analiseTendencia: Tendency Analise

In danielfhenrique789/profitmaximization: What the package does (short line)

Tendency Analise

Description

Verify if some ticket are in a up case or down case.

Usage

analiseTendencia(obj, vFast, vSlow)

Arguments

obj
vFast
vSlow

Examples

##---- Should be DIRECTLY executable !! ----
##-- ==>  Define data, use random,
##--	or do  help(data=index)  for the standard data sets.

## The function is currently defined as
function (obj, vFast, vSlow) 
{
    tickets <- as.character(read.csv("objTickets.csv")[[1]])
    newObj <- new.env()
    for (ticket in tickets) {
        tryCatch({
            dataRange <- obj[[ticket]][!is.na(obj[[ticket]]$Adjusted), 
                ]
            if (nrow(dataRange) > vSlow) {
                ma <- SMA(dataRange$Adjusted, n = vSlow)
                mar <- SMA(dataRange$Adjusted, n = vFast)
                newObj[[ticket]] <- data.frame(dataRange[vSlow:nrow(dataRange), 
                  ]$Date, dataRange[vSlow:nrow(dataRange), ]$Adjusted, 
                  ma[vSlow:nrow(dataRange)], mar[vSlow:nrow(dataRange)])
                names(newObj[[ticket]]) <- c("Date", "Ticket", 
                  "MA.Slow", "MA.Fast")
                newObj[[ticket]]$Tendency <- ifelse((newObj[[ticket]]$MA.Slow < 
                  newObj[[ticket]]$MA.Fast), "up", "down")
            }
        }, error = function(e) {
            print("Error:")
            print(e)
        })
    }
    return(newObj)
  }

danielfhenrique789/profitmaximization documentation built on April 5, 2025, 4:05 p.m.