Stochastic RSI Buy/Sell SignalThis indicator will show you a red circle above candles when Stoch RSI K value is greater than your "overbought" value, and a green circle above candles when Stoch RSI K value is below your "oversold" value. Updatable oversold and overbought values.
Oscilador Estocástico
[KVA]K Stochastic IndicatorOriginal Stochastic Oscillator Formula:
%K=(C−Lowest Low)/(Highest High−Lowest Low)×100
Lowest Low refers to the lowest low of the past n periods.
Highest High refers to the highest high of the past n periods.
K Stochastic Indicator Formula:
%K=(Source−Lowest Source)/(Highest Source−Lowest Source)×100
Lowest Source refers to the lowest value of the chosen source over the past length periods.
Highest Source refers to the highest value of the chosen source over the past length periods.
Key Difference :
The original formula calculates %K using the absolute highest high and lowest low of the price over the past n periods.
The K Stochastic formula calculates %K using the highest and lowest values of a chosen source (which could be the close, open, high, or low) over the specified length periods.
So, if _src is set to something other than the high for the Highest Source or something other than the low for the Lowest Source, the K Stochastic will yield different results compared to the original formula which strictly uses the highest high and the lowest low of the price.
Impact on Traders :
Flexibility in Price Source :
By allowing the source (_src) to be customizable, traders can apply the Stochastic calculation to different price points (e.g., open, high, low, close, or even an average of these). This could provide a different perspective on market momentum and potentially offer signals that are more aligned with a trader's specific strategy.
Sensitivity to Price Action :
Changing the source from high/low to potentially less extreme values (like close or open) could result in a less volatile oscillator, smoothing out some of the extreme peaks and troughs and possibly offering a more filtered view of market conditions.
Customization of Periods :
The ability to adjust the length period offers traders the opportunity to fine-tune the sensitivity of the indicator to match their trading horizon. Shorter periods may provide earlier signals, while longer periods could filter out market noise.
Possibility of Applying the Indicator on Other Indicators :
Layered Technical Analysis :
The K Stochastic can be applied to other indicators, not just price. For example, it could be applied to a moving average to analyze its momentum or to indicators like RSI or MACD, offering a meta-analysis that studies the oscillator's behavior of other technical tools.
Creation of Composite Indicator s:
By applying the K Stochastic logic to other indicators, traders could create composite indicators that blend the characteristics of multiple indicators, potentially leading to unique signals that could offer an edge in certain market conditions.
Enhanced Signal Interpretation :
When applied to other indicators, the K Stochastic can help in identifying overbought or oversold conditions within those indicators, offering a different dimension to the interpretation of their output.
Overall Implications :
The KStochastic Indicator's modifications could lead to a more tailored application, giving traders the ability to adapt the tool to their specific trading style and analysis preferences.
By being applicable to other indicators, it broadens the scope of stochastic analysis beyond price action, potentially offering innovative ways to interpret data and make trading decisions.
The changes might also influence the trading signals, either by smoothing the oscillator's output to reduce noise or by altering the sensitivity to generate more or fewer signal
Including the additional %F line, which is unique to the K Stochastic Indicator, further expands the potential impacts and applications for traders:
Impact on Traders with the %F Line:
Triple Smoothing :
The %F line introduces a third level of smoothing, which could help in identifying longer-term trends and filtering out short-term fluctuations. This could be particularly useful for traders looking to avoid whipsaws and focus on more sustained movements.
Potential for Enhanced Confirmation :
The %F line might be used as a confirmation signal. For instance, if all three lines (%K, %D, and %F) are in agreement, a trader might consider this as a stronger signal to buy or sell, as opposed to when only the traditional two lines (%K and %D) are used.
Risk Management:
The additional line could be utilized for more sophisticated risk management strategies, where a trader might decide to scale in or out of positions based on the convergence or divergence of these lines.
Possibility of Applying the Indicator on Other Indicators with the %F Line:
Depth of Analysis :
When applied to other indicators, the %F line can provide an even deeper layer of analysis, perhaps identifying macro trends within the indicator it is applied to, which could go unnoticed with just the traditional two-line approach.
Refined Signal Strength Assessment :
The strength of signals from other indicators could be assessed by the position and direction of the %F line, providing an additional filter to evaluate the robustness of buy or sell signals.
Overall Implications with the %F Line :
The inclusion of the %F line in the K Stochastic Indicator enhances its utility as a tool for trend analysis and signal confirmation. It allows traders to potentially identify and act on more reliable trading opportunities.
This feature can enrich the trader's toolkit by providing a nuanced view of momentum and trend strength, which can be particularly valuable in volatile or choppy markets.
For those applying the K Stochastic to other indicators, the %F line could be integral in creating a multi-tiered analysis strategy, potentially leading to more sophisticated interpretations and decisions.
The presence of the %F line adds a dimension of depth to the analysis possible with the K Stochastic Indicator, making it a versatile tool that could be tailored to a variety of trading styles and objectives. However, as with any indicator, the additional complexity requires careful study and back-testing to ensure its signals are understood and actionable within the context of a comprehensive trading plan.
Stochastic Signal Enhancer
This script defines a custom Stochastic Oscillator indicator with additional visual features to assist traders in identifying potential buy and sell opportunities based on overbought and oversold conditions, as well as the crossovers of the %K and %D lines.
How the Indicator Works:
Stochastic Oscillator Components:
- The Stochastic Oscillator is a momentum indicator that compares a particular closing price of an asset to a range of its prices over a certain period of time. The sensitivity of the oscillator to market movements is reducible by adjusting the time period or by taking a moving average of the result.
- The script uses inputs for %K length , %K smoothing , and %D smoothing to calculate the Stochastic lines (%K and %D).
Overbought and Oversold Levels:
- The overbought and oversold levels are set by default at 80 and 20 , respectively. These levels are user-adjustable.
- Horizontal lines are drawn on the chart to visually represent these levels.
Trading Signals:
- Buy Signal : A buy signal is generated when the %K line crosses above the oversold level, indicating potential upward momentum as the price may be considered "cheap" or "undervalued".
- Sell Signal : Conversely, a sell signal occurs when the %K line crosses below the overbought level, suggesting downward momentum as the price may be "expensive" or "overvalued".
- Additionally, the indicator plots a " strong buy " arrow when the %K line crosses above the %D line while in the oversold area, and a " strong sell " arrow when the %K line crosses below the %D line in the overbought area. These signals imply a confirmation of the trend reversal.
Visual Elements:
- The %K line is plotted in blue and the %D line in orange.
- Buy and sell opportunities are highlighted with green and red labels respectively, with arrows pointing up for buy and down for sell.
- Strong buy and sell signals due to %K and %D crossovers are marked with blue and yellow arrows.
Performance in Market Trends:
Trending Markets : During strong trends, stochastic signals can result in false signals as the oscillator can remain in overbought or oversold territories for extended periods. It is often more effective in non-trending or sideways markets.
Sideways Markets : In a range-bound market, the Stochastic Oscillator performs well as prices tend to close near the extremes of the recent range before reversing.
Confirmation with Other Indicators : The indicator can be more effective when used in conjunction with other technical analysis tools, such as trend lines or moving averages, to confirm the signals.
Adjustable Parameters : Traders can adjust the parameters (%K length, smoothing values, overbought/oversold levels) to better suit the asset being traded or to align with personal trading styles.
The given script provides a multi-faceted view of the Stochastic Oscillator by not only providing the basic overbought and oversold signals but also by enhancing the visual cues for better decision-making. The additional crossover signals act as a potential confirmation, offering a layered approach to interpreting market momentum and possible reversals.
// © ClearTradingMind
GKD-C TMMS Oscillator [Loxx]The Giga Kaleidoscope GKD-C TMMS Oscillator is a confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System."
█ GKD-C TMMS Oscillator
TMMS Oscillator uses the Relative Strength Index (RSI) and two stochastic oscillators to gauge market momentum. By normalizing these indicators around a central value, it identifies upward, downward, or neutral market conditions. Based on these assessments, the algorithm generates potential buy and sell signals determined by whether the combined momentum crosses or intersects with a central line.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Multi-Ticker CC Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Advance Trend Pressure as shown on the chart above
Confirmation 2: uf2018
Continuation: Coppock Curve
Exit: Rex Oscillator
Metamorphosis: Baseline Optimizer
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
Stochastic StrategyThis strategy is designed to make trading decisions based on the Stochastic Oscillator (Stoch) indicator with settings of (7,2,2). The strategy opens a long (buy) position when the Stoch indicator crosses above the 50 level from below. Conversely, it opens a short (sell) position when the Stoch indicator crosses below the 50 level from above. Additionally, when a long position is opened, any existing short position is closed, and vice versa.
Key Parameters:
Stochastic Oscillator Settings: Length = 7, SmoothK = 2, SmoothD = 2.
Overbought Level: 80.
Oversold Level: 20.
Strategy Description:
The Stochastic Oscillator (Stoch) is calculated based on the closing price, high price, and low price with a period of 7, and both the %K and %D lines are smoothed with periods of 2.
When the %K line crosses above the oversold level (20), it generates a long (buy) signal.
When the %K line crosses below the overbought level (80), it generates a short (sell) signal.
The strategy visually marks long and short signals on the chart using upward and downward triangles, respectively.
The strategy automatically enters long or short positions when the respective conditions are met.
If a long position is opened, any existing short position is closed, and vice versa.
Please note that this is a basic example of a trading strategy and does not take into account all possible risk factors or optimizations. Before using this strategy in live trading, it's essential to thoroughly test and customize it to suit your specific needs, and carefully analyze the results. Trading carries risks, and it's important to use proper risk management techniques when implementing any trading strategy.
MarketSmith Stochasticversion=5
This version of the stochastic produces the identical stochastic as used in MarketSmith
The three primary differences from a classic stochastic are as follows:
1. Close values only
2. 5-day ema instead of 3-day simple moving averages for smoothing the fast and slow lines
3. Slow and fast lines are truncated to integer values
by Mike Scott
2023-09-11
Fib TSIFib TSI = Fibonacci True Strength Index
The Fib TSI indicator uses Fibonacci numbers input for the True Strength Index moving averages. Then it is converted into a stochastic 0-100 scale.
The Fibonacci sequence is the series of numbers where each number is the sum of the two preceding numbers. 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610...
TSI uses moving averages of the underlying momentum of a financial instrument.
Stochastic is calculated by a formula of high and low over a length of time on a scale of 0-100.
How to use Fib TSI:
100 = overbought
0 = oversold
Rising = bullish
Falling = bearish
crossover 50 = bullish
crossunder 50 = bearish
The default input settings are:
2 = Stoch D smoothing
3 = TSI signal
TSI uses 2 moving averages compared with each other.
5 = TSI fastest
TSI uses 2 moving averages compared with each other.
Default value is 3/5.
color = white
8 = TSI fast
TSI uses 2 moving averages compared with each other.
Default value is 5/8.
color = blue
13 = TSI mid
TSI uses 2 moving averages compared with each other.
Default value is 8/13.
color = orange
21 = TSI slow
TSI uses 2 moving averages compared with each other.
Default value is 13/21.
color = purple
34 = TSI slowest
TSI uses 2 moving averages compared with each other.
Default value is 21/34.
color = yellow
55 = Stoch K length
All total / 5 = All TSI
color rising above 50 = bright green
color falling above 50 = mint green
color falling below 50 = bright red
color rising below 50 = pink
Up bullish reversal = green arrow up
bullish trend = green dots
Down bearish reversal = red arrow down
bearish trend = red dots
Horizontal lines:
100
75
50
25
0
2 different visual options example snapshot:
MACDVMACDV = Moving Average Convergence Divergence Volume
The MACDV indicator uses stochastic accumulation / distribution volume inflow and outflow formulas to visualize it in a standard MACD type of appearance.
To be able to merge these formulas I had to normalize the math.
Accumulation / distribution volume is a unique scale.
Stochastic is a 0-100 scale.
MACD is a unique scale.
The normalized output scale range for MACDV is -100 to 100.
100 = overbought
-100 = oversold
Everything in between is either bullish or bearish.
Rising = bullish
Falling = bearish
crossover = bullish
crossunder = bearish
convergence = direction change
divergence = momentum
The default input settings are:
7 = K length, Stochastic accumulation / distribution length
3 = D smoothing, smoothing stochastic accumulation / distribution volume weighted moving average
6 = MACDV fast, MACDV fast length line
color = blue
13 = MACDV slow, MACDV slow length line
color = white
4 = MACDV signal, MACDV histogram length
color rising above 0 = bright green
color falling above 0 = dark green
color falling below 0 = bright red
color rising below 0 = dark red
2 = Stretch, Output multiplier for MACDV visual expansion
Horizontal lines:
100
75
50
25
0
-25
-50
-75
-100
Multiple Ticker Stochastic RSIThe Stochastic RSI is a technical indicator ranging between 0 and 100, based on applying the Stochastic oscillator formula to a set of relative strength index (RSI). Unlike the original Stochastic RSI indicator, this allows you to define up to two additional tickers for which all three will be averaged and outputted visually looking like a standard Stochastic RSI indicator. Potential buy and sell visuals are included, as well as alerts. Please note that this indicator is not meant to be used by itself.
Velocity Indicator [CC]The Velocity Indicator was created by Scott Cong (Stocks and Commodities Sep 2023, pgs 8-15). This is my variation of his formula designed to capture the overall velocity of the underlying stock by applying the typical velocity formula. This indicator is visually similar to a typical stochastic indicator but uses a different underlying calculation. This works well as a momentum indicator, and the values are completely unbounded, so the best ways to determine bullish or bearish trends is either by using a crossover or crossunder between the indicator and the midline or to buy or sell the indicator when it reaches a high or low point and starts to fall or rise respectively. For my default version, I used the zero line to help determine the bullish or bearish trends. I have also included multiple colors to differentiate between very strong signals and normal signals, so very strong signals are darker in color, and normal signals use lighter colors. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators or scripts you would like to see me publish! I will have some more new scripts in the next week or so.
Stocashi + CaffeineCrush Momentum Indicator by CoffeeShopCryptoThis is just a fun script to give a different representation to the ever popular Stochastic RSI
Even for me over the years the stochastic has been a difficult one to use in trading merely because of its choppy look.
Since Heikin-Ashi Candles do such a powerful job in smoothing out the look of choppy markets,
I decided to test it out on the look of the Stochastic RSI.
From an initial visual standpoint it worked out WAY better than I thought but it seemed to need something more.
I decided to use the PineScript "Color.From_Gradient" feature to give the Stochastic a more 3 dimensional look, which really brought the "old-school" indicator to life.
Description:
The CaffeineCrush Momentum Indicator is your ultimate trading companion, blending the invigorating world of coffee with the excitement of market momentum. Just like a finely brewed cup of joe,
This indicator provides you with a powerful insight into market dynamics, helping you stay in the trading groove.
As you sip on this caffeinated delight, CaffeineCrush monitors the velocity and strength of price movements,
measuring the momentum of the market. But here's where it gets even more enticing – it goes a step further by incorporating a pressure indication, adding a stimulating twist to your trading experience.
Imagine yourself in a bustling coffee shop, surrounded by the aroma of freshly roasted beans and the energetic buzz of conversations.
CaffeineCrush mimics that atmosphere, keeping you on your toes, always aware of market forces at play.
With CaffeineCrush, you'll never miss a beat. It identifies and highlights moments of heightened momentum and increased pressure,
giving you an edge in capturing profitable opportunities. Just like a perfectly extracted espresso shot, this indicator helps you maintain your trading momentum and navigate the market with confidence.
So, grab your favorite cup of joe, fire up your trading charts, and let CaffeineCrush awaken your trading prowess.
Stay in the groove, embrace the buzz, and master the momentum with this flavorful indicator by your side.
Divergence -
Regular Divergence shows when there is a conflict between the strength of the trend and the swing of the price movement.
Hidden Divergence -
Are to be traded using the same methods as hidden divergences of the MACD or the RSI. A hidden divergence is commonly a trend CONTINUATION move.
Pink Pause -
This shows a ranging area where price is taking a pause. It can be a single candle or a string of candles. But histogram with continue with its RED / GREEN colors once the pause is over.
Stocashi + CaffeineCrush is not an entry / exit indicator. It's designed to help you understand:
1. Weather your trend is continuing
2. When it pauses
3. Has your pullback started / ended
Its best used near area of conflict. For example:
1. If you have a breakout to the low side of support zone, and you get a BULLISH divergence, this can be viewed as a false breakout.
2. If you trading towards the opposite area of a range or key level and you get conflicting movement in the Stocashi + CaffeineCrush, then you should take ur profits and wait for the next move.
3. If you are following through with example 2 above, but get NO conflicts, you can immediately look for a secondary take profit area and split / hedge your take profits.
Price Exhaustion IndicatorThe Price Exhaustion Indicator (PE) is a powerful tool designed to identify trends weakening and strengthening in the financial markets. It combines the concepts of Average True Range (ATR), Moving Average Convergence Divergence (MACD), and Stochastic Oscillator to provide a comprehensive assessment of trend exhaustion levels. By analyzing these multiple indicators together, traders and investors can gain valuable insights into potential price reversals and long-term market highs and lows.
The aim of combining the ATR, MACD, and Stochastic Oscillator, is to provide a comprehensive analysis of trend exhaustion. The ATR component helps assess the volatility and range of price movements, while the MACD offers insights into the convergence and divergence of moving averages. The Stochastic Oscillator measures the current price in relation to its range, providing further confirmation of trend exhaustion. The exhaustion value is derived by combining the MACD, ATR, and Stochastic Oscillator. The MACD value is divided by the ATR value, and then multiplied by the Stochastic Oscillator value. This calculation results in a single exhaustion value that reflects the combined influence of these three indicators.
Application
The Price Exhaustion Indicator utilizes a unique visual representation by incorporating a gradient color scheme. The exhaustion line dynamically changes color, ranging from white when close to the midline (40) to shades of purple as it approaches points of exhaustion (overbought at 100 and oversold at -20). As the exhaustion line approaches the color purple, this represents extreme market conditions and zones of weakened trends where reversals may occur. This color gradient serves as a visual cue, allowing users to quickly gauge the strength or weakness of the prevailing trend.
To further enhance its usability, the Price Exhaustion Indicator also includes circle plots that signify potential points of trend reversion. These plots appear when the exhaustion lines cross or enter the overbought and oversold zones. Red circle plots indicate potential short entry points, suggesting a weakening trend and the possibility of a downward price reversal. Conversely, green circle plots represent potential long entry points, indicating a strengthening trend and the potential for an upward price reversal.
Traders and investors can leverage the Price Exhaustion Indicator in various ways. It can be utilized as a trend-following tool, or a mean reversion tool. When the exhaustion line approaches the overbought or oversold zones, it suggests a weakening trend and the possibility of a price reversal, helping identify potential market tops and bottoms. This can guide traders in timing their entries or exits in anticipation of a trend shift.
Utility
The Price Exhaustion Indicator is particularly useful for long-term market analysis, as it focuses on identifying long-term market highs and lows. By capturing the gradual weakening or strengthening of a trend, it assists investors in making informed decisions about portfolio allocation, trend continuation, or potential reversals.
In summary, the Price Exhaustion Indicator is a comprehensive and visually intuitive tool that combines ATR, MACD, and Stochastic Oscillator to identify trend exhaustion levels. By utilizing a gradient color scheme and circle plots, it offers traders and investors valuable insights into potential trend reversals and long-term market highs and lows. Its unique features make it a valuable addition to any trader's toolkit, providing a deeper understanding of market dynamics and assisting in decision-making processes. Please note that future performance of any trading strategy is fundamentally unknowable, and past results do not guarantee future performance.
Kalman Filtered ROC & Stochastic with MA SmoothingThe "Smooth ROC & Stochastic with Kalman Filter" indicator is a trend following tool designed to identify trends in the price movement. It combines the Rate of Change (ROC) and Stochastic indicators into a single oscillator, the combination of ROC and Stochastic indicators aims to offer complementary information: ROC measures the speed of price change, while Stochastic identifies overbought and oversold conditions, allowing for a more robust assessment of market trends and potential reversals. The indicator plots green "B" labels to indicate buy signals and blue "S" labels to represent sell signals. Additionally, it displays a white line that reflects the overall trend for buy signals and a blue line for sell signals. The aim of the indicator is to incorporate Kalman and Moving Average (MA) smoothing techniques to reduce noise and enhance the clarity of the signals.
Rationale for using Kalman Filter:
The Kalman Filter is chosen as a smoothing tool in the indicator because it effectively reduces noise and fluctuations. The Kalman Filter is a mathematical algorithm used for estimating and predicting the state of a system based on noisy and incomplete measurements. It combines information from previous states and current measurements to generate an optimal estimate of the true state, while simultaneously minimizing the effects of noise and uncertainty. In the context of the indicator, the Kalman Filter is applied to smooth the input data, which is the source for the Rate of Change (ROC) calculation. By considering the previous smoothed state and the difference between the current measurement and the predicted value, the Kalman Filter dynamically adjusts its estimation to reduce the impact of outliers.
Calculation:
The indicator utilizes a combination of the ROC and the Stochastic indicator. The ROC is smoothed using a Kalman Filter (credit to © Loxx: ), which helps eliminate unwanted fluctuations and improve the signal quality. The Stochastic indicator is calculated with customizable parameters for %K length, %K smoothing, and %D smoothing. The smoothed ROC and Stochastic values are then averaged using the formula ((roc + d) / 2) to create the blended oscillator. MA smoothing is applied to the combined oscillator aiming to further reduce fluctuations and enhance trend visibility. Traders are free to choose their own preferred MA type from 'EMA', 'DEMA', 'TEMA', 'WMA', 'VWMA', 'SMA', 'SMMA', 'HMA', 'LSMA', and 'PEMA' (credit to: © traderharikrishna for this code: ).
Application:
The indicator's buy signals (represented by green "B" labels) indicate potential entry points for buying assets, suggesting a bullish trend. The white line visually represents the trend, helping traders identify and follow the upward momentum. Conversely, the sell signals (blue "S" labels) highlight possible exit points or opportunities for short selling, indicating a bearish trend. The blue line illustrates the bearish movement, aiding in the identification of downward momentum.
The "Smoothed ROC & Stochastic" indicator offers traders a comprehensive view of market trends by combining two powerful oscillators. By incorporating the ROC and Stochastic indicators into a single oscillator, it provides a more holistic perspective on the market's momentum. The use of a Kalman Filter for smoothing helps reduce noise and enhance the accuracy of the signals. Additionally, the indicator allows customization of the smoothing technique through various moving average types. Traders can also utilize the overbought and oversold zones for additional analysis, providing insights into potential market reversals or extreme price conditions. Please note that future performance of any trading strategy is fundamentally unknowable, and past results do not guarantee future performance.
RSI with J-Line ***For ease of use, I recommend changing the J Histogram to a line indicator, then it works like the KDJ Stochastic indicator. Full disclosure, I created this script with the help of GPT. This script was inspired by the KDJ Stochastic indicator by Dreadblitz***
The "RSI with J-Line" script is essentially a modified Relative Strength Index (RSI) indicator with an added histogram component. Here's how to use the different components of the script:
RSI Line (Blue): The RSI is a momentum oscillator that measures the speed and change of price movements. It oscillates between zero and 100, and is typically used to identify overbought and oversold conditions in a market. Traditionally, readings over 70 are considered overbought, and readings under 30 are considered oversold. However, these are not strict rules and can vary depending on the market and the overall trend.
RSI Smooth Line (Orange): This is the simple moving average of the RSI. It helps to smooth out the RSI and to identify the overall trend of the momentum. When the RSI line crosses above the RSI Smooth line, it might indicate that the momentum is moving upwards. When the RSI line crosses below the RSI Smooth line, it might indicate that the momentum is moving downwards.
RSI J-Line (Red Histogram): The J-Line is an additional line that's calculated as 3*rsiSmooth - 2*rsi. It's similar to the %J line in the Stochastic indicator and is designed to provide quicker signals than the RSI or RSI Smooth line. When the histogram is above the 0 line, it might indicate bullish momentum. When it's below the 0 line, it might indicate bearish momentum.
Please note that these interpretations are standard for these types of indicators, but actual market behavior can be complex and is influenced by many factors. Indicators should be used as part of a comprehensive trading strategy, not in isolation. Always take into account other market information and indicators before making trading decisions.
MOM HEATThe "MOM HEAT" indicator combines MACD, Stochastic, MFI, and RSI to create a heat map of market momentum.
It calculates wave values based on these indicators for four different timeframes.
The wave values are then normalized and combined to determine overall momentum.
The indicator plots squares on the chart to represent the wave values for each timeframe.
It also draws a line to indicate potential momentum shifts.
Additionally, a table displays the timeframes and their corresponding colors (lib kaigouthro/hsvColor/15).
Overall, the indicator provides a visual representation of market momentum and potential shifts.
Stochastic Distance Indicator [CC]The Stochastic Distance Indicator was created by Vitali Apirine (Stocks and Commodities Jun 2023 pgs 16-21), and this is a new method that measures the absolute distance between a price and its highest and lowest values over a long period. It uses the stochastic formula to create an oscillator using this distance value and smooths the value. Obviously, there is a lag in signals due to the lookback periods, but it does a good job of staying above the midline when the stock is in a strong uptrend and vice versa. Of course, I'm open to suggestions, but I'm deciding to create buy and sell signals based on comparing the unsmoothed and smoothed values. Buy when the line turns green and sell when it turns red.
Let me know if there are any other indicators you would like to see me publish!
GKD-C Adaptive-Lookback Stochastic [Loxx]Giga Kaleidoscope GKD-C Adaptive-Lookback Stochastic is a Metamorphosis module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C Adaptive-Lookback Stochastic
The Adaptive-Lookback Stochastic uses a swing pivot lookback algorithm to adjust the periiod input bar-bar-bar thereby converting the regular Stochasitc oscillator into an adaptive Stochatic oscillator.
What is the Adaptive Lookback Period?
The adaptive lookback period is a technique used in technical analysis to adjust the period of an indicator based on changes in market conditions. This technique is particularly useful in volatile or rapidly changing markets where a fixed period may not be optimal for detecting trends or signals.
The concept of the adaptive lookback period is relatively simple. By adjusting the lookback period based on changes in market conditions, traders can more accurately identify trends and signals. This can help traders to enter and exit trades at the right time and improve the profitability of their trading strategies.
The adaptive lookback period works by identifying potential swing points in the market. Once these points are identified, the lookback period is calculated based on the number of swings and a speed parameter. The swing count parameter determines the number of swings that must occur before the lookback period is adjusted. The speed parameter controls the rate at which the lookback period is adjusted, with higher values indicating a more rapid adjustment.
The adaptive lookback period can be applied to a wide range of technical indicators, including moving averages, oscillators, and trendlines. By adjusting the period of these indicators based on changes in market conditions, traders can reduce the impact of noise and false signals, leading to more profitable trades.
The adaptive lookback period is a powerful technique for traders and analysts looking to optimize their technical indicators. By adjusting the period based on changes in market conditions, traders can more accurately identify trends and signals, leading to more profitable trades. While there are various ways to implement the adaptive lookback period, the basic concept remains the same, and traders can adapt and customize the technique to suit their individual needs and trading styles.
What is the Stochastic Oscillator?
The Stochastic Oscillator is a popular technical analysis indicator developed by George Lane in the 1950s. It is a momentum indicator that compares a security's closing price to its price range over a specified period. The main idea behind the Stochastic Oscillator is that, in an upward trending market, prices tend to close near their high, while in a downward trending market, prices tend to close near their low. The Stochastic Oscillator ranges from 0 to 100 and is primarily used to identify overbought and oversold conditions or potential trend reversals.
The Stochastic Oscillator is calculated using the following formula:
%K = ((C - L14) / (H14 - L14)) * 100
Where:
%K: The Stochastic Oscillator value.
C: The most recent closing price.
L14: The lowest price of the last 14 periods (or any other chosen period).
H14: The highest price of the last 14 periods (or any other chosen period).
Additionally, a moving average of %K, called %D, is calculated to provide a signal line:
%D = Simple Moving Average of %K over 'n' periods
The Stochastic Oscillator generates signals based on the following conditions:
1. Overbought and Oversold Levels: The Stochastic Oscillator typically uses 80 and 20 as overbought and oversold levels, respectively. When the oscillator is above 80, it is considered overbought, indicating that the market may be overvalued and a price decline is possible. When the oscillator is below 20, it is considered oversold, indicating that the market may be undervalued and a price rise is possible.
2. Bullish and Bearish Divergences: A bullish divergence occurs when the price makes a lower low, but the Stochastic Oscillator makes a higher low, suggesting a potential trend reversal to the upside. A bearish divergence occurs when the price makes a higher high, but the Stochastic Oscillator makes a lower high, suggesting a potential trend reversal to the downside.
3. Crosses: Buy signals are generated when %K crosses above %D, indicating upward momentum. Sell signals are generated when %K crosses below %D, indicating downward momentum.
The Stochastic Oscillator is commonly used in combination with other technical analysis tools to confirm signals and improve the accuracy of predictions.
When using the Stochastic Oscillator, it's important to consider a few best practices and additional insights:
1. Confirmation with other indicators: While the Stochastic Oscillator can provide valuable insights into potential trend reversals and overbought/oversold conditions, it is generally more effective when used in conjunction with other technical indicators, such as moving averages, RSI (Relative Strength Index), or MACD (Moving Average Convergence Divergence). This can help confirm signals and reduce the chances of false signals or whipsaws.
2. Timeframes: The Stochastic Oscillator can be applied to various timeframes, such as daily, weekly, or intraday charts. Adjusting the lookback period for the calculation can also alter the sensitivity of the indicator. A shorter lookback period will make the oscillator more sensitive to price movements, while a longer lookback period will make it less sensitive. Traders should choose a timeframe and lookback period that aligns with their trading strategy and risk tolerance.
3. Variations: There are two primary variations of the Stochastic Oscillator: Fast Stochastic and Slow Stochastic. The Fast Stochastic uses the original %K and %D calculations, while the Slow Stochastic smooths %K with an additional moving average and uses this smoothed %K as the new %D. The Slow Stochastic is generally considered to generate fewer false signals due to the additional smoothing.
4. Overbought and Oversold: It's important to remember that overbought and oversold conditions can persist for an extended period, especially during strong trends. This means that the Stochastic Oscillator alone should not be relied upon as a definitive buy or sell signal. Instead, traders should wait for additional confirmation from other indicators or price action before entering or exiting a trade.
The Stochastic Oscillator is a valuable momentum indicator that helps traders identify potential trend reversals and overbought/oversold conditions in the market. However, it is most effective when used in combination with other technical analysis tools and should be adapted to suit the specific needs of the individual trader's strategy and risk tolerance.
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
8. Metamorphosis - a technical indicator that produces a compound signal from the combination of other GKD indicators*
*(not part of the NNFX algorithm)
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
What is an Metamorphosis indicator?
The concept of a metamorphosis indicator involves the integration of two or more GKD indicators to generate a compound signal. This is achieved by evaluating the accuracy of each indicator and selecting the signal from the indicator with the highest accuracy. As an illustration, let's consider a scenario where we calculate the accuracy of 10 indicators and choose the signal from the indicator that demonstrates the highest accuracy.
The resulting output from the metamorphosis indicator can then be utilized in a GKD-BT backtest by occupying a slot that aligns with the purpose of the metamorphosis indicator. The slot can be a GKD-B, GKD-C, or GKD-E slot, depending on the specific requirements and objectives of the indicator. This allows for seamless integration and utilization of the compound signal within the GKD-BT framework.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v2.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
6. GKD-M - Metamorphosis module (Metamorphosis, Number 8 in the NNFX algorithm, but not part of the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data to A backtest module wherein the various components of the GKD system are combined to create a trading signal.
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Full GKD Backtest
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Composite RSI
Confirmation 2: uf2018
Continuation: Vortex
Exit: Rex Oscillator
Metamorphosis: Fisher Transform, Universal Oscillator, Aroon, Vortex .. combined
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, GKD-M, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD system.
█ Giga Kaleidoscope Modularized Trading System Signals
Standard Entry
1. GKD-C Confirmation gives signal
2. Baseline agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
1-Candle Standard Entry
1a. GKD-C Confirmation gives signal
2a. Baseline agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Baseline Entry
1. GKD-B Basline gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Volatility/Volume agrees
7. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
1-Candle Baseline Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSBC Bars Back' prior
Next Candle
1b. Price retraced
2b. Baseline agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Volatility/Volume Entry
1. GKD-V Volatility/Volume gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Confirmation 2 agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Volatility/Volume Entry
1a. GKD-V Volatility/Volume gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSVVC Bars Back' prior
Next Candle
1b. Price retraced
2b. Volatility/Volume agrees
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Baseline agrees
Confirmation 2 Entry
1. GKD-C Confirmation 2 gives signal
2. Confirmation 1 agrees
3. Price inside Goldie Locks Zone Minimum
4. Price inside Goldie Locks Zone Maximum
5. Volatility/Volume agrees
6. Baseline agrees
7. Confirmation 1 signal was less than 7 candles prior
1-Candle Confirmation 2 Entry
1a. GKD-C Confirmation 2 gives signal
2a. Confirmation 1 agrees
3a. Price inside Goldie Locks Zone Minimum
4a. Price inside Goldie Locks Zone Maximum
5a. Confirmation 1 signal was less than 'Maximum Allowable PSC2C Bars Back' prior
Next Candle
1b. Price retraced
2b. Confirmation 2 agrees
3b. Confirmation 1 agrees
4b. Volatility/Volume agrees
5b. Baseline agrees
PullBack Entry
1a. GKD-B Baseline gives signal
2a. Confirmation 1 agrees
3a. Price is beyond 1.0x Volatility of Baseline
Next Candle
1b. Price inside Goldie Locks Zone Minimum
2b. Price inside Goldie Locks Zone Maximum
3b. Confirmation 1 agrees
4b. Confirmation 2 agrees
5b. Volatility/Volume agrees
Continuation Entry
1. Standard Entry, 1-Candle Standard Entry, Baseline Entry, 1-Candle Baseline Entry, Volatility/Volume Entry, 1-Candle Volatility/Volume Entry, Confirmation 2 Entry, 1-Candle Confirmation 2 Entry, or Pullback entry triggered previously
2. Baseline hasn't crossed since entry signal trigger
4. Confirmation 1 agrees
5. Baseline agrees
6. Confirmation 2 agrees
█ Connecting to Backtests
All GKD indicators are chained indicators meaning you export the value of the indicators to specialized backtest to creat your GKD trading system. Each indicator contains a proprietary signal generation algo that will only work with GKD backtests. You can find these backtests using the links below.
GKD-BT Giga Confirmation Stack Backtest:
GKD-BT Giga Stacks Backtest:
GKD-BT Full Giga Kaleidoscope Backtest:
GKD-BT Solo Confirmation Super Complex Backtest:
GKD-BT Solo Confirmation Complex Backtest:
GKD-BT Solo Confirmation Simple Backtest:
RSI, SRSI, MACD and DMI cross - Open source codeHello,
I'm a passionate trader who has spent years studying technical analysis and exploring different trading strategies. Through my research, I've come to realize that certain indicators are essential tools for conducting accurate market analysis and identifying profitable trading opportunities. In particular, I've found that the RSI, SRSI, MACD cross, and Di cross indicators are crucial for my trading success.
Detailed explanation:
The RSI is a momentum indicator that measures the strength of price movements. It is calculated by comparing the average of gains and losses over a certain period of time. In this indicator, the RSI is calculated based on the close price with a length of 14 periods.
The Stochastic RSI is a combination of the Stochastic Oscillator and the RSI. It is used to identify overbought and oversold conditions of the market. In this indicator, the Stochastic RSI is calculated based on the RSI with a length of 14 periods.
The MACD is a trend-following momentum indicator that shows the relationship between two moving averages of prices. It consists of two lines, the MACD line and the signal line, which are used to generate buy and sell signals. In this indicator, the MACD is calculated based on the close price with fast and slow lengths of 12 and 26 periods, respectively, and a signal length of 9 periods.
The DMI is a trend-following indicator that measures the strength of directional movement in the market. It consists of three lines, the Positive Directional Indicator (+DI), the Negative Directional Indicator (-DI), and the Average Directional Index (ADX), which are used to generate buy and sell signals. In this indicator, the DMI is calculated with a length of 14 periods and an ADX smoothing of 14 periods.
The indicator generates buy signals when certain conditions are met for each of these indicators.
1) For the RSI, a buy signal is generated when the RSI is below or equal to 35 and the Stochastic RSI %K is below or equal to 15, or when the RSI is below or equal to 28 the Stochastic RSI %K is below or equal to 15 or when the RSI is below or equal to 25 and the Stochastic RSI %K is below or equal to 10 or when the RSI is below or equal to 28.
2) For the MACD, a buy signal is generated when the MACD line is below 0, there is a change in the histogram from negative to positive, the MACD line and histogram are negative in the previous period, and the current histogram value is greater than 0.
3) For the DMI, a buy signal is generated when the Positive Directional Indicator (+DI) crosses above the Negative Directional Indicator (-DI), and the -DI is less than the +DI.
The indicator generates sell signals when certain conditions are met for each of these indicators:
1) For the RSI, a sell signal is generated when the RSI is above or equal to 75 and the Stochastic RSI %K is above or equal to 85, or when the RSI is above or equal to 80 and the Stochastic RSI %K is above or equal to 85, or when the RSI is above or equal to 85 and the Stochastic RSI %K is above or equal to 90 or when the RSI is above or equal to 82.
2)For the MACD, a sell signal is generated when the MACD line is above 0, there is a change in the histogram from positive to negative, the MACD line and histogram are positive in the previous period, and the current histogram value is less than the previous histogram value. On the other hand, a buy signal is generated when the MACD line is below 0, there is a change in the histogram from negative to positive, the MACD line and histogram are negative in the previous period, and the current histogram value is greater than the previous histogram value.
3)For the DMI a bearish signal is generated when plusDI crosses above minusDI, indicating that bulls are losing strength and bears are taking control.
The indicator uses a combination of these four indicators to generate potential buy and sell signals. The buy signals are generated when RSI and SRSI values are in oversold conditions, while sell signals are generated when RSI and SRSI values are in overbought conditions. The indicator also uses MACD crossovers and DMI crossovers to generate additional buy and sell signals.
When a signal is strong?
The use of multiple signals within a specific timeframe can increase the accuracy and reliability of the signals generated by this indicator. It is recommended to look for at least two signals within a range of 5-8 candles in order to increase the probability of a successful trade.
Why it's original?
1) There is no indicator in the library that combine all of these indicators and give you a 360 view
2)The combination of the RSI, Stochastic RSI, MACD, and DMI indicators in a single script it's unique and not available in the libray.
3)The specific parameters and conditions used to calculate the signals may be unique and not found in other scripts or libraries.
4)The use of plotshape() to plot the signals as shapes on the chart may be unique compared to other scripts that simply plot lines or bars to indicate signals.
5)The use of alertcondition() to trigger alerts based on the signals may be unique compared to other scripts that do not have custom alert functionality.
Keep attention!
It is important to note that no trading indicator or strategy is foolproof, and there is always a risk of losses in trading. While this indicator may provide useful information for making conclusions, it should not be used as the sole basis for making trading decisions. Traders should always use proper risk management techniques and consider multiple factors when making trading decisions.
Support me:)
If you find this new indicator helpful in your trading analysis, I would greatly appreciate your support! Please consider giving it a like, leaving feedback, or sharing it with your trading network. Your engagement will not only help me improve this tool but will also help other traders discover it and benefit from its features. Thank you for your support!
TASC 2023.06 Stochastic Distance Oscillator█ OVERVIEW
This script implements the stochastic distance oscillator (SDO) , a momentum indicator introduced by Vitali Apirine in an article featured in TASC's June 2023 edition of Traders' Tips . The SDO is a variation of the classic stochastic oscillator and is designed to identify overbought and oversold levels, as well as detect bull and bear trend changes.
█ CONCEPTS
Unlike the classic stochastic oscillator, which compares an asset's price to its past price range, the SDO measures the size of the current distance relative to the maximum-minimum distance range over a set number of periods. The current distance is defined as the distance between the current price and the price n periods ago.
The readings of the SDO can be used to identify the following states of the asset price:
Uptrend state: the oscillator crosses over 50 from a non-uptrend state.
Downtrend state: the oscillator crosses under -50 from a non-downtrend state.
Overbought state: the oscillator is in an uptrend and crosses -50 for the first time.
Oversold state: the oscillator is in a downtrend and crosses 50 for the first time.
Trend continuity: the oscillator crosses 0 in the direction of the current trend.
The script indicates these five conditions using on-chart signals and background coloring.
█ CALCULATIONS
The SDO is calculated as follows:
1. Calculate the distance between the current price and the price n periods ago, as well as the maximum and minimum distances for the selected lookback period. The author recommends using one of two values of n , 14 or 40 bars.
2. Calculate the time series % D that represents the relation between the asset's current distance and its distance range over a loockback period:
% D = (Abs(current distance) − Abs(minimum distance)) / (Abs(maximum distance) − Abs(minimum distance)) * 100
3. Use the calculated % D to obtain the SDO:
If the closing price is above the close n periods ago, SDO = % D
If the closing price is below the close n periods ago, SDO = −% D
If the closing price equals the close n periods ago or the current distance equals the minimum distance, SDO = 0
4. Smooth the SDO using an exponential moving average (EMA). The author recommends using an EMA in the range from 3 to 6 .
Adjustable input parameters include the number of periods n , the lookback period for calculating % D , the smoothing EMA length, and the overbought/oversold threshold level.
[Trendycator] Trendycator Trend Following IndicatorThis script proposes a simple and intuitive trend following indicator, better usage on those assets which are sufficiently liquid and don't go through random spikes.
Since it is a trend-following system, it works well during trends only and his intent is to find a primary trend and ride it for as long as possible.
We know that the biggest problem is how to understand if asset is in trend or not: for this purpose, the intuitive colors explained hereafter help Traders to understand when asset is in non trend.
It will never enter on the minimum and will never exit on the maximum but will always try to identify the central part of the trend, maintaining the position until the forces supporting the rise of the stock fail.
Usage details
Color interpretation
Green color mean that asset is in a UP Trend.
Red color mean that asset is in a Down Trend.
Gray color mean that indicator is not able to find any clear trend.
Trendycator use stochastic oscillator, which establish the trend and his strength.
As additional filter as noise removal the stochastic oscillator is smoothened using simple moving average.
Trendycator use as well price swing recognition which identify significant high and significant low breakouts.
When stochastic find trend with strength and significant breakout change color: green for up trend and red for down trend.
This mix of trend-following indicator and breakout system is made to avoid, as much as possible, false signal generated from side movement.
Settings
Trendycator usually doesn’t need to set anything.
This because we believe that the user have to searching for the charts where it works well and never "overfitting" the system on a chart.
Overfitting never work as a long time and in the first step for loosing money.
In Tradingview we decide to let the possibilities to set two parameters: "Period_UP" and "Period_DN".
The reason is because this can be adjusted slightly for testing in intraday, but we recommend to manipulate as less as possible.
Period UP/DN meaning: Period_UP are the number of bars considered for swing high detection and Period_DN is the number of bar that Trendycator use for swing low detection.
Important usage note
Trendycator was born and tested in weekly timeframe and works in daily as well. Intraday charts, normally have high volatility that is the opposite of trend; weekly, or daily bars reduce the noise.
Trendycator is tested, and used, in Etf and stocks.
Trendycator is tested, and used, for long operation only.
Trendycator is not tested in different timeframe from what explained above, or chart type different from bars (eg. Renko or Heikin Ashi).
Trendycator is not tested in instrument different from what listed above: like future or Forex.
Trendycator is not tested for short operation. Normally short have very strong movement in less time that is different from trend following concept.
Entry/Exit recommended filters
Investor and traders are free to use and interpretate Trendycator as they feel more confortable but, we recommend to apply some filters on entry and exit.
As you can see in example, we use a trigger for enter in position (not plotted by this indicator).
The high of first green bar is the trigger level for entry: the long position will be in Buy Stop above this level.
The low of first red bar is the trigger level for exit: the long position will be exit in Stop after this level.
Use this trigger criteria is useful to avoid, once more, the false signal.
Conclusion
Trendycator do not provide any guarantees regarding your ability to obtain results or earn money with our ideas, information, tools or strategies.
Nothing on our content makes any promise or guarantee of future results or earnings.
You alone are responsible for your decisions, actions and results in life, and using our code you agree that you will not attempt to hold us responsible for your decisions, actions or results, at any time, under any circumstances.
Strategy Creator5 indicators. Backtesting available. Uses ADX, RSI, Stochastic, MACD, and crossing EMAs (1,2, or 3). This strategy creator allows you to turn on or off these indicators and adjust the parameters for each indicator. It allows you to make one trade at a time e.g the next trade doesn't open until the last one closes. (You are also able to enter how many trades in one direction you want for example if you want only 2 long trades in a row, then the strategy waits for the next short position without making anymore long trades. Once there are 2 short positions in a row, it waits for a long position). The code can be edited to for automated trading by editing the comment in the source code for the strategy parameters. This took many hours to finish. ENJOY.
Stochastic Chebyshev Smoothed With Zero Lag SmoothingFast and Smooth Stochastic Oscillator with Zero Lag
Introduction
In this post, we will discuss a custom implementation of a Stochastic Oscillator that not only smooths the signal but also does so without introducing any noticeable lag. This is a remarkable achievement, as it allows for a fast Stochastic Oscillator that is less prone to false signals without being slow and sluggish.
We will go through the code step by step, explaining the various functions and the overall structure of the code.
First, let's start with a brief overview of the Stochastic Oscillator and the problem it addresses.
Background
The Stochastic Oscillator is a momentum indicator used in technical analysis to determine potential overbought or oversold conditions in an asset's price. It compares the closing price of an asset to its price range over a specified period. However, the Stochastic Oscillator is susceptible to false signals due to its sensitivity to price movements. This is where our custom implementation comes in, offering a smoother signal without noticeable lag, thus reducing the number of false signals.
Despite its popularity and widespread use in technical analysis, the Stochastic Oscillator has its share of drawbacks. While it is a price scaler that allows for easier comparisons across different assets and timeframes, it is also known for generating false signals, which can lead to poor trading decisions. In this section, we will delve deeper into the limitations of the Stochastic Oscillator and discuss the challenges associated with smoothing to mitigate its drawbacks.
Limitations of the Stochastic Oscillator
False Signals: The primary issue with the Stochastic Oscillator is its tendency to produce false signals. Since it is a momentum indicator, it reacts to short-term price movements, which can lead to frequent overbought and oversold signals that do not necessarily indicate a trend reversal. This can result in traders entering or exiting positions prematurely, incurring losses or missing out on potential gains.
Sensitivity to Market Noise: The Stochastic Oscillator is highly sensitive to market noise, which can create erratic signals in volatile markets. This sensitivity can make it difficult for traders to discern between genuine trend reversals and temporary fluctuations.
Lack of Predictive Power: Although the Stochastic Oscillator can help identify potential overbought and oversold conditions, it does not provide any information about the future direction or strength of a trend. As a result, it is often used in conjunction with other technical analysis tools to improve its predictive power.
Challenges of Smoothing the Stochastic Oscillator
To address the limitations of the Stochastic Oscillator, many traders attempt to smooth the indicator by applying various techniques. However, these approaches are not without their own set of challenges:
Trade-off between Smoothing and Responsiveness: The process of smoothing the Stochastic Oscillator inherently involves reducing its sensitivity to price movements. While this can help eliminate false signals, it can also result in a less responsive indicator, which may not react quickly enough to genuine trend reversals. This trade-off can make it challenging to find the optimal balance between smoothing and responsiveness.
Increased Complexity: Smoothing techniques often involve the use of additional mathematical functions and algorithms, which can increase the complexity of the indicator. This can make it more difficult for traders to understand and interpret the signals generated by the smoothed Stochastic Oscillator.
Lagging Signals: Some smoothing methods, such as moving averages, can introduce a time lag into the Stochastic Oscillator's signals. This can result in late entry or exit points, potentially reducing the profitability of a trading strategy based on the smoothed indicator.
Overfitting: In an attempt to eliminate false signals, traders may over-optimize their smoothing parameters, resulting in a Stochastic Oscillator that is overfitted to historical data. This can lead to poor performance in real-time trading, as the overfitted indicator may not accurately reflect the dynamics of the current market.
In our custom implementation of the Stochastic Oscillator, we used a combination of Chebyshev Type I Moving Average and zero-lag Gaussian-weighted moving average filters to address the indicator's limitations while preserving its responsiveness. In this section, we will discuss the reasons behind selecting these specific filters and the advantages of using the Chebyshev filter for our purpose.
Filter Selection
Chebyshev Type I Moving Average: The Chebyshev filter was chosen for its ability to provide a smoother signal without sacrificing much responsiveness. This filter is designed to minimize the maximum error between the original and the filtered signal within a specific frequency range, effectively reducing noise while preserving the overall shape of the signal. The Chebyshev Type I Moving Average achieves this by allowing a specified amount of ripple in the passband, resulting in a more aggressive filter roll-off and better noise reduction compared to other filters, such as the Butterworth filter.
Zero-lag Gaussian-weighted Moving Average: To further improve the Stochastic Oscillator's performance without introducing noticeable lag, we used the zero-lag Gaussian-weighted moving average (GWMA) filter. This filter combines the benefits of a Gaussian-weighted moving average, which prioritizes recent data points by assigning them higher weights, with a zero-lag approach that minimizes the time delay in the filtered signal. The result is a smoother signal that is less prone to false signals and is more responsive than traditional moving average filters.
Advantages of the Chebyshev Filter
Effective Noise Reduction: The primary advantage of the Chebyshev filter is its ability to effectively reduce noise in the Stochastic Oscillator signal. By minimizing the maximum error within a specified frequency range, the Chebyshev filter suppresses short-term fluctuations that can lead to false signals while preserving the overall trend.
Customizable Ripple Factor: The Chebyshev Type I Moving Average allows for a customizable ripple factor, enabling traders to fine-tune the filter's aggressiveness in reducing noise. This flexibility allows for better adaptability to different market conditions and trading styles.
Responsiveness: Despite its effective noise reduction, the Chebyshev filter remains relatively responsive compared to other smoothing filters. This responsiveness allows for more accurate detection of genuine trend reversals, making it a suitable choice for our custom Stochastic Oscillator implementation.
Compatibility with Zero-lag Techniques: The Chebyshev filter can be effectively combined with zero-lag techniques, such as the Gaussian-weighted moving average filter used in our custom implementation. This combination results in a Stochastic Oscillator that is both smooth and responsive, with minimal lag.
Code Overview
The code begins with defining custom mathematical functions for hyperbolic sine, cosine, and their inverse functions. These functions will be used later in the code for smoothing purposes.
Next, the gaussian_weight function is defined, which calculates the Gaussian weight for a given 'k' and 'smooth_per'. The zero_lag_gwma function calculates the zero-lag moving average with Gaussian weights. This function is used to create a Gaussian-weighted moving average with minimal lag.
The chebyshevI function is an implementation of the Chebyshev Type I Moving Average, which is used for smoothing the Stochastic Oscillator. This function takes the source value (src), length of the moving average (len), and the ripple factor (ripple) as input parameters.
The main part of the code starts by defining input parameters for K and D smoothing and ripple values. The Stochastic Oscillator is calculated using the ta.stoch function with Chebyshev smoothed inputs for close, high, and low. The result is further smoothed using the zero-lag Gaussian-weighted moving average function (zero_lag_gwma).
Finally, the lag variable is calculated using the Chebyshev Type I Moving Average for the Stochastic Oscillator. The Stochastic Oscillator and the lag variable are plotted on the chart, along with upper and lower bands at 80 and 20 levels, respectively. A fill is added between the upper and lower bands for better visualization.
Conclusion
The custom Stochastic Oscillator presented in this blog post combines the Chebyshev Type I Moving Average and zero-lag Gaussian-weighted moving average filters to provide a smooth and responsive signal without introducing noticeable lag. This innovative implementation results in a fast Stochastic Oscillator that is less prone to false signals, making it a valuable tool for technical analysts and traders alike.
However, it is crucial to recognize that the Stochastic Oscillator, despite being a price scaler, has its limitations, primarily due to its propensity for generating false signals. While smoothing techniques, like the ones used in our custom implementation, can help mitigate these issues, they often introduce new challenges, such as reduced responsiveness, increased complexity, lagging signals, and the risk of overfitting.
The selection of the Chebyshev Type I Moving Average and zero-lag Gaussian-weighted moving average filters was driven by their combined ability to provide a smooth and responsive signal while minimizing false signals. The advantages of the Chebyshev filter, such as effective noise reduction, customizable ripple factor, and responsiveness, make it an excellent fit for addressing the limitations of the Stochastic Oscillator.
When using the Stochastic Oscillator, traders should be aware of these limitations and challenges, and consider incorporating other technical analysis tools and techniques to supplement the indicator's signals. This can help improve the overall accuracy and effectiveness of their trading strategies, reducing the risk of losses due to false signals and other limitations associated with the Stochastic Oscillator.
Feel free to use, modify, or improve upon this custom Stochastic Oscillator code in your trading strategies. We hope this detailed walkthrough of the custom Stochastic Oscillator, its limitations, challenges, and filter selection has provided you with valuable insights and a better understanding of how it works. Happy trading!
GKD-C Stochastic of Two-Pole Super Smoother [Loxx] Giga Kaleidoscope GKD-C Stochastic of Two-Pole Super Smoother is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ GKD-C Stochastic of Two-Pole Super Smoother
What is the Two-Pole Super Smoother?
The two-pole Super Smoother is a sophisticated filtering technique used in the field of time series analysis to reduce noise and reveal underlying trends in data. It was developed by John F. Ehlers, an expert in the application of digital signal processing techniques to financial market data. The two-pole Super Smoother is based on digital signal processing principles and offers improved smoothing performance over traditional moving averages. The following will provide an in-depth explanation of the two-pole Super Smoother, including its mathematical formulation, characteristics, and advantages.
Mathematical Formulation
The two-pole Super Smoother is a low-pass filter that combines two first-order infinite impulse response (IIR) filters in a cascading manner. The filter coefficients are designed to provide optimal smoothing performance by minimizing the lag associated with traditional moving averages.
The two-pole Super Smoother is defined by the following difference equation:
y = (a1 * x ) + (a2 * x ) - (b1 * y ) - (b2 * y )
Here, x represents the input data series, y represents the filtered output data series, and n is the index of the current data point. The filter coefficients a1, a2, b1, and b2 are calculated based on the filter's cutoff frequency, which determines the degree of smoothing.
The filter coefficients are calculated as follows:
a1 = 1 - exp(-1.414 * 2 * π * Fc)
a2 = a1 - exp(-sqrt(2) * π * Fc)
b1 = 2 * (1 - exp(-sqrt(2) * π * Fc))
b2 = exp(-2 * sqrt(2) * π * Fc)
In the equations above, Fc is the normalized cutoff frequency, defined as the ratio of the desired cutoff frequency to the sampling frequency (usually the number of data points per unit of time). The value of Fc should be between 0 and 0.5 for the filter to work correctly.
Characteristics of the Two-Pole Super Smoother
1. Reduced Lag: The two-pole Super Smoother is designed to minimize the lag associated with traditional moving averages. By leveraging digital signal processing techniques, the filter is able to effectively reduce noise while maintaining a faster response to sudden changes in the data.
2. Improved Smoothing: The Super Smoother offers superior smoothing performance over traditional moving averages, such as simple and exponential moving averages. This is achieved through the cascading combination of two first-order IIR filters, which enhances the filter's noise reduction capabilities.
3. Robustness to Market Data: The two-pole Super Smoother is less sensitive to sudden price spikes and irregularities in financial market data. This makes it an ideal choice for traders and analysts who want to uncover underlying trends in noisy and volatile market data.
4. Flexibility: The two-pole Super Smoother can be easily adapted to different data sets and applications by adjusting the cutoff frequency. Users can fine-tune the degree of smoothing to suit their specific needs, making the filter highly versatile.
Advantages of the Two-Pole Super Smoother
1. The two-pole Super Smoother offers several advantages over traditional moving averages:
2. Faster Response: Due to its reduced lag, the two-pole Super Smoother provides a faster response to sudden changes in data, allowing users to identify trends and make informed decisions more quickly.
3. Improved Signal-to-Noise Ratio: The superior smoothing performance of the two-pole Super Smoother results in a higher signal-to-noise ratio, making it easier to identify underlying trends
What is the Stochastic Oscillator?
The Stochastic Oscillator is a popular technical analysis indicator developed by George Lane in the 1950s. It is a momentum indicator that compares a security's closing price to its price range over a specified period. The main idea behind the Stochastic Oscillator is that, in an upward trending market, prices tend to close near their high, while in a downward trending market, prices tend to close near their low. The Stochastic Oscillator ranges from 0 to 100 and is primarily used to identify overbought and oversold conditions or potential trend reversals.
The Stochastic Oscillator is calculated using the following formula:
%K = ((C - L14) / (H14 - L14)) * 100
Where:
%K: The Stochastic Oscillator value.
C: The most recent closing price.
L14: The lowest price of the last 14 periods (or any other chosen period).
H14: The highest price of the last 14 periods (or any other chosen period).
Additionally, a moving average of %K, called %D, is calculated to provide a signal line:
%D = Simple Moving Average of %K over 'n' periods
The Stochastic Oscillator generates signals based on the following conditions:
1. Overbought and Oversold Levels: The Stochastic Oscillator typically uses 80 and 20 as overbought and oversold levels, respectively. When the oscillator is above 80, it is considered overbought, indicating that the market may be overvalued and a price decline is possible. When the oscillator is below 20, it is considered oversold, indicating that the market may be undervalued and a price rise is possible.
2. Bullish and Bearish Divergences: A bullish divergence occurs when the price makes a lower low, but the Stochastic Oscillator makes a higher low, suggesting a potential trend reversal to the upside. A bearish divergence occurs when the price makes a higher high, but the Stochastic Oscillator makes a lower high, suggesting a potential trend reversal to the downside.
3. Crosses: Buy signals are generated when %K crosses above %D, indicating upward momentum. Sell signals are generated when %K crosses below %D, indicating downward momentum.
The Stochastic Oscillator is commonly used in combination with other technical analysis tools to confirm signals and improve the accuracy of predictions.
When using the Stochastic Oscillator, it's important to consider a few best practices and additional insights:
1. Confirmation with other indicators: While the Stochastic Oscillator can provide valuable insights into potential trend reversals and overbought/oversold conditions, it is generally more effective when used in conjunction with other technical indicators, such as moving averages, RSI (Relative Strength Index), or MACD (Moving Average Convergence Divergence). This can help confirm signals and reduce the chances of false signals or whipsaws.
2. Timeframes: The Stochastic Oscillator can be applied to various timeframes, such as daily, weekly, or intraday charts. Adjusting the lookback period for the calculation can also alter the sensitivity of the indicator. A shorter lookback period will make the oscillator more sensitive to price movements, while a longer lookback period will make it less sensitive. Traders should choose a timeframe and lookback period that aligns with their trading strategy and risk tolerance.
3. Variations: There are two primary variations of the Stochastic Oscillator: Fast Stochastic and Slow Stochastic. The Fast Stochastic uses the original %K and %D calculations, while the Slow Stochastic smooths %K with an additional moving average and uses this smoothed %K as the new %D. The Slow Stochastic is generally considered to generate fewer false signals due to the additional smoothing.
4. Overbought and Oversold: It's important to remember that overbought and oversold conditions can persist for an extended period, especially during strong trends. This means that the Stochastic Oscillator alone should not be relied upon as a definitive buy or sell signal. Instead, traders should wait for additional confirmation from other indicators or price action before entering or exiting a trade.
In summary, the Stochastic Oscillator is a valuable momentum indicator that helps traders identify potential trend reversals and overbought/oversold conditions in the market. However, it is most effective when used in combination with other technical analysis tools and should be adapted to suit the specific needs of the individual trader's strategy and risk tolerance.
What is a Discontinued Signal Line (DSL)?
Many indicators employ signal lines to more easily identify trends or desired states of the indicator. The concept of a signal line is straightforward: by comparing a value to its smoothed, slightly lagging state, one can determine the current momentum or state.
The Discontinued Signal Line builds on this fundamental idea by extending it: rather than having a single signal line, multiple lines are used based on the indicator's current value.
The "signal" line is calculated as follows:
When a specific level is crossed in the desired direction, the EMA of that value is calculated for the intended signal line.
When that level is crossed in the opposite direction, the previous "signal" line value is "inherited," becoming a sort of level.
This approach combines signal lines and levels, aiming to integrate the advantages of both methods.
In essence, DSL enhances the signal line concept by inheriting the previous signal line's value and converting it into a level.
What is the Stochastic of Two-Pole Super Smoother
This indicator uses Two-Pole Super Smoother to smooth price. This smoothed price is then injected into the Stochastic algorithm. The final result is wrapped by Unanchored Discontinued Signal Lines
█ Giga Kaleidoscope Modularized Trading System
Core components of an NNFX algorithmic trading strategy
The NNFX algorithm is built on the principles of trend, momentum, and volatility. There are six core components in the NNFX trading algorithm:
1. Volatility - price volatility; e.g., Average True Range, True Range Double, Close-to-Close, etc.
2. Baseline - a moving average to identify price trend
3. Confirmation 1 - a technical indicator used to identify trends
4. Confirmation 2 - a technical indicator used to identify trends
5. Continuation - a technical indicator used to identify trends
6. Volatility/Volume - a technical indicator used to identify volatility/volume breakouts/breakdown
7. Exit - a technical indicator used to determine when a trend is exhausted
What is Volatility in the NNFX trading system?
In the NNFX (No Nonsense Forex) trading system, ATR (Average True Range) is typically used to measure the volatility of an asset. It is used as a part of the system to help determine the appropriate stop loss and take profit levels for a trade. ATR is calculated by taking the average of the true range values over a specified period.
True range is calculated as the maximum of the following values:
-Current high minus the current low
-Absolute value of the current high minus the previous close
-Absolute value of the current low minus the previous close
ATR is a dynamic indicator that changes with changes in volatility. As volatility increases, the value of ATR increases, and as volatility decreases, the value of ATR decreases. By using ATR in NNFX system, traders can adjust their stop loss and take profit levels according to the volatility of the asset being traded. This helps to ensure that the trade is given enough room to move, while also minimizing potential losses.
Other types of volatility include True Range Double (TRD), Close-to-Close, and Garman-Klass
What is a Baseline indicator?
The baseline is essentially a moving average, and is used to determine the overall direction of the market.
The baseline in the NNFX system is used to filter out trades that are not in line with the long-term trend of the market. The baseline is plotted on the chart along with other indicators, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR).
Trades are only taken when the price is in the same direction as the baseline. For example, if the baseline is sloping upwards, only long trades are taken, and if the baseline is sloping downwards, only short trades are taken. This approach helps to ensure that trades are in line with the overall trend of the market, and reduces the risk of entering trades that are likely to fail.
By using a baseline in the NNFX system, traders can have a clear reference point for determining the overall trend of the market, and can make more informed trading decisions. The baseline helps to filter out noise and false signals, and ensures that trades are taken in the direction of the long-term trend.
What is a Confirmation indicator?
Confirmation indicators are technical indicators that are used to confirm the signals generated by primary indicators. Primary indicators are the core indicators used in the NNFX system, such as the Average True Range (ATR), the Moving Average (MA), and the Relative Strength Index (RSI).
The purpose of the confirmation indicators is to reduce false signals and improve the accuracy of the trading system. They are designed to confirm the signals generated by the primary indicators by providing additional information about the strength and direction of the trend.
Some examples of confirmation indicators that may be used in the NNFX system include the Bollinger Bands, the MACD (Moving Average Convergence Divergence), and the MACD Oscillator. These indicators can provide information about the volatility, momentum, and trend strength of the market, and can be used to confirm the signals generated by the primary indicators.
In the NNFX system, confirmation indicators are used in combination with primary indicators and other filters to create a trading system that is robust and reliable. By using multiple indicators to confirm trading signals, the system aims to reduce the risk of false signals and improve the overall profitability of the trades.
What is a Continuation indicator?
In the NNFX (No Nonsense Forex) trading system, a continuation indicator is a technical indicator that is used to confirm a current trend and predict that the trend is likely to continue in the same direction. A continuation indicator is typically used in conjunction with other indicators in the system, such as a baseline indicator, to provide a comprehensive trading strategy.
What is a Volatility/Volume indicator?
Volume indicators, such as the On Balance Volume (OBV), the Chaikin Money Flow (CMF), or the Volume Price Trend (VPT), are used to measure the amount of buying and selling activity in a market. They are based on the trading volume of the market, and can provide information about the strength of the trend. In the NNFX system, volume indicators are used to confirm trading signals generated by the Moving Average and the Relative Strength Index. Volatility indicators include Average Direction Index, Waddah Attar, and Volatility Ratio. In the NNFX trading system, volatility is a proxy for volume and vice versa.
By using volume indicators as confirmation tools, the NNFX trading system aims to reduce the risk of false signals and improve the overall profitability of trades. These indicators can provide additional information about the market that is not captured by the primary indicators, and can help traders to make more informed trading decisions. In addition, volume indicators can be used to identify potential changes in market trends and to confirm the strength of price movements.
What is an Exit indicator?
The exit indicator is used in conjunction with other indicators in the system, such as the Moving Average (MA), the Relative Strength Index (RSI), and the Average True Range (ATR), to provide a comprehensive trading strategy.
The exit indicator in the NNFX system can be any technical indicator that is deemed effective at identifying optimal exit points. Examples of exit indicators that are commonly used include the Parabolic SAR, the Average Directional Index (ADX), and the Chandelier Exit.
The purpose of the exit indicator is to identify when a trend is likely to reverse or when the market conditions have changed, signaling the need to exit a trade. By using an exit indicator, traders can manage their risk and prevent significant losses.
In the NNFX system, the exit indicator is used in conjunction with a stop loss and a take profit order to maximize profits and minimize losses. The stop loss order is used to limit the amount of loss that can be incurred if the trade goes against the trader, while the take profit order is used to lock in profits when the trade is moving in the trader's favor.
Overall, the use of an exit indicator in the NNFX trading system is an important component of a comprehensive trading strategy. It allows traders to manage their risk effectively and improve the profitability of their trades by exiting at the right time.
How does Loxx's GKD (Giga Kaleidoscope Modularized Trading System) implement the NNFX algorithm outlined above?
Loxx's GKD v1.0 system has five types of modules (indicators/strategies). These modules are:
1. GKD-BT - Backtesting module (Volatility, Number 1 in the NNFX algorithm)
2. GKD-B - Baseline module (Baseline and Volatility/Volume, Numbers 1 and 2 in the NNFX algorithm)
3. GKD-C - Confirmation 1/2 and Continuation module (Confirmation 1/2 and Continuation, Numbers 3, 4, and 5 in the NNFX algorithm)
4. GKD-V - Volatility/Volume module (Confirmation 1/2, Number 6 in the NNFX algorithm)
5. GKD-E - Exit module (Exit, Number 7 in the NNFX algorithm)
(additional module types will added in future releases)
Each module interacts with every module by passing data between modules. Data is passed between each module as described below:
GKD-B => GKD-V => GKD-C(1) => GKD-C(2) => GKD-C(Continuation) => GKD-E => GKD-BT
That is, the Baseline indicator passes its data to Volatility/Volume. The Volatility/Volume indicator passes its values to the Confirmation 1 indicator. The Confirmation 1 indicator passes its values to the Confirmation 2 indicator. The Confirmation 2 indicator passes its values to the Continuation indicator. The Continuation indicator passes its values to the Exit indicator, and finally, the Exit indicator passes its values to the Backtest strategy.
This chaining of indicators requires that each module conform to Loxx's GKD protocol, therefore allowing for the testing of every possible combination of technical indicators that make up the six components of the NNFX algorithm.
What does the application of the GKD trading system look like?
Example trading system:
Backtest: Strategy with 1-3 take profits, trailing stop loss, multiple types of PnL volatility, and 2 backtesting styles
Baseline: Hull Moving Average
Volatility/Volume: Hurst Exponent
Confirmation 1: Stochastic of Two-Pole Super Smoother as shown on the chart above
Confirmation 2: Williams Percent Range
Continuation: Fisher Transform
Exit: Rex Oscillator
Each GKD indicator is denoted with a module identifier of either: GKD-BT, GKD-B, GKD-C, GKD-V, or GKD-E. This allows traders to understand to which module each indicator belongs and where each indicator fits into the GKD protocol chain.
Giga Kaleidoscope Modularized Trading System Signals (based on the NNFX algorithm)
Standard Entry
1. GKD-C Confirmation 1 Signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 1 signal was less than 7 candles prior
Continuation Entry
1. Standard Entry, Baseline Entry, or Pullback; entry triggered previously
2. GKD-B Baseline hasn't crossed since entry signal trigger
3. GKD-C Confirmation Continuation Indicator signals
4. GKD-C Confirmation 1 agrees
5. GKD-B Baseline agrees
6. GKD-C Confirmation 2 agrees
1-Candle Rule Standard Entry
1. GKD-C Confirmation 1 signal
2. GKD-B Baseline agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume agrees
1-Candle Rule Baseline Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close )
2. GKD-B Baseline agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
1-Candle Rule Volatility/Volume Entry
1. GKD-V Volatility/Volume signal
2. GKD-C Confirmation 1 agrees
3. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
4. GKD-C Confirmation 1 signal was less than 7 candles prior
Next Candle:
1. Price retraced (Long: close < close or Short: close > close)
2. GKD-B Volatility/Volume agrees
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-B Baseline agrees
PullBack Entry
1. GKD-B Baseline signal
2. GKD-C Confirmation 1 agrees
3. Price is beyond 1.0x Volatility of Baseline
Next Candle:
1. Price is within a range of 0.2x Volatility and 1.0x Volatility of the Goldie Locks Mean
2. GKD-C Confirmation 1 agrees
3. GKD-C Confirmation 2 agrees
4. GKD-V Volatility/Volume Agrees
]█ Setting up the GKD
The GKD system involves chaining indicators together. These are the steps to set this up.
Use a GKD-C indicator alone on a chart
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
Use a GKD-V indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Use a GKD-B indicator alone on a chart
**nothing, it's already useable on the chart without any settings changes
Baseline (Baseline, Backtest)
1. Import the GKD-B Baseline into the GKD-BT Backtest: "Input into Volatility/Volume or Backtest (Baseline testing)"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline"
Volatility/Volume (Volatility/Volume, Backte st)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Solo"
2. Inside the GKD-V indicator, change the "Signal Type" setting to "Crossing" (neither traditional nor both can be backtested)
3. Import the GKD-V indicator into the GKD-BT Backtest: "Input into C1 or Backtest"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Volatility/Volume"
5. Inside the GKD-BT Backtest, a) change the setting "Backtest Type" to "Trading" if using a directional GKD-V indicator; or, b) change the setting "Backtest Type" to "Full" if using a directional or non-directional GKD-V indicator (non-directional GKD-V can only test Longs and Shorts separately)
6. If "Backtest Type" is set to "Full": Inside the GKD-BT Backtest, change the setting "Backtest Side" to "Long" or "Short
7. If "Backtest Type" is set to "Full": To allow the system to open multiple orders at one time so you test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Solo Confirmation Simple (Confirmation, Backtest)
1. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Simple"
1. Import the GKD-C indicator into the GKD-BT Backtest: "Input into Backtest"
2. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Solo Confirmation Simple"
Solo Confirmation Complex without Exits (Baseline, Volatility/Volume, Confirmation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
6. Import the GKD-C into the GKD-BT Backtest: "Input into Exit or Backtest"
Solo Confirmation Complex with Exits (Baseline, Volatility/Volume, Confirmation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C indicator, change the "Confirmation Type" setting to "Solo Confirmation Complex"
4. Import the GKD-V indicator into the GKD-C indicator: "Input into C1 or Backtest"
5. Import the GKD-C indicator into the GKD-E indicator: "Input into Exit"
6. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
7. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Full GKD without Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full wo/ Exits"
9. Import the GKD-E into the GKD-BT Backtest: "Input into Exit or Backtest"
Full GKD with Exits (Baseline, Volatility/Volume, Confirmation 1, Confirmation 2, Continuation, Exit, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Chained"
2. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
3. Inside the GKD-C 1 indicator, change the "Confirmation Type" setting to "Confirmation 1"
4. Import the GKD-V indicator into the GKD-C 1 indicator: "Input into C1 or Backtest"
5. Inside the GKD-C 2 indicator, change the "Confirmation Type" setting to "Confirmation 2"
6. Import the GKD-C 1 indicator into the GKD-C 2 indicator: "Input into C2"
7. Inside the GKD-C Continuation indicator, change the "Confirmation Type" setting to "Continuation"
8. Import the GKD-C Continuation indicator into the GKD-E indicator: "Input into Exit"
9. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "GKD Full w/ Exits"
10. Import the GKD-E into the GKD-BT Backtest: "Input into Backtest"
Baseline + Volatility/Volume (Baseline, Volatility/Volume, Backtest)
1. Inside the GKD-V indicator, change the "Testing Type" setting to "Baseline + Volatility/Volume"
2. Inside the GKD-V indicator, make sure the "Signal Type" setting is set to "Traditional"
3. Import the GKD-B Baseline into the GKD-V indicator: "Input into Volatility/Volume or Backtest (Baseline testing)"
4. Inside the GKD-BT Backtest, change the setting "Backtest Special" to "Baseline + Volatility/Volume"
5. Import the GKD-V into the GKD-BT Backtest: "Input into C1 or Backtest"
6. Inside the GKD-BT Backtest, change the setting "Backtest Type" to "Full". For this backtest, you must test Longs and Shorts separately
7. To allow the system to open multiple orders at one time so you can test all Longs or Shorts, open the GKD-BT Backtest, click the tab "Properties" and then insert a value of something like 10 orders into the "Pyramiding" settings. This will allow 10 orders to be opened at one time which should be enough to catch all possible Longs or Shorts.
Requirements
Inputs
Confirmation 1: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Continuation: GKD-C Confirmation indicator
Solo Confirmation Simple: GKD-B Baseline
Solo Confirmation Complex: GKD-V Volatility / Volume indicator
Solo Confirmation Super Complex: GKD-V Volatility / Volume indicator
Stacked 1: None
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 1
Outputs
Confirmation 1: GKD-C Confirmation 2 indicator
Confirmation 2: GKD-C Continuation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest
Solo Confirmation Complex: GKD-BT Backtest or GKD-E Exit indicator
Solo Confirmation Super Complex: GKD-C Continuation indicator
Stacked 1: GKD-C, GKD-V, or GKD-B Stacked 2+
Stacked 2+: GKD-C, GKD-V, or GKD-B Stacked 2+ or GKD-BT Backtest
Additional features will be added in future releases.
