RSI & Backed-Weighted MA StrategyRSI & MA Strategy :
INTRODUCTION :
This strategy is based on two well-known indicators that work best together: the Relative Strength Index (RSI) and the Moving Average (MA). We're going to use the RSI as a trend-follower indicator, rather than a reversal indicator as most are used to. To the signals sent by the RSI, we'll add a condition on the chart's MA, filtering out irrelevant signals and considerably increasing our winning rate. This is a medium/long-term strategy. There's also a money management method enabling us to reinvest part of the profits or reduce the size of orders in the event of substantial losses.
RSI :
The RSI is one of the best-known and most widely used indicators in trading. Its purpose is to warn traders when an asset is overbought or oversold. It was designed to send reversal signals, but we're going to use it as a trend indicator by increasing its length to 20. The RSI formula is as follows :
RSI (n) = 100 - (100 / (1 + (H (n)/L (n))))
With n the length of the RSI, H(n) the average of days closing above the open and L(n) the average of days closing below the open.
MA :
The Moving Average is also widely used in technical analysis, to smooth out variations in an asset. The SMA formula is as follows :
SMA (n) = (P1 + P2 + ... + Pn) / n
where n is the length of the MA.
However, an SMA does not weight any of its terms, which means that the price 10 days ago has the same importance as the price 2 days ago or today's price... That's why in this strategy we use a RWMA, i.e. a back-weighted moving average. It weights old prices more heavily than new ones. This will enable us to limit the impact of short-term variations and focus on the trend that was dominating. The RWMA used weights :
The 4 most recent terms by : 100 / (4+(n-4)*1.30)
The other oldest terms by : weight_4_first_term*1.30
So the older terms are weighted 1.30 more than the more recent ones. The moving average thus traces a trend that accentuates past values and limits the noise of short-term variations.
PARAMETERS :
RSI Length : Lenght of RSI. Default is 20.
MA Type : Choice between a SMA or a RWMA which permits to minimize the impact of short term reversal. Default is RWMA.
MA Length : Length of the selected MA. Default is 19.
RSI Long Signal : Minimum value of RSI to send a LONG signal. Default is 60.
RSI Short signal : Maximum value of RSI to send a SHORT signal. Default is 40.
ROC MA Long Signal : Maximum value of Rate of Change MA to send a LONG signal. Default is 0.
ROC MA Short signal : Minimum value of Rate of Change MA to send a SHORT signal. Default is 0.
TP activation in multiple of ATR : Threshold value to trigger trailing stop Take Profit. This threshold is calculated as multiple of the ATR (Average True Range). Default value is 5 meaning that to trigger the trailing TP the price need to move 5*ATR in the right direction.
Trailing TP in percentage : Percentage value of trailing Take Profit. This Trailing TP follows the profit if it increases, remaining selected percentage below it, but stops if the profit decreases. Default is 3%.
Fixed Ratio : This is the amount of gain or loss at which the order quantity is changed. Default is 400, which means that for each $400 gain or loss, the order size is increased or decreased by a user-selected amount.
Increasing Order Amount : This is the amount to be added to or subtracted from orders when the fixed ratio is reached. The default is $200, which means that for every $400 gain, $200 is reinvested in the strategy. On the other hand, for every $400 loss, the order size is reduced by $200.
Initial capital : $1000
Fees : Interactive Broker fees apply to this strategy. They are set at 0.18% of the trade value.
Slippage : 3 ticks or $0.03 per trade. Corresponds to the latency time between the moment the signal is received and the moment the order is executed by the broker.
Important : A bot has been used to test the different parameters and determine which ones maximize return while limiting drawdown. This strategy is the most optimal on BITSTAMP:ETHUSD with a timeframe set to 6h. Parameters are set as follows :
MA type: RWMA
MA Length: 19
RSI Long Signal: >60
RSI Short Signal : <40
ROC MA Long Signal : <0
ROC MA Short Signal : >0
TP Activation in multiple ATR : 5
Trailing TP in percentage : 3
ENTER RULES :
The principle is very simple:
If the asset is overbought after a bear market, we are LONG.
If the asset is oversold after a bull market, we are SHORT.
We have defined a bear market as follows : Rate of Change (20) RWMA < 0
We have defined a bull market as follows : Rate of Change (20) RWMA > 0
The Rate of Change is calculated using this formula : (RWMA/RWMA(20) - 1)*100
Overbought is defined as follows : RSI > 60
Oversold is defined as follows : RSI < 40
LONG CONDITION :
RSI > 60 and (RWMA/RWMA(20) - 1)*100 < -1
SHORT CONDITION :
RSI < 40 and (RWMA/RWMA(20) - 1)*100 > 1
EXIT RULES FOR WINNING TRADE :
We have a trailing TP allowing us to exit once the price has reached the "TP Activation in multiple ATR" parameter, i.e. 5*ATR by default in the profit direction. TP trailing is triggered at this point, not limiting our gains, and securing our profits at 3% below this trigger threshold.
Remember that the True Range is : maximum(H-L, H-C(1), C-L(1))
with C : Close, H : High, L : Low
The Average True Range is therefore the average of these TRs over a length defined by default in the strategy, i.e. 20.
RISK MANAGEMENT :
This strategy may incur losses. The method for limiting losses is to set a Stop Loss equal to 3*ATR. This means that if the price moves against our position and reaches three times the ATR, we exit with a loss.
Sometimes the ATR can result in a SL set below 10% of the trade value, which is not acceptable. In this case, we set the SL at 10%, limiting losses to a maximum of 10%.
MONEY MANAGEMENT :
The fixed ratio method was used to manage our gains and losses. For each gain of an amount equal to the value of the fixed ratio, we increase the order size by a value defined by the user in the "Increasing order amount" parameter. Similarly, each time we lose an amount equal to the value of the fixed ratio, we decrease the order size by the same user-defined value. This strategy increases both performance and drawdown.
Enjoy the strategy and don't forget to take the trade :)
在脚本中搜索"Trailing stop"
Moving Average SARHello Traders,
Today, I have brought to you an indicator that utilizes the Parabolic SAR.
To begin with, the Parabolic SAR is an indicator that trails the price in the form of a parabola, seeking out Stop And Reverse points.
The indicator I present merges the calculation formula of the Parabolic SAR with the Moving Average.
One aspect I pondered over was how to determine the starting point of this SAR. Trailing the price flow with the logic set by the moving average was fine, but the question was where to begin.
My approach involves a variable I call 'sensitiveness,' which automatically adjusts the length according to the timeframe you are observing. Using pinescript's math.ceil, I formulated:
interval_to_len = timeframe.multiplier * (timeframe.isdaily ? 1440 : timeframe.isweekly ? 1440 * 7 : timeframe.ismonthly ? 1440 * 30 : 1)
main_len = math.ceil(sensitiveness / interval_to_len)
This formula represents the length, and through variables like:
_highest = math.min(ta.highest(high, main_len), close + ta.atr(46)*4)
_lowest = math.max(ta.lowest(low, main_len), close - ta.atr(46)*4)
I have managed to set the risk at a level that does not impose too great a burden.
Moreover, the 'Trend Strength Parameter' allows you to choose how strongly to trail the current price.
Lastly, think of the Band Width as a margin for accepting changes in the trend. As the value increases, the Band Width expands, measured through the ATR.
This indicator is particularly useful for holding positions and implementing trailing stops. It will be especially beneficial for those interested in price tracking of trends, like with Parabolic SAR or Supertrend.
I hope you find this tool useful.
Long-Only Opening Range Breakout (ORB) with Pivot PointsIntraday Trading Strategy: Long-Only Opening Range Breakout (ORB) with Pivot Points
Background:
Opening Range Breakout (ORB) is a popular long-only trading strategy that capitalizes on the early morning volatility in financial markets. It's based on the idea that the initial price movements during the first few minutes or hours of the trading day can set the tone for the rest of the session. The strategy involves identifying a price range within which the asset trades during the opening period and then taking long positions when the price breaks out to the upside of this range.
Pivot Points are a widely used technical indicator in trading. They represent potential support and resistance levels based on the previous day's price action. Pivot points are calculated using the previous day's high, low, and close prices and can help traders identify key price levels for making trading decisions.
How to Use the Script:
Initialization: This script is written in Pine Script, a domain-specific language for trading strategies on the TradingView platform. To use this script, you need to have access to TradingView.
Apply the Script: You can do this by adding it to your favorites, then selecting the script in the indicators list under favorites or by searching for it by name under community scripts.
Customize Settings: The script allows you to customize various settings through the TradingView interface. These settings include:
Opening Session: You can set the time frame for the opening session.
Max Trades per Day: Specify the maximum number of long trades allowed per trading day.
Initial Stop Loss Type: Choose between using a percentage-based stop loss or the previous candles low for stop loss calculations.
Stop Loss Percentage: If you select the percentage-based stop loss, specify the percentage of the entry price for the stop loss.
Backtesting Start and End Time: Set the time frame for backtesting the strategy.
Strategy Signals:
The script will display pivot points in blue (R1, R2, R3, R4, R5) and half-pivot points in gray (R0.5, R1.5, R2.5, R3.5, R4.5) on your chart.
The green line represents the opening range.
The script generates long (buy) signals based on specific conditions:
---The open price is below the opening range high (h).
---The current high price is above the opening range high.
---Pivot point R1 is above the opening range high.
---It's a long-only strategy designed to capture upside breakouts.
---It also respects the maximum number of long trades per day.
The script manages long positions, calculates stop losses, and adjusts long positions according to the defined rules.
Trailing Stop Mechanism
The script incorporates a dynamic trailing stop mechanism designed to protect and maximize profits for long positions. Here's how it works:
1. Initialization:
The script allows you to choose between two types of initial stop loss:
---Percentage-based: This option sets the initial stop loss as a percentage of the entry price.
---Previous day's low: This option sets the initial stop loss at the previous day's low.
2. Setting the Initial Stop Loss (`sl_long0`):
The initial stop loss (`sl_long0`) is calculated based on the chosen method:
---If "Percentage" is selected, it calculates the stop loss as a percentage of the entry price.
---If "Previous Low" is selected, it sets the stop loss at the previous day's low.
3. Dynamic Trailing Stop (`trail_long`):
The script then monitors price movements and uses a dynamic trailing stop mechanism (`trail_long`) to adjust the stop loss level for long positions.
If the current high price rises above certain pivot point levels, the trailing stop is adjusted upwards to lock in profits.
The trailing stop levels are calculated based on pivot points (`r1`, `r2`, `r3`, etc.) and half-pivot points (`r0.5`, `r1.5`, `r2.5`, etc.).
The script checks if the high price surpasses these levels and, if so, updates the trailing stop accordingly.
This dynamic trailing stop allows traders to secure profits while giving the position room to potentially capture additional gains.
4. Final Stop Loss (`sl_long`):
The script calculates the final stop loss level (`sl_long`) based on the following logic:
---If no position is open (`pos == 0`), the stop loss is set to zero, indicating there is no active stop loss.
---If a position is open (`pos == 1`), the script calculates the maximum of the initial stop loss (`sl_long0`) and the dynamic trailing stop (`trail_long`).
---This ensures that the stop loss is always set to the more conservative of the two values to protect profits.
5. Plotting the Stop Loss:
The script plots the stop loss level on the chart using the `plot` function.
It will only display the stop loss level if there is an open position (`pos == 1`) and it's not a new trading day (`not newday`).
The stop loss level is shown in red on the chart.
By combining an initial stop loss with a dynamic trailing stop based on pivot points and half-pivot points, the script aims to provide a comprehensive risk management mechanism for long positions. This allows traders to lock in profits as the price moves in their favor while maintaining a safeguard against adverse price movements.
End of Day (EOD) Exit:
The script includes an "End of Day" (EOD) exit mechanism to automatically close any open positions at the end of the trading day. This feature is designed to manage and control positions when the trading day comes to a close. Here's how it works:
1. Initialization:
At the beginning of each trading day, the script identifies a new trading day using the `is_newbar('D')` condition.
When a new trading day begins, the `newday` variable becomes `true`, indicating the start of a new trading session.
2. Plotting the "End of Day" Signal:
The script includes a plot on the chart to visually represent the "End of Day" signal. This is done using the `plot` function.
The plot is labeled "DayEnd" and is displayed as a comment on the chart. It signifies the EOD point.
3. EOD Exit Condition:
When the script detects that a new trading day has started (`newday == true`), it triggers the EOD exit condition.
At this point, the script proceeds to close all open positions that may have been active during the trading day.
4. Closing Open Positions:
The `strategy.close_all` function is used to close all open positions when the EOD exit condition is met.
This function ensures that any remaining long positions are exited, regardless of their current profit or loss.
The function also includes an `alert_message`, which can be customized to send an alert or notification when positions are closed at EOD.
Purpose of EOD Exit
The "End of Day" exit mechanism serves several essential purposes in the trading strategy:
Risk Management: It helps manage risk by ensuring that positions are not left open overnight when markets can experience increased volatility.
Capital Preservation: Closing positions at EOD can help preserve trading capital by avoiding potential adverse overnight price movements.
Rule-Based Exit: The EOD exit is rule-based and automatic, ensuring that it is consistently applied without emotions or manual intervention.
Scalability: It allows the strategy to be applied to various markets and timeframes where EOD exits may be appropriate.
By incorporating an EOD exit mechanism, the script provides a comprehensive approach to managing positions, taking profits, and minimizing risk as each trading day concludes. This can be especially important in volatile markets like cryptocurrencies, where overnight price swings can be significant.
Backtesting: The script includes a backtesting feature that allows you to test the strategy's performance over historical data. Set the start and end times for backtesting to see how the long-only strategy would have performed in the past.
Trade Execution: If you choose to use this script for live trading, make sure you understand the risks involved. It's essential to set up proper risk management, including position sizing and stop loss orders.
Monitoring: Monitor the long-only strategy's performance over time and be prepared to make adjustments as market conditions change.
Disclaimer: Trading carries a risk of capital loss. This script is provided for educational purposes and as a starting point for your own long-only strategy development. Always do your own research and consider seeking advice from a qualified financial professional before making trading decisions.
Nifty 50 5mint Strategy
The script defines a specific trading session based on user inputs. This session is specified by a time range (e.g., "1000-1510") and selected days of the week (e.g., Monday to Friday). This session definition is crucial for trading only during specific times.
Lookback and Breakout Conditions:
The script uses a lookback period and the highest high and lowest low values to determine potential breakout points. The lookback period is user-defined (default is 10 periods).
The script also uses Bollinger Bands (BB) to identify potential breakout conditions. Users can enable or disable BB crossover conditions. BB consists of an upper and lower band, with the basis.
Additionally, the script uses Dema (Double Exponential Moving Average) and VWAP (Volume Weighted Average Price) . Users can enable or disable this condition.
Buy and Sell Conditions:
Buy conditions are met when the close price exceeds the highest high within the specified lookback period, Bollinger Bands conditions are satisfied, Dema-VWAP conditions are met, and the script is within the defined trading session.
Sell conditions are met when the close price falls below the lowest low within the lookback period, Bollinger Bands conditions are satisfied, Dema-VWAP conditions are met, and the script is within the defined trading session.
When either condition is met, it triggers a "long" or "short" position entry.
Trailing Stop Loss (TSL):
Users can choose between fixed points ( SL by points ) or trailing stop (Profit Trail).
For fixed points, users specify the number of points for the stop loss. A fixed stop loss is set at a certain distance from the entry price if a position is opened.
For Profit Trail, users can enable or disable this feature. If enabled, the script uses a "trail factor" (lookback period) to determine when to adjust the stop loss.
If the price moves in the direction of the trade and reaches a certain level (determined by the trail factor), the stop loss is adjusted, trailing behind the price to lock in profits.
If the close price falls below a certain level (lowest low within the trail factor(lookback)), and a position is open, the "long" position is closed (strategy.close("long")).
If the close price exceeds a certain level (highest high within the specified trail factor(lookback)), and a position is open, the "short" position is closed (strategy.close("short")).
Positions are also closed if they are open outside of the defined trading session.
Background Color:
The script changes the background color of the chart to indicate buy (green) and sell (red) signals, making it visually clear when the strategy conditions are met.
In summary, this script implements a breakout trading strategy with various customizable conditions, including Bollinger Bands, Dema-VWAP crossovers, and session-specific rules. It also includes options for setting stop losses and trailing stop losses to manage risk and lock in profits. The "trail factor" helps adjust trailing stops dynamically based on recent price movements. Positions are closed under certain conditions to manage risk and ensure compliance with the defined trading session.
CE=Buy, CE_SL=stoploss_buy, tCsl=Trailing Stop_buy.
PE=sell, PE_SL= stoploss_sell, tpsl=Trailing Stop_sell.
Remember that trading involves inherent risks, and past performance is not indicative of future results. Exercise caution, manage risk diligently, and consider the advice of financial experts when using this script or any trading strategy.
SuperTrend AI (Clustering) [LuxAlgo]The SuperTrend AI indicator is a novel take on bridging the gap between the K-means clustering machine learning method & technical indicators. In this case, we apply K-Means clustering to the famous SuperTrend indicator.
🔶 USAGE
Users can interpret the SuperTrend AI trailing stop similarly to the regular SuperTrend indicator. Using higher minimum/maximum factors will return longer-term signals.
The displayed performance metrics displayed on each signal allow for a deeper interpretation of the indicator. Whereas higher values could indicate a higher potential for the market to be heading in the direction of the trend when compared to signals with lower values such as 1 or 0 potentially indicating retracements.
In the image above, we can notice more clear examples of the performance metrics on signals indicating trends, however, these performance metrics cannot perform or predict every signal reliably.
We can see in the image above that the trailing stop and its adaptive moving average can also act as support & resistance. Using higher values of the performance memory setting allows users to obtain a longer-term adaptive moving average of the returned trailing stop.
🔶 DETAILS
🔹 K-Means Clustering
When observing data points within a specific space, we can sometimes observe that some are closer to each other, forming groups, or "Clusters". At first sight, identifying those clusters and finding their associated data points can seem easy but doing so mathematically can be more challenging. This is where cluster analysis comes into play, where we seek to group data points into various clusters such that data points within one cluster are closer to each other. This is a common branch of AI/machine learning.
Various methods exist to find clusters within data, with the one used in this script being K-Means Clustering , a simple iterative unsupervised clustering method that finds a user-set amount of clusters.
A naive form of the K-Means algorithm would perform the following steps in order to find K clusters:
(1) Determine the amount (K) of clusters to detect.
(2) Initiate our K centroids (cluster centers) with random values.
(3) Loop over the data points, and determine which is the closest centroid from each data point, then associate that data point with the centroid.
(4) Update centroids by taking the average of the data points associated with a specific centroid.
Repeat steps 3 to 4 until convergence, that is until the centroids no longer change.
To explain how K-Means works graphically let's take the example of a one-dimensional dataset (which is the dimension used in our script) with two apparent clusters:
This is of course a simple scenario, as K will generally be higher, as well the amount of data points. Do note that this method can be very sensitive to the initialization of the centroids, this is why it is generally run multiple times, keeping the run returning the best centroids.
🔹 Adaptive SuperTrend Factor Using K-Means
The proposed indicator rationale is based on the following hypothesis:
Given multiple instances of an indicator using different settings, the optimal setting choice at time t is given by the best-performing instance with setting s(t) .
Performing the calculation of the indicator using the best setting at time t would return an indicator whose characteristics adapt based on its performance. However, what if the setting of the best-performing instance and second best-performing instance of the indicator have a high degree of disparity without a high difference in performance?
Even though this specific case is rare its however not uncommon to see that performance can be similar for a group of specific settings (this could be observed in a parameter optimization heatmap), then filtering out desirable settings to only use the best-performing one can seem too strict. We can as such reformulate our first hypothesis:
Given multiple instances of an indicator using different settings, an optimal setting choice at time t is given by the average of the best-performing instances with settings s(t) .
Finding this group of best-performing instances could be done using the previously described K-Means clustering method, assuming three groups of interest (K = 3) defined as worst performing, average performing, and best performing.
We first obtain an analog of performance P(t, factor) described as:
P(t, factor) = P(t-1, factor) + α * (∆C(t) × S(t-1, factor) - P(t-1, factor))
where 1 > α > 0, which is the performance memory determining the degree to which older inputs affect the current output. C(t) is the closing price, and S(t, factor) is the SuperTrend signal generating function with multiplicative factor factor .
We run this performance function for multiple factor settings and perform K-Means clustering on the multiple obtained performances to obtain the best-performing cluster. We initiate our centroids using quartiles of the obtained performances for faster centroids convergence.
The average of the factors associated with the best-performing cluster is then used to obtain the final factor setting, which is used to compute the final SuperTrend output.
Do note that we give the liberty for the user to get the final factor from the best, average, or worst cluster for experimental purposes.
🔶 SETTINGS
ATR Length: ATR period used for the calculation of the SuperTrends.
Factor Range: Determine the minimum and maximum factor values for the calculation of the SuperTrends.
Step: Increments of the factor range.
Performance Memory: Determine the degree to which older inputs affect the current output, with higher values returning longer-term performance measurements.
From Cluster: Determine which cluster is used to obtain the final factor.
🔹 Optimization
This group of settings affects the runtime performances of the script.
Maximum Iteration Steps: Maximum number of iterations allowed for finding centroids. Excessively low values can return a better script load time but poor clustering.
Historical Bars Calculation: Calculation window of the script (in bars).
Elliott Wave with Supertrend Exit - Strategy [presentTrading]## Introduction and How it is Different
The Elliott Wave with Supertrend Exit provides automated detection and validation of Elliott Wave patterns for algorithmic trading. It is designed to objectively identify high-probability wave formations and signal entries based on confirmed impulsive and corrective patterns.
* The Elliott part is mostly referenced from Elliott Wave by @LuxAlgo
Key advantages compared to discretionary Elliott Wave analysis:
- Wave Labeling and Counting: The strategy programmatically identifies swing pivot highs/lows with the Zigzag indicator and analyzes the waves between them. It labels the potential impulsive and corrective patterns as they form. This removes the subjectivity of manual wave counting.
- Pattern Validation: A rules-based engine confirms valid impulsive and corrective patterns by checking relative size relationships and fib ratios. Only confirmed wave counts are plotted and traded.
- Objective Entry Signals: Trades are entered systematically on the start of new impulsive waves in the direction of the trend. Pattern failures invalidate setups and stop out positions.
- Automated Trade Management: The strategy defines specific rules for profit targets at fib extensions, trailing stops at swing points, and exits on Supertrend reversals. This automates the entire trade lifecycle.
- Adaptability: The waveform recognition engine can be tuned by adjusting parameters like Zigzag depth and Supertrend settings. It adapts to evolving market conditions.
ETH 1hr chart
In summary, the strategy brings automation, objectivity and adaptability to Elliott Wave trading - removing subjective interpretation errors and emotional trading biases. It implements a rules-based, algorithmic approach for systematically trading Elliott Wave patterns across markets and timeframes.
## Trading Logic and Rules
The strategy follows specific trading rules based on the detected and validated Elliott Wave patterns.
Entry Rules
- Long entry when a new impulsive bullish (5-wave) pattern forms
- Short entry when a new impulsive bearish (5-wave) pattern forms
The key is entering on the start of a new potential trend wave rather than chasing.
Exit Rules
- Invalidation of wave pattern stops out the trade
- Close long trades on Supertrend downturn
- Close short trades on Supertrend upturn
- Use a stop loss of 10% of entry price (configurable)
Trade Management
- Scale out partial profits at Fibonacci levels
- Move stop to breakeven when price reaches 1.618 extension
- Trail stops below key swing points
- Target exits at next Fibonacci projection level
Risk Management
- Use stop losses on all trades
- Trade only highest probability setups
- Size positions according to chart timeframe
- Avoid overtrading when no clear patterns emerge
## Strategy - How it Works
The core logic follows these steps:
1. Find swing highs/lows with Zigzag indicator
2. Analyze pivot points to detect impulsive 5-wave patterns:
- Waves 1, 3, and 5 should not overlap
- Waves 3 and 5 must be longer than wave 1
- Confirm relative size relationships between waves
3. Validate corrective 3-wave patterns:
- Look for overlapping, choppy waves that retrace the prior impulsive wave
4. Plot validated waves and Fibonacci retracement levels
5. Signal entries when a new impulsive wave pattern forms
6. Manage exits based on pattern failures and Supertrend reversals
Impulsive Wave Validation
The strategy checks relative size relationships to confirm valid impulsive waves.
For uptrends, it ensures:
```
Copy code- Wave 3 is longer than wave 1
- Wave 5 is longer than wave 2
- Waves do not overlap
```
Corrective Wave Validation
The strategy identifies overlapping corrective patterns that retrace the prior impulsive wave within Fibonacci levels.
Pattern Failure Invalidation
If waves fail validation tests, the strategy invalidates the pattern and stops signaling trades.
## Trade Direction
The strategy detects impulsive and corrective patterns in both uptrends and downtrends. Entries are signaled in the direction of the validated wave pattern.
## Usage
- Use on charts showing clear Elliott Wave patterns
- Start with daily or weekly timeframes to gauge overall trend
- Optimize Zigzag and Supertrend settings as needed
- Consider combining with other indicators for confirmation
## Default Settings
- Zigzag Length: 4 bars
- Supertrend Length: 10 bars
- Supertrend Multiplier: 3
- Stop Loss: 10% of entry price
- Trading Direction: Both
Pullback AnalyzerPullback Analyzer - a trailing stop helper.
This indicator measures the biggest pullback encountered during an up or down move.
You can use the reported percentages to fine-tune your trailing stop.
The reporting is very precise: On higher timeframes, the pullback size can sometimes not be determined exactly from the candles.
In this case, the script displays a lower and upper bound for this number.
I suggest that you use the upper bound as your trailing stop callback rate (plus some safety margin if you like).
The size of the move itself is always reported as a lower bound.
The biggest pullback within each move is marked with a gray dotted line.
There is only one parameter, "lookback"' (or lookback limit), which determines how many bars a single move can comprise. A value of 50 was found to be a nice default. If you lower the lookback, long moves will be split up into multiple moves, each being at or below the lookback limit. Conversely, you can capture longer moves in one piece by raising the lookback limit.
The algorithm automatically ignores small moves and trading ranges near a bigger move. (We may add a parameter to control this behavior more precisely in the future.)
How the algorithm works
There is a central class called MoveFinder which scans the candle feed for the biggest possible move in a certain direction (up or down).
Two instances of this class are used, one for each direction, to find the biggest next up and down move simultaneously (upFinder and downFinder).
Additionally, each of these main MoveFinders contains two more MoveFinders. These are used to find pullbacks within the move. (This comes from the observation that finding a pullback is fundamentally the exact same operation as finding a move, just with opposing direction and limited to the time between the move's beginning and end.)
Why two nested MoveFinders per parent (for a total of 6 in the program)? Well, one of them runs in "lower bound" and one runs in "upper bound" mode, so we can print the detected pullback size as an exact interval (lower bound <= real pullback <= upper bound). I am a mathematician. I like precision.
Moves as well as pullbacks that have been found are stored as instances of class Move which simply stores start and end bar index as well as start and end price.
Turtle Soup IndicatorTurtle Soup Indicator plots a shape when we have a 20-period high or 20-period low.
Turtle Soup Setup
The Turtle Soup setup was published in the book Street Smarts by Laurence A Connors and Linda Raschke. You can learn about it there. It is a great setup for false breakouts or breakdowns in the group failure tests.
Going long
1) We have a new 20-period low
2) that must have occured at least four trading sessions earlier <- this is very important
Then we place a buy stop above 5-10 ticks or 5 to 10 cents above the previous 20-period low.
If filled immediately place a good til cancelled sell stop one tick or one cent below todays low.
Turtle Soup Plus One
Similar to above but occurs one day later. It should close at/below previous 20-period low.
Buy stop at earlier 20 day low. Cancel fi not filled on day 2.
Take partials within 2-6 bars on this one and trail stop rest of position.
Going short
Reverse
Time frames
Works on all timeframes. Only adjust stoplosses accordingly to chosen timeframe.
Settings
You can change the color, shape and placement of the indicator shape. I actually prefer a grey color for both highs and lows as the color actually doesn't add much information. The placement says it all but it is up to you to change this as you like.
Strategy DesignerHello traders.
Thanks to the tool I have published, everyone who knows or does not know coding will be able to create strategies and see the results instantly on the screen. Yes it looks very nice :)
What does this script do?
Thanks to this tool, even if you don't know any coding, you will be able to create your own strategies. You can add and remove indicators.
Entrance
The first thing you need to do is to set a strategy in your mind.
Then you need to adjust the settings of the indicators installed in the system. Please set the indicators first, because later they are forgotten.
The screen for entering the parameters of the indicators will be as follows.
After entering the parameters there is an important part . In this section, we can adjust the strategy settings.
First we choose between which dates we want the strategy to run. We then choose whether we want the strategy results to be displayed in a table or not.
We choose how the Terms should be linked together. For example, if you have a condition that is expected to produce more than one receive signal, select whether these conditions are connected to each other with and or with the connector.
In this way, you can determine whether all or any of the rules in your strategy should apply.
Next, we choose whether our strategy will work in the spot market or in a bidirectional market. Yes, you can design a strategy for both spot and bidirectional trades :)
At the bottom of the above image, we see a screen where we can adjust the stop level and tp level. As a standard, adjustments are made according to the percentage level you enter. However, if you remove the tick next to the percent sign, the previous stop level and the next profit level are determined as much as the value you entered.
At the bottom is the trailing stop. When you open the trailing stop, the trailing stop becomes active in your strategy.
Very important, when the trailing stop and the stop are active at the same time, the trailing stop value is valid.
It's time to design our strategy. Each chapter that begins with an exclamation point is a separate fiction.
If you do not mark the Active button, that condition will not be included in the calculation.
Direction = It is the direction for which the fiction in this region is valid.
We came to the indicator setting screen. Here, there is a screen where we can select two different indicators on the right and left.
We choose the first indicator starting with 1.
Then we choose from the middle region how we want these two indicators to interact.
We choose our second indicator from the place starting with 2.
If you want an indicator to interact with any value, tick the box where it says Value and fill in the value in the blank. When Value is ticked, the second indicator does not work.
LowFinder_PyraMider_V2This strategy is a result of an exploration to experiment with other ways to detect lows / dips in the price movement, to try out alternative ways to exit and stop positions and a dive into risk management. It uses a combination of different indicators to detect and filter the potential lows and opens multiple positions to spread the risk and opportunities for unrealized losses or profits. This script combines code developed by fellow Tradingview community_members.
LowFinder
The lows in the price movement are detected by the Low finder script by RafaelZioni . It finds the potential lows based on the difference between RSI and EMA RSI. The MTF RSI formula is part of the MTFindicators library developed by Peter_O and is integrated in the Low finder code to give the option to use the RSI of higher timeframes. The sensitivity of the LowFinder is controlled by the MA length. When potential lows are detected, a Moving Average, a MTF Stochastic (based the the MTFindiicators by Peter_O) and the average price level filter out the weak lows. In the settings the minimal percentage needed for a low to be detected below the average price can be specified.
Order Sizing and Pyramiding
Pyramiding, or spreading multiple positions, is at the heart of this strategy and what makes it so powerful. The order size is calculated based on the max number of orders and portfolio percentage specified in the input settings. There are two order size modes. The ‘base’ mode uses the same base quantity for each order it opens, the ‘multiply’ mode multiplies the quantity with each order number. For example, when Long 3 is opened, the quantity is multiplied by 3. So, the more orders the bigger the consecutive order sizes. When using ‘multiply’ mode the sizes of the first orders are considerably lower to make up for the later bigger order sizes. There is an option to manually set a fixed order size but use this with caution as it bypasses all the risk calculations.
Stop Level, Take Profit, Trailing Stop
The one indicator that controls the exits is the Stop Level. When close crosses over the Stop Level, the complete position is closed and all orders are exited. The Stop Level is calculated based on the highest high given a specified candle lookback (settings). There is an option to deviate above this level with a specified percentage to tweak for better results. You can activate a Take Profit / Trailing Stop. When activated and close crosses the specified percentage, the Stop Level logic changes to a trailing stop to gain more profits. Another option is to use the percentage as a take profit, either when the stop level crosses over the take profit or close. With this option active, you can make this strategy more conservative. It is active by default.
And finally there is an option to Take Profit per open order. If hit, the separate orders close. In the current settings this option is not used as the percentage is 10%.
Stop Loss
I published an earlier version of this script a couple of weeks ago, but it got hidden by the moderators. Looking back, it makes sense because I didn’t pay any attention to risk management and save order sizing. This resulted in unrealistic results. So, in this script update I added a Stop Loss option. There are two modes. The ‘average price’ mode calculates the stop loss level based on a given percentage below the average price of the total position. The ‘equity’ mode calculates the stop loss level based on a given percentage of your equity you want to lose. By default, the ‘equity’ mode is active. By tweaking the percentage of the portfolio size and the stop loss equity mode, you can achieve a quite low risk strategy set up.
Variables in comments
To sent alerts to my exchange I use a webhook server. This works with a sending the information in the form of a comment. To be able to send messages with different quantities, a variable is added to the comment. This makes it possible to open different positions on the exchange with increasing quantities. To test this the quantities are printed in the comment and the quantities are switched off in the style settings.
This code is a result of a study and not intended for use as a worked out and full functioning strategy. Use it at your own risk. To make the code understandable for users that are not so much introduced into pine script (like me), every step in the code is commented to explain what it does. Hopefully it helps.
Enjoy!
Interactive SAR Stop-Loss [TANHEF]This indicator is "Interactive" which means some inputs can are manually added through the first click after adding the indicator to the chart (SAR Trailing Stop-loss start point).
Unlike the normal Parabolic SAR, this indicator allows for the modification of the start point of the Parabolic SAR’s first bar calculation. Normally, the Parabolic SAR automatically has a start point after the first bar of an asset’s historical price that will then switch between trailing above and below price respectively. It must be noted that due to how the first position of the Parabolic SAR is calculated, on occasion the Parabolic SAR will immediately flip on the next bar to the opposite side relative to price that it was just located. Modifying the setting “⭐Initial Interactive SAR Position Source”, then selecting either 'Clicked' or 'ATR' level as the vertical start position will prevent this. See images below for more explanation.
Why use a trailing stop-loss?
A trailing stop-loss provides an exit when price moves against you but also enables you to move the exit point further into profit when price is moving in the desired direction of a trade. The Parabolic SAR ( stop and reverse ) which is used to determine price direction as well as when price direction is changing, is very effective at functioning as a trailing stop loss.
Indicator Explanation
Initially when this indicator is added to the chart, you will be prompted to select where to begin the SAR Trailing Stop-loss.
For a long stop-loss, select below price.
For a short stop-loss, select above price.
After this indicator is placed, it can be modified via dragging or from within the settings by modifying the time and the price input. Or simply re-add the indicator to the chart. Another option is to have this Parabolic SAR begin directly on the price that was initially ‘Clicked’ or the ‘ATR’ level, which requires selecting the option in settings labeled “⭐Initial Interactive SAR Position Source”
The SAR Stop Loss plotted. Note that the calculation that occurs on this first bar of the ‘Interactive SAR’ is as if the prior bar was the oldest historical bar of the asset. Due to the SAR’s calculations, if the ‘Normal SAR’ were to also flip sides over to the position that has been manually set for the ‘Interactive SAR’, they won’t necessarily have the same result.
An optional fixed profit target can be added within the settings. This profit target will only actively be plotted when the SAR Trailing Stop-loss has not be hit yet or until the profit target has been hit.
Here shows that the profit target was hit, then later on the SAR Trailing Stop-loss was hit.
Note, trailing stop-loss will continue to be plotted until it has been hit regardless of the profit target being hit or not.
Here is an example of when the Parabolic SAR will immediately flip on the next bar to the opposite side relative to price that it was just first located. This is due to how the Parabolic SAR is calculated and will also occur with the traditional Parabolic SAR that is not interactively (manually) given a start location. To prevent this, either relocate this time in which this SAR beings or consider modifying the SAR’s (start, increment, max) settings specifically.
Here instead of using the SAR’s calculation for an initial bar, the ‘ATR’ was selected as the start point within the setting “⭐Initial Interactive SAR Position Source”.
Alerts
1. 'Check' alerts to use within indicator settings (trailing stop hit and/or profit target hit).
2. Select 'Create Alert'
3. Set the condition to 'Interactive SAR''
4. Select create.
Moving Average - fade when crossed [cajole]This indicator simply provides a moving average (SMA, EMA, etc. can be selected) which hides itself when touched by the price.
Two potential uses:
Set the growth rate to be slow, to highlight only very rapid moves on a chart.
Use the default settings and change the averaging period until the MA line remains bright. This MA can then act as a good trailing stop for the specific security.
TradingView does not remember indicator settings for specific charts. Consider adding a text label to your chart after you identify the ideal trailing stop. Similar trailing-stop methods are recommended by Kristjan Qullamagie is identical to Jesse Stine's "magic line" concept .
Interactive ATR Stop-Loss [TANHEF]This indicator is "Interactive" which means some inputs can are manually added through the first click after adding the indicator to the chart (ATR Trailing Stop-loss start point). See images below for more explanation.
Why use a trailing stop-loss?
A trailing stop-loss provides an exit when price moves against you but also enables you to move the exit point further into profit when price is moving in the desired direction of a trade. The ATR (Average True Range) which is used to measure volatility, is very effective at functioning as a trailing stop loss.
Indicator Explanation
Initially when this indicator is added to the chart, you will be prompted to select where to begin the ATR Trailing Stop-loss.
For a long stop-loss, select below price.
For a short stop-loss, select above price.
After this indicator is placed, it can be modified via dragging or from within the settings by modifying the time and the price input. Or simply re-add the indicator to the chart.
The ATR Stop Loss plotted. Note that the trailing value that is considered as the stop loss value is the value of the ATR from the prior candle. The settings for the ATR calculation can be modified within the settings.
An optional fixed profit target can be added within the settings. This profit target will only actively be plotted when the ATR Trailing Stop-loss has not be hit hit yet or until the profit target has been hit.
Here shows that the profit target was hit, then later on the ATR Trailing Stop-loss was hit.
Note, trailing stop-loss will continue to be plotted until it has been hit regardless of the profit target being hit or not.
Alerts
1. 'Check' alerts to use within indicator settings (trailing stop hit and/or profit target hit).
2. Select 'Create Alert'
3. Set the condition to 'Interactive ATR''
4. Select create.
R19 STRATEGYHello again.
Let me introduce you R19 Strategy I wrote for mostly BTC long/short signals
This is an upgrated version of STRATEGY R18 F BTC strategy.
I checked this strategy on different timeframes and different assest and found it very usefull for BTC 1 Hour and 5 minutes chart.
Strategy is basically takes BTC/USDT as a main indicator, so you can apply this strategy to all cryptocurrencies as they mostly acts accordingly with BTC itself (Of course you can change main indicator to different assets if you think that there is a positive corelation with. i.e. for BTC signals you can sellect DXY index for main indicator to act for BTC long/short signals)
Default variables of the inticator is calibrated to BTC/USDT 5 minute chart. I gained above %77 success.
Strategy simply uses, ADX, MACD, SMA, Fibo, RSI combination and opens positions accordingly. Timeframe variable is very important that, strategy decides according the timeframe you've sellected but acts within the timeframe in the chart. For example, if you're on the 5 minutes chart, but you've selected 1 hour for the time frame variable, strategy looks for 1 hour MACD crossover for opening a position, but this happens in 5 minutes candle, It acts quickly and opens the position.
Strategy also uses a trailing stop loss feature. You can determine max stoploss, at which point trailing starts and at which distance trailing follows. The green and red lines will show your stoploss levels according to the position strategy enters (green for long, red for short stop loss levels). When price exceeds to the certaing levels of success, stop loss goes with the profitable price (this means, when strategy opens a position, you can put your stop loss to the green/red line in actual trading)
You can fine tune strategy to all assets.
Please write down your comments if you get more successfull about different time zones and different assets. And please tell me your fine tuning levels of this strategy as well.
See you all.
EMA Cross CloudSimple ema cross trading alerts, completely customizable fast and slow crossovers with rendered cloud.
This cross indicator attempts to filter counter trend trades by added additional ema market and if crossunder/over occurs opposite of ema market the cloud will turn gray, otherwise if it's with the overall trend then red/green.
The last ema is a trailing stop guideline that is rendered with yellow crosses, could also utilize other stops such as the top or bottom of the cloud.
Alerts are baked in for ema crosses, trend breaks into stops.
Jurik-Filtered, Gann HiLo Activator [Loxx]Jurik-Filtered, Gann HiLo Activator is a Gann HiLo activator that has been smoothed using Jurik Filtering to reduce noise and better identify trending markets.
What is Gann HiLo
The HiLo Activator study is a trend-following indicator introduced by Robert Krausz as part of the Gann Swing trading strategy. In addition to indicating the current trend direction, this can be used as both entry signal and trailing stop.
Here is how the HiLo Activator is calculated:
1. The system calculates the moving averages of the high and low prices over the last several candles. By default, the average is calculated using the last three candles.
2. If the close price falls below the average low or rises above the average high, the system plots the opposite moving average. For example, if the price crosses above the average high, the system will plot the average low. If the price crosses below the average low afterward, the system will stop plotting the average low and will start plotting the average high, and so forth.
The plot of the HiLo Activator thus consists of sections on the top and bottom of the price plot. The sections on the bottom signify bullish trending conditions. Vice versa, those on the top signify the bearish conditions.
What is Jurik Volty used in the Juirk Filter?
One of the lesser known qualities of Juirk smoothing is that the Jurik smoothing process is adaptive. "Jurik Volty" (a sort of market volatility ) is what makes Jurik smoothing adaptive. The Jurik Volty calculation can be used as both a standalone indicator and to smooth other indicators that you wish to make adaptive.
What is the Jurik Moving Average?
Have you noticed how moving averages add some lag (delay) to your signals? ... especially when price gaps up or down in a big move, and you are waiting for your moving average to catch up? Wait no more! JMA eliminates this problem forever and gives you the best of both worlds: low lag and smooth lines.
Ideally, you would like a filtered signal to be both smooth and lag-free. Lag causes delays in your trades, and increasing lag in your indicators typically result in lower profits. In other words, late comers get what's left on the table after the feast has already begun.
Included
-Toggle bar color on/off
VXD Cloud EditionVXD Cloud Edition.
to overcome sideways market conditions this cloud configured for low timeframe.
every TA is same as VXD Supercycle but show as cloud.
Symbols on chart show Premium and Discount Prices
X-Cross = Engulfing Candle with weak volume .
O-circle - Engulfing Candle with strong volume .
Pivot point and Rejected Block
Pivot show last High and low of a price in past bars
Rejected Block show when that High or Low price are important level to determined if it's Hidden Divergence or Divergence (with RSI)
Setting
Momentum: RSI = 25 , RSI MA = 14
Trend: Rolling VWAP and ATR and Subhag (Everthing show as a cloud)
Trailing STOP: ATR 12 x 2.4
Highlight Bars color when volume is above SMA 6
SMA200 act as TP Line
Risk:Reward Calculation
if Buy your Stoploss will be previous Pivot low
if Sell your Stoploss will be previous Pivot high
and TP line will be calculated form there, then show in Orange color line
Buy condition : Close is above Cloud and close above pivot high
Sell condition : Close is below Cloud and close below pivot low
Trip : add this to alerts setting.
Order {{strategy.order.action}} filled on {{ticker}} @ {{strategy.order.price}} {{strategy.order.alert_message}}.
AlphaTrendAlphaTrend is a brand new indicator which I've personally derived from Trend Magic and still developing:
In Magic Trend we had some problems, Alpha Trend tries to solve those problems such as:
1-To minimize stop losses and overcome sideways market conditions.
2-To have more accurate BUY/SELL signals during trending market conditions.
3- To have significant support and resistance levels.
4- To bring together indicators from different categories that are compatible with each other and make a meaningful combination regarding momentum, trend, volatility, volume and trailing stop loss.
according to those purposes Alpha Trend:
1- Acts like a dead indicator like its ancestor Magic Trendin sideways market conditions and doesn't give many false signals.
2- With another line with 2 bars offsetted off the original one Alpha Trend have BUY and SELL signals from their crossovers.
BUY / LONG when Alpha Trend line crosses above its 2 bars offsetted line and there would be a green filling between them
SELL / SHORT when Alpha Trend line crosses below its 2 bars offsetted line and filling would be red then.
3- Alpha Trend lines
-act as support levels when an uptrend occurs trailing 1*ATR (default coefficient) distance from bar's low values
-conversely act as resistancelevels when a downtrend occurs trailing 1*ATR (default coefficient) distance from bar's high values
and acting as trailing stop losses
the more Alpha Trend lines straighter the more supports and resistances become stronger.
4- Trend Magic has CCI in calculation
Alpha Trend has MFI as momentum, but when there's no volume data MFI has 0 values, so there's abutton to change calculation considering RSI after checking the relevant box to overcome this problem when there is no volume data in that chart.
Momentum: RSI and MFI
Trend: Magic Trend
Volatility: ATR,
Trailing STOP: ATR TRAILING STOP
Volume: MFI
Alpha trend is really a combination of different types...
default values:
coefficient: 1 which is the factor of trailing ATR value
common period: 14 which is the length of ATR MFI and RSI
Wish you all use AlphaTrend in profitable trades.
Kıvanç Özbilgiç
Trend Following with Donchian Channels and MACDThis is a trend following system based on the Donchian Channels. Instead of using a simple moving average crossover, this system uses the MACD as the trendfilter:
Long positions:
* Price makes a new 50 day high,
* The MACD-line crosses above or is above the Signal-line.
* Both the MACD and the Signal-lines are above the zero-line.
Short positions:
* Price makes a new 50 day low,
* The MACD-line crosses below or is below the Signal-line.
* Both the MACD and the Signal-lines are below the zero-line.
Stoploss:
The initial and the trailing stoploss are 4 ATRs away from the price.
CCI45/SMA50 indy for 30 min SP500SPCFD:SPX
The script determines entry points using 45 period CCI and 50 period SMA.
Long condition: When CCI crosses up 150 treshold while price above 50 period SMA
Short condition: When CCI crosses down -150 treshold while price below 50 period SMA
Trades are executed above/below 1 point of high/low for long/short positions. Stops are just 1 point below/above of SMA. After 4 points of profit stops should be tightened. If you do not plan to hold the position for a long time, it can produce quick profit within 5-6 bars namely 2.5-3 hour. Otherwise you can manage the trade using SMA as trailing stop. This can be treated as a strategy of scalping which turns out a trend trading eventually if conditions good.
Have a nice trading
[fareid] Quick Backtest Framework█ OVERVIEW
This Framework allows Pine Coders to quickly code Study() based signal/strategy and validate its viability before proceed to code with more advance/complex customized rules for entry, exit, trailstop, risk management etc..
This is somewhat an upgraded version of my earlier personal template with different strategy used, cleaner code
and additional features.
█ USE CASES
- You have an idea for trade signal and need a quick way to verify its potential before writing lengthy/complicated code
- You found a study script for trading signal in public library and want to validate it profitability with minimum effort before including it in your trading playbook
█ FEATURES
- Alert: Ready to use alert function based on signals from your custom indicator.
- Visual Backtest: Auto-plot entry, stop-loss and take profit for simple strategy performance analysis
- Backtest Statistic: Provide basic key metrics based on backtest strategy
- BTE External Signal Protocol: Ready to use code that will supply required state to PineCoders Backtesting & Trading Engine if you wish to have more advance and sophisticated backtesting engine
Notes: All of the above features have On/Off toggle
█ Description & How To Use
This Framework consist of 5 Modules but you only need to edit the first 2 Modules:
Module1: Indicator
Module2: Framework Input Protocol
Module3: Alert
Module4: Backtest
Module5: Backtest & Trading Engine
Tips: The source-code includes collapsible block by module for easy navigating
Module1: Indicator:
-----------------------------------------------------------------------------------
Main Module. Place custom indicator input parameter/calculation/indicator plotting here
Sample Strategy: Double MACD Crossover
MACD Signal: 1st MACD Cross above signal line indicate Buy Signal
1st MACD Cross below signal line indicate Sell Signal
MACD Filter: 2nd MACD is above 0 line indicate Uptrend
2nd MACD is below 0 line indicate Downtrend
Module2: Framework Input Protocol:
-----------------------------------------------------------------------------------
Use this module to connect main indicator/signal calculated in Module1 to the rest of the framework's module
4 variables needed to be defined here:
1. Uptrend
2. Dntrend
3. BuySignal
4. SellSignal
i'm not sure how to place a code snippet here to show you example so in the source code i already put a comment in Module2 on which part u need to edit. I hope its pretty simple to use.
Module3: Alert Module Description:
-----------------------------------------------------------------------------------
As long as the variables in Module2 properly defined, the alert module is ready to use without any further modification.
Input:
Enable Alert --> Enable TV's alert and plot signal to chart
Alert Type --> Set to take Buy only, Sell only or Both alert
Module4: Backtest Module Description:
-----------------------------------------------------------------------------------
As long as the variables in Module2 properly defined, the backtest module is ready to use without any further modification.
Input:
Backtest Stat --> Enable Backtest Statistic Label
Backtest Visual --> Enable Backtest visual simulation
Backtest Type --> Set to take Buy only or Sell only or both
SL Type -->
ATR : Set SL in ATR times Multiplier below entry price
Fixed : Set SL in fixed point below entry point (in 'Dollar'). e.g. for Stocks -> 0.5 equals to 50cent while for EURUSD currency -> 0.005 equal to 50 pips
HiLo Bar: Set SL at highest/lowest wick of previous bar plus/minus Fixed point. e.g. EURUSD HiLo=3 and Fixed Point = 0.0005, buy trade will place SL 5 Pips below lowest of previous 3 bar
SL ATR Multi --> Set Lookback Period used for SL's ATR calculation
SL ATR Multi --> Set ATR Multiplier for SL
SL Fixed --> Set Fixed Level for SL
SL Bar --> Set Number of previous bar to check for SL placement
TP RR Ratio --> Set TP based on RR multiplier. e.g. 2 means TP level will be twice further from entry point compared to Entry-SL distance.
Notes: The point is for preliminary testing, so it only supports 1 trade at a time and no Trailing Stop
Module5: Backtest & Trading Engine Description:
-----------------------------------------------------------------------------------
As long as the variables in Module2 properly defined, the Pinecoders BTE module is ready to use without any further modification.
Input:
External Signal Protocol --> Set ESP State to send to "Backtesting & Trading Engine "
Signal With Filter --> Use this to send entry signal that already filtered by this study indicator (without stoploss level)
Signal Without Filter --> Use this to send raw entry signal that are NOT YET FILTERED by this study indicator (without stoploss level)
Signal and Stop With Filter --> Use this to send entry signal WITH StopLoss that already filtered by this study indicator (with stoploss level)
Signal and Stop Without Filter --> Use this to send raw entry signal WITH StopLoss that are NOT YET FILTERED by this study indicator (with stoploss level)
Notes: Backtesting & Trading Engine already have built-in Filter, Entries and Stop Level. e.g. Unselect all their filter state if only want to use custom filter and make sure send Signal with Filter (with or without SL level)
█ DISCLAIMER:
This framework main objective is to create my personal indicator template so that i just have to modify the indicator module for preliminary testing in future.
The sample strategy included are for educational purpose only. Use at your own risk
credit: LucF/PineCoders for a lot of his scripts that i use as a guide to complete this
Anti-Volume Stop LossFINALLY!
As everyone who tried to create, understand, or even find the Buff Pelz Dormeier Anti-volume stop-loss indicator knows that - it's not easy. Personally, I have partially, or perhaps completely figured out, the tips Buff had given in Investing with Volume Analysis book.
AVSL now is ready.
Please do some test and give me a feedback how it works in your trade strategy.
Anti-Volume stop loss - AVSL
from Investing with Volume Analysis book CHAPTER 20 • RISKY BUSINESS 253-256:
"It is important in any risk-management process to predetermine an objective decision point level (a stop loss) to exit, thereby protecting principal in case you are wrong. My objective sell point is determined by using a quantitative formula I refer to as Anti-Volume Stop Loss (AVSL). Having a quantitative, yet intelligent sell point eliminates the emotional struggles involved in deciding when to exit a position.
AVSL is a technical methodology that incorporates the concepts of support, volatility, and, most importantly, the inverse relationship between price and volume. The AVSL combines the concepts of the VPCI (Volume Price Confirmation Indicator) and John Bollinger’s Bollinger Bands to create a trailing stop loss.
AVSL = Lower Bollinger Band – (Price, Length, Standard Deviation)
Where:
Length = Round (3 + VPCI)
Price = Average (Lows × 1 / VPC × 1 / VPR, Length)
Standard Deviation = 2 × (VPCI × VM)
One of the most difficult decisions is determining what one’s maximum loss threshold should be. Some say 2 percent; others say 20 percent. I believe the more volatile a security, the looser the stop should be. A nonvolatile security, such as Coca-Cola, might move 7 percent a year, while a volatile security such as Google might move 7 percent in a day. If you use a 7 percent stop for Coca-Cola, it might take a year to be stopped out while the security underperforms.
However, if you use 7 percent for Google, you can be stopped out intraday, not allowing the investment an opportunity to develop. By using the lower Bollinger Band of the securities lows, the AVSL considers each individual security’s own volatility. Thus, a volatile security would be granted more room of the stocks low while a stable security would have a tighter leash (see Figure 20.7).
The next important step is employing the price-volume relationship into the calculation. Volume gauges the power behind price moves. In accounting for this, when a security is in an uptrend and has positive volume characteristics, it is given more room. However, if the security exhibits contracting volume characteristics, then the stop is tightened. In this way, if a negative news event affects an unhealthy security, the stop is tighter, thus preserving more of your profits.
However, if the negative news event affects a security whose price-volume relationship is healthy, the stop has been loosened, avoiding the temporary whipsaw of an otherwise strong position. In these ways, AVSL lets the market decide when to exit your position.
AVSL tailors each security for support, volatility, and the pricevolume relationship based on an investor’s time frame as calculated from the chart data. For example, my portfolio positions are continually re-evaluated with this AVSL methodology, which yields the possibility of raising the decision point threshold periodically based on the time frame of my investment objective. With my short-term Giddy-up portfolios, I use daily chart data and seek to raise my maximum loss stop on a daily basis.
My intermediate ETF and stock positions are calculated off of weekly data and then re-evaluated weekly. With my longer term stock portfolios, the decision point is calculated off data revised monthly. This analytical approach that uses measurable facts over emotion or gut instincts allows me to maintain my objectivity. Thus objectivity, not emotion, informs my investment decisions."
How look mine AVSL:
Price component = low × 1/VPC × 1/VPR : for VPC > 1 and VPC < -1 | low × 1 × 1/VPR : for 1 > VPC > 0 | low × -1 × 1/VPR : for 0 > VPC > -1
AVSL Price = sma((low × 1/VPC × 1/VPR) , length) / 100
length = round : for VPCI > 0 | round [ absolute ] : for VPCI < 0 | 3 : for VPCI=0
Standard Deviation = mult × VPCI × VM)
AVSL = sma(Actual low price - AWSL Price + Standard Deviation, 26)
It's hard to say is it the same as in Buff Pelz Dormeier book, but I encourage you to modify the script for better results.
Percent Drop from Highest HighBuy and hold investors may decide to use trailing stops to protect profits and capital from market crashes, especially during bull markets.
The purpose of this indicator is to hep investors to identify a location to place them. The indicator plots the highest high from 'x' bars ago. It then plots a trailing stop loss 'y' percent below that line.
The indicator enables its users to input different 'x' and 'y' values to observe what they think works best for them in different markets.
Users might choose to pair the indicator with trend confirming indicators, such as moving average cross overs, to determine that the market is trending and not ranging.
There is no magic in this indicator, only maths. Like every indicator, it has no ability to predict anything. Just because the market is doing one thing now, it might do something different later. The past does not equal the present nor the future. Make your own decisions and be responsible for them.
All the best to you and your family.
