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TUF_LOGICThe TUF_LOGIC library incorporates three-valued logic (also known as trilean logic) into Pine Script, enabling the representation of states beyond the binary True and False to include an 'Uncertain' state. This addition is particularly apt for financial market contexts where information may not always be black or white, accommodating scenarios of partial or ambiguous data. Key Features: Trilean Data Type: Defines a tri type, facilitating the representation of True (1), Uncertain (0), and False (-1) states, thus accommodating a more nuanced approach to logical evaluation. Validation and Conversion: Includes methods like validate, to ensure trilean variables conform to expected states, and to_bool, for converting trilean to boolean values, enhancing interoperability with binary logic systems. Core Logical Operations: Extends traditional logical operators (AND, OR, NOT, XOR, EQUALITY) to work within the trilean domain, enabling complex conditionals that reflect real-world uncertainties. Specialized Logical Operations: Implication Operators: Features IMP_K (Kleene's), IMP_L (Łukasiewicz's), and IMP_RM3, offering varied approaches to logical implication within the trilean framework. Possibility, Necessity, and Contingency Operators: Implements MA ("it is possible that..."), LA ("it is necessary that..."), and IA ("it is unknown/contingent that..."), derived from Tarski-Łukasiewicz's modal logic attempts, enriching the library with modal logic capabilities. Unanimity Functions: The UNANIMOUS operator assesses complete agreement among trilean values, useful for scenarios requiring consensus or uniformity across multiple indicators or conditions. This library is developed to support scenarios in financial trading and analysis where decisions might hinge on more than binary outcomes. By incorporating modal logic aspects and providing a framework for handling uncertainty through the MA, LA, and IA operations, TUF_LOGIC bridges the gap between classical binary logic and the realities of uncertain information, making it a valuable tool for developing sophisticated trading strategies and analytical models. Library "TUF_LOGIC" 3VL Implementation (TUF stands for True, Uncertain, False.) method validate(self)   Ensures a valid trilean variable. This works by clamping the variable to the range associated with the trilean type.   Namespace types: tri   Parameters:      self (tri)   Returns: Validated trilean object. method to_bool(self)   Converts a trilean object into a boolean object. True -> True, Uncertain -> na, False -> False.   Namespace types: tri   Parameters:      self (tri)   Returns: A boolean variable. method NOT(self)   Negates the trilean object. True -> False, Uncertain -> Uncertain, False -> True   Namespace types: tri   Parameters:      self (tri)   Returns: Negated trilean object. method AND(self, comparator)   Logical AND operation for trilean objects.   Namespace types: tri   Parameters:      self (tri) : The first trilean object.      comparator (tri) : The second trilean object to compare with.   Returns: `tri` Result of the AND operation as a trilean object. method OR(self, comparator)   Logical OR operation for trilean objects.   Namespace types: tri   Parameters:      self (tri) : The first trilean object.      comparator (tri) : The second trilean object to compare with.   Returns: `tri` Result of the OR operation as a trilean object. method EQUALITY(self, comparator)   Logical EQUALITY operation for trilean objects.   Namespace types: tri   Parameters:      self (tri) : The first trilean object.      comparator (tri) : The second trilean object to compare with.   Returns: `tri` Result of the EQUALITY operation as a trilean object, True if both are equal, False otherwise. method XOR(self, comparator)   Logical XOR (Exclusive OR) operation for trilean objects.   Namespace types: tri   Parameters:      self (tri) : The first trilean object.      comparator (tri) : The second trilean object to compare with.   Returns: `tri` Result of the XOR operation as a trilean object. method IMP_K(self, comparator)   Material implication using Kleene's logic for trilean objects.   Namespace types: tri   Parameters:      self (tri) : The antecedent trilean object.      comparator (tri) : The consequent trilean object.   Returns: `tri` Result of the implication operation as a trilean object. method IMP_L(self, comparator)   Logical implication using Łukasiewicz's logic for trilean objects.   Namespace types: tri   Parameters:      self (tri) : The antecedent trilean object.      comparator (tri) : The consequent trilean object.   Returns: `tri` Result of the implication operation as a trilean object. method IMP_RM3(self, comparator)   Logical implication using RM3 logic for trilean objects.   Namespace types: tri   Parameters:      self (tri) : The antecedent trilean object.      comparator (tri) : The consequent trilean object.   Returns: `tri` Result of the RM3 implication as a trilean object. method MA(self)   Evaluates to True if the trilean object is either True or Uncertain, False otherwise.   Namespace types: tri   Parameters:      self (tri) : The trilean object to evaluate.   Returns: `tri` Result of the operation as a trilean object. method LA(self)   Evaluates to True if the trilean object is True, False otherwise.   Namespace types: tri   Parameters:      self (tri) : The trilean object to evaluate.   Returns: `tri` Result of the operation as a trilean object. method IA(self)   Evaluates to True if the trilean object is Uncertain, False otherwise.   Namespace types: tri   Parameters:      self (tri) : The trilean object to evaluate.   Returns: `tri` Result of the operation as a trilean object. UNANIMOUS(self, comparator)   Evaluates the unanimity between two trilean values.   Parameters:      self (tri) : The first trilean value.      comparator (tri) : The second trilean value.   Returns: `tri` Returns True if both values are True, False if both are False, and Uncertain otherwise. method UNANIMOUS(self)   Evaluates the unanimity among an array of trilean values.   Namespace types: array   Parameters:      self (array) : The array of trilean values.   Returns: `tri` Returns True if all values are True, False if all are False, and Uncertain otherwise. tri   Three Value Logic (T.U.F.), or trilean. Can be True (1), Uncertain (0), or False (-1).   Fields:      v (series int) : Value of the trilean variable. Can be True (1), Uncertain (0), or False (-1).
Perpustakaan Pine Script™
oleh The_Peaceful_Lizard
4
SML SuiteIntroducing the "SML Suite" Indicator The "SML Suite" is a powerful and easy-to-use trading indicator designed to help traders make informed decisions in the world of financial markets. Whether you're a seasoned trader or a novice, this indicator is your trusty sidekick for evaluating market trends. Key Features: Three Moving Averages: The indicator employs three different moving averages, each with a distinct length, allowing you to adapt to various market conditions. Customizable Parameters: You can easily customize the moving average lengths and source data to tailor the indicator to your specific trading strategy. Standard Deviation Multiplier: Adjust the standard deviation multiplier to fine-tune the indicator's sensitivity to market fluctuations. Binary Results: The indicator provides clear binary signals (1 or -1) based on whether the current price is above or below certain bands. This simplifies your decision-making process. SML Calculation: The SML (Short, Medium, Long) calculation is a smart combination of the binary results, offering you an overall sentiment about the market. Color-Coded Visualization: Visualize market sentiment with color-coded bars, making it easy to spot trends at a glance. Interactive Table: A table is displayed on your chart, giving you a quick overview of the binary results and the overall SML sentiment. With the "SML Suite" indicator, you don't need to be a coding expert to harness the power of technical analysis. Stay ahead of the game and enhance your trading strategy with this user-friendly tool. Make your trading decisions with confidence and clarity, backed by the insights provided by the "SML Suite" indicator.
Penunjuk Pine Script™
oleh kikfraben
PhiSmoother Moving Average Ribbon [ChartPrime]DSP FILTRATION PRIMER: DSP (Digital Signal Processing) filtration plays a critical role with financial indication analysis, involving the application of digital filters to extract actionable insights from data. Its primary trading purpose is to distinguish and isolate relevant signals separate from market noise, allowing traders to enhance focus on underlying trends and patterns. By smoothing out price data, DSP filters aid with trend detection, facilitating the formulation of more effective trading techniques. Additionally, DSP filtration can play an impactful role with detecting support and resistance levels within financial movements. By filtering out noise and emphasizing significant price movements, identifying key levels for entry and exit points become more apparent. Furthermore, DSP methods are instrumental in measuring market volatility, enabling traders to assess volatility levels with improved accuracy. In summary, DSP filtration techniques are versatile tools for traders and analysts, enhancing decision-making processes in financial markets. By mitigating noise and highlighting relevant signals, DSP filtration improves the overall quality of trading analysis, ultimately leading to better conclusions for market participants. APPLYING FIR FILTERS: FIR (Finite Impulse Response) filters are indispensable tools in the realm of financial analysis, particularly for trend identification and characterization within market data. These filters effectively smooth out price fluctuations and noise, enabling traders to discern underlying trends with greater fidelity. By applying FIR filters to price data, robust trading strategies can be developed with grounded trend-following principles, enhancing their ability to capitalize on market movements. Moreover, FIR filter applications extend into wide-ranging utility within various fields, one being vital for informed decision-making in analysis. These filters help identify critical price levels where assets may tend to stall or reverse direction, providing traders with valuable insights to aid with identification of optimal entry and exit points within their indicator arsenal. FIRs are undoubtedly a cornerstone to modern trading innovation. Additionally, FIR filters aid in volatility measurement and analysis, allowing traders to gauge market volatility accurately and adjust their risk management approaches accordingly. By incorporating FIR filters into their analytical arsenal, traders can improve the quality of their decision-making processes and achieve better trading outcomes when contending with highly dynamic market conditions. INTRODUCTORY DEBUT: ChartPrime's " PhiSmoother Moving Average Ribbon " indicator aims to mark a significant advancement in technical analysis methodology by removing unwanted fluctuations and disturbances while minimizing phase disturbance and lag. This indicator introduces PhiSmoother, a powerful FIR filter in it's own right comparable to Ehlers' SuperSmoother. PhiSmoother leverages a custom tailored FIR filter to smooth out price fluctuations by mitigating aliasing noise problematic to identification of underlying trends with accuracy. With adjustable parameters such as phase control, traders can fine-tune the indicator to suit their specific analytical needs, providing a flexible and customizable solution. Mathemagically, PhiSmoother incorporates various color coding preferences, enabling traders to visualize trends more effectively on a volatile landscape. Whether utilizing progression, chameleon, or binary color schemes, you can more fluidly interpret market dynamics and make informed visual decisions regarding entry and exit points based on color-coded plotting. The indicator's alert system further enhances its utility by providing notifications of specifically chosen filter crossings. Traders can customize alert modes and messages while ensuring they stay informed about potential opportunities aligned with their trading style. Overall, the "PhiSmoother Moving Average Ribbon" visually stands out as a revolutionary mechanism for technical analysis, offering traders a comprehensive solution for trend identification, visualization, and alerting within financial markets to achieve advantageous outcomes. NOTEWORTHY SETTINGS FEATURES: Price Source Selection - The indicator offers flexibility in choosing the price source for analysis. Traders can select from multiple options. Phase Control Parameter - One of the notable standout features of this indicator is the phase control parameter. Traders can fine-tune the phase or lag of the indicator to adapt it to different market conditions or timeframes. This feature enables optimization of the indicator's responsiveness to price movements and align it with their specific trading tactics. Coloring Preferences - Another magical setting is the coloring features, one being "Chameleon Color Magic". Traders can customize the color scheme of the indicator based on their visual preferences or to improve interpretation. The indicator offers options such as progression, chameleon, or binary color schemes, all having versatility to dynamically visualize market trends and patterns. Two colors may be specifically chosen to reduce overlay indicator interference while also contrasting for your visual acuity. Alert Controls - The indicator provides diverse alert controls to manage alerts for specific market events, depending on their trading preferences. Alertable Crossings: Receive an alert based on selectable predefined crossovers between moving average neighbors Customizable Alert Messages: Traders can personalize alert messages with preferred information details Alert Frequency Control: The frequency of alerts is adjustable for maximum control of timely notifications
Penunjuk Pine Script™
oleh ChartPrime
11
Pattern Probability with EMA FilterThe provided code is a custom indicator that identifies specific price patterns on a chart and uses a 14-period Exponential Moving Average (EMA) as a filter to display only certain patterns based on the EMA trend direction. These code identifies patterns display them as upward and downward arrows indicates potential price corrections and short term trend reversals in the direction of the arrow. Use with indicators such as RSI that inform overbought and oversold condition to add reliability and confluence. Code Explanation: The code first calculates three values 'a', 'b', and 'c' based on the difference between the current high, low, and close prices, respectively, and their respective previous moving average values. Binary values are then assigned to 'a', 'b', and 'c', where each value is set to 1 if it's greater than 0, and 0 otherwise. The 'pattern_type' is determined based on the binary values of 'a', 'b', and 'c', combining them into a single number (ranging from 0 to 7) to represent different price patterns. The code calculates a 14-period Exponential Moving Average (EMA) of the closing price. It determines the EMA trend direction by comparing the current EMA value with the previous EMA value, setting 'ema_going_up' to true if the EMA is going up and 'ema_going_down' to true if the EMA is going down. The indicator then plots arrows on the chart for specific pattern_type values while considering the EMA trend direction as a filter. It displays different colored arrows for each pattern_type. The 14-period EMA is also plotted on the chart, with the color changing to green when the EMA is going up and red when the EMA is going down. Concept: pattern_type = 0: H- L- C- (Downward trend continuation) - Indicates a continuation of the downward trend, suggesting further losses ahead. pattern_type = 1: H- L- C+ (Likely trend change: Downwards to upwards) - Implies the upward trend or price movement change. pattern_type = 2: H- L+ C- (Likely trend change: Upwards to downwards) - Suggests a potential reversal from an uptrend to a downtrend, but further confirmation is needed. pattern_type = 3: H- L+ C+ (Trend uncertainty: Potential reversal) - Indicates uncertainty in the trend, potential for a reversal, but further price action confirmation is required. pattern_type = 4: H+ L- C- (Downward trend continuation with lower volatility) - Suggests the downward trend may continue, but with reduced price swings or lower volatility. pattern_type = 5: H+ L- C+ (Likely trend change: Downwards to upwards) - Implies a potential reversal from a downtrend to an uptrend, with buying interest increasing. (pattern_type = 6: H+ L+ C- (Likely trend change: Upwards to downwards) - Suggests a potential reversal from an uptrend to a downtrend, with selling pressure increasing. pattern_type = 7: H+ L+ C+ (Upward trend continuation) - Indicates a continuation of the upward trend, suggesting further gains ahead. In the US market, when analyzing a 15-minute chart, we observe the following proportions of the different pattern_type occurrences: The code will plot the low frequency patterns (P1 - P6) P0 (H- L- C-): 37.60% P1 (H- L- C+): 3.60% P2 (H- L+ C-): 3.10% P3 (H- L+ C+): 3.40% P4 (H+ L- C-): 2.90% P5 (H+ L- C+): 2.70% P6 (H+ L+ C-): 3.50% P7 (H+ L+ C+): 43.50% When analyzing higher time frames, such as daily or weekly charts, the occurrence of these patterns is expected to be even lower, but they may carry more significant implications due to their rarity and potential impact on longer-term trends.
Penunjuk Pine Script™
oleh federalTacos5392b
TMA Legacy - "The Arty"This is a script based on the original "The Arty" indicator by PhoenixBinary. The Phoenix Binary community and the TMA community built this version to be public code for the community for further use and revision after the reported passing of Phoenix Binary (The community extends our condolences to Phoenix's family). The intended uses are the same as the original but some calculations are different and may not act or signal the same as the original. Description of the indicator from original posting. This indicator was inspired by Arty and Christy .
Penunjuk Pine Script™
oleh Hotchachachaaa
9
TMA-LegacyThis is a script based on the original TMA- RSI Divergence indicator by PhoenixBinary. The Phoenix Binary community and the TMA community built this version to be public code for the community for further use and revision after the reported passing of Phoenix Binary (The community extends our condolences to Phoenix's family. The intended uses are the same as the original but some calculations are different and may not act or signal the same as the original. Description of the indicator from original posting. This indicator was inspired by Arty and Christy . █ COMPONENTS Here is a brief overview of the indicator from the original posting: 1 — RSI Divergence Arty uses the RSI divergence as a tool to find entry points and possible reversals. He doesn't use the traditional overbought/oversold. He uses a 50 line. This indicator includes a 50 line and a floating 50 line. The floating 50 line is a multi-timeframe smoothed moving average . Price is not linear, therefore, your 50 line shouldn't be either. The RSI line is using a dynamic color algo that shows current control of the market as well as possible turning points in the market. 2 — Smoothed RSI Divergence The Smoothed RSI Divergence is a slower RSI with different calculations to smooth out the RSI line. This gives a different perspective of price action and more of a long term perspective of the trend. When crosses of the floating 50 line up with the traditional RSI crossing floating 50. 3 — Momentum Divergence This one will take a little bit of time to master. But, once you master this, and combined with the other two, damn these entries get downright lethal!
Penunjuk Pine Script™
oleh Hotchachachaaa
11
Machine Learning: Perceptron-based strategyPerceptron-based strategy Description: The Learning Perceptron is the simplest possible artificial neural network (ANN), consisting of just a single neuron and capable of learning a certain class of binary classification problems. The idea behind ANNs is that by selecting good values for the weight parameters (and the bias), the ANN can model the relationships between the inputs and some target. Generally, ANN neurons receive a number of inputs, weight each of those inputs, sum the weights, and then transform that sum using a special function called an activation function. The output of that activation function is then either used as the prediction (in a single neuron model) or is combined with the outputs of other neurons for further use in more complex models. The purpose of the activation function is to take the input signal (that’s the weighted sum of the inputs and the bias) and turn it into an output signal. Think of this activation function as firing (activating) the neuron when it returns 1, and doing nothing when it returns 0. This sort of computation is accomplished with a function called step function: f(z) = {1 if z > 0 else 0}. This function then transforms any weighted sum of the inputs and converts it into a binary output (either 1 or 0). The trick to making this useful is finding (learning) a set of weights that lead to good predictions using this activation function. Training our perceptron is simply a matter of initializing the weights to zero (or random value) and then implementing the perceptron learning rule, which just updates the weights based on the error of each observation with the current weights. This has the effect of moving the classifier’s decision boundary in the direction that would have helped it classify the last observation correctly. This is achieved via a for loop which iterates over each observation, making a prediction of each observation, calculating the error of that prediction and then updating the weights accordingly. In this way, weights are gradually updated until they converge. Each sweep through the training data is called an epoch. In this script the perceptron is retrained on each new bar trying to classify this bar by drawing the moving average curve above or below the bar. This script was tested with BTCUSD, USDJPY, and EURUSD. Note: TradingViews's playback feature helps to see this strategy in action. Warning: Signals ARE repainting. Style tags: Trend Following, Trend Analysis Asset class: Equities, Futures, ETFs, Currencies and Commodities Dataset: FX Minutes/Hours+/Days
Penunjuk Pine Script™
oleh capissimo
33
Relative Falling three Methods IndicatorAbstract This script measure the related speed between rising and falling. This script can replace binary Falling Three Methods detector and, report continuous value and estimate potential trend direction. My suggestion of using this script is combining it with trading emotion. Introduction Falling Three Methods (F3M) is a candlestick pattern. Many trading courses say traders can regard it as predicting falling will continue. However, it is not easy to see perfect Falling Three Methods pattern from charts. Therefore, we need an alternative method to measure it. We can use the observation that falling is faster than rising during those time. When falling is faster than rising, some long ( buy , call , higher , upper ) position owners may worry the price will fall very much suddenly. When rising is faster than falling, some traders may worry they may miss buy opportunities. Computing Related Falling Three Methods Indicator (1) The value of rising and falling In this script, open price is replaced with previous close price. If the previous price is equal to the close price, than both rising and falling are equal to high-low. If the previous price is lower than the close price, than the falling value becomes smaller, high-close+previous-low. If the previous price is higher than the close price, than the rising value becomes smaller, high-previous+close-low. (2) Area of value (aov) Area of value is equal to highest-lowest. The previous close price is included. (3) Compute weight and filter noise We need a threshold for the noise filter. The default setting is aov/length, where length means how many days are counted. When a rising or falling value <= threshold, it is not counted. When a rising or falling value > threshold, the counted value = original value - threshold and its weight = min ( counted value , threshold ) (4) compute speed Rising speed = sum ( counted rising value ) / sum ( rising weight ) Falling speed = sum ( counted falling value ) / sum ( falling weight ) (5) Final result Final result = Rising speed / ( Rising speed + Falling speed ) * 100 - 50 I move the middle level to 0 because 0 axis is always visible unless you cannot see negative values or you cannot see positive values. Parameters Length : how many days are counted. The default value is 16 just because 16=4*4, using binary characteristic. Multi : the multiplier of noise threshold. Threshold applied = default threshold * multi src : current not used Conclusion Related Falling Three Methods Indicator can measure the related speed between rising and falling. I hope this indicator can help us to evaluate the possibility of trend continue or reversal and potential breakout direction. After all, we care how trading emotion control the price movement and therefore we can take advantage to it. Reference How to trade with Falling Three Methods pattern How to trade with Related Strength Indicator
Penunjuk Pine Script™
oleh clocks156t174
4 in 1 Stoch Indicators as used by HG (Stoch, SRSIx2, DMIStoch)By using this indicator you can better view the Stoch indicators used by this strategy which are: - Stochastic (14,3,3) - Stochastic RSI (14,14,3,3) - Stochastic RSI (6,6,3,3) - DMI Stochastic This is best used alongside: - Evan Cabral binary strategy 2 - Binary with Temito The analisis is: - When all lines in the indicator are above or below the overbough/oversold lines - When the bollinger bands are broken - A support or resistance is reached That means a change of Trend.
Penunjuk Pine Script™
oleh AngelRChaconM
1
Edge-Preserving FilterIntroduction Edge-preserving smoothing is often used in image processing in order to preserve edge information while filtering the remaining signal. I introduce two concepts in this indicator, edge preservation and an adaptive cumulative average allowing for fast edge-signal transition with period increase over time. This filter have nothing to do with classic filters for image processing, those filters use kernels convolution and are most of the time in a spatial domain. Edge Detection Method We want to minimize smoothing when an edge is detected, so our first goal is to detect an edge. An edge will be considered as being a peak or a valley, if you recall there is one of my indicator who aim to detect peaks and valley (reference at the bottom of the post) , since this estimation return binary outputs we will use it to tell our filter when to stop filtering. Filtering Increase By Using Multi Steps Cumulative Average The edge detection is a binary output, using a exponential smoothing could be possible and certainly more efficient but i wanted instead to try using a cumulative average approach because it smooth more and is a bit more original to use an adaptive architecture using something else than exponential averaging. A cumulative average is defined as the sum of the price and the previous value of the cumulative average and then this result is divided by n with n = number of data points. You could say that a cumulative average is a moving average with a linear increasing period. So lets call CMA our cumulative average and n our divisor. When an edge is detected CMA = close price and n = 1 , else n is equal to previous n+1 and the CMA act as a normal cumulative average by summing its previous values with the price and dividing the sum by n until a new edge is detected, so there is a "no filtering state" and a "filtering state" with linear period increase transition, this is why its multi-steps. The Filter The filter have two parameters, a length parameter and a smooth parameter, length refer to the edge detection sensitivity, small values will detect short terms edges while higher values will detect more long terms edges. Smooth is directly related to the edge detection method, high values of smooth can avoid the detection of some edges. smooth = 200 smooth = 50 smooth = 3 Conclusion Preserving the price edges can be useful when it come to allow for reactivity during important price points, such filter can help with moving average crossover methods or can be used as a source for other indicators making those directly dependent of the edge detection. Rsi with a period of 200 and our filter as source, will cross triggers line when an edge is detected Feel free to share suggestions ! Thanks for reading ! References Peak/Valley estimator used for the detection of edges in price.
Penunjuk Pine Script™
oleh alexgrover
18
Heiken Ashi zero lag EMA v1.1 by JustUncleLI originally wrote this script earlier this year for my own use. This released version is an updated version of my original idea based on more recent script ideas. As always with my Alert scripts please do not trade the CALL/PUT indicators blindly, always analyse each position carefully. Always test indicator in DEMO mode first to see if it profitable for your trading style. DESCRIPTION: This Alert indicator utilizes the Heiken Ashi with non lag EMA was a scalping and intraday trading system that has been adapted also for trading with binary options high/low. There is also included filtering on MACD direction and trend direction as indicated by two MA: smoothed MA(11) and EMA(89). The the Heiken Ashi candles are great as price action trending indicator, they shows smooth strong and clear price fluctuations. Financial Markets: any. Optimsed settings for 1 min, 5 min and 15 min Time Frame; Expiry time for Binary options High/Low 3-6 candles. Indicators used in calculations: - Exponential moving average, period 89 - Smoothed moving average, period 11 - Non lag EMA, period 20 - MACD 2 colour (13,26,9) Generate Alerts use the following Trading Rules Heiken Ashi with non lag dot Trade only in direction of the trend. UP trend moving average 11 period is above Exponential moving average 89 period, Doun trend moving average 11 period is below Exponential moving average 89 period, CALL Arrow appears when: Trend UP SMA11>EMA89 (optionally disabled), Non lag MA blue dot and blue background. Heike ashi green color. MACD 2 Colour histogram green bars (optional disabled). PUT Arrow appears when: Trend UP SMA11<EMA89 (optionally disabled), Heike ashi red color. Non lag MA red dot and red background. MACD 2 colour histogram red bars (optionally disabled). HINTS: - Good positions occur when MACD crosses the Zero line. - Switch between Heikin Ashi and Normal candles as part of your analysis of the price action. - Large Heikin Ashi candles with small wicks in direction of trend are good strong trends.
Penunjuk Pine Script™
oleh JustUncleL
31
MLActivationFunctionsLibrary "MLActivationFunctions" Activation functions for Neural networks. binary_step(value) Basic threshold output classifier to activate/deactivate neuron.   Parameters:      value : float, value to process.   Returns: float linear(value) Input is the same as output.   Parameters:      value : float, value to process.   Returns: float sigmoid(value) Sigmoid or logistic function.   Parameters:      value : float, value to process.   Returns: float sigmoid_derivative(value) Derivative of sigmoid function.   Parameters:      value : float, value to process.   Returns: float tanh(value) Hyperbolic tangent function.   Parameters:      value : float, value to process.   Returns: float tanh_derivative(value) Hyperbolic tangent function derivative.   Parameters:      value : float, value to process.   Returns: float relu(value) Rectified linear unit (RELU) function.   Parameters:      value : float, value to process.   Returns: float relu_derivative(value) RELU function derivative.   Parameters:      value : float, value to process.   Returns: float leaky_relu(value) Leaky RELU function.   Parameters:      value : float, value to process.   Returns: float leaky_relu_derivative(value) Leaky RELU function derivative.   Parameters:      value : float, value to process.   Returns: float relu6(value) RELU-6 function.   Parameters:      value : float, value to process.   Returns: float softmax(value) Softmax function.   Parameters:      value : float array, values to process.   Returns: float softplus(value) Softplus function.   Parameters:      value : float, value to process.   Returns: float softsign(value) Softsign function.   Parameters:      value : float, value to process.   Returns: float elu(value, alpha) Exponential Linear Unit (ELU) function.   Parameters:      value : float, value to process.      alpha : float, default=1.0, predefined constant, controls the value to which an ELU saturates for negative net inputs. .   Returns: float selu(value, alpha, scale) Scaled Exponential Linear Unit (SELU) function.   Parameters:      value : float, value to process.      alpha : float, default=1.67326324, predefined constant, controls the value to which an SELU saturates for negative net inputs. .      scale : float, default=1.05070098, predefined constant.   Returns: float exponential(value) Pointer to math.exp() function.   Parameters:      value : float, value to process.   Returns: float function(name, value, alpha, scale) Activation function.   Parameters:      name : string, name of activation function.      value : float, value to process.      alpha : float, default=na, if required.      scale : float, default=na, if required.   Returns: float derivative(name, value, alpha, scale) Derivative Activation function.   Parameters:      name : string, name of activation function.      value : float, value to process.      alpha : float, default=na, if required.      scale : float, default=na, if required.   Returns: float
Perpustakaan Pine Script™
oleh RicardoSantos
2
Stochastic with Outlier Labels/MTFTL;DR This indicator is an update to a simple stochastic ('Stoch_MTF' by binarytrader666) that provides a novel outlier highlighting feature Improvements on stochastic: 1. Novel outlier highlighting that points out crosses that are the Nth consecutive cross or greater. 2. Allowing for multiple timeframes to be shown on the same chart 3. Highlighting/Labelling crosses and providing labels for alerts A cross of the stochastics in the high or low zones establishes a trend. Successive crosses in the same region seem to indicate a continuation of that trend. The outlier functionality here provides a signal for when X number of crosses have been in the same trend, signaling further strength of that signal. I also provided the necessary code for converting this to a strategy if you so wish at the bottom.
Penunjuk Pine Script™
oleh on2valhalla
1
Linear Regression Trend Channel with Entries & AlertsPlease Use this Indicator If you understand the risk posed by linear regression trend channel Features Provides trend channel (best value for period is 40 on 5 minute timeframe Provides BUY/SELL entries based on current channel Provides custom color for channel Best used with MattyPips strategy indicators Risks : Please note, this script is the likes of Bollinger bands and poses a risk of falling in a trend range. Entries may keep running on the same direction while the market is moving.
Penunjuk Pine Script™
oleh MrTuanDoan
23