Variable Transformations in Visual Basic QuickStart Sample
Illustrates how to perform a range of transformations on statistical data in Visual Basic.
View this sample in: C# F# IronPython
Option Infer On
Imports Extreme.Data.Text
Imports Extreme.DataAnalysis
Imports Extreme.Mathematics
Imports Extreme.Statistics
Imports Extreme.Statistics.TimeSeriesAnalysis
' Illustrates various kinds of transformations of numerical variables
' by showing how to compute several financial indicators.
Module VariableTransforms
Sub Main()
' The license is verified at runtime. We're using
' a demo license here. For more information, see
' https://numerics.net/trial-key
Extreme.License.Verify("Demo license")
' We load the data into a data frame with a DateTime row index
Dim timeSeries = DelimitedTextFile.ReadDataFrame(Of DateTime)(
"..\..\..\..\Data\MicrosoftStock.csv", "Date")
Dim open = timeSeries("Open").As(Of Double)
Dim close = timeSeries("Close").As(Of Double)
Dim high = timeSeries("High").As(Of Double)
Dim low = timeSeries("Low").As(Of Double)
Dim volume = timeSeries("Volume").As(Of Double)
'
' Arithmetic operations
'
' The NumericalVariable class defines the standard
' arithmetic operators. Operands can be either
' numerical variables or constants.
' The Typical Price (TP) is the average of the day's high, low and close:
Dim TP = (high + low + close) / 3.0
' Exponentiation is available through the ElementwisePow method,
' with special cases for square roots and reciprocals:
Dim inverseVolume = volume.Reciprocal
'
' Simple transformations
'
' The Transforms property of a numerical variable gives access
' to a large number of transformations.
' The GetLag method returns a variable whose observations
' are moved ahead by the specified amount:
Dim close1 = close.Lag(1)
' You can get cumulative sums and products:
Dim cumVolume = volume.CumulativeSum
'
' Indicators of change
'
' You can get the absolute change, percent change,
' or (exponential) growth rate of a variable. The optional
' parameter is the number of periods to go back.
' The default is 1.
Dim closeChange = close.Change(10)
' You can extrapolate the change to a longer number of periods.
' The additional argument is the number of large periods.
Dim monthyChange = close.ExtrapolatedChange(10, 20)
'
' Moving averages
'
' You can get simple, exponential, and weighted moving averages.
Dim MA20 = close.MovingAverage(20)
' Weighted moving averages can use either a fixed array or vector
' to specify the weight. The weights are automatically normalized.
Dim weights As Double() = {1.0, 2.0, 3.0}
Dim WMA3 = close.WeightedMovingAverage(weights)
' You can also specify another variable for the weights.
' In this case, the corresponding observations are used.
' For example, to obtain the volume weighted average
' of the close price over a 14 day period, you can write:
Dim VWA14 = close.WeightedMovingAverage(14, volume)
' Other statistics, such as maximum, minimum and standard
' deviation are also available.
'
' Misc. transforms
'
' The Box-Cox transform is often used to reduce the effects
' of non-normality of a variable. It takes one parameter,
' which must be between 0 and 1.
Dim bcVolume = volume.BoxCoxTransform(0.4)
'
' Creating more complicated indicators
'
' All these transformations can be combined to create
' more complicated transformations. We give some examples
' of common Technical Analysis indicators.
' The Accumulation Distribution is a leading indicator of price movements.
' It is used in many other indicators.
' The formula uses only arithmetic operations:
Dim AD = Vector.ElementwiseMultiply(
Vector.ElementwiseDivide(close - open, high - low),
volume)
' The Chaikin oscillator is used to monitor the flow of money into
' and out of a market. It is the difference between a 3 day and a 10 day
' moving average of the Accumulation Distribution.
' We use the GetExponentialMovingAverage method for this purpose.
Dim CO = AD.ExponentialMovingAverage(3) - AD.ExponentialMovingAverage(10)
' Bollinger bands provide an envelope around the price that indicates
' whether the current price level is relatively high or low.
' It uses a 20 day simple average as a central line:
Dim TPMA20 = TP.MovingAverage(20)
' The actual bands are at 2 standard deviations (over the same period)
' from the central line. We have to pass the moving average
' over the same period as the second parameter.
Dim SD20 = TP.MovingStandardDeviation(20, TPMA20)
Dim BOLU = MA20 + 2 * SD20
Dim BOLD = MA20 - 2 * SD20
' The Relative Strength Index is an index that compares
' the average price gain to the average loss.
' The GetPositiveToNegativeIndex method performs this
' calculation in one operation. The first argument is the period.
' The second argument is the variable that determines
' if an observation counts towards the plus or the minus side.
Dim change = close.Change(1)
Dim RSI = change.PositiveToNegativeIndex(14, change)
' Finally, let's print some of our results:
Dim index As Integer = timeSeries.RowIndex.Lookup(New DateTime(2002, 9, 17))
Console.WriteLine("Data for September 17, 2002:")
Console.WriteLine("Acumulation Distribution (in millions): {0:F2}", AD(index) / 1000000)
Console.WriteLine("Chaikin Oscillator (in millions): {0:F2}", CO(index) / 1000000)
Console.WriteLine("Bollinger Band (Upper): {0:F2}", BOLU(index))
Console.WriteLine("Bollinger Band (Central): {0:F2}", TPMA20(index))
Console.WriteLine("Bollinger Band (Lower): {0:F2}", BOLD(index))
Console.WriteLine("Relative Strength Index: {0:F2}", RSI(index))
Console.WriteLine("Press Enter key to continue.")
Console.ReadLine()
End Sub
End Module