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Catalogador Binarias Padron MHI DejaVuTradesQuadrant patterns with 1 minute cataloging. This script simulates the quadrants between candles from minute 1 to 5. set your time frame to 1M. Ready, now we have our quadrants and we will do the analysis of these patterns using them. Green circles indicate winning trades, and blue circles Martingale steps. Counting candles within the quadrants (time frame m1 ) MHI There are several variants of MHI . In our cataloguer we offer 3 variants. MHI 1, 2 and 3. The analysis is carried out from the last three candles in the last quadrant. And the entry is made: on the first candle of the current quadrant ( MHI 1), on the second candle of the current quadrant ( MHI 2) and on the third candle of the current quadrant ( MHI 3). MHI 1 Entry into the first candle after the quadrant analysis. First martingale (in case of loss) in the second candle and second martingale (in case of two losses) in the third candle. MHI 2 Entry into the second candle after the quadrant analysis. First martingale (in case of loss) on the third candle and second martingale (in case of two losses) on the fourth candle. MHI 3 Entry into the third candle after the quadrant analysis. First martingale (in case of loss) on the fourth candle and second martingale (in case of two losses) on the fifth candle. The million dollar pattern It is an analysis very similar to that of the MHI , with the difference that it is in the entire quadrant. The million analysis consists of looking at all the candles in the last quadrant and entering the first candle of the current quadrant saying that that first candle will be the same color as most of the last quadrant. In cases where we have the same number of candles (3 red and 3 green) we do not trade! And the cataloger will not count these operations. Three Neighbors Pattern The analysis of the pattern of the three neighbors will always be in the third candle of the quadrant. Either in M5 or M1 . And it consists of observing the third candle and entering the following ones saying that it will be the same. Pattern C3 The C3 pattern is also an analysis in the candlestick count. We will enter the first quadrant candle saying that it will be equal to the first candle of the last quadrant. In the case of 1 martingale we will enter the third candle saying that it will be equal to the third candle of the last quadrant. And finally, in need of a second martingale, the entry will be in the fifth candle saying that it will be similar to the fifth of the last candle. Moonwalker Pattern The moonwalker pattern is also a quadrant pattern. Our entries will be in the first, second and third candles of the current quadrant. The analysis is performed on the third, second and first candle of the last quadrant. The entry of the first candle will be observed in the third candle of the last quadrant, being the opposite color to that observed. Being necessary a martingale, we make our entry into the second candle that claims the opposite color to the second candle in the last quadrant. Finally, our second martingale will be on the third candle of the current quadrant with analysis in which the color will be opposite to the first candle of the last quadrant.
Pine Script® indicator
by DejaVuTrades_BettoLe
5
Black-Scholes Model and Greeks for European OptionsThe Black-Scholes model is a mathematical model used for pricing options. From this model you can derive the theoretical fair value of a European option (an option where you have to wait until expiry to exercise). Additionally, you can derive various risk parameters called Greeks. This indicator includes three types of data: Theoretical Option Price (blue), the Greeks (green), and implied volatility (red); their values are presented in that order. 1) Theoretical Option Price: This first value gives only the theoretical fair value of an option with a given strike based on the Black-Scholes framework. Remember this is a model and does not reflect actual option prices, just the theoretical price based on the Black-Scholes model and its parameters and assumptions. 2)Greeks (all of the Greeks included in this indicator are listed below): a)Delta is the rate of change of the theoretical option price with respect to the change in the underlying's price. This can also be used to approximate the probability of your option expiring in the money. For example, if you have an option with a delta of 0.62, then it has about a 62% chance of expiring in-the-money. This number runs from 0 to 1 for Calls, and 0 to -1 for Puts. b)Gamma is the rate of change of delta with respect to the change in the underlying's price. c)Theta, aka "time decay", is the rate of change in the theoretical option price with respect to the change in time. Theta tells you how much an option will lose its value day by day. d)Vega is the rate of change in the theoretical option price with respect to change in implied volatility. e)Rho is the rate of change in the theoretical option price with respect to change in the risk-free rate. Rho is rarely used because it is the parameter that options are least effected by, it is more useful for longer term options, like LEAPs. f)Vanna is the sensitivity of delta to changes in implied volatility. Vanna is useful for checking the effectiveness of delta-hedged and vega-hedged portfolios. g)Charm, aka "delta decay", is the instantaneous rate of change of delta over time. Charm is useful for monitoring delta-hedged positions. h)Vomma measures the sensitivity of vega to changes in implied volatility. i)Veta measures the rate of change in vega with respect to time. j)Vera measures the rate of change of rho with respect to implied volatility. k)Speed measures the rate of change in gamma with respect to changes in the underlying's price. Speed can be used when evaluating delta-hedged and gamma hedged portfolios. l)Zomma measures the rate of change in gamma with respect to changes in implied volatility. Zomma can be used to evaluate the effectiveness of a gamma-hedged portfolio. m)Color, aka "gamma decay", measures the rate of change of gamma over time. This can also be used to evaluate the effectiveness of a gamma-hedged portfolio. n)Ultima measures the rate of change in vomma with respect to implied volatility. o)Probability of Touch, is not a Greek, but a metric that I included, which tells you the probability of price touching your strike price before expiry. 3) Implied Volatility: This is the market's forecast of future volatility. Implied volatility is directionless, it cannot be used to forecast future direction. All it tells you is the forecast for future volatility. How to use this indicator: 1st. Input the strike price of your option. If you input a strike that is more than 3 standard deviations away from the current price, the model will return a value of n/a. 2nd. Input the current risk-free rate.(Including this is optional, because the risk-free rate is so small, you can just leave this number at zero.) 3rd. Input the time until expiry. You can enter this in terms of days, hours, and minutes. 4th.Input the chart time frame you are using in terms of minutes. For example if you're using the 1min time frame input 1, 4 hr time frame input 480, daily time frame input 1440, etc. 5th. Pick what type of option you want data for, Long Call or Long Put. 6th. Finally, pick which Greek you want displayed from the drop-down list. *Remember the Option price presented, and the Greeks presented, are theoretical in nature, and not based upon actual option prices. Also, remember the Black-Scholes model is just a model based upon various parameters, it is not an actual representation of reality, only a theoretical one.
Pine Script® indicator
by SegaRKO
5
Trend Pulse Pro V2Trend Pulse Pro V2 (Non Repaint) TradingView Account Needed: Free You don't need to be an expert to use Trend Pulse Pro. Just follow the signals and that's all and use simple Fibonacci levels to find stop loss and take profit! You can increase the win rate even more by following some simple technical analysis, for example, when trend breaks (price break signal level) you can use that as support become resistance level (sell) or resistance becomes support (buy): No complex things. No waste of time. And although you won't win 100% of the trades (no signals can guarantee that), your trading will surely improve a lot! Even someone with almost no trading experience can read the simple trading rules given in the included user guide, watch the how-to videos and follow Trend Pulse Pro’s signals to consistently make smarter trades. With Trend Pulse Pro you will get accurate buy and sell signals every time there is a new trading opportunity so that you never miss any big price movements and makes your trading both easier and more profitable. How to use the signals and alerts: Trend Pulse Pro automatically analyze trend and price action to give you a signal when there's a good trade. These trend signals and alerts are derived from live data but the stability of our code allows it to not repaint. Trend Pulse Pro allow you to easily determine the trend and will give you buy and sell entry levels. Works on all markets on all time frames so it's suitable for scalpers, day and swing traders. If you want more details, the link is in the signature. Disclaimer: Past performance is not indicative of future performance. No representation is being made that any results discussed within the service and its related media content will be achieved. All opinions, news, research, analyses, prices or other information is provided as general market commentary and not as investment advice. TradingWalk, their members, shareholders, employees, agents, representatives and resellers do not warrant the completeness, accuracy or timeliness of the information supplied, and they shall not be liable for any loss or damages, consequential or otherwise, which may arise from the use or reliance of the TradingWalk service and its content. © 2019 TradingWalk. TradingWalk indicators are built for TradingView. TradingWalk is on no way a part of TradingView.
Pine Script® indicator
by tradingwalk
192
MM-Microtrend-Reversal-IndicatorThis indicator detects microtrend reversals based on crossing of the DMI+ and DMI- + signals It indicates the trigger event on the chart as well as the reversal candle In addition to that it shows a countdown above the bars This is helping when multiple reversals occur Important: when the Bollinger Bands are crossed in the previous bars it's possible that the prognosted reversal will NOT show up Recommended timeframes are M1 and M2 Avoid trading sideway trends, the reverals are low and reversal triggers and assumed reversal candles could get chaotic
Pine Script® indicator
by Meunier
28
MM-Microtrend-Reversal-IndicatorThis indicator detects microtrend reversals based on crossings of the DMI+ and DMI- signals It indicates the trigger event on the chart as well as the reversal candle In addition to that it shows a countdown above the bars This is helping when multiple reversals occur. Important: when the Bollinger Bands are crossed in the previous bars it's possible that the prognosted reversal will NOT show up Recommended timeframes are M1 and M2 Avoid trading sideway trends, the reversals are low and reversal triggers and assumed reversal candles could get chaotic sometimes
Pine Script® indicator
by Meunier
2
Chatterjee CorrelationThis is my first attempt on implementing a statistical method. This problem was given to me by @lejmer (who also helped me later on building more efficient code to achieve this) when we were debating on the need for higher resource allocation to run scripts so it can run longer and faster. The major problem faced by those who want to implement statistics based methods is that they run out of processing time or need to limit the data samples. My point was that such things need be implemented with an algorithm which suits pine instead of trying to port a python code directly. And yes, I am able to demonstrate that by using this implementation of Chatterjee Correlation. 🎲 What is Chatterjee Correlation? The Chatterjee rank Correlation Coefficient (CCC) is a method developed by Sourav Chatterjee which can be used to study non linear correlation between two series. Full documentation on the method can be found here: arxiv.org In short, the formula which we are implementing here is: Algorithm can be simplified as follows: 1. Get the ranks of X 2. Get the ranks of Y 3. Sort ranks of Y in the order of X (Lets call this SortedYIndices) 4. Calculate the sum of adjacent Y ranks in SortedYIndices (Lets call it as SumOfAdjacentSortedIndices) 5. And finally the correlation coefficient can be calculated by using simple formula CCC = 1 - (3*SumOfAdjacentSortedIndices)/(n^2 - 1) 🎲 Looks simple? What is the catch? Mistake many people do here is that they think in Python/Java/C etc while coding in Pine. This makes code less efficient if it involves arrays and loops. And the simple code may look something like this. var xArray = array.new() var yArray = array.new() array.push(xArray, x) array.push(yArray, y) sortX = array.sort_indices(xArray) sortY = array.sort_indices(yArray) SumOfAdjacentSortedIndices = 0.0 index = array.get(xSortIndices, 0) for i=1 to n > 1? n -1 : na indexNext = array.get(sortX, i) SumOfAdjacentSortedIndices += math.abs(array.get(sortY, indexNext)-array.get(sortY, index)) index := indexNext correlation := 1 - 3*SumOfAdjacentSortedIndices/(math.pow(n,2)-1) But, problem here is the number of loops run. Remember pine executes the code on every bar. There are loops run in array.sort_indices and another loop we are running to calculate SumOfAdjacentSortedIndices. Due to this, chances of program throwing runtime errors due to script running for too long are pretty high. This limits greatly the number of samples against which we can run the study. The options to overcome are Limit the sample size and calculate only between certain bars - this is not ideal as smaller sets are more likely to yield false or inconsistent results. Start thinking in pine instead of python and code in such a way that it is optimised for pine. - This is exactly what we have done in the published code. 🎲 How to think in Pine? In order to think in pine, you should try to eliminate the loops as much as possible. Specially on the data which is continuously growing. My first thought was that sorting takes lots of time and need to find a better way to sort series - specially when it is a growing data set. Hence, I came up with this library which implements Binary Insertion Sort. Replacing array.sort_indices with binary insertion sort will greatly reduce the number of loops run on each bar. In binary insertion sort, the array will remain sorted and any item we add, it will keep adding it in the existing sort order so that there is no need to run separate sort. This allows us to work with bigger data sets and can utilise full 20,000 bars for calculation instead of few 100s. However, last loop where we calculate SumOfAdjacentSortedIndices is not replaceable easily. Hence, we only limit these iterations to certain bars (Even though we use complete sample size). Plots are made for only those bars where the results need to be printed. 🎲 Implementation Current implementation is limited to few combinations of x and fixed y. But, will be converting this into library soon - which means, programmers can plug any x and y and get the correlation. Our X here can be Average volume ATR And our Y is distance of price from moving average - which identifies trend. Thus, the indicator here helps to understand the correlation coefficient between volume and trend OR volatility and trend for given ticker and timeframe. Value closer to 1 means highly correlated and value closer to 0 means least correlated. Please note that this method will not tell how these values are correlated. That is, we will not be able to know if higher volume leads to higher trend or lower trend. But, we can say whether volume impacts trend or not. Please note that values can differ by great extent for different timeframes. For example, if you look at 1D timeframe, you may get higher value of correlation coefficient whereas lower value for 1m timeframe. This means, volume to trend correlation is higher in 1D timeframe and lower in lower timeframes.
Pine Script® indicator
by Trendoscope
10
MM-Burj Khalifa IndicatorThis indicator uses several signals to visualize a "perfect candle" to enter a trade. It colors the background to identify the zones of interest (multiple configurable high or low RSI zones). Underlying is a trendbar with the current MACD direction. The indicator is using signals of: --MACD --RSI --PVT --ATR --AD and DMI+/DMI- When all 7 criterias are met it highlights the candle. It also creates different colums with different height and width, so that you can see which signal is OK and which is maybe missing. When all signals are on GO you'll see a Burj-Khalifa-like figure. If not all signals are on GO you'see crippled versions. To be clear: it's not intended to detect trends or supertrends or reversals. It's purpose it's just to decide if this current candle is really going in the right direction. The Burj-Khalifa indicator could help to confirm the entry point of an trade which was already planned.
Pine Script® indicator
by Meunier
31
Inflection PointInflection Point - The Adaptive Confluence Reversal Engine This is not just another peak and valley indicator; it is a complete and total reimagining of how market turning points are detected, qualified, and acted upon. Born from the foundational concepts explored in systems like my earlier creation, DAFE - Turning Point, Inflection Point is a ground-up engineering feat designed for the modern trader. It moves beyond static rules and simple pattern recognition into the realm of dynamic, multi-factor confluence analysis and adaptive machine learning. Where other indicators provide a guess, Inflection Point provides a probability. It meticulously analyzes the market's deepest currents—momentum, exhaustion, and reversal velocity—and fuses them into a single, unified "Confluence Score." This is not a simple combination of indicators; it is an intelligent, weighted system where each component works in concert, creating an analytical engine that is orders of magnitude more sophisticated and reliable than any standard reversal tool. Furthermore, Inflection Point learns. Through its advanced Adaptive Learning Engine, it constantly monitors its own performance, adjusting its confidence and selectivity in real-time based on its recent success rate. This allows it to adapt its behavior to any security, on any timeframe, with remarkable success. Theoretical Foundation - Confluence Core Inflection Point's predictive power does not come from a single, magical formula. It comes from the intelligent synthesis of three critical market phenomena, weighted and scored in real-time to generate a single, high-conviction probability rating. 1. Factor One: Pre-Reversal Momentum State (RSI Analysis) Instead of reacting to a simple RSI cross, Inflection Point proactively scans for the build-up of momentum that precedes a reversal. • Formulaic Concept: It measures the highest RSI value over a lookback period for peaks and the lowest RSI for valleys. A signal is only considered valid if significant momentum has been established before the turn, indicating a stretched market condition ripe for reversal. • Asymmetric Sophistication: The engine uses different, optimized thresholds for bull and bear momentum, recognizing that markets often fall faster than they rise. 2. Factor Two: Volatility Exhaustion (Bollinger Band Analysis) A true reversal often occurs when price makes a final, exhaustive push into unsustainable territory. • Formulaic Concept: The engine detects when price has significantly pierced the outer Bollinger Bands. This is not just a touch, but a statistical deviation from the mean that signals volatility exhaustion, where the energy for the current move is likely depleted. 3. Factor Three: Reversal Strength (Rate of Change Analysis) The character of a reversal matters. A sharp, decisive turn is more significant than a slow, meandering one. • Formulaic Concept: Using a short-term Rate of Change (ROC), the engine measures the velocity of the reversal itself. A higher ROC score adds significant weight to the final probability, confirming that the new direction has conviction. 4. The Final Calculation: The Adaptive Learning Engine This is the system's "brain." It maintains a history of its past signals and calculates its real-time win rate. This hitRate is then used to generate an adaptiveMultiplier. • Self-Correction: In "Quality Control" mode, a high win rate makes the indicator more selective, demanding a higher probability score to issue a signal, thereby protecting streaks. A lower win rate makes it slightly less selective to ensure it continues learning from new market conditions. • The result is a system that is not static, but a living, breathing tool that adapts its personality to the unique rhythm of any chart. Why Inflection Point is a Paradigm Shift Inflection Point is fundamentally different from other reversal indicators for three key reasons: Confluence Over Isolation: Standard indicators look at one thing (e.g., RSI > 70). Inflection Point simultaneously analyzes momentum, volatility, and velocity, understanding that true reversals are a product of multiple converging factors. It answers not just "if," but "why" a reversal is likely. Probabilistic Over Binary: Other tools give you a simple "yes" or "no." Inflection Point provides a probability score from 0-100, allowing you to gauge the conviction of every potential signal. This empowers you to differentiate between a weak setup and an A+ opportunity. Adaptive Over Static: Every other indicator uses the same rules forever. Inflection Point's Adaptive Engine means it is constantly refining its own logic based on what is actually working in the current market, on the specific asset you are trading. It is tailored to the now. The Inputs Menu - Your Command Center Every setting is a lever of control, allowing you to tune the engine to your precise trading style and market focus. 🧠 Neural Core Engine Analysis Depth: This is the primary lookback for the Bollinger Band and other core calculations. A shorter depth makes the indicator faster and more sensitive, ideal for scalping. A longer depth makes it slower and more stable, ideal for swing trading. Minimum Probability %: This is your master signal filter. It sets the minimum Confluence Score required to plot a signal. Higher values (85-95) will give you only the highest-conviction A+ setups. Lower values (70-80) will show more potential opportunities. 🤖 Adaptive Neural Learning Enable Adaptive Learning Engine: Toggles the entire learning system. Disabling it will make the indicator's logic static. Peak/Valley Success Threshold (ATR): This defines what constitutes a "successful" trade for the learning engine. A value of 1.5 means price must move 1.5x the ATR in your favor for the signal to be marked as a win. Adjust this to match your personal take-profit strategy. Adaptive Mode: This dictates how the engine uses its hitRate. "Quality Control" is recommended for its intelligent filtering. "Aggressive" will always boost signal scores, useful for finding more setups in a known, trending environment. Asymmetric Balance: Allows you to apply a "boost" to either peak (short) or valley (long) signals. If you find the market you're trading has stronger long reversals, you can increase the "Valley Signal Boost" to catch them more effectively. 🛡️ Elite Filters Market Noise Filter: An exceptional tool for avoiding choppy markets. It counts the number of directional changes in the last 5 bars. If the market is whipping back and forth too much, it will block the signal. Lower the "Max Direction Changes" to be extremely selective. Volume Filter: Requires signal confirmation from a significant volume spike. The "Volume Multiplier" dictates how large this spike must be (e.g., 1.2 = 20% above average volume). This is invaluable for filtering out low-conviction moves in stocks and crypto. The Dashboard - Your Analytical Co-Pilot The dashboard is not just a set of numbers; it is a holistic overview of the market's health and the engine's current state. Unified AI Score: This section provides the most critical, at-a-glance information. "Total Score" is the current probability reading, while "Quality" gives you a human-readable interpretation. "Win Rate" shows the real-time performance of the Adaptive Engine. Order Flow (OFPI): This measures the "weight" of money behind recent price moves by analyzing price change relative to volume. A high positive OFPI suggests strong buying pressure, while a high negative value suggests strong selling pressure. It gives you a peek into the market's underlying flow. Component Analysis: This allows you to see the individual "Peak" and "Valley" confidence scores before they are filtered, giving you insight into building momentum before a signal forms. Market Structure: This panel assesses the broader environment. "HTF Trend" tells you the direction of the larger trend (based on EMAs), while "Vol Regime" tells you if the market is in a high, medium, or low volatility state. Use this to align your signals with the broader market context. Filter & Engine Statistics: Available on the "Large" dashboard, this provides deep insight into how many signals are being blocked by your filters and the current status of the Adaptive Engine's multiplier. The Visual Interface - A Symphony of Data Every visual element on the chart is designed for instant interpretation and insight. Signal Markers: Simple, clean triangles mark the exact bar of a valid signal. A box is drawn around the high/low of the signal bar to highlight the precise point of inflection. Dynamic Support/Resistance Zones: These are the glowing lines on your chart. They are not static lines; they are dynamic levels that represent the current battlefield between buyers and sellers. Cyber Cyan (Valley Blue): This is the current Support Zone. This is the price level the market is currently trying to defend. Neural Pink (Peak Red): This is the current Resistance Zone. This is the price level the market is currently trying to break through. Grey (Next Level): This line is a projection, based on the current momentum and the size of the S/R range, of where the next major level of conflict will likely be. It acts as a potential price target. Development & Philosophy Inflection Point was not assembled; it was engineered. It represents hundreds of hours of research into market dynamics, statistical analysis, and machine learning principles. The goal was to create a tool that moves beyond the limitations of traditional technical analysis, which often fails in modern, algorithm-driven markets. By building a system based on multi-factor confluence and self-adaptive logic, Inflection Point provides a quantifiable, statistical edge that is simply unattainable with simpler tools. This is the result of a relentless pursuit of a better, more intelligent way to trade. Universal Applicability The principles of momentum, exhaustion, and velocity are universal to all freely traded markets. Because of its adaptive core and robust filtering options, Inflection Point has proven to be exceptionally effective on any security (stocks, crypto, forex, indices, futures) and on any timeframe (from 1-minute scalping charts to daily swing trading charts). " Markets are constantly in a state of uncertainty and flux and money is made by discounting the obvious and betting on the unexpected. " — George Soros Trade with insight. Trade with anticipation. — Dskyz, for DAFE Trading Systems
Pine Script® indicator
by DskyzInvestments
28