months will be categorized into 4 groups. 1)both 5 month and 1 month delta are positive -> bp 2) both negative -> bm 3) 5month negative and 1 month positive -> mp, and 4) 5 month positive and 1 month negative -> pm.
count # of months when index moves more than given parameter. when the prameter is (0.9,"c"), close is more than 10% lower than open. (0.85,"h"), low is more than 15% lower than high.
the sample below is to calculate # of months when price moved down more than 10% on close base. the index moves down more than 10% 8 time when both delta are minus, whereas never when both are positive.
> func(0.9,"c")
bp [1] 289
bm [1] 287
mp [1] 55
pm [1] 55
pm+bm+mp [1] 397
correction sp5 vs. bm[1] "1973-11-01" "1974-09-01" "1980-03-01" "1998-08-01" "2002-09-01" "2008-10-01" "2009-02-01" "2018-12-01"
correction sp5 vs. bpDate of length 0
correction sp5 vs. pm[1] "1987-10-01"
correction sp5 vs. mpDate of length 0
# delta is parameter relation against month close vs. open, when delta is 0.9.
# close price is 10% down from open
# when m is "c", its open vs. close. in the case of "h", it is high versus low
#
func <- function(delta=0.9,m="c"){
ind_bp <- index(na.omit(diff(cli_xts$oecd,lag=5))["1962::"])[na.omit(diff(cli_xts$oecd,lag=5))["1962::"] > 0 & na.omit(diff(cli_xts$oecd,lag=1))["1962::"] > 0]
ind_bm <- index(na.omit(diff(cli_xts$oecd,lag=5))["1962::"])[na.omit(diff(cli_xts$oecd,lag=5))["1962::"] < 0 & na.omit(diff(cli_xts$oecd,lag=1))["1962::"] < 0]
ind_mp <- index(na.omit(diff(cli_xts$oecd,lag=5))["1962::"])[na.omit(diff(cli_xts$oecd,lag=5))["1962::"] < 0 & na.omit(diff(cli_xts$oecd,lag=1))["1962::"] > 0]
ind_pm <- index(na.omit(diff(cli_xts$oecd,lag=5))["1962::"])[na.omit(diff(cli_xts$oecd,lag=5))["1962::"] > 0 & na.omit(diff(cli_xts$oecd,lag=1))["1962::"] < 0]
# sp_correction_ind <- index(SP5["1962::"][SP5["1962::"][,4] / SP5["1962::"][,1] < delta])
# sp_correction_ind <- index(SP5["1962::"][SP5["1962::"][,3] / SP5["1962::"][,2] < delta])
# if(c == "h"){ print("T")}
# if(c == "o"){ print("S")}else{print("F")}
sp_correction_ind <- c()
a <- m
# switch(a, # switch(文字列,
# "h" = append(sp_correction_ind,index(SP5["1962::"][SP5["1962::"][,3] / SP5["1962::"][,2] < delta])),
# "c" = append(sp_correction_ind,index(SP5["1962::"][SP5["1962::"][,4] / SP5["1962::"][,1] < delta])),
# print("?") # 一致するものが
# )
if(a == "h"){
sp_correction_ind <- index(SP5["1962::"][SP5["1962::"][,3] / SP5["1962::"][,2] < delta])
}
else if(a == "c"){
sp_correction_ind <- index(SP5["1962::"][SP5["1962::"][,4] / SP5["1962::"][,1] < delta])
}
else{
print("?")
}
# cat("sp_corr ");print(sp_correction_ind)
cat("bp ");print(length(ind_bp))
cat("bm ");print(length(ind_bm))
cat("mp ");print(length(ind_mp))
cat("pm ");print(length(ind_pm))
# cat("pm+bm+mp ");print(length(append(append(ind_pm,ind_bm),ind_mp)))
cat("pm+bm+mp ");print(length(c(ind_pm,ind_bm,ind_mp)))
cat("correction sp5 vs. bm");print(sp_correction_ind[is.element(sp_correction_ind,ind_bm)])
cat("correction sp5 vs. bp");print(sp_correction_ind[is.element(sp_correction_ind,ind_bp)])
cat("correction sp5 vs. pm");print(sp_correction_ind[is.element(sp_correction_ind,ind_pm)])
cat("correction sp5 vs. mp");print(sp_correction_ind[is.element(sp_correction_ind,ind_mp)])
# t.test(as.vector(VIX[,4][ind_bp]),as.vector(VIX[,4][ind_bm]))
# print("######################################")
# t.test(as.vector(VIX[,4][ind_bp]),as.vector(VIX[,4][append(append(ind_pm,ind_bm),ind_mp)]))
# # t.test(as.vector(VIX[,4][ind_bp]),as.vector(VIX[,4][ind_bm]))
}
func(0.9,"c")
