GKD-C Jurik-Filtered Random Walk Index [Loxx]Giga Kaleidoscope GKD-C Jurik-Filtered Random Walk Index is a Confirmation module included in Loxx's "Giga Kaleidoscope Modularized Trading System".
█ Giga Kaleidoscope Modularized Trading System
What is Loxx's "Giga Kaleidoscope Modularized Trading System"?
The Giga Kaleidoscope Modularized Trading System is a trading system built on the philosophy of the NNFX (No Nonsense Forex) algorithmic trading.
What is the NNFX algorithmic trading strategy?
The NNFX (No-Nonsense Forex) trading system is a comprehensive approach to Forex trading that is designed to simplify the process and remove the confusion and complexity that often surrounds trading. The system was developed by a Forex trader who goes by the pseudonym "VP" and has gained a significant following in the Forex community.
The NNFX trading system is based on a set of rules and guidelines that help traders make objective and informed decisions. These rules cover all aspects of trading, including market analysis, trade entry, stop loss placement, and trade management.
Here are the main components of the NNFX trading system:
1. Trading Philosophy: The NNFX trading system is based on the idea that successful trading requires a comprehensive understanding of the market, objective analysis, and strict risk management. The system aims to remove subjective elements from trading and focuses on objective rules and guidelines.
2. Technical Analysis: The NNFX trading system relies heavily on technical analysis and uses a range of indicators to identify high-probability trading opportunities. The system uses a combination of trend-following and mean-reverting strategies to identify trades.
3. Market Structure: The NNFX trading system emphasizes the importance of understanding the market structure, including price action, support and resistance levels, and market cycles. The system uses a range of tools to identify the market structure, including trend lines, channels, and moving averages.
4. Trade Entry: The NNFX trading system has strict rules for trade entry. The system uses a combination of technical indicators to identify high-probability trades, and traders must meet specific criteria to enter a trade.
5. Stop Loss Placement: The NNFX trading system places a significant emphasis on risk management and requires traders to place a stop loss order on every trade. The system uses a combination of technical analysis and market structure to determine the appropriate stop loss level.
6. Trade Management: The NNFX trading system has specific rules for managing open trades. The system aims to minimize risk and maximize profit by using a combination of trailing stops, take profit levels, and position sizing.
Overall, the NNFX trading system is designed to be a straightforward and easy-to-follow approach to Forex trading that can be applied by traders of all skill levels.
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: Jurik-Filtered Random Walk Index 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
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
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
3. GKD-C Confirmation 1 agrees
4. GKD-C Confirmation 2 agrees
5. GKD-V Volatility/Volume Agrees
█ GKD-C Jurik-Filtered Random Walk Index
What is the Jurik Filter?
The Jurik Filter is a technical analysis tool that is used to filter out market noise and identify trends in financial markets. It was developed by Mark Jurik in the 1990s and is based on a non-linear smoothing algorithm that provides a more accurate representation of price movements.
Traditional moving averages, such as the Simple Moving Average ( SMA ) or Exponential Moving Average ( EMA ), are linear filters that produce a lag between price and the moving average line. This can cause false signals during periods of market volatility , which can result in losses for traders and investors.
The Jurik Filter is designed to address this issue by incorporating a damping factor into the smoothing algorithm. This damping factor adjusts the filter's responsiveness to the changes in price, allowing it to filter out market noise without overshooting price peaks and valleys.
The Jurik Filter is calculated using a mathematical formula that takes into account the current and past prices of an asset, as well as the volatility of the market. This formula incorporates the damping factor and produces a smoother price curve than traditional moving average filters.
One of the advantages of the Jurik Filter is its ability to adjust to changing market conditions. The damping factor can be adjusted to suit different securities and time frames, making it a versatile tool for traders and investors.
Traders and investors often use the Jurik Filter in conjunction with other technical analysis tools, such as the MACD or RSI , to confirm or complement their trading strategies. By filtering out market noise and identifying trends in the financial markets, the Jurik Filter can help improve the accuracy of trading signals and reduce the risks of false signals during periods of market volatility .
Overall, the Jurik Filter is a powerful technical analysis tool that can help traders and investors make more informed decisions about buying and selling securities. By providing a smoother price curve and reducing false signals, it can help improve trading performance and reduce risk in volatile markets.
What is the Random Walk Index?
The Random Walk Index (RWI) is a technical analysis indicator used in financial markets to determine whether a stock or index is trending or moving in a random manner. It was developed by Michael Poulos in the 1990s and is based on the concept of a random walk.
A random walk is a mathematical model that describes a process in which a variable moves randomly over time. In the context of financial markets, a random walk implies that the price movements of a stock or index are essentially unpredictable, and any movement is just as likely to go up as it is to go down.
The RWI attempts to measure the randomness of a stock or index by comparing its actual price movements with a theoretical random walk. The indicator calculates the ratio of the actual distance traveled by the price to the expected distance of a random walk, over a given period of time.
Here are the steps to calculate the RWI:
Calculate the average distance traveled by the price for the given period of time (e.g. 10 days).
Calculate the cumulative distance between the price and its moving average for the same period of time.
Calculate the standard deviation of the cumulative distance.
Divide the average distance by the standard deviation to get the RWI.
The RWI typically ranges between 0 and 1. If the RWI is close to 0, it suggests that the price is moving randomly, while a value close to 1 indicates that the price is trending.
Traders use the RWI to help identify when a stock or index is trending or moving in a random manner. A high RWI value indicates that the market is trending and may be a good time to enter or exit a trade. Conversely, a low RWI value indicates that the market is not trending, and traders should avoid entering or exiting trades based on trend-following strategies.
It is worth noting that the RWI is not a perfect indicator and may produce false signals, particularly during periods of low volatility. Traders should always use the RWI in combination with other technical indicators and fundamental analysis to make informed trading decisions.
What is Jurik-Filtered Random Walk Index?
Jurik-Filtered Random Walk Index applies Jurik Smoothing halfway through the calculation process to filter out noise thereby producing a cleaner output signal.
Requirements
Inputs
Confirmation 1 and Solo Confirmation: GKD-V Volatility / Volume indicator
Confirmation 2: GKD-C Confirmation indicator
Outputs
Confirmation 2 and Solo Confirmation Complex: GKD-E Exit indicator
Confirmation 1: GKD-C Confirmation indicator
Continuation: GKD-E Exit indicator
Solo Confirmation Simple: GKD-BT Backtest strategy
Additional features will be added in future releases.
Random Walk Index (RWI)
Highly Optimized (Aroon, DMI, RWI)It is a highly optimized script for H4, D1. Backtests from (2016 - 2019, depending on the currency pair). Optimization still
going on.
Following alerts can be activated:
-
Buy-Signal (Baseline-Cross)!
Sell-Signal (Baseline-Cross)!
Buy Signal (Aroon)!
Sell Signal (Aroon)!
Buy Signal (DMI)!
Sell Signal (DMI)!
Buy Signal (RWI)!
Sell Signal (RWI)!
Can be used by the following pairs:
AUDCAD
AUDCHF
AUDJPY
AUDNZD
AUDSGD
AUDUSD
CADCHF
CADJPY
CHFJPY
CHFSGD
EURAUD
EURCAD
EURCHF
EURGBP
EURJPY
EURNZD
EURSGD
EURTRY
EURUSD
GBPAUD
GBPCAD
GBPCHF
GBPJPY
GBPNZD
GBPSGD
GBPUSD
NZDCAD
NZDCHF
NZDJPY
NZDUSD
SEKJPY
SGDJPY
USDCAD
USDCHF
USDCNH
USDJPY
USDSGD
USDTRY
XRPUSD
Price is 5€ per Month or 75€ lifetime. One week free for testing.
Smoothed RWI(Random Walk Index)Smoothed Random Walk Index.
It gives slightly slower but less false signal than stochastic.
If it draws double bottom with higher low, long entry is considered.
If it draws double with lower high, short entry is considered.
For more accuracy, another smoothed RWI with slower setting is needed.
If fast setting RWI draws lower high AND slower setting RWI is also going down(red color),
short entry is considered with more confidence.
Random Walk SimulationUnderstanding the Random Walk Simulation
This indicator randomly generates alternative price outcomes derived from the price movements of the underlying security. Monte Carlo methods rely on repeated random sampling to create a data set that has the same characteristics as the sample source, representing examples of alternate outcomes. The data set created using random sampling is called a “random walk”.
First, every bar in the time stamp is measured and put into a logarithmic population. Then, a sample is drawn at random from the population and is used to determine the next price movement of the random walk. This process is repeated fifteen times to visualise whether the alternative outcomes lie above or beneath the current market price of the security.
Random Walk Utility
The random walk generator allows users of the Monte Carlo to further understand how the Monte Carlo projection is generated by creating a visual representation of individual random walks. Trends that occur on the random walks may correlate to the historical price action of the underlying security.
You can find the Monte Carlo Simulator here:
Input Values
Select the “ Format ”, button located next to the indicator label to adjust the input values and the style.
The Random Walk indicator only has one user-defined input value that can be changed.
The Random_Variable randomises a set of random walks. If this variable is changed, it will run a fresh set of 15 random walks which will result in a slightly different outcome.
Adding the indicator to your chart multiple times using many different random variables will allow you to achieve a more accurate reading. Ideally, the Monte Carlo Simulator takes an average of these to be interpreted.
For more information on this indicator, the full PDF can be found here: www.kenzing.com
Monte Carlo Simulation (200 Random Walks)Understanding the Monte Carlo Simulation
This indicator uses Monte Carlo methods to predict the future price of a security using 200 random walks.
Monte Carlo methods rely on repeated random sampling to create a data set that has the same characteristics as the sample source, representing examples of alternate possible outcomes. The data set created using random sampling is called a “random walk”. Obtaining a mean from 200 random walks allows us to benchmark the performance of the source against the random walks obtained from the source.
Monte Carlo Utility
This Monte Carlo simulator plots a single line that represents 200 random walks across any security and time stamp. The line is red if most of the random walks are lower than the price of the security, and blue if the walks are higher.
Input Values
Select the “ Format ”, button located next to the indicator label to adjust the input values and the style.
The Monte Carlo indicator has only one user-defined input value that can be changed.
The Random_Variable determines set of random walks. If this variable is changed, it will run a fresh set
of 200 random walks which will result in a slightly different outcome. 200 random walks will load
relatively quick and produce roughly the same outcome as 10,000 random walks.
Adding the indicator to your chart multiple times using many different random variables will allow you
to achieve a more accurate reading.
For more information on this indicator view the PDF here: www.kenzing.com
Louis Bachelier's Random WalkSeveral tests of market efficiency have been developed over the years. The very first test, constructed by Louis Bachelier in 1900, measured the probability of a number of consecutively positive or consecutively negative price changes, or “runs.”
The randomness of runs is rejected with 95 percent statistical confidence whenever the plotted value is greater than 0. The randomness of runs cannot be rejected if it's < 0.
[GU]Shadow_RWI_v1.1Random Walk Shadow indicator. The shadow indicates the short period trend that usually will be copied by the longer trend trend.
Enjoy
Random Walk IndexRandom Walk Index indicator script. This indicator was originally developed by Michael Poulos.
As you can see, the result is very similar to the Vortex Indicator (was developed by Etienne Botes and Douglas Siepman).
