AIS Fibonacci P Numbers

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 are in the range of 0 - 255.

After the indicator is launched, the "Fibonacci p-number level" and the length of the series used to calculate the indicator values ("Length of a number series") are displayed in the Experts tab. The length of the calculated series depends on the number of decimal places in the quotes of the currencies. For 5-digit quotes, the accuracy of calculations is higher, so the length of the series will be greater.

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AIS Correct Averages indicator allows you to determine the beginning of the trend movement in the market. Another important quality of the indicator is a clear signal of the end of the trend. The indicator is not redrawn or recalculated. Displayed values h_AE - the upper limit of the AE channel l_AE - the lower boundary of the AE channel h_EC - High value projected for the current bar l_EC - Low predicted value for the current bar Signals for the indicator The main channel signal is the inters
The AIS Weighted Moving Average indicator calculates weighted moving average, allowing to determine the beginning of market trend. Weights are calculated taking into account the specific characteristics of each bar. This allows filtering random market movements. The main signal, confirming the beginning of a trend, is change in the direction of indicator line movement and the intersection of the indicator lines with the indicator price. WH (blue line) - the weighted average High price. WL (red l
The AIS Advanced Grade Feasibility indicator is designed for forecasting levels that a price can reach in future. Its operation is based on the analysis of the last three bars and creating the forecast. The indicator can be used on any timeframe and any currency pair. Using settings, you can achieve the desired quality of the forecast. Depth of forecast - sets the desired depth of forecast in bars. The recommended values for these parameters are 18-31. You can try beyond this range. But in this
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
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
When making trading decisions, it is useful to rely not only on historical data, but also on the current market situation. In order to make it more convenient to monitor current trends in market movement, you can use the AIS Current Price Filter  indicator. This indicator takes into account only the most significant price changes in one direction or another. Thanks to this, it is possible to predict short-term trends in the near future - no matter how the current market situation develops, soon
When analyzing financial time series, researchers most often make a preliminary assumption that prices are distributed according to the normal (Gaussian) law. This approach is due to the fact that a large number of real processes can be simulated using the normal distribution. Moreover, the calculation of the parameters of this distribution presents no great difficulties. However, when applied to financial markets, normal distribution does not always work. The returns on financial instruments of
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