AIS Money Management

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 transactions that will be modeled when the script is running. In order to get more or less significant results, it is necessary that this parameter be greater than 30.
  • Probability Winning - the probability of a winning trade. Indicated as a percentage, valid value from 1 to 99.
  • Min. StopLoss - indicates the minimum StopLoss value in points, which will be used when modeling trading operations.
  • Max. StopLoss - sets the maximum value of StopLoss in points.
  • Positive Win. - this variable establishes the amendment, with the help of which a positive expectation is obtained in the simulated transaction.
The job of the script is to do the following. First, the expected probability of a winning trade is calculated - PW. After that, randomly set the value of StopLoss, which will be used in this transaction. Considering that the expected payoff should be positive, the TakeProfit size is calculated. Taking into account the pip value, the TakeProfit and StopLoss levels are converted to the values ​​of possible profit and loss - Profit and Loss. In conclusion, the result of the transaction is determined - the win (“1”) or loss (“-1”). All data is stored in the SpecificationsTrade.csv file in the last line of which indicates the total amount of winnings in this series of transactions.
The resulting transaction values ​​are transferred to the Money management systems block, where you can select the money management systems of interest.
  • Fixed Lot - trade in a fixed lot. The results are stored in the file "FixedLot.csv". The “Bal.” Column indicates the value of the trade balance before opening a trade, and the “Rez” column indicates its result.
  • Fixed Percentage - fixed percentage trading. The simulation results are recorded in the file "FixedPercentage.csv". In the “Bal.” Column, the balance value is stored, in the “Lot” column - the lot size during the transaction, and in the “Rez” column - its result.
  • Moral Expectation - trade based on moral expectations is modeled. When modeling transactions, restrictions on the required number of transactions and the size of the trade balance are not taken into account. Due to this, it is possible to more accurately select the parameters of the trading system for trading with this money management system. The results are recorded in the file “MoralExpectation.csv”.
  • Theory Perspective - trading with the use of money management according to the theory of prospects.
  • Frac. Linear Growth - trade modeling using fractional linear growth.
  • Linear Growth - trading using the linear growth model.
  • Power Growth - modeling of power growth in trade.
  • Exponential Growth - application of the model of exponential growth.
  • Hyperbolic Growth - shows trading when using the hyperbolic growth model.
  • Hyperbolic Exponential Growth - models the use of hyperbolic-exponential growth.
A detailed description of all methods of money management is in the book Forex Money Management
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Telegram to MT4 Multi-Channel Copier automatically copies trading signals from your Telegram channels directly into MetaTrader 4. No bots, no browser extensions, no manual copying. You receive a signal on Telegram and the EA opens the trade on your terminal in a few seconds. The product includes two components: a Windows application that listens to your Telegram channels, and this Expert Advisor that executes the signals on your MT4 terminal. An MT5 version is also available. Setup guide and app
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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 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 trad
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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 is designed so that the trader can determine the average duration of trade transactions, at which the ratio of possible profits and losses will be optimal. First, let's look at the general approach to determining the optimal duration of trade transactions. We introduce the following variables: R   - the result of the transaction; T   - the time during which the transaction was open; W  - the time between the closing of the previous transaction and the opening of the next one. Every t
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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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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
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
MinDeposit
Aleksej Poljakov
5 (1)
The script analyzes the history of quotes and gives recommendations on the minimum deposit. The calculations take into account the variability of prices and the standard deviation. Margin requirements for the instrument are also taken into account. The result of the script is the minimum recommended deposit for trading the given currency pair.
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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
This script is designed so that the trader can determine the average duration of trade transactions, at which the ratio of possible profits and losses will be optimal. First, let's look at the general approach to determining the optimal duration of trade transactions. We introduce the following variables: R   - the result of the transaction; T   - the time during which the transaction was open; W - the time between the closing of the previous transaction and the opening of the next one. Every 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
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
The Cauchy distribution is a classic example of a fat-tailed distribution. Thick tails indicate that the probability of a random variable deviating from the central trend is very high. So, for a normal distribution, the deviation of a random variable from its mathematical expectation by 3 or more standard deviations is extremely rare (the 3 sigma rule), and for the Cauchy distribution, deviations from the center can be arbitrarily large. This property can be used to simulate price changes in th
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