Rolling exponentially weighted standard deviation pandas
ROLLING EXPONENTIALLY WEIGHTED STANDARD DEVIATION PANDAS CODE
In a few lines of code we can express the basic technical indicators, if you like this explonation check my library on github. We can also use MAPE but it’s not comutative and have a problem near zero. Return Math.sqrt(mean(sqrDiff)) / (Math.max(.f) - Math.min(.f)) Let sqrDiff = pointwise((a, b) => (a - b) * (a - b), f, g) There are various ways of determining the measure of error between the two functions but in this case the normalized mean square error is better fit because it is dimensionless quantity in contrast to RMSE and it is relative.įor example, bitcoin can cost $20,000 and a difference in $10 is small, while when entire altcoin can cost $1 and difference in $10 is huge. If we have accurate tables of indicator values we can precisely test our calculation. Here correlation matrix of different cryptoassets in 2 month. Return (Efg - Ef * Eg) / Math.sqrt((Ef2 - Ef * Ef) * (Eg2 - Eg * Eg))
Let Efg = mean(pointwise((a, b) => a * b, f, g)) Let Eg2 = mean(pointwise((a) => a * a, g)) Let Ef2 = mean(pointwise((a) => a * a, f)) If you intrested in long term investition and portfolio analysis you will find usefull the correlation matrix. Where mean is operation that calculates the average of array and rolling is the combination of the window function that for each existing element in the array produces an array of the last n elements and the operation that folds this window into a number.įunction rolling(operation, window, array) Return rolling(x => mean(x), window, $close) For example, the moving average it is just the average of each value of the rolling window. When coding indicators, it is very convenient to use functional approach. It is not uncommon for indicators to use different filtering, minimums and maximums or other indicators as a basis for subsequent calculations. Most often technical indicators are a window function, recursive function or weighted function of prices/volumes that is pulled from the stock exchange in the UOHLCV format (unix time, open, high, low, close, volume). If you want to implement a trading strategy or indicators by yourself.You are planning to write a trading bot.But how are they actually works? And to whom it can be useful? But they greatly improve my trading ability, while displaying alot of important data. You may have heard the opinions that they don’t work. Open source, Финансы в IT, Математика, Статистика в ITĪnyone, who has ever been interested in stocks or cryptocurrencies has seen these additional lines on charts.