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.
Cerca negli script per "binary"
Kioseff Trading - AI-Optimized Supertrend
AI-Optimized Supertrend
Introducing AI-Optimized Supertrend: a streamlined solution for traders of any skill level seeking to rapidly test and optimize Supertrend. Capable of analyzing thousands of strategies, this tool cuts through the complexity to identify the most profitable, reliable, or efficient approaches.
Paired with TradingView's native backtesting capabilities, the AI-Optimized Supertrend learns from historical performance data. Set up is easy for all skill levels, and it makes fine-tuning trading alerts and Supertrend straightforward.
Features
Rapid Supertrend Strategy Testing : Quickly evaluate thousands of Supertrend strategies to find the most effective ones.
AI-Assisted Optimization : Leverage AI recommendations to fine-tune strategies for superior results.
Multi-Objective Optimization : Prioritize Supertrend based on your preference for the highest win rate, maximum profit, or efficiency.
Comprehensive Analytics : The strategy script provides an array of statistics such as profit factor, PnL, win rate, trade counts, max drawdown, and an equity curve to gauge performance accurately.
Alerts Setup : Conveniently set up alerts to be notified about critical trade signals or changes in performance metrics.
Versatile Stop Strategies : Experiment with profit targets, trailing stops, and fixed stop losses.
Binary Supertrend Exploration : Test binary Supertrend strategies.
Limit Orders : Analyze the impact of limit orders on your trading strategy.
Integration with External Indicators : Enhance strategy refinement by incorporating custom or publicly available indicators from TradingView into the optimization process.
Key Settings
The image above shows explanations for a list of key settings for the optimizer.
Set the Factor Range Limits : The AI suggests optimal upper and lower limits for the Factor range, defining the sensitivity of the Supertrend to price fluctuations. A wider range tests a greater variety, while a narrower range focuses on fine-tuning.
Adjust the ATR Range : Use the AI's recommendations to establish the upper and lower bounds for the Average True Range (ATR), which influences the Supertrend's volatility threshold.
ATR Flip : This option lets you interchange the order of ATR and Factor values to quicky test different sequences, giving you the flexibility to explore various combinations and their impact on the Supertrend indicator's performance.
Strategies Evaluated : Adjust this setting to determine how many Supertrend strategies you want to assess and compare.
Enable AI Mode : Turn this feature on to allow the AI to determine and employ the optimal Supertrend strategy with the desired performance metric, such as the highest win rate or maximum profitability.
Target Metric : Adjust this to direct the AI towards optimizing for maximum profit, top win rates, or the most efficient profits.
AI Mode Aggressiveness : Set how assertively the AI pursues the chosen performance goal, such as highest profit or win rate.
Strategy Direction : Choose to focus the AI's testing and optimization on either long or short Supertrend strategies.
Stop Loss Type : Specify the stop loss approach for optimization—fixed value, a trailing stop, or Supertrend direction changes.
Limit Order : Decide if you want to execute trades using limit orders for setting your profit targets, stop losses, or apply them to both.
Profit Target : Define your desired profit level when using either a fixed stop loss or a trailing stop.
Stop Loss : Define your desired stop loss when using either a fixed stop loss or a trailing stop.
How to: Find the best Supertrend for trading
It's important to remember that merely having the AI-Optimized Supertrend on your chart doesn't automatically provide you with the best strategy. You need to follow the AI's guidance through an iterative process to discover the optimal Supertrend settings and strategy.
Optimizing Supertrend involves adjusting two key parameters: the Factor and the Average True Range (ATR). These parameters significantly influence the Supertrend indicator's sensitivity and responsiveness to price movements.
Factor : This parameter multiplies the ATR to determine the distance of the Supertrend line from the price. Higher values will create a wider band, potentially leading to fewer trade signals, while lower values create a narrower band, which may result in more signals but also more noise.
ATR (Average True Range) : ATR measures market volatility. By using the ATR, the Supertrend adapts to changing market volatility; a higher ATR value means a more volatile market, so the Supertrend adjusts accordingly.
During the optimization process, these parameters are systematically varied to determine the combination that yields the best performance based on predefined criteria such as profitability, win rate, or risk management efficiency. The optimization aims to find the optimal Factor and ATR settings.
1.Starting Your Strategy Setup
Begin by deciding your goals for each trade: your profit target and stop loss, or if all trades exit when Supertrend changes direction. You'll also choose how to manage your stops – whether they stay put (fixed) or move with the price (trailing), and whether you want to exit trades at a specific price (limit orders). Keep the initial settings for Supertrend Factor Range and Supertrend ATR Range at their default to give the tool a broad testing field. The AI's guidance will refine these settings to pinpoint the most effective ones through a process of comprehensive testing.
Demonstration Start: We'll begin with the settings outlined in the key settings section, using Supertrend's direction change to the downside as our exit signal for all trades.
2. Continue applying the AI’s suggestions
Keep updating your optimization settings based on the AI's recommendations. Proceed with this iterative optimization until the "Best Found" message is displayed, signaling that the most effective strategy has been identified.
While following the AI's suggestions, we've been prompted with a new suggestion: increase the
number of strategies evaluated. Keep following the AI's new suggestions to evaluate more strategies. Do this until the "Best Found" message shows up.
Success! We continued to follow the AI’s suggestions until “Best Found” was indicated!
AI Mode
AI Mode incorporates Heuristic-Based Adaptive Learning to fine-tune trading strategies in a continuous manner. This feature consists of two main components:
Heuristic-Based Decision Making: The algorithm evaluates multiple Supertrend-based trading strategies using metrics such as Profit and Loss (PNL), Win Rate, and Most Efficient Profit. These metrics act as heuristics to assist the algorithm in identifying suitable strategies for trade execution.
Online Learning: The algorithm updates the performance evaluations of each strategy based on incoming market data. This enables the system to adapt to current market conditions.
Incorporating both heuristic-based decision-making and online learning, this feature aims to provide a framework for trading strategy optimization.
AI Mode Settings
AI Mode Aggressiveness:
Description: The "AI Mode Aggressiveness" setting allows you to fine-tune the AI's trading behavior. This setting ranges from “Low” to “High”, with “High” indicating a more assertive trading approach.
Functionality: This feature filters trading strategies based on a proprietary evaluation method. A higher setting narrows down the strategies that the AI will consider, leaning towards more aggressive trading. Conversely, a lower setting allows for a more conservative approach by broadening the pool of potential strategies.
Optimization
Trading system optimization is immensely advantageous when executed with prudence.
Technical-oriented, mechanical trading systems work when a valid correlation is methodical to the extent that an objective, precisely-defined ruleset can consistently exploit it. If no such correlation exists, or a technical-oriented system is erroneously designed to exploit an illusory correlation (absent predictive utility), the trading system will fail.
Evaluate results practically and test parameters rigorously after discovery. Simply mining the best-performing parameters and immediately trading them is unlikely a winning strategy. Put as much effort into testing strong-performing parameters and building an accompanying system as you would any other trading strategy. Automated optimization involves curve fitting - it's the responsibility of the trader to validate a replicable sequence or correlation and the trading system that exploits it.
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 .
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!
Evan Cabral Binary Strategy 2 / Lobowass Binary SignalThe script contains 1 Bollinger band with 2 different deviations also incorporated with a maximum and minimum of 30 minutes in green and red and a maximum and minimum of 4 hours in fuchsia. Also a 200 period EMA .
The red arrows appear whenever the stochastic , the DMI-stochastic and the two stochastics RSI are overbought and the low of the candle is breaking the bollnger band.
The green arrows appear whenever the stochastic , the DMI-stochastic and the two stochastics RSI are oversold and the high of the candle is breaking the bollnger band.
What makes this script unique is the combination of different indicators to give a buy or sell signal made by Edrul_Alejandro.
Indicator parameters:
Stochastic = (14,3,3) / (80,20)
Stochastic RSI 1 = (3,3,14,14) / (80,20)
Stochastic RSI 2 = (3,3,6,6) / (80,20)
Stochastic DMI = (10.3) / (90.10)
Bollinger band 1 = (34,2.0)
Bollinge band 2 = (34,2.5)
EMA = 200
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
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
Dex Atomic for nadexThis script utilizes two major concepts of price action.
1. Support and resistance - shown as the colored lines.
2. Dynamic price action movement - shown as the arrows on the chart.
This script is best utilized with the Nadex (north american derivative exchange ) system
Their exchange utilizes a derivative timed statement of true or false.
eurusd will be > the 1.0987 at 2pm you will either agree or disagree
You can learn more from their website.
A sell signal
Spotting the red arrow for direction
use the closest Higher support and resistance line as the statement price you would look for as a binary on nadex
A buy signals
use the closest lower support and resistance line as the statement price you would look for as a binary on nadex
These signals represented as arrows are a perceived notion of direction for a short period of time.
There are three times frames our systems work for
a 1 min time frame is used for a 5 min statement on nadex
a 5 min time frame is used for a one hour statement on nadex
a 15 in time frame is used for a 2 hour statement on nadex
Nadex uses ten pairs as well for forex, but also has indices , commodities and bitcoin statements as well. This script be used for those as well.
This script has an availability to be used as a forex trading potential with a litlle creative thought. but I wold suggest to just stay with the derivative exchange.
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.
Sifo's DMIHelps for better entries with my strategy (link bellow) on binary trades and some swing trades 1H-4H (10-100 pips).
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.
Momentum Strategy, rev.2This is a revised version of the Momentum strategy listed in the built-ins.
For more information check out this resource:
www.forexstrategiesresources.com
Profit Maximizer 90%-95% IntraDayTrade Strategy WithTester Developed for Intraday and for very very Lesser Time Frame Trading. Note: Invite only Script .Request to me Access permission to test this.
Strategy tester enabled .All you can test this in live market in any segment.
Lesser the time frame greater the success rates as the test results.
This can be used : Crypto Currency/Bitcoins ,Forex,currencies ,Index ,Commodity Gold/silver ,Oil Market and in Equity /Futures
It will work for BINARY OPTION ,BINARY DIGITAL to enter and hold the position in right direction, User test it and confirm .
How to Use:
Three Main Zone BackGrounds: 1. Green Zone 2. LightRed Zone 3. Yellow Zone
1.Long only when Bar Color changed from Red or Black to BLUE and BackGround in Green, Hold the position until opposite color comes.
2.Short when BAR become Black and BackGround Red Exit when opposite color come.
3.Yellow Back Ground : Risk Trade Zone : When Red BARs Cautious Short , Yellow Zone LightGreen Bars (Avoid Trade) .In Yellow Zone Close the previous Entered postions.
Time Frame : Lesser Time Frame and holding for longer time will give Good Result . 1min-1Hrs . This will not work >1Hr Strategy and Candle will disappear >1hr TimeFrame.
Strategy Tester : Choose any Date Month Year to Current Date and check the results below in the Strategy Tester.
REPAINT/NO REPAINT : No Repaint ,Previous candles and Background Color wont change. In the current candle position wait for the candle to close to see the stability.Current candle color might oscillate bit However it will not change from Blue to Black or Black to Blue or Black to Red.
Note : Last Bar will be a actual Green or Red Bar by Default Do not Confuse with this.It is trading view default strategy design working way.Once Bar closes actual strategy color will appear.
ALERT /AUTOVIEW capabilities : Strategy Tester does not support ALERT by default as you all know.In the Indicator version Alert will be added for all Buy Sell and cover entries.
Test the strategy.
SCRIPT : Access must be given by me to test this .Once access given you can test ,Request for access .Without access Study Not Auth error will come.
Review and Feedback.Thank you!
Refer the Release notes for any updates and my posts below and in my idea page for more details. Thank you!
Any issues report to me to Fix.Thank you!
SuperR V.2Hi,
This is the same indicator but now it's more accurate. you can use it with 1- minute binary options trading. Please note that SuperR is not for FX or stock trading expect binary options. With this system, we're using 2 step of martingale.
And my indicator is for sale. once you buy it you will get permission to access indicator. as simple as that.
Mail me, if you are interested. SuperR indicator is priced at $150. once-off fee.
For more information
Drop me a mail, id is jogadiyahemlata786@gmail.com ( Ensure spelling before you send it out )
(This is officile annocenment )
SPG Fx Volume IndicatorThis indicator is for Forex intraday trading and works best for binary 5 minute contracts but will work for Contracts up to 2 hours in length.
The "SPG - FOREX BINARY INTRA" indicator is a companion for this one. It will give confirmation of the entry signals that this will show you.
This script is broken up into 4 parts
Confidence Cloud/Background Color
This will indicate the current bull/bear trend and if your entering a position - the strength of the direction of that bar will be reflected by the background color behind that bar.
Green - Bull Trend
Red - Bear Trend
Yellow - Transition/unsure
Small BUY/SELL arrows and Green/Red triangles
On the bottom of the chat are the main entry indicators
Green/Red Triangles are a strong entry signal
Green/Red Tringles and a Buy/Sell arrow is a very strong entry signal
Buy/Sell Pressure
The histogram indicated the buy/sell pressure for the bar – This indicated in which direction the bar moved the most – This is mostly for a future “rating” on a position that was taken and perhaps can drive an indication when to Hold or exit the contract.
Green/Red arrows and Xs labeled OS, OB or X
These are located on the top of this indicator and aren’t necessarily actionable indicators but are meant to indicate overbought or oversold conditions and transitions when prices are moving out of those states.
The indicators may correlate with entry signals but watch for the Xs and do not enter a trade on a transition.
PRO MomentumINVITE ONLY SCRIPT:
FEATURES:
As its name suggests, PRO Momentum provides non-subjective momentum analysis to traders through automatic pattern detections, covering a wide range of statistically relevant structures in both ranging and trending contexts. Our goal was to provide a professional grade risk management tool capable of providing various signals, which guide the trader in its decision to engage or not in a certain price area filtered by Framework. Nevertheless, both indicators are complex tools requiring extensive learning. To support students in their journey, there is a wide open online community of users in our Discord channel, providing peer-to-peer assistance to progress with the strategy as well as tutored courses.
OUTPUTS:
To share a brief description of the PRO Momentum functioning, we will scroll through the major set of outputs that are presented to the user. Please note that the indicator is meant to assist from Junior to Senior expertise, to achieve this we have set different base templates right into the indicators. To keep this description simple, we will present the outputs you’ll see with the beginner setup:
Momentum Signals: As shown on the chart, there are multiple types of output signals, each corresponding to different momentum patterns. Detailed documentation is available on our website for those seeking in-depth information. Here's a high-level overview: The patterns are divided into three categories, each represented by different colors. Blue and Red signals are used in trending contexts, Gray signals are for ranging contexts, and dark-colored signals are exclusive to reversal contexts, suitable for more experienced traders. Momentum signals are binary outputs, making it easy for users to set alerts. The indicator includes built-in alerts for these groups to streamline the process. However, it’s crucial to remember that momentum signals are not standalone trading signals. The Framework indicator must first filter interesting prices and identify the context. Only then should traders use momentum signals to adjust risk.
Sinewave Oscillators: Cyclical analysis is a critical aspect of professional risk management. Markets naturally oscillate, and significant statistical probabilities can be derived from cycle studies. We use a custom-modified version of Ehlers’ sinewave methodology. Cyclical analysis, while somewhat predictive, scans past prices to predict probable future states. Since markets are inherently unpredictable, cycle analysis is used as a confirmation signal in our strategy. Essentially, we filter out all momentum signals that occur outside favorable cyclical conditions. Bearish signals are only exploited if the sinewave is in the top area of the oscillator, and vice-versa for bullish signals.
GENERAL STRATEGY:
Overall, the PRO Strategy combines two “core” indicators, Framework and Momentum. Framework is plotted on the main chart section as an overlay, it is definitely the most important as it guides the user through the hard process of filtering prices and timeframes that are suitable for technical analysis. On the other hand, PRO Momentum is on a separate oscillator tab under the chart section, it will study the momentum and cyclical structure, also offering automated pattern detection. Ultimately, our strategy is based on collecting and processing non-subjective rules, emanating from the indicators outputs. Essentially, this means that the indicator actually takes care of producing all the necessary binary outputs, leaving you with the remaining task of combining them correctly following the strategy’s patterns.
RISK LIMITATION:
Even if we provide automated momentum signal detection, there is no “one-click” or "easy-win” solution, the user still needs to carefully review the elements. When applicable pattern rules are confirmed, the user will gather risk-limitation information from both indicators (breakout targets, price confirmations, momentum and cyclical coordination) and decide whether or not to trade according to its own risk profile. If so, the position sizing, stop-loss positioning, risk management and profit targets will all be defined according to the same indicator’s outputs. This effectively suppresses most behavioral and personal biases the trader could introduce, creating a stable and statistical risk management structure aiming for a durable profitability.
EMA Strong Trend MarketUse this indicator with my binary blast v2 indicator for getting good binary signals if combine. Don't call or put option when this signal comes in a bar while using previous indicator.
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.
Bollinger Bands NEW
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tradingview_embed_options.width = 640;
tradingview_embed_options.height = 400;
tradingview_embed_options.chart = 's48QJlfi';
new TradingView.chart(tradingview_embed_options);
Vdub Binary Options SniperVX v1 by vdubus on TradingView.com
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
KayeDinero Ranger HFX NFXThis script combines my favorite indicators with an added flare.
The mindset for this strategy is a ranging market, where price is moving in a consistent wave like pattern.
The most unique concept of this script is the candlestick indications. This is different from other scripts on the platform because of the close tie in with the relative strength index as well as the on balance volume.
Best Traded during Hours 3am to 12am EST (NY Time).
This method works best in volatile markets.
Time Frame, 1,3,5,15,30min
Currency Pairs: All Major, Exotic,
Here's The Strategy:
Uptrend and Buy: When those are present, proceed to take a buy (call) option.
Downtrend and Sell: When those are present, proceed to take a sell (put) option.
Keep in mind, timeframe will depend on your time of trading in the markets.
Morning typically 2-4min
Afternoon / Evening: 3-5min
Hint:
Best Trades on reversals at top and bottom of Bollinger bands.
Whole NumbersThis is a simple indicator for the whole numbers.
It breaks down every pair for 10 pips.
Its also simple and nice to use
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.
