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 04 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
## 1 INCO 6750 2022-11-04 New Uptrend 90.74 Still Buy 1.89 0.00 3.85
## 2 CMRY 4710 2022-11-04 Uptrend 33.29 Still Sell -1.88 0.00 5.84
## 3 BACA 133 2022-11-04 Downtrend 13.42 Still Buy 0.76 -1.49 -8.90
## 4 ASRI 168 2022-11-04 Downtrend 24.29 Alert Buy -2.33 1.18 -5.08
## 5 ISAT 6700 2022-11-04 Uptrend 60.97 Still Sell -1.83 -1.44 5.51
## 6 ADHI 550 2022-11-04 Downtrend 29.29 Sell Now -0.90 -0.89 -0.90
## Ch20D Ch60D YTDRet Volume ChTurnover ChTurnover5D AvgCondition
## 1 -0.74 -2.53 44.23 Above Previous 1.18 -0.74 Low TO
## 2 7.53 7.53 38.53 --- -0.37 -0.73 High TO
## 3 12.71 -12.50 -50.00 --- -0.14 -0.71 Low TO
## 4 -2.89 -4.00 3.70 Abv Prev&Avg 1.40 -0.69 High TO
## 5 -1.83 -6.62 8.06 Above Previous 0.19 -0.68 Low TO
## 6 -25.17 -27.15 -38.55 --- -0.39 -0.68 High TO
## RCTrend RCMomentum RCTrendSignal RCMomentumSignal KairiMABB20
## 1 O/P Trend O/P Momentum O/P Trend Signal O/P Momentum Signal 0.65
## 2 O/P Trend U/P Momentum --- --- 3.09
## 3 U/P Trend U/P Momentum --- --- -7.09
## 4 U/P Trend U/P Momentum --- U/P Momentum Signal -2.39
## 5 O/P Trend U/P Momentum --- --- 0.71
## 6 U/P Trend O/P Momentum --- --- -13.61
## KairiMABB60 KairiMABB200 Prev.KairiMABB200 OP.Trend.Start BB Bandwidth
## 1 5.03 7.11 5.45 --- 74.28 6.67
## 2 7.69 17.60 20.20 --- 77.67 14.61
## 3 -2.61 -22.42 -23.17 --- 27.35 27.26
## 4 -4.23 0.33 2.87 --- 28.24 6.74
## 5 -3.53 5.65 7.80 --- 61.93 13.82
## 6 -24.85 -28.08 -27.51 --- 19.54 41.69
## F1D F2D F1Wk F1Mo MTTrend WkESOValue WkESO PriceVolumeCond
## 1 2.89 -4.40 14.11 25.52 Uptrend 46.67 Still Buy Real +
## 2 -1.08 -3.07 2.66 17.42 Uptrend 40.91 Alert Buy fake -
## 3 0.01 0.00 -0.37 -1.09 New Downtrend 47.62 Buy Now Fake +
## 4 0.40 0.73 0.58 -4.16 New Downtrend 49.32 Still Sell Real -
## 5 -0.99 -6.26 -7.20 -73.69 Downtrend 17.74 Still Buy Real -
## 6 2.21 2.19 6.78 11.95 Downtrend 1.89 Still Buy fake -
## Last1DPVCond Last2DPVCond RC.JKSE MA.RC RC.BB PrevRC.BB Corr20D Corr60D
## 1 --- --- 958.05 951.82 57.23 37.92 -0.15 -0.36
## 2 --- --- 668.51 648.47 75.78 96.09 0.63 -0.35
## 3 Real - Real - 18.88 20.32 25.95 28.15 -0.33 -0.03
## 4 Fake + Fake + 23.84 24.43 10.81 48.85 0.50 0.83
## 5 fake - fake - 950.96 944.28 55.56 70.37 0.39 0.67
## 6 fake - fake - 78.06 90.36 20.16 19.08 -0.71 0.63
## Corr5D KairiMA20 KairiMA60 KairiMA200 MA20Direction MA60Direction
## 1 -0.57 1.59 4.11 7.40 -2.50 -2.92
## 2 -0.75 3.89 6.47 15.79 16.50 5.50
## 3 0.88 -6.58 -3.43 -27.20 0.75 -0.32
## 4 0.54 -1.49 -5.25 1.29 -0.25 -0.12
## 5 -0.42 1.62 -4.48 6.27 -6.25 -7.92
## 6 -0.32 -14.55 -34.23 -37.44 -9.25 -3.42
## MA200Direction LTTrend MoESOValue MoESO MarketCap Turnover
## 1 11.20 Uptrend 49.32 Still Buy 67070.29 57.96
## 2 6.50 --- 81.13 Buy Now 37372.36 1.75
## 3 -0.58 Downtrend 33.10 Buy Now 932.02 1.46
## 4 0.03 New Downtrend 47.93 Still Sell 3301.10 4.08
## 5 2.50 Uptrend 68.47 Still Sell 54020.11 10.22
## 6 -1.88 Downtrend 10.43 Alert Buy 1958.47 13.25
## AvgMOTurnover TurnoverRatio AvgMOTurnoverRatio IDXSector
## 1 71.96 0.09 0.11 Barang Baku
## 2 6.21 0.00 0.02 Barang Konsumen Primer
## 3 14.83 0.16 1.40 Keuangan
## 4 3.02 0.12 0.09 Properti & Real Estat
## 5 28.43 0.02 0.05 Infrastruktur
## 6 16.50 0.68 0.78 Infrastruktur
## IDXIndustry Candle MA200
## 1 Logam & Mineral Lainnya Marubozu - Closing White Above MA200
## 2 Produk Susu Olahan Hammer - Inverted Above MA200
## 3 Bank Harami - Bullish Below MA200
## 4 Pengembang & Operator Real Estat Black Candle Above MA200
## 5 Jasa Telekomunikasi Nirkabel Marubozu - Opening Black Above MA200
## 6 Konstruksi Bangunan Marubozu - Black 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: 6502.98507462687
## standard deviation: 552.633282363738## Standardization Parameters
## mean: 4364.57711442786
## standard deviation: 196.45850776597## Standardization Parameters
## mean: 0.0772139303482587
## standard deviation: 1.87944119328192## Standardization Parameters
## mean: 0.0173134328358209
## standard deviation: 1.57106102563489 Draft Top Stocks
10 Super Quadrant Stocks - Stable Algorithm
# unique(dandy.rotation$IDXSector)
# head(dandy.rotation)
# selected.date <- print("2022-02-09")
# Date.Signs2 <- "Based on Trading Date 09 Februari 2022"
#
# TPT <- TPT.IDX %>%
# filter(DateTime == selected.date)
#
# dandy.rotation <- TPT %>%
# mutate(RCBB = RC.BB - PrevRC.BB,
# kairiRC = round(((RC.JKSE - MA.RC)/MA.RC*100),2))
#
# dandy.rotation %>%
# filter(Ticker == "ENRG")10.1 Super Quadrant Stocks : Consumer and Interest Rate Sector
10.2 Super Quadrant Stocks : Commodity and Infrastructure Related Sector
10.3 Super Quadrant Stocks : Champion Quadrant & Uptrend
10.3.1 Cluster Stocks in Champion Quadrant and Uptrend
10.3.2 Table
10.3.3 Table (cluster)
10.4 Super Quadrant Stocks : Champion Quadrant (Short Term Return Graphic)
10.5 Super Quadrant Stocks : Champion Quadrant (Medium Term Return Graphic)
10.6 Super Quadrant Stocks : Champion Quadrant with Cluster (Short Term Return Graphic)
10.7 Super Quadrant Stocks : Champion Quadrant with Cluster (Medium Term Return Graphic)
10.8 New Outperform Trend
10.8.1 Draft
11 Line Graph
range(TPT.IDX$DateTime)## [1] "2022-01-10" "2022-11-04"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: 3270
## max: 3480## Normalization Parameters
## min: 8250
## max: 8900## Normalization Parameters
## min: 4130
## max: 4450## Normalization Parameters
## min: 22100
## max: 25475## Normalization Parameters
## min: 6350
## max: 6700