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joshuaulrich avatar joshuaulrich commented on August 23, 2024 1

Thanks! I just noticed that you're checking whether two numbers are exactly equal (x[1] != x[2]). That's subject to floating point precision error (see FAQ 7.31). Use this instead:

num_diff <- function(x) { abs(diff(x)) > sqrt(.Machine$double.eps) }
(last_row_from_window500)[apply(TwolastRows, 2, num_diff)]

Once you do that, very few of the final indicator values are different. Here are the results using all 40-ish indicators:

print(diffs <- last_row_from_window500[apply(TwolastRows, 2, num_diff)])
##                      ADX.ADX chaikinAD   obv   SMI.SMI SMI.signal williamsAD
## 1999-12-31 23:59:59 35.06024 -4886.041 -2129 -55.81354  -49.64856      -1.43

TwolastRows[, colnames(diffs)]
##                       ADX.ADX chaikinAD   obv   SMI.SMI SMI.signal williamsAD
## 1999-12-31 23:59:59  35.06024 -4886.041 -2129 -55.81354  -49.64856      -1.43
## 1999-12-31 23:59:591 35.06024 -2925.638  -124 -55.81354  -49.64856      -0.55

So it looks like only chaikinAD(), OBV(), and williamsAD() are different. All 3 of those functions use the cumulative sum of the series, so it makes sense that they would be different depending on the start of the series. That's not something I can fix.

ADX and SMI look close and are probably just a bit smaller than floating point precision error.

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mytarmail avatar mytarmail commented on August 23, 2024 1

Thank you! You are amazing!!

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joshuaulrich avatar joshuaulrich commented on August 23, 2024

Your example has almost 40 indicators. Can you please provide a minimal example with the indicators you think have an issue?

Your comment says that the SMA() result is different based on the number of observations in the window. That's extremely unlikely. Also note that recursive indicators like EMA() and indicators that use them (e.g. RSI()) are unlikely to have the same values for different window sizes. See the Warning section in ?TTR::MovingAverages.

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mytarmail avatar mytarmail commented on August 23, 2024

Your example has almost 40 indicators. Can you please provide a minimal example with the indicators you think have an issue?

Your comment says that the SMA() result is different based on the number of observations in the window. That's extremely unlikely. Also note that recursive indicators like EMA() and indicators that use them (e.g. RSI()) are unlikely to have the same values for different window sizes. See the Warning section in ?TTR::MovingAverages.

Hi!
Here is a shorter example where all three indicators work differently on different windows

library(xts)
library(quantmod)
library(TTR)
n <- 100000
set.seed(1)
#######################################
#########  make some prices ###########
#######################################
volume <- sample(1:10,n,replace = TRUE,prob = c(10:1))
prices <- round(cumsum(rnorm(n,sd = 0.01)),2)+1000

p <-  cbind(price = prices, volume = volume) |> 
  xts(as.POSIXct("2000-01-01 00:00:00 EET")-n:1) |> 
  to.minutes(name = "my") 
colnames(p) <- gsub("^my\\.", "", colnames(p))

############################################################
#########  function for calculate all indicators ###########
############################################################

MINI_get_all_indicators <- function(p, n= 10){
  CLOSE <- quantmod::Cl(p)
  OHLC <-  quantmod::OHLC(p)
  HLC <-   quantmod::HLC(p)
  HL <-    quantmod::HL(p)
  VOLUME <- quantmod::Vo(p)
  
  data.frame(
    stoch = TTR::stoch(HLC = HLC, nFastK = n, nFastD = n, nSlowD = n*2),
    TRIX =  TTR::TRIX(price = CLOSE, n = n),
    williamsAD = TTR::williamsAD(HLC = HLC)
  )
}

############################################################
######### Making a comparison on different windows #########
############################################################

last_row_from_window500 <- tail(p,500) |> MINI_get_all_indicators(n = 10) |> tail(1)
last_row_from_window200 <- tail(p,200) |> MINI_get_all_indicators(n = 10) |> tail(1)


TwolastRows <- rbind.data.frame(last_row_from_window500,
                                last_row_from_window200)
#print(TwolastRows)

# Which indicators do not correspond to each other
colnames(last_row_from_window500)[  apply(TwolastRows,2, \(x)  x[1]!=x[2]) ]

[1] "stoch.slowD" "TRIX.signal" "williamsAD"

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