1 Data Prep

2 Super Quadrant Stocks - Stable Algorithm

2.1 Super Quadrant Stocks : Consumer and Interest Rate Sector

2.3 New Outperform Trend

2.4 Super Quadrant Stocks : Champion Quadrant & Uptrend

2.5 Super Quadrant Stocks : Outperform Trend (Spring)

2.6 Super Quadrant Stocks : Outperform Momentum (Sunrise)

2.7 Super Quadrant Stocks : Sunset

2.8 Super Quadrant Stocks : Autumn

2.9 Super Quadrant Stocks : Champion Quadrant (Short Term Return Graphic)

2.10 Super Quadrant Stocks : Champion Quadrant (Medium Term Return Graphic)

2.11 Cluster Stocks in Champion Quadrant and Uptrend

2.11.1 Table

2.11.2 Table (cluster)

2.11.2.1 Super Quadrant Stocks : Champion Quadrant with Cluster (Short Term Return Graphic)

2.11.2.2 Super Quadrant Stocks : Champion Quadrant with Cluster (Medium Term Return Graphic)

3 General Cluster

3.1 1D, 5D, 20D & YTD Return

Table dan Grafik ini menggolongkan saham pada return 1, 5, 20 hari dan YTD (dari sejak awal tahun 2020).

3.1.1 Graph YTD - 5D

3.1.2 Graph YTD - 60D

3.1.3 Graph 60D - 20D

3.1.4 Graph 20D - 5D

3.1.5 Graph 1D - 5D

3.1.6 Table

4 Ch Turnover

5 Draft : 2 Days Comparison

6 SuperQuadrant Yesterday

6.1 Super Quadrant Stocks : Consumer and Interest Rate Sector

6.3 Super Quadrant Stocks : Champion Quadrant & Uptrend

7 Timetk

stock <- "TLKM"
stocks <- c("TLKM", "ISAT", "EXCL")

7.1 Plot Time Series

TPT.IDX %>% 
  filter(Ticker %in% stocks) %>%
  arrange(DateTime) %>% 
  filter_by_time(.start_date = "2022-10-03") %>%
  group_by(Ticker) %>% 
  plot_time_series(DateTime, Close, Ticker, .smooth = F)
## .date_var is missing. Using: DateTime

7.2 Seasonality

TPT.IDX %>% 
  # filter(Ticker == "TLKM") %>% 
  filter(Ticker %in% stock) %>% 
  arrange(DateTime) %>% 
  plot_seasonal_diagnostics(DateTime, Ch1D)

7.3 Seasonal Decomposition

TPT.IDX %>% 
  # filter(Ticker == "TLKM") %>% 
  filter(Ticker %in% stock) %>% 
  arrange(DateTime) %>% 
  plot_stl_diagnostics(DateTime, Ch1D, .feature_set = c("observed", "trend", "season",  "remainder"))
## frequency = 5 observations per 1 week
## trend = 65 observations per 3 months