Grid Premium Indicator - The Quant ScienceGrid Premium Indicator - The Quant Science™ is an indicator that represent the grid trading strategy. Unlike our GRID SPOT TRADING ALGORITHM (which buys in a "buy the dip" style, offering a swing type operation) this indicator uses a trend following strategy with a larger number of grids.
A trend-following strategy in a grid algorithm allows you to open long positions if price rises and breaks up or open short positions if price breaks down.
This indicator was created following the guidelines of the best grid algorithms on 3Commas, Bitsgap, Kucoin, and Binance.
Our goal is to recreate a universal and trust model for all traders and investors who use grid algorithms for their trading.
The ideal market condition as for all grid algorithms is the side market. In the side market this algorithm will create profit during upward movements.
The trader using this algorithm can use it to:
1. Manual trading
2. Backtesting
3. Algorithmic trading
HOW TO SET UP
Using this indicator is very simple. We have configured the creation for a three-step set up. You can manage it without any problems experience in coding. All you have to do is click the grid start and end level and the indicator will automatically load generating the grids and backtesting.
OPERATIVITY
Each open trade is long and is opened when the price crossover an upward level. Each order is closed at the next level. If the price breaks upward or downward the extremes of the grid the algorithm stops trading and will not open any more positions.
FEATURES
Grids: this indicator generates 20 levels of grids.
Direction: opens exclusively long positions.
Strategy: trend-following.
Data table: a table collects all the quantitative data on the strategy's performance. By entering your broker's commission costs and initial capital you will have an instant report on the strategy's performance.
MAIN ADVANTAGE
Compound Interest: the high number of grids allows the gains from each trade to be reinvested quickly by speeding capitalization through compound interest.
LIMITATIONS OF THE MODEL
Like all grid strategies, maximum profit is made when the market is flat or sideways. A market with a bullish or bearish trend does not allow you to generate good profits with this strategy.
在腳本中搜尋"algo"
Unicorn QuantDeeply customizable trading algorithm with instant backtesting. It emulates real trading and displays all the actions it takes on the chart. For example, it shows when to enter or partially close a position, move Stop-Loss to breakeven, etc. The user can replicate these actions in their trading terminal in real time. The algorithm uses up to three Take-Profit levels, and a Stop-Loss level that can move in a trade to protect the floating profit.
The script can send real-time alerts to the user’s Email and to the cell phone via notifications in the TradingView app.
The indicator is designed to be used on all timeframes, including lower ones for intraday trading and scalping.
HOW TO USE
Set the Stop-Loss and up to three Take-Profit levels. Choose the rules for moving the Stop-Loss level in a trade. Adjust the sensitivity of the trading signals. And check the backtest result in the Instant Backtesting dashboard. 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 there are many factors that influence trading results.
FEATURES
Trading Signals
The feature calculates Buy and Sell signals for trend or swing trading. The user can change the Sensitivity parameter to control the frequency of the signals. This allows them to be adjusted for different markets and timeframes.
Position Manager
To make the Position Manager setup as easy as possible, the algorithm calculates Stop-Loss and Take-Profit levels in Average True Range (ATR) units. They are self-adjusting for any market and timeframe, since they account for its average volatility .
You don't have to worry about what market you are trading - Forex, Stocks, Crypto, etc. With the self-adjusting Stop-Loss and Take-Profit, you can find settings that work for one market and use the same numerical values as a starting point for a completely different market.
Instant Backtesting
After changing any settings, you can immediately see the performance of the strategy on the Instant Backtesting panel. Two metrics are displayed there - the percentage of profitable trades and the total return. This information, as well as the historical trades shown on the chart, will help you quickly and easily evaluate the settings.
SETTINGS
TRADING SIGNALS
Sensitivity - controls the sensitivity of the trading signals algorithm. It determines the frequency of the trading signals. The higher the value of this parameter, the less trading signals you get and the longer trends the algorithm tries to catch. The lower the sensitivity value, the more signals you receive. This can be useful if you want to profit from small price movements.
POSITION MANAGER
SL - sets the Stop-Loss level measured in ATR units.
TP1, TP2, TP3 - set the Take-Profit levels measured in the ATR units.
Close % at TP1, Close % at TP2, Close % at TP3 - set 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 - set the rules for moving the Stop-Loss level in an open trade to protect the floating profit.
Show Open Position Dashboard - turns on/off a dashboard that shows the current Stop-Loss and Take-Profit levels for the open position.
BACKTESTING
Use Starting Date - turns on/off the starting date for the strategy and backtests. When off, all available historical data is used.
Starting Date - sets the starting date for the strategy and backtests.
Show Instant Backtesting Dashboard - turns on/off a dashboard that shows the current strategy performance: the percentage of profitable trades and total return.
Leverage - sets the leverage that the strategy uses.
MZ HTF HFT ROCit Bot - Non Repainting Scalper v1.2 ADX RSI MOM This is a new iteration based on my Momentum trading bot.
This 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. Unfortunately due to various plotting constraints in Pinescript, you cannot plot the rate of change and momentum and price in the same pane. To counter this, I have a showdata toggle to give you values of the indicators at each entry.
This version has two main entry settings toggled with a checkbox. There is the ROC (rate of change) version and the MOM (momentum) entry signals.
The rate of change version is meant to take a look at your moving average and try to trigger when it hits a certain rate of change point. This can be helpful if you rather play it safer. I have noticed that you can get slightly better entry points but also does not give you as many entries. The momentum algorithm will give you faster entry points and might work best with a slight offset (use your back test to help you figure it out).
I have started to add tooltips to help you along. If you have suggestions please let me know.
How does it work?
Let's just assume that you are looking at a one minute chart. I recommend using the one minute for bots because it will give you the fastest execution for entries. Pinescript has an issue where the signal is not usually sent until the end of the bar/beginning of next bar. If the signal was triggered at the beginning of a 15 minute bar, it might not actually send the signal until the following 15 minute bar. If you are trading on small time frames, this can make all the difference. If you are using an algo platform that trailing stops, stop losse, take profits, etc. I would recommend you use that platform to close your trade. The close trade message will work, but pinescript does not know the exact entry price you received, so if you are trying to collect small profits, it is best that intermediary platform does that calculation for you. If you are dealing with larger moves, instead of small 1-3% scalps, you are probably fine to use the close message setting from pinescript.
Ok, so to take an example. I like to use the 3L and 3S tokens on Kucoin. This gives you a lot of volatility to work with compared to other tokens and coins. However, it can also meas that you are likely taking a higher risk. However, there are some things that can help with that (more on that later).
So we have a token we want to run, and have it on the 1m chart.
First, be sure that all of your filters are OFF when you start playing with the back test. This allows you to see how to best optimize the bot.
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.
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Find the source of your data with the variant drop down. 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. I have been finding that Open and SMA work well, but feel free to explore. If you use a source like open, close, high, low, etc - the interval will not change anything further. If you use a variant such as an sma, you should try to find an interval that works well for that token. For instance, try an sma of 8-11 minutes and see which gives you the best backtest result without changing anything else. Offset ALMA/LSMA parameters are only used for those specific variants. These specific parameters will also affect the ALMA and LSMA if you use that variant in the trend filter. In other words, you can skip these if you are not using those types of moving averages.
www.dropbox.com
Configure the ROC and MOM intervals. If you are using a source such as open, close, etc- this is where you set the interval for your change. So consider using OHLC4 or a interval of 5 thru 15 and see what works best. The Momentum inverval usually works best in the 2-5 bars. There is a custom calculation I added in to try to filter out false entries as momentum is waning. This calculation works best in 2-5 bar interval.
Configure the trigger point and offset. If you are using rate of change, the best settings will likely be between -1 to 0.5. If you are using momentum, you will likely want -20 to 10. This is where you will notice the entries will shift a bit. Try to find a balance between your backtest settings and actually finding what you thin will be the best entries based on a slight delay from trading view, to algo, to your trading platform. This can likely be a minute (maybe even) or so- so be sure to not get too caught up between the backtest results and be sure to finesse the entries to actually fit nicely - maybe a bar earlier than you would likely think. If your entries are coming in too early, you can use the offset to delay your entry by a few bars. This is both science and an art form- don't get too caught up on the back test results as that is based on having all the data tha already transpired, it's not based on how it will actually perform during deployment.
Take profit and stop loss. This should be self explanatory. This script can toggle between static take profit and a trailing profit. For scalping, you will likely want to limit it below 2% to get a good win ratio. Stop loss should be at least 5-6% for these types of 3L/3S tokens to give the strategy some room to move (if the token goes down 2% before it shoots back up, the price will go down 6%). This does not yield the best R/R ratio from a traditional trader perspective, but the statistical probabilities are in your favor for these events will happen. If you have better ideas for how to set this all up, feel free to contribute your ideas in the comments as we can all learn from each other. You can definitely set a much tighter stop loss with a larger take profit to get a lower win rate but in turn might get much better returns. It's all up to you.
FILTERS www.dropbox.com
These filters require you to know a bit about each indicator and how you want to use them. I will only go over the general idea.
Variant Filter - this is especially useful if you want to trade above a moving average. Say for instance you only want to take trades when we are over the 100 Day moving average. Or above a 30 minute, 30 bar EMA, etc. Although originally ported over from my other scripts, this is not a filter that I use often in conjunction with this script.
RSI - perhaps you want to buy when we are below the 30 line on the 30 minute RSI, or we want only want to have the strategy work when we are above the 50 RSI, this can all be configured here. I typically like to try a few different rationales here.
Now with brand NEW ADX filter - this is a brand new idea that seems to work rather well. Based on your ADX settings you can also turn on the "only uptrend" which will try to calculate if you are in an uptrend based on your ADX config. Please keep in mind that uptrend is based relatively on the ADX settings.
- There is a sprinkle of RSI magic in the entry signal to make sure that rsi is not declining in the calculation, so this can affect how many entries you get.
Some other tips:
Forward test.
Set up your algo bot on a one minute interval.
Set up take profit and stop loss on your algo trading platform.
Don't use the exact settings as your backtest, maybe try a slightly more conservative approach from the algo trading platform to make sure you are within range of triggering your events with a slight delay from signal to execution. If you have a 1.6% take profit, perhaps try 1.5% on your platform first.
By using these scripts you agree that you are trading at your own risk. I make no guarantees of returns or results. I just provide tools to help you trade better. However, I hope this ROCit will take you to the moon. And if it does, be sure to give me a shout as well as some tips of your own.
Send me a message with any questions or suggestions.
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.
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.
Statistical Correlation Algorithm - The Quant ScienceStatistical Correlation Algorithm - The Quant Science™ is a quantitative trading algorithm.
ALGORITHM DESCRIPTION
This algorithm analyses the correlation ratios between two assets. The main asset (on the chart), and the secondary asset (set by the user). Then apply the long or short trading strategy.
The algorithm divides trading work into three parts:
1. Correlation analysis
2. Long or short entry
3. Closing trades
Inside the strategy: the algorithm analyses the percentage change yields from a previous session, of the secondary asset. If the variation meets the set condition then it will open a long or short position, on the primary asset. The open position is closed after 'x' number of sessions. Stop loss and take profit can be added to the trade exit parameters.
Logic: analyses the correlation between two assets and looks for a statistical advantage within the correlation.
INDICATOR DESCRIPTION
The algorithm includes a quantitative indicator. This indicator is used for correlation analysis and offers a quick reading of the quantitative data. The blue area shows the correlation ratio values. The yellow histograms show the percentage change in the yields of the main asset. Purple histograms show the percentage change in secondary asset yields.
GENERAL FEATURES
Multi time-frame: the user can set any time-frame for the secondary asset.
Multi asset: the user analyses the conditions on a second asset.
Multi-strategy: the algorithm can apply either the long strategy or the short strategy.
Built-in alerts: the algorithm contains alerts that can be customized from the user interface.
Integrated indicator: the quantity indicator is included.
Backtesting included: automatic backtesting of the strategy is generated based on the values set.
Auto-trading compliant: functions for auto trading are included.
USER INTERFACE SETTINGS
Through the intuitive user interface, you can manage all the parameters of this algorithm without any programming experience. The user interface is extremely descriptive and contains all the information needed to understand the logic of the algorithm and to configure it correctly.
1. Date range: through this function you can adjust the analysis and working period of the algorithm.
2. Asset: through this function you can adjust the secondary asset and its time-frame. You can enter any type of asset, even indices and economic indicators.
3. Asset details: this function is used to adjust the percentage change to be analyzed on the secondary asset. The analysis and input conditions are also chosen.
4. Active long or short strategy: this function is used to set the type of strategy to be used, long or short.
5. Setting algo trading alert: with this function, users can manage alerts for their web-hook.
6. Exit&Money management: with this function the user can adjust the exit periods of each trade and activate or deactivate any stop losses and take profits.
7. Data Value Analysis: this function is used to adjust the parameters for the quantity indicator.
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
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.
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!
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!
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!
[Round Numbers] Signal Clean Up Analysis with Backtest (TSO)Round Numbers NEW GEN indicator!
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This is a full-cycle trading system indicator - it will show and alert each step of the trade from open to close. The algorithm here uses Round Numbers for generating signals, TP (Take Profit) and SL (Stop Loss) levels. Round numbers play big role in trading and can easily become strong support and resistance levels where price can bounce and go the opposite way or go through with a very nice run afterwards.
In addition there is a chained (NOTE: You can select several or ALL of the features, this is not limited to either one) signal cleanup and analysis approach with scheduling and alerting capabilities. Works with most popular timeframes: 1M, 3M, 5M, 15M, 30M, 1H, 4H, D.
NOTE: Every action of the trade is calculated on a confirmed closed candle bar state (barstate.isconfirmed), so the indicator will never repaint!
NOTE: At position open - there will be calculated Take-Profit and Stop-Loss targets, however each target is considered hit, when candle bar closes breaking that target, so Take-Profit and Stop-Loss when hit will slightly differ then what you see at trade/position open.
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Round Numbers up|down unit setting and overall explanation
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Round Number up|down unit: is the distance between round numbers on the chart. Since these round number levels are also used by the algorithm to open/close trades, it is important to set this setting to a logical number, which will correspond to an average price movement of the instrument.
Here are some examples for a few popular instruments on what will the default 1 round number unit correspond to and what would be suggested:
BTCUSD > $1 (this won't work for Bitcoin, try at least $100 - 100units)
SPY: > $1 (one of the best settings for SPY or QQQ, 50cents shows good results as well - 0.5units)
FOREX (all major pairs): > 10PIPs (that may be a bit small, unless scalping, try 50PIPs - 5units)
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Explanation of all the Features | Strategy Configuration Guide | Indicator Settings | Signal Cleanup Analysis
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>>> Customizable Backtesting for a specific date range, results via TradingView strategy, which includes “Deep Backtesting” for largest amounts of data on trading results.
>>> Trading Schedule with customizable trading daily time range, automatic closing/alert trades before Power Hour or right before market closes or leave it open until next day.
>>> 3 Trading Systems.
>>> Static/Dynamic/Trailing Take-Profit and Stop-Loss setups (HIGHLIGHT: Stop-Loss will be moved to Entry after TP1 is taken or a smart trailing Stop-Loss can be used with Stop-Loss dynamically following the trade to minimize risk).
>>> Single or Multiple profit targets (up to 5).
>>> Take-Profit customizable offset feature (set your Take-Profit targets slightly before everyone is expecting it!).
>>> Candle bar signal analysis (matching candle color, skip opposite structured and/or doji candle uncertain signals).
>>> Additional analysis of VWAP/EMA/ATR/EWO (Elliot Wave Oscillator)/Divergence MACD+RSI/Volume signal confirmation (clean up your chart with indicator showing only the best potential signals!).
>>> Advanced Alerts setup, which can be potentially setup with a trading bot over TradingView Webhook (NOTE: This will require advanced programming knowledge).
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Labels, plots, colors explanations:
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>>>>> LONG open: green "house" looking arrow below candle bar.
>>>>> SHORT open: red "house" looking arrow above candle bar.
>>>>> LONG/SHORT take-profit target: green/red circles (multi-profit > TP2/3/4/5 smaller circles).
>>>>> LONG/SHORT stop-loss target: green/red + crosses.
>>>>> LONG/SHORT take-profit hits: green/red diamonds.
>>>>> LONG/SHORT stop-loss hits: green/red X-crosses.
>>>>> LONG/SHORT EOD (End of Day | Intraday style) close (profitable trade): green/red squares.
>>>>> LONG/SHORT EOD (End of Day | Intraday style) close (loss trade): green/red PLUS(+)-crosses.
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Date Range and Trading Schedule Settings
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>>>>> Date Range: Select your start and/or end dates (uncheck “End” for indicator to show results up to the very moment and to use for LIVE trading) for backtesting results, if not using backtesting – uncheck “Start”/“End” to turn it off.
>>>>> Use TradingView “Strategy Tester” to see backtesting results
NOTE: If Strategy Tester does not show any results with Date Ranged fully unchecked, there may be an issue where a script opens a trade, but there is not enough TradingView power to set the Take-Profit and Stop-Loss and somehow an open trade gets stuck and never closes, so there are “no trades present”. In such case you will need to manually check “Start”/“End” dates or use “Depp Backtesting” feature!
>>>>> Trading Schedule: This is where you can setup Intraday Session or any custom session schedule you wish. Turn it ON. Select trading hours. Select EOD (End of Day) setting (NOTE: If it will be OFF, the indicator will assume you are holding your position open until next day!). Please note the EOD trade closure times with the 2 different Intraday close settings when turned on:
At Market Close:
1/3/5min > will close at 15:55pm ET
15min > will close at 15:45pm ET
30min > will close at 15:30pm ET
45min > will close at 15:45pm ET
60min > will close at 15:00pm ET
Before Power Hour:
1/3/5min > will close at 15:00pm ET
15min > will close at 15:00pm ET
30min > will close at 15:00pm ET
45min > will close at 15:00pm ET
60min > will close at 15:00pm ET
>>> Trading Systems: 1) "Open Until Closed by TP or SL": the signal will only open a trade if no trades are currently open/trunning, a trade can only be closed by Take Profit, Stop Loss or End of Day close (if turned on) | 2) "Open Until Closed by TP or SL + OCA": Same as 1), but if there is an opposite signal to the trade which is currently open > it will immediately be closed with new trade open or End of Day close (if turned on) | 3) "OCA (no TP or SL)": There are is Take Profit or Stop Loss, only an opposite signal will close current trade and open an opposite one or End of Day close (if turned on).
>>> Turn On/Off: Current Position SL + Opposite Position Open Signal on the same closing candle bar (If current trade hits Stop-Loss and at that same closing candle bar there is a signal for an opposite direction trade > indicator will close current position as Stop-Loss and immediately open an opposite position). NOTE: With this option turned on, there will be more trades, but not necessarily better results, since after Stop-Loss is hit, it may make sense to wait a little before opening an opposite trade, even if it matches the condition at the same time when Stop-Loss is hit, but sometimes it shows great results, so this setting/feature is included. NOTE: This setting only will work/make sense with TP and SL style/behavior both be set to "Fully Closed Candle"!
>>> Turn On/Off: Turn On/Off: Current Position REGULAR SL | Only the SL + Opposite Position Open will trigger if turned on, IF NOT - THERE WILL BE NO STOP-LOSS AT ALL!!! NOTE: It is very dangerous to trade without Stop-Loss!
>>>>> Signal Candle Bar consuming Take-Profits - position/trade signal candle bar is big enough to "consume"/close ahead the first TP setting > the signal can either be skipped, or all Take-Profit areas pushed ahead using smart formula)
>>>>> MULTIPROFIT | TP (Take-Profit) System: 1) Static – Once the trade is open, all Take-Profit target(s) are immediately calculated and set for the trade > once the target(s) is hit > trade will be partially closed (if candle bar closes beyond several Take-Profit targets > trade will be reduced accordingly to the amount of how many Take-Profit targets were hit) ||| 2) Dynamic – Once the trade is open, only the 1st Take-Profit target is calculated, once the 1st Take-Profit is hit > next Take-Profit distance is calculated based on the distance from trade Entry to where 1st Take-Profit was taken, once 2nd Take-Profit is taken > 3rd Take-Profit is calculated per same logic, these are good for price momentum as with price speeding up – profits increase as well!
>>>>> MULTIPROFIT: SL (stop loss) System | Static: SL is set at position open and remains such; Dynamic: Once ANY TP is taken > SL will be moved to Entry; Trailing: SL will be moved along the position (smart trailing stop-loss), at TP1 taken > SL moves to Entry, at TP2 taken > SL moves to TP1, at TP3 taken > SL moves to TP2 and so on.
>>>>> # of TPs (number of take profit targets): Just like it is named, this is where you select the number of Take-Profit targets for your trading system (NOTE: If "OCA (no TP or SL)" Trading System is selected, this setting won’t do anything, since there are no TP or SLs for that system).
>>>>> TP(s) offset: This is a special feature for all Take-Profit targets, where you can turn on a customizable offset, so that if the price is almost hitting the Take-Profit target, but never actually touches it > you will capture it. This is good to use with HHLL (Highest High Lowest Low), which is pretty much a Support/Resistance as often the price will nearly touch these strong areas and turn around…
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Dynamic/Static/Trailing Take-Profit and Stop-Loss visual examples:
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1) Fully Static Take-Profit and Stop-Loss
This one is a fully static setup for both Take-Profit and Stop-Loss, you can also observe how trade is closed right before the Power Hour (trade can be closed right before Power Hour or right before Market Closes or left overnight as desired).
2) Static/Dynamic, Static Take-Profit and Dynamic Stop-Loss
You can see a static Take-Profit set at position open, while Stop-Loss moves to Entry once TP1 target is taken.
3) Static/Trailing, Static Take-Profit and Trailing Stop-Loss
In here with each Take-Profit taken, Stop-Loss moves along the trade to previous Take-Profit level, you can notice how stop-loss literally follows the trade and reduces the potential loss.
4) Dynamic/Trailing, Dynamic Take-Profit and Trailing Stop-Loss
See how Take-Profit distances increase with price momentum. Just like in previous example - Trailing Stop-Loss is following the trade and reducing the riks.
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Signal Analysis and Cleanup Settings
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>>>>> Candle Analysis | Candle Color signal confirmation: If closed candle bar color does not match the signal direction > no trade will be open.
>>>>> Candle Analysis | Skip opposite candle signals: If closed candle bar color will match the signal direction, but candle structure will be opposite (for example: bearish green hammer, long high stick on top of a small green square) > no trade will be open.
>>>>> Candle Analysis | Skip doji candle signals: If closed candle bar will be the uncertain doji > no trade will be open.
>>>>> Divergence/Oscillator Analysis | EWO (Elliot Wave Oscillator) signal confirmation: LONG will only be open if at signal, EWO is green or will be at bullish slope (you can select which setting you desire), SHORT if EWO is red or will be at bearish slope.
>>>>> Divergence/Oscillator Analysis | VWAP signal confirmation: LONG will only be open if at signal, the price will be above VWAP, SHORT if below.
>>>>> Divergence/Oscillator Analysis | Moving Average signal confirmation: LONG will only be open if at signal, the price will be above selected Moving Average, SHORT if below.
>>>>> Divergence/Oscillator Analysis | ATR signal confirmation: LONG will only be open if at signal, the price will be above ATR, SHORT if below.
>>>>> Divergence/Oscillator Analysis | RSI + MACD signal confirmation: LONG will only be open if at signal, RSI + MACD will be bullish, SHORT if RSI + MACD will be bearish.
>>>>> Volume signal confirmation: LONG/SHORT will only be opened with strong Volume matching the signal direction, by default, strong Volume percentage is set to 150% and weak to 50%, but you can change it as you desire.
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TP System - VERY IMPORTANT INFO!
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"TP PERCENTAGE" - amount by which current trade/position needs to be reduced/partially closed/sold.
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TP System: Dynamic
"TP PERCENTAGE" - will always be the same amount (trade/position size divided by the # of take-profit(TP) targets) and percentage to be closed will always be of the ORIGINAL trade/position.
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TP System: Static
"TP PERCENTAGE" - will always be the same amount IF take-profit(TP) targets are hit 1-by-1 (TP1 > TP2 > TP3 > TP4 > TP5), otherwise it will vary and unless it is a 1st take-profit(TP1), the REMAINING trade/position size will always be smaller than original and therefore the percentage to be closed will always be of the REMAINING trade/position and NOT the original one!
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"TP PERCENTAGE" CheatSheet (these are the only percentages you may see)
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TP PERCENTAGE---Close/Sell Amount-------------Example (trade size: 50 stocks)
20%-------------trade size * 0.2--------------50 * 0.2 = 10 stocks
25%-------------trade size * 0.25-------------50 * 0.25 = 12.5(~13) stocks
34%-------------trade size * 0.34-------------50 * 0.34 = 17 stocks
40%-------------trade size * 0.4--------------50 * 0.4 = 20 stocks
50%-------------trade size * 0.5--------------50 * 0.5 = 25 stocks
60%-------------trade size * 0.6--------------50 * 0.6 = 30 stocks
66%-------------trade size * 0.66-------------50 * 0.66 = 33 stocks
75%-------------trade size * 0.75-------------50 * 0.75 = 37.5(~38) stocks
80%-------------trade size * 0.8--------------50 * 0.8 = 40 stocks
100%------------trade size--------------------50 = 50 stocks
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If for any reason a portion of the current/remaining trade closed at such occurrence was slightly wrong, it is not an issue. Such occurrences are rare and with slight difference in partial TP closed is not significant to overall performance of our algorithms.
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Alert Settings (you don’t have to touch this section unless you will be using TradingView alerts through a Webhook to use with trading bot)
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Here is how a LONG OPEN alert looks like.
NOTE: Each label , , etc. is customizable, you can change the text of it within indicator Input settings.
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
LONG: OPEN
ENTRY: 20000
TP1: 20500
TP2: 21000
TP3: 21500
TP4: 22500
TP5: 23500
SL: 19000
Leverage: 0
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Here is how a TP1 alert will look with 5 TPs breakdown of the trade.
NOTE1: Next to TP1 taken it will show at which price it was triggered.
NOTE2: Next to "TP Percentage" it shows how much of the CURRENT/ACTIVE/REMAINING trade needs to be closed.
NOTE2: If TP2/3/4/5 comes before TP1 - the alert will tell you exactly how many percent of the trade needs to be closed!
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
LONG: TP1
TP1: 20500
TP Percentage: 20%
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Here is how an alert will look for LONG - STOP-LOSS.
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
ENTRY: 20000
LONG: SL
SL: 19000
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Here is how an alert will look for LONG - EOD (End of Day) In Profit close.
ALERT >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>
COIN: BTCUSD
TIMEFRAME: 15M
LONG: EOD-Close (profit)
ENTRY: 20000
EOD-Close: 21900
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Adding Alerts in TradngView
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-Add indicator to chart and make sure the correct strategy is configured (check Backtesting results)
-Right-click anywhere on the TradingView chart
-Click on Add alert
-Condition: Select this indicator by it’s name
-Immediately below, change it to "alert() function calls only", as other wise there will be 2 alerts for every alert!
-Expiration: Open-ended (that may require higher tier TradingView account, otherwise the alert will need to be occasionally re-triggered)
-Alert name: Whatever you desire
-Hit “Create”
-Note: If you change ANY Settings within the indicator – you must DELETE the current alert and create a new one per steps above, otherwise it will continue triggering alerts per old Settings!
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If you have any questions or issues with the indicator, please message me directly via TradingView.
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Good Luck! (NOTE: Trading is very risky, past performance is not necessarily indicative of future results, so please trade responsibly!)
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NOTE: There seems to be a strange glitch when strategy is running live, it will show "double-take" take-profits labels on the chart. This is not affecting the script logic and backtesting results, if you simply change the timeframe real quick to something else then back - it will no longer show the duplicate orders... this must be some sort of a glitch as every alert was thoroughly tested to make sure everything is working!
Alpha-Numerologia by Alien CrewAlpha-Numerologia is our latest generation of market analytical tools, built completely from the ground up using a new cutting-edge mathematical formula, designed by the Alien Crew team.
The purpose of this tool, is to tap into the mathematics behind the market prices themselves, in order to extrapolate areas where the price is likely to find support or resistance. This indicator does not use Fibonacci or Pivot Points in any way whatsoever. It does however rhyme with them every now and then, as is the systematic nature of markets. The key strength of this indicator is its ability to adapt to ever-evolving market conditions, providing users with a real-time, clear visualization of essential price zones.
There are several aspects to the process that goes on in this algorithm. Firstly, it gathers range data from multiple lookback periods of time to understand the underlying asset volatility and reference points for calculation. Following that, it identifies the numerical structure of all the ranges, and finds their common denominators, which are essentially subsets. These subsets are then scaled in real-time, reacting to the change in volatility. A scaling mechanism occurs when the volatility either increases or decreases, causing the algorithm to recalculate the levels using the identified subsets. Since each subset has the same character as the whole, it is by definition a fractal. From a mathematical standpoint, such subsets have no limits on scale. They can be infinitesimal, or infinitely large.
Such a fractal nature provides the benefit of this algorithm being able to adjust to virtually any asset and any chart timeframe. Furthermore, through the monitoring of several temporal periods it is able to correlate alignments of the subsets, which is denominated as a percentage on the chart. Such confluences give more importance to the detected level.
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Remember, the world of trading comes with significant risks and unpredictability. While the Alpha-Numerologia Indicator is a highly sophisticated tool, it should be used in combination with other analytical techniques and a sound risk management strategy. Always conduct your own research before making trading decisions. Due to the extended research and work placed into it, the inner workings behind Alpha-Numerologia are proprietary, and shall not be discussed or disclosed in any way by Alien Crew. The source code is not for sale either.
AUTOMATIC GRID BOT STRATEGY [ilovealgotrading]
OVERVIEW:
This Grid trading strategy can help you maximize your profit in a ranging sideways market with no clear direction.
INDICATOR:
We can get some money by taking advantage of the movement of the price between the range we have determined.
Short positions are opened while the price is rising, long positions are opened while the price is falling.
Therefore, there is no need to predict the trend direction.
What is different in this indicator:
I want to say thank you to © thequantscience. His GRID SPOT TRADING ALGORITHM - GRID BOT TRADING strategy helped me when I was writing my indicator.
I want to explain what I have improved:
1- Grid strategy is a type of strategy that can be traded in very short time frames and users can trade this strategy algorithmically by connecting this strategy to their own accounts with the help of API systems. For this reason, I have developed a software that can give us signals by dynamically changing the long and short messages when users are trading.
2- We can change the start and end dates of our grid bot as we want. It is necessary to use this setting when setting up automatic bots, so that previously opened transactions are not taken into account.
3 - Lot or quantity size should not be excessively small when users are taking automatic trades because exchanges have limitations, to avoid this problem, I have prevented this error by automatically rounding up to the nearest quantity size inside the software.
4 - Users can avoid excessive losses by using stop loss on this grid bot if they wish.
5 - When our price is over the range high or below the range low, our open positions are closed, if the stop button is active. We can also change which close price time frame we take as a basis from the settings.
6 -Users can set how many dollars they can enter per transaction while performing their transactions automatically.
IMPLEMENTATION DETAILS – SETTINGS:
This script allows the user to choose the highs and lows leves of our range. Our bot trades in the specified range.
1. This strategy allows us to set start and end backtest dates.
2. We can change range high and range low leves of our bot
3. IF people want to trade algorithmically with the help of this bot, there are 6 different input systems that will receive the Json codes as an alarm
4. IF the price closes above the upper line or below the lower line, all transactions will be closed. We can determine in which time frame our transactions will be stopped if the price closes outside these levels.We can adjust how our bot works by activating or turning off the Stop Loss button.
5. In this strategy, you can determine your dollar cost for per position.
6. The user can also divide the interval we have determined into 10 parts or 20 equal parts.
7. The grid is divided and colored at the interval we set. At the same time, if we don't want we can turn off colored channels.
Notes:
If you're going to connect this bot to an automatic Long and 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:
Set your range below the support zones and above the resistance zones.
Don't be afraid to take a wide range, it doesn't matter if you make a little money, the important thing is that you don't lose money.
If you have any ideas what to add to my work to add more sources or make calculations cooler, suggest in DM .
Mean Reverse Grid Algorithm - The Quant ScienceMean Reverse Grid Algorithm - The Quant Science™ is a dynamic grid algorithm that follows the trend and run a mean reverting strategy on average percentage yield variation.
DESCRIPTION
Trades on different price levels of the grid, following the trend. The grid consists of 10 levels, 5 higher and 5 lower. The grids together create a channel, this channel represents the total percentage change where the algorithm works. The channel also represents the average change yields of the asset, identified during analysis with the "Yield Trend Indicator".
The algorithm can be set long or short.
1. Long algorithm: opens long positions with 20% of the capital every time the price crossunder a lower grid, for a maximum total of 5 simultaneous trades. Trades are closed each time the price crossover a higher grid.
2. Short algorithm: opens short positions with 20% of the capital every time the price crossover a higher grid, for a maximum total of 5 simultaneous trades. Trades are closed each time the price crossunder a lower grid.
USER INTERFACE SETTING
The user configures the percentage value of each grid from the user interface.
AUTO TRADING COMPLIANT
With the user interface, the trader can easily set up this algorithm for automatic trading. Automating it is very simple, activate the alert functions and enter the links generated by your broker.
BACKTESTING INCLUDED
With the user interface, the trader can adjust the backtesting period of the strategy before putting it live. You can analyze large periods such as years or months or focus on short-term periods.
NO LIMIT TIMEFRAME
This algorithm can be used on all timeframes and is ideal for lower timeframes.
GENERAL FEATURES
Multi-strategy: the algorithm can apply either the long strategy or the short strategy.
Built-in alerts: the algorithm contains alerts that can be customized from the user interface.
Integrated grid: the grid indicator is included.
Backtesting included: automatic backtesting of the strategy is generated based on the values set.
Auto-trading compliant: functions for auto trading are included.
ABOUT BACKTESTING
Backtesting refers to the period 1 August 2022 - today, ticker: ETH/USDT, timeframe 1H.
Initial capital: $1000.00
Commission per trade: 0.03%
Maddrix_club I - Scalper (3commas)Maddrix club I Scalper (3commas version). The code is very different from the ALERTATRON version.
It really is not the same!
Maddrix Club I is a simple, straightforward trading algorithm that goes long or short, based on user’s choice. It is considered to be a scalper, because it aims to capture small profits that accumulates and compound over time.
The theory behind it is based on trend following and DCA .
Strategy type one uses momentum to generate signals.
Strategy type two uses price action only
Very good results have been observed on the 1 min time frame though it technically works on all timeframe (5 min for example, 1 hour also). The most important part of this algorithm is risk management and capital preservation.
You can run this with very little capital, and always make sure that in the worst case scenario, meaning when the market goes against you and all your SO (Safety Orders) are filled, you are using less than your account balance.
If you are in a trending up phase on the weekly time frame, you can go long. If this is a definite trend down, of course go short. During a bear market, stay long, during a bull market, evidently long as well.
For totally new traders, I would recommend to LONG only, and set super low risk settings (cover a 50% drop for example), and see how it runs. Then, as you become a more experienced trader, you can identify trends and short as well, and/or increase your risk.
It works on all markets as long as there is volatility .
The best way to go about changing the settings, is to start off the default values. I’d run it and see how it fits your risk preferences.
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.
*** This one is SPECIAL 3COMMAS**
