Liquidity Trading Algorithm (LTA)
The Liquidity Trading Algorithm is an algorithm designed to provide trade signals based on
liquidity conditions in the market. The underlying algorithm is based on the Liquidity
Dependent Price Movement (LDPM) metric and the Liquidity Dependent Price Stability (LDPS)
algorithm.
Together, LDPM and LDPS demonstrate statistically significant forecasting capabilities for price-
action on equities, cryptocurrencies, and futures. LTA takes these liquidity measurements and
translates them into actionable insights by way of entering or exiting a position based
on the future outlooks, as measured by the current liquidity status.
The benefit of LTA is that it can incorporate these powerful liquidity measurements into
actionable insights with several features designed to help you tailor LTA's behavior and
measurements to your desired vantage point. These customizable features come by the way of determining LTA's assessment style, and additional monitoring systems for avoiding bear and bull traps, along with various other quality of life features, discussed in more detail below.
First, a few quick facts:
- LTA is compatible on a wide array of instruments, including Equities, Futures, Cryptocurrencies, and Forex.
- LTA is compatible on most intervals in so long as the data can be calculated appropriately,
(be sure to do a backtest on timescales less than 1-minue to ensure the data can be computed).
- LTA only measures liquidity at the end of the interval of the chart chosen, and does not respond to conditions during the candle interval, unless specified (such as with `Stops`).
- LTA is interval-dependent, this means it will measure and behave differently on different
intervals as the underlying algorithms are dependent on the interval chosen.
- LTA can utilize fractional share sizing for cryptocurrencies.
- LTA can be restricted to either bullish or bearish indications.
- Additional Monitoring Systems are available for additional risk mitigation.
In short, LTA is a widely applicable, unique algorithm designed to translate liquidity measurements into liquidity insights.
Before getting more into the details, here is a quick list of the main features and settings
available for customization:
- Backtesting Start Date: Manual selection of the start date for the algorithm during backtesting.
- Assessment Style: adjust how LDPM and LDPS measure and respond to changes in liquidity.
- Impose Wait: force LTA to wait before entering or exiting a position to ensure conditions have remained conducive.
- Trade Direction Allowance: Restrict LTA to only long or only short, if desired.
- Position Sizing Method: determine how LTA calculates position sizing.
- Fractional Share Sizing: allow LTA to calculate fractional share sizes for cryptocurrencies
- Max Size Limit: Impose a maximum size on LTA's positions.
- Initial Capital: Indicate how much capital LTA should stat with.
- Portfolio Allotment: Indicate to LTA how much (in percentages) of the available balance should be considered when calculating position size.
- Enact Additional Monitoring Systems: Indicate if LTA should impose additional safety criteria when monitoring liquidity.
- Configure Take Profit, Stop-Loss, Trailing Stop Loss
- Display Information tables on the current position, overall strategy performance, along
with a text output showing LTA's processes.
- Real-time text output and updates on LTA's inner workings.
Let's get into some more of the details.
LTA's Assessment Style
LTA's assessment style determines how LTA collects and responds to changing data. In traditional terms, this is akin to (but not quite exactly the same as) the sensitivity versus specificity spectrum, whereby on one end (the sensitive end), an algorithm responds to changes in data in a reactive manner (which tends to lower its specificity, or how often it is correct in its indications), and on the other end, the opposite one, the algorithm foresakes quick changes for longevity of outlook.
While this is in part true, it is not a full view of the underlying mechanisms that changing the assessment style augments. A better analogy would be that the sensitive end of the spectrum (`Aggressive`) is in a state such that the algorithm wants to changing its outlooks, and as such, with changes in data, the algorithm has to be convinced as to why that is not a good idea to change outlooks, whereas the the more specific states (`Conservative`, `Diamond`) must be convinced that their view is no longer valid and that it needs to be changed.
This means the `Aggressive` and the `Diamond` settings fundamentally differ not just in their
data collection, but also in the data processing such that the `Aggressive` decision tree has to
be convinced that the data is the same (as its defualt is that it has changed),
and the `Diamond` decision tree has to be convinced that the data is not the same, and as such, the outlook need changed.
From there, the algorithm cooks through the data and determines to what the outlook should be changed to, given the current state of liquidity.
`Balanced` lies in the middle of this balance, attempting to balance being open to new ideas while not removing the wisdom of the past, as it were.
On a scale of most `sensitive` to most `specific`, it is as follows: `Aggressive`, `Balanced`,
`Conservative`, `Diamond`.
Functionally, these different modes can help in different liquidity environments, as certain
environments are more conducive to an eager approach (such as found near `Aggressive`) or are more conducive to a more conservative approach, where sudden changes in liquidity are known to be short-lived and unremarkable (such as many previously identified bull or bear traps).
For instance, on low interval views, it can often-times be beneficial to keep the algorithm towards the `Sensitive` end, since on the lower-timeframes, the crosswinds can change quite dramatically; whereas on the longer intervals, it may be useful to maintain a more `Specific` algorithm (such as found near `Diamond` mode) setting since longer intervals typically lend themselves to longer time-horizons, which themselves typically lend themselves to "weathering the storm", as it were.
LTA's Assessment Style is also supported by the Additional Monitoring Systems which works
to add sensitivity without sacrificing specificity by enacting a separate monitoring system, as described below.
Additional Monitoring Systems
The Additional Monitoring System (AMS) attempts to add more context to any changes in liquidity conditions as measured, such that LTA as a whole will have an expanded view into any rapidly changing liquidity conditions before these changes manifest in the traditional data streams. The ideal is that this allows for early exits or early entrances to positions "a head of time".
The traditional use of this system is to indicate when liquidity is suggestive of the end of a particular run (be it a bear run or a bull run), so an early exit can be initiated (and thus,
downside averted) even before the data officially showcase such changes. In such cases (when AMS becomes activated), the algorithm will signal to exit any open positions, and will restrict the opening of any new positions.
When a position is exited because of AMS, it is denoted as an `Early Exit` and if a position is prevented from being entered, the text output will display `AM prevented entry...` to indicate that conditions are not meeting AMS' additional standards.
The algorithm will wait to make any actions while `AMS` is `active` and will only enter into a new position once `AMS` has been `deactivated` and overall liquidity conditions are appropriate.
Functionally, the benefits of AMS translate to:
- Toggeling AMS on will typically see a net reduction in overall profitability, but
- AMS will typically (almost always) reduce max drawdown,
an increases in max runup, and increase return-over-maxdrawdown, and
- AMS can provide benefit for equities that experience a lot of "traps" by navigating early
entrance and early exits.
So in short, AMS is way of adding an additional level of liquidity monitoring that attempts to
exit positions if conditions look to be deteriorating, and to enter conditions if they look to be
improving. The cost of this additional monitoring, however, is a greater number of trades indicated, and a lower overall profitability.
Impose Wait
Note: `Impose Wait` will not force Take Profit, Stop Loss, or Trailing Stop Loss to
wait.
LTA can be indicated to `wait` before entering or exiting a position if desired. This means that if conditions change, whereas without a `wait` imposed, the algorithm would immediately indicate this change via a signal to alter the strategy's position, with a `wait` imposed, the algorithm will `wait` the indicated number of bars, and then re-check conditions before proceeding.
If, while waiting, conditions change to a state that is no longer compatible with the "order-in-
waiting", then the order-in-waiting is removed, and the counts reset (i.e.: conditions must remain favorable to the intended positional change throughout the wait period).
Since LTA works at the end-of-intervals, there is an inherently "built-in" wait of 1 bar when
switching directly from long to short (i.e.: if a full switch is indicated, then it is indicated as
conditions change -> exit new position -> wait until -> check conditions ->
enter new position as indicated). Thus, to impose a wait of `1 bar` would be to effectively have a total of two candles' ends prior to the entrance of the new position).
There are two main styles of `Impose Wait` that you can utilize:
- `Wait` : this mode will cause LTA to `wait` when both entering and exiting a position (in so long as it is not an exit signaled via a Take Profit, Stop Loss or Trailing Stop Loss).
- `Exit-Wait` : This mode will >not< cause LTA to `wait` if conditions require the closing of a position, but will force LTA to wait before entering into a position.
Position:
In addition to the availability to restrict LTA to either a long-only or short-only strategy, LTA
also comprises additional flexibility when deciding on how it should navigate the markets with
regards to sizing. Notably, this flexibility benefits several aspects of LTA's existence, namely the ability to determine the `Sizing Method`, or if `Fractional Share Sizing` should be employed, and more, as discussed below.
Position Sizing Method
There are two main ways LTA can determine the size of a position. Either via the `Fixed-Share` choice, or the `Fixed-Percentage` choice.
- `Fixed-Share` will use the amount indicated in the `Max Sizing Limit` field as the position size, always.
Note: With `Fixed-Share` sizing, LTA will >not< check if the balance is sufficient
prior to signaling an entrance.
- `Fixed-Percentage` will use the percentage amount indicated in the `Portfolio Allotment` field as the percentage of available funds to use when calculating the position size. Additionally, with the `Fixed-Percentage` choice, you can set the `Max Sizing Limit` if desired, which will ensure that no position will be entered greater than the amount indicated in the field.
Fractional Share Sizing
If the underlying instrument supports it (typically only cryptocurrencies), share sizing can be
fractionalized. If this is done, the resulting positin size is rounded to `4 digits`. This means any
position with a size less than `0.00005` will be rounded to `0.0000`
Note: Ensure that the underlying instrument supports fractional share sizing prior
to initiating.
Max Sizing Limit
As discussed above, the `Max Sizing Limit` will determine:
- The position size for every position, if `Sizing Method : Fixed-Share` is utilized, or
- The maximum allowed size, regardless of available capital, if `Sizing Method : Fixed-Percentage` is utilized.
Note: There is an internal maximum of 100,000 units.
Initial Capital
Note: There are 2 `Initial Capital` settings; one in LTA's settings and one in the
`Properties` tab. Ensure these two are the same when doing backtesting.
The initial capital field will be used to determine the starting balanace of the strategy, and
is used to calculate the internal data reporting (the data tables).
Portfolio Allotment
You can specify how much of the total available balance should be used when calculating the share size. The default is 100%.
Stops
Note: Stops over-ride `AMS` and `Impose Wait`, and are not restricted to only the
end-of-candle and will occur instantaneously upon their activation. Neither `AMS` nor `Impose Wait` can over-ride a signal from a `Take-Profit`, `Stop-Loss`, or a `Trailing-Stop Loss`.
LTA enhouses three stops that can be configured, a `Take-Profit`, a `Stop-Loss` and a `Trailing-Stop Loss`. The configurations can be set in the settings in percent terms. These exit signals will always over-ride AMS or any other restrictions on position exit.
Their configuration is rather standard; set the percentages you want the signal to be sent at and so it will be done.
Some quick notes on the `Trailing-Stop Loss`:
- The activation percentage must be reached (in profits) prior to the `Traililng-Stop Loss`
from activating the downside protection. For example, if the `Activation Percentage` is 10%, then unless the position reaches (at any point) a 10% profit, then it will not signal any exits on the downside, should it occur.
- The downside price-point is continuously updated and is calculated from the maximum profit reached in the given position and the loss percentage placed in the appropriate field.
Data Tables and Data Output
LTA provides real-time data output through a variety of mechanisms:
- `Position Table`
The `Position Table` displays information about the current position, including:
> Position Duration : how long the position has been open for.
> Indicates if the side is Long or Short, depending on if it is long or short.
> Entry Price: the price the position was entered at.
> Current Price (% Dif): the current price of the underlying and the %-difference between the entry price and the current price.
> Max Profit ($/%): the maximum profit reached in $ and % terms.
> Current PnL ($/%) : the current PnL for the open position.
- `Performance Table`
The `Performance Table` displays information regarding the overall performance of the algorithm since its `Start Date`. These data include:
> Initial Equity ($): The initial equity the algorithm started with.
> Current Equity ($): The current total equity of the account (including open positions)
> Net Profits ($|%) : The overall net profit in $ and % terms.
> Long / Short Trade Counts: The respective trade counts for the positions entered.
> Total Closed Trades: The running sum of the number of trades closed.
> Profitability: The calculation of the number of profitable trades over the total number of
trades.
> Avg. Profit / Trade: The calculation of the average profit per trade in both $ and % terms.
> Avg. Loss / Trade: The calculation of the average loss per trade in both $ and % terms.
> Max Run-Up: The maximum run-up the algorithm has seen in both $ and % terms.
> Max Drawdown: The maximum draw-down the algorithm has seen in both $ and % terms.
> Return-Over-Max-Drawdown: the ratio of the maximum drawdown against the current net profits.
- `Text Output`
LTA will output, if desired, signals to the text output field every time it analysis or performs and action. These messages can include information such as:
"
08:00:00 >> AM Protocol activated ... exiting position ...
08:00:00 >> Exit Order Created for qty: 2, profit: 380 (4.34%)
...
09:30:00 >> Checking conditions ...
09:30:00 >> AM protocol prevented entry ... waiting ...
"
This way, you can keep an eye out on what is happening "under the hood", as it were.
LTA will produce a message at the end of its assessment at the end of each candle interval, as well as when a position is exited due to a `Stop` or due to `AMS` being activated.
Additionally, the `Text Output` includes a initial message, but for space-constraints, this
can be toggled off with the `Blank Text Output` option within LTA's configurations.
For additional information, please refer to the Author's Instructions below.
Komut dosyalarını "algo" için ara
Broadview Algorithmic StudioWelcome! This is the writeup for the Broadview Algorithmic Studio.
There are many unique features in this script.
- Broadview Underpriced & Overpriced
- Broadview Blackout Bollinger Bands
- Trailing Take Profit Suite
- Algorithmic Weights
- VSA Score
- Pip Change Log
- Activation Panel
- Weight Scanner
There are 116 primary inputs that allow users to algorithmically output unique DCA signal-sets. There are 85 inputs that allow users to control individual lengths, levels, thresholds, and multiplicative weights of the script. You will not find any other script with this many inputs, properly strung together for you to produce unlimited strategies for any market. The entire premise for the Broadview Algorithmic Studio is for users to be able to have extensive-cutting-edge features that allow them to produce more strategies, having control over every element that outputs a signal set. The number of unique strategies you can output with this script is VAST, and each continues to follow a safe DCA methodology.
This script is ready for use with 3Commas, interactive brokers, and other means of automation. It provides detailed information on Base Orders and Safety Orders, giving the number, cumulative spending, position average, and remaining balance for each SO in the series. Using this script we will explore the depths of strategic volume scaling, and the algorithms we use to determine spending.
Let me first start by saying the number of safe DCA-friendly signal-sets this script can output is absolutely staggering.
Let's limit the scope just to the Broadview Underpriced & Overpriced and Broadview Dominance indicators.
Each band of the Dominance Suite can be controlled individually with unique lengths, levels, and weights. This means the Dominance Suite can establish Bearish or Bullish dominance, in any market condition, and give it a unique overloading weight. The Broadview Underpriced & Overpriced indicator finally gives us the ability to establish these "market conditions" first with cycles. Of all the cycles this indicator establishes, the two primary are Underpriced & Overpriced. We determine this using a composite Overbought & Oversold with an Exponential Moving Average. So the script can now know, what cycle it is in, who is dominant during that cycle, and exactly how much weight in volume scaling the order should have.
Brand new is the ability for indicators of this level to be able to talk together in a single script. The Broadview Underpriced & Overpriced indicator and the Broadview Dominance indicator can inform one another across multiple vectors, create a unique market snapshot, and give that snapshot a unique weight every bar. The unique weight is compiled in the volume scaling math, thus giving us an automated-strategic-safe and quite efficient volume scaling for every order. In our coming updates we will explore this synergy to its very deepest layers. These indicators can be laced together in many ways, called vectors.
Only in the Algorithmic Studio do we explore these depths and yield those findings, features, and inputs to the user.
Let me take a quick break to explain another area-of-opportunity for our research and development.
The VSA Score is something we've tried before, but until the creation of the Broadview Blackout Bollinger Bands Auto Indicator it was not possible. The concept we want to explore is "Positional Honing". Over time we want users and the script itself to be able to understand the difference between a script-config that produces a high number of Hits, from a configuration that produces a high number of "Misses". The Volume Scaling Accuracy Score uses the BBB Auto Indicator as a heavily reliable, non-repainting, method of determining what the very-best signals for increased volume-scaling are.
Increased volume scaling is denoted by the near-white highlighter line running vertically. This line will either fall inside the BBB Auto Indicator bands (which are hidden), or, they will fall below and outside the BBB Auto bands. If increased spending happens inside the bands it's a "Miss". If increased spending happens below and outside the bands, it's a Hit. Oftentimes misses are actually pretty good spots for extra spending, which helps lower your position average, but Hits are always better. The Hits that the BBB Auto Indicator provides are extremely good.
Let's talk about the Trailing Take Profit Suite. This suite allows us to set a trailing take profit which is a feature that lets one maximize their profits. If the trailing take profit is engaged, then when the regular take profit is hit, it will trigger, denoted in red vertical lines, and the trailing take profit will look for a specified rate of change before it actually takes profit. This usually helps traders in those times when their regular take profit was set too low, allowing them to maximize their profits with a Trailing Take Profit.
For the moment, let's think about our scores. In the dashboard you'll notice a score beginning the Pip Change Log, the VSA Score, and the Activation Panel.
These scores use a new kind of logistic correlation formula where 4 digits are given to activation, rather than 1. This is to allow room for a future concept in AI we call "Deadzones" or you can think of it as impedance. This is not a bias in logistic regression. It's an entirely different concept. A neuron, which a perceptron attempts to mimic, has a bias.. but it also has a sort of electrical resistance. This is because a neuron is individually-alive entity. So a perceptron, as it were, would need to have both a bias and a natural resistance, or deadzone.
It is a lot of fun to watch the scores and how they react during playback. They tend to smooth trends but are also quite quick to correct to accuracy. In the future we will add the deadzones and biases to the scores. This should help both users and the script produce better signal sets. The Pip Change Log is an indicator that measures Rate of Change in Pips. This is one that I am particularly excited to study, as I am a huge fan of ROC. The Activation Panel shows these scores for 4 primary indicators: On Balance Volume, Relative Strength Index, Average Directional Index, and Average True Range.
Having the Pip Change Log, VSA Score, and Activation Panel up on the dashboard with their logistic correlation scores allows traders to study markets and setups quite intimately. The weight scanner at the bottom allows users to track the cumulative applied multiplicative weights during playback. The massive number of inputs, connected vectors of indicators, input-weights, lengths, levels, and thresholds sets up all the algorithmic infrastructure for powerusers to explore every idea and strategy output they could imagine. Also with the connected vector infrastructure we can deepen our indicators in a way where, "How they talk to each other.", comes first in every development conversation.
The Algorithmic Studio is for the Power-user.
These are not basic equations coming together to determine spending. This is a massive multi-layered-perceptron with everything from Trailing-Take-Profits to strategic-automatic algorithmic downscaling. The Broadview Algorithmic Studio gives a home to the poweruser who wants access to everything in a trading and investing AI, right up until the backpropagation. The Broadview Algorithmic Studio, gives users the ability to sit in the chair of the would-be AI.
Thank you.
Orion Algo Strategy v2.0Hi everyone.
I decided to make the latest Orion Algo open to people. I don't have enough time to work on it lately, so I figured it would be best that everyone can have it to work on it. I took out some stuff from the original but it should give an idea on how things work. I made two strategies with this so far so you can use that to come up with your own. I recommend the DCA strategy because it gives you the most bang for Orion Algo's buck. It's pretty good at finding long entries.
Overall I hope you guys like this one. Also, Banano is the best crypto currency :)
-INFO-
Orion Algo is a trading algorithm designed to help traders find the highs and lows of the market before, during, and after they happen. We wanted to give an indicator to people that was simple to use. In fact we created the algorithm in such a way that it currently only needs a single input from the user. Since no indicator can predict the market perfectly, Orion should be used as just another tool (although quite a sharp one) for you to trade with. Fundamental knowledge of price action and TA should be used with Orion Algo.
Being an oscillator, Orion currently has a bias towards market volatility . So you will want to be trading markets over 30% volatility . We have plans to develop future versions that take this into account and adjust automatically for dead conditions. Also, while there are some similarities across all oscillators, what sets ours apart is the prediction curve. The prediction curve looks at the current signal values and gives it a relative score to approximate tops and bottoms 1-2 bars ahead of the signal curve. We also designed a velocity curve that attempts to predict the signal curve 2+ bars ahead. You can find the relative change in velocity in the Info panel. The bottom momentum wave is based on the signal curve and helps find overall market direction of higher time-frames while in a lower one.
Settings and How to Use them:
User Agreement – Orion Algo is a tool for you to use while trading. We aren’t responsible for losses OR the gains you make with it. By clicking the checkbox on the left you are agreeing to the terms.
Super Smooth – Smooths the main signal line based on the value inside the box. Lower values shift the pivot points to the left but also make things more noisy. Higher values move things to the right making it lag a bit more while creating a smoother signal. 8 is a good value to start with.
Theme – Changes the color scheme of Orion.
Dashboard – Turns on a dashboard with useful stats, such as Delta v, Volatility , Rsi , etc. Changing the value box will move the dashboard left and right.
Prediction – A secondary prediction model that attempts to predict a reversal before it happens (0-2bars). This can be noisy some times so make your best judgement. Curve will toggle a curve view of the prediction. Pivots will toggle bull/bear dots.
∆v – Delta v (change in velocity). This shows momentum of the signal. Crossing 0 signals a reversal. If you see the delta v changing direction, it may signify a reversal in the several bars depending on the overall momentum of the market.
Momentum Wave – Uses the signal as a macro trend indicator. Changes in direction of the wave can signify macro changes in the market. Average will toggle an averaging algorithm of the momentum waves and makes it easy to understand.
-STRATEGIES-
Simple - Just buy and sell on the dots
DCA - Uses the settings in the script for entries. If a buy dot appears then it will buy, if the price goes below the percentage it will wait for another dot before entering. This drastically improves DCA potential.
MyAlgoPLEASE READ THE ENTIRE POST BEFORE PURCHASING & USING THE MyAlgo Tool. Saves you and me some time in emails and messages. :)
This is the official version of MyAlgo
PLEASE UNDERSTAND THAT THIS IS A DIFFERENT AND SEPARATE PRODUCT AND SCRIPT FROM "MyAlgo SLIM" FROM THE MyAlgo TRADING TOOL SERIES
Description
Buy & Sell Alerts can be set on all Tickers. This includes, but is not limited to Crypto, Commodities , FOREX, Equities and Indices. Also all candle Types are compatible.
Recommended Time-frames - Due to the complexity of MyAlgo-SLIM the user has a choice between three algorithms and is like that able to trade on all timeframes with the highest returns.
MyAlgo combines many different aspects at the same time, scans multiple other Algorithms and comes to a conclusion based on over 1350 lines of code.
It is based on Divergences, Elliott Waves , Ichimoku , MACD , MACD Histogram, RSI , Stoch , CCI , Momentum, OBV, DIOSC, VWMACD, CMF and multiple EMAs.
Every single aspect is weighted into the decision before giving out an indication.
Most buy/sell Algorithms FAIL because they try to apply the same strategy to every single chart, which
are as individual as humans. To conquer this problem, MyAlgo has a wide range of settings and variables which can be easily
modified.
To make it a true strategy, MyAlgo has as well settings for Take Profit Points and Stop
Losses. Everything with an Alert Feature of course so that FULL AUTOMATION IS POSSIBLE.
I know from experience that many people take one Algorithm and are simply too LAZY to add multiple Algorithms to make a rational choice. The result of that is that they lose money, by following blatantly only one Algorithm.
MyAlgo has additional 15 Indicators, perfect for all markets, which can be turned on and off individually.
Side Notes
MyAlgo is being updated and upgraded very frequently to suit the requests of our customers.
This is not financial advice. Please read our disclaimer before using.
Anything below this sentence will be Updates regarding MyAlgo
MyAlgo-SLIMPLEASE READ THE ENTIRE POST BEFORE PURCHASING & USING THE MyAlgo-SLIM Tool. Saves you and me some time in emails and messages. :)
This is the official version of MyAlgo-SLIM
Description
Buy & Sell Alerts can be set on all Tickers. This includes, but is not limited to Crypto, Commodities , FOREX, Equities and Indices. Also all candle Types are compatible.
Recommended Time-frames - Due to the complexity of MyAlgo-SLIM the user has a choice between three algorithms and is like that able to trade on all timeframes with the highest returns.
MyAlgocombines many different aspects at the same time, scans multiple other Algorithms and comes to a conclusion based on over 1350 lines of code.
It is based on Divergences, Elliott Waves , Ichimoku , MACD , MACD Histogram, RSI , Stoch , CCI , Momentum, OBV, DIOSC, VWMACD, CMF and multiple EMAs.
Every single aspect is weighted into the decision before giving out an indication.
Most buy/sell Algorithms FAIL because they try to apply the same strategy to every single chart, which
are as individual as humans. To conquer this problem, MyAlgo has a wide range of settings and variables which can be easily
modified.
To make it a true strategy, MyAlgo has as well settings for Take Profit Points and Stop
Losses. Everything with an Alert Feature of course so that FULL AUTOMATION IS POSSIBLE.
I know from experience that many people take one Algorithm and are simply too LAZY to add multiple Algorithms to make a rational choice. The result of that is that they lose money, by following blatantly only one Algorithm.
MyAlgo has additional 15 Indicators, perfect for all markets, which can be turned on and off individually.
Side Notes
MyAlgo is being updated and upgraded very frequently to suit the requests of our customers.
This is not financial advice. Please read our disclaimer before using.
Anything below this sentence will be Updates regarding MyAlgo-SLIM
Order Blocks v2Order Blocks v2 – Smart OB Detection with Time & FVG Filters
Order Blocks v2 is an advanced tool designed to identify potential institutional footprints in the market by dynamically plotting bullish and bearish order blocks.
This indicator refines classic OB logic by combining:
Fractal-based break conditions
Time-level filtering (Power of 3)
Optional Fair Value Gap (FVG) confirmation
Real-time plotting and auto-invalidation
Perfect for traders using ICT, Smart Money, or algorithmic timing models like Hopplipka.
🧠 What the indicator does
Detects order blocks after break of bullish/bearish fractals
Supports 3-bar or 5-bar fractal structures
Allows OB detection based on close breaks or high/low breaks
Optionally confirms OBs only if followed by a Fair Value Gap within N candles
Filters OBs based on specific time levels (3, 7, 11, 14) — core anchors in many algorithmic models
Automatically deletes invalidated OBs once price closes through the zone
⚙️ How it works
The indicator:
Tracks local fractal highs/lows
Once a fractal is broken by price, it backtracks to identify the best OB candle (highest bullish or lowest bearish)
Validates the level by checking:
OB type logic (close or HL break)
Time stamp match with algorithmic time anchors (e.g. 3, 7, 11, 14 – known from the Power of 3 concept)
Optional FVG confirmation after OB
Plots OB zones as lines (body or wick-based) and removes them if invalidated by a candle close
This ensures traders see only valid, active levels — removing noise from broken or out-of-context zones.
🔧 Customization
Choose 3-bar or 5-bar fractals
OB detection type: close break or HL break
Enable/disable OBs only on times 3, 7, 11, 14 (Hopplipka style)
Optional: require nearby FVG for validation
Line style: solid, dashed, or dotted
Adjust OB length, width, color, and use body or wick for OB height
🚀 How to use it
Add the script to your chart
Choose your preferred OB detection mode and filters
Use plotted OB zones to:
Anticipate price rejections and reversals
Validate Smart Money or ICT-based entry zones
Align setups with algorithmic time sequences (3, 7, 11, 14)
Filter out invalid OBs automatically, keeping your chart clean
The tool is useful on any timeframe but performs best when combined with a liquidity-based or time-anchored trading model.
💡 What makes it original
Combines fractal logic with OB confirmation and time anchors
Implements time-based filtering inspired by Hopplipka’s interpretation of the "Power of 3"
Allows OB validation via optional FVG follow-up — rarely available in public indicators
Auto-cleans invalidated OBs to reduce clutter
Designed to reflect market structure logic used by institutions and algorithms
💬 Why it’s worth using
Order Blocks v2 simplifies one of the most nuanced parts of SMC: identifying clean and high-probability OBs.
It removes subjectivity, adds clear timing logic, and integrates optional confluence tools — like FVG.
For traders serious about algorithmic-level structure and clean setups, this tool delivers both logic and clarity.
⚠️ Important
This indicator:
Is not a signal generator or financial advice tool
Is intended for experienced traders using OB/SMC/time-based logic
Does not predict market direction — it provides visual structural levels only
Altcoins DCA ScalperIntroduction
The Altcoins DCA Scalper is a Pine Strategy Script designed to automate Altcoins trading through 3Commas integration. It implements a Dollar-Cost Averaging (DCA) strategy that expands upon 3Commas' standard DCA capabilities, helping to manage risk while trading both long and short positions automatically.
This tool aims to assist both beginners exploring automated trading and experienced 3Commas users seeking dynamic DCA automation. The script is specifically designed for the 1-minute timeframe , where it has shown a good balance between performance and risk management. Complete setup typically takes less than 10 minutes, with a detailed guide making configuration straightforward for users of all experience levels.
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🔶 What is DCA?
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Dollar-cost averaging (DCA) refers to the practice of gradually increasing your position size at lower prices when trading long, or at higher prices when trading short, to achieve a better average entry price if the market moves against the initial entry . Instead of investing all capital at once, which could result in a significant drawdown if the price moves unfavorably, DCA spreads entries across different price levels to help manage potential drawdowns as they occur.
In this script, DCA is implemented through a system that:
🔹 Triggers safety orders only when/if needed (if take profit isn't reached quickly)
🔹 Dynamically adjusts order sizing based on market volatility
🔹 Automatically reduces take profit targets after each DCA order to increase the likelihood of a positive outcome
🔹 Can handle drawdowns depending on market volatility and settings
The images below illustrate two scenarios: one where an entry reaches the take profit directly, without activating DCA orders, and another where DCA is utilized, with the order closing positively after two DCA orders.
Case 1: Order closes in profit after entry
Case 2: Order closes in profit after 2 DCA orders (dynamically placed based on trend and volatility)
This DCA implementation aims to enhance standard 3Commas DCA by adding market-adaptive features while maintaining risk management principles.
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🔶 Could this strategy script benefit you?
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This script may be helpful if you are:
✅ Looking to automate your trading through 3Commas integration while maintaining full control of your assets
✅ Wanting to enhance 3Commas' standard DCA with market-adaptive features that consider:
Multi-timeframe trend analysis
Real-time volatility assessment
Dynamic safety order sizing and timing
✅ Seeking to minimize chart monitoring through full automation of:
Entry and exit decisions
Safety order management
Risk controls
✅ Interested in comprehensive performance tracking with:
Real-time position metrics
Detailed backtesting capabilities
Risk/reward analysis
Backtesting Metrics (script performance over the backtesting period - which is approx. 15 days on the 1min timeframe with the TradingView Pro Plan):
Current/Open Deal Metrics (the deal is currently under DCA, and waiting for further actions to close):
✅ Looking for trading automation that remains easy to set up and use
Note: While this script provides trading automation, successful trading requires proper education, risk management, and regular performance monitoring. No automated tool can guarantee trading success or profits.
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🔶 How it Works
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The Altcoins DCA Scalper provides trading automation through:
Market Analysis
* Multi-timeframe trend analysis (1m to 1d) for market direction and entry validation
* Volatility assessment (1h, 4h, 24h) benchmarked against TOTAL3 (excluding Top10 Altcoins and Stablecoins)
* Real-time adjustment of DCA parameters based on:
* Current volatility class (low/medium/high) vs. overall Altcoins market
* Market trend strength
* Price action dynamics
Trading Execution
* Position opening aligned with detected market trends
* "Beast Mode" base order sizing that increases position size during strong trends
* Dynamic take-profit targets that automatically reduce after each safety order to increase the likelihood of positive exits
* Dynamic DCA with safety orders that can:
* Adapt timing based on volatility
* Scale order sizes based on market conditions
* Handle 30-50% drawdowns depending on volatility class
* Execute up to 6 safety orders per position
Risk Management
* Emergency exits during extreme market events:
* "Black Swan" protection for long positions
* "God-Candle" protection for short positions
* Configurable stop-loss with volatility-based placement
* Trend-switch management with automated position reversal
* Position aging controls to prevent capital lock-up
* Leveraged trading protection with a pre-liquidation exit system
Integration & Automation
* Quick setup with two 3Commas bots (typically under 10 minutes)
* Fully automated signal generation and execution through 3Commas
* Detailed performance tracking including:
* Real-time position metrics
* DCA depth analysis
* Win rate and ROE calculations
* Pre-configured settings optimized for most pairs
* Multiple customization options for experienced users
Note: While this strategy employs automation and risk management, trading always carries the risk of loss. No system can guarantee profits, and market conditions significantly impact performance. Always do your own research and monitor your positions closely.
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How to Use
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Setting up the Altcoins DCA Scalper is quick and facilitated by the User Interface:
1️⃣ 3Commas/TradingView Setup
* Create two 3Commas accounts if using the FREE plan:
* One account for Long Bot
* One account for Short Bot
* This split allows full functionality while staying within 3Commas' free tier limits
* You do not need two separate accounts if you have a Paid 3Commas subscription
* While a free TradingView account works with the script, it limits you to one trading pair and a 4-day backtesting history. A paid TradingView subscription removes these limitations (such as the "Essential" plan).
2️⃣ Bot Configuration
* Create one Long and one Short DCA Bot in 3Commas
* Follow the setup guide available in the script itself for hassle-free configuration
* Copy Bot IDs and Email Token for script connection
* No complex settings needed - the script manages all DCA parameters by itself
3️⃣ Script Implementation
* Apply the script to your TradingView charts
* Use the built-in backtesting to analyze performance on different pairs
* Focus on USDT.P futures pairs with good volatility
4️⃣ Trading Activation
* Create TradingView alerts for each trading pair you want to activate
* Example: Set an alert for BINANCE: XRPUSDT.P following the in-script guide
* The script automatically manages all aspects:
* Entry and exit decisions
* DCA execution
* Risk management
* Position monitoring
Capital Requirements
* Important: Ensure sufficient capital to cover all activated pairs
* Consider volatility class when allocating capital to specific pairs
Once setup is complete, the script operates fully automatically while you maintain complete control of your funds through 3Commas and your exchange.
Note: While the setup is straightforward, always start with a small number of pairs and monitor performance before expanding. Trade responsibly and never risk more than you can afford to lose.
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Explaining the Settings
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The Altcoins DCA Scalper offers mulitple customization options during the setup process. All settings include detailed tooltips and default values.
Core Settings Sections:
1️⃣ 3Commas Connection
* Bot IDs and Email Token configuration
* Leverage settings (1x to 5x supported)
* Detailed 3Commas bot setup guide included
* Automatic bot control configuration
2️⃣ Trading Parameters
* Capital allocation per trade
* Timeframe verification
* Alert system setup
* Backtesting period control
* Performance tracking preferences
3️⃣ Advanced Features
🔹 Risk Management Suite
* Emergency exit controls (to strengthen protection against extraordinary market events)
* Customizable stop-loss system
* Trend-based exit management
* Position aging controls
* Liquidation protection features
* Advanced DCA controls
🔹 Performance Analytics
* Real-time position monitoring
* Comprehensive backtesting metrics
* DCA depth analysis
* Win rate calculations
* Capital efficiency tracking
🔹 Technical Optimizations
* Exchange minimum order adjustment
* Trading pair name override capability
* System stability controls
* Error handling mechanisms
🔹 Interface Customization
* Theme selection
* Chart overlay options
* Warning display preferences
* Performance metrics visibility
All settings come pre-configured but can be fully customized based on your trading preferences and risk tolerance. The script includes tooltips and setup guides for each option.
Note: While default settings may be tested, market conditions vary and all trading involves risk. Monitor performance and adjust settings according to your risk management requirements.
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Frequently Asked Questions
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Here are some common questions you may have, and our answers:
❓ Is this tool only for experts? I'm new to algo trading, can I use it?
No, the Altcoins DCA Scalper could be used by both beginners and experienced traders. The setup process is guided, and the algorithm handles all the calculations in the background.
❓ I'm not familiar with 3Commas. Is that a problem?
While the script is designed to work with 3Commas, a step-by-step guide is provided within the script to help you set up your 3Commas accounts and bots, if needed.
❓ Do I need to constantly monitor the script after it's set up?
No, after the initial setup and configuration, the script operates autonomously. It handles all aspects of trading including entries, exits, DCA management, and risk controls. However, we recommend:
* Checking performance metrics daily
* Reviewing position statistics weekly
* Adjusting pair selection monthly based on performance
* Monitoring overall market conditions that might require adjustments
❓ Can I use it with leverage?
Yes, the script is designed to work with leverage up to 5x on perpetual futures pairs (USDT.P). It includes specific features for leveraged trading:
* Dynamic safety order placement based on distance to liquidation
* Pre-liquidation exit system to minimize exchange fees
* Adjustable take-profit targets optimized for leveraged positions
* Emergency exit system for extreme market movements
* Optional risk controls specific to leverage:
* Automatic exit in the liquidation danger zone
* Position size scaling based on leverage level
* Safety order adjustments for different leverage settings
While leverage can amplify returns, it also increases risk. We recommend starting with lower leverage (2x), or no leverage at all, until familiar with the script's operation.
❓ Does this script guarantee profits?
No, no script or trading strategy can guarantee profits. The Altcoins DCA Scalper provides a framework for implementing an automated DCA strategy, but your success will depend on many different factors and conditions.
❓ Do I need to understand the complex algorithms used in the script?
No, it’s not necessary. The logic is handled by the script, and you do not need to understand every detail to use it effectively. However, a basic knowledge of DCA concepts will be beneficial.
❓ Can I use this script with spot or leveraged trades?
The script is optimized for USDT.P pairs (perpetual futures) with leverage up to 5x. This allows:
* Automatic long/short position management
* Increased capital utilization
* Full DCA functionality without holding the underlying assets
* Enhanced risk management features specific to futures
While spot trading is possible, it requires holding underlying assets for shorts and doesn't access the script's full capabilities.
❓What timeframe should I use?
This script is optimized for the 1-minute timeframe , which is the recommended setting for the best balance between performance, capital efficiency, and risk. While we recommend using the tool on the 1 minute TF, it would work on other timeframes too.
❓ What happens if my internet/computer goes down?
Since the script sends signals from Tradingview to 3Commas (which executes trades on your exchange), your positions and DCA management continue to function even if your TradingView chart is closed or your computer is off. The script only needs to be active to generate new signals.
❓ How are the DCA parameters determined?
The script dynamically adjusts DCA parameters based on:
* The pair's volatility class (compared to the overall altcoin market)
* Current market conditions and volatility
* Position direction (long/short)
* Leverage settings
* Number of safety orders already executed
This allows for adaptive/dynamic DCA compared to static or %-based parameters.
❓ What exchanges are supported?
The script works with any exchange supported by 3Commas for futures trading (approximately 15 different crypto Exchanges). However, it's optimized for Binance Futures (USDT.P pairs) due to its high liquidity and for consistency.
❓ What happens during extreme market conditions?
The script includes some (optional) protective measures that can be activated:
* Emergency exits during sharp and abnormal market moves
* Automatic adjustment of DCA parameters during high volatility
* Position closure on significant trend changes
* Special handling of aged positions
These features aim to protect capital during unusual market conditions.
❓How many pairs can I trade simultaneously?
This depends on your total capital. As a general indication, define the number of pairs to activate based on:
* Total available capital
* Desired position size per pair
* Risk tolerance
* Pairs' volatility class
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Final Thoughts
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We believe that your trading performance will greatly depend on your selection of appropriate trading pairs for this script (high volatility), and your commitment to regularly monitoring its performance and adjust the settings, rather than on the script alone.
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⚠️ Risk Disclaimer
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Remember that trading involves risk, and most day traders experience losses. This script is for educational and informational purposes only. Past performance does not guarantee future results. This is not financial advice, and you should always do your own research (DYOR). Trade responsibly with capital you can afford to lose.
The Altcoins DCA Scalper is an independent tool and is not endorsed, connected, or validated by TradingView.
3Commas is a third-party service, and TradingView is not responsible for the 3Commas integration or the performance of 3Commas bots. You are solely responsible for the security and management of your 3Commas account. Do not share your 3Commas access credentials (like login information, Bots-ID, Email Token) with anyone. The Author of the script has no access to such information, and nobody (but you) should.
NexTrade
Overview of NexTrade: The Future of Crypto Trading
Introduction
NexTrade is a cutting-edge algorithmic trading platform designed to optimize cryptocurrency trading strategies. Developed by myself, a software engineer with a passion for quantitative development. Over the past year, I have focused on learning and applying quantitative techniques to the crypto space, ultimately crafting a platform that leverages advanced market analysis, automation, and robust risk management to help investors maximize returns while minimizing risk. NexTrade is engineered to help you capitalize on market movements in a fast-paced and highly competitive space, that is Cryptocurrency.
Key Features and Advantages
Sophisticated Market Analysis: NexTrade uses a comprehensive market analysis framework that examines historical trends, price movements, and market conditions across multiple cryptocurrency exchanges. The algorithm identifies trading opportunities by chart analysis on higher timeframes in order to follow trends, allowing it to execute trades at optimal moments.
Multi-Exchange Integration: NexTrade connects to multiple leading cryptocurrency exchanges, such as Binance, Kraken, and Coinbase Pro, to ensure access to diverse liquidity pools. This multi-exchange connectivity allows the platform to execute trades at the most favorable prices, optimizing profitability and minimizing slippage across various platforms. However, we suggest using the exchange with lowest fees possible.
Risk Management: NexTrade’s risk management features such as Stop Losses, ATR Trailing SL, and ADX chop indicator allows us to ensure we are effectively managing our risk.
Backtesting and Optimization: Before going live, NexTrade’s trading strategies undergo rigorous backtesting using historical market data. This enables users to see how strategies would have performed under various conditions, providing transparency and confidence in the platform’s potential for generating consistent returns. Ongoing optimization ensures that strategies evolve in response to market changes.
Real-Time Performance Monitoring: Users have access to detailed, real-time performance reports, tracking key metrics such as trades executed, profits, losses, and overall portfolio performance. This transparency allows investors to make informed decisions and monitor their investments closely at any time.
Market Opportunity
The cryptocurrency market continues to experience rapid growth, with trillions of dollars in trading volume annually. However, it is also notoriously volatile, creating both risk and reward opportunities for traders. To successfully navigate this market, investors need sophisticated tools that can automate the trading process and optimize decisions based on accurate market analysis.
NexTrade was developed to address this need. With its combination of data-driven market analysis, automated execution, and risk management, NexTrade is positioned to help investors gain an edge in a market that is often unpredictable and challenging. The platform offers a reliable, scalable solution to crypto trading, designed for both beginners and seasoned professionals.
Why Invest in NexTrade?
Scalable and Flexible: Whether you’re trading small amounts or large volumes, NexTrade can scale to accommodate your needs. The platform supports multiple exchanges, giving users the flexibility to diversify and grow their investments. Users can start with as low as $100!
Risk-Adjusted Returns: By focusing on risk management, NexTrade aims to deliver returns that are balanced with the level of risk the investor is willing to accept. The algorithm continuously adjusts trading strategies to align with market conditions, maximizing the potential for profits while minimizing the likelihood of significant losses.
24/7 Trading: The cryptocurrency market operates around the clock, and NexTrade is designed to take advantage of this. Its automated nature means that it can execute trades at any time, without the need for human intervention.
Conclusion
NexTrade offers a sophisticated yet accessible solution for investors looking to capitalize on the growth of the cryptocurrency market. With its focus on data-driven analysis, automated trade execution, and advanced risk management, NexTrade empowers investors to achieve optimal returns while managing risk effectively. Whether you are new to crypto or an experienced trader, NexTrade provides the tools needed to stay competitive and succeed in a fast-moving market.
By investing in NexTrade, you are gaining access to a proven algorithmic trading platform that has the potential to enhance your crypto trading strategy and deliver consistent results. The future of cryptocurrency trading is automated, risk-managed, and optimized—and NexTrade is leading the way.
If users wish the enable the chop detector on the bot, which uses ADX, they can turn it on in the settings after the strategu is added to the chart. By default, it is set to false.
Spot Martingale KuCoin - The Quant ScienceINTRODUCTION
Backtesting software of the Spot Martingale algorithm offered by the KuCoin exchange.
This script replicates the logic used by the KuCoin bot and is useful for analyzing strategy on any cryptocurrency historical series.
It's not intended as an automatic trading algorithm and does not offer the possibility of automatic order execution.
The trader will use this software exclusively to research the best parameters with which to work on KuCoin.
LOGIC OF EXECUTION
The execution of orders is composed as follows:
1) Start Martingale: initial order
2) Martingale-Number: orders following Start Martingale
(A) The software is designed and developed to replicate trading without taking into account technical indicators or particular market conditions. The Initial Order (Start Martingale) will be executed immediately the close of the previous Martingale when the balance of market orders is zero. It will use the capital set in the Properties section for the initial order.
(B) After the first order, the software will open new orders as the price decreases. For orders following Start Martingale, the initial capital, multiplier, and number of orders in the exponential growth context are considered. The multiplier is the factor that determines the proportional increase in capital with each new order. The number of orders, indicates how many times the multiplier is applied to increase the investment.
Example
To find out the capital used in Martingale order number 5, with a Multiple For Position Increase equal to 2 and a starting capital of $100, the formula will be as follows:
Martingale Order = ($100 * (2 * 2 * 2 * 2 * 2)) = $100 * 32 = $3.200
(C) A multiplier is used for each new order that will increase the quantity purchased.
(D) All previously open orders are closed once the take profit is reached.
USER MANUAL
The user interface consists of two main sections:
1. Settings
Percentage Drop for Position Increase (0.1-15%) : percentage distance between Martingale orders. For example, if you set 5% each new order will be opened after a 5% price decrease from the previous one.
Max Position Increases (1-15) : number of Martingale orders to be executed after Start Martingale. For example, if you set 10, up to10 orders will be opened after Start Martingale.
Multiple For Position Increase (1-2x) : capital multiplier. For example, if you set 2 each for each new order, the capital involved will be doubled, order by order.
Take Profit Percentage (0.5-1000%) : percentage take profit, calculated on the average entry price.
2. Date Range Backtesting
The Date Range Backtesting section adjusts the analysis period. The user can easily adjust the UI parameters, and automatically the software will update the data.
LIMITATIONS OF THE MODEL
Although the Martingale model is widely used in position management, even this model has limitations and is subject to real risks during particular market conditions. Knowing these conditions will help you understand which asset is best to use the strategy on.
The main risks in adopting this automatic strategy are 2:
1) The price falls below our last order.
It happens during periods of strong bear-market in which the price collapses abruptly without experiencing any pullback. In this case the algorithm will enter a drawdown phase and the strategy will become a loser. The trader will then have to consider whether to wait for a price recovery or to incur a loss by manually closing the algorithm.
2) The price increases quickly.
It happens during periods of strong bull-market in which the price rises abruptly without experiencing any pullback. In this case the algorithm will not optimize order execution, working only with Start Martingale in the vast majority of trades. Given the exponential nature of the investment, the algorithm will in this case generate a profit that is always less than that of the reference market.
The best market conditions to use this strategy are characterized by high volatility such as correction phases during a bull run and/or markets that exhibit sideways price trends (such as areas of accumulation or congestion where price will generate many false signals).
FEATURES
This script was developed by including features to optimize the user experience.
Includes a dashboard at launch that allows the user to intuitively enter backtesting parameters.
Includes graphical indicator that helps the user analyze the behavior of the strategy.
Includes a date period backtesting feature that allows the user to adjust and choose custom historical periods.
DISCLAIMER
This script was released using parameters researched solely for the BTC/USDT pair, 4H timeframe, traded on the KuCoin Exchange (2017-present). Do not consider this combination of parameters as universal and usable on all assets and timeframes.
Risk Reward Calculator [lovealgotrading]
OVERVIEW:
This Risk Reward Calculator strategy can help you maximize your RR value with help of algorithmic trading.
INDICATOR:
I wanted to setup my trades more easier with this indicator, I didn't want to calculate everytime before orders, with help this indicator we can calculate R:R value, avarage price, stoploss price, take-profit price, order prices, all position cost and more ...
Our strategy is a risk revard calculation indicator that is made easy to use by using visualized lines and panels, and also has algorithmic trading support.
With the help of this indicator, we can quickly and easily calculate our risk reward values and enter the positions.
If we want to ensure that our balance grows regularly while trading in the stock market, we need to manage the risks and rewards otherwise we may fall below our initial balance at the end of the day, even if we seem to be winning.
What is the Risk-Reward value ?
This value is a value that shows how many times the amount of risk we take when entering the position is successful, we will earn.
- For example, you risked $100 while entering the trade, so if your trade stops, you will lose 100 $.
Your Risk-Reward(RR) value is 2 means that if your position is successful, you will have 200 $ in your pocket.
A trader's success is determined by the amount of R he earns monthly or yearly, not how much money he makes.
What is different in this indicator ?
I want to say thank you to © EvoCrypto. His Calculator (weighted) – evo indicator helped me when I was developed my indicator.
I want to explain what I have improved:
1-In this strategy, we can determine the time period in which we want to open our positions.
2-We can open a maximum of 4 positions in the same direction and close our positions at a single level. StopLoss or TakeProfit
3-This indicator, which works in the form of a strategy, shows where our positions have been opened or closed. With the help of this, it helps us to determine our strategy in our future positions more accurately.
4-The most important improvement is that we do not miss our positions with the help of alarms (WEB HOOK). if we want, we receive by quickly connecting all these positions to our robot, the software can enter and exit the position while we are busy.
IMPLEMENTATION DETAILS – SETTINGS:
1 - We can set the start and end dates of the positions we will take.
2- We can set our take profit, stoploss levels.
3- If your trade is stopped, we can determine the amount of the trade that we will lose.
4- We can adjust our entry levels to positions and our position sizes at entry levels.
(Sum of positions weight must be 100%)
5- We can receive our positions even if we are busy with the help of algorithmic trading. For this, we must paste our Jshon codes into the fields specified in the settings panel.
6- Finally, we can change the settings we want and don't want to have in our visual elements.
Let's make a LONG side example together
We have determined our positions to enter stoploss, take profit and long positions. We did not forget to set the start time of our strategy
Our strategy appear on the graph as follows.
Our strategy has calculated the total position size, our R-R value, the distance of the current price to the stop and take profit levels, in short, a lot of things we could look visually.
Notes:
If you're going to connect this bot to an automatic Long or Short direction,
Don’t forget! you need to Webhook URL,
Don’t miss paste this code to your message window {{strategy.order.alert_message}}
ALSO:
If you have any ideas what to add to my work to add more sources or make calculations cooler, feel free to write me.
Cloud X MesoHello there fellow Traders!
Thanks for stopping by, so today I will be covering everything you need to to know about this TradingView strategy.
Below I will discuss everything you need to know about this strategy so you can get a full grasp of what the strategy is, the features, what it does, how it works, the benefits of how this strategy can help you, and the results.
What is Cloud X Meso?
-Cloud X Meso is a strategy that consists of 7 indicators to all line up for total confluence to take a buy or sell once all 6 indicators conditions are met. This strategy does not repaint and doesn't require any technical analysis to be used. The strategy can be used on any timeframe, and any instrument.
-I have optimized many different variations for different types of trading instruments of this strategy ready to be used. The difference of this strategy is that these variations do not need any reoptimization to keep up with recent market conditions since there are hardly any inputs used, which prevents common overfitting problems. The main goal was for this strategy to be automated, as well as plug and play or you can officially consider this as set and forever forget.
What does this strategy do?
-The main goal for this strategy is to catch long or short term trends by waiting for all 7 indicators to line up as well as using customized trading times to trade certain sessions where there is high amounts of volume in the market. This strategy doesn't always need to have a clear trending market, since it can also catch short term trends in choppy markets as well. Overall, the strategy tell you when it buys, sells, and exits after all conditions are met.
How does the strategy work?
-The way that this strategy works is when all of the indicators confluences are met. Next, a buy or sell label will print and the candles colors will color blue or red to show that the trade is in the buy or sell position followed along with a magenta colored line which is the trailing stop to follow the trade until the trade exits from the trailing stop being hit or if the strategies exit condition is met.
-The strategy does have a set Take Profit target since it relies on the trailing stop to end the trade. This is beneficial so you can catch any size of a trend move when the strategy is in high volume market sessions. You catch these trends by customizing the settings to toggle on or off certain indicators, functions, configuring a customized trading time, and toggling on or off certain trading days to make a specific approach for fine tuning a pair to trade in a certain time window with high amounts of volume to catch trending moves whether it be a long or short term trend.
Below I will explain each functionality of the strategy for you to better understand the different ways you can adjust the settings of this strategy.
Backtest Settings:
-You can use these settings to determine a start / end date of what results you would like to see in the strategy tester.
-You can determine the $ amount you would like to see on strategy testers results to be in terms of net profit and max drawdown.
-You can choose whether you want the strategy to take buys only, sells only, or buys and sells.
Automation:
-Compatible with Pine Connectors to fully automate this strategy for MT4/5
-It uses a % based risk when placing trades so you won't have to calculate a proper lot size or dollar amount.
-You can also put the symbol of what that strategy will be trading on so you know what pair its trading.
Custom Trading Times:
-When you customize a trading time for the strategy to trade in, the background will turn blue for that specific time window, and you can use the "Session Exit" function to have trades close once the time window ends when toggled on, or you can have the existing trades close on their own when "Session Exit" is toggled off.
Dynamic Trailing:
-The algorithm uses a volatility based indicator to determine proper stop loss placement depending on how volatile the market is. This will prevent you from guesstimating if your stop loss is too big or too small.
-When Dynamic trailing is off, then the strategy will use a Risk Reward based stop loss to trail everytime the trades hits a new Risk Reward target.
-You can also toggle on or off for the stop loss to go to break even once the trade hits a 1:1 Risk Reward.
Directional Bias Settings:
-This indicator is the main directional bias that uses a multi timeframe function to determine the directional bias, you can also use the Exponential Moving Average as a form of directional bias instead, or you can use both of them to work together to find the directional bias. You can also toggle each one on or off
Entry / Exit Settings:
-This indicator also uses a multi timeframe function but it determines the entry and exit for a trade when all confluences are met. You can also toggle the entry and exit functions on or off.
1 Candle Rule:
-This feature is inspired by No Nonsense Forex (NNFX) the main function of this is if your entry doesn't meet all the entry conditions, then the strategy will wait 1 more candle to meet all the entry conditions to take a trade.
No Trade Zone:
-This feature will uses a Volume based indicator to filter out low volume markets. The candles will turn grey to indicate the algorithm not to take trades, and you can also customize the sensitivity of how strong this indicator will filter out the low volume in the markets.
Indicator functions
Each indicator plays a certain role and also meets certain conditions when a buy or sell trade is placed. I will reveal 3 out of 7 of the indicators used to preserve the uniqueness of this strategy but overall, the logic of this strategies main goal is to ride long or short terms trends while getting dynamic Risk Reward trades.
-The first indicator that the strategy uses an Exponential Moving Average that is customizable, and is used as a form of a filter for either a long or short term directional bias to filter out false signals to help the algorithm trade with the trend.
-The second indicator that the strategy uses is an Oscillator which is the Wavetrend and this indicators functionality for the algorithm is used for the its buy and sell signals to line up with all the other indicators for confluence. This indicator can also be toggled on or off for you own preference
-The third indicator used is the Volume indicator, and this is used to give the other indicators the green light to enter a trade if there are high amounts of volume in the market.
What are the benefits of using this algorithm?
Stress Free Trading:
-Once automated, you will no longer need to stare at the charts all day, as well as trying to execute the trades on time or worried that you missed a setup. Or you can choose to take trades manually when a buy or sell signal comes up
Stress Free Risk Management:
-All you have to do is provide a risk % and the algorithm will do the rest of the work calculating the stop loss, exiting trades, etc. No more needing to find the right lot size, or dollar amount, all in all the strategy will manage the trades for you.
Psychology:
-when you choose to have a systematic trading approach, it eliminates a lot bad habits from human nature
What are the results like?
-I have multiple different variations of results of this strategy, but I will share one of the results.
Here is a screenshot below of what this strategy can do from just one of the variations.
The backtest below was done with another variation on simulating a 100k account risking 0.50% per trade.
Thank you for taking the time to read through this whole guide, and I hope this helped you better understand the strategy.
iMoku (Ichimoku Complete Tool) - The Quant Science iMoku™ is a professional all-in-one solution for the famous Ichimoku Kinko Hyo indicator.
The algorithm includes:
1. Backtesting spot
2. Visual tool
3. Auto-trading functions
With iMoku you can test four different strategies.
Strategy 1: Cross Tenkan Sen - Kijun Sen
A long position is opened with 100% of the invested capital ($1000) when "Tenkan Sen" crossover "Kijun Sen".
Closing the long position on the opposite condition.
There are 3 different strength signals for this strategy: weak, normal, strong.
Weak : the signal is weak when the condition is true and the price is above the 'Kumo'
Normal : the signal is normal when the condition is true and the price is within the 'Kumo'
Strong : the signal is strong when the condition is true and the price is below the 'Kumo'
Strategy 2: Cross Price - Kijun Sen
A long position is opened with 100% of the invested capital ($1000) when the price crossover the 'Kijun Sen'.
Closing the long position on the opposite condition.
There are 3 different strength signals for this strategy: weak, normal, strong.
Weak : the signal is weak when the condition is true and the price is above the 'Kumo'
Normal : the signal is normal when the condition is true and the price is inside the 'Kumo'
Strong : the signal is strong when the condition is true and the price is below the 'Kumo'
Strategy 3: Kumo Breakout
A long position is opened with 100% of the invested capital ($1000) when the price breakup the 'Kumo'.
Closing the long position with a percentage stop loss and take profit on the invested capital.
Strategy 4: Kumo Twist
A long position is opened with 100% of the invested capital ($1000) when the 'Kumo' goes from negative to positive (called "Twist").
Closing the long position on the opposite condition.
There are 2 different strength signals for this strategy: weak, and strong.
Weak : the signal is weak when the condition is true and the price is above the 'Kumo'
Strong : the signal is strong when the condition is true and the price is below the 'Kumo'
This script is compliant with algorithmic trading.
You can use this script with trading terminals such as 3Commas or CryptoHopper. Connecting this script is very easy.
1. Enter the user interface
2. Select and activate a strategy
3. Copy your bot's links into the dedicated fields
4. Create and activate alert
Disclaimer: algorithmic trading involves risk, the user should consider aspects such as slippage, liquidity and costs when evaluating an asset. The Quant Science is not responsible for any kind of damage resulting from use of this script. By using this script you take all the responsibilities and risks.
MZ Momentum Non Repainting HTF HFT Scalper BotThis is an original script meant to be a high frequency trader that works on higher time frame calculations. I came up with the idea that using calculus I can figure out the actual rate of change and momentum with different calculations than the momentum indicator that is provided by trading view. Once momentum is shifted on a small time frame, it will provide an entry signal. The script is meant to be used on an algorithmic trading system for scalping purposes. It should be run on a one minute time frame.
Set it up on a one minute chart - setup your bot on a one minute interval.
Find the source of your data. You can use any time frame, open, close. high, low, olc4. Open is pretty much guaranteed to not have any repainting issues - although all the other calcs use a custom isbarconfirmed security repaint calculation.
Set your rate of change period - typically I use a one minute time frame for this as well - but set my length fairly long (30-40).
Then set your period for momentum calculation. This will sample the rate of change data to figure out your momentum. I typically try a setting of 6-8. If that doesn't work, try setting it about the same as the rate of change period and add or subtract a few from there.
Unfortunately due to various plotting constraints in Pinescript, you cannot plot the rate of change and momentum and price in the same.
Set your trigger point. I try values -30, -20, -10, 0, 1. Then finesse to get an earlier entry signal. You should account for a slight delay from the signal to the actual entry. Your backtest should test well, but please note that does not gaurantee results. In my findings, I have seen that there is a slight minimal delay between signal to entry and that can make the difference whether your trade is profitable or not.
Use the show data to show you additional data when you are backtesting. This can allow you to try to filter out results or market conditions that do not work. I typically work with the RSI and use the 30 minute and 15 minute RSIs. I make sure that it is trading within a certain band - about 40-75. You can try the inverse and only buy during really low RSI's as well.
Use the enter and close messages to setup your webhook messages. But I recommend to allow the algo trading platform to close the trade for you based on their calcs since that platform knows the actual price level and when it has become profitable.
Filters have been setup for
Moving Average Variants - any time frame, any length.
RSI - Any time frame, any length,
Future Plans: ATR Filter so you can filter out low volatility periods.
Send me a message with any suggestions.
Customizable Non-Repainting HTF MACD MFI Scalper Bot StrategyThis script was originally shared by Wunderbit as a free open source script for the community to work with.
WHAT THIS SCRIPT DOES:
It is intended for use on an algorithmic bot trading platform but can be used for scalping and manual trading.
This strategy is based on the trend-following momentum indicator . It includes the Money Flow index as an additional point for entry.
HOW IT DOES IT:
It uses a combination of MACD and MFI indicators to create entry signals. Parameters for each indicator have been surfaced for user configurability.
Take profits are fixed, but stop loss uses ATR configuration to minimize losses and close profitably.
HOW IS MY VERSION ORIGINAL:
I started trying to deploy this script myself in my algorithmic trading but ran into some issues which I have tried to address in this version.
Delayed Signals : The script has been refactored to use a time frame drop down. The higher time frame can be run on a faster chart (recommended on one minute chart for fastest signal confirmation and relay to algotrading platform.)
Repainting Issues : All indicators have been recoded to use the security function that checks to see if the current calculation is in realtime, if it is, then it uses the previous bar for calculation. If you are still experiencing repainting issues based on intended (or non intended use), please provide a report with screenshot and explanation so I can try to address.
Filtering : I have added to additional filters an ABOVE EMA Filter and a BELOW RSI Filter (both can be turned on and off)
Customizable Long and Close Messages : This allows someone to use the script for algorithmic trading without having to alter code. It also means you can use one indicator for all of your different alterts required for your bots.
HOW TO USE IT:
It is intended to be used in the 5-30 minute time frames, but you might be able to get a good configuration for higher time frames. I welcome feedback from other users on what they have found.
Find a pair with high volatility (example KUCOIN:ETH3LUSDT ) - I have found it works particularly well with 3L and 3S tokens for crypto. although it the limitation is that confrigurations I have found to work typically have low R/R ratio, but very high win rate and profit factor.
Ideally set one minute chart for bots, but you can use other charts for manual trading. The signal will be delayed by one bar but I have found configurations that still test well.
Select a time frame in configuration for your indicator calculations.
Select the strategy config for time frame. I like to use 5 and 15 minutes for scalping scenarios, but I am interested in hearing back from other community memebers.
Optimize your indicator without filters (trendFilter and RSI Filter)
Use the TrendFilter and RSI Filter to further refine your signals for entry. You will get less entries but you can increase your win ratio.
I will add screenshots and possibly a video provided that it passes community standards.
Limitations: this works rather well for short term, and does some good forward testing but back testing large data sets is a problem when switching from very small time frame to large time frame. For instance, finding a configuration that works on a one minute chart but then changing to a 1 hour chart means you lose some of your intra bar calclulations. There are some new features in pine script which might be able to address, this, but I have not had a chance to work on that issue.
Maddrix_club III (strategy)Maddrix club III (STRATEGY) is an advanced trading algorithm that goes long and short in spite of the market condition. It aims to capture large moves. It is the fruit of over a thousand hours of work, trials, errors, research, etc.
The STUDY version is also posted.
There are 5 main variables to adjust the indicator:
Framework length – Use this to establish the environment. Shorter length = volatile environment. Longer length = steadier.
Framework multiplier – Use this to adjust the environment to the asset. Lower value for less volatile price action and higher value for very volatile price action.
Search timeframe – Use this to lookback for a fractal . In theory, the longer the lookback the more reliable the fractal recognition.
Trigger line – Use this to adjust the trigger level. In theory, the lower the trigger the more signals you get.
Threshold – Use this to filter the signals. The higher the threshold, the less signal you get.
The best way to go about changing the settings, is to start off the default value. I’d do a monthly check-in playing with few of them and readjusting based on results from the exchange.
They are different, as this one can show you the equity curve.
It works on many markets as long as there is sufficient activity to create patterns and repetition.
You will notice a slight difference between the strategy calculation and the algo calculation (built in the algo) - this is because the exits are not exactly at the same levels. I left this on purpose, so that you can see that even with a little slippage, overall this is positive.
Very good results have been observed on the 15 min time frame though it technically works on all timeframe (5 min for example, 1 hour also). On the example above ETHUSDT – 15 min, the back test shows consistency in the results for the last 2 years. The theory behind it is based on probabilities, human emotions, and repetition in market patterns.
Results have also shown great adaptability, meaning the total profits don’t change considerably when we play with settings. This is very good because even if you try to fine tune a set of settings to the past, the probability that it keeps working in the future is rather high.
Very important note: the calculations DO NOT take into account any fee or slippage that you always experience on the exchanges.
The indicators only uses real time data, therefore it can’t repaint.
There are absolutely no guarantees about this algorithm and past results are not indicative of future performance.
Fees, slippage and API delay: for any algorithm you will use (from me or others), please keep in mind that fees add up, slippage and delay creates differences between algo theory and reality. We can put in place systems to circumvent that, but we will always have them.
Unicorn Quant Strategy [Astride Unicorn]Deeply customizable trading algorithm with instant back-testing. Its position management and trading signals engines emulate every step of the trading process and display all the actions on the chart. For example, the algorithm shows when to enter or partially close a position, move stop-loss to breakeven, etc. The trader can use these signals in their decision-making and replicate these actions in their trading terminal. The script can also send real-time alerts to the user’s Email.
The trading signals feature calculates entry signals for momentum and trend trading. The calculation is based on trend filtering using our custom filter based on rolling historical volatility. The historical volatility is used to distinguish the market regime and determine the current trend direction. In its calculations, the algorithm uses linear regressions instead of averaging. As our practice shows, it helps to reduce signal lag while keeping the number of false signals low.
HOW TO USE
Set stop-loss and up to three take-profit levels, choose rules for moving the stop-loss level, adjust sensitivity of the entry signals and see the back-test result immediately. If the performance of the strategy satisfies you, proceed with the forward-testing or live-trading.
When using this script, please, keep in mind that past results do not necessarily reflect future results and that many factors influence trading results.
SETTINGS
Use Starting Date - when the flag is turned off, the algorithm uses all available pricing data to calculate back-tests; when turned on, back-tests start from a starting date the user can select in the setting below.
Starting Date - sets a starting date for back-testing.
Trading Signals
Trade Length - defines the length of the trades the algorithm tries to calculate entry signals for. Recommended values are from 1.0 to 6.0.
Sensitivity - controls the sensitivity of the trading signals algorithm. The sensitivity determines the density of trading signals and how close the trailing-stop levels follow the price. The higher the value of this parameter is, the less sensitive the algorithm is. High values of the Sensitivity parameters (100-500) can help to withstand large price swings to stay in longer price moves. Lower values (10-100) work well for short- and medium-term trades.
Signals Type - In the Signals Type dropdown list, there are two options: Market Timing and Market Bias. Market timing is a type of trading signaling when the algorithm tries to find a perfect moment to enter and exit a trade. Market Bias is the type of trading signaling when the algorithm tries to be in a position all the time. When a trade is closed, the algorithm determines a direction to which the market is currently “biased” and immediately opens a trade in this direction.
Position Management
SL - sets stop-loss level measured as a percentage of the trade entry price
TP1, TP2, TP3 - sets take-profit levels measured as a percentage of the trade entry price
Close % at TP1, Close % at TP2, Close % at TP3 - Sets portions of the open position(as a percentage of the initial order size) to close at each of the TP levels
At TP1 move SL to, At TP2 move SL to - Sets the rules for moving stop-loss level in an open trade to protect the floating profit
Dashboards
Active Position Information - turns on/off a dashboard that shows the current SL and TP levels for the active position.
Recommended SL,TP Settings - turns on/off a dashboard that shows recommended settings for the SL and TP levels.
Relativity Autonomous Distribution Blocks
The relativity method is a method of trade inspired by the Theory of Relativity of Albert Einstein , which argues that trade is a relative concept and, according to the case it advocates, creates the values to be evaluated relatively by using various engineering methods, and converts these values to factors to ensure the highest efficiency.
Many layers are common with Autonomous LSTM.
For more information about Autonomous LSTM :
But there are additional layers that are much higher than that.
These systems use COT (Commitment of Traders) data positively in trade and significantly increase the hit rate compared to conventional methods.
And in all traded instruments, it decides the degree of scoring by linking with global markets.
The more liquidity of the selected parities, the higher the success rate, the higher liquidity in the markets.
***STRUCTURE
Feature Layer 1 : Formulation : Common Layer with Autonomous LSTM
Feature Layer 2: Forecast Algorithm : Common Layer with Autonomous LSTM
Feature Layer 3 : Composite of Two Layers : Adaptive Period (Length) Algorithm : Common Layer with Autonomous LSTM
Feature Layer 4 : High - Low Selection Algorithm : Common Layer with Autonomous LSTM
Feature Layer 5 : Volume (Ticker ) - Open Interest (Global Market) Power Factor according to Global Markets and Related instrument (Ticker)
Feature Layer 6 : Quantum Equations including COT Commercial Positions (Communicate with layer 5)
Feature Layer 7 : World's Price/Earnings Ratio (This layer is automatically added to layer 6 as a factor each week.)
Feature Layer 8 : Distribution Blocks : The design of script as a histogram, with distributional buying and selling points and positive/negative zone coloring, with alerts.
Uses the relativity algorithm. This will contribute not only to leveraged transactions but also to portfolio management and will give a more realistic perspective.
Informs the trading points within the regions.
In this way, it allows for gradual buying and selling and reduces the risk to a much lower level.
These feature allows a difference perspective especially for traders who act with portfolio logic and / or add regular income.
The educational idea I shared in order to set an example for this logic:
***SETTINGS
Menu
1. * Market Type
The menu is divided into 5 different algorithms and covers all instruments around the world.
For example:
Futures : XAUUSD , GC , XAGUSD , SUGARUSD , SB1! , XAGUSD
Stocks : All Stocks and Modified Parities (Example : AAPL/EUR , XAU/XAG , AAPL , MT , BAC)
Forex Excluding USD/X : CHFUSD , EURUSD , EURJPY , AUDNZD
Forex USD/X : USDJPY , USDTRY , USDMXN
Crypto : BTCUSD , ETHUSD , ADAUSD or BTCETH , ETHBTC
2. * Barcolor
Barcolor Plotting Rules : On / off section with these rules when barcolor on :
Orange : Distributional Sell Signal ( Not Short )
Blue : Distributinaol Buy Signal
*** FEATURES
Indicator Features :
Red Background with Cross : Short Signal
Green Background with Cross : Buy Signal
Blue Histogram Color : Distributional Buy Signal
Orange Histogram Color : Distributional Sell Signal
Alerts
Long Alert
Short Alert
Distributional Buy Alert
Distributional Sell Alert
*** USAGE
Since the script uses various Commitment of Traders data, it is designed only for the weekly time frame. ( TF = 1W )
Script does not repaint 1 Week and above time frames . (Source = close )
NOTE :
The script design was inspired by one of RafaelZioni's script :
Best regards.
My AlgoTraderFirst, please find it in your heart to donate to my broke college student fund. I am in the final stages of making an algorithmic trading bot in Python, which hooks up to this particular exchange, but I do not have the disposable income to really test it out, so any donation helps. Comment below to let me know you donated so others can see your support!
Please send BTC Donations to: 13ZJ3xTLgJ6hNrv7e5eyEqhabxivYnuu8p
Please send LTC Donations to: LYeFrR9faLaAxJdB1anqVu3mCNxADZDHND
Anyway, on the the program.
I made an algorithmic trader which uses a set of self made indicators. This algorithm was written in pine version 3 and does not calculate_on_tick , therefore it does not repaint . The numbers you see are, to the best of my understanding, accurate.
Because I was concerned about overfitting, I created this algorithm with the intention of being generalizable to many different trading pairs. This program is generalizable to most trading pairs -- both crypto and normal stocks. This algorithm works best on shorter time frames for crypto markets, and longer timeframes for the conventional stock market.
Please let me know what you think and what I could do better!
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Are you ready to take your trading to the next level? Introducing *MEERU-72-FX-ALGO* — a powerful, automated trading algorithm designed for success. Whether you're a beginner or an experienced trader, MEERU-72-FX-ALGO is built to optimize your trades, increase accuracy, and maximize profits. Say goodbye to emotional trading and hello to consistent, data-driven results.
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MEERU-72-FX-ALGO"Unlock Your Trading Potential with MEERU-72-FX-ALGO! 🚀💹
Are you ready to take your trading to the next level? Introducing *MEERU-72-FX-ALGO* — a powerful, automated trading algorithm designed for success. Whether you're a beginner or an experienced trader, MEERU-72-FX-ALGO is built to optimize your trades, increase accuracy, and maximize profits. Say goodbye to emotional trading and hello to consistent, data-driven results.
Get started today and let MEERU-72-FX-ALGO work for you! DM for more details or click the link below to join our exclusive community.
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Simple Decesion Matrix Classification Algorithm [SS]Hello everyone,
It has been a while since I posted an indicator, so thought I would share this project I did for fun.
This indicator is an attempt to develop a pseudo Random Forest classification decision matrix model for Pinescript.
This is not a full, robust Random Forest model by any stretch of the imagination, but it is a good way to showcase how decision matrices can be applied to trading and within Pinescript.
As to not market this as something it is not, I am simply calling it the "Simple Decision Matrix Classification Algorithm". However, I have stolen most of the aspects of this machine learning algo from concepts of Random Forest modelling.
How it works:
With models like Support Vector Machines (SVM), Random Forest (RF) and Gradient Boosted Machine Learning (GBM), which are commonly used in Machine Learning Classification Tasks (MLCTs), this model operates similarity to the basic concepts shared amongst those modelling types. While it is not very similar to SVM, it is very similar to RF and GBM, in that it uses a "voting" system.
What do I mean by voting system?
How most classification MLAs work is by feeding an input dataset to an algorithm. The algorithm sorts this data, categorizes it, then introduces something called a confusion matrix (essentially sorting the data in no apparently order as to prevent over-fitting and introduce "confusion" to the algorithm to ensure that it is not just following a trend).
From there, the data is called upon based on current data inputs (so say we are using RSI and Z-Score, the current RSI and Z-Score is compared against other RSI's and Z-Scores that the model has saved). The model will process this information and each "tree" or "node" will vote. Then a cumulative overall vote is casted.
How does this MLA work?
This model accepts 2 independent variables. In order to keep things simple, this model was kept as a three node model. This means that there are 3 separate votes that go in to get the result. A vote is casted for each of the two independent variables and then a cumulative vote is casted for the overall verdict (the result of the model's prediction).
The model actually displays this system diagrammatically and it will likely be easier to understand if we look at the diagram to ground the example:
In the diagram, at the very top we have the classification variable that we are trying to predict. In this case, we are trying to predict whether there will be a breakout/breakdown outside of the normal ATR range (this is either yes or no question, hence a classification task).
So the question forms the basis of the input. The model will track at which points the ATR range is exceeded to the upside or downside, as well as the other variables that we wish to use to predict these exceedences. The ATR range forms the basis of all the data flowing into the model.
Then, at the second level, you will see we are using Z-Score and RSI to predict these breaks. The circle will change colour according to "feature importance". Feature importance basically just means that the indicator has a strong impact on the outcome. The stronger the importance, the more green it will be, the weaker, the more red it will be.
We can see both RSI and Z-Score are green and thus we can say they are strong options for predicting a breakout/breakdown.
So then we move down to the actual voting mechanisms. You will see the 2 pink boxes. These are the first lines of voting. What is happening here is the model is identifying the instances that are most similar and whether the classification task we have assigned (remember out ATR exceedance classifier) was either true or false based on RSI and Z-Score.
These are our 2 nodes. They both cast an individual vote. You will see in this case, both cast a vote of 1. The options are either 1 or 0. A vote of 1 means "Yes" or "Breakout likely".
However, this is not the only voting the model does. The model does one final vote based on the 2 votes. This is shown in the purple box. We can see the final vote and result at the end with the orange circle. It is 1 which means a range exceedance is anticipated and the most likely outcome.
The Data Table Component
The model has many moving parts. I have tried to represent the pivotal functions diagrammatically, but some other important aspects and background information must be obtained from the companion data table.
If we bring back our diagram from above:
We can see the data table to the left.
The data table contains 2 sections, one for each independent variable. In this case, our independent variables are RSI and Z-Score.
The data table will provide you with specifics about the independent variables, as well as about the model accuracy and outcome.
If we take a look at the first row, it simply indicates which independent variable it is looking at. If we go down to the next row where it reads "Weighted Impact", we can see a corresponding percent. The "weighted impact" is the amount of representation each independent variable has within the voting scheme. So in this case, we can see its pretty equal, 45% and 55%, This tells us that there is a slight higher representation of z-score than RSI but nothing to worry about.
If there was a major over-respresentation of greater than 30 or 40%, then the model would risk being skewed and voting too heavily in favour of 1 variable over the other.
If we move down from there we will see the next row reads "independent accuracy". The voting of each independent variable's accuracy is considered separately. This is one way we can determine feature importance, by seeing how well one feature augments the accuracy. In this case, we can see that RSI has the greatest importance, with an accuracy of around 87% at predicting breakouts. That makes sense as RSI is a momentum based oscillator.
Then if we move down one more, we will see what each independent feature (node) has voted for. In this case, both RSI and Z-Score voted for 1 (Breakout in our case).
You can weigh these in collaboration, but its always important to look at the final verdict of the model, which if we move down, we can see the "Model prediction" which is "Bullish".
If you are using the ATR breakout, the model cannot distinguish between "Bullish" or "Bearish", must that a "Breakout" is likely, either bearish or bullish. However, for the other classification tasks this model can do, the results are either Bullish or Bearish.
Using the Function:
Okay so now that all that technical stuff is out of the way, let's get into using the function. First of all this function innately provides you with 3 possible classification tasks. These include:
1. Predicting Red or Green Candle
2. Predicting Bullish / Bearish ATR
3. Predicting a Breakout from the ATR range
The possible independent variables include:
1. Stochastics,
2. MFI,
3. RSI,
4. Z-Score,
5. EMAs,
6. SMAs,
7. Volume
The model can only accept 2 independent variables, to operate within the computation time limits for pine execution.
Let's quickly go over what the numbers in the diagram mean:
The numbers being pointed at with the yellow arrows represent the cases the model is sorting and voting on. These are the most identical cases and are serving as the voting foundation for the model.
The numbers being pointed at with the pink candle is the voting results.
Extrapolating the functions (For Pine Developers:
So this is more of a feature application, so feel free to customize it to your liking and add additional inputs. But here are some key important considerations if you wish to apply this within your own code:
1. This is a BINARY classification task. The prediction must either be 0 or 1.
2. The function consists of 3 separate functions, the 2 first functions serve to build the confusion matrix and then the final "random_forest" function serves to perform the computations. You will need all 3 functions for implementation.
3. The model can only accept 2 independent variables.
I believe that is the function. Hopefully this wasn't too confusing, it is very statsy, but its a fun function for me! I use Random Forest excessively in R and always like to try to convert R things to Pinescript.
Hope you enjoy!
Safe trades everyone!
QuantBuilder | FractalystWhat's the strategy's purpose and functionality?
QuantBuilder is designed for both traders and investors who want to utilize mathematical techniques to develop profitable strategies through backtesting on historical data.
The primary goal is to develop profitable quantitive strategies that not only outperform the underlying asset in terms of returns but also minimize drawdown.
For instance, consider Bitcoin (BTC), which has experienced significant volatility, averaging an estimated 200% annual return over the past decade, with maximum drawdowns exceeding -80%. By employing this strategy with diverse entry and exit techniques, users can potentially seek to enhance their Compound Annual Growth Rate (CAGR) while managing risk to maintain a lower maximum drawdown.
While this strategy employs quantitative techniques, including mathematical methods such as probabilities and positive expected values, it demonstrates exceptional efficacy across all markets. It particularly excels in futures, indices, stocks, cryptocurrencies, and commodities, leveraging their inherent trending behaviors for optimized performance.
In both trending and consolidating market conditions, QuantBuilder employs a combination of multi-timeframe probabilities, expected values, directional biases, moving averages and diverse entry models to identify and capitalize on bullish market movements.
How does the strategy perform for both investors and traders?
The strategy has two main modes, tailored for different market participants: Traders and Investors.
1. Trading:
- Designed for traders looking to capitalize on bullish markets.
- Utilizes a percentage risk per trade to manage risk and optimize returns.
- Suitable for both swing and intraday trading with a focus on probabilities and risk per trade approach.
2. Investing:
- Geared towards investors who aim to capitalize on bullish trending markets without using leverage while mitigating the asset's maximum drawdown.
- Utilizes pre-define percentage of the equity to buy, hold, and manage the asset.
- Focuses on long-term growth and capital appreciation by fully/partially investing in the asset during bullish conditions.
How does the strategy identify market structure? What are the underlying calculations?
The strategy utilizes an efficient logic with for loops to pinpoint the first swing candle featuring a pivot of 2, establishing the point at which the break of structure begins.
What entry criteria are used in this script? What are the underlying calculations?
The script utilizes two entry models: BreakOut and fractal.
Underlying Calculations:
Breakout: The script assigns the most recent swing high to a variable. When the price closes above this level and all other conditions are met, the script executes a breakout entry (conservative approach).
Fractal: The script identifies a swing low with a period of 2. Once this condition is met, the script executes the trade (aggressive approach).
How does the script calculate probabilities? What are the underlying calculations?
The script calculates probabilities by monitoring price interactions with liquidity levels. Here’s how the underlying calculations work:
Tracking Price Hits: The script counts the number of times the price taps into each liquidity side after the EQM level is activated. This data is stored in an array for further analysis.
Sample Size Consideration: The total number of price interactions serves as the sample size for calculating probabilities.
Probability Calculation: For each liquidity side, the script calculates the probability by taking the average of the recorded hits. This allows for a dynamic assessment of the likelihood that a particular side will be hit next, based on historical performance.
Dynamic Adjustment: As new price data comes in, the probabilities are recalculated, providing real-time aduptive insights into market behavior.
Note: The calculations are performed independently for each directional range. A range is considered bearish if the previous breakout was through a sellside liquidity. Conversely, a range is considered bullish if the most recent breakout was through a buyside liquidity.
How does the script calculate expected values? What are the underlying calculations?
The script calculates expected values by leveraging the probabilities of winning and losing trades, along with their respective returns. The process involves the following steps:
This quantitative methodology provides a robust framework for assessing the expected performance of trading strategies based on historical data and backtesting results.
How is the contextual bias calculated? What are the underlying calculations?
The contextual bias in the QuantBuilder script is calculated through a structured approach that assesses market structure based on swing highs and lows. Here’s how it works:
Identification of Swing Points: The script identifies significant swing points using a defined pivot logic, focusing on the first swing high and swing low. This helps establish critical levels for determining market structure.
Break of Structure (BOS) Assessment:
Bullish BOS: The script recognizes a bullish break of structure when a candle closes above the first swing high, followed by at least one swing low.
Bearish BOS: Conversely, a bearish break of structure is identified when a candle closes below the first swing low, followed by at least one swing high.
Bias Assignment: Based on the identified break of structure, the script assigns directional biases:
A bullish bias is assigned if a bullish BOS is confirmed.
A bearish bias is assigned if a bearish BOS is confirmed.
Quantitative Evaluation: Each identified bias is quantitatively evaluated, allowing the script to assign numerical values representing the strength of each bias. This quantification aids in assessing the reliability of market sentiment across multiple timeframes.
What's the purpose of using moving averages in this strategy? What are the underlying calculations?
Using moving averages is a widely-used technique to trade with the trend.
The main purpose of using moving averages in this strategy is to filter out bearish price action and to only take trades when the price is trading ABOVE specified moving averages.
The script uses different types of moving averages with user-adjustable timeframes and periods/lengths, allowing traders to try out different variations to maximize strategy performance and minimize drawdowns.
By applying these calculations, the strategy effectively identifies bullish trends and avoids market conditions that are not conducive to profitable trades.
The MA filter allows traders to choose whether they want a specific moving average above or below another one as their entry condition.
What type of stop-loss identification method are used in this strategy? What are the underlying calculations?
- Initial Stop-loss:
1. ATR Based:
The Average True Range (ATR) is a method used in technical analysis to measure volatility. It is not used to indicate the direction of price but to measure volatility, especially volatility caused by price gaps or limit moves.
Calculation:
- To calculate the ATR, the True Range (TR) first needs to be identified. The TR takes into account the most current period high/low range as well as the previous period close.
The True Range is the largest of the following:
- Current Period High minus Current Period Low
- Absolute Value of Current Period High minus Previous Period Close
- Absolute Value of Current Period Low minus Previous Period Close
- The ATR is then calculated as the moving average of the TR over a specified period. (The default period is 14)
2. ADR Based:
The Average Day Range (ADR) is an indicator that measures the volatility of an asset by showing the average movement of the price between the high and the low over the last several days.
Calculation:
- To calculate the ADR for a particular day:
- Calculate the average of the high prices over a specified number of days.
- Calculate the average of the low prices over the same number of days.
- Find the difference between these average values.
- The default period for calculating the ADR is 14 days. A shorter period may introduce more noise, while a longer period may be slower to react to new market movements.
3. PL Based:
This method places the stop-loss at the low of the previous candle.
If the current entry is based on the hunt entry strategy, the stop-loss will be placed at the low of the candle that wicks through the lower FRMA band.
Example:
If the previous candle's low is 100, then the stop-loss will be set at 100.
This method ensures the stop-loss is placed just below the most recent significant low, providing a logical and immediate level for risk management.
- Trailing Stop-Loss:
One of the key elements of this strategy is its ability to detect structural liquidity and structural invalidation levels across multiple timeframes to trail the stop-loss once the trade is in running profits.
By utilizing this approach, the strategy allows enough room for price to run.
By using these methods, the strategy dynamically adjusts the initial stop-loss based on market volatility, helping to protect against adverse price movements while allowing for enough room for trades to develop.
Each market behaves differently across various timeframes, and it is essential to test different parameters and optimizations to find out which trailing stop-loss method gives you the desired results and performance.
What type of break-even and take profit identification methods are used in this strategy? What are the underlying calculations?
For Break-Even:
Percentage (%) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain percentage above the entry.
Calculation:
Break-even level = Entry Price * (1 + Percentage / 100)
Example:
If the entry price is $100 and the break-even percentage is 5%, the break-even level is $100 * 1.05 = $105.
Risk-to-Reward (RR) Based:
Moves the initial stop-loss to the entry price when the price reaches a certain RR ratio.
Calculation:
Break-even level = Entry Price + (Initial Risk * RR Ratio)
For TP1 (Take Profit 1):
- You can choose to set a take profit level at which your position gets fully closed or 50% if the TP2 boolean is enabled.
- Similar to break-even, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP1 level as a percentage amount above the entry price or based on RR.
For TP2 (Take Profit 2):
- You can choose to set a take profit level at which your position gets fully closed.
- As with break-even and TP1, you can select either a percentage (%) or risk-to-reward (RR) based take profit level, allowing you to set your TP2 level as a percentage amount above the entry price or based on RR.
What's the day filter Filter, what does it do?
The day filter allows users to customize the session time and choose the specific days they want to include in the strategy session. This helps traders tailor their strategies to particular trading sessions or days of the week when they believe the market conditions are more favorable for their trading style.
Customize Session Time:
Users can define the start and end times for the trading session.
This allows the strategy to only consider trades within the specified time window, focusing on periods of higher market activity or preferred trading hours.
Select Days:
Users can select which days of the week to include in the strategy.
This feature is useful for excluding days with historically lower volatility or unfavorable trading conditions (e.g., Mondays or Fridays).
Benefits:
Focus on Optimal Trading Periods:
By customizing session times and days, traders can focus on periods when the market is more likely to present profitable opportunities.
Avoid Unfavorable Conditions:
Excluding specific days or times can help avoid trading during periods of low liquidity or high unpredictability, such as major news events or holidays.
What tables are available in this script?
- Summary: Provides a general overview, displaying key performance parameters such as Net Profit, Profit Factor, Max Drawdown, Average Trade, Closed Trades and more.
Total Commission: Displays the cumulative commissions incurred from all trades executed within the selected backtesting window. This value is derived by summing the commission fees for each trade on your chart.
Average Commission: Represents the average commission per trade, calculated by dividing the Total Commission by the total number of closed trades. This metric is crucial for assessing the impact of trading costs on overall profitability.
Avg Trade: The sum of money gained or lost by the average trade generated by a strategy. Calculated by dividing the Net Profit by the overall number of closed trades. An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.
MaxDD: Displays the largest drawdown of losses, i.e., the maximum possible loss that the strategy could have incurred among all of the trades it has made. This value is calculated separately for every bar that the strategy spends with an open position.
Profit Factor: The amount of money a trading strategy made for every unit of money it lost (in the selected currency). This value is calculated by dividing gross profits by gross losses.
Avg RR: This is calculated by dividing the average winning trade by the average losing trade. This field is not a very meaningful value by itself because it does not take into account the ratio of the number of winning vs losing trades, and strategies can have different approaches to profitability. A strategy may trade at every possibility in order to capture many small profits, yet have an average losing trade greater than the average winning trade. The higher this value is, the better, but it should be considered together with the percentage of winning trades and the net profit.
Winrate: The percentage of winning trades generated by a strategy. Calculated by dividing the number of winning trades by the total number of closed trades generated by a strategy. Percent profitable is not a very reliable measure by itself. A strategy could have many small winning trades, making the percent profitable high with a small average winning trade, or a few big winning trades accounting for a low percent profitable and a big average winning trade. Most mean-reversion successful strategies have a percent profitability of 40-80% but are profitable due to risk management control.
BE Trades: Number of break-even trades, excluding commission/slippage.
Losing Trades: The total number of losing trades generated by the strategy.
Winning Trades: The total number of winning trades generated by the strategy.
Total Trades: Total number of taken traders visible your charts.
Net Profit: The overall profit or loss (in the selected currency) achieved by the trading strategy in the test period. The value is the sum of all values from the Profit column (on the List of Trades tab), taking into account the sign.
- Monthly: Displays performance data on a month-by-month basis, allowing users to analyze performance trends over each month and year.
- Weekly: Displays performance data on a week-by-week basis, helping users to understand weekly performance variations.
- UI Table: A user-friendly table that allows users to view and save the selected strategy parameters from user inputs. This table enables easy access to key settings and configurations, providing a straightforward solution for saving strategy parameters by simply taking a screenshot with Alt + S or ⌥ + S.
User-input styles and customizations:
To facilitate studying historical data, all conditions and filters can be applied to your charts. By plotting background colors on your charts, you'll be able to identify what worked and what didn't in certain market conditions.
Please note that all background colors in the style are disabled by default to enhance visualization.
How to Use This Quantitive Strategy Builder to Create a Profitable Edge and System?
Choose Your Strategy mode:
- Decide whether you are creating an investing strategy or a trading strategy.
Select a Market:
- Choose a one-sided market such as stocks, indices, or cryptocurrencies.
Historical Data:
- Ensure the historical data covers at least 10 years of price action for robust backtesting.
Timeframe Selection:
- Choose the timeframe you are comfortable trading with. It is strongly recommended to use a timeframe above 15 minutes to minimize the impact of commissions/slippage on your profits.
Set Commission and Slippage:
- Properly set the commission and slippage in the strategy properties according to your broker/prop firm specifications.
Parameter Optimization:
- Use trial and error to test different parameters until you find the performance results you are looking for in the summary table or, preferably, through deep backtesting using the strategy tester.
Trade Count:
- Ensure the number of trades is 200 or more; the higher, the better for statistical significance.
Positive Average Trade:
- Make sure the average trade is above zero.
(An important value since it must be large enough to cover the commission and slippage costs of trading the strategy and still bring a profit.)
Performance Metrics:
- Look for a high profit factor, and net profit with minimum drawdown.
- Ideally, aim for a drawdown under 20-30%, depending on your risk tolerance.
Refinement and Optimization:
- Try out different markets and timeframes.
- Continue working on refining your edge using the available filters and components to further optimize your strategy.
What makes this strategy original?
QuantBuilder stands out due to its unique combination of quantitative techniques and innovative algorithms that leverage historical data for real-time trading decisions. Unlike most algorithmic strategies that work based on predefined rules, this strategy adapts to real-time market probabilities and expected values, enhancing its reliability. Key features include:
Mathematical Framework: The strategy integrates advanced mathematical concepts, such as probabilities and expected values, to assess trade viability and optimize decision-making.
Multi-Timeframe Analysis: By utilizing multi-timeframe probabilities, QuantBuilder provides a comprehensive view of market conditions, enhancing the accuracy of entry and exit points.
Dynamic Market Structure Identification: The script employs a systematic approach to identify market structure changes, utilizing a blend of swing highs and lows to detect contextual/direction bias of the market.
Built-in Trailing Stop Loss: The strategy features a dynamic trailing stop loss based on multi-timeframe analysis of market structure. This allows traders to lock in profits while adapting to changing market conditions, ensuring that exits are executed at optimal levels without prematurely closing positions.
Robust Performance Metrics: With detailed performance tables and visualizations, users can easily evaluate strategy effectiveness and adjust parameters based on historical performance.
Adaptability: The strategy is designed to work across various markets and timeframes, making it versatile for different trading styles and objectives.
Suitability for Investors and Traders: QuantBuilder is ideal for both investors and traders looking to rely on mathematically proven data to create profitable strategies, ensuring that decisions are grounded in quantitative analysis.
These original elements combine to create a powerful tool that can help both traders and investors to build and refine profitable strategies based on algorithmic quantitative analysis.
Terms and Conditions | Disclaimer
Our charting tools are provided for informational and educational purposes only and should not be construed as financial, investment, or trading advice. They are not intended to forecast market movements or offer specific recommendations. Users should understand that past performance does not guarantee future results and should not base financial decisions solely on historical data.
Built-in components, features, and functionalities of our charting tools are the intellectual property of @Fractalyst Unauthorized use, reproduction, or distribution of these proprietary elements is prohibited.
By continuing to use our charting tools, the user acknowledges and accepts the Terms and Conditions outlined in this legal disclaimer and agrees to respect our intellectual property rights and comply with all applicable laws and regulations.
SFX Signals & Overlays [YinYangAlgorithms]SFX Signals & Overlays aims to help traders Identify Buy & Sell locations, Reversals, Volatility Zones, Support & Resistance and Overbought & Oversold Zones. All of these may work in harmony with each other by helping to identify when to enter and exit a trade; as well as helping to determine the risk / reward the trade may ensue.
SFX Signals & Overlays’s Buy & Sell signals are momentum based, meaning the Initial ‘Buy’ & ‘Sell’ signal may not be exactly where you want to get in/out. What may occur is the initial signal appears, a few more continuation signals appear afterwards (always in a chain); and once the momentum has ended a ‘Reversal’ signal appears. The reversal is there to help signify that the ‘opportune’ time to buy/sell may have passed and the price may now correct in the opposite direction. This Indicator aims to Buy Low and Sell High; and therefore the Buy signal momentum may occur as the price is either about to fall, currently falling or has started to consolidate. When the Buy signal momentum has ended, this means the momentum is at an impasse, but is favoring Buy momentum and a reversal (correction) may occur.
Buying & Selling at reversal signals may be profitable, however it may be less risky to DCA into your long / short positions during the Buy/Sell momentum signals instead. Let's get into the Tutorial so you can better understand how our SFX Signals & Overlays indicator works.
Tutorial:
Our example above showcases how our SFX Signals & Overlays Indicator looks on the default settings ‘Medium’ for each of our Algorithm Settings:
Trend Sensitivity
Signal Sensitivity
Zone Sensitivity
All of our Algorithm Settings feature 3 different speeds:
Fast
Medium
Slow
These speeds may be applied to each Algorithm Setting individually and affect how quickly they adapt to the current market's momentum. This allows you to tailor this Indicator to fit your trading style by adjusting it to meet your needs accordingly. If you are someone who likes to swing trade on the 1-5 minute timeframe, you may find better confluence with all settings on ‘Fast’. Medium term holders and traders may find better results with all settings on ‘Medium’. Likewise, long term investors may find best results with all settings on ‘Slow’. However, this shouldn’t stop you from finding your own best result by adjusting them individually to meet your own unique trading style.
SFX Signals & Overlays helps you identify shifts in momentum by displaying Momentum Signals. Momentum Signals are shown by either a Green or Red Triangle. Momentum Signals can continue for quite some time until the momentum has ended. We rank the first Momentum Signal from 1/5 to 5/5 for their strength and may help determine the chances of the momentum shift occurring. Once the Momentum Signals have ended we display a Reversal Signal. This Reversal Signal helps signify that the Momentum has ended. When the Momentum ends it means that a reversal may have started. This reversal may mean the price will continue in the direction the signal mentioned; or it may mean the price will consolidate. If the price consolidates then the signal is void as when the consolidation ends the price could go in either direction. If you notice consolidation occurring after a Reversal Signal; wait for more confirmations as it is now too risky.
Our Indicator displays different evaluations for each INITIAL Buy and Sell signal. These evaluations rank the current start of the signal from 1-5; 1 being the lowest and least reliable, 5 being the highest and most reliable. These rankings aren’t indefinite and are simply an evaluation at the time of the initial signal. We may potentially provide evaluations at the reversal later on if requested enough. When a Buy or Sell signal occurs this defines where momentum is occurring in this direction. This momentum is indicated by momentum signals shown through red / green triangles. These triangles indicate that this momentum is present. When these momentum signals end is when the Reversal Signal appears indicating that since this momentum has ended, there may be a decent chance of a reversal occurring. There also adherently may be the potential of consolidation occurring; but generally it means there is either a reversal, or consolidation + then a reversal or a continuation; however it may be apparent that the momentum has ended.
ES:
NQ:
BTC:
If you refer to the 3 examples above, we show how the ES, NQ and BTC look within a 5 minute scalping example. Essentially you’d make your decision on the Buy / Sell signal, the momentum signals, the Reversal Signals, the Trend Colors as well as other oscillators and Due Diligence.
Remember, there’s no such thing as a perfect entry / exit, the more you understand about trading and do your own Due Diligence the better. These Buy and Sell as well as Reversal signals attempt to locate and rank momentum shifts to help you identify where the momentum may be ending and reversing in the opposite direction.
Our zones defined by the Outer (red) and Inner (green) are representations of not only Support and Resistance locations, but likewise Overbought and Oversold locations. These zones help in multiple ways. The hard lines that define each zone's start / end are very useful locations of support / resistance which may indicate where the price will bounce off of. Likewise, when the price is within these zones it represents the price being Overbought or Oversold. Then the price is for instance within the Red Resistance Zone, what generally may happen is the price will correct quickly to get back to the ‘Black Empty Zone’ between the Red and Green zones; OR it may consolidate sideways until it has entered the ‘Black Empty Zone’. This is how the price may redeem itself back to being valued correctly. These zones help you identify and understand, in concatenation with our signals when and how much the price may move.
Our Settings are minimalistic so you don’t need to worry and get overwhelmed about changing values and trying to fiddle to find which values works the best for what. Our Algorithms will take care of all of that for you. Simply select the speeds for your Trend, Signals and Zones and you’re good to start trading! You can likewise customize what information is visible to you and the colors to better customize your experience.
Fast:
Medium:
Slow:
The 3 examples above display what the same portion of the chart looks like when Trend, Signal and Zone Sensitivity is changed from Fast, Medium and Slow.
As you can see, they all look quite different in the results they produce. By default all settings are set to Medium, however they can all be individually changed to suit your trading style and needs.
Our Indicator offers many different alert options which may help you stay informed with how the market is moving and any momentum changes that may occur.
Settings:
1. Algorithm Settings
Trend Sensitivity (Fast, Medium, Slow): Trend Sensitivity refers to how quickly the Trend Bar Colors change. Fast: will change colors very quickly if it senses momentum is changing. Medium: will change almost as quickly as Fast, however, rather than swapping from Bullish to Bearish momentum right away it has an intermediate 'Neutral - Slightly Bullish (Yellow)' and 'Neutral - Slightly Bearish (Orange)'. This way you can better visualize when the momentum is dying in the trend and starting back up by having these trend 'Neutral/Consolidation' areas. Slow: will attempt to only change Trend Bar Colors when the momentum has surely shifted. This may result in a bit of lagging behind.
Signal Sensitivity (Fast, Medium, Slow): Signal Sensitivity refers to how quickly the Buy & Sell Momentum Signals & Reversal Signals appear. These signals are meant to appear when it thinks the price may reverse, but the speeds refer to how much of a reversal they think may happen. Fast: will attempt to locate any and all momentum swings. Medium: will attempt to only locate momentum swings which may drive the price up considerably. Slow: will attempt to locate only the most extreme momentum swings. This may result in some potentially good ones missed however; but the ones it finds may have a higher probability of occuring.
Zone Sensitivity (Fast, Medium, Slow): Zone Sensitivity refers to how quickly the Zones expand based on price movement. These zones may be useful for not only seeing Support & Resistance; but also identifying when it is Overbought & Oversold; as well as visualizing volatility between the Black (Empty area) and the zones. The lines that separate each zone are the Support and Resistance locations; the area within the zones are simply the spacing between these Support and Resistance locations. However, the further the price is to the outer zones does represent Overbought and Oversold. Fast: will expand very quickly. This causes the price to be within the Black (Empty area) more often. This may be useful for finding extremities in price movement which may have a better chance of correcting. Medium: moves fast but not anywhere close to as fast as 'Fast'. Medium will hold its values in an attempt to be as accurate as possible for identifying Support and Resistance locations. Slow: will expand very slowly. This may be useful for identifying Support & Resistance as well as Volatility targets on higher time frames since these zones move much slower.
2. Display Settings:
Show Trend Bar Colors: Trend Bar Color are a way of seeing how the Trend is holding up on a bar by bar basis. This may be useful for seeing momentum starting, ending or simply dying down before any signals actually appear.
Signal Text Display (Both, Buy & Sell, Reversals, None: Signals are a way of seeing potential changes in momentum and when they have actually occurred. Our signals also rank from 1/5 to 5/5 how strong of a chance this momentum change may occur (only at the time of the signal, not at the time of the reversal). These may be useful as potential Entry and Exit locations; as well as when you see the reversal, you know that this momentum change has either begun or a consolidation may be occurring. If a consolidation occurs, the signal is no longer valid as the price can now go either way and it is best to wait for more signals or other technical analysis to determine momentum and movement.
Zone Display (All, Outer + Middle, Inner + Middle, Outer, Middle, Inner, None): Zones are composed of 3 areas above and below. These areas attempt to project Support & Resistance locations as well as display when the Price is Overbought and Oversold. You can specify which zones you wish to view, however all are important.
3. Color Settings:
Buy Color: This is the color of all Buy Signals and Zones.
Sell Color: This is the color of all Sell Signals and Zones.
Buy Reversal Color: This is the color of all Buy Signal Reversals.
Sell Reversal Color: This is the color of all Sell Signal Reversals.
If you have any questions, comments, ideas or concerns please don't hesitate to contact us.
HAPPY TRADING!
