Most Important MMD Chart Data Science
MM Dandytra, CFTe
Halo Investor dan Trader,
Halaman ini berisi Raw Information dari Technical Analysis ala Muhamad Makky Dandytra, CFTe untuk MMD Charts.
## [1] "Based on Trading Date 07 November 2022"Untuk informasi lengkap, silahkan kunjungi website https://www.mmdcharts.com.
Semoga berguna dan bermanfaat.
1 Graphic Stocks
1.1 Stocks with High Turnover (IDX Sector)
1.2 Stocks with High Turnover and Buy Signs
1.3 Stocks with Positive Change of Turnover
1.4 Stocks with Positive Change of Turnover (Trend)
1.5 Stocks with Trend and Momentum (Best Area only)
2 Graphic IDXSectors
2.1 IDXSector in Trend and Momentum
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Trend dan Stoch. Oscillator.
2.2 IDXIndustry in Trend and Momentum
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Trend dan Stoch. Oscillator.
2.3 IDXIndustry in Trend and Momentum (Best Area Only)
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Trend dan Stoch. Oscillator.
2.3.1 Table
2.4 IDXIndustry in Trend and Momentum (Infra Only)
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Trend dan Stoch. Oscillator.
2.5 IDXSector in Foreign Net Buy 5D Positive
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Net Buy Asing yang positif dalam 5 hari.
2.6 IDXIndustry in Foreign Net Buy 5D Positive
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Net Buy Asing yang positif dalam 5 hari.
2.7 IDXIndustry in Foreign Net Buy 5D Positive (Infra Only)
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Net Buy Asing yang positif dalam 5 hari.
2.8 IDXSector in 1D, 5D and 20D % Change
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Rata - Rata Pergerakannya dalam 1D, 5D dan 20D.
2.9 IDXIndustry in 1D, 5D and 20D % Change
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Rata - Rata Pergerakannya dalam 1D, 5D dan 20D.
2.10 IDXIndustry in 1D, 5D and 20D % Change (Infra Only)
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Rata - Rata Pergerakannya dalam 1D, 5D dan 20D.
2.11 IDXSector in Change Turnover 1D and 5D
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Rata - Rata Pergerakannya dalam 1D, 5D dan 20D.
2.12 IDXIndustry in Change Turnover 1D and 5D
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Rata - Rata Pergerakannya dalam 1D, 5D dan 20D.
2.13 IDXIndustry in Change Turnover 1D and 5D (Infra Only)
Grafik ini menampilkan Sektor dan Relasinya-nya dengan Rata - Rata Pergerakannya dalam 1D, 5D dan 20D.
3 SUPER QUADRANT STOCKS
3.1 SUPER QUADRANT STOCKS - Seluruh Sektor
Grafik Super Quadrant Stocks ini menampilkan Trend dan Sinyal dibagi per Sektor.
3.2 SUPER QUADRANT STOCKS - Seluruh Sektor dan sinyal Buy
Grafik Super Quadrant Stocks ini menampilkan Trend dan sinyal Buy dibagi per Sektor.
3.3 SUPER QUADRANT STOCKS - Outperform Trend dan Uptrend
Grafik Super Quadrant Stocks ini hanya menampilkan Saham dalam Outperform Trend dan Uptrend - dibagi berdasarkan Sektor.
3.4 SUPER QUADRANT STOCKS - Outperform Trend, Uptrend dan Sinyal Buy
Grafik Super Quadrant Stocks ini hanya menampilkan Saham dalam Outperform Trend dan Uptrend dengan sinyal Buy - dibagi berdasarkan Sektor.
3.5 SUPER QUADRANT STOCKS - Champion Quadrant dan Uptrend
Grafik Super Quadrant Stocks ini hanya menampilkan Saham dalam Champion Quadrant dan Uptrend - dibagi berdasarkan Sektor.
3.6 SUPER QUADRANT STOCKS - Champion Quadrant, Uptrend dan sinyal Buy
Grafik Super Quadrant Stocks ini hanya menampilkan Saham dalam Champion Quadrant dan Uptrend dengan sinyal Buy - dibagi berdasarkan Sektor.
3.7 SUPER QUADRANT STOCKS - TOP STOCKS FROM SUPER QUADRANT
4 Standard Graphic Stocks
4.1 1D and 5D Return Saham Outperform Trend dan Uptrend
4.2 5D and 20D Return Saham Outperform Trend dan Uptrend
4.3 5D and 20D Return TOP STOCKS FROM SUPER QUADRANT
4.4 YTDCh and Ch60D Return TOP STOCKS FROM SUPER QUADRANT
4.5 1D and 5D Return Saham dalam Champion Quadrant and Uptrend
4.6 1D Change of Price and Turnover dari Saham Outperform Trend dan Uptrend
5 Ch Turnover
5.1 Consumer Related
5.2 Infrastructure Related
5.3 Multiple Line Chart (draft)
# TPT.IDX
#
# TPT %>%
# filter(KairiMABB20 > 0, KairiMABB60 > 0, KairiMABB200 > 0) %>%
# arrange(DateTime, Ticker) %>%
# select(Ticker, Close, Ch1D, Ch5D, Ch20D, YTDRet) %>%
# ggplot(aes(x = DateTime))+
# geom_bar(aes(y = Ch1D))+
# facet_wrap(~ Ticker, ncol = 5)6 Cluster
6.1 1D, 5D, 20D & YTD Return
Table dan Grafik ini menggolongkan saham pada return 1, 5, 20 hari dan YTD (dari sejak awal tahun 2020).
6.1.1 Graph YTD - 5D
6.1.2 Graph YTD - 60D
6.1.3 Graph 60D - 20D
6.1.4 Graph 20D - 5D
6.1.5 Graph 1D - 5D
6.1.6 Table
7 Data Explorer (Draft)
head(TPT)## Ticker Close DateTime Trend SO SOSignal Ch1D YestCh Ch5D Ch20D
## 1 ISAT 6800 2022-11-07 Uptrend 52.95 Alert Buy 1.49 -1.83 0.37 -0.73
## 2 MIKA 2750 2022-11-07 Downtrend 56.39 Still Buy 0.00 3.00 -0.36 -1.43
## 3 CMRY 4750 2022-11-07 Uptrend 21.50 Still Sell 0.85 -1.88 2.81 8.20
## 4 UNVR 4620 2022-11-07 Downtrend 55.90 Still Buy 1.76 0.67 -0.43 -3.75
## 5 MYOR 2420 2022-11-07 Uptrend 84.44 Still Buy 0.00 3.42 0.83 17.48
## 6 BBTN 1535 2022-11-07 Uptrend 62.50 Warning Sell 0.00 0.66 -0.65 2.68
## Ch60D YTDRet Volume ChTurnover ChTurnover5D AvgCondition RCTrend
## 1 -7.48 9.68 Above Previous 0.05 -0.82 Low TO O/P Trend
## 2 5.36 21.68 --- -0.61 -0.82 High TO U/P Trend
## 3 11.76 39.71 Above Previous 0.56 -0.77 Low TO O/P Trend
## 4 -3.14 12.41 Above Previous 0.03 -0.77 High TO U/P Trend
## 5 29.07 18.63 --- -0.34 -0.74 Low TO O/P Trend
## 6 -5.54 -11.27 --- -0.21 -0.67 Low TO U/P Trend
## RCMomentum RCTrendSignal RCMomentumSignal KairiMABB20 KairiMABB60
## 1 O/P Momentum --- O/P Momentum Signal 1.51 -2.75
## 2 U/P Momentum --- U/P Momentum Signal -4.19 1.20
## 3 U/P Momentum --- --- 2.81 7.53
## 4 O/P Momentum --- --- -7.87 -3.53
## 5 U/P Momentum --- U/P Momentum Signal 3.49 20.66
## 6 U/P Momentum U/P Trend Signal U/P Momentum Signal -0.16 0.62
## KairiMABB200 Prev.KairiMABB200 OP.Trend.Start BB Bandwidth F1D F2D
## 1 6.33 5.65 --- 73.45 13.67 0 -0.99
## 2 5.70 6.65 --- 29.83 12.74 0 -21.94
## 3 17.50 17.60 --- 80.33 14.87 0 -1.08
## 4 2.99 2.05 --- 26.32 26.63 0 1.38
## 5 27.73 28.79 --- 69.53 26.48 0 -1.00
## 6 -5.64 -4.96 --- 68.16 8.29 0 1.33
## F1Wk F1Mo MTTrend WkESOValue WkESO PriceVolumeCond Last1DPVCond
## 1 -8.83 -76.68 Downtrend 33.77 Still Buy Real + Real -
## 2 -76.24 -157.75 Uptrend 31.27 Alert Buy --- Fake +
## 3 -3.02 21.94 Uptrend 40.00 Still Buy Real + fake -
## 4 -143.66 -35.21 Downtrend 18.34 Alert Buy Real + Real +
## 5 21.65 17.04 Uptrend 86.38 Still Sell --- Fake +
## 6 0.03 38.35 Uptrend 73.41 Still Sell --- Real +
## Last2DPVCond RC.JKSE MA.RC RC.BB PrevRC.BB Corr20D Corr60D Corr5D KairiMA20
## 1 Real - 957.42 943.18 62.23 55.56 0.43 0.67 -0.32 3.11
## 2 Fake + 387.19 404.13 19.81 23.43 -0.02 -0.62 0.77 -2.64
## 3 fake - 668.79 650.53 73.66 75.78 0.68 -0.33 -0.30 4.32
## 4 Real + 650.48 706.02 20.92 15.74 0.00 -0.45 0.98 -6.73
## 5 Fake + 340.73 329.23 65.29 70.65 0.75 -0.58 0.57 4.92
## 6 Real + 216.12 216.47 46.04 66.91 0.92 0.70 0.19 1.48
## KairiMA60 KairiMA200 MA20Direction MA60Direction MA200Direction LTTrend
## 1 -2.81 7.58 -2.5 -9.17 4.25 Uptrend
## 2 1.30 7.10 -2.0 2.33 3.00 Uptrend
## 3 7.08 16.37 18.0 8.33 6.35 ---
## 4 -3.55 4.72 -9.0 -2.50 2.20 Uptrend
## 5 17.27 23.21 18.0 9.08 1.25 Uptrend
## 6 0.66 -4.01 2.0 -1.50 -0.82 Downtrend
## MoESOValue MoESO MarketCap Turnover AvgMOTurnover TurnoverRatio
## 1 68.47 Still Sell 54826.38 10.71 27.03 0.02
## 2 51.66 Alert Buy 39177.46 23.18 49.65 0.06
## 3 81.13 Buy Now 37689.74 2.74 6.20 0.01
## 4 37.73 Alert Buy 176253.02 86.57 149.19 0.05
## 5 71.97 Warning Sell 54108.05 6.30 25.51 0.01
## 6 42.58 Warning Sell 16093.09 8.05 17.97 0.05
## AvgMOTurnoverRatio IDXSector IDXIndustry
## 1 0.05 Infrastruktur Jasa Telekomunikasi Nirkabel
## 2 0.12 Kesehatan Penyedia Jasa Kesehatan
## 3 0.02 Barang Konsumen Primer Produk Susu Olahan
## 4 0.08 Barang Konsumen Primer Produk Perawatan Tubuh
## 5 0.05 Barang Konsumen Primer Makanan Olahan
## 6 0.11 Keuangan Bank
## Candle MA200
## 1 Harami - Bullish Above MA200
## 2 Marubozu - Opening Black Above MA200
## 3 Spinning Top - Whaite Above MA200
## 4 Marubozu - Closing White Above MA200
## 5 Hanging Man Above MA200
## 6 Hammer Below MA200# value : SO, Ch1D, Ch5D, Ch20D, YTDRet, ChTurnover, KairiMABB20, KairiMABB60, KairiMABB200, BB, Bandwidth, F1D, F2D, F1Wk, F1Mo,KairiMA20, KairiMA60, KairiMA200, MA20Direction, MA60Direction, MA200Direction
# Discrete : Ticker, Trend, SOSignal, Volume, AvgCondition, RCTrend, RCMomentum, RCTrendSignal, RCMomentumSignal, PriceVolumeCond, MA200
TPT.value <- TPT %>%
select(c("SO", "Ch1D", "Ch5D", "Ch20D", "YTDRet", "ChTurnover", "KairiMABB20", "KairiMABB60", "KairiMABB200", "BB", "Bandwidth", "F1D", "F2D", "F1Wk", "F1Mo","KairiMA20", "KairiMA60", "KairiMA200", "MA20Direction", "MA60Direction", "MA200Direction"))
TPT.Discrete <- TPT %>%
select(c("Trend", "SOSignal", "Volume", "AvgCondition", "RCTrend", "RCMomentum", "RCTrendSignal", "RCMomentumSignal", "PriceVolumeCond", "MA200"))library(DataExplorer)##
## Attaching package: 'DataExplorer'## The following object is masked from 'package:expss':
##
## split_columnsplot_intro(TPT)
plot_intro(TPT.Discrete)
plot_intro(TPT.value)
plot_missing(TPT)
plot_missing(TPT.Discrete)
plot_missing(TPT.value)
plot_bar(TPT.Discrete)
plot_histogram(TPT.value)
8 Stock Insights
8.1 Select Stocks
single.stock <- "JSMR"8.2 Plot
TPT.IDX %>%
filter(Ticker == single.stock) %>%
arrange(DateTime) %>%
select(DateTime, Close, Ch1D) %>%
filter_by_time(.start_date = "2021-12-31") %>%
plot_time_series(DateTime, Close)## .date_var is missing. Using: DateTimeTPT.IDX %>%
filter(Ticker == single.stock) %>%
arrange(DateTime) %>%
select(DateTime, Close, Ch1D) %>%
filter_by_time(.start_date = "2021-12-31") %>%
plot_time_series(DateTime, Ch1D, .smooth = F)## .date_var is missing. Using: DateTime8.3 Seasonality
TPT.IDX %>%
filter(Ticker == single.stock) %>%
arrange(DateTime) %>%
select(DateTime, Close, Ch1D) %>%
filter_by_time(.start_date = "2021-12-31") %>%
plot_seasonal_diagnostics(DateTime, Ch1D, .feature_set = "wday.lbl")## .date_var is missing. Using: DateTime8.4 STL Decomposition
TPT.IDX %>%
filter(Ticker == single.stock) %>%
arrange(DateTime) %>%
select(DateTime, Close, Ch1D) %>%
filter_by_time(.start_date = "2021-12-31") %>%
plot_stl_diagnostics(DateTime, Close, .feature_set = c("observed", "season", "trend"))## .date_var is missing. Using: DateTime## frequency = 5 observations per 1 week## trend = 65 observations per 3 monthsTPT.IDX %>%
filter(Ticker == single.stock) %>%
arrange(DateTime) %>%
select(DateTime, Close, Ch1D) %>%
filter_by_time(.start_date = "2021-12-31") %>%
plot_stl_diagnostics(DateTime, Ch1D, .feature_set = c("observed", "season", "trend"))## .date_var is missing. Using: DateTime## frequency = 5 observations per 1 week## trend = 65 observations per 3 months8.5 ACF / PACF
TPT.IDX %>%
filter(Ticker == single.stock) %>%
arrange(DateTime) %>%
select(DateTime, Close, Ch1D) %>%
filter_by_time(.start_date = "2021-12-31") %>%
plot_acf_diagnostics(DateTime, Ch1D, .lags = 20)## .date_var is missing. Using: DateTime## Warning: `gather_()` was deprecated in tidyr 1.2.0.
## Please use `gather()` instead.8.6 Joining
TPT.IDX %>%
filter(Ticker %in% c("ASII", "TLKM")) %>%
arrange(Ticker, DateTime) %>%
select(Ticker, DateTime, Close, Ch1D) %>%
filter_by_time(.start_date = "2021-12-31") %>%
plot_time_series(DateTime, Close, .facet_vars = Ticker)## .date_var is missing. Using: DateTimeTPT.IDX %>%
filter(Ticker %in% c("ASII", "TLKM")) %>%
arrange(Ticker, DateTime) %>%
select(Ticker, DateTime, Close, Ch1D) %>%
filter_by_time(.start_date = "2021-12-31") %>%
pivot_wider(names_from = Ticker, values_from = c(Close, Ch1D)) %>%
drop_na() %>%
mutate(across(Close_ASII:Ch1D_TLKM, .fns = standardize_vec)) %>%
pivot_longer(Close_ASII:Ch1D_TLKM) %>%
filter(name == c("Close_ASII", "Close_TLKM")) %>%
plot_time_series(DateTime, value, .color_var = name, .smooth = FALSE)## .date_var is missing. Using: DateTime## Standardization Parameters
## mean: 6511.25
## standard deviation: 547.698186979015## Standardization Parameters
## mean: 4366.85
## standard deviation: 195.166666309057## Standardization Parameters
## mean: 0.08345
## standard deviation: 1.88365825979621## Standardization Parameters
## mean: 0.0353
## standard deviation: 1.574503482397049 Draft Top Stocks
10 Super Quadrant Stocks - Stable Algorithm
# unique(dandy.rotation$IDXSector)
# head(dandy.rotation)
# selected.date <- print("2022-02-09")
# Date.Signs2 <- "Based on Trading Date 09 Februari 2022"
#
# TPT <- TPT.IDX %>%
# filter(DateTime == selected.date)
#
# dandy.rotation <- TPT %>%
# mutate(RCBB = RC.BB - PrevRC.BB,
# kairiRC = round(((RC.JKSE - MA.RC)/MA.RC*100),2))
#
# dandy.rotation %>%
# filter(Ticker == "ENRG")10.0.1 Animated
# library(gganimate)
# TPT.IDX %>%
# na.omit() %>%
# filter(DateTime >= max(DateTime) %-time% "3 day") %>%
# arrange(DateTime) %>%
# filter(IDXSector == "Kesehatan") %>%
# ggplot(aes(x = KairiMABB200, y = KairiMABB20, label = Ticker, color = Trend))+
# # geom_text_repel(aes(size = ChTurnover))+
# geom_text_repel(max.overlaps = 20)+
# geom_point(aes(shape = SOSignal))+
# theme_bw() +
# theme(panel.border = element_blank(), panel.grid.major = element_blank(),panel.grid.minor = element_blank(), axis.line = element_line(colour = "black"))+
# # facet_wrap(~ IDXSector, ncol = 2, scales = "free")+
# scale_shape_manual(values=SOSignal.shape,name = "Signal")+
# scale_size(range = c(2, 6), name = "%Ch in Turnover")+
# scale_y_continuous("Momentum Performance")+
# scale_x_continuous("Trend Performance")+
# scale_color_manual(values=Trend.color)+
# geom_vline(xintercept = 0, linetype="dotted")+
# geom_hline(yintercept = 0, linetype="dotted")+
# annotate("text", x = max(dandy.rotation.consumer.interest$KairiMABB200), y = max(dandy.rotation.consumer.interest$KairiMABB20), label = "Champion", hjust = "top")+
# annotate("text", x = min(dandy.rotation.consumer.interest$KairiMABB200), y = min(dandy.rotation.consumer.interest$KairiMABB20), label = "Loser", hjust = "bottom")+
# annotate("text", x = max(dandy.rotation.consumer.interest$KairiMABB200), y = min(dandy.rotation.consumer.interest$KairiMABB20), label = "Recharge", hjust = "top")+
# annotate("text", x = min(dandy.rotation.consumer.interest$KairiMABB200), y = max(dandy.rotation.consumer.interest$KairiMABB20), label = "Quick", hjust = "bottom")+
# labs(title = "Date : {frame_time}", subtitle = Date.Signs2, caption = "IG : @superquadrant")+
# watermark(show = TRUE, lab = "Super Quadrant Stocks")+
# transition_time(DateTime)10.1 Super Quadrant Stocks : Consumer and Interest Rate Sector
10.2 Super Quadrant Stocks : Commodity and Infrastructure Related Sector
10.3 Super Quadrant Stocks : Champion Quadrant & Uptrend
10.3.1 Cluster Stocks in Champion Quadrant and Uptrend
10.3.2 Table
10.3.3 Table (cluster)
10.4 Super Quadrant Stocks : Champion Quadrant (Short Term Return Graphic)
10.5 Super Quadrant Stocks : Champion Quadrant (Medium Term Return Graphic)
10.6 Super Quadrant Stocks : Champion Quadrant with Cluster (Short Term Return Graphic)
10.7 Super Quadrant Stocks : Champion Quadrant with Cluster (Medium Term Return Graphic)
10.8 New Outperform Trend
10.8.1 Draft
11 Line Graph
range(TPT.IDX$DateTime)## [1] "2022-01-12" "2022-11-07"min_max_norm <- function(x) {
(x - min(x)) / (max(x) - min(x))
}
TPT.IDX %>%
filter(Ticker %in% c("ASII", "TLKM", "JSMR", "BBCA", "GGRM")) %>%
filter(DateTime >= max(TPT.IDX$DateTime) %-time% "20 day") %>%
arrange(DateTime) %>%
select(DateTime, Ticker, Close) %>%
pivot_wider(names_from = Ticker, values_from = Close) %>%
# mutate(across(-DateTime, .fns = standardize_vec)) %>%
mutate(across(-DateTime, .fns = normalize_vec)) %>%
# mutate(across(-DateTime, .fns = min_max_norm)) %>%
pivot_longer(-DateTime) %>%
plot_time_series(.date_var = DateTime, .color_var = name, .value = value, .smooth = F)## Normalization Parameters
## min: 22125
## max: 25475## Normalization Parameters
## min: 4130
## max: 4450## Normalization Parameters
## min: 6350
## max: 6700## Normalization Parameters
## min: 8275
## max: 8900## Normalization Parameters
## min: 3300
## max: 3480