (TG fork)Display outliers in either value change, volume or volume change that significantly deviate from the past. This uses the standard deviation calculation and the n-sigmas statistical rule of significance, with 2-sigma (a value of 2) signifying that the observed value is stronger than 95% of past values, and 3-sigma 98.5% of past values, and so on for higher sigma values. Outliers in price action or in volume can indicate a strong support for the move, and hence potentially more moves in the same direction in the future. Inversely, an insignificant move is less likely to be supported. And of course the stronger, the more support. This indicator also doubles as a standard volume indicator if volume is selected as the source, but with the option of highlighting outliers. Bars below significance can be uncolored (gray) to unclutter the visuals. Differently to almost all other similar indicators, the background highlighting is dynamical, so that all values will be highlighted differently, not just 2-sigma or 3-sigma, but also 4-sigma, 5-sigma, etc, with a different value of transparency. The dynamical transparency value can be calculated in two ways: either statically proportionally to the n-sigma but capped at 10-sigma, or either as a ratio relative to the highest observed sigma value over the defined lookback period (default: 300). If you like this indicator, which is an extension of previously published indicators, please give some love to the original authors: * tvjvzl : * vnhilton : This extension, authored by Tartigradia, extends tvjvzl's indi, implements vnhilton's idea of highlighting the background, and go further by adding dynamical background highlighting for any value of sigma, add support for volume and volume change (VolumeDiff) as inputs, add option to uncolor insignificant bars, allow plotting in both directions and more.
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tartigradia tarafından
1
MA MomentumThis simple script takes two ma's sums them and takes the the difference between the current and previous data points. This gives a lovely smoothed momentum indicator. The way it works is if its green its good and if its red its bad. In other words, I take the smooth signal as a filter for the momentum. You can also spot divergences between the indicator and the price to make decisions. Some features include extra smoothing and adjustable ma's. I hope you find this script useful! Thank you.
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The_Peaceful_Lizard tarafından