DCA Detective | v1.0BINANCE:FETBUSD
The DCA Detective | v1.0 strategy revolutionizes the realm of DCA (Dollar Cost Averaging) trading, integrating advanced trade initiation predicated on savvy Technical Analysis (TA) signals. This strategy's distinctive feature rests in its capacity to leverage TA signals or preset percentage levels to trigger safety orders, providing adaptability based on your preference. Bid farewell to rudimentary safety order placements.
The strategy incorporates a comprehensive array of parameters:
RSI Oversold Level - a predetermined level signaling a potential oversold condition where a price rebound may be imminent.
Divergence Lookback Period - this parameter specifies the duration over which the system scrutinizes for any disparity between price and RSI.
Minimum Bars Between Trades - this guarantees a specific interval between trades, thwarting excessive trading and promoting diversification over time.
Rate of Change (ROC) - a momentum-oriented technical indicator that gauges the percentage alteration in price between the current price and the price a certain number of periods back.
Stochastic Length and Oversold - parameters that delineate the Stochastic Oscillator, another momentum indicator that compares a particular closing price of a security to a spectrum of its prices over a specified period.
Higher Timeframe RSI Length and Oversold Level - for heightened precision, these parameters operate on lower timeframes, offering a wider outlook and aiding in the filtering of market noise.
The DCA Detective | v1.0 strategy deploys bullish divergence identified by the RSI and a crossover of the RSI over the oversold level as primary entry signals. Safety order conditions can be set to either Percentage or Smart, based on your preference. The "Smart" condition utilizes the same rules as the initial entry order to place safety orders.
The strategy also entails additional configuration settings such as the maximum safety orders, safety order price deviation, safety order volume scale, safety order step scale, and take profit percentage.
Main goal is to catch possible market bottom/dip.
In summary, the DCA Detective | v1.0 strategy proposes a sophisticated and nuanced approach to DCA trading. It taps into the potential of TA signals to initiate trades, while using safety orders as a risk management tool, with the intent to minimize possible losses and decrease overall time in trade. This strategy stands as a testament to refined trading tactics, crafted for those who endorse strategic investment and measured risk-taking.
Through webhook integration, the DCA Detective | v1.0 strategy can send signals to 3commas to initiate trades, adjust safety orders, and take profit at the designated percentages. This provides traders with a hands-off approach to trading, allowing them to focus on other areas of their portfolio or strategy while the DCA Detective | v1.0 strategy runs in the background.
So far, I haven't come across a good DCA strategy based on TA orders, so I created my own. I was troubled by my prolonged exposure to red bags, but with proper configuration, this strategy should get you out of the trade as soon as possible. I have managed to enter most of the good coins at an unbeatable average trade time and also eliminate the maximum trade time to less than 10 days !
DCA
TTP AbsolutnoAbsolutno is a pine script strategy for backtesting DCA bots with a different approach for placing both safety orders and take profit levels.
Motivation
Using DCA bots with safety orders most of the time is great during bull markets but in bear markets and strong downtrends it can be really challenging to close your deals only relying on safety orders placed based on percentages: price scale and volume scale.
In the past we introduced a script called "add funds simulator" that people used for sending alerts to bots to add funds and help closing deals in red.
We want to cross the use of TA with the safety orders with the intention of getting better results than statically placed safety orders.
What does Absolutno do?
Absolutno uses TA for safety orders, both for opening new safety orders and also to define how low they should be placed based on the volatility of the asset.
Main features
- ATR SO mode: Safety orders can be placed dynamically based on the general volatility of the asset plus the current volatility.
- TA based SO entries: Safety orders are only placed when the deal start condition is true not only when the price pulls back below the next safety order price level. This acts like a hybrid between "add funds simulator" and a traditional DCA bot. Once a safety order is filled, the next SO level gets active waiting for a DSC to trigger below the new entry level.
- Take profit scale: Traditional DCA bots offer a percentage or TA based exit conditions. Absolutno offers a new mode when you can decide to increase or decrease the TP level with each SO getting filled. For example a value of 1.1 TP scale will cause that each SO getting filled makes the TP% grow 10%. A value of 0.9% will reduce each SO by 10%. The lower the price goes you can "lower your expectation", or if you are filling bullish you can actually increase it.
External signal
It comes with a built-in deal start condition that uses RSI cross over 30 which is used only for illustration purposes since Absolutno is designed to be used with external signals.
Use any external signal to enter a new deal and for adding new safety orders.
You can also activate external take profit signal.
When external TP is enabled, all TP features from the bot are disabled to only react to what the external signal instructs the bot.
Bot integration and alerts
Three type of alerts will be sent to the bot: open deal, add funds and close deal.
You will need to enter your bot id and email token in the settings.
Since this strategy uses add funds: you must be aware that the alerts sent from this strategy will contain the amount of funds to add and therefore the bot receiving these alerts will respect them EVEN if the bot was defined with different SO sizes.
Please make sure you fully understand this before using this signal.
The base order alerts don't contain funds information so the bot will always use the base order size as defined in its own settings.
Simple_RSI+PA+DCA StrategyThis strategy is a result of a study to understand better the workings of functions, for loops and the use of lines to visualize price levels. The strategy is a complete rewrite of the older RSI+PA+DCA Strategy with the goal to make it dynamic and to simplify the strategy settings to the bare minimum.
In case you are not familiar with the older RSI+PA+DCA Strategy, here is a short explanation of the idea behind the strategy:
The idea behind the strategy based on an RSI strategy of buying low. A position is entered when the RSI and moving average conditions are met. The position is closed when it reaches a specified take profit percentage. As soon as the first the position is opened multiple PA (price average) layers are setup based on a specified percentage of price drop. When the price hits the layer another position with the same position size is is opened. This causes the average cost price (the white line) to decrease. If the price drops more, another position is opened with another price average decrease as result. When the price starts rising again the different positions are separately closed when each reaches the specified take profit. The positions can be re-opened when the price drops again. And so on. When the price rises more and crosses over the average price and reached the specified Stop level (the red line) on top of it, it closes all the positions at once and cancels all orders. From that moment on it waits for another price dip before it opens a new position.
This is the old RSI+PA+DCA Strategy:
The reason to completely rewrite the code for this strategy is to create a more automated, adaptable and dynamic system. The old version is static and because of the linear use of code the amount of DCA levels were fixed to max 6 layers. If you want to add more DCA layers you manually need to change the script and add extra code. The big difference in the new version is that you can specify the amount of DCA layers in the strategy settings. The use of 'for loops' in the code gives the possibility to make this very dynamic and adaptable.
The RSI code is adapted, just like the old version, from the RSI Strategy - Buy The Dips by Coinrule and is used for study purpose. Any other low/dip finding indicator can be used as well
The distance between the DCA layers are calculated exponentially in a function. In the settings you can define the exponential scale to create the distance between the layers. The bigger the scale the bigger the distance. This calculation is not working perfectly yet and needs way more experimentation. Feel free to leave a comment if you have a better idea about this.
The idea behind generating DCA layers with a 'for loop' is inspired by the Backtesting 3commas DCA Bot v2 by rouxam .
The ideas for creating a dynamic position count and for opening and closing different positions separately based on a specified take profit are taken from the Simple_Pyramiding strategy I wrote previously.
This code is a result of a study and not intended for use as a full functioning strategy. To make the code understandable for users that are not so much introduced into pine script (like myself), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
CryptoGraph Entry BuilderA complete system to generate buy & sell signals, based on multiple indicators, timeframes and assets
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🟣 How it works
This indicator allows you to create buy & sell signals, based on multiple trigger conditions, placed in one easy to use TradingView indicator to produce alerts, backtest, reduce risk and increase profitability. This script is especially designed to be used with the CryptoGraph Strategizer indicator. Signals produced by this indicator, can be used as external input with the CryptoGraph Strategizer, by adding both indicators to your chart and selecting "External Input" as entry source in the inputs of the Strategizer indicator. From that point on, buy & sell signals generated by the Entry Builder, will be used for backtesting.
Each trigger or filtering condition is selectable and able to be combined using the selection boxes.
Trigger or filter conditions can be used on a different timeframes, and with different assets or coin pairs. Make sure to set higher timeframe filters, to a higher timeframe than your chart timeframe.
🟣 How to use
• Add the indicator to your chart
• Select an indicator you woud like to use for entry analysis. Combine more indicators for more entry filtering
• Configure entry conditions per indicator. It is recommended to add and configure one indicator at a time
• Analyse your buy/sell entries
• Connect to CryptoGraph Strategizer as external input source for backtesting purposes
🟣 Indicator Filters
• ATR :
Average True Range (ATR) is a tool used in technical analysis to measure volatility .
Possible options for ATR entry filtering are an ATR value greater/smaller than your input variable for trade entries, or the ATR crossing your input variable for trade entries.
This enables the possibility to only enter positions when the market has a certain degree of volatility .
• ADX :
The Average Directional Index ( ADX ) helps traders determine the strength of a trend, not its actual direction. It can be used to find out whether the
market is ranging or starting a new trend.
Possible options for ADX entry filtering are an ADX value greater/smaller than your input variable for trade entries, or the ADX crossing your input variable for trade entries.
• OBV :
The On Balance Volume indicator (OBV) is used in technical analysis to measure buying and selling pressure. It is a cumulative indicator meaning that on days where price went up, that day's volume is added to the cumulative OBV total.
Possible options for OBV entry filtering are Regular, Hidden or Regular&Hidden divergences. Divergence is when the price of an asset is moving in the opposite direction of a technical indicator, such as an oscillator, or is moving contrary to other data. Divergence warns that the current price trend may be weakening, and in some cases may lead to the price changing direction.
• Moving Average :
Moving Average (MA) is a price based, lagging (or reactive) indicator that displays the average price of a security over a set period of time. A Moving Average is a good way to gauge momentum as well as to confirm trends, and define areas of support and resistance .
Possible options for MA entry filtering are price being above/below Moving Average 1, price crossing up/down Moving Average 1, Moving Average 1 being above/below Moving Average 2 and Moving Average 1 crossing up/down Moving Average 2.
• Supertrend :
Supertrend (ST) is a trend-following indicator based on Average True Range (ATR). The calculation of its single line combines trend detection and volatility . It can be used to detect changes in trend direction and to position stops.
Possible options for ST entry filtering are Supertrend being in upward/downward direction, or Supertrend changing direction.
• RSI :
The Relative Strength Index ( RSI ) is a well versed momentum based oscillator which is used to measure the speed (velocity) as well as the change (magnitude) of directional price movements.
Possible options for RSI entry filtering are RSI being smaller/greater than your input value, or RSI crossing up/down your input value.
• Stochastic RSI :
The Stochastic RSI indicator ( Stoch RSI ) is essentially an indicator of an indicator. It is used in technical analysis to provide a stochastic calculation to the RSI indicator. This means that it is a measure of RSI relative to its own high/low range over a user defined period of time.
Possible options for Stoch RSI entry filtering are Stoch RSI crossing below or above your input value.
• VWAP Bands :
Volume Weighted Average Price ( VWAP ) is a technical analysis tool used to measure the average price weighted by volume . VWAP is typically used with intraday charts as a way to determine the general direction of intraday prices.
We use standard deviations, determined by user input, to create VWAP bands.
Possible options for VWAP long entry filtering are: price being below the lower VWAP band, price crossing back up the lower VWAP band or price crossing down the lower VWAP band.
Possible options for VWAP short entry filtering are: price being above the upper VWAP band, price crossing back down the upper VWAP band, or price crossing up the upper VWAP band.
• Bollinger Bands :
Bollinger Bands (BB) are a widely popular technical analysis instrument created by John Bollinger in the early 1980’s. Bollinger Bands consist of a band of three lines which are plotted in relation to security prices. The line in the middle is usually a Simple Moving Average ( SMA ) set to a period of 20 days (the type of trend line and period can be changed by the trader; however a 20 day moving average is by far the most popular).
Possible options for BB long entry filtering are: price being below the lower Bollinger band , price crossing back up the lower Bollinger band or price crossing down the lower Bollinger band .
Possible options for BB short entry filtering are: price being above the upper Bollinger band , price crossing back down the upper Bollinger band , or price crossing up the upper Bollinger band .
• WaveTrend :
WaveTrend (WT) is a smoothed momentum oscillator which enables it to detect true reversals in an accurate manner.
Possible options for WT entry filtering are: Green/red dots below or above a certain WaveTrend value, Regular Divergence, Hidden Divergence and Regular&Hidden Divergence.
CryptoGraph StrategizerA complete system to backtest and automate comprehensive trading strategies
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🟣 How it works
This indicator allows you to use buy & sell signals from external CryptoGraph indicators, and fully backtest these signals in the TradingView strategy tester. After configuring buy & sell signals, the trader can look into exit criteria with this indicator. The indicator offers percentage based an ATR based take profit/stop losses, as well as safety orders (DCA) in order to get a better average entry price.
Once your strategy is fully set up to your desired results, it's possible to set up alerts and connect the indicator through an automation platform ( API connection), to your broker. Alertatron & Wick Hunter auto configuration is included, meaning everything configured in the indicator settings, will automatically be carried out with Alertatron & Wick Hunter syntaxes.
🟣 Features
• Multiple methods of scaling in entries (Multiple DCA/Pyramiding methods). There will be an option to scale up or down your volume per order and distance between orders.
• Multiple methods of determining order sizes. Methods are percentage risk per trade, dollar risk per trade, position size in contracts, position size in percentage and position size in dollar.
• Multiple methods and levels of taking profits and losses. Both percentage based and ATR based take profit and stop loss.
• Option to use external indicator buy/sell signals for entry.
• Visualised liquidation prices in TradingView (both cross and isolated)
• Information panel on chart with additional information regarding your strategy results
• Bot setup directly from indicator inputs tab with Wick Hunter & Alertatron
🟣 How to use
• Choose a symbol that corresponds to your bot pair and exchange
• Pick a chart time frame
• Always use the regular candle type
• Configure your deal start condition
• Configure your profit target
• Use the Take Profit/Stop Loss feature to set a target for profit and loss
• Configure your safety orders
• Check your backtest parameters
•Make sure that the initial capital and order size make sense. Since you can use pyramiding in your strategy with safety orders, the sum of all deals should not be bigger than the initial capital
Broadview Economic StudioThank you for taking the time to read this description. We'll be taking a look at the Broadview Economic Studio. This has been a work-in-progress for years and is a very powerful tool for planning trades with complex volume scaling strategies. We will be talking about many indicators and types of indicators used in the public domain, but it is NOT recommended to reverse engineer our scripts as there is quite a bit of logic in the code that works to make each common approach entirely unique. So although you may understand quite a bit about oscillators, the way they work with the rest of the logic within the script may change the way you know them to work from elsewhere.
In the chart snapshot above you'll see a mild configuration where I only had to tweak a few settings. Commissions are set to 0.1%, starting capital is set to $10,000, and slippage is off. In my tests orders came through less than a penny off. Generally speaking, there are really only two situations in which you should be concerned about slippage. The first is if you trade really low timeframe charts like the 1 second. This tool, while it works for any timeframe, is programmed on the 45 minute timeframe and works best there. The other situation in which you should be prepared for slippage is if you're using extremely high volume trades in the hundreds of thousands or millions depending on the market cap and liquidity of the asset you're studying. Large orders like that have to be split up among several deals and that can cause slippage.
There are 31 primary inputs for users to tweak. Each input is grouped within a module called a Suite. Each suite has a focus like filtering signals or strategically allocating volume according to your strategy. Everything starts with the Origin Suite. The Origin Suite is a group of inputs that generates Tops & Bottoms from price action. It uses math like Rate of Change, where one can specify a required rate of change before an Origin signal can be made, and users can specify how much lower in price a bar must be compared to previous bars. So with the Origin Suite, users can control how often they want to see originating signals and under what conditions they can appear.
We used to use WVF and CVI to produce top and bottom signals, but our Origin Suite works much better for systematically generating profitable configurations.
The triangles you see on the chart represent markers, potential signals, or Prop Signals as they're referred to within the script. The blue arrows represent trades where Prop Signals were allowed to pass as true long signals. There are two ways to ignore Prop Signals. You can filter the markers entirely, or you can reduce their volume scaling to the minimum which is usually $10 for most exchanges. We're first going to be talking about some of the primary DCA inputs before we talk about the technology we use to filter and overload signals.
Here are some important features found within the script:
Base Orders
Safety Orders
Take Profits
Change-Based Volume Scaling
Ignoring Low or Medium Changes
Overloading
Filtering
Alert Messages w/ Volume Scaling
Let's walk through each of these features in more depth.
The Base Order is the initial Long position within a series. It comes in first and is followed by all of its Safety Orders. The Base Order is set to $25 within the script by default. Keeping the base order low allows one to reserve more of their capital for Safety Orders that are lower within a dip, and thus, lower the user's Position Average. The primary feature of this script is to help users plan their volume scaling strategically, and this is where we start. It's this kind of due diligence and effort in protecting trades that makes this script unique.
So we start with a low Base Order. Then, we follow with a lot of Safety Orders. Typically in DCA this is done in consistent time intervals and in consistent amounts. So in regular DCA one may invest the same amount bi-weekly on pay day. They use the financial instrument as a sort of savings and average their position over their consistent investments. This is not where the bleeding edge of DCA is today though. In modern Doller Cost Averaging, I would expect to see signals and volume scaling based on logic.. as opposed to being consistent intervals.
This sets up the explanation of the primary means of volume scaling within the script. Mathematically, we start with the net balance. This is your specified starting balance plus any wins or losses. Users specify what % of their Available Balance they would like to start with when volume scaling. This percent of capital is then multiplied by a Safety Order Multiplier. The safety order multiplier is made up of a number specified by the user, multiplied by the number of the Safety Order you're on. So user's can control this equation/algorithm and scale their investments as the number of Safety Orders increases and drops in price become more opportune.
The Take Profit within the script lets users specify their desired ROI from a series. So if a user sets a 60% take profit, the script will set a price from the position average that when reached will give the user a 60% ROI for the series including its Base Order and all its Safety Orders.
Before moving on, let's talk about the amazing internal reporting found in the script. When you zoom in on the blue arrows, you can see each trade is accompanied by some extremely helpful information. This is just another feature that makes this script unique, it is the feature that gives us accurate reporting and ultimately allows us to connect with TradingView's Strategy Tester in a way that provides instant backtests with good merit. With this reporting not only can users get reports and information on trades made on different assets with different configurations, but user's can perform a deep dive on each configuration and know exactly what was going on for each trade. The first number is the number of the safety order the script is on. Remember, this is used in the primary volume scaling math. The second number is the amount the script spent on the current trade. The third number denotes the cumulative spending for the series. The final number displays the script's available balance at that time. With these numbers, the TradingView Strategy Tester, and the List of Trades feature, users can practice as much due diligence as they need during their studies.
Let's move on to talking about my favorite suite within the script, the Volume Scaling Suite. Here there are two primary means of controlling volume scaling. Although, in the near future there will be more.
In this suite you'll find Change-Based Volume Scaling and Position Average Volume Scaling. Position Average Volume Scaling is quite easy to explain. This feature only allows signals to pass if they are lower in price than your base order. In this way, users can apply most of their capital to trades that lower their position average. Simply having the money in the market can boost profits, but having a lower Position Average is the entire reason we DCA. Change-Based Volume Scaling is quite a bit more complex.
In theory, one could argue that every moment is a great moment to buy. It's just that some moments are more opportune than others. So it's not about perfect signals as much as it's about proper volume scaling.
Change-Based Volume Scaling allows us to set rules that dictate how much volume scaling is used based on the asset's current delta, or Rate of Change.
Using CBVS, one can downscale capital applied to signals with a low ROC, or simply ignore them. So if a signal comes in and the price hasn't changed very much then you can automatically use less volume for the trade. One can do the same thing for medium changes, and the user can specify what quantifies as a low or medium change. Users can give extra volume to signals with a greater rate of change, or overload signals with a high rate of change! So the CBVS feature gives users the ability to allocate volume based on logic rooted in the asset's rate of change. If a signal has dropped a lot in price, then generally, it is deserving of more capital and that's what makes this feature unique and so powerful.
There are two kinds of Overloading found in the script. There's overloading from CBVS, and then overloading from the 4 signal filtering suites. There's an important difference to note before we move on. Overloading performed by CBVS is based on ignored signals. So if you ignore low or medium change signals, and you have CBVS Overloading on, the script will allocate more capital to High Change signals. When signals are ignored, they are downscaled to $10. Whereas with the filtering suites, if a signal is filtered the Prop Signal triangle marker is removed entirely. The overloading in that scenario is simply applied to signals that aren't filtered. The reason it's done this way is because allowing ignored signals to still come in, with the lowest volume scaling possible, keeps the Safety Order count rising which works in the volume scaling math. This math is intrinsic to getting capital deep within dips and crashes.
So in future versions we may allow ignored signals to be filtered out entirely but for the time being, simply scaling them down to the lowest possible amount is what produces the best and most consistent configurations.
Let's talk about filtering signals, and the overloading provided within each filtering suite.
Here you can see our Overbought & Oversold Heatmap V3. This is a unique indicator that takes 15 common oscillators and visualizes them in a way that clearly denotes confluence. Looking at this indicator makes it easer to read cycles and trends. It is quite common for investors to base their entire scripts on one or more of the oscillators found within the OBOS Heatmap V3. So the OBOS Heatmap V3 is an awesome way to ensure your signals follow an oversold trend! The orange represents an oscillator being oversold, while the yellow represents it being overbought. Generally, when an asset is oversold it is a better time to buy. One can filter signals based on this information and use the Heatmap's unique ability to quantify confluences. In this script users can set a sensitivity and that sets the number of oscillators that must be in agreement before a signal is allowed to pass.
Here are the oscillators found within the OBOS Heatmap:
*Please keep in mind that although some of these oscillators may have big names, the code and math in the script may work differently than you're used to. This is because the code and math is changed quite a bit, and the overall intended functionality of the OBOS Heatmap has a larger scope than any one indicator. It's also important to note that the lengths for these oscillators are set low and are meant to classify the individual signal as either overbought or oversold, and not the entire period. So while the OBOS Heatmap is awesome for trends and cycles, it's ultimately meant to classify individual price bars as either overbought or oversold according to a consensus.*
Relative Strength Index
Money Flow Index
Commodity Channel Index
Aroon Oscillator
Relative Volatility Index
Fast Stochastic Detrended Price Oscillator
Fast Stochastic Elders Force Index
Fast Stochastic Relative Strength Index
Fast Stochastic Relative Vigor Index
Fast Stochastic Klinger Oscillator
Fast Stochastic Awesome Oscillator
Fast Stochastic Ultimate Oscillator
Fast Stochastic Chande Momentum Oscillator
Fast Stochastic On Balance Volume Oscillator
Fast Stochastic Moving Average Convergence/Divergence
Each band of the Overbought & Oversold Heatmap represents an oscillator. When it's orange it's said to be oversold. When it's yellow it's said to be overbought. The indicator turns purple during trends and reversals where it is neither overbought nor oversold. It can differentiate between uptrends and downtrends with differing colors of purple, but the OBOS Heatmap is not used for trends or cycles in this script. It is used to quantify oversold confluence.
Let's talk about the Dominance Suite.
First note in the top portion of the screenshot above, you will see various colors in the script. It replaces the price line with something we call Price Flow bars. So when you add the script it's best to make the stock price line invisible in TV settings. The Price Flow Bars use a preset EMA to color price action as being in either a downward momentum or upward momentum. The triangular signals represent dark teal for the initial long marker within a series, dark green for long orders and long signals that convert into safety orders, and light green for safety orders. This is more logic that makes this script really unique. The dark green initial long marker signals are rarely seen. You can find them at the beginning of a new series of signals and they work to establish when a new series of signals should begin. The dark green signals actually denote a long base order opportunity, but if a series has already started then these signals are converted into Safety Orders. The Safety Orders then come in light green, and red for Prop Shorts. Prop Shorts work with Initial Longs to establish the start of a new series. More on that math I cannot tell.
In the bottom half of the screenshot is the Dominance Suite itself. It's another one of the four filtering suites found in the script. It is made up of 7 oscillators that work to classify a price bar as being controlled by either the bears or the bulls. If a price bar is controlled by the bears it is said to be a better investment. The Dominance Suite works by applying a moving average to the balance of power. This is the way TradingView has intended the balance of power to be used, and works quite nicely in classifying individual price bars as either bearish or bullish. It's not an overall trend indicator as much as it states whether a bar is mostly controlled by the bears or the bulls.
Here are the oscillators found within the Dominance Suite:
SMA of BOP
EMA of BOP
HMA of BOP
WMA of BOP
VWMA of BOP
TEMA of BOP
LSMA of BOP
Within the script, there is an input for a negative threshold. When each of these 7 oscillators is in confluence and below this set threshold, the Prop Long will be allowed to pass as a real trade.
Keep in mind that each filtering suite also has the option to overload signals.
So not only can you filter signals based on these suites but you can also apply additional volume scaling to signals that don't get filtered.
Here we have the True Oscillator. The True Oscillator is a brand new oscillator. It's similar to things like the RSI or DPO, but technically speaking it considers many more factors into its average than other oscillators. It considers balance of power, sentiment, volume, momentum, gravity, and places special-strategic weighting on price data based on whether it's opening, closing, high, or low. If you stack the True Oscillator up with the RSI you'll notice right away they look similar, but each movement is quite different. Overall the movements are more balanced, the individual bars are more consistent with price data, and the swings are more clearly pronounced while simultaneously having a better register of strength in momentum. We use this indicator to filter and overload signals, to trade according to momentum, and to provide a 16th independent oscillator that can check the OBOS Heatmap without having to be confluent.
The final filtering suite is based on Net Volume. It classifies signals as oversold when there is a significant negative trend in net volume. If Net Volume is under 0, and trends downward for either 3, 4, or 5 bars in a row then it will mark a signal as oversold and allow it to pass. Then, if overloading for this suite is turned on it will allocate more volume to signals it does not filter out.
There is a lot that can be said about this strategy. The primary takeaway though is that it's not just one strategy. It's a tool for everyone, to help them plan their approach to different assets in different market climates. This tool can help you study current market conditions. It can allow you to plan a strategic approach to market segments, and see how your strategy would fare if new market data performed similarly. It's not just one strategy, but more of a strategy printer.
The Origin Suite allows users to plan the positioning of their signals. The Overbought & Oversold Suite allows users to filter their signals based on whether or not they are oversold. The Dominance Suite allows users to filter signals based on whether the market is being controlled by the bears or the bulls. The True Oscillator gives users the ability to filter signals based on a deep and powerful momentum oscillator. The Net Volume Suite lets users filter signals based on volume trends. When signals are filtered, signals that pass, can be overloaded with additional volume scaling. Features like Change-Based Volume Scaling and Position Average Volume Scaling give users plenty of inputs to create complex volume scaling strategies. Common-sense DCA inputs allow users to scale into markets the way pros do.
The Broadview Economic Studio is a powerful tool for planning trades with complex volume scaling strategies.
Users can plan their approach to different kinds of markets. They can link the script with their bot or broker like 3Commas, and the script will automatically send the correct volume scaling through to the bot.
Thank you for your time, and for reading the description of the Broadview Economic Studio.
DCA Simulator A simple yet powerful Dollar Cost Averaging (DCA) simulator.
You just add the script to your chart, and you'll be able to see:
- Every single entry with its size
- The evolution of you average price in time (blue line)
- The profit and loss areas (where market price < average price the DCA is at loss, and the background is colored in red. At the contrary, where mkt price is > average price, it's profit area and the background is green).
- Max drawdown: the point in price and time where the DCA loss is maximum in the considered time interval. The drawdown amount is specified.
- Profit (or loss) and total cost at the end of the time interval or at the present day: the script shows how much the DCA is netting at a profit or loss, as well as the total cost of the DCA itself.
The parameters are:
- Date start and date end: time interval of the DCA simulation
- DCA period (you can choose between daily, weekly and monthly)
- Week day or month day if you choose those periods
- Single operation size (in base currency)
- Option to choose a DCA LONG or DCA SHORT (for uber bears)
- Option to include an exit strategy that partially closes your position (the % size closed can be chosen as well with the parameter "exit_close_perc") every time the DCA realizes a specific gain (choosable with the parameter "exit_gain_threshold"). If you choose "none" as an exit strategy, the script will assume to never close positions until the end of the period or the present day for simulation purpose.
NB: just ignore the TV strategy tester results, all the data are visible on the chart.
Linear EDCA v1.2Strategy Description:
Linear EDCA (Linear Enhanced Dollar Cost Averaging) is an enhanced version of the DCA fixed investment strategy. It has the following features:
1. Take the 1100-day SMA as a reference indicator, enter the buy range below the moving average, and enter the sell range above the moving average
2. The order to buy and sell is carried out at different "speed", which are set with two linear functions, and you can change the slope of the linear function to achieve different trading position control purposes
3. This fixed investment is a low-frequency strategy and only works on a daily level cycle
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Strategy backtest performance:
BTCUSD (September 2014~September 2022): Net profit margin 26378%, maximum floating loss 47.12% (2015-01-14)
ETHUSD (August 2018~September 2022): Net profit margin 1669%, maximum floating loss 49.63% (2018-12-14)
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How the strategy works:
Buying Conditions:
The closing price of the day is below the 1100 SMA, and the ratio of buying positions is determined by the deviation of the closing price from the moving average and the buySlope parameter
Selling Conditions:
The closing price of the day is above the 1100 SMA, and the ratio of the selling position is determined by the deviation of the closing price and the moving average and the sellSlope parameter
special case:
When the sellOffset parameter>0, it will maintain a small buy within a certain range above the 1100 SMA to avoid prematurely starting to sell
The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
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Version Information:
Current version v1.2 (the first officially released version)
v1.2 version setting parameter description:
defInvestRatio: The default fixed investment ratio, the strategy will calculate the position ratio of a single fixed investment based on this ratio and a linear function. The default 0.025 represents 2.5% of the position
buySlope: the slope of the linear function of the order to buy, used to control the position ratio of a single buy
sellSlope: the slope of the linear function of the order to sell, used to control the position ratio of a single sell
sellOffset: The offset of the order to sell. If it is greater than 0, it will keep a small buy within a certain range to avoid starting to sell too early
maxSellRate: Controls the maximum sell multiple. The maximum ratio of a single sell position does not exceed defInvestRatio * maxSellRate
maxBuyRate: Controls the maximum buy multiple. The maximum ratio of a single buy position does not exceed defInvestRatio * maxBuyRate
maPeriod: the length of the moving average, 1100-day MA is used by default
smoothing: moving average smoothing algorithm, SMA is used by default
useDateFilter: Whether to specify a date range when backtesting
settleOnEnd: If useDateFilter==true, whether to close the position after the end date
startDate: If useDateFilter==true, specify the backtest start date
endDate: If useDateFilter==true, specify the end date of the backtest
investDayofweek: Invest on the day of the week, the default is to close on Monday
intervalDays: The minimum number of days between each invest. Since it is calculated on a weekly basis, this number must be 7 or a multiple of 7
The v1.2 version data window indicator description (only important indicators are listed):
MA: 1100-day SMA
RoR%: floating profit and loss of the current position
maxLoss%: The maximum floating loss of the position. Note that this floating loss represents the floating loss of the position, and does not represent the floating loss of the overall account. For example, the current position is 1%, the floating loss is 50%, the overall account floating loss is 0.5%, but the position floating loss is 50%
maxGain%: The maximum floating profit of the position. Note that this floating profit represents the floating profit of the position, and does not represent the floating profit of the overall account.
positionPercent%: position percentage
positionAvgPrice: position average holding cost
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策略说明：
Linear EDCA（Linear Enhanced Dollar Cost Averaging）是一个DCA定投策略的增强版本，它具有如下特性：
1. 以1100日SMA均线作为参考指标，在均线以下进入定买区间，在均线以上进入定卖区间
2. 定买和定卖以不同的“速率”进行，它们用两条线性函数设定，并且你可以通过改变线性函数的斜率，以达到不同的买卖仓位控制的目的
3. 本定投作为低频策略，只在日级别周期工作
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策略回测表现：
BTCUSD（2014年09月~2022年09月）：净利润率26378%，最大浮亏47.12%（2015-01-14）
ETHUSD（2018年08~2022年09月）：净利润率1669%，最大浮亏49.63%（2018-12-14）
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策略工作原理：
买入条件：
当日收盘价在 1100 SMA 之下，由收盘价和均线的偏离度，以及buySlope参数决定买入仓位比例
卖出条件：
当日收盘价在 1100 SMA之上，由收盘价和均线的偏离度，以及sellSlope参数决定卖出仓位比例
特例：
当sellOffset参数>0，则在 1100 SMA以上一定范围内还会保持小幅买入，避免过早开始卖出
单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
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版本信息：
当前版本v1.2（第一个正式发布的版本）
v1.2版本设置参数说明：
defInvestRatio: 默认定投比例，策略会根据此比例和线性函数计算得出单次定投的仓位比例。默认0.025代表2.5%仓位
buySlope: 定买的线性函数斜率，用来控制单次买入的仓位倍率
sellSlope: 定卖的线性函数斜率，用来控制单次卖出的仓位倍率
sellOffset: 定卖的偏移度，如果大于0，则在一定范围内还会保持小幅买入，避免过早开始卖出
maxSellRate: 控制最大卖出倍率。单次卖出仓位比例最大不超过 defInvestRatio * maxSellRate
maxBuyRate: 控制最大买入倍率。单次买入仓位比例最大不超过 defInvestRatio * maxBuyRate
maPeriod: 均线长度，默认使用1100日MA
smoothing: 均线平滑算法，默认使用SMA
useDateFilter: 回测时是否要指定日期范围
settleOnEnd: 如果useDateFilter==true，在结束日之后是否平仓所持有的仓位平仓
startDate: 如果useDateFilter==true，指定回测开始日期
endDate: 如果useDateFilter==true，指定回测结束日期
investDayofweek: 每次在周几定投，默认在每周一收盘
intervalDays: 每次定投之间的最小间隔天数，由于是按周计算，所以此数字必须是7或7的倍数
v1.2版本数据窗口指标说明（只列出重要指标）：
MA：1100日SMA
RoR%: 当前仓位的浮动盈亏
maxLoss%: 仓位曾经的最大浮动亏损，注意此浮亏代表持仓仓位的浮亏情况，并不代表整体账户浮亏情况。例如当前仓位是1%，浮亏50%，整体账户浮亏是0.5%，但仓位浮亏是50%
maxGain%: 仓位曾经的最大浮动盈利，注意此浮盈代表持仓仓位的浮盈情况，并不代表整体账户浮盈情况。
positionPercent%: 仓位持仓占比
positionAvgPrice: 仓位平均持仓成本
3Commas Bot DCA Backtester & Signals FREEThis is a DCA Strategy backtester + signals, built to emulate the 3Commas DCA bots. It uses your choice of 4 different buy signals, 2 of which can be adjusted in the settings. Everything is customizable so you can backtest specific settings with different buy signals and find the best performing strategy for your risk tolerance and capital. It can be used to backtest strategies on stocks as well, but just make sure your base order is larger than the share price for the entire backtesting range or it will not calculate properly.
You can use this template to code your own buy signals and then backtest them as a DCA strategy if you know some basic pine script.
The indicator shows all of your backtesting orders on the chart. The red line is your take profit level, the blue line is your average price level, the white line is your first order and the green lines are your average down orders. If you enable a stop loss in the settings your stop loss will be shown as an orange line once all of your average down orders have been hit, it will not be set until price has dipped below your covered trading range.
These levels update when things change during backtesting so you can visualize your strategy and how it would perform as well as see if your percentage deviation is large enough to cover dips. When backtesting trades are taken, the chart will show where they were taken(in backtesting) along with info on those trades such as the number each order is, the size of that order and the percentage deviation that order is from the initial buy.
SENDING SIGNALS TO 3COMMAS
Tradingview cannot sync this backtester to 3Commas and with the way alerts are setup for strategies on Tradingview, the best option for you to give signals to your bot would be to use this backtester to figure out what trigger you want to use and then setup that indicator separately to send alerts to your bot. All of the indicators used for signals in this backtester are available for free and can be configured to match this backtester and send alerts to 3Commas for you. Just make sure you set your alerts to once per bar close and don’t use less than a 15 second timeframe because then you could trigger the Tradingview threshold for alerts and get your alerts shut off.
You can also use this backtester with your own buy triggers if you know a little pine script. Just make copy of the script and code in your own buy signals and see how it backtests.
INFO PANEL FOR ANALYZING YOUR STRATEGY
The right hand side of the screen will show an info panel that shows a lot of different information so you can quickly see your bot settings and how it performed right on the screen.
In the top right corner you will see in purple your bot settings. These include your stoploss % if turned on, take profit %, average down order %, average down order % multiplier, volume multiplier, max number of orders allowed and size of your base order.
The top section of the first column “Current Trade” shows these stats: the open trade’s average price, the open trade’s take profit price, the open trade’s PNL, how far price is from your open tarde’s take profit level in percentage, your open position size and number of open orders.
The bottom section of the first column “Overall Performance” shows these stats: total number of trades taken during backtesting range, the largest amount of trades that were open at one time during backtesting, the max drawdown, the average number of bars per trade, gross profit, net profit, percent profit from your initial capital, current portfolio value and your initial capital.
CUSTOMIZABLE OPTIONS TO FIND THE PERFECT STRATEGY
Stoploss On/Off
This will turn your stoploss on or off. By default it is set to off and will not affect anything unless turned on.
Stoploss Percentage
This is the percentage below your final average down order price that will be set as a stoploss to keep your account from going too far in the red on big dips.
Take Profit Percentage - This is the percentage of profit you want the trade to hit before taking profit on your entire DCA trade. This level updates everytime you average down.
Average Down Percentage - This is the percentage that price has to drop from your initial order to initiate your first safety order. If the Average Down Percent Multiplier is set to 1 then this percentage will be the same for every average down order.
Average Down Percentage Multiplier - This multiplies your Average Down Percentage so each safety order needs a larger percentage deviation than the previous one. This keeps your buys closer together at the beginning and further apart when you hit more orders so you can extend your trading range but still be aggressive when price is going sideways.
Volume Multiplier Per New Order - This multiplies the size of each trade based on your base order. If you set it to a 2x multiplier then each average down order will be 2 times the size of the last one. So for example, a $100 base order with a 2x multiplier would have these values for the first 3 average down orders: 200, 400, 800.
Size Of Base Order - This is the size of your first position entry and will be used as a starting point for the volume multiplier. If your base order is $100 then it will buy $100 worth of whatever crypto you are backtesting this on. If you are looking at stock charts, you need to make sure your base order is higher than the share price across the entire backtesting range or it will not perform correctly.
Max Number Of Orders - This is the maximum number of orders the bot can take, including your base order. Adjust this to suit the amount of capital you are willing to allocate to your bot based on how much money it will require to run according to your bot settings.
TIPS ON HOW TO USE FOR BEST RESULTS
If you don’t have a lot of capital to work with, then use longer timeframes with a reasonable take profit percentage so that you don’t need a lot of average down orders. You can also try keeping the volume multiplier close to 1.
You can use the 3Commas dca bot settings page to see how much capital you will need for your strategy if you match it to the settings you have on this indicator. You can also check to see how much of a percentage deviation your bot is covering to make sure you have a reasonable range to trade in and orders to cover big dips. You can also check your coverage by seeing how far down the chart the green lines cover, which are your average down orders.
Make sure the initial capital in the properties tab of the settings has enough to cover all of your orders otherwise you will get unrealistic backtesting results. Also, make sure you leave the order size in the properties tab on contracts so it calculates your trades correctly. The only settings you need to touch in the properties tab is the initial capital. Unless you are trading somewhere that has lower commission fees, then you can change that to match, but leave all the other settings as is for it to function properly.
Increasing the volume multiplier will make your average price and take profit target follow the price action a lot closer as price falls, but it can also lead to having very large orders very quickly once you get into the 1.5-3x multiple range. Try using a high volume multiplier with less safety orders and you will get better results, however you need to have money on the sidelines to add on major dips to keep your bot turning a profit. Be very careful with this as greed and impatience will hurt your overall performance. This bot is meant to make money with lots of small wins so don’t get greedy and make sure you have enough money to cover large dips. If you are being aggressive with your bot, then I recommend only using 25% or less of your portfolio to trade aggressively and then use the smart trade feature on 3commas to add chunks of funds to your trades when price dips below your last safety order. Or if you want it to run without any supervision, then use lower volume multipliers and have lots of safety orders that can cover entire bear markets and still keep buying lower.
It’s a good idea to have some capital on the sidelines that you can add in when price dips quickly. This will help lower your average price and allow your bot to get out in profit quicker. 3Commas bot has a smart trade feature that will allow you to track your average price when adding extra funds and it will automatically update your other orders which is very convenient. Look at the longer timeframes when price dips and only add chunks at major areas where price is very likely to bounce. Or you can be aggressive when trading and add to your position when price dips and is at a likely bounce zone to maximize profits.
Only trade coins that have a good amount of liquidity as the larger your orders get, the harder it will be to sell if there isn’t much liquidity. Also, beware of how large your first order is as it will usually be a market order and can move the market if there is not much liquidity.
Since this bot takes a lot of trades and performs best when taking small profits consistently, you will need to factor in exchange fees. The bot is set to .5% commission(you can change this) on the buy and sell orders as most exchanges charge that amount. Some exchanges offer no fee trading on certain coins so be sure to look around for those so you can keep the commissions and maximize profits.
I strongly encourage you to try out a lot of different setting combinations across multiple different coins and do it across a few months to see how it would have performed under various market conditions. This will help you get a better idea of how much of a percentage deviation you’ll need to be able to cover to keep your bot running and making constant profits. You can also use the deep backtesting feature of the strategy panel to see how it would have done, but just beware that the info panel of the indicator will not reflect deep backtesting results, only the normal backtesting range.
MARKETS
This backtester can be used on any market including crypto, stocks, forex & futures. You just need to make sure your base order is larger than the share price when using this on things besides crypto.
TIMEFRAMES
This backtester can be used on all timeframes.
Position size in dollar cost average strategySTATIC DCA
Using the tradingview.com, an algorithm was generated that simulates the behavior of the DCA methodology. This algorithm simulates the purchase of 1000 USD on the 15th of each month, regardless of the bitcoin price. It is considered a static DCA, since the amount to be invested remains always fixed.
The inputs to the function are, the day number of the month in which the purchase is to be made, the start date of the simulation and the capital to be invested month by month. What the function does is to receive the value of the investment, and if the day entered in the function coincides with the current day, it will divide the invested capital by the price of the asset, obtaining a position size that accumulates in each purchase. With this data we can obtain the total invested capital, the net profit, as well as the average buying price.
DYNAMIC DCA
The dynamic DCA, bases its operation on the use of moving averages and standard deviations, in order to find the zones where the price has a lower value than the deviation under the mean. This condition can be considered as an accumulation zone.
The data were obtained in a one-week time window, using the security request method. Since purchases are made one every month, the daily time window generates many false signals, while the one-month time window generates few signals. The analysis is performed on data from 52 weeks equivalent to one year.
Subsequently we created an algorithm based on the ATR, for the selection of the position size, the fundamental characteristic of this development is that the algorithm will not invest the total of the capital destined to month to month. The amount of money to be invested will vary between 0 and 100%, in discrete values defined by the mean and standard deviation in the ATR calculation. Uninvested money will accumulate until the asset price enters the accumulation zone, where this capital will be released and used to accumulate as much of the asset as possible.
The function developed for the dynamic DCA receives the same inputs as the previous function, plus an extra condition and the variable resulting from the calculation of the position size.
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ANALYSIS
In the analysis, we will consider ratios, such as cumulative position size, percentage net profit, invested amount and average buying price. The simulation of the results starts on 12/18/2017. For the analysis in all charts, the red line will represent the static DCA ratios, while the blue line will represent the dynamic DCA ratios.
Amount invested
At the end of this backtesting, the quantity invested is the same for each of the cases, however, the way the money enters the market is different. Money enters steadily and in the same amount in the static DCA, while in the dynamic DCA, there are months in which no purchases are made, or partial purchases are made. The remaining capital that accumulates and flows into the market, when bitcoin reaches its lowest price and enters accumulation zones.
Accumulated position size
It can be noted that the dynamic DCA strategy obtains a better result, accumulating a total of 6.62 bitcoins, 18% higher than the static DCA strategy.
Percentage net profit
The static DCA strategy in the last rally was approximately 40% lower in percentage return on invested capital than the dynamic DCA strategy.
Average buying price
In the initial part of the simulation the average buying price of bitcoin using the static DCA strategy was lower, however, as time went on, the dynamic DCA strategy obtained a better average buying price, with 15% cheaper.
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CONCLUSIONS
The dynamic DCA strategy was more efficient in the use of investment resources.
- One of the main advantages of the dynamic DCA strategy is that it will allow us to enter the spot market even after it has passed its parabolic growth cycle. We will be able to accumulate bitcoin in the bearish regime, having our largest purchases in the accumulation zone.
- Due to these characteristics, the time in which we stay in negative returns is going to be shorter than with a DCA strategy.
- This algorithm can be tested on different assets, extrapolated to Python and by connecting via API, you can configure the automatic purchase of cryptocurrencies, which generates an accumulation of assets based on back testing, relatively superior to what several wallets and exchanges offer.
- The parameters for configuring the dynamic DCA strategy are quite basic and do not require professional knowledge, and the optimal configuration can be obtained by visualizing the results.
Wunder DCA BotThe bot is based on the DCA system.
1. DCA is the investment method in which you buy a certain portion of the asset after the determined price deviation.
2. For entry, we evaluate the maximum and minimum levels for a given period that you can adjust in the script. The bot enters when price rebound from the specified levels.
3. For the exit, the bot will use the take profit percentage that you will specify in settings.
It is also possible to choose how the take profit is calculated either from the average entry price or from the entry order (first order).
4. DCA uses the following settings:
- Base order Volume: Volume of your first order on entry signal
- Subsequent orders volume: The volume of all subsequent orders except the first
- DCA orders count: This parameter will determine how many entries your overall strategy will have. For example: If you will put 3, that will mean that including your initial position you will have 2 additional orders.
- DCA order price deviation:
This is the value in % which determines the deviation of the additional entries from the entry price. Example: If you go long and the price of the asset is 100$ and you put an order price deviation of 1% that will mean that the first additional entry will occur when the price will drop by 1%, and the second entry will be triggered when the overall price will drop by 2% (as the interval between the first and the second additional entry will be 1%).
- DCA Order Volume Multiplier:
This parameter will determine the amount that you put into each additional position. If this parameter is equal to 1 that means that each additional entry will be equal to the initial amount. The extra volume will be added to your position from the second DCA entry. Example: Your initial position was 10$ and your Volume Multiplier is set to 2. When you reach your 1st DCA target your additional order will have the same volume of 10$. When you reach your 2nd DCA target your additional order will be 20$ (previous position volume * multiplier). Your 3rd DCA target will place the order of 40$.
- DCA order price Deviation Multiplier:
This value will increase the price deviation between each additional entry. It is calculated as the price deviation multiplied by the deviation multiplier. For example: if you enter long at the price 100$ and have a price deviation of 1% with the price deviation multiplier of 2 that will mean that the first additional entry will occur when the price will drop to 99$ however the second will occur when the price will go to 97$. The third additional position will be entered at 94$
5. For full automation of the bot, you should set your comments to the input in the bot settings in the "LONG" and "SHORT" fields. You also need to create an alert signal and set a Webhook to send signals.
IMPORTANT!!!
1. Position calculation should take into account several factors: your deposit, leverage, the number of DCA orders, the distance to the last DCA order;
2. When choosing leverage, it is important to correctly calculate the possible drawdown. If you set a high leverage value, then liquidation awaits and the bot will not be able to take profits and will exit the position ahead of time;
3. The size of the position must be determined in accordance with all risks and take into account the size of your deposit;
4. This DCA Bot is able to earn consistently with the correct calculated money management.
DCA After Downtrend v2 (by BHD_Trade_Bot)The purpose of the strategy is to identify the end of a short-term downtrend . So that you can easily to DCA certain amount of money for each month.
ENTRY
The buy orders are placed on a monthly basis for assets at the end of a short-term downtrend:
- Each month condition: In 1-hour time frame, each month has 24 * 30 candles
- The end of short-term downtrend condition: use MACD for less delay
CLOSE
The sell orders are placed when:
- Is last bar
The strategy use $1000 and trading fee is 1.1% for each order.
Pro tip: The 1-hour time frame has the best results on average:
- Total spent: $1000 x 33 = $33,000
- Total profit: $65,578
Price change scalping short and long strategyPrice change scalping Short and Long strategy uses a rate of change momentum oscillator to calculate the percent change in price between a period of time. Rate of change calculation takes the current price and compares it to a price of "n" periods while the period of time can be defined by a user. The calculated rate of change value is then compared to the upper threshold and the lower threshold values to determine if a position should be opened. If the threshold is crossed and filtering conditions are met a strategy position will be triggered. Entry, take profit, and stop loss prices are calculated and displayed on the chart as well as positions directions. Once the entry price is crossed, a long or short position is created and once the take profit price is crossed, the stop loss price will begin to trail behind the price action using the close of the previous bar. Once the trailing stop price is crossed, the position is closed. If the entry price is not crossed and the price action crosses the stop level, the trade setup is cancelled. The strategy is enhanced by DCA algorithm which allows to average entry price with safety orders. The script also allows to use Martingale coefficient to increase averaging power
Advantages of this script:
Strategy has high net profit of 293% at backtests
Backtests show high accuracy around 71%
High frequency and low duration of trades
Can be used with short-term timeframes ranging from 5 to 60 minutes
Strategy is sustainable to market slumps due to DCA implementation
Can be used for short and long positions (can be adjusted to long only, short only or both)
Can be applied to any market and quote currency
Easy to configure user interface settings
Built in detailed statistic menu
How to use?
1. Apply the strategy to a trading pair your are interested in using 5 to 60 minutes timeframe chart
2. Configure the strategy: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView alert to trigger when strategy conditions are met
4. Strategy will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
3Commas dollar cost averaging (DCA) QFL IndicatorAs investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex indicator based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The indicator script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry alerts. During price action development an asset value can go lower and in this way the script will perform safety entries alerts at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action alert.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements. These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The indicator supports traditional and cryptocurrency spot, futures , options and marginal trading exchanges. It works accurately with BTC , USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The indicator can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
The difference between core script and this interpretation is that this strategy is specially designed for 3Commas bots
How to use?
1. Apply indicator to a trading pair your are interested in using 1H timeframe chart
2. Configure the indicator: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView custom alert using the indicator settings to trigger on a condition you are interested in
4. The indicator will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
3Commas Dollar cost averaging trading system (DCA)As investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex trading system based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The strategy script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry actions. During price action development an asset value can go lower and in this way the script will perform safety entries at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements.
These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The strategy supports traditional and cryptocurrency spot, futures , options and marginal trading exchanges. It works accurately with BTC, USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The strategy can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
The difference between core script and this interpretation is that this strategy is specially designed for 3Commas bots
How to use?
1. Apply strategy to a trading pair your are interested in using 1H timeframe chart
2. Configure the strategy: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView alert to trigger when strategy conditions are met
4. Strategy will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
Dollar cost averaging (DCA) QFL IndicatorAs investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex indicator based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The indicator script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry alerts. During price action development an asset value can go lower and in this way the script will perform safety entries alerts at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action alert.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements. These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The indicator supports traditional and cryptocurrency spot, futures, options and marginal trading exchanges. It works accurately with BTC, USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The indicator can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
Advantages of this indicator:
The indicator has custom alert settings for each strategy action
The indicator can be used with 3Commas, Cryptohopper, Alertatron or Zignaly bots
The indicator is sustainable to market slumps and can be used for long-term trading
The indicator provides a large number of entries which is good for diversification
Can be applied to any market and quote currency
Easy to configure user interface settings
How to use?
1. Apply indicator to a trading pair your are interested in using 1H timeframe chart
2. Configure the indicator: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView custom alert using the indicator settings to trigger on a condition you are interested in
4. The indicator will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
DCA After Downtrend (by BHD_Trade_Bot)The purpose of the strategy is to identify the end of a short-term downtrend . So that you can easily to DCA certain amount of money for each month.
ENTRY
The buy orders are placed on a monthly basis for assets at the end of a short-term downtrend:
- Each month condition: In 1-hour time frame, each month has 240 candles
- The end of short-term downtrend condition: use MACD for less delay
CLOSE
The sell orders are placed when:
- Is last bar
The strategy use $1000 and trading fee is 0.1% for each order.
Pro tip: The 1-hour time frame for TSLA has the best results on average:
- Total spent: $1000 x 85 = $85,000
- Total profit: $790,556
Crypto Force IndexIntroduction
The Crypto Force Index (CFI) indicator helps us understand the current strength and weakness of the price. It is very useful when used on high timeframes for investment purposes and not for short term trading.
To determine the strength and weakness of the price, a level grid based on the RSI indicator is used.
Based on the RSI value, red circles (oversold condition) and green circles (overbought condition) appear under the price candles. The more intense the color of the circles, the more that the current price is in an overbought or oversold condition.
The signal levels are all configurable to adapt the indicator across multiple instruments and markets.
The default configuration have been designed to obtain more accurate signals on Ethereum and Bitcoin, using the weekly timeframe.
Why Crypto Force Index?
The Crypto Force Index (CFI) is the consequence of my study of investments based on the accumulation plan. I wanted to demonstrate that I am improving the returns of the classic DCA ( dollar cost averaging ) and VA ( value averaging ).
After finding my own model of an accumulation plan, I decided to create the Crypto Force Index to help me visually enter the market.
The formulas of the indicator are very simple, but my studies confirm the power of this tool.
How are the signals to be interpreted?
The Crypto Force Index helps us to highlight the overbought and oversold areas, with the use of circles under the price of candles and with a thermometer inserted at the base of the graph, where all the phases of strength and weakness are highlighted.
As soon as the red circles start to appear on the chart, that may be a good time to enter LONG to the market and start accumulating. If the circles are green, we can consider decreasing the current exposure by selling part of your portfolio, or decide to stay flat.
I personally use these signals on the weekly timeframe, to decide to feed my accumulation plan at the beginning of each month.
I hope it can be of help to you! Please help me improve the Crypto Force Index! :)
Dollar cost averaging trading system (DCA)As investors, we often face the dilemma of willing high stock prices when we sell, but not when we buy. There are times when this dilemma causes investors to wait for a dip in prices, thereby potentially missing out on a continual rise. This is how investors get lured away from the markets and become tangled in the slippery slope of market timing, which is not advisable to a long-term investment strategy.
Skyrex developed a complex trading system based on dollar-cost averaging in Quick Fingers Luc's interpretation. It is a combinations of strategies which allows to systematically accumulate assets by investing scaled amounts of money at defined market cycle global support levels. Dollar-cost averaging can reduce the overall impact of price volatility and lower the average cost per asset thus even during market slumps only a small bounce is required to reach take profit.
The strategy script monitors a chart price action and identifies bases as they form. When bases are reached the script provides entry actions. During price action development an asset value can go lower and in this way the script will perform safety entries at each subsequent accumulation levels. When weighted average entry price reaches target profit the script will perform a take profit action.
Bases are identified as pivot lows in a fractal pattern and validated by an adjustable decrease/rise percentage to ensure significancy of identified bases. To qualify a pivot low, the indicator will perform the following validation:
Validate the price rate of change on drops and bounces is above a given threshold amount.
Validate the volume at the low pivot point is above the volume moving average (using a given length).
Validate the volume amount is a given factor of magnitude above is above the volume moving average.
Validate the potential new base is not too close to the previous range by using a given price percent difference threshold amount.
A fractal pattern is a recurring pattern on a price chart that can predict reversals among larger, more chaotic price movements.
These basic fractals are composed of five or more bars. The rules for identifying fractals are as follows:
A bearish turning point occurs when there is a pattern with the highest high in the middle and two lower highs on each side.
A bullish turning point occurs when there is a pattern with the lowest low in the middle and two higher lows on each side.
Basic dollar-cost averaging approach is enhances by implementation of adjustable accumulation levels in order to provide opportunity of setting them at defined global support levels and Martingale volume coefficient to increase averaging effect. According to Quick Fingers Luc's principles trading principles we added volume validation of a base because it allows to confirm that the market is resistant to further price decrease.
The strategy supports traditional and cryptocurrency spot, futures, options and marginal trading exchanges. It works accurately with BTC, USD, USDT, ETH and BNB quote currencies. Best to use with 1H timeframe charts and limit orders. The strategy can be and should be configured for each particular asset according to its global support and resistance levels and price action cycles. You can modify levels and risk management settings to receive better performance
Advantages of this script:
Strategy has high net profit of 255% at backtests
Backtests show high accuracy around 75%
Low Drawdowns of around 14% at backtests
Strategy is sustainable to market slumps and can be used for long-term trading
The strategy provides a large number of entries which is good for diversification
Can be applied to any market and quote currency
Easy to configure user interface settings
How to use?
1. Apply strategy to a trading pair your are interested in using 1H timeframe chart
2. Configure the strategy: change layer values, order size multiple and take profit/stop loss values according to current market cycle stage
3. Set up a TradingView alert to trigger when strategy conditions are met
4. Strategy will send alerts when to enter and when to exit positions which can be applied to your portfolio using external trading platforms
5. Update settings once market conditions are changed using backtests on a monthly period
Mean reversal QFL v3My aim is to make the bots trade as you would trading QFL manually and “by the book” or at least to my experience and understanding from the material out there of how you should plan a QFL trade.
Im absolutely not a pro trader, I have made my share of costly mistakes trying to be clever or Beeing impatient resulting in painful losses. QFL is we’re I’ve had consistently good results tough.
Is this where I have to say I’m not a financial advisor and all that? Well I’m not. As always Do your own research and backtest, backtest, backtest.
First: I believe no bot strategy are set and forget, while they can run unattended 80-90% of the time you're always going to find yourself in a situation where you will have to manually handle a bad deal. It would also make sense to be somewhat involved in the really good trades making the most out of them. That’s why understanding the strategy the bot Is using is really important, hence why I prefer QFL. It's an easy concept to understand, and proved to be a safe way of making steady profit in pretty much all market conditions if done right.
Some changes in how aggressive you are might be needed if you are the impatient kind of trader who needs to see a lot of deals happening. But it is an added risk. In those cases Luc would advise to start “nibbling” but that would be hard to implement in a bot but I will see if that’s something I can implement.
Same goes for going the more conservative route when market conditions calls for it.
QFL stands for Quickfingersluc, and sometimes it is referred to as the Base Strategy or Mean Reversals. Its main idea is about identifying the moment of panic selling and buying below the base level and utilizing Safety orders.
Base level or Support Level refers to the lowest price level that was reached before the moment the price started increasing again. At that level, you can notice that buyers of some cryptocurrencies make a strong reaction.
As a bit of a learning material i want to make a few points on important factors in trading using the QFL strategy:
• Identify strong bases
• Read the history of the chart
• No emotions
Trading QFL using a bot has it’s limitations:
· Some of the bases are questionable but im constantly trying to improve this
· The strategy don’t take into consideration chart history(success rate)*
· You need to follow a predefined (by you) buying ladder, hence not considering a particular coin's average price movement, which may vary quite a lot. This why I for now has limited the strategy to SIMPLE bots. So that unique alerts can be created for each pair.
· A set Take profit %, possibly making you miss out on higher profits(This is easy to change during a trade though), and no chance of selling in layers(This is coming soon).
1. Some of the bases are questionable
The strategy will start trades of bases that you wouldn’t consider being a strong base(or a base at all) when looking at the chart.
For those not as familiar with QFL. What is a base, and what qualifies as a strong base?
• A base is also called the Support Level, which is the lowest price level that was reached before the price started turning and increasing again.
• A strong base is recognized by a steep fall in price after breaking the base(Panic), followed by a big reaction pump.
• The reaction pump is the most important factor to say that it is a strong base.
• And also the last base, the one you are trading of is the one that counts
Tip: Look for V shapes on the chart, easy to spot when zoomed out.
2. The integrated signals don’t take into consideration chart history(success rate)*
How can you assess the success rate by looking at the chart?
After finding the bases based on the criterias from the 1st point. Looking at the, how many times did it respect the base after breaking it? 7/10, 8/10, 9/10 times? Great! Chances of the next trade also respecting the base is big, and I would consider raising the TP on that deal. Any lower than that I would keep a really close eye on the deal, or even consider closing the deal. And again remember the last base is the one that counts. If all the others are nice strong bases but that last one you are about to take a trade off is no good the base is invalidated so be cautious.
3. You need to follow a predefined (by you) buying ladder
Crypto is volatile, and there is a huge variation in price movements on all the coins.
Trading manually, looking at the chart gives you a good idea on how much a coin on avg. drops below base, and how big the following reaction is. This gives you an indication on how deep you need to set your layers, and where you can take profit.
Using the strategy you have the backtester to see how much max deviation has been in the past so that you can figure out what the optimal max deviation is.
4. A set Take profit %, possibly making you miss out on higher profits(This is easy to change during a trade though), and no chance of selling in layers.
Not going to say to much about this other than what I often do is:
When a bot has started a trade I usually take a look at the chart. If I like what I see, nice chart history, success rate and trading of a strong previous base etc, with the current base break resulting in a panic drop I will consider increasing the TP so that it will make more profit. This can be a bit risky but also very rewarding. Imagine filling all safeties and then selling just below base! Massive profits!! (Gotta be honest though, almost never stretch it that far with a bot though, but it is a possibility) .
If you have studied the chart and concluded that this particular trade has a 90% chance of success, there isn’t really any reason not to place TP just below base. This is where I would like to have the option of layering my sell orders as well so its something im working on implementing.
Trailing is an option in 3commas, but it’s slow to place orders making you miss a selling opportunity when the coin makes a sudden spike up.
ABOUT THIS STRATEGY
In this strategy we can also reverse the strategy and go short. But i must warn you that that is alot riskier.
QFL is meant to be used on higher TF's like 1hr, 2hr and 4hr. But this strategy also work well on lower Timeframes.
The script also simulates DCA strategy with parameters used in 3commas DCA bots for futures trading.
Experiment with parameters to find your trading setup.
Beware how large your total leveraged position is and how far can market go before you get liquidated!
Do that with the help of futures liquidation calculators you can find online!
Included:
An internal average price and profit calculating, instead of TV`s native one, which is subject to severe slippage.
A graphic interface, so levels are clearly visible and back-test analyzing made easier.
Long & Short direction of the strategy.
Table display a summary of past trades
Vertical colored lines appear when the new maximum deviation from the original price has
been reached
All the trading happens with total account capital, and all order sizes inputs are expressed in percent.
How to use:
- Add the script to the current chart
- Open the strategy settings
-Tweak the settings to to your liking.
-Make a SIMPLE bot in 3commas and use the same settings as you did in tradingview if you only want the strategy to send signals to open a deal and let 3commas handle the rest.
If you check safety orders, Take profit deal stop and Stop loss. The strategy will send all the orders to 3 commas. If that’s what you want set TP in 3commas to 50% set number of safety orders to 0 and keep stop loss unchecked.
- Insert bot details using the deal start condition message found in your 3commas bot.
- When happy, right click on the "..." next to the strategy name, then "Add alert'".
- Under "Condition", on the second line, chose "Any alert () function call". Add the webhook from 3commas( 3commas.io ), give it a name, use {{strategy.order.alert_message}} as a placeholder message and "create".
In the future this signal might make it to the 3commas marketplace. You can then subscribe to that signal where I have cherrypicked coins based on thorough backtesting and optimization.
How to obtain access to the script: send me a private message in Tradingview
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%
DCA Average Arbitrage - The Quant ScienceDCA Average Arbitrage - The Quant Science™ is a quantitative algorithm based on a DCA model that uses averaging to create a statistical arbitrage system.
DESCRIPTION
The algorithm can be set long or short.
1. Long algorithm: opens long positions with 100% of the capital every time the price deviates negatively for a certain percentage distance from the average.
2. Short algorithm: opens short positions with 100% of capital every time the price deviates positively for a certain percentage distance from the average.
The closing of positions depends on the parameters activated by the user. The user can set the closing on the reverse condition and/or add functions such as stop loss, take profit and closing after a certain bar period.
USER INTERFACE SETTING
The user chooses the long or short direction and sets the parameters for average as length, source and percent distance.
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 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.
ABOUT THE BACKTEST
Backtesting refers to the period 1 January 2022 - today, ticker: ICP/USDT, timeframe 5 minutes.
Initial capital: $1000.00
Commission per trade: 0.03%
3C QFL Mean reversalWhat is QFL trading strategy?
QFL stands for Quickfingersluc, and sometimes it is referred to as the Base Strategy or Mean Reversals. Its main idea is about identifying the moment of panic selling and buying below the base level and utilizing Safety orders.
What is Base level or Support Level?
Base level or Support Level refers to the lowest price level that was reached before the moment the price started increasing again. At that level, you can notice that buyers of some cryptocurrencies make a strong reaction.
In this strategy we can also reverse the strategy and go short. But i must warn you that that is alot riskier.
QFL is meant to be used on higher TF's like 1hr, 2hr and 4hr. But this strategy also work well on lower Timeframes.
The script also simulates DCA strategy with parameters used in 3commas DCA bots for futures trading.
Experiment with parameters to find your trading setup.
Beware how large your total leveraged position is and how far can market go before you get liquidated!
Do that with the help of futures liquidation calculators you can find online!
Included:
An internal average price and profit calculating, instead of TV`s native one, which is subject to severe slippage.
A graphic interface, so levels are clearly visible and back-test analyzing made easier.
Long & Short direction of the strategy.
Table display a summary of past trades
Vertical colored lines appear when the new maximum deviation from the original price has
been reached
All the trading happens with total account capital, and all order sizes inputs are expressed in percent.
