Dual-Supertrend with MACD - Strategy [presentTrading]## Introduction and How it is Different
The Dual-Supertrend with MACD strategy offers an amalgamation of two trend-following indicators (Supertrend 1 & 2) with a momentum oscillator (MACD). It aims to provide a cohesive and systematic approach to trading, eliminating the need for discretionary decision-making.
Key advantages over traditional single-indicator strategies:
- Dual Supertrend Validation: Utilizes two Supertrend indicators with different ATR periods and factors to confirm the trend direction. This double-check mechanism minimizes false signals.
- Momentum Confirmation: The MACD histogram acts as a momentum filter, confirming entries and exits, thus adding an extra layer of validation.
- Objective Entry and Exit: The strategy generates buy and sell signals based on a combination of trend direction and momentum, leaving no room for subjective interpretation.
- Automated Trade Management: The strategy includes built-in settings for commission, slippage, and initial capital, automating the trade execution process.
- Adaptability: The strategy allows for easy customization of all its parameters, adapting to a trader's specific needs and varying market conditions.
BTCUSD 8hr chart Long Condition
BTCUSD 6hr chart Long Short Condition
## Strategy, How it Works
The strategy operates on a set of clearly defined rules, primarily focusing on the trend direction confirmed by the Dual-Supertrend and the momentum as indicated by the MACD histogram.
### Entry Rules
- Long Entry: When both Supertrend indicators are bullish and the MACD histogram is above zero.
- Short Entry: When both Supertrend indicators are bearish and the MACD histogram is below zero.
### Exit Rules
- Exit long positions when either of the Supertrends turn bearish or the MACD histogram drops below zero.
- Exit short positions when either of the Supertrends turn bullish or the MACD histogram rises above zero.
### Trade Management
- The strategy uses a fixed commission rate and slippage in its calculations.
- Automated risk management features are integrated to avoid overexposure.
## Trade Direction
The strategy allows for trading in both bullish and bearish markets. Users can select their preferred trading direction ("long", "short", or "both") to align with their market outlook and trading objectives.
## Usage
- The strategy is best applied on timeframes where the trend is evident.
- Users can modify the ATR periods, factors for Supertrends, and MACD settings to suit their trading needs.
## Default Settings
- ATR Period for Supertrend 1: 10
- Factor for Supertrend 1: 3.0
- ATR Period for Supertrend 2: 20
- Factor for Supertrend 2: 5.0
- MACD Fast Length: 12
- MACD Slow Length: 26
- MACD Signal Smoothing: 9
- Commission: 0.1%
- Slippage: 1 point
- Trading Direction: Both
The strategy comes with these default settings to offer a balanced trading approach but can be customized according to individual trading preferences.
ค้นหาในสคริปต์สำหรับ "the strat"
Linear Cross Trading StrategyLinear Cross Trading Strategy
The Linear Cross trading strategy is a technical analysis strategy that uses linear regression to predict the future price of a stock. The strategy is based on the following principles:
The price of a stock tends to follow a linear trend over time.
The slope of the linear trend can be used to predict the future price of the stock.
The strategy enters a long position when the predicted price crosses above the current price, and exits the position when the predicted price crosses below the current price.
The Linear Cross trading strategy is implemented in the TradingView Pine script below. The script first calculates the linear regression of the stock price over a specified period of time. The script then plots the predicted price and the current price on the chart. The script also defines two signals:
Long signal: The long signal is triggered when the predicted price crosses above the current price.
Short signal: The short signal is triggered when the predicted price crosses below the current price.
The script enters a long position when the long signal is triggered and exits the position when the short signal is triggered.
Here is a more detailed explanation of the steps involved in the Linear Cross trading strategy:
Calculate the linear regression of the stock price over a specified period of time.
Plot the predicted price and the current price on the chart.
Define two signals: the long signal and the short signal.
Enter a long position when the long signal is triggered.
Exit the long position when the short signal is triggered.
The Linear Cross trading strategy is a simple and effective way to trade stocks. However, it is important to note that no trading strategy is guaranteed to be profitable. It is always important to do your own research and backtest the strategy before using it to trade real money.
Here are some additional things to keep in mind when using the Linear Cross trading strategy:
The length of the linear regression period is a key parameter that affects the performance of the strategy. A longer period will smooth out the noise in the price data, but it will also make the strategy less responsive to changes in the price.
The strategy is more likely to generate profitable trades when the stock price is trending. However, the strategy can also generate profitable trades in ranging markets.
The strategy is not immune to losses. It is important to use risk management techniques to protect your capital when using the strategy.
I hope this blog post helps you understand the Linear Cross trading strategy better. Booost and share with your friend, if you like.
Liquidity Breakout - Strategy [presentTrading]- Introduction and How It Is Different
The Liquidity Breakout Strategy is a unique trading strategy that focuses on identifying and leveraging patterns in market price data. This strategy, mainly inspired by the script "Master Pattern" by LuxAlgo, takes a different approach from many traditional strategies that rely on technical indicators or fundamental analysis. Instead, the Liquidity Breakout is based on the concept of contraction detection and liquidity levels. This approach allows traders to identify potential trading opportunities that other strategies might miss.
BTCUSDT 6h
The strategy is different from other trading strategies because it uses a unique combination of pattern detection, liquidity levels, and user-defined trading direction. This combination allows the strategy to adapt to various market conditions and trading styles, making it a versatile tool for traders.
- Strategy: How It Works
1. Contraction Detection: The strategy uses a lookback period defined by the user (default is 10 bars) to identify contractions in the market. A contraction is a period where the market is consolidating, often followed by a significant price movement. The strategy identifies contractions by finding pivot highs and pivot lows within the lookback period. If a pivot high is lower than the previous pivot high and a pivot low is higher than the previous pivot low, a contraction is detected.
2. liquidity Levels:
What are Liquidity levels? Liquidity levels, also known as liquidity pools or zones, are price levels at which there is a significant amount of trading activity. They are often areas where large institutional traders (like banks or hedge funds) have placed orders. These levels are important because they can act as support or resistance levels, and price often reacts at these levels.
In the context of this strategy, liquidity levels are used to identify potential entry and exit points for trades. When the price reaches a liquidity level, it could indicate a potential trading opportunity. For example, if the price breaks through a liquidity level, it could signal the start of a new trend. On the other hand, if the price approaches a liquidity level and then reverses, it could signal a potential reversal.
The strategy uses these two elements to identify potential trading opportunities. When a contraction is detected, the strategy will look for a breakout in the direction of the trend. If the breakout occurs at a liquidity level, the strategy will execute a trade.
The strategy also allows traders to set their stop loss based on either the Average True Range (ATR) or a fixed percentage. This flexibility allows traders to manage their risk according to their personal risk tolerance and trading style.
- Trade Direction
One of the unique features of the Master Pattern Strategy is the ability to choose the trading direction. Traders can choose to trade in the "Long" direction, the "Short" direction, or "Both". This feature allows traders to adapt the strategy to their personal trading style and market outlook.
For example, if a trader believes that the market is in an uptrend, they can choose to trade only in the "Long" direction. Conversely, if the market is in a downtrend, they can choose to trade only in the "Short" direction. If the trader believes that the market is volatile and there are opportunities in both directions, they can choose to trade in "Both" directions.
- Usage
To use the strategy, traders need to input their preferred settings, including the contraction detection lookback period, liquidity levels, stop loss type, and trading direction. Once these settings are input, the strategy will automatically detect potential trading opportunities and execute trades according to the defined parameters.
- Default Settings
The default settings for the Master Pattern Strategy are as follows:
Contraction Detection Lookback: 10
Liquidity Levels: 20
Stop Loss Type: ATR
ATR Length: 20
ATR Multiplier: 3.0
Fixed Percentage: 0.01
Trading Direction: Both
These settings can be adjusted according to the trader's personal preferences and market conditions. It's recommended that traders experiment with different settings to find the ones that work best for their trading style and goals.
SuperTrend Enhanced Pivot Reversal - Strategy [PresentTrading]
- Introduction and How it is Different
The SuperTrend Enhanced Pivot Reversal is a unique approach to trading that combines the best of two worlds: the precision of pivot reversal points and the trend-following power of the SuperTrend indicator. This strategy is designed to provide traders with clear entry and exit points, while also filtering out potentially false signals using the SuperTrend indicator.
BTCUSDT 6hr
ETHBTC 6hr
Unlike traditional pivot reversal strategies, this approach uses the SuperTrend indicator as a filter. This means that it only takes trades that align with the overall trend, as determined by the SuperTrend indicator. This can help to reduce the number of false signals and improve the overall profitability of the strategy.
The Pivot Reversal Strategy with SuperTrend Filter is particularly well-suited to the cryptocurrency market for the reason of High Volatility. This means that prices can change rapidly in a very short time, making it possible to make a profit quickly. The strategy's use of pivot points allows traders to take advantage of these rapid price changes by identifying potential reversal points
- Strategy: How it Works
The strategy works by identifying pivot reversal points, which are points in the price chart where the price is likely to reverse. These points are identified using a combination of the ta.pivothigh and ta.pivotlow functions, which find the highest and lowest points in the price chart over a certain period.
Once a pivot reversal point is identified, the strategy checks the direction of the SuperTrend indicator. If the SuperTrend is positive (indicating an uptrend), the strategy will only take long trades. If the SuperTrend is negative (indicating a downtrend), the strategy will only take short trades.
The strategy also includes a stop loss level, which is set as a percentage of the entry price. This helps to limit potential losses if the price moves in the opposite direction to the trade.
- Trade Direction
The trade direction can be set to "Long", "Short", or "Both". This allows the trader to choose whether they want to take only long trades (buying low and selling high), only short trades (selling high and buying low), or both. This can be useful depending on the trader's view of the market and their risk tolerance.
- Usage
To use the Pivot Reversal Strategy with SuperTrend Filter, simply input the desired parameters into the script and apply it to the price chart of the asset you wish to trade. The strategy will then identify potential trade entry and exit points, which will be displayed on the price chart.
- Default Settings
The default settings for the strategy are as follows:
ATR Length: 5
Factor: 2.618
Trade Direction: Both
Stop Loss Level: 20%
Commission: 0.1%
Slippage: 1
Currency: USD
Each trade: 10% of account equity
Initial capital: $10,000
These settings can be adjusted to suit the trader's preferences and risk tolerance. Always remember to test any changes to the settings using historical data before applying them to live trades.
ATR GOD Strategy by TradeSmart (PineConnector-compatible)This is a highly-customizable trading strategy made by TradeSmart, focusing mainly on ATR-based indicators and filters. The strategy is mainly intended for trading forex , and has been optimized using the Deep Backtest feature on the 2018.01.01 - 2023.06.01 interval on the EUR/USD (FXCM) 15M chart, with a Slippage value of 3, and a Commission set to 0.00004 USD per contract. The strategy is also made compatible with PineConnector , to provide an easy option to automate the strategy using a connection to MetaTrader. See tooltips for details on how to set up the bot, and check out our website for a detailed guide with images on how to automate the strategy.
The strategy was implemented using the following logic:
Entry strategy:
A total of 4 Supertrend values can be used to determine the entry logic. There is option to set up all 4 Supertrend parameters individually, as well as their potential to be used as an entry signal/or a trend filter. Long/Short entry signals will be determined based on the selected potential Supertrend entry signals, and filtered based on them being in an uptrend/downtrend (also available for setup). Please use the provided tooltips for each setup to see every detail.
Exit strategy:
4 different types of Stop Losses are available: ATR-based/Candle Low/High Based/Percentage Based/Pip Based. Additionally, Force exiting can also be applied, where there is option to set up 4 custom sessions, and exits will happen after the session has closed.
Parameters of every indicator used in the strategy can be tuned in the strategy settings as follows:
Plot settings:
Plot Signals: true by default, Show all Long and Short signals on the signal candle
Plot SL/TP lines: false by default, Checking this option will result in the TP and SL lines to be plotted on the chart.
Supertrend 1-4:
All the parameters of the Supertrends can be set up here, as well as their individual role in the entry logic.
Exit Strategy:
ATR Based Stop Loss: true by default
ATR Length (of the SL): 100 by default
ATR Smoothing (of the SL): RMA/SMMA by default
Candle Low/High Based Stop Loss: false by default, recent lowest or highest point (depending on long/short position) will be used to calculate stop loss value. Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Candle Lookback (of the SL): 50 by default
Percentage Based Stop Loss: false by default, Set the stop loss to current price - % of current price (long) or price + % of current price (short).
Percentage (of the SL): 0.3 by default
Pip Based Stop Loss: Set the stop loss to current price - x pips (long) or price + x pips (short). Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Pip (of the SL): 10 by default
Base Risk Multiplier: 4.5 by default, the stop loss will be placed at this risk level (meaning in case of ATR SL that the ATR value will be multiplied by this factor and the SL will be placed that value away from the entry level)
Risk to Reward Ratio: 1.5 by default, the take profit level will be placed such as this Risk/Reward ratio is met
Force Exiting:
4 total Force exit on custom session close options: none applied by default. If enabled, trades will close automatically after the set session is closed (on next candle's open).
Base Setups:
Allow Long Entries: true by default
Allow Short Entries: true by default
Order Size: 10 by default
Order Type: Capital Percentage by default, allows adjustment on how the position size is calculated: Cash: only the set cash amount will be used for each trade Contract(s): the adjusted number of contracts will be used for each trade Capital Percentage: a % of the current available capital will be used for each trade
ATR Limiter:
Use ATR Limiter: true by default, Only enter into any position (long/short) if ATR value is higher than the Low Boundary and lower than the High Boundary.
ATR Limiter Length: 50 by default
ATR Limiter Smoothing: RMA/SMMA by default
High Boundary: 1000 by default
Low Boundary: 0.0003 by default
MA based calculation: ATR value under MA by default, If not Unspecified, an MA is calculated with the ATR value as source. Only enter into position (long/short) if ATR value is higher/lower than the MA.
MA Type: RMA/SMMA by default
MA Length: 400 by default
Waddah Attar Filter:
Explosion/Deadzone relation: Not specified by default, Explosion over Deadzone: trades will only happen if the explosion line is over the deadzone line; Explosion under Deadzone: trades will only happen if the explosion line is under the deadzone line; Not specified: the opening of trades will not be based on the relation between the explosion and deadzone lines.
Limit trades based on trends: Not specified by default, Strong Trends: only enter long if the WA bar is colored green (there is an uptrend and the current bar is higher then the previous); only enter short if the WA bar is colored red (there is a downtrend and the current bar is higher then the previous); Soft Trends: only enter long if the WA bar is colored lime (there is an uptrend and the current bar is lower then the previous); only enter short if the WA bar is colored orange (there is a downtrend and the current bar is lower then the previous); All Trends: only enter long if the WA bar is colored green or lime (there is an uptrend); only enter short if the WA bar is colored red or orange (there is a downtrend); Not specified: the color of the WA bar (trend) is not relevant when considering entries.
WA bar value: Not specified by default, Over Explosion and Deadzone: only enter trades when the WA bar value is over the Explosion and Deadzone lines; Not specified: the relation between the explosion/deadzone lines to the value of the WA bar will not be used to filter opening trades.
Sensitivity: 150 by default
Fast MA Type: SMA by default
Fast MA Length: 10 by default
Slow MA Type: SMA
Slow MA Length: 20 by default
Channel MA Type: EMA by default
BB Channel Length: 20 by default
BB Stdev Multiplier: 2 by default
Trend Filter:
Use long trend filter 1: false by default, Only enter long if price is above Long MA.
Show long trend filter 1: false by default, Plot the selected MA on the chart.
TF1 - MA Type: EMA by default
TF1 - MA Length: 120 by default
TF1 - MA Source: close by default
Use short trend filter 1: false by default, Only enter long if price is above Long MA.
Show short trend filter 1: false by default, Plot the selected MA on the chart.
TF2 - MA Type: EMA by default
TF2 - MA Length: 120 by default
TF2 - MA Source: close by default
Volume Filter:
Only enter trades where volume is higher then the volume-based MA: true by default, a set type of MA will be calculated with the volume as source, and set length
MA Type: RMA/SMMA by default
MA Length: 200 by default
Date Range Limiter:
Limit Between Dates: false by default
Start Date: Jan 01 2023 00:00:00 by default
End Date: Jun 24 2023 00:00:00 by default
Session Limiter:
Show session plots: false by default, show market sessions on chart: Sidney (red), Tokyo (orange), London (yellow), New York (green)
Use session limiter: false by default, if enabled, trades will only happen in the ticked sessions below.
Sidney session: false by default, session between: 15:00 - 00:00 (EST)
Tokyo session: false by default, session between: 19:00 - 04:00 (EST)
London session: false by default, session between: 03:00 - 11:00 (EST)
New York session: false by default, session between: 08:00 - 17:00 (EST)
Trading Time:
Limit Trading Time: true by default, tick this together with the options below to enable limiting based on day and time
Valid Trading Days Global: 123567 by default, if the Limit Trading Time is on, trades will only happen on days that are present in this field. If any of the not global Valid Trading Days is used, this field will be neglected. Values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) To trade on all days use: 123457
(1) Valid Trading Days: false, 123456 by default, values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) The script will trade on days that are present in this field. Please make sure that this field and also (1) Valid Trading Hours Between is checked
(1) Valid Trading Hours Between: false, 1800-2000 by default, hours between which the trades can happen. The time is always in the exchange's timezone
All other options are also disabled by default
PineConnector Automation:
Use PineConnector Automation: false by default, In order for the connection to MetaTrader to work, you will need do perform prerequisite steps, you can follow our full guide at our website, or refer to the official PineConnector Documentation. To set up PineConnector Automation on the TradingView side, you will need to do the following:
1. Fill out the License ID field with your PineConnector License ID;
2. Fill out the Risk (trading volume) with the desired volume to be traded in each trade (the meaning of this value depends on the EA settings in Metatrader. Follow the detailed guide for additional information);
3. After filling out the fields, you need to enable the 'Use PineConnector Automation' option (check the box in the strategy settings);
4. Check if the chart has updated and you can see the appropriate order comments on your chart;
5. Create an alert with the strategy selected as Condition, and the Message as {{strategy.order.comment}} (should be there by default);
6. Enable the Webhook URL in the Notifications section, set it as the official PineConnector webhook address and enjoy your connection with MetaTrader.
License ID: 60123456789 by default
Risk (trading volume): 1 by default
NOTE! Fine-tuning/re-optimization is highly recommended when using other asset/timeframe combinations.
Swing Algo V1.4◆ Introduction
The latest version of the Swing Algo features a complementary system consisting of two internal swing trading logics: an enhanced Swing Algo V1.3 and a secondary control engine to stabilize the overall strategy behaviour in times of increased market chop. Both algorithms feature different averaging lines as well as oscillators, leading to a higher strategy diversification for swing trading as well as a reduced maximum drawdown in comparison to each stand-alone strategy.
While the Swing Algo V1.x series so far featured a single trend-following swing algorithm for each release, where one just switches between Long and Short trades based on one general logic, here two strategies, which act independently of each other, are applied. Due to this, we introduce a third position a trader can be in: the Hedge. The overall logic is as follows:
When both sub-logics are Long, the overall strategy is Long.
When both sub-logics are Short, the overall strategy is Short.
When one sub-logic is Long and the other is Short, the overall strategy is in a Hedge position. It doesn't matter which component is Short and which is Long.
As PineScript doesn't currently offer a real steady hedging-function for two competing swing trading sub-logics (in the sense of a continuously applied Hedge state after hedging conditions are met at least once for an entry), a workaround via position closes was created for this release. For each new internal sub-signal, the overall strategy changes its state (Long/Short/Hedge) visibly on the chart, and the trader can adjust their position accordingly.
For detailed differences to previous Swing Algo V1.x releases, see further below.
◆ Purpose of this Script
This indicator will give Long, Short and Hedge signals on the chart that can be used for e.g. swing trading. Each of the aforementioned sub-logics uses a combination of several (custom) functions and rules to find good entry points for trend trading. After many iterations and tests I came up with this particular setup, which is highly optimized for the ETH/USD trading pair on the daily (D) timeframe.
Attention was also paid to stability, as all parameters are set onto plateaus, so that smaller changes in the characteristic price action should not affect the efficiancy too much, done as an attempt to reduce overfitting as much as possible. Additionally this dual algorithm system is specifically designed to have a safety net: should for the unlikely scenario one swing trading algorithm not trigger at a certain mid-term reversal point, the probability is high that the other will trigger, resulting in an overall hedged position (so that no money is lost in the meantime) until the first algorithm can rejoin at the next mid-term trend change.
For other assets and/or timeframes it is in principle possible to change algorithmic parameters within the indicator settings to tune the swing algorithms, though it is strongly recommended to use the standard asset and timeframe mentioned above.
◆ Viability
For the here presented backtest data, we omitted the biggest portion of the cryptocurrency bullrun in 2017 (starting only at 1st July 2017) so that the results become more realistic for long-term swing traders (investing at least 2-4 years into trading) if such large runs do not happen again. As cryptocurrencies like Ethereum are still to this date capable of doing comparatively smaller runs of about 2-3x in a few weeks/months during accumulation phases (as witnessed e.g. in 2020 and more recently in 2023) and bigger runs during bullmarkets (as witnessed in 2021), the quality of the shown results is still realistic for long-term trend trading efforts over several years, Note that very conservative trading parameters as mentioned below in "Forwardtesting and Backtesting" are used here.
Generally do not expect results in a matter of days or weeks, and of course as with any trading strategy past performances are not indicative of future results.
◆ Forwardtesting and Backtesting
The individual components have been back- and partially forwardtested: The first sub-logic is an advancement of Swing Algo V1.3, with which we have extensive experience running back to October 2020 for its release, while the secondary control strategy, which was privately published for DeanTrader members as a stand-alone script on TradingView in June 2022 and was running in the background since then, is showing good & expected behaviour so far.
While this does not mean that fowardtesting was performed specifically for the combined Swing Algo V1.4 system we have now (which cannot be done realistically considering the timeframes used, i.e. months and especially years), we can at least look at some considerable experience with the individual components. Then again, as I have implemented an exact hedging-function so that both sub-algorithms run independently from each other, it is not likely to see any unexpected behaviour resulting purely from the combination into one script.
For strategy backtesting you can choose the backtest time interval to test the performance of this algorithm for different time windows and different trading pairs. Here various backtesting parameters (e.g. trading fees) can be customized. Default settings for the shown backtest are a starting balance of $1000, a slippage of 20 ticks (= $0.20) and a trading fee of 0.05 % (which is the worst taker fee on the Kraken Pro futures exchange) to have realistic settings. However as we do not conduct many trades with this strategy, fees should not impact our performance too much. As long-term swing traders, we at DeanTrader generally devote one initial portion of our portfolio to swing trading and from then on always use 100% of this portion for the next trade to get the compounding starting. This is in difference to other trading styles which use various, often very small, percentage values for their short- or mid-term trades. Please note that for the here presented backtest only 10% of compounded equity is used for each successive trade to show an estimation for a lower risk & lower reward approach . Keep this in mind when evaluating the backtest data. You can set appropriate values for each backtest parameter in the "Properties" setting menu of the strategy, including the order size percentage of equity value for your trades. Also note that due to the small number of trades the statistical significance is low. It is not possible to gather an abundance of long-term trend signals in the order of hundreds or thousands trades, as much more time would have to pass for this in the case of rather new assets like Ethereum.
Additionally to the TradingView Strategy Tester you can also plot your equity directly on the chart to get a sense for the performance. For this you can also scale the equity graph to e.g. match the starting point of your equity with some price point on the chart to get a direct comparison to 'Buy & Hold' strategies over time.
This indicator (and all other content I provide) is no financial advice. If you use this indicator you agree to my Terms and Conditions which can be found on my website linked on my TradingView profile or in my signature.
◆ Visual Representation on the Chart
Shown below is a screenshot of how the chart looks like when the strategy is applied. Here we can see two different averaging lines, where each line belongs to one of the two sub-logics respectively. Note that this is not a MA-crossover strategy, and the crossing of the lines is not accounted for in the code at all and therefore has no effect on the strategy's signal output. Also note that the price scale is set on logarithmic.
The space between the lines is filled with a faint background color as a rough visual indicator. Magenta-colored fills indicate zones where only Short or Hedge signals can appear, while green-colored fills indicate zones where only Long or Hedge signals can appear. Gray-colored fills mark zones where only Hedge signals can appear, which also means that Hedge signals can appear in any zone. So treat those background fills more as a visual aid to roughly know what can happen next, but pay most attention to the actual signals (with arrows) that appear on the chart.
◆ Differences to Other Versions
Consists now of two competing sub-algorithms instead of just one algorithm. The new system outputs Long, Short and Hedge signals instead of just Long and Short signals.
The first sub-logic is the spiritual successor of the original Swing Algo V1.3 release, with a modified oscillator part.
The second sub-logic serves as a control algorithm (while still having equal rights in terms of strategy impact), newly introduced to the Swing Algo series, but already forwardtested for roughly a year at time of release.
Lowers risk significantly by diversifying swing trading strategies, so that for the rare scenario of a missed trend on one sub-algorithm, losses are prevented as the overall strategy is hedged during that time.
Lowers risk further as the maximum drawdown of the combined strategy is reduced by roughly 1/3 in comparison to each stand-alone strategy while almost retaining the same net profit over a 6-year backtest compared to the first, leading sub-logic.
No guesswork anymore when to use which short leverage (1x corresponding to a Hedge, or 2x corresponding to a Short with an asset-value-change-to-gain-proportionality of -1) as it is clearly defined within the trading system via the displayed signals. In earlier Swing Algo versions, the short leverage for any particular Short signal had to be chosen by hand dependent on market sentiment, which required further market analysis, or was fixed at 2x, leading to less flexibility.
◆ Access
For access please contact me via DM on TradingView or via other channels (linked on my TradingView profile and in my signature).
Williams %R Cross Strategy with 200 MA Filter
1. The script is a trading strategy based on the Williams %R indicator and a 200-period moving average (MA) filter.
2. The user can input the length of the Williams %R indicator (`wrLength`), the threshold for %R crossing (`crossPips`), the take profit level in pips (`takeProfitPips`), and the stop loss level in pips (`stopLossPips`).
3. The script calculates the Williams %R using the `ta.highest` and `ta.lowest` functions to find the highest high and lowest low over the specified length (`wrLength`).
4. It also calculates a 200-period simple moving average (`ma200`) using the `ta.sma` function.
5. The entry conditions are defined as follows:
- For a long entry, it checks if the Williams %R crosses above the -50 line by a threshold of `crossPips` and if the close price is above the 200-period MA.
- For a short entry, it checks if the Williams %R crosses below the -50 line by a threshold of `crossPips` and if the close price is below the 200-period MA.
6. The exit conditions are defined as follows:
- For a long position, it checks if the close price reaches the take profit level (defined as the average entry price plus `takeProfitPips` in pips) or the stop loss level (defined as the average entry price minus `stopLossPips` in pips).
- For a short position, it checks if the close price reaches the take profit level (defined as the average entry price minus `takeProfitPips` in pips) or the stop loss level (defined as the average entry price plus `stopLossPips` in pips).
7. The script uses the `strategy.entry` function to place long and short orders when the respective entry conditions are met.
8. It uses the `strategy.close` function to close the long and short positions when the respective exit conditions are met.
The script allows you to customize the parameters such as the length of Williams %R, the crossing threshold, take profit and stop loss levels, and the moving average period to suit your trading preferences.
DCA-Integrated Trend Continuation StrategyIntroducing the DCA-Integrated Trend Continuation Strategy 💼💰
The DCA-Integrated Trend Continuation Strategy represents a robust trading methodology that harnesses the potential of trend continuation opportunities while seamlessly incorporating the principles of Dollar Cost Averaging (DCA) as a risk management and backup mechanism. This strategy harmoniously blends these two concepts to potentially amplify profitability and optimize risk control across diverse market conditions.
This strategy is well-suited for both trending and ranging markets. During trending markets, it aims to capture and ride the momentum of the trend while optimizing entry points. In ranging markets or pullbacks, the DCA feature comes into play, allowing users to accumulate more assets at potentially lower prices and potentially increase profits when the market resumes its upward trend. This cohesive approach not only enhances the overall effectiveness of the strategy but also fosters a more resilient and adaptable trading approach in ever-changing market dynamics.
💎 How it Works:
▶️ The strategy incorporates a customizable entry signal based on candlestick patterns, enabling the identification of potential trend continuation opportunities. By focusing on consecutive bullish candles, it detects the presence of bullish momentum, indicating an optimal time to enter a long position.
To refine the precision of the signals, traders can set a specific percentage threshold for the closing price of the candle, ensuring it is above a certain percentage of its body. This condition verifies strong bullish momentum and confirms significant upward movement within the candle, thereby increasing the reliability of the signal.
In addition, the strategy offers further confirmation by examining the relationship between the closing price of the signal candle and its previous candles. If the closing price of the signal candle is higher than its preceding candles, it provides an additional layer of assurance before entering a position. This approach is particularly effective in detecting sharp movements and capturing significant price shifts, as it focuses on identifying instances where the closing price shows clear strength and outperforms the previous candle's price action. By prioritizing such occurrences, the strategy aims to capture robust trends and capitalize on notable market movements.
▶️ During market downturns, the strategy incorporates intelligent management of price drops, offering flexibility through fixed or customizable price drop percentages. This unique feature allows for additional entries at specified drop percentages, enabling traders to accumulate positions at more favorable prices.
By strategically adjusting the custom price drop percentages, you can optimize your entry points to potentially maximize profitability. Utilizing lower percentages for initial entries takes advantage of price fluctuations, potentially yielding higher returns. On the other hand, employing higher percentages for final entries adopts a more cautious approach during significant market downturns, emphasizing enhanced risk management. This adaptive approach ensures that the strategy effectively navigates challenging market conditions while seeking to optimize overall performance.
▶️ To enhance performance and mitigate risks, the strategy integrates average purchase price management. This feature dynamically adjusts the average buy price percentage decrease after each price drop, expediting the achievement of the target point even in challenging market conditions. By reducing recovery times and ensuring investment safety, this strategy optimizes outcomes for traders.
▶️ Risk management is at the core of this strategy, prioritizing the protection of capital. It incorporates an account balance validation mechanism that conducts automatic checks prior to each entry, ensuring alignment with available funds. This essential feature provides real-time insights into the affordability of price drops and the number of entries, enabling traders to make informed decisions and maintain optimal risk control.
▶️ Furthermore, the strategy offers take profit options, allowing traders to secure gains by setting fixed percentage profits from the average buy price or using a trailing target. Stop loss protection is also available, enabling traders to set a fixed percentage from the average purchase price to limit potential losses and preserve capital.
▶️ This strategy is fully compatible with third-party trading bots, allowing for easy connectivity to popular trading platforms. By leveraging the TradingView webhook functionality, you can effortlessly link the strategy to your preferred bot and receive accurate signals for position entry and exit. The strategy provides all the necessary alert message fields, ensuring a smooth and user-friendly trading experience. With this integration, you can automate the execution of trades, saving time and effort while enjoying the benefits of this powerful strategy.
🚀 How to Use:
To effectively utilize the DCA-Integrated Trend Continuation Strategy, follow these steps:
1. Choose your preferred DCA Mode - whether by quantity or by value - to determine how you want to size your positions.
2. Customize the entry conditions of the strategy to align with your trading preferences. Specify the number of consecutive bullish candles, set a desired percentage threshold for the close of the signal candle relative to its body, and determine the number of previous candles to compare with.
3. Adjust the pyramiding parameter to suit your risk tolerance and desired returns. Whether you prefer a more conservative approach with fewer pyramids or a more aggressive stance with multiple pyramids, this strategy offers flexibility.
4. Personalize the price drop percentages based on your risk appetite and trading strategy. Choose between fixed or custom percentages to optimize your entries in different market scenarios.
5. Configure the average purchase price management settings to control the percentage decrease in the average buy price after each price drop, ensuring it aligns with your risk tolerance and strategy.
6. Utilize the account balance validation feature to ensure the strategy's actions align with your available funds, enhancing risk management and preventing overexposure.
7. Set take profit options to secure your gains and implement stop loss protection to limit potential losses, providing an additional layer of risk management.
8. Use the date and time filtering feature to define the duration during which the strategy operates, allowing for specific backtesting periods or integration with a trading bot.
9. For automated trading, take advantage of the compatibility with third-party trading bots to seamlessly integrate the strategy with popular trading platforms.
By following these steps, traders can harness the power of the DCA-Integrated Trend Continuation Strategy to potentially maximize profitability and optimize their trading outcomes in both trending and ranging markets.
⚙️ User Settings:
To ensure the backtest result is representative of real-world trading conditions, particularly in the highly volatile Crypto market, the default strategy parameters have been carefully selected to produce realistic results with a conservative approach. However, you have the flexibility to customize these settings based on your risk tolerance and strategy preferences, whether you're focusing on short-term or long-term trading, allowing you to potentially achieve higher profits. The backtesting was conducted using the BTCUSDT pair in 15-minute timeframe on the Binance exchange. Users can configure the following options:
General Settings:
- Initial Capital (Default: $10,000)
- Currency (Default: USDT)
- Commission (Default: 0.1%)
- Slippage (Default: 5 ticks)
Order Size Management:
- DCA Mode (Default: Quantity)
- Order Size in Quantity (Default: 0.01)
- Order Size in Value (Default: $300)
Strategy's Entry Conditions:
- Number of Consecutive Bullish Candles (Default: 3)
- Close Over Candle Body % (Default: 50% - Disabled)
- Close Over Previous Candles Lookback (Default: 14 - Disabled)
- Pyramiding Number (Default: 30)
Price Drop Management:
- Enable Price Drop Calculations (Default: Enabled)
- Enable Current Balance Check (Default: Enabled)
- Price Drop Percentage Type (Default: Custom)
- Average Price Move Down Percentage % (Default: 50%)
- Fixed Price Drop Percentage % (Default: 0.5%)
- Custom Price Drop Percentage % (Defaults: 0.5, 0.5, 0.5, 1, 3, 5, 5, 10, 10, 10)
TP/SL:
- Take Profit % (Default: 3%)
- Stop Loss % (Default: 100%)
- Enable Trailing Target (Default: Enabled)
- Trailing Offset % (Default: 0.1%)
Backtest Table (Default: Enabled)
Date & Time:
- Date Range Filtering (Default: Disabled)
- Start Time
- End Time
Alert Message:
- Alert Message for Enter Long
- Alert Message for Exit Long
By providing these customizable settings, the strategy allows you to tailor it to your specific needs, enhancing the adaptability and effectiveness of your trading approach.
🔐 Source Code Protection:
The source code of the DCA-Integrated Trend Continuation Strategy is designed to be robust, reliable, and highly efficient. Its original and innovative implementation merits protecting the source code and limiting access, ensuring the exclusivity of this strategy. By safeguarding the code, the integrity and uniqueness of the strategy are preserved, giving users a competitive edge in their trading activities.
Equity Curve Trading with EMAWhat Is Equity Curve Trading?
In equity curve trading, traders apply a moving average to the curve. The idea is when the equity curve drops below the moving average, the strategy is put on hold. This is done to stop losses when either the hopes of the plan working start dimming or when the trader knows he cannot afford more losses on a strategy. The trader can resume trading this particular strategy when the equity curve is above the moving average.
Equity Curve Trading puts an investor at the ease of knowing that his investment is covered even when he is not actively tracking his strategy. When the equity curve dips below a level investor is comfortable with, it can be paused until such time that the equity curve is back above the determined moving average.
Example:
Equity Curve Trading Example
Trading Strategy
I choosed the SuperTrend strategy for BTCUSDT on 4 hour time frame. That shows nice equity curve with default settings. Let's find out and check can we improve the equity curve with this modern money management trade method?
Some shift is exist in original equity curve relatively to filtered equity curve, because of array usage, but it is not affected on calculations.
Conclusion
I tested a different time frames, settings and equity curves shapes, but it not gives advantages in equity curve. You can look at the table on the top right corner of the strategy with equity curve and you will see some statistic information for the original strategy and for the modified equity curve trade strategy. In most cases we have lower Win Rate and lower Net Profit after turning on Equity curve trading method. In some cases this can be help if you have the equity curve looks like at the picture above, but this equity curve is really bad for choosing this strategy to trade. I found that EMA works better than SMA, and RMA works better then EMA applied to Equity Curve. You can test your strategy with this trade method if you want, I make the source code opened for it. Please share your results, I hope it will helps.
Conclusion 2
Equity Curve Trading definitely has its proponents in the industry, some of them quite vocal. But, the overall efficacy of the approach is certainly not crystal clear. In fact, what is clear is that it is relatively easy to take a good strategy, and significantly degrade its performance by employing equity curve trading. While the overall objective of equity curve trading is unquestionable – cease trading poor performing strategies - it is probable that there are better ways of accomplishing that goal. From this study, the conclusion is equity curve trading with simple indicators has more downside than upside.
Simple Bollinger Bands Strategy [JoseMetal]============
ENGLISH
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- Description:
This is a simple strategy based on Bollinger Bands found in "journeymaninvestor.com" by "nealosis" in 15 feb 2021, original strategy and credits to him.
The original strategy:
- Bollinger Bands, 20 length simple moving average and 2 standard deviations.
- Buy when the closing price crosses the lower band up.
- Exit trade when the closing price touches the upper band.
This strategy worked on mayor indices such as SP500 before the current economic crisis, because those indices just retrace to continue up and up. That's why after testing it on the current data and other markets the strategy is NO longer viable and I made some optimizations to it.
The modified strategy:
- Now you can LONG and SHORT, not only LONG, but depending on the asset (mainly bullish like BTC or Indices) is better to just BUY.
- You can customize BB length and deviation, a deviation of 1.5 triggers more trades and is usually better.
- Averaging added, by default you can have up to 7 positions at 1% capital each, but all is customizable.
Other extra stuff:
- Able to pick a date range.
- Able to pick % of capital used on each trade.
- Able to close trades ON PROFIT ONLY.
- Able to increase position ONLY if the price is a certain percentage better than your average.
- Able to pick a leverage.
- Visual:
Bollinger Bands are shown.
On LONG entries you get a green background color, red for SHORTs, olive to close LONG and orange to close SHORT.
Position entries/exists with contract size are shown by TradingView by default as usual.
- Customization:
Everything is customizable, from date range to BB colors.
- Usage and recommendations:
Works better on bigger timeframes, daily is the best.
Enjoy!
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INGLÉS
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- Descripción:
Esta es una simple estrategia basada en las Bandas de Bollinger encontrada en "journeymaninvestor.com" por "nealosis" en el 15 de febrero de 2021, estrategia original y créditos a él.
La estrategia original:
- Bandas de Bollinger, media móvil simple de 20 y 2 desviaciones estándar.
- Comprar cuando el precio de cierre cruza la banda inferior hacia arriba.
- Salir de la posición cuando el precio de cierre toca la banda superior.
Esta estrategia funcionaba en índices mayores como el SP500 antes de la crisis económica actual, porque esos índices sólo retroceden para seguir subiendo y subiendo. Por eso después de probarla con los datos actuales y otros mercados la estrategia ya NO es viable y le hice algunas optimizaciones.
La estrategia modificada:
- Ahora puedes operar LONG y SHORT, no solo LONG, pero dependiendo del activo (principalmente alcistas como BTC o Índices) es mejor solo COMPRAR.
- Se puede personalizar la longitud de BB y la desviación, una desviación de 1,5 desencadena más operaciones y suele ser mejor.
- Promedio añadido, por defecto puedes tener hasta 7 posiciones al 1% de capital cada una, pero todo es personalizable.
Otras cosas extra:
- Posibilidad de elegir un rango de fechas.
- Posibilidad de elegir el % de capital utilizado en cada operación.
- Posibilidad de cerrar operaciones SÓLO CON BENEFICIO.
- Posibilidad de aumentar la posición sólo si el precio es un cierto porcentaje mejor que su promedio.
- Posibilidad de elegir un apalancamiento.
- Visual:
Se muestran las Bandas de Bollinger.
En las entradas de LARGO se obtiene un color de fondo verde, rojo para CORTO, oliva para cerrar LARGO y naranja para cerrar CORTO.
Las entradas/existencias de posiciones con tamaño de contrato son mostradas por TradingView por defecto como es habitual.
- Personalización:
Todo es personalizable, desde el rango de fechas hasta los colores de BB.
- Uso y recomendaciones:
Funciona mejor en marcos de tiempo más grandes, diario es el mejor.
¡Que lo disfrutes!
Bitcoin 30m Swing Trader Long/Short StrategyIntro
I want to share the results of my passionate hobby and the unstoppable chase for a profitable automated trading strategy. It has been created with the intention of trading only Bitcoin. Altcoins are not interesting for me, as I have discovered lots of issues with finding the right parameter values for experiencing a good performance. As altcoins typically follow the trend of bitcoin and characteristically have a high volatility that may cause stop-hunts, I decided to not over complicate this project. I was just aiming for a profitable trading strategy with an acceptable drawdown and enough confidence by a statistically significant number of trades beside a wide backtesting timespan (credits going out to TradingView: Deep Backtesting).
Total time spent on this is approximately 2 years.
Indicators used
RSI: Used for entries and trend reversal spots
MACD: Used for entry and exit optimiziation
ATR: Used for dynamic offsets in trend definition indicator
Custom trend indicator: Self-made indicator, based on simple price action of higher timeframes using pivot points to find support and resistance zones that have formerly been created
Strategy parameters
I have reduced the total parameters used to just a few. It took lots of working hours to find appropriate values along the trading algorithm and I don’t want to overcomplicate it to you.
This strategy is for those, who have been looking for a working strategy. No DIY kit.
Feel free to adapt Take profit or stop loss targets. But it’s not recommended to do so.
How it works
Entries:
I started with a kind of template that I have been using for strategies for a long time. This includes how to find the right Entries during a trend as well as spotting trend reverse opportunities. Here I combine simple indicators like RSI and MACD beside necessary trend conditions. If a target RSI Value is hit, it will enter a trade, after MACD histogram has stopped to fall/rise. Depends on long/short. While we are in a trade and trend reversed, it waits for a specific RSI target level to be hit, to reverse the trade. As simple as it is, it closes the open one and starts a trade in other direction.
Micro trend:
It starts to get more interesting when it comes to trend recognition, as it forms the core of the strategy and discovering appropriate values for it has been very hard. The final trend variable is defined by the responses over higher timeframes of my self-made trend indicator. Executed on the current timeframe, the trend indicator is quite interesting. But for a automated trading strategy it is necessary to deviate trading instructions from higher timeframes trends.
Macro trend:
The same process that happens for micro trend is also applied with much higher timeframes, like 3D or weekly. The basic assumption is, that if we are in a bull or bear run, where retail investors are flooding the markets, we are increasing our take profit targets respectively. This way we can catch bigger moves in bigger trends.
Exits:
Closing a trade generally happens when a TP target (in %) is hit, or the SL (in %) is hit. The strategy has a special treatment with SL’s. After it happens, the strategy is more careful about market conditions and typically waits for a countertrade. The third way of closing a trade has already been mentioned: the reverse trades. They happen during choppy market conditions. The strategy has also special awareness here and tracks, if reverse trades start to happen more often. After a while, it starts to be more restrictive in opening new reverse trades.
Performance
Capabilities and limitations:
As I have already mentioned the strategy is only optimized for bitcoin (Perpetual Futures). This does not mean, it can not be used on other markets, because the algorithm itself is universal appliable. A very hard task was about finding the right parameter values for the strategy performing like this. If you have a special wish to configure this strategy for a specific market, DM me. The strategy has been tested with different configurations on the following timeframes: 30, 15, 10, 5, 1. I have decided to publish the one for 30m TF, because its performance simply convinced me.
Repainting:
It has been tested lots of times against repainting.
Confidence:
The total backtesting performance reaches out to 2019-09-08. So the strategy has been managing to be successful since then, but this does not guarantee that the logic, this strategy follows, is going to continue this level in future.
Commission:
The algorithm is configured with 0.04% commission per trade, as it is on Binance (for Future Market orders).
Ordersize:
Its totally up to you, how much of your total equity should be traded. Nevertheless, I would personally recommend to not exceed 50% ordersize of your equity with this strategy. In the past, you would have had great performance beside a drawdown, that was from psychological point of view good to handle with. This strategy additionally uses STOP LOSSES, so you can never loose you whole ordersize at one trade.
Slippage:
You also must consider about getting slipped when trading this strategy on live markets. Statistically one could assume, that the slippage could be neutral, as it can be both positive or negative. It depends on your execution time, the exchange, on which you are executing trades and market conditions. But keep it in mind, as if you have too much slippage, this strategy would be unprofitable.
The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)The Flash-Strategy (Momentum-RSI, EMA-crossover, ATR)
Are you tired of manually analyzing charts and trying to find profitable trading opportunities? Look no further! Our algorithmic trading strategy, "Flash," is here to simplify your trading process and maximize your profits.
Flash is an advanced trading algorithm that combines three powerful indicators to generate highly selective and accurate trading signals. The Momentum-RSI, Super-Trend Analysis and EMA-Strategy indicators are used to identify the strength and direction of the underlying trend.
The Momentum-RSI signals the strength of the trend and only generates trading signals in confirmed upward or downward trends. The Super-Trend Analysis confirms the trend direction and generates signals when the price breaks through the super-trend line. The EMA-Strategy is used as a qualifier for the generation of trading signals, where buy signals are generated when the EMA crosses relevant trend lines.
Flash is highly selective, as it only generates trading signals when all three indicators align. This ensures that only the highest probability trades are taken, resulting in maximum profits.
Our trading strategy also comes with two profit management options. Option 1 uses the so-called supertrend-indicator which uses the dynamic ATR as a key input, while option 2 applies pre-defined, fixed SL and TP levels.
The settings for each indicator can be customized, allowing you to adjust the length, limit value, factor, and source value to suit your preferences. You can also set the time period in which you want to run the backtest and how many dollar trades you want to open in each position for fully automated trading.
Choose your preferred trade direction and stop-loss/take-profit settings, and let Flash do the rest. Say goodbye to manual chart analysis and hello to consistent profits with Flash. Try it now!
General Comments
This Flash Strategy has been developed in cooperation between Baby_whale_to_moon and JS-TechTrading. Cudos to Baby_whale_to_moon for doing a great job in transforming sophisticated trading ideas into pine scripts.
Detailed Description
The “Flash” script considers the following indicators for the generation of trading signals:
1. Momentum-RSI
2. ‘Super-Trend’-Analysis
3. EMA-Strategy
1. Momentum-RSI
• This indicator signals the strength of the underlying upward- or downward-trend.
• The signal range of this indicator is from 0 to 100. Values > 60 indicate a confirmed upward- or downward-trend.
• The strategy will only generate trading signals in case the stock (or any other financial security) is in a confirmed upward- (long entry signals) or downward-trend (short entry signals).
• This indicator provides information with regards to the strength of the underlying trend and it does not give any insight with regard to the direction of the trend. Therefore, this strategy also considers other indicators which provide technical confirmation with regards to the direction of the underlying trend.
Graph 1 shows this concept:
• The Momentum-RSI indicator gives lower readings during consolidation phases and no trading signals are generated during these periods.
Example (graph 2):
2. Super-Trend Analysis
• The red line in the graph below represents the so-called super-trend-line. Trading signals are only generated in case the price action breaks through this super-trend-line indicating a new confirmed upward-trend (or downward-trend, respectively).
• If that happens, the super trend-line changes its color from red to green, giving confirmation that the trend changed from bearish to bullish and long-entries can be considered.
• The vice-versa approach can be considered for short entries.
Graph 3 explains this concept:
3. Exponential Moving Average / EMA-Strategy
The functionality of this EMA-element of the strategy has been programmed as follows:
• The exponential moving average and two other trend lines are being used as qualifiers for the generation of trading-signals.
• Buy-signals for long-entries are only considered in case the EMA (yellow line in the graph below) crosses the red line.
• Sell-signals for short-entries are only considered in case the EMA (yellow line in the graph below) crosses the green line.
An example is shown in graph 4 below:
We use this indicator to determine the new trend direction that may occur by using the data of the price's past movement.
4. Bringing it all together
This section describes in detail, how this strategy combines the Momentum-RSI, the super-trend analysis and the EMA-strategy.
The strategy only generates trading-signals in case all of the following conditions and qualifiers are being met:
1. Momentum-RSI is higher than the set value of this strategy. The standard and recommended value is 60 (graph 5):
2. The super-trend analysis needs to indicate a confirmed upward-trend (for long-entry signals) or a confirmed downward-trend (for short-entry signals), respectively.
3. The EMA-strategy needs to indicate that the stock or financial security is in a confirmed upward-trend (long-entries) or downward-trend (short-entries), respectively.
The strategy will only generate trading signals if all three qualifiers are being met. This makes this strategy highly selective and is the key secret for its success.
Example for Long-Entry (graph 6):
When these conditions are met, our Long position is opened.
Example for Short-Entry (graph 7):
Trade Management Options (graph 8)
Option 1
In this dynamic version, the so-called supertrend-indicator is being used for the trade exit management. This supertrend-indicator is a sophisticated and optimized methodology which uses the dynamic ATR as one of its key input parameters.
The following settings of the supertrend-indicator can be changed and optimized (graph 9):
The dynamic SL/TP-lines of the supertrend-indicator are shown in the charts. The ATR-length and the supertrend-factor result in a multiplier value which can be used to fine-tune and optimize this strategy based on the financial security, timeframe and overall market environment.
Option 2 (graph 10):
Option 2 applies pre-defined, fixed SL and TP levels which will appear as straight horizontal lines in the chart.
Settings options (graph 11):
The following settings can be changed for the three elements of this strategy:
1. (Length Mom-Rsi): Length of our Mom-RSI indicator.
2. Mom-RSI Limit Val: the higher this number, the more momentum of the underlying trend is required before the strategy will start creating trading signals.
3. The length and factor values of the super trend indicator can be adjusted:ATR Length SuperTrend and Factor Super Trend
4. You can set the source value used by the ema trend indicator to determine the ema line: Source Ema Ind
5. You can set the EMA length and the percentage value to follow the price: Length Ema Ind and Percent Ema Ind
6. The backtesting period can be adjusted: Start and End time of BackTest
7. Dollar cost per position: this is relevant for 100% fully automated trading.
8. Trade direction can be adjusted: LONG, SHORT or BOTH
9. As we explained above, we can determine our stop-loss and take-profit levels dynamically or statically. (Version 1 or Version 2 )
Display options on the charts graph 12):
1. Show horizontal lines for the Stop-Loss and Take-profit levels on the charts.
2. Display relevant Trend Lines, including color setting options for the supertrend functionality. In the example below, green lines indicate a confirmed uptrend, red lines indicate a confirmed downtrend.
Other comments
• This indicator has been optimized to be applied for 1 hour-charts. However, the underlying principles of this strategy are supply and demand in the financial markets and the strategy can be applied to all timeframes. Daytraders can use the 1min- or 5min charts, swing-traders can use the daily charts.
• This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
• The combination of the qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
• Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Advanced VWAP_Pullback Strategy_Trend-Template QualifierGeneral Description and Unique Features of this Script
Introducing the Advanced VWAP Momentum-Pullback Strategy (long-only) that offers several unique features:
1. Our script/strategy utilizes Mark Minervini's Trend-Template as a qualifier for identifying stocks and other financial securities in confirmed uptrends. Mark Minervini, a 2x US Investment Champion, developed the Trend-Template, which covers eight different and independent characteristics that can be adjusted and optimized in this trend-following strategy to ensure the best results. The strategy will only trigger buy-signals in case the optimized qualifiers are being met.
2. Our strategy is based on the supply/demand balance in the market, making it timeless and effective across all timeframes. Whether you are day trading using 1- or 5-min charts or swing-trading using daily charts, this strategy can be applied and works very well.
3. We have also integrated technical indicators such as the RSI and the MA / VWAP crossover into this strategy to identify low-risk pullback entries in the context of confirmed uptrends. By doing so, the risk profile of this strategy and drawdowns are being reduced to an absolute minimum.
Minervini’s Trend-Template and the ‘Stage-Analysis’ of the Markets
This strategy is a so-called 'long-only' strategy. This means that we only take long positions, short positions are not considered.
The best market environment for such strategies are periods of stable upward trends in the so-called stage 2 - uptrend.
In stable upward trends, we increase our market exposure and risk.
In sideways markets and downward trends or bear markets, we reduce our exposure very quickly or go 100% to cash and wait for the markets to recover and improve. This allows us to avoid major losses and drawdowns.
This simple rule gives us a significant advantage over most undisciplined traders and amateurs!
'The Trend is your Friend'. This is a very old but true quote.
What's behind it???
• 98% of stocks made their biggest gains in a Phase 2 upward trend.
• If a stock is in a stable uptrend, this is evidence that larger institutions are buying the stock sustainably.
• By focusing on stocks that are in a stable uptrend, the chances of profit are significantly increased.
• In a stable uptrend, investors know exactly what to expect from further price developments. This makes it possible to locate low-risk entry points.
The goal is not to buy at the lowest price – the goal is to buy at the right price!
Each stock goes through the same maturity cycle – it starts at stage 1 and ends at stage 4
Stage 1 – Neglect Phase – Consolidation
Stage 2 – Progressive Phase – Accumulation
Stage 3 – Topping Phase – Distribution
Stage 4 – Downtrend – Capitulation
This strategy focuses on identifying stocks in confirmed stage 2 uptrends. This in itself gives us an advantage over long-term investors and less professional traders.
By focusing on stocks in a stage 2 uptrend, we avoid losses in downtrends (stage 4) or less profitable consolidation phases (stages 1 and 3). We are fully invested and put our money to work for us, and we are fully invested when stocks are in their stage 2 uptrends.
But how can we use technical chart analysis to find stocks that are in a stable stage 2 uptrend?
Mark Minervini has developed the so-called 'trend template' for this purpose. This is an essential part of our JS-TechTrading pullback strategy. For our watchlists, only those individual values that meet the tough requirements of Minervini's trend template are eligible.
The Trend Template
• 200d MA increasing over a period of at least 1 month, better 4-5 months or longer
• 150d MA above 200d MA
• 50d MA above 150d MA and 200d MA
• Course above 50d MA, 150d MA and 200d MA
• Ideally, the 50d MA is increasing over at least 1 month
• Price at least 25% above the 52w low
• Price within 25% of 52w high
• High relative strength according to IBD.
NOTE: In this basic version of the script, the Trend-Template has to be used as a separate indicator on TradingView (Public Trend-Template indicators are available in TradingView – community scripts). It is recommended to only execute buy signals in case the stock or financial security is in a stage 2 uptrend, which means that the criteria of the trend-template are fulfilled.
This strategy can be applied to all timeframes from 5 min to daily.
The VWAP Momentum-Pullback Strategy
For the JS-TechTrading VWAP Momentum-Pullback Strategy, only stocks and other financial instruments that meet the selected criteria of Mark Minervini's trend template are recommended for algorithmic trading with this startegy.
A further prerequisite for generating a buy signals is that the individual value is in a short-term oversold state (RSI).
When the selling pressure is over and the continuation of the uptrend can be confirmed by the MA / VWAP crossover after reaching a price low, a buy signal is issued by this strategy.
Stop-loss limits and profit targets can be set variably. You also have the option to make use of the trailing stop exit strategy.
Relative Strength Index (RSI)
The Relative Strength Index (RSI) is a technical indicator developed by Welles Wilder in 1978. The RSI is used to perform a market value analysis and identify the strength of a trend as well as overbought and oversold conditions. The indicator is calculated on a scale from 0 to 100 and shows how much an asset has risen or fallen relative to its own price in recent periods.
The RSI is calculated as the ratio of average profits to average losses over a certain period of time. A high value of the RSI indicates an overbought situation, while a low value indicates an oversold situation. Typically, a value > 70 is considered an overbought threshold and a value < 30 is considered an oversold threshold. A value above 70 signals that a single value may be overvalued and a decrease in price is likely , while a value below 30 signals that a single value may be undervalued and an increase in price is likely.
For example, let's say you're watching a stock XYZ. After a prolonged falling movement, the RSI value of this stock has fallen to 26. This means that the stock is oversold and that it is time for a potential recovery. Therefore, a trader might decide to buy this stock in the hope that it will rise again soon.
The MA / VWAP Crossover Trading Strategy
This strategy combines two popular technical indicators: the Moving Average (MA) and the Volume Weighted Average Price (VWAP). The MA VWAP crossover strategy is used to identify potential trend reversals and entry/exit points in the market.
The VWAP is calculated by taking the average price of an asset for a given period, weighted by the volume traded at each price level. The MA, on the other hand, is calculated by taking the average price of an asset over a specified number of periods. When the MA crosses above the VWAP, it suggests that buying pressure is increasing, and it may be a good time to enter a long position. When the MA crosses below the VWAP, it suggests that selling pressure is increasing, and it may be a good time to exit a long position or enter a short position.
Traders typically use the MA VWAP crossover strategy in conjunction with other technical indicators and fundamental analysis to make more informed trading decisions. As with any trading strategy, it is important to carefully consider the risks and potential rewards before making any trades.
This strategy is applicable to all timeframes and the relevant parameters for the underlying indicators (RSI and MA/VWAP) can be adjusted and optimized as needed.
Backtesting
Backtesting gives outstanding results on all timeframes and drawdowns can be reduced to a minimum level. In this example, the hourly chart for MCFT has been used.
Settings for backtesting are:
- Period from Jan 2020 until March 2023
- Starting capital 100k USD
- Position size = 25% of equity
- 0.01% commission = USD 2.50.- per Trade
- Slippage = 2 ticks
Other comments
- This strategy has been designed to identify the most promising, highest probability entries and trades for each stock or other financial security.
- The combination of the Trend-Template and the RSI qualifiers results in a highly selective strategy which only considers the most promising swing-trading entries. As a result, you will normally only find a low number of trades for each stock or other financial security per year in case you apply this strategy for the daily charts. Shorter timeframes will result in a higher number of trades / year.
- Consequently, traders need to apply this strategy for a full watchlist rather than just one financial security.
Cloud X MesoHello there fellow Traders!
Thanks for stopping by, so today I will be covering everything you need to to know about this TradingView strategy.
Below I will discuss everything you need to know about this strategy so you can get a full grasp of what the strategy is, the features, what it does, how it works, the benefits of how this strategy can help you, and the results.
What is Cloud X Meso?
-Cloud X Meso is a strategy that consists of 7 indicators to all line up for total confluence to take a buy or sell once all 6 indicators conditions are met. This strategy does not repaint and doesn't require any technical analysis to be used. The strategy can be used on any timeframe, and any instrument.
-I have optimized many different variations for different types of trading instruments of this strategy ready to be used. The difference of this strategy is that these variations do not need any reoptimization to keep up with recent market conditions since there are hardly any inputs used, which prevents common overfitting problems. The main goal was for this strategy to be automated, as well as plug and play or you can officially consider this as set and forever forget.
What does this strategy do?
-The main goal for this strategy is to catch long or short term trends by waiting for all 7 indicators to line up as well as using customized trading times to trade certain sessions where there is high amounts of volume in the market. This strategy doesn't always need to have a clear trending market, since it can also catch short term trends in choppy markets as well. Overall, the strategy tell you when it buys, sells, and exits after all conditions are met.
How does the strategy work?
-The way that this strategy works is when all of the indicators confluences are met. Next, a buy or sell label will print and the candles colors will color blue or red to show that the trade is in the buy or sell position followed along with a magenta colored line which is the trailing stop to follow the trade until the trade exits from the trailing stop being hit or if the strategies exit condition is met.
-The strategy does have a set Take Profit target since it relies on the trailing stop to end the trade. This is beneficial so you can catch any size of a trend move when the strategy is in high volume market sessions. You catch these trends by customizing the settings to toggle on or off certain indicators, functions, configuring a customized trading time, and toggling on or off certain trading days to make a specific approach for fine tuning a pair to trade in a certain time window with high amounts of volume to catch trending moves whether it be a long or short term trend.
Below I will explain each functionality of the strategy for you to better understand the different ways you can adjust the settings of this strategy.
Backtest Settings:
-You can use these settings to determine a start / end date of what results you would like to see in the strategy tester.
-You can determine the $ amount you would like to see on strategy testers results to be in terms of net profit and max drawdown.
-You can choose whether you want the strategy to take buys only, sells only, or buys and sells.
Automation:
-Compatible with Pine Connectors to fully automate this strategy for MT4/5
-It uses a % based risk when placing trades so you won't have to calculate a proper lot size or dollar amount.
-You can also put the symbol of what that strategy will be trading on so you know what pair its trading.
Custom Trading Times:
-When you customize a trading time for the strategy to trade in, the background will turn blue for that specific time window, and you can use the "Session Exit" function to have trades close once the time window ends when toggled on, or you can have the existing trades close on their own when "Session Exit" is toggled off.
Dynamic Trailing:
-The algorithm uses a volatility based indicator to determine proper stop loss placement depending on how volatile the market is. This will prevent you from guesstimating if your stop loss is too big or too small.
-When Dynamic trailing is off, then the strategy will use a Risk Reward based stop loss to trail everytime the trades hits a new Risk Reward target.
-You can also toggle on or off for the stop loss to go to break even once the trade hits a 1:1 Risk Reward.
Directional Bias Settings:
-This indicator is the main directional bias that uses a multi timeframe function to determine the directional bias, you can also use the Exponential Moving Average as a form of directional bias instead, or you can use both of them to work together to find the directional bias. You can also toggle each one on or off
Entry / Exit Settings:
-This indicator also uses a multi timeframe function but it determines the entry and exit for a trade when all confluences are met. You can also toggle the entry and exit functions on or off.
1 Candle Rule:
-This feature is inspired by No Nonsense Forex (NNFX) the main function of this is if your entry doesn't meet all the entry conditions, then the strategy will wait 1 more candle to meet all the entry conditions to take a trade.
No Trade Zone:
-This feature will uses a Volume based indicator to filter out low volume markets. The candles will turn grey to indicate the algorithm not to take trades, and you can also customize the sensitivity of how strong this indicator will filter out the low volume in the markets.
Indicator functions
Each indicator plays a certain role and also meets certain conditions when a buy or sell trade is placed. I will reveal 3 out of 7 of the indicators used to preserve the uniqueness of this strategy but overall, the logic of this strategies main goal is to ride long or short terms trends while getting dynamic Risk Reward trades.
-The first indicator that the strategy uses an Exponential Moving Average that is customizable, and is used as a form of a filter for either a long or short term directional bias to filter out false signals to help the algorithm trade with the trend.
-The second indicator that the strategy uses is an Oscillator which is the Wavetrend and this indicators functionality for the algorithm is used for the its buy and sell signals to line up with all the other indicators for confluence. This indicator can also be toggled on or off for you own preference
-The third indicator used is the Volume indicator, and this is used to give the other indicators the green light to enter a trade if there are high amounts of volume in the market.
What are the benefits of using this algorithm?
Stress Free Trading:
-Once automated, you will no longer need to stare at the charts all day, as well as trying to execute the trades on time or worried that you missed a setup. Or you can choose to take trades manually when a buy or sell signal comes up
Stress Free Risk Management:
-All you have to do is provide a risk % and the algorithm will do the rest of the work calculating the stop loss, exiting trades, etc. No more needing to find the right lot size, or dollar amount, all in all the strategy will manage the trades for you.
Psychology:
-when you choose to have a systematic trading approach, it eliminates a lot bad habits from human nature
What are the results like?
-I have multiple different variations of results of this strategy, but I will share one of the results.
Here is a screenshot below of what this strategy can do from just one of the variations.
The backtest below was done with another variation on simulating a 100k account risking 0.50% per trade.
Thank you for taking the time to read through this whole guide, and I hope this helped you better understand the strategy.
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!
Macro Score (DFMA) and Donchian Cloud Score StrategyA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger.
The DFMA - Democratic Fibonacci Moving Average - is a separate indicator that we have released that takes 10 different Fibonacci MAs (lengths of 3 to 233, at Fibonacci intervals) and averages them to form the DFMA line. This helps by creating a consensus on the trend based on moving averages alone. Crossovers of the DFMA with the various Fib MA lengths as well as a cross of the price source and these lines can provide adequate long and short signals.
This strategy has the signals and weights pre-determined in the code. Heaviest weights have been given to crosses of the DFMA line/Fib MA (233) as well as the crosses of the Fib MA (3)/DFMA. Additionally, there are thresholds for DPO ( Detrended Price Oscillator , above or below 0), CMO ( Chande Momentum Oscillator , above or below 0), Jurik Volatility Bands (above or below 0), and Stoch RSI (above or below 50). These four signals hold a lighter weight than the MA cross signals.
The macro score itself is printed in an underlay as a white line that goes between -10 and 10 for this strategy. In addition to the macro score line, a blue momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score. Long and short thresholds can be determined by the user in the settings menu.
The Donchian Cloud Score is derived from a set of 5 Donchian channels (upper, lower, and basis plotted) defaulted to lengths of 25, 50, 100, 150, and 200. A set of conditions associated with the channels aims to determine ranging versus trending markets. Weights are given to these conditions accordingly, then tallied up to determine the "cloud score", ranging between -25 and 25. In general, a ranging market is determined by a cloud score between -10 and 10, while a positive trending market has a score higher than 10 and a negative trending market has a score lower than -10. That said, long and short thresholds similar to the macro score itself are included in the user settings and set to a default of 5 or -5. The cloud score is plotted as a line in the underlay with coloration reflecting ranging or trending markets (green color above the long threshold, gray between the thresholds, and red below the short threshold). The cloud score is incorporated into the strategy syntax for long and short positions in that the score must be above or below the set threshold for a trade to be placed. A breakdown for the Donchian scoring is as follows:
- Broke the 25-length DC (DC(25)) upper band in the previous 3 bars - +1 if true, 0 if false
- Broke the DC(50) upper band in the previous 3 bars - +2 if true, 0 if false
- Broke the DC(100) upper band in the previous 3 bars - +3 if true, 0 if false
- Broke the DC(150) upper band in the previous 3 bars - +4 if true, 0 if false
- Broke the DC(200) upper band in the previous 3 bars - +5 if true, 0 if false
- Broke the DC(25) lower band in the previous 3 bars - -1 if true, 0 if false
- Broke the DC(50) lower band in the previous 3 bars - -2 if true, 0 if false
- Broke the DC(100) lower band in the previous 3 bars - -3 if true, 0 if false
- Broke the DC(150) lower band in the previous 3 bars - -4 if true, 0 if false
- Broke the DC(200) lower band in the previous 3 bars - -5 if true, 0 if false
- DC(25) basis line above the DC(50) basis line - +1 if true, -1 if false
- DC(25) basis line above the DC(100) basis line - +1 if true, -1 if false
- DC(25)basis line above the DC(150) basis line - +1 if true, -1 if false
- DC(25) basis line above the DC(200) basis line - +1 if true, -1 if false
- DC(50) basis line above the DC(100) basis line - +1 if true, -1 if false
- DC(50) basis line above the DC(150) basis line - +1 if true, -1 if false
- DC(50) basis line above the DC(200) basis line - +1 if true, -1 if false
- DC(100) basis line above the DC(150) basis line - +1 if true, -1 if false
- DC(100) basis line above the DC(200) basis line - +1 if true, -1 if false
- DC(150) basis line above the DC(200) basis line - +1 if true, -1 if false
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. The option for adding in a trailing stop has also been included, with options to choose between an ATR-based trail or a percentage-based trail. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview/Pineconnector Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else. If using Pineconnector, follow the same directions for setting up an alert, but use the ",buy,,risk=" syntax as noted in the tooltips.
Rocket Grid Algorithm - The Quant ScienceThe Rocket Grid Algorithm is a trading strategy that enables traders to engage in both long and short selling strategies. The script allows traders to backtest their strategies with a date range of their choice, in addition to selecting the desired strategy - either SMA Based Crossunder or SMA Based Crossover.
The script is a combination of trend following and short-term mean reversing strategies. Trend following involves identifying the current market trend and riding it for as long as possible until it changes direction. This type of strategy can be used over a medium- to long-term time horizon, typically several months to a few years.
Short-term mean reversing, on the other hand, involves taking advantage of short-term price movements that deviate from the average price. This type of strategy is usually applied over a much shorter time horizon, such as a few days to a few weeks. By rapidly entering and exiting positions, the strategy seeks to capture small, quick gains in volatile market conditions.
Overall, the script blends the best of both worlds by combining the long-term stability of trend following with the quick gains of short-term mean reversing, allowing traders to potentially benefit from both short-term and long-term market trends.
Traders can configure the start and end dates, months, and years, and choose the length of the data they want to work with. Additionally, they can set the percentage grid and the upper and lower destroyers to manage their trades effectively. The script also calculates the Simple Moving Average of the chosen data length and plots it on the chart.
The trigger for entering a trade is defined as a crossunder or crossover of the close price with the Simple Moving Average. Once the trigger is activated, the script calculates the total percentage of the side and creates a grid range. The grid range is then divided into ten equal parts, with each part representing a unique grid level. The script keeps track of each grid level, and once the close price reaches the grid level, it opens a trade in the specified direction.
The equity management strategy in the script involves a dynamic allocation of equity to each trade. The first order placed uses 10% of the available equity, while each subsequent order uses 1% less of the available equity. This results in the allocation of 9% for the second order, 8% for the third order, and so on, until a maximum of 10 open trades. This approach allows for risk management and can help to limit potential losses.
Overall, the Rocket Grid Algorithm is a flexible and powerful trading strategy that can be customized to meet the specific needs of individual traders. Its user-friendly interface and robust backtesting capabilities make it an excellent tool for traders looking to enhance their trading experience.
Macro Score - Dem. Fib. McGinley DynamicsA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger.
The DFMG - Democratic Fibonacci McGinley Dynamic - is a separate indicator that we have released that takes 10 different Fibonacci McGinley Dynamics (lengths of 3 to 233, at Fibonacci intervals) and averages them to form the DFMG line. This helps by creating a consensus on the trend based on these dynamic lines alone. Crossovers of the DFMG with the various McGinley lengths as well as a cross of the price source and these lines can provide adequate long and short signals.
This strategy has the signals and weights pre-determined in the code. Heaviest weights have been given to crosses of the DFMG line/McGinley(233) as well as the crosses of the McGinley(3)/DFMG. Additionally, there are thresholds for DPO ( Detrended Price Oscillator , above or below 0), CMO ( Chande Momentum Oscillator , above or below 0), Jurik Volatility Bands (above or below 0), and Stoch RSI (above or below 50). These four signals hold a lighter weight than the McGinley cross signals.
The macro score itself is printed in an underlay as a white line that goes between -10 and 10 for this strategy. In addition to the macro score line, a green momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to long and short thresholds for the macro score, defaulted to 5 and -5 respectively.
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. The option for adding in a trailing stop has also been included, with options to choose between an ATR-based trail or a percentage-based trail.
This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview/Pineconnector Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else. If using Pineconnector, follow the same directions for setting up an alert, but use the " ,buy, ,risk=" syntax as noted in the tooltips.
Default Properties for AVAX 20M:
DPO - 35 , uncentered
CMO - 25, open
K/D - 3/3
RSI Stoch Length - 3
Stoch Length - 4
Stoch Source - open
JVB Length - 14
JVB Smoothing - 2
DFMG source - close
Macro Length - 14
TP % - 1.5%
TTP % - 0.005%
SL % - 1.8%, no trail
Weird Renko StratThis strategy uses Renko, it generates a signal when there is a reversal in Renko. When using historical data, it provides a good entry and an okay exit. However, in a real-time environment, this strategy is subject to repaint and may produce a false signal.
As a result, the backtesting result should not be used as a metric to predict future results. It is highly recommended to forward-test the strategy before using it in real trading. I forward test it from 12/18/2022 to 12/21/2022 in paper trading, using the alert feature in Tradingview. I made 60 trades trading the BTCUSDT BINANCE 3 min with 26 as the param and under the condition that I use 20x margin, compounding my yield, and having 0 trading fee, a steady loss is generated: from $10 to $3.02.
This is quite interesting. As if I flip the signal from "Long" to "Short" and another way too, it will be a steady profit from $10 to $21.85. Hence, if I'm trying to anti-trade the real-time alert signal, the current "4 Days Result" will be good. Nevertheless, I still have to forward-test it for longer to see if it will fail eventually.
Dive into the setting of the strategy
- Margin is the leverage you use. 1 means 1x, 10 means 10x. It affects the backtest yield when you backtest
- Compound Yield button is for compound calculation, disable it to go back to normal backtesting
- Anti Strategy button is to do the opposite direction trade, when the original strat told you to "Long", you "Short" instead. Enable it to use the feature
- Param is the block size for the Renko chart
- Drawdown is just a visual tool for you in case you want to place a stop loss (represent by the semitransparent red area in the chart)
- From date Thru Date is to specify the backtest range of the strategy, This feature is turned off by default. It is controlled by the Max Backtest Timeframe which will be explain below
- Max Backtest Timeframe control the From date Thru Date function, disable it to enable the From Date Thru Date function
Param is the most important input in this strategy as it directly affects performance. It is highly recommended to backtest nearly all the possible parameters before deploying it in real trading. Some factors should be considered:
- Price of the asset (like an asset of 1 USD vs an asset of 10000 USD required different param)
- Timeframe (1-minute param is different than 1-month param)
I believe this is caused by the volatility of the selected timeframe since different timeframe has different volatility. Param should be fine-tuned before usage.
Here is the param I'm using:
BTCUSDT BINANCE 3min: 26
BTCUSDT BINANCE 5min: 28
BTCUSDT BINANCE 1day: 15
Background of the strategy:
- The strategy starts with $10 at the start of backtesting (customizable in setting)
- The trading fee is set to 0.00% which is not common for most of the popular exchanges (customizable in setting)
- The contract size is not a fixed amount, but it uses your balance to buy it at the open price. If you are using the compound mode, your balance will be your current total balance. If you are using the non-compound mode, it will just use the $10 you start with unless you change the amount you start with. If you are using a margin higher than 1, it will calculate the corresponding contract size properly based on your margin. (Only these options are allowed, you are not able to change them without changing the code)
Macro Score - DFMA-BasedA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger.
The DFMA - Democratic Fibonacci Moving Average - is a separate indicator that we have released that takes 10 different Fibonacci MAs (lengths of 3 to 233, at Fibonacci intervals) and averages them to form the DFMA line. This helps by creating a consensus on the trend based on moving averages alone. Crossovers of the DFMA with the various Fib MA lengths as well as a cross of the price source and these lines can provide adequate long and short signals.
This strategy has the signals and weights pre-determined in the code. Heaviest weights have been given to crosses of the DFMA line/Fib MA (233) as well as the crosses of the Fib MA (3)/DFMA. Additionally, there are thresholds for DPO ( Detrended Price Oscillator , above or below 0), CMO ( Chande Momentum Oscillator , above or below 0), Jurik Volatility Bands (above or below 0), and Stoch RSI (above or below 50). These foursignals hold a lighter weight than the MA cross signals.
The macro score itself is printed in an underlay as a white line that goes between -10 and 10 for this strategy. In addition to the macro score line, a blue momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score (-5/5).
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else.
Default Properties, for AVAX 20M:
DPO - 40, uncentered
CMO - 25, open
K/D - 3/3
RSI Stoch Length - 3
Stoch Length - 4
Stoch Source - open
JVB Length - 25
JVB Smoothing - 2
DFMA source - close
Macro Length - 13
TP % - 1.5%
TTP % - 0.005%
SL % - 2%
MACD + RSI + ADX Strategy (ChatGPT-powered) by TradeSmartThis is a trading strategy made by TradeSmart, using the recommendations given by ChatGPT . As an experiment, we asked ChatGPT on which indicators are the most popular for trading. We used all of the recommendations given, and added more. We ended up with a strategy that performs surprisingly well on many crypto and forex assets. See below for exact details on what logic was implemented and how you can change the parameters of the strategy.
The strategy is a Christmas special , this is how we would like to thank the support of our followers.
The strategy has performed well on Forex, tested on 43 1-hour pairs and turned a profit in 21 cases. Also it has been tested on 51 crypto pairs using the 1-hour timeframe, and turned a profit in 45 cases with a Profit Factor over 1.4 in the top-5 cases. Tests were conducted without commission or slippage, unlike the presented result which uses 0.01% commission and 5 tick slippage.
Some of the top performers were:
SNXUSDT
SOLUSDT
CAKEUSDT
LINKUSDT
EGLDUSDT
GBPJPY
TRYJPY
USDJPY
The strategy was implemented using the following logic:
Entry strategy:
Long entry:
Price should be above the Simple Moving Average (SMA)
There should be a cross up on the MACD (indicated by the color switch on the histogram, red to green)
RSI should be above the 50 level
Volume is above the selected volume-based Exponential Moving Average (EMA)
ADX should also agree to this position: below 50 and over 20, and above the Regularized Moving Average (REMA)
Short entry:
Price should be under the Simple Moving Average (SMA)
There should be a cross down on the MACD (indicated by the color switch on the histogram, red to green)
RSI should be below the 50 level
Volume is above the selected volume-based Exponential Moving Average (EMA)
ADX should also agree to this position: below 50 and over 20, and above the Regularized Moving Average (REMA)
Exit strategy:
Stop Loss will be placed based on ATR value (with 1.5 Risk)
Take profit level will be placed with a 2.5 Risk/Reward Ratio
Open positions will be closed early based on the Squeeze Momentum (Long: change to red, Short: change to green)
NOTE! : The position sizes used in the example is with 'Risk Percentage (current)', according which the position size will be determined such
that the potential loss is equal to % of the current available capital. This means that in most of the cases, the positions are calculated using leverage.
Parameters of every indicator used in the strategy can be tuned in the strategy settings as follows:
Plot settings:
Plot Signals: true by default, Show all Long and Short signals on the signal candle
Allow early TP/SL plots: false by default, Checking this option will result in the TP and SL lines to be plotted also on the signal candle rather than just the entry candle. Consider this only when manual trading, since backtest entries does not happen on the signal candle.
Entry Signal:
Fast Length: 12 by default
Slow Length: 26 by default
Source: hlcc4 by default
Signal Smoothing: 9 by default
Oscillator MA Type: EMA by default
Signal Line MA Type: EMA by default
Exit Strategy:
ATR Based Stop Loss: true by default
ATR Length (of the SL): 14 by default
ATR Smoothing (of the SL): EMA by default
Candle Low/High Based Stop Loss: false by default, recent lowest or highest point (depending on long/short position) will be used to calculate stop loss value. Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier. Please select only one active stop loss. Default value (if nothing or multiple stop losses are selected) is the 'ATR Based Stop Loss'.
Candle Lookback (of the SL): 10 by default
Base Risk Multiplier: 1.5 by default, the stop loss will be placed at this risk level (meaning in case of ATR SL that the ATR value will be multiplied by this factor and the SL will be placed that value away from the entry level)
Risk to Reward Ratio: 2.5 by default, the take profit level will be placed such as this Risk/Reward ratio is met
Force Exit based on Squeeze Momentum: true by default, a Long position will be closed when Squeeze Momentum turns red inside an open position and a Short position will be closed when Squeeze Momentum turns green inside an open position
BB Length: 20 by default
BB Mult Factor: 1.0 by default
KC Length: 20 by default
KC Mult Factor: 1.5 by default
Use True Range (KC): Yes by default
Base Setups:
Allow Long Entries: true by default
Allow Short Entries: true by default
Order Size: 1.5 by default
Order Type: Risk Percentage (current) by default, allows adjustment on how the position size is calculated: Cash: only the set cash ammount will be used for each trade Contract(s): the adjusted number of contracts will be used for each trade Capital Percentage: a % of the current available capital will be used for each trade Risk Percentage (current): position size will be determined such that the potential loss is equal to % of the current available capital Risk Percentage (initial): position size will be determined such that the potential loss is equal to % of the initial capital
Trend Filter:
Use long trend filter: true by default, only enter long if price is above Long MA
Show long trend filter: true by default, plot the selected MA on the chart
MA Type (Long): SMA by default
MA Length (Long): 100 by default
MA Source (Long): close by default
Use short trend filter: true by default, only enter long if price is under Short MA
Show short trend filter: false by default, plot the selected MA on the chart
MA Type (Short): SMA by default
MA Length (Short): 100 by default
MA Source (Short): close by default
Simple RSI Limiter:
Limit using Simple RSI: true by default, if set to 'Normal', only enter long when Simple RSI is lower then Long Boundary, and only enter short when Simple RSI is higher then Short Boundary. If set to 'Reverse', only enter long when Simple RSI is higher then Long Boundary, and only enter short when Simple RSI is lower then Short Boundary.
Simple RSI Limiter Type:
RSI Length: 14 by default
RSI Source: hl2 by default
Simple RSI Long Boundary: 50 by default
Simple RSI Short Boundary: 50 by default
ADX Limiter:
Use ADX Limiter: true by default, only enter into any position (long/short) if ADX value is higher than the Low Boundary and lower than the High Boundary.
ADX Length: 5 by default
DI Length: 5 by default
High Boundary: 50 by default
Low Boundary: 20 by default
Use MA based calculation: Yes by default, if 'Yes', only enter into position (long/short) if ADX value is higher than MA (ADX as source).
MA Type: REMA by default
MA Length: 5 by default
Volume Filter:
Only enter trades where volume is higher then the volume-based MA: true by default, a set type of MA will be calculated with the volume as source, and set length
MA Type: EMA by default
MA Length: 10 by default
Session Limiter:
Show session plots: false by default, show crypto market sessions on chart: Sidney (red), Tokyo (orange), London (yellow), New York (green)
Use session limiter: false by default, if enabled, trades will only happen in the ticked sessions below.
Sidney session: false by default, session between: 15:00 - 00:00 (EST)
Tokyo session: false by default, session between: 19:00 - 04:00 (EST)
London session: false by default, session between: 03:00 - 11:00 (EST)
New York session: false by default, session between: 08:00 - 17:00 (EST)
Date Range:
Limit Between Dates: false by default
Start Date: Jul 01 2021 00:00:00 by default
End Date: Dec 31 2022 00:00:00 by default
Trading Time:
Limit Trading Time: false by default, tick this together with the options below to enable limiting based on day and time
Valid Trading Days Global: 1234567 by default, if the Limit Trading Time is on, trades will only happen on days that are present in this field. If any of the not global Valid Trading Days is used, this field will be neglected. Values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) To trade on all days use: 123457
(1) Valid Trading Days: false, 1234567 by default, values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) The script will trade on days that are present in this field. Please make sure that this field and also (1) Valid Trading Hours Between is checked
(1) Valid Trading Hours Between: false, 0930-1600 by default, hours between which the trades can happen. The time is always in the exchange's timezone
Fine-tuning is highly recommended when using other asset/timeframe combinations.
Macro Score -- User-Customized Scores and SignalsA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger. This particular strategy allows the user to choose between 18 different signals to be used in scoring as well as allowing the user to determine the individual weights of each score as well as the overall threshold to determine long or short signals. Weights for each score range between 1 and 5, with 5 being the greatest weight. The overall threshold for long or short is dependent on the total possible weights added together (i.e. if your weights total -10 or +10, a threshold within this range must be used).
The macro score itself is printed in an underlay as a white line that goes between the maximum positive and negative values for all weights added together for this strategy. In addition to the macro score line, a green momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score. The length of the Macro Score's momentum line can be found in the settings.
The current signals to choose from include:
- ADX Threshold - if the Average Directional Index is above a set threshold, signal positive or negative
- CMF Threshold - if the Chaikin Money Flow oscillator is above 0, signal positive; otherwise, signal negative
- CMO > TSI Signal - signal positive if there is a cross of the Chande Momentum Oscillator and the True Strength Index signal line
- CMO Threshold - if the Chande Momentum Oscillator is above 0, signal positive; otherwise, signal negative
- DPO Threshold - if the Detrended Price Oscillator is above 0, signal positive; otherwise, signal negative
- EOM Threshold - if the Ease of Money Oscillator is above 0, signal positive; otherwise, signal negative
- Jurik Threshold - if the Jurik price line (from the Jurik Volatility Bands) is above 0, signal positive; otherwise, signal negative
- MACD Threshold - if the MACD signal line is above 0, signal positive; otherwise, signal negative
- McGinley Cross - a crossover of a fast McGinley Dynamic length line and a slow McGinley Dynamic line signals positive; otherwise, signal negative
- PSAR - if the direction of the PSAR is heading long, signal positive; otherwise, signal negative
- ROC Threshold - if the Rate of Change oscillator is above 0, signal positive; otherwise, signal negative
- RSI Threshold - if the Relative Strength Index is above 50, signal positive; otherwise, signal negative
- Stoch RSI Threshold - if the Stoch RSI is above 50, signal positive; otherwise, signal negative
- Supertrend - if the Supertrend determines long, signal positive; otherwise, signal negative
- TSI Cross - a crossover of the True Strength Index value line and the TSI signal line signals positive; otherwise, signal negative
- TSI Signal Threshold - if the TSI signal line is above 0, signal positive; otherwise, signal negative
- Williams Alligator Cross - if the Williams Alligator lips cross the teeth and jaw, signal positive; otherwise, signal negative
- Williams %R - if the Williams %R is above -50, signal positive; otherwise, signal negative
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else.
Sample setup for SOLUSDT 30M:
- Score 1 - Value 4, PSAR (0.05 start, 0.02 increment, 0.2 max value; sourced open)
- Score 2 - Value 4, Jurik Threshold (JVB Length 25, JVB Smoothing 6, JVB Price Threshold 0)
- Score 3 - Value 5, DPO Threshold (DPO Length 40, uncentered)
- Score 4 - Value 5, CMO Threshold (CMO Length 40, sourced open)
- Score 5 - Value 2, MACD Threshold (Fast Length 12, Slow Length 30, sourced open)
- Macro Length 21
- Long Threshold - -3
- Short Threshold - +3
- Take Profit % - 0.9/0.9
- Trail % - 0.005
- Stop Loss % - 1.4
Sample setup for AVAXUSDT 20M:
- Score 1 - Value 3, TSI Cross (Long Length 25, Short Length 16, Signal Length 17)
- Score 2 - Value 2, TSI Signal Threshold (same settings as the TSI Cross)
- Score 3 - Value 2, Jurik Threshold (JVB Length 20, JVB Smoothing 8, JVB Price Threshold 0)
- Score 4 - Value 2, DPO Threshold (DPO Length 40, uncentered)
- Score 5 - Value 1, Stoch Threshold (K/D 3, RSI (Stoch) Length 10, Stochastic Length 4, sourced open)
- Macro Length 13
- Long Threshold - +5
- Short Threshold - -5
- Take Profit % - 1.2/1.2
- Trail % - 0.005
- Stop Loss % - 1.5
Macro Score - TSI-BasedA "macro score", as defined here, is created by giving various weights to different signals and adding them together to get one smooth score. Positive or negative values are assigned to each of the signals depending on if the statement is true or false (e.g. DPO > 0: +1, DPO < 0: -1). This manner of strategy allows for a subset of the available signals to be present at one time as opposed to every technical signal having to be active in order for a long/short signal to trigger.
This strategy has the signals and weights pre-determined in the code. Heaviest weights have been given to various TSI (True Strength Index) signals, including a crossover/crossunder of TSI signal and TSI value, a threshold for the TSI Signal (above or below 0), and a crossover/crossunder of the CMO (Chande Momentum Oscillator) and the TSI signal line. Additionally, there are thresholds for DPO (Detrended Price Oscillator, above or below 0), Jurik Volatility Bands (above or below 0), and Stoch RSI (above or below 50). These three signals hold a lighter weight than the three TSI signals.
The macro score itself is printed in an underlay as a white line that goes between -10 and 10 for this strategy. In addition to the macro score line, a red momentum line (sourced by the macro score itself) has been included. A crossover/crossunder of the macro score and the macro momentum line is included into the long/short signal syntax in addition to a threshold for the macro score (-6/6).
Take profit, stop loss, and trailing percentages are also included, found at the bottom of the Input tab under “TT and TTP” as well as “Stop Loss”. Make sure to understand the TP/SL ratio that you desire before use, as the desired hit rate/profitability percentage will be affected accordingly. This strategy does NOT guarantee future returns. Apply caution in trading regardless of discretionary or algorithmic. Understand the concepts of risk/reward and the intricacies of each strategy choice before utilizing them in your personal trading.
Profitview Settings:
If you wish to utilize Profitview’s automation system, find the included “Profitview Settings” under the Input tab of the strategy settings menu. If not, skip this section entirely as it can be left blank. Options will be “OPEN LONG TITLE”, “OPEN SHORT TITLE”, “CLOSE LONG TITLE”, and “CLOSE SHORT TITLE”. If you wished to trade SOL, for example, you would put “SOL LONG”, “SOL SHORT”, “SOL CLOSE LONG”, and “SOL CLOSE SHORT” in these areas. Within your Profitview extension, ensure that your Alerts all match these titles. To set an alert for use with Profitview, go to the “Alerts” tab in TradingView, then create an alert. Make sure that your desired asset and timeframe are currently displayed on your screen when creating the alert. Under the “Condition” option of the alert, select the strategy, then select the expiration time. If using TradingView Premium, this can be open-ended. Otherwise, select your desired expiration time and date. This can be updated whenever desired to ensure the strategy does not expire. Under “Alert actions”, nothing necessarily needs to be selected unless so desired. Leave the “Alert name” option empty. For the “Message”, delete the generated message and replace it with {{strategy.order.alert_message}} and nothing else.
