Papercuts Time Sampled Higher Timeframe EMA Without SecurityThis EMA uses a higher time sampled method instead of using security to gather higher timeframe data.
Its quite fast and worked well with the timeframes prescribed, up to 8hrs, after 8hrs, the formatting gets more complicated and i probably wouldn't use it anyway.
You can use this as a guide to avoid security and even f_security with this method.
NOTE: This includes the non repainting f_security call so that i woudl be able to check my results against what it does, thats not nessecary to keep at all.
There is some minor differences in data, but its so minor it doesnt bother me, though it would be interesting to know what the difference actually is. If anyone figures that out, leave a comment and let me know!
This is meant to be an example for others to build and learn and play with.. so enjoy!
Moving Averages
Z-Score Weighted Moving Averages
Indicator: Z-Score Weighted Moving Averages
Another way of calculating moving average
This indicator calculates two types of weighted moving averages (WMAs) based on z-scores and inverse z-scores. The indicator's purpose is to provide traders with a unique perspective on price movements by assigning different weights to data points based on their deviations from the mean . The two types of WMAs generated are as follows:
Smoothed Weighted Moving Average (wma_smoothed):
Z-score is calculated as (price - SMA of price/(MAD*1.2533), where MAD is mean absolute deviation around the median).
Weights are assigned to each data point based on the inverse of (1 + absolute value of the z-scores). This emphasizes points closer to the mean and reduces the influence of extreme deviations.
The weighted moving average is computed using the calculated weights, giving more importance to data points with smaller z-scores and, therefore, points that are closer to the mean.
Dynamic Weighted Moving Average (wma_dynamic):
Z-scores are still calculated in the same way.
Weights are assigned based on the absolute value of the z-scores. This emphasizes data points with significant deviations from the mean, without considering the direction of deviation.
The weighted moving average is computed using these dynamic weights, giving more weight to data points that have larger absolute z-scores, irrespective of whether they are above or below the mean.
Moving Average Continuity [QuantVue]"Moving Average Continuity," is designed to compare the position of two Moving Averages (MAs) across multiple timeframes.
The user can select three timeframes and determine the length and type of both a fast and slow moving average.
The indicator will display a small table in a user selected location.
This table helps traders quickly determine if, for their selected timeframes, the faster moving average is trending above or below the slower moving average.
The “Moving Average Continuity” indicator can also send you three types of alerts;
1. All moving averages are aligned bullish
2. All moving averages are aligned bearish
3. Moving averages are mixed
Key Features:
1. Timeframes: The user can select up to three distinct timeframes to compare the moving averages.
2. Moving Average Inputs: For each MA, users can determine:
• Length of the MA
• Type of the MA - Options include EMA (Exponential Moving Average), SMA (Simple Moving Average), HMA (Hull Moving Average), WMA (Weighted Moving Average), and VWMA (Volume Weighted Moving Average).
3. Positioning: Users have the ability to adjust the table's positioning (top, middle, or bottom) and horizontal alignment (right, center, or left) on the chart overlay.
4. Runtime Error Prevention: The indicator will throw an error if the chart's timeframe exceeds the maximum selected timeframe, ensuring that comparisons are done correctly.
Give this indicator a BOOST and COMMENT your thoughts!
We hope you enjoy.
Cheers.
FIRST-HOUR TOOL V.1.8.08.23Three horizontal lines are drawn on the chart to represent session prices. These prices are calculated based on the user-specified session:
"FirstHour Session High" represents the highest price reached during the firsthour session.
"FirstHour Session Open" represents the opening price of the firsthour session
"FirstHour Session Low" represents the lowest price reached during the firsthour session.
These prices are respectively colored with light blue, light yellow, and light pink.
The chart background can change color based on whether the current time is within the specified session. If the current time is within the session, the background will be colored in semi-transparent aqua green. Otherwise, it will remain transparent.
Upward-pointing triangle markers are used to highlight points where the closing price crosses above (crossover) or below (crossunder) the session levels.
These markers appear below the corresponding bar.
They are colored based on the type of crossover:
Yellow for crossover above the "FirstHour High"
Red for crossover above the "FirstHour Open"
Green for crossover above the "FirstHour Low"
Alerts:
Alert messages are generated when crossovers or crossunders of the closing price relative to the session levels occur.
The alerts appear once per bar. Alerts are generated for the following events:
Crossover of the price above the "Session High" with the message "High First Hour Crossover."
Crossunder of the price below the "Session Open" with the message "Open First Hour Crossunder."
Crossunder of the price below the "Session Low" with the message "Low First Hour Crossunder."
Crossover of the price above the "Session Low" with the message "Low First Hour Crossover."
In summary, this indicator provides a visual representation of session prices and events, helping traders spot significant crossovers and crossunders relative to key price levels.
Author @tumiza999
White NoiseThe "White Noise" indicator is designed to visualize the dispersion of price movements around a moving average, providing insights into market noise and potential trend changes. It highlights periods of increased volatility or noise compared to the underlying trend.
Code Explanation:
Inputs:
mlen: Input for the length of the noise calculation.
hlen: Input for the length of the Hull moving average.
col_up: Input for the color of the up movement.
col_dn: Input for the color of the down movement.
Calculations:
ma: Calculate the simple moving average of the high, low, and close prices (hlc3) over the specified mlen period.
dist: Calculate the percentage distance between the hlc3 and the moving average ma, then scale it by 850. This quantifies the deviation from the moving average as a value.
sm: Smooth the calculated dist values using a weighted moving average (WMA) twice, with different weights, and subtract one from the other. This provides a smoothed representation of the dispersion.
Coloring:
col_wn: Determine the color of the bars based on whether dist is positive or negative and whether it's greater or less than the smoothed sm value. This creates color-coded columns indicating upward or downward movements with varying opacity.
col_switch: Define the color for the current trend state. It switches color when the smoothed sm crosses above or below its previous value, indicating potential trend changes.
col_switch2: Define the color for the horizontal line that separates the two trend states. It switches color based on the same crossover and crossunder conditions as col_switch.
Plots:
plot(dist): Plot the dispersion values as columns with color defined by col_wn.
plot(sm): Plot the smoothed dispersion line with a white color and thicker linewidth.
plot(sm ): Plot the previous smoothed dispersion value with a lighter white color to create a visual distinction.
Usage:
This indicator can help traders identify periods of increased market noise, visualize potential trend reversals, and assess the strength of price movements around the moving average. The colored columns and smoothed line offer insights into the ebb and flow of market sentiment, aiding in decision-making.
ps. This can be used as a long-term TPI component if you dabble in Modern Portfolio Theory (MPT)
Recommended for timeframes on the 1D or above:
AlpHay : ToolKitToolKit:
First Impressions for Securities; (like crime scene investigators) 🧐
Our first job is to understand "What did happen here?" (historically, like Price Ranges or Price Performances) 🤔
Secondly, we try to figure out "where are we now?" (like common indicators or Moving Averages) 🤔
Then "What was the chain of events?" (macro, local, fundamentals, shorts, etc.)
Note: There are a lot of useful scripts out there, but If you want to see my approach for "Fundamentals" or "Finra Short Report" scripts, have a look.
Now we have a Clue. 😎
Includes;
1. Daily Metrics (Price performance, Price Difference, Volume, Trade)
2. Historic Price Performances
3. Historic Price ranges
4. RSI and MACD (you can change) Indicators for four "Time Frame" (you can change also)
5. Moving Averages (also shows daily values on the chart)
* Easy to customize.
* You can be positioned where ever you need. (be careful about overlays)
* You can turn on/off tables for your daily usage.
* You can flip Horizontally for some of the tables.
* Always look at tooltips (mouse over for Averages etc.)
I hope you enjoy it.
Disclaimer and Warning!
* Do not forget this is my Interpolation of the data sets. You can't invest in relying on this indicator. This is just a visual representation of the data sets.
* Just be careful what you wish for. And search for anomalies.
// ToDO List.
* Pre/Post Market Price and Volume
MACD HIstgramMA signl CrossingThis indicator highlights points where the MACD's Signal and Simple Moving Average of Histogram cross as entry points.
By incorporating the Simple Moving Average of the Histogram, it aims to avoid false entries during MACD and Signal crosses when volatility is low.
However, since it employs the Simple Moving Average of the Histogram, the appearance of entry points is less frequent and lagging compared to the cross of MACD and Signal.
Trend Confirmation StrategyThe profitability and uniqueness of a trading strategy depend on various factors including market conditions, risk management, and the strategy's ability to capitalize on price movements. I'll describe the strategy provided and highlight its potential benefits and differences compared to other strategies:
Strategy Overview:
The provided strategy combines three technical indicators: Supertrend, MACD, and VWAP. It aims to identify potential entry and exit points by confirming trend direction and considering the proximity to the VWAP level. The strategy also incorporates stop-loss and take-profit mechanisms, as well as a trailing stop.
Unique Aspects and Potential Benefits:
Trend Confirmation: The strategy uses both Supertrend and MACD to confirm the trend direction. This dual confirmation can increase the likelihood of accurate trend identification and filter out false signals.
VWAP Confirmation: The strategy considers the proximity of the price to the VWAP level. This dynamic level can act as a support or resistance and provide additional context for entry decisions.
Adaptive Stop Loss: The strategy sets a stop-loss range, which helps provide some tolerance for minor price fluctuations. This adaptive approach considers market volatility and helps prevent premature stop-loss triggers.
Trailing Stop: The strategy incorporates a trailing stop mechanism to lock in profits as the trade moves in the desired direction. This can potentially enhance profitability during strong trends.
Partial Profit Booking: While not explicitly implemented in the provided code, you could consider booking partial profits when the MACD shows a crossover in the opposite direction. This aspect could help secure gains while still keeping exposure to potential further price movements.
Key Differences from Other Strategies:
Dual Indicator Confirmation: The combination of Supertrend and MACD for trend confirmation is a unique aspect of this strategy. It adds an extra layer of filtering to enhance the accuracy of entry signals.
Dynamic VWAP: Incorporating the VWAP level into the decision-making process adds a dynamic element to the strategy. VWAP is often used by institutional traders, and its inclusion can provide insights into the market sentiment.
Adaptive Stop Loss and Trailing: The strategy's use of an adaptive stop-loss range and a trailing stop can help manage risk and protect profits more effectively during changing market conditions.
Partial Profit Booking: The suggestion to consider partial profit booking upon MACD crossovers in the opposite direction is a practical approach to secure gains while staying in the trade.
Caution and Considerations:
Backtesting: Before deploying any strategy in real trading, it's crucial to thoroughly backtest it on historical data to understand its performance under various market conditions.
Risk Management: While the strategy has built-in risk management mechanisms, it's essential to carefully manage position sizes and overall portfolio risk.
Market Conditions: No strategy works well in all market conditions. It's important to be flexible and adjust the strategy or refrain from trading during particularly volatile or unpredictable periods.
Continuous Monitoring: Even though the strategy includes automated components, continuous monitoring of the trades and market conditions is necessary.
Adaptability: Markets can change over time. Traders need to be prepared to adapt the strategy as necessary to stay aligned with evolving market dynamics.
HighLowBox+220MAs[libHTF]HighLowBox+220MAs
This is a sample script of libHTF to use HTF values without request.security().
import nazomobile/libHTFwoRS/1
HTF candles are calculated internally using 'GMT+3' from current TF candles by libHTF .
To calcurate Higher TF candles, please display many past bars at first.
The advantage and disadvantage is that the data can be generated at the current TF granularity.
Although the signal can be displayed more sensitively, plots such as MAs are not smooth.
In this script, assigned ➊,➋,➌,➍ for htf1,htf2,htf3,htf4.
HTF candles
Draw candles for HTF1-4 on the right edge of the chart. 2 candles for each HTF.
They are updated with every current TF bar update.
Left edge of HTF candles is located at the x-postion latest bar_index + offset.
DMI HTF
ADX/+DI/DI arrows(8lines) are shown each timeframes range.
Current TF's is located at left side of the HighLowBox.
HTF's are located at HighLowBox of HTF candles.
The top of HighLowBox is 100, The bottom of HighLowBox is 0.
HighLowBox HTF
Enclose in a square high and low range in each timeframe.
Shows price range and duration of each box.
In current timeframe, shows Fibonacci Scale inside(23.6%, 38.2%, 50.0%, 61.8%, 76.4%)/outside of each box.
Outside(161.8%,261.8,361.8%) would be shown as next target, if break top/bottom of each box.
In HTF, shows Fibonacci Level of the current price at latest box only.
Boxes:
1 for current timeframe.
4 for higher timeframes.(Steps of timeframe: 5, 15, 60, 240, D, W, M, 3M, 6M, Y)
HighLowBox TrendLine
Draw TrendLine for each HighLow Range. TrendLine is drawn between high and return high(or low and return low) of each HighLowBox.
Style of TrendLine is same as each HighLowBox.
HighLowBox RSI
RSI Signals are shown at the bottom(RSI<=30) or the top(RSI>=70) of HighLowBox in each timeframe.
RSI Signal is color coded by RSI9 and RSI14 in each timeframe.(current TF: ●, HTF1-4: ➊➋➌➍)
In case of RSI<=30, Location: bottom of the HighLowBox
white: only RSI9 is <=30
aqua: RSI9&RSI14; <=30 and RSI9RSI14
green: only RSI14 <=30
In case of RSI>=70, Location: top of the HighLowBox
white: only RSI9 is >=70
yellow: RSI9&RSI14; >=70 and RSI9>RSI14
orange: RSI9&RSI14; >=70 and RSI9=70
blue/green and orange/red could be a oversold/overbought sign.
20/200 MAs
Shows 20 and 200 MAs in each TFs(tfChart and 4 Higher).
TFs:
current TF
HTF1-4
MAs:
20SMA
20EMA
200SMA
200EMA
Gaussian Average Rate Oscillator
Within the ALMA calculation, the Gaussian function is applied to each price data point within the specified window. The idea is to give more weight to data points that are closer to the center and reduce the weight for points that are farther away.
The strategy calculates and compares two different Rate of Change (ROC) indicators: one based on the Arnaud Legoux Moving Average (ALMA) and the other based on a smoothed Exponential Moving Average (EMA). The primary goal of this strategy is to identify potential buy and sell signals based on the relationship between these ROC indicators.
Here's how the strategy logic works
Calculating the ROC Indicators:
The script first calculates the ROC (Rate of Change) of the smoothed ALMA and the smoothed EMA. The smoothed ALMA is calculated using a specified window size and is then smoothed further with a specified smoothing period. The smoothed EMA is calculated using a specified EMA length and is also smoothed with the same smoothing period.
Comparing ROCs:
The script compares the calculated ROC values of the smoothed ALMA and smoothed EMA.
The color of the histogram bars representing the ROC of the smoothed ALMA depends on its relationship with the ROC of the smoothed EMA. Green indicates that the ROC of ALMA is higher, red indicates that it's lower, and black indicates equality.
Similarly, the color of the histogram bars representing the ROC of the smoothed EMA is determined based on its relationship with the ROC of the smoothed ALMA, they are simply inversed so that they match.
With the default color scheme, green bars indicate the Gaussian average is outperforming the EMA within the breadth and red bars mean it's underperforming. This is regardless of the rate of average price changes.
Generating Trade Signals:
Based on the comparison of the ROC values, the strategy identifies potential crossover points and trends. Buy signals could occur when the ROC of the smoothed ALMA crosses above the ROC of the smoothed EMA. Sell signals could occur when the ROC of the smoothed ALMA crosses below the ROC of the smoothed EMA.
Additional Information:
The script also plots a zero rate line at the zero level to provide a reference point for interpreting the ROC values.
In summary, the strategy attempts to capture potential buy and sell signals by analyzing the relationships between the ROC values of the smoothed ALMA and the smoothed EMA. These signals can provide insights into potential trends and momentum shifts in the price data.
Golden Transform The Golden Transform Oscillator contains multiple technical indicators and conditions for making buy and sell decisions. Here's a breakdown of its components and what it's trying to achieve:
Strategy Setup:
The GT is designed to be plotted on the chart without overlaying other indicators.
Rate of Change (ROC) Calculation:
The Rate of Change (ROC) indicator is calculated with a specified period ("Rate of Change Length").
The ROC measures the percentage change in price over the specified period.
Hull Modified TRIX Calculation:
The Hull Modified TRIX indicator is calculated with a specified period ("Hull TRIX Length").
The Hull MA (Moving Average) formula, a modified WMA, is used to calculate a modified TRIX indicator, which is a momentum oscillator.
Hull MA Calculation:
A Hull Moving Average (Hull MA) is calculated as an entry filter.
Fisher Transform Calculation:
The Fisher Transform indicator is calculated to serve as a preemptive exit filter.
It involves mathematical transformations of price data to create an oscillator that can help identify potential reversals. The Fisher Transform is further smoothed using a Hull Moving Average (HMA).
Conditions and Signals:
Long conditions are determined based on crossovers between ROC and TRIX, as well as price relative the the MA. Short conditions are inversed.
Exit Conditions:
Exit conditions are defined for both long and short positions.
For long positions, the strategy exits if ROC crosses under TRIX, or if the smoothed Fisher Transform crosses above a threshold and declines. Once again, short conditions are the inverse.
Visualization and Plotting:
The script uses background colors for entry and shapes for exits to highlight different levels and conditions for the ROC/TRIX correlation.
It plots the Fisher Transform values and a lag trigger on the chart.
Overall, this script is a complex algorithm that combines multiple technical indicators and conditions to generate trading signals and manage positions in the financial markets. It aims to identify potential entry and exit points based on the interplay of the mentioned indicators and conditions.
Ultimate Momentum OscillatorThe Ultimate Momentum Oscillator is a tool designed to help traders identify the current trend direction and the momentum of the prices.
This oscillator is composed of one histogram and one line, paired with the two overbought and the two oversold levels.
The histogram is a trend-based algorithm that allows the user to read the market bias with multiple trend lengths combined.
The line is a momentum-based formula that allows traders to identify potential reversal and the speed of the price.
This tool can be used to:
- Identify the current trend direction
- Identify the momentum of the price
- Identify oversold and overbought levels
Gaussian Detrended ReversionThis strategy, titled "Gaussian Detrended Reversion Strategy," aims to identify potential price reversals using the customized Gaussian Detrended Price Oscillator (GDPO) in combination with smoothed price cycles.
Key Elements of the Strategy:
GDPO Calculation: The strategy first calculates the Detrended Price Oscillator (DPO) by comparing the close price to an Exponential Moving Average (EMA) of a specified period. This calculation helps identify short-term price cycles by detrending the price data.
Gaussian Smoothing: The DPO values are then smoothed using the Arnaud Legoux Moving Average (ALMA), applying a Gaussian smoothing technique. This smoothed version of the DPO is intended to filter out noise and provide a clearer picture of price trends.
Entry and Exit Conditions: The strategy defines conditions for both long and short entry points as well as exit points. It looks for specific crossover events between the smoothed GDPO and its lagged version. The strategy enters a long position when the smoothed GDPO crosses above the lag and is negative, and exits the long position when the smoothed GDPO crosses below the lag or the zero line. Similarly, the strategy enters a short position when the smoothed GDPO crosses below the lag and is positive, and exits the short position when the smoothed GDPO crosses above the lag or the zero line.
Visualization: The smoothed GDPO and its lag are plotted on the chart using distinct colors. The zero line is also displayed as a reference point. Additionally, the chart background changes color when the strategy enters a long or short position. Cross markers are also plotted at the crossover points as exit cues.
Overall, this strategy aims to capture potential price reversals using the GDPO and Gaussian smoothing, with specific entry and exit conditions to guide trading decisions.
EMA X Oscillator
This indicator combines elements of the Exponential Moving Average (EMA) crossover and Rate of Change (ROC), generating a solid simple tool for technical analysis.
Overall, this script creates an oscillator by calculating the Rate of Change between two Exponential Moving Averages (Fast and Slow) based on the chosen smoothing methods and lengths. The oscillator helps identify potential trends. It offers customization options for the types of smoothing and other parameters, making it versatile for various strategies.
Custom EMA from X Days AgoThis is an indicator to plot the selected EMA value from X days ago on today's candle.
Or it will helps to plot the previous candle's EMA value on current candle.
LNL Trend SystemLNL Trend System is an ATR based day trading system specifically designed for intra-day traders and scalpers. The System works on any chart time frame & can be applied to any market. The study consist of two components - the Trend Line and the Stop Line. Trend System is based on a special ATR calculation that is achieved by combining the previous values of the 13 EMA in relation to the ATR which creates a line of deviations that visually look similar to the basic moving average but actually produce very different results ESPECIALLY in sideways market.
Trend Line:
Trend Line is a simple line which is basically a fast gauge represented by the 13 EMA that can change the color based on the current trend structure defined by multiple averages (8,13,21,34 EMAs). Trend Line is there to simply add the confluence for the current trend. Colors of the line are pretty much self-explanatory. Whenever the line turns red it states that the current structure is bearish. Vice versa for green line. Gray line represents neutral market structure.
Stop Line:
Stop Line is an ATR deviaton line with special calculation based on the previous bar ATRs and position of the price in relation to the current and previous values of 13 EMA. As already stated, this creates an ATR deviation marker either above or below the price that trails the price up or down until they touch. Whenever the price comes into the Stop Line it means it is making an ATR expansion move up or down .This touch will usually resolve into a reaction (a bounce) which provides trade opportunities.
Trend Bars:
When turned ON, Trend Bars can provide additional confulence of the current trend alongside with the Trend Line color. Trend Bars are based on the DMI and ADX indicators. Whenever the DMI is bearish and ADX is above 20 the candles paint themselfs red. And vice versa applies for the green candles and bullish DMI. Whenever the ADX falls below the 20, candles are netural (Gray) which means there is no real trend in place at the moment.
Trend Mode:
There are total of 5 different trend modes available. Each mode is visualizing different ATR settings which provides either aggressive or more conservative approach. The more tigher the mode, the more closer the distance between the price and the Stop Line. First two modes were designed for slower markets, whereas the "Loose" and "FOMC" modes are more suitable for products with high volatility.
Trend Modes:
1. Tight
Ideal for the slowest markets. Slowest market can be any market with unusually small average true range values or just simply a market that does have a personality of a "sleeper". Tight Mode can be also used for aggresive entries in the most ridiculous trends. Sometimes price will barely pullback to the Trend Line not even the Stop Line.
2. Normal
Normal Mode is the golden mean between the modes. "Normal" provides the ideal ATR lengths for the most used markets such as S&P Futures (ES) or SPY, AAPL and plenty of other highly popular stocks. More often than not, the length of this mode is respected considering there is no breaking news or high impact market event scheduled.
3. Loose
The "Loose" mode is basically a normal mode but a little bit more loose. This mode is useful whenever the ATRs jump higher than usual or during the days of highly anticipated news events. This mode is also better suited for more active markets such as NQ futures.
4. FOMC
The FOMC mode is called FOMC for a reason. This mode provides the maximum amount of wiggle room between the price and the Stop Line. This mode was designed for the extreme volatility, breaking news events or post-FOMC trading. If the market quiets down, this mode will not get the Stop Line touch as frequently as othete modes, thus it is not very useful to run this on markets with the average volatlity. Although never properly tested, perhaps the FOMC mode can find its value in the crypto market?
5. The Net
The net mode is basically a combination of all modes into one stop line system which creates "the net" effect. The Net provides the widest Stop Line zone which can be mainly appreciated by traders that like to use scale-in scale-out methods for their trading. Not to mention the visual side of the indicator which looks pretty great with the net mode on.
HTF (Higher Time Frame) Trend System:
The system also includes additional higher time frame (HTF) trend system. This can be set to any time frame by manual HTF mode. HTF mode set to "auto" will automatically choose the best suitable higher time frame trend system based on how appropriate the aggregation is. For everything below 5min the HTF Trend System will stay on 5min. Anything between 5-15min = 30min. 30min - 120min will turn on the 240min. 180min and higher will result in Daily time frame. Anything above the Daily will result in Weekly HTF aggregation, above W = Monthly, above M = Quarterly.
Background Clouds:
In terms of visualization, each trend system is fully customizable through the inputs settings. There is also an option to turn on/off the background clouds behind the stop lines. These clouds can make the charts more clean & visible.
Tips & Tricks:
1. Different Trend Modes
Try out different modes in different markets. There is no one single mode that will fit to everyone on the same type of market. I myself actually prefer more Loose than the Normal.
2. Stop Line Mirroring
Whenever the Stop Lines start to mirror each other (there is one above the price and one below) this means the price is entering a ranging sideways market. It does not matter which Stop Line will the price touch first. They can both be faded until one of them flips.
3. Signs of the Ranging Market
Watch out for signs of ranging market. Whenever the Trend System looses its colors whether on trend line or trend bars, if everything turns neutral (gray) that is usually a solid indication of a range type action for the following moments. Also as already stated before, the Stop Line mirroring is a good sign of the range market.
4. Trailing Tool, Trend System as an Additional Study?
In case you are not a fan of the colorful green / red charts & candles. You can switch all of them off and just leave the Stop Line on. This way you can use the benefits of the trend system and still use other studies on top of that. Similarly as the Parabolic SAR is often used.
5. The Flip Setup
One of my favorite trades is the Flip Setup on the 5min charts. Whenever the Stop Line is broken , the very first opposing touch after the Trend System flips is a usually a highly participated touch. If there is a strong reaction, this means this is likely a beginning of a new trend. Once I am in the position i like to trail the Stop Line on the 1min charts.
Hope it helps.
