@@ -1895,6 +1895,113 @@ if(exists('fl')) rm(fl)
18951895
18961896## Intraday Seasonal Data  
18971897
1898+ 
1899+ ### 20Hr >> 1min  
1900+ 
1901+ I set the length of data as Daily (` 1200 mins `  which is 1 trading days) to forecast ` 1 min `  in advance.
1902+ 
1903+ ``` {r,  eval = FALSE}
1904+ # --------- eval=FALSE --------- 
1905+ ets.m <- 'MNN' 
1906+ source('function/intra_min.R') 
1907+ 
1908+ timeID <- unique(dsmp$date) 
1909+ bse <- dsmp[year == 2016]$date[1] #"2016-01-04" #1st trading date in 2nd year 
1910+ timeID %<>% .[. >= bse] 
1911+ #timeID %<>% .[. >= as_date('2016-01-04')] 
1912+ data_len <- 1200 
1913+ hrz1 <- 1 
1914+ 
1915+ llply(ets.m, function(md) { 
1916+   intra_min(timeID = timeID, dsmp,  
1917+             data_len = data_len, hrz1 = hrz1,  
1918+             .model = md) 
1919+   }) 
1920+ ``` 
1921+ 
1922+ ``` {r  18hr-1min, warning = FALSE, message = FALSE, results = 'asis'}
1923+ #```{r, warning = FALSE, message = FALSE, results = 'asis'} 
1924+ fl <- list.files(paste0(.dtr, 'data/fx/USDJPY/intraday/'), pattern = '^ts_ets_MNN_1200_1.p_[0-9]{0,}.[0-9]{4}')[1:6] 
1925+ #smp <- readRDS(paste0(.dtr, 'data/fx/USDJPY/intraday/', fl)) 
1926+ 
1927+ if(all(is.na(fl))){ 
1928+   smp <- NA 
1929+ 
1930+ } else { 
1931+   smp <- ldply(fl, function(x) { 
1932+     readRDS(paste0(.dtr, 'data/fx/USDJPY/intraday/', x)) 
1933+   }) 
1934+    
1935+   smp %>%  
1936+     kbl(caption = 'Data Sample (ETS MNN 1200 forecast 1)', escape = FALSE) %>%  
1937+     row_spec(0, background = 'DimGrey', color = 'yellow') %>%  
1938+     column_spec(1, background = '#556DAC') %>%  
1939+     column_spec(2, background = 'Gainsboro', color = 'goldenrod') %>%  
1940+     column_spec(3, background = 'LightGray', color = 'goldenrod') %>%  
1941+     kable_styling(bootstrap_options = c('striped', 'hover', 'condensed', 'responsive')) %>%  
1942+     kable_material(full_width = FALSE) %>%  
1943+     scroll_box(width = '100%', fixed_thead = TRUE) 
1944+ } 
1945+ ``` 
1946+ 
1947+ ``` {r  include = FALSE}
1948+ if(exists('smp')) rm(smp) 
1949+ if(exists('fl')) rm(fl) 
1950+ ``` 
1951+ 
1952+ ### 18Hr >> 1min  
1953+ 
1954+ I set the length of data as Daily (` 1080 mins `  which is 1 trading days) to forecast ` 1 min `  in advance.
1955+ 
1956+ ``` {r,  eval = FALSE}
1957+ # --------- eval=FALSE --------- 
1958+ ets.m <- 'MNN' 
1959+ source('function/intra_min.R') 
1960+ 
1961+ timeID <- unique(dsmp$date) 
1962+ bse <- dsmp[year == 2016]$date[1] #"2016-01-04" #1st trading date in 2nd year 
1963+ timeID %<>% .[. >= bse] 
1964+ #timeID %<>% .[. >= as_date('2016-01-04')] 
1965+ data_len <- 1080 
1966+ hrz1 <- 1 
1967+ 
1968+ llply(ets.m, function(md) { 
1969+   intra_min(timeID = timeID, dsmp,  
1970+             data_len = data_len, hrz1 = hrz1,  
1971+             .model = md) 
1972+   }) 
1973+ ``` 
1974+ 
1975+ ``` {r  18hr-1min, warning = FALSE, message = FALSE, results = 'asis'}
1976+ #```{r, warning = FALSE, message = FALSE, results = 'asis'} 
1977+ fl <- list.files(paste0(.dtr, 'data/fx/USDJPY/intraday/'), pattern = '^ts_ets_MNN_1080_1.p_[0-9]{0,}.[0-9]{4}')[1:6] 
1978+ #smp <- readRDS(paste0(.dtr, 'data/fx/USDJPY/intraday/', fl)) 
1979+ 
1980+ if(all(is.na(fl))){ 
1981+   smp <- NA 
1982+ 
1983+ } else { 
1984+   smp <- ldply(fl, function(x) { 
1985+     readRDS(paste0(.dtr, 'data/fx/USDJPY/intraday/', x)) 
1986+   }) 
1987+    
1988+   smp %>%  
1989+     kbl(caption = 'Data Sample (ETS MNN 1080 forecast 1)', escape = FALSE) %>%  
1990+     row_spec(0, background = 'DimGrey', color = 'yellow') %>%  
1991+     column_spec(1, background = '#556DAC') %>%  
1992+     column_spec(2, background = 'Gainsboro', color = 'goldenrod') %>%  
1993+     column_spec(3, background = 'LightGray', color = 'goldenrod') %>%  
1994+     kable_styling(bootstrap_options = c('striped', 'hover', 'condensed', 'responsive')) %>%  
1995+     kable_material(full_width = FALSE) %>%  
1996+     scroll_box(width = '100%', fixed_thead = TRUE) 
1997+ } 
1998+ ``` 
1999+ 
2000+ ``` {r  include = FALSE}
2001+ if(exists('smp')) rm(smp) 
2002+ if(exists('fl')) rm(fl) 
2003+ ``` 
2004+ 
18982005### 16Hr >> 1min  
18992006
19002007I set the length of data as Daily (` 960 mins `  which is 1 trading days) to forecast ` 1 min `  in advance.
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