Posts (page 9)
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5 min readTo compute Ichimoku Cloud in Lua, you will need to first gather the necessary data like the high, low, and closing prices of a particular asset for a given period.Next, you can start calculating the components of the Ichimoku Cloud such as the Tenkan-sen (Conversion Line), Kijun-sen (Base Line), Senkou Span A (Leading Span A), and Senkou Span B (Leading Span B).
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5 min readIn Fortran, momentum is calculated by multiplying the mass of an object by its velocity. The formula for calculating momentum is:Momentum = Mass x VelocityTo compute momentum in Fortran, you will first need to declare variables for the mass and velocity of the object. You can then ask the user to input the mass and velocity values. Once you have obtained the input values, you can perform the calculation using the formula mentioned above.
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5 min readTo calculate the Simple Moving Average (SMA) in Kotlin, you first need to create a function that takes the list of numbers and the period as parameters. Then, iterate through the list using a for loop and calculate the sum of the numbers in the list for the specified period. Next, divide the sum by the period to get the moving average. Finally, return the moving average as the result. This function can be called whenever you need to calculate the SMA for a given set of numbers.
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5 min readIn Clojure, volume analysis refers to the study and interpretation of trading volume data in financial markets. Volume plays a crucial role in technical analysis as it provides valuable insights into market trends and price movements.Clojure, being a functional programming language, offers various tools and libraries that can be utilized for volume analysis.
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5 min readMoving averages (MA) are a commonly used technical analysis tool in the stock market to analyze trends and identify potential entry and exit points for trades. In Ruby, implementing moving averages is relatively straightforward using the built-in capabilities of the language.To calculate a simple moving average (SMA), you can create a method that takes in an array of numbers representing the closing prices of a stock over a certain period of time.
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7 min readThe Relative Strength Index (RSI) is a technical indicator used in financial market analysis to determine the momentum of a market. It is a mathematical formula that measures the magnitude of recent price changes to evaluate overbought or oversold conditions. This indicator is commonly used by traders and investors to make informed decisions on buying, selling, or holding financial assets.
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6 min readTo calculate pivot points using Python, you first need to have the high, low, and close prices of a financial instrument for a specific period. These values are used in the calculation of pivot points, which can help traders determine potential support and resistance levels in the market.The formula for calculating pivot points involves finding the average of the high, low, and close prices for the previous period, and using this value to calculate different support and resistance levels.
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6 min readTo compute Fibonacci extensions using Ruby, you can start by creating a method that calculates the Fibonacci sequence up to a certain number of terms. Once you have the sequence, you can then calculate the Fibonacci extensions by multiplying the last Fibonacci number by the Fibonacci ratios (0.618, 1, 1.618, etc.).You can store the Fibonacci sequence in an array and use that array to calculate the extensions.
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5 min readTo compute Williams %R in VB.NET, you can use the following formula:Williams %R = (Highest High - Close) / (Highest High - Lowest Low) * -100You will need to iterate through your data to calculate the Highest High and Lowest Low values, and then use these values along with the closing price to calculate the Williams %R value for each data point.[rating:e7d6ab69-30b7-47df-928e-7baf86754500]What are some common strategies for trading with Williams %R.
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6 min readThe Relative Strength Index (RSI) is a popular momentum oscillator that measures the speed and change of price movements. It is commonly used by traders to identify overbought or oversold conditions in a market.To calculate the RSI using Swift, you will need to first collect historical price data for the asset you are interested in analyzing. This data typically consists of closing prices for a specified period, such as the past 14 days.
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6 min readTo create Parabolic SAR (Stop and Reverse) in Lua, you can start by defining the variables needed for the calculation such as the acceleration factor (AF), initial and maximum AF values, and the current SAR value.Next, you can initialize the SAR value to the low of the first period and set the initial AF value. Then, loop through the price data to calculate the SAR for each period.
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9 min readIn order to calculate support and resistance levels using Golang, you can start by gathering historical price data for the asset you are analyzing. This data should include the highs, lows, and closing prices over a specific time period.Next, you can use this data to identify the key support and resistance levels. Support levels are areas where the price tends to find support as it falls, while resistance levels are areas where the price tends to find resistance as it rises.