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5 min readTo calculate the Relative Strength Index (RSI) in JavaScript, you can follow these steps:Gather the necessary data: You will need to collect historical price data for a specific asset or security over a chosen time period. This data typically includes the closing prices for each day. Calculate the daily price changes: For each day in the time period, subtract the closing price from the previous day's closing price to determine the daily price change.
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5 min readPivot points are technical analysis indicators used to identify potential support and resistance levels in financial markets. They are calculated based on the high, low, and close prices of a previous trading period.In Python, pivot points can be calculated using various formulas. One common method is the standard pivot point formula, which involves adding the high, low, and close prices of the previous trading day and dividing the sum by three.
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7 min readIn Lua, the Simple Moving Average (SMA) can be calculated by summing up a specified number of data points and then dividing that sum by the total number of data points. The formula for calculating the SMA is: SMA = (Sum of data points) / (Number of data points).To calculate the SMA in Lua, you would first need to create a table to store your data points. Then, you can loop through the table to sum up the specified number of data points.
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6 min readThe Average True Range (ATR) is a popular technical indicator used in trading to measure volatility. In Clojure, you can calculate the ATR by taking the average of the true ranges over a specified period. The true range is the maximum of three values: the distance between the current high and low, the absolute value of the current high minus the previous close, and the absolute value of the current low minus the previous close.
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4 min readThe Chaikin Money Flow (CMF) is a technical analysis tool that measures the buying and selling pressure of a security over a specific period of time. It is based on the accumulation/distribution line and is often used to confirm trends and spot potential reversal points.In F#, you can implement the CMF calculation by first calculating the Money Flow Multiplier, which is calculated by multiplying the [(Close - Low) - (High - Close)] by the volume of the security.
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7 min readVolume analysis is a technique used in TypeScript to understand and analyze the codebase in terms of its complexity and size. By examining the volume of code, developers can gain insights into potential issues such as high complexity, redundancy, and maintenance challenges. This analysis can help developers make informed decisions about refactoring, optimizing, and improving the codebase for better performance and maintainability.
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5 min readTo compute Fibonacci extensions using Lisp, you first need to define a recursive function to calculate the Fibonacci numbers. This function can be defined using a simple if-else statement to handle the base cases (fibonacci of 0 and 1) and recursively calculate the Fibonacci numbers for other input values.Once you have this function defined, you can use it to calculate the Fibonacci numbers for the desired input values.
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7 min readCreating Ichimoku Cloud using Swift involves implementing the mathematical calculations behind the Ichimoku indicator. This involves calculating the nine-period high and low, as well as the conversion line, base line, and leading span. These calculations can be done using the historical price data of a financial instrument.Once the calculations are done, the Ichimoku Cloud can be plotted on a chart using a library or custom drawing code in Swift.
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5 min readTo calculate the Parabolic SAR (Stop and Reverse) in JavaScript, you can use the formula provided by Welles Wilder Jr. The Parabolic SAR is a technical indicator used to determine potential reversals in the price movement of an asset. It is based on the idea that a trailing stop-and-reverse trading signal is generated when the price intersects the SAR line.To calculate the Parabolic SAR, you first need to determine the initial SAR value.
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3 min readSupport and Resistance levels are key concepts in technical analysis used to identify potential price levels where the market may reverse its direction. In Lua, these levels can be calculated using historical price data and plotted on a chart to help traders make informed decisions. Traders can use these levels to identify potential entry and exit points for their trades, as well as to set stop-loss and take-profit orders.
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5 min readTo create Rate of Change (ROC) in Groovy, you can calculate it by taking the difference between the current value and the previous value, and then dividing it by the previous value. This calculation is commonly used in financial analysis to measure the speed at which a variable is changing over a specific period of time. By implementing this calculation in Groovy, you can easily track the rate of change of any data set or variable within your application.