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AIS Evil and Odious Numbers

30 USD

Demo downloaded: 2

Published: 19 June 2022

Current version: 1.0

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AIS Evil and Odious Numbers

Indicators
Aleksej Poljakov
Aleksej Poljakov
Russia

20944
4.7 (7)
92 products 28 articles 11 codes 72 comments
Version: 1.0
Activations: 5

This indicator uses the so-called "evil" numbers as weights. Their opposite is "odious" numbers, which are also presented in this indicator. The division of numbers into these two classes is associated with the Hamming weight, which is determined by the number of units in the binary notation of a particular number.

Using these numbers as weighting factors results in a trend-following indicator. Moreover, odious numbers give a more sensitive indicator, and evil numbers give a conservative one. The difference between them is not very large, and can be noticeable only with a sharp price movement in the market. The use of this indicator can help in determining the start of a new trend. This makes it possible to more accurately determine the moments of opening positions.

Indicator parameters:

Type numbers - choice of number type, Evil or Odious;
iPeriod - indicator period. The sensitivity of the indicator depends on this parameter. The smaller it is, the higher the sensitivity to price changes and changes in market trends.

Examples of the indicator operation are shown in the figures.

more...

Screenshot #1 AIS Evil and Odious Numbers

Screenshot #2 AIS Evil and Odious Numbers

Screenshot #3 AIS Evil and Odious Numbers

Screenshot #4 AIS Evil and Odious Numbers

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Screenshot #7 AIS Evil and Odious Numbers

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Choosing the levels of StopLoss and TakeProfit can have a very strong impact on the overall performance of trading. In addition to the obvious parameters of a trade transaction - the size of a possible win or probable loss - the levels of StopLoss and TakeProfit also affect the expected duration of the transaction, and the profitability of trading in general. If you have already determined the optimal transaction duration using the “ AIS-ODT ” script, then you can begin to determine the paramete

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This script allows selecting the TakeProfit and StopLoss levels. It analyzes the history data, and then calculates the probability of reaching a given price level. How the script works Suppose you have a trading strategy and you want to select the TakeProfit and StopLoss levels. Run the script and set the parameter: Number of Bars - the average position holding time in bars. Once the script operation is complete, the AIS-PPL.csv file will be created in the Files folder in the terminal data cata

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This script allows selecting the TakeProfit and StopLoss levels. It analyzes the history data, and then calculates the probability of reaching a given price level. How the script works Suppose you have a trading strategy and you want to select the TakeProfit and StopLoss levels. Run the script and set the parameter: Number of Bars - the average position holding time in bars. Once the script operation is complete, the AIS-PPL.csv file will be created in the Files folder in the terminal data cata

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The indicator is designed to measure the price volatility. This allows determining the moments for opening or closing trade positions more accurately. High intensity of the market indicates the instability of its movement, but allows for better results. And, conversely, low intensity of the market indicates the stability of its movement. Parameters Bars to process - the number of bars to measure the price movements. A low value of this parameter allows determining the moments of rapid price mov

This indicator uses the Fibonacci p-numbers to smooth a price series. This allows combining the advantages of the simple and exponential moving averages. The smoothing coefficients depend on the level of the p-number, which is set in the indicator parameters. The higher the level, the greater the influence of the simple moving average and the less significant the exponential moving average. Parameters Fibonacci Numbers Order - order of the Fibonacci p-number, specified by trader. Valid values a

The indicator is based on the analysis of interaction of two filters. The first filter is the popular Moving Average. It helps to identify linear price movements and to smooth minor price fluctuations. The second filter is the Sliding Median. It is a non-linear filter. It allows to filter out noise and single spikes in the price movement. A predictive filter implemented in this indicator is based on the difference between these filters. The indicator is trained during operation and is therefore

This indicator studies the price action as a combination of micro-trends. All micro-trends are analyzed and averaged. Price movement is filtered based on this averaging. IP_High and IP_Low (blue and red dashed lines) show the instantaneous price movement. They display the forecast only for the current price values, taking into account only the number of bars defined by the 'Filter level' parameter. SP_High and SP_Low (blue and red solid lines) smooth the price movements with respect to history.

The script allows selecting the required 'Filter level' value of the AIS-MTF indicator. Run the script on the required chart and selected timeframe. Once its operation is complete, the HPS.csv file will be created in the Files folder. Open the file. You will see three columns. The 'Filter lvl' column represents the value of the 'Filter level' for the AIS-MTF indicator. Am. dev. - degree and direction of the indicator's deviation from the price level (sorted in ascending order). Negative values i

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This indicator implements the process of simple linear smoothing. One of the disadvantages of exponential smoothing is the rapid attenuation of the signal. This does not allow for a full-fledged monitoring of long-term tendency of a price series. Linear smoothing allows fine-tuning the signal filtering. The indicator is configured by selecting the parameters: LP - period of smoothing. The higher the value, the more long-term tendencies are displayed by the indicator. Valid values are from 0 to 2

Этот индикатор представляет гибридный фильтр основанный на совместном использовании медианы и скользящей средней. Использование медианы позволяет отфильтровывать аномальные выбросы и случайные импульсы в значениях ценового ряда. При этом на трендовую составляющую медианный фильтр не действует, оставляя ее без изменений. Так как медианный фильтр является нелинейным, то для сглаживания его значений используется скользящая средняя. Такой подход позволяет более точно выделять не только тренд, но и п

This indicator is a combination of two modified Lanczos filters. The first filter serves to extrapolate the price. Based on past values, he predicts a possible price movement within the current bar. That is, it shows what the price would be if the past trends remained unchanged. The second filter for smoothing and averaging prices within the window, determined by the level of the filter. Thanks to the selection of weights, this filter is most actively responding to the periodic component that is

The script is based on the simulation of trade transactions using a random number generator. This allows you to get completely different results, even with the same input parameters. When you run the script, a dialog box opens in which you can set the desired values for external variables. In the Trading options block, the basic parameters that are necessary for trading modeling are defined. Start Balance - sets the initial size of the trade balance. Number Trade - sets the number of trade tr

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Let's look at the nature of price changes in the Forex market, not paying attention to the reasons why these changes occur. This approach will allow us to identify the main factors affecting the price movement. For example, let's take the opening prices of bars on the EUR-USD currency pair and the H1 timeframe. For these prices, we construct the Lameray diagram (Figure 1). In this diagram, it can be seen that the price movement basically occurs according to a linear equation. To determine the pa

Choosing the levels of StopLoss and TakeProfit can have a very strong impact on the overall performance of trading. In addition to the obvious parameters of a trade transaction - the size of a possible win or probable loss - the levels of StopLoss and TakeProfit also affect the expected duration of the transaction, and the profitability of trading in general. If you have already determined the optimal transaction duration using the “ AIS-ODT ” script, then you can begin to determine the paramete

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This indicator is more informative. His work is based on the assumption that the price movement in the market can be represented as noise of a particular color, which depends on the parameters of the distribution of price values. Thanks to this, it is possible to analyze the price change from different angles, and considering the price movement as noise of a particular color, one can get information about the current state of affairs in the market and make a forecast about the price behavior. W

Despite some drawbacks of the “ AIS Color Noise Filter ” indicator, the idea to use it to smooth the price series and forecast prices looks quite attractive. This is due to several reasons: first, taking into account several noise components allows building a forecast on factors independent of each other, which can improve the quality of forecasting; secondly, the noise characteristics of the price series behave quite stably throughout the entire history, which makes it possible to obtain stabl

Very often, in the study of financial series apply their smoothing. Using smoothing, you can remove high-frequency components - it is believed that they are caused by random factors and therefore irrelevant. Smoothing always includes some way of averaging the data, in which random changes in the time series mutually absorb each other. Most often, for this purpose, simple or weighted moving average methods are used, as well as exponential smoothing. Each of these methods has its advantages and d

In order to isolate long-term and non-random components, it is necessary to know not only how much the price has changed, but also how these changes occurred. In other words - we are interested not only in the values of price levels, but also in the order in which these levels replace each other. Through this approach, one can find long-term and stable factors that influence (or may influence) the price change at a given point in time. And knowledge of these factors allows you to make a more

One of the powerful methods of analysis is the modeling of financial series using Levy processes. The main advantage of these processes is that they can be used to model a huge number of phenomena - from the simplest to the most complex. Suffice it to say that the idea of the fractal price movement in the market is only a special case of Levy processes. On the other hand, with proper selection of parameters, any Levy process can be represented as a simple moving average. Figure 1 shows an exa

Very often, the trader is faced with the task of determining the extent to which the price may change in the near future. For this purpose, you can use the Johnson distribution type SB. The main advantage of this distribution is that it can be used even with a small amount of accumulated data. The empirical approach used in determining the parameters of this distribution, allows you to accurately determine the maximum and minimum levels of the price channel. These values can be used in differ

This indicator allows you to determine the likelihood that the price will reach one or another level. Its algorithm is quite simple and is based on the use of statistical data on the price levels of a particular currency pair. Thanks to the collected historical data, it is possible to determine the extent to which the price will change during the current bar. Despite its simplicity, this indicator can provide invaluable assistance in trading. So, with its help it is possible to determine TakePr

Stable distributions can be used to smooth financial series. Since a fairly deep history can be used to calculate the distribution parameters, such smoothing may in some cases be even more effective than other methods. The figure shows an example of the distribution of the opening prices of the currency pair " EUR-USD " on the time frame H1 for ten years (figure 1). Looks fascinating, doesn't it? The main idea behind this indicator is to determine the parameters of a stable distribution based

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