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Indeks Bursa Malaysia KLCIKLSE
Hang SengHSI
Indeks Komposit JakartaCOMPOSITE
Nikkei 225NI225
Komposit Shanghai000001
FTSE Straits Times SingapuraSTI
DATASONIC GROUP BERHADDSONIC
KNM GROUP BHDKNM
ZECON BHDZECON
EXCEL FORCE MSC BHDEFORCE
PCCS GROUP BHDPCCS
VSOLAR GROUP BERHADVSOLAR
Modal Pasaran KryptoTOTAL
BitcoinBTCUSD
BTC/EURBTCEUR
BTC/JPYBTCJPY
BTC/GBPBTCGBP
BTC/RUBBTCRUB
USD/MYRUSDMYR
SGD/MYRSGDMYR
EUR/USDEURUSD
GBP/USDGBPUSD
CNY/MYRCNYMYR
JPY/MYRJPYMYR
Brent OilBR1!
Minyak MentahCL1!
EmasGC1!
PerakSI1!
Gas AsliNG1!
BitcoinBTC1!
US 10YUS10Y
Euro 10TEU10Y
Jerman 10YDE10Y
Hasil Jepun 10TJP10Y
UK 10YGB10Y
India 10YIN10Y

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innature-menarik juga untuk di kaji bersamaNOTE: ini bukan BUY CALL . ini memerlukan kajian bersama DAN tolong kaji ikut pemahaman masing-masing dan tidak bertanggungjawap sebarang kerugian. Penafian : Kajian diatas bertujuan untuk KITA bersama sama mengkaji dan bukanlah bertujuan untuk membeli atau menjual instrumen ini . Berdagang Diatas Risiko Sendiri #strong&loyal #ma100ma50ZZL&goldencross #4eDucationOnly #KISS #TADSweek 1.di skala harian harga kekal ditutup di atas EMA100 & EMA200 (sila masukan indi ) 2.untuk meneruskan kenaikan akan lebih cantik jika : -jika bo & kekal di 0.685 with strong volume ,aftifkan SL di 0.630 3.di carta juga disertakan S&R gann untuk di jadikan sedikit panduan begitulah dunia TA, perkara sama tetapi lihat berbeza2 . tiada yang betul atau salah kerana ianya belum berlaku
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QES terus bertahanQES membuat lantunan keatas setelah menguji kawasan RBS 1 bagi titik C. QES berjaya melepasi dan cuba untuk bertahan diatas kawasan RBS 2 QES mencatatkan peningkatan hasil pada Q3 Sep 22 sebanyak RM71,982,000 berbanding Q2 Jun 22 RM53,123,000 mencatatkan perbezaan sebanyak RM18,859,000. Keuntungan bersih mecatatkan perbezaan yang positif bagi Q3 Sep 22 RM 9,515,000 jika dibandingkan dengan Q2 Jun 22 RM4,726,000 mencatat perbezaan sebanyak RM4,789,000. Pemegang saham utama bagi QES terdiri daripada WA CAPITAL SDN BHD 26.13% sebanyak 218,000,000 unit saham yang bernialai 152.60M , diikuti LIEW SOO KEANG 22.87% sebagai pemegang saham kedua terbesar sebanyak 190,751,105 unit saham dengan nilai sebanyak 133.53M . corak carta : wedge menurun Nota : menerbit kan idea ini ada semata mata bertujuan sebagai perkongsian pemahaman dan pembelajaran. Sekiranya ingin memiliki saham ini, hendaklah membuat kajian yang lebih mendalam dan merujuk kepada pihak yang lebih pakar sebelum membeli saham.
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Masteel dilihat seperti membuat corak "bullish pennant"Kaunter: Masteel Sektor: Besi Tempoh masa harian dilihat masteel seperti membuat corak pennat namun harga perlu Bo 385 dengan kehadiran volum belian yang tinggi untuk membuat pengesahan corat menaik/pembalikan ke atas. Sebaik-baik lilin corak "bullish morubozu" berlaku di carta harian. Di tempoh masa 15minit tampak pembetukan bullish divergerce di mana harga bergerak secara sideways tetapi oscilator bergerak ke atas. Namun seperti dinyatakan tadi harga perlu bergerak melepasi rintangan berserta minat belian yang padu (volum masuk). Perlu ada pengesahan kemasukan dengan pengesahan lilin bullish yang kuat sebagai contoh "bullish morubozu" atau "bullish engulfing" ketika harga memecah rintangan. Sasaran harga adalah seperti yang dilukiskan di carta. Sekadar kajian bagi tujuan pembelajran semata-mata. Kaji risko terlebih dahlu sebelum memasuki sesuatu kaunter. kanal pasti snr. Keluar sesuatu kaunter sekiranya harga sokongan telah bocor.Beli jual sesuatu saham adalah tanggungjawab anda. #tayor
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APEX dalam kawasanAPEX membuat pembetulan harga setelah gagal bertahan diatas 1.250. harga berkemungkinan bakal menguji kawasan sokongan terdekat. untuk meneruskan kenaikan, APEX perlu bertahan diatas harga 1.250 dan membuat harga tertinggi memecahkan 1.290. APEX mencatatkan peningkatan hasil pada Q3 Sep 22 sebanyak RM8,784,000 berbanding Q2 Jun 22 RM7,759,000 mencatatkan perbezaan sebanyak RM1,025,000. Keuntungan bersih tidak mecatatkan perbezaan yang ketara bagi Q3 Sep 22 RM 985,000 jika dibandingkan dengan Q2 Jun 22 RM986,000 mencatat perbezaan sebanyak RM1,000. Pemegang saham utama bagi APEX terdiri daripada FUN SHEUNG DEVELOPMENT LIMITED 15.78% sebanyak 31,966,914 unit saham yang bernialai 36.76M , diikuti KENANGA GROWTH FUND 15.57% sebagai pemegang saham kedua terbesar sebanyak 31,552,800 unit saham dengan nilai sebanyak 36.29M . corak carta : segitiga menaik Nota : menerbit kan idea ini ada semata mata bertujuan sebagai perkongsian pemahaman dan pembelajaran. Sekiranya ingin memiliki saham ini, hendaklah membuat kajian yang lebih mendalam dan merujuk kepada pihak yang lebih pakar sebelum membeli saham.
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NU Holding Ltd dalam saluran Downtrend1. Resistance R1 pada $3.75, R2 pada $4.18 dan R3 pada $4.50. 2. Support S1 pada $3.54 dan S2 pada $3.26. 3. MACD menunjukkan momentum yang kurang. 4. SmartMCDX menunjukkan big money belum masuk. 5. Candle bergerak dalam saluran downtrend sejak Nov 2022. 6. VPVR menunjukkan pembelian tinggi berlaku pada harga $3.86. 7. Bollinger band belum kembang. 8. Jika candle dapat bertahan di atas S1 maka mungkin bergerak di sideway sementara volume tinggi dan big money masuk. Sila LIKE jika bersetuju dengan idea saya sebagai sokongan. Disclaimer: Ini bukan BUY or SELL call, sila buat kajian sendiri sebelum ambil keputusan.
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Aliran berita

Teruskan membacaTeruskan membaca

Arah aliran komuniti

NYLEX (M) BHDNYLEX
DAGANG NEXCHANGE BERHADDNEX
ATA IMS BERHADATAIMS
HIBISCUS PETROLEUM BHDHIBISCS
QES GROUP BERHADQES
COSMOS TECHNOLOGY INTERNATIONAL BERHADCOSMOS
CAPITAL A BERHADCAPITALA
ANN JOO RESOURCES BHDANNJOO
DS SIGMA HOLDINGS BERHADDSS
CENGILD MEDICAL BERHADCENGILD

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Kedudukan berasaskan permodalan pasaran

SimbolPermodalan PasaranHarga & perubahan 1H

DeFi berasaskan permodalan pasaran

SimbolPermodalan PasaranHarga & perubahan 1H

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Idea dagangan

XAUUSD: MAJOR HEAD & SHOULSERS IN MAKING H4Harga breaks resistance sebelum ( demand 1) dan ia masih lagi di area tersebut dan demand1 kelihatan agak kuat dimana jumaat ia melantun dari situ. Area ini perlu di observe sebagai area BUY. Jika ia breakdown demand1 maka ia akan mencari demand2. Dari paparan besar kelihatan ia membentuk corak KEPALA DAN BAHU. sasaran terdekat ialah 1780. Apa apa pun boleh berlaku sebaliknya. Jadi observe zon demand & supply untuk wajaran BUY @ SELL. PENAFIAN : CATATAN INI BUKANLAH BUY/SELL CALL, HANYA IDEA DAN ANALISIS KAJIAN UNTUK PENDIDIKAN. TAKE AT YOUR OWN RISK.
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GBPUSD berada di Resistance1. Resistance R1 pada 1.245 dan R2 pada 1.264. 2. Support S1 pada 1.220 dan S2 pada 1.199. 3. Garisan Uptrend menjadi support yang kukuh. 4. Stoch berada di zon overbought. 5. MACD menunjukkan bullish momentum berkurangan. 6. Jika candle betahan di atas garisan uptrend mungkin akan bergerak di sideway sementara. Sila LIKE jika bersetuju dengan idea saya sebagai sokongan. Disclaimer: Ini bukan BUY or SELL call, sila buat kajian sendiri sebelum ambil keputusan.
Dataprp Nampak Membuat "Bullish Divergence"Kaunter: Dataprp Sektor: Teknologi & digital servis Tempoh masa harian (1D) boleh dilihat pembetukan bullish divergence. Harga perlu memecahkan harga 235 dan kekal di atas 235 untuk masuk ke zon "bullish". Sasaran harga adalah LH sebelum (sila rujuk garisan di carta) harga sekitar 265-275 menjadi sasaran terdekat. Pada temph masa kecil ada rintangan garisan tad (garis merah jambu) 235..perlu memecahkan rintangan tersebut untuk membuat kenaikan yang baru,jika tidak berjaya memecahkan harga 235 pergerakan harga berada pada "sideways". Perhatikan pergerakan harga,cari ep di zon "bullish" dengan volum kemasukan yang padu (belian yang menarik). Sekadar kajian bagi tujuan pembelajran semata-mata. Bukan saranan jual beli saham. Beli jual adalah tanggungjawab anda.
APEX dalam kawasanAPEX membuat pembetulan harga setelah gagal bertahan diatas 1.250. harga berkemungkinan bakal menguji kawasan sokongan terdekat. untuk meneruskan kenaikan, APEX perlu bertahan diatas harga 1.250 dan membuat harga tertinggi memecahkan 1.290. APEX mencatatkan peningkatan hasil pada Q3 Sep 22 sebanyak RM8,784,000 berbanding Q2 Jun 22 RM7,759,000 mencatatkan perbezaan sebanyak RM1,025,000. Keuntungan bersih tidak mecatatkan perbezaan yang ketara bagi Q3 Sep 22 RM 985,000 jika dibandingkan dengan Q2 Jun 22 RM986,000 mencatat perbezaan sebanyak RM1,000. Pemegang saham utama bagi APEX terdiri daripada FUN SHEUNG DEVELOPMENT LIMITED 15.78% sebanyak 31,966,914 unit saham yang bernialai 36.76M , diikuti KENANGA GROWTH FUND 15.57% sebagai pemegang saham kedua terbesar sebanyak 31,552,800 unit saham dengan nilai sebanyak 36.29M . corak carta : segitiga menaik Nota : menerbit kan idea ini ada semata mata bertujuan sebagai perkongsian pemahaman dan pembelajaran. Sekiranya ingin memiliki saham ini, hendaklah membuat kajian yang lebih mendalam dan merujuk kepada pihak yang lebih pakar sebelum membeli saham.
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USDJPY (MATAWANG)Pelan Pelaburan - Limit Belian - Entri: Garisan Putus-Putus Warna Biru Ambil Untung: Garisan Putus-Putus Warna Merah Target Keuntungan: 100pips Target Kerugian: 30pips Nisbah Risiko dan Ganjaran: Lebih 1:3 - Limit Jualan - Entri: Garisan Putus-Putus Warna Biru Ambil Untung: Garisan Putus-Putus Warna Merah Target Keuntungan: 100pips Target Kerugian: 30pips Nisbah Risiko dan Ganjaran: Lebih 1:3 Tip untuk membuat entri: Entri apabila terdapat pengesahan paten pembalikan arah berdasarkan selang masa m15 semasa harga masuk ke dalam zon belian atau jualan bagi mengurangkan risiko rugi. Sekiranya tiada pengesahan pembalikan arah dan pasaran mengesahakan paten penerusan, maka entri berdasarkan trend ketika harga menguji semula zon tersebut. Berdagang Atas Risiko Anda Sendiri (BARAS)
CITAGLB - Berjaya melepasi PivotKajian Kaunter CITAGLB Menarik untuk diperhatikan. Kajian sebelum ini di paras Pivot Point , kaunter ini melakukan pullback yang agak banyak telah memecahkan MA20 dan MA50. Namun, kelihatan volume jualan yang kurang dan setelah selling pressure berkurang kaunter ini berjaya mendaki semula. Kelihatan kenaikkan kali ini melepasi Pivot dengan significant volume atau Fresh Volume. Sasaran seterusnya adalah pada paras Fibo 2.618. Boleh perhatikan #BAYOR #TAYOR
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Skrip Pine

CVD - Cumulative Volume Delta (Chart)█   OVERVIEW This indicator displays cumulative ​volume delta (​CVD) as an on-chart oscillator. It uses intrabar analysis to obtain more precise ​volume delta information compared to methods that only use the chart's timeframe. The core concepts in this script come from our first ​ CVD indicator , which displays CVD​ values as plot candles in a separate indicator pane. In this script, CV​D values are scaled according to price ranges and represented on the main chart pane. █   CONCEPTS Bar polarity Bar polarity refers to the position of the close price relative to the open price. In other words, bar polarity is the direction of price change. Intrabars Intrabars are chart bars at a lower timeframe than the chart's. Each 1H chart bar of a 24x7 market will, for example, usually contain 60 bars at the lower timeframe of 1min, provided there was market activity during each minute of the hour. Mining information from intrabars can be useful in that it offers traders visibility on the activity inside a chart bar. Lower timeframes (LTFs) A lower timeframe is a timeframe that is smaller than the chart's timeframe. This script utilizes a LTF to analyze intrabars, or price changes within a chart bar. The lower the ​LTF, the more intrabars are analyzed, but the less chart bars can display information due to the limited number of intrabars that can be analyzed. Volume delta Volume delta is a measure that separates ​volume​ into "up" and "down" parts, then takes the difference to estimate the net demand for the asset. This approach gives traders a more detailed insight when analyzing volume​ and market sentiment. There are several methods for determining whether an asset's volume​ belongs in the "up" or "down" category. Some indicators, such as On Balance Volume​ and the Klinger Oscillator , use the change in price between bars to assign ​volume​ values to the appropriate category. Others, such as Chaikin Money Flow , make assumptions based on open, high, low, and close prices. The most accurate method involves using tick data to determine whether each transaction occurred at the bid or ask price and assigning the ​volume​ value to the appropriate category accordingly. However, this method requires a large amount of data on historical bars, which can limit the historical depth of charts and the number of symbols for which tick data is available. In the context where historical tick data is not yet available on TradingView, intrabar analysis is the most precise technique to calculate ​volume delta on historical bars on our charts. This indicator uses intrabar analysis to achieve a compromise between simplicity and accuracy in calculating ​volume delta on historical bars. Our Volume Profile indicators use it as well. Other ​volume delta indicators in our Community Scripts , such as the Realtime 5D Profile , use real-time chart updates to achieve more precise ​volume delta calculations. However, these indicators aren't suitable for analyzing historical bars since they only work for real-time analysis. This is the logic we use to assign intrabar ​volume to the "up" or "down" category:  • If the intrabar's open and close values are different, their relative position is used.  • If the intrabar's open and close values are the same, the difference between the intrabar's close and the previous intrabar's close is used.  • As a last resort, when there is no movement during an intrabar and it closes at the same price as the previous intrabar, the last known polarity is used. Once all intrabars comprising a chart bar are analyzed, we calculate the net difference between "up" and "down" intrabar volume​ to produce the volume​ delta for the chart bar. █   FEATURES CVD resets The "cumulative" part of the indicator's name stems from the fact that calculations accumulate during a period of time. By periodically resetting the volume​ delta accumulation, we can analyze the progression of ​volume delta across manageable chunks, which is often more useful than looking at ​volume delta accumulated from the beginning of a chart's history. You can configure the reset period using the "CVD Resets" input, which offers the following selections:  • None : Calculations do not reset.  • On a fixed higher timeframe : Calculations reset on the higher timeframe you select in the "Fixed higher timeframe" field.  • At a fixed time that you specify.  • At the beginning of the regular session .  • On trend changes : Calculations reset on the direction change of either the Aroon indicator, Parabolic SAR , or Supertrend .  • On a stepped higher timeframe : Calculations reset on a higher timeframe automatically stepped using the chart's timeframe and following these rules: Chart TF ​HTF < 1min 1H < 3H 1D <= 12H 1W < 1W 1M >= 1W 1Y Specifying intrabar precision Ten options are included in the script to control the number of intrabars used per chart bar for calculations. The greater the number of intrabars per chart bar, the fewer chart bars can be analyzed. The first five options allow users to specify the approximate amount of chart bars to be covered:  • Least Precise (Most chart bars) : Covers all chart bars by dividing the current timeframe by four.   This ensures the highest level of intrabar precision while achieving complete coverage for the dataset.  • Less Precise (Some chart bars) & More Precise (Less chart bars) : These options calculate a stepped ​LTF in relation to the current chart's timeframe.  • Very precise (2min intrabars) : Uses the second highest quantity of intrabars possible with the 2min ​LTF.  • Most precise (1min intrabars) : Uses the maximum quantity of intrabars possible with the 1min ​LTF. The stepped lower timeframe for "Less Precise" and "More Precise" options is calculated from the current chart's timeframe as follows: Chart Timeframe Lower Timeframe Less Precise More Precise < 1hr 1min 1min < 1D 15min 1min < 1W ​2hr​ 30min > 1W 1D 60min The last five options allow users to specify an approximate fixed number of intrabars to analyze per chart bar. The available choices are 12, 24, 50, 100, and 250. The script will calculate the LTF​ which most closely approximates the specified number of intrabars per chart bar. Keep in mind that due to factors such as the length of a ticker's sessions and rounding of the LTF​, it is not always possible to produce the exact number specified. However, the script will do its best to get as close to the value as possible. As there is a limit to the number of intrabars that can be analyzed by a script, a tradeoff occurs between the number of intrabars analyzed per chart bar and the chart bars for which calculations are possible. Display This script displays raw or cumulative volume​ delta values on the chart as either line or histogram oscillator zones scaled according to the price chart, allowing traders to visualize volume​ activity on each bar or cumulatively over time. The indicator's background shows where CVD​ resets occur, demarcating the beginning of new zones. The vertical axis of each oscillator zone is scaled relative to the one with the highest price range, and the oscillator values are scaled relative to the highest volume​ delta. A vertical offset is applied to each oscillator zone so that the highest oscillator value aligns with the lowest price. This method ensures an accurate, intuitive visual comparison of volume​ activity within zones, as the scale is consistent across the chart, and oscillator values sit below prices. The vertical scale of oscillator zones can be adjusted using the "Zone Height" input in the script settings. This script displays labels at the highest and lowest oscillator values in each zone, which can be enabled using the "Hi/Lo Labels" input in the "Visuals" section of the script settings. Additionally, the oscillator's value on a chart bar is displayed as a tooltip when a user hovers over the bar, which can be enabled using the "Value Tooltips" input. Divergences occur when the polarity of ​volume delta does not match that of the chart bar. The script displays divergences as bar colors and background colors that can be enabled using the "Color bars on divergences" and "Color background on divergences" inputs. An information box in the lower-left corner of the indicator displays the HTF used for resets, the ​LTF used for intrabars, the average quantity of intrabars per chart bar, and the number of chart bars for which there is LTF data. This is enabled using the "Show information box" input in the "Visuals" section of the script settings. FOR Pine Script™ CODERS  • This script utilizes `ltf()` and `ltfStats()` from the lower_tf library.   The `ltf()` function determines the appropriate lower timeframe from the selected calculation mode and chart timeframe, and returns it in a format that can be used with request.security_lower_tf() .   The `ltfStats()` function, on the other hand, is used to compute and display statistical information about the lower timeframe in an information box.  • The script utilizes display.data_window and display.status_line to restrict the display of certain plots.   These new built-ins allow coders to fine-tune where a script’s plot values are displayed.  • The newly added session.isfirstbar_regular built-in allows for resetting the ​CVD segments at the start of the regular session.  • The VisibleChart library developed by our resident PineCoders team leverages the chart.left_visible_bar_time and chart.right_visible_bar_time variables to optimize the performance of this script.   These variables identify the opening time of the leftmost and rightmost visible bars on the chart, allowing the script to recalculate and draw objects only within the range of visible bars as the user scrolls.   This functionality also enables the scaling of the oscillator zones.   These variables are just a couple of the many new built-ins available in the chart.* namespace.   For more information, check out this blog post or look them up by typing "chart." in the Pine Script™ Reference Manual .  • Our ta library has undergone significant updates recently, including the incorporation of the `aroon()` indicator used as a method for resetting ​CVD segments within this script.   Revisit the library to see more of the newly added content! Look first. Then leap.
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Penunjuk Skrip Pine™
15
Smart Money Concepts [LUX]This all-in-one indicator displays real-time market structure (internal & swing BOS / CHoCH), order blocks, premium & discount zones, equal highs & lows, and much more...allowing traders to automatically mark up their charts with widely used price action methodologies. Following the release of our Fair Value Gap script, we received numerous requests from our community to release more features in the same category. "Smart Money Concepts" (SMC) is a fairly new yet widely used term amongst price action traders looking to more accurately navigate liquidity & find more optimal points of interest in the market. Trying to determine where institutional market participants have orders placed (buy or sell side liquidity) can be a very reasonable approach to finding more practical entries & exits based on price action. The indicator includes alerts for the presence of swing structures and many other relevant conditions. Features This indicator includes many features relevant to SMC, these are highlighted below: Full internal & swing market structure labeling in real-time Break of Structure (BOS) Change of Character (CHoCH) Order Blocks (bullish & bearish) Equal Highs & Lows Fair Value Gap Detection Previous Highs & Lows Premium & Discount Zones as a range Options to style the indicator to more easily display these concepts Settings Mode: Allows the user to select Historical (default) or Present, which displays only recent data on the chart. Style: Allows the user to select different styling for the entire indicator between Colored (default) and Monochrome. Color Candles: Plots candles based on the internal & swing structures from within the indicator on the chart. Internal Structure: Displays the internal structure labels & dashed lines to represent them. (BOS & CHoCH). Confluence Filter: Filter non-significant internal structure breakouts. Swing Structure: Displays the swing structure labels & solid lines on the chart (larger BOS & CHoCH labels). Swing Points: Displays swing points labels on chart such as HH, HL, LH, LL. Internal Order Blocks: Enables Internal Order Blocks & allows the user to select how many most recent Internal Order Blocks appear on the chart. Swing Order Blocks: Enables Swing Order Blocks & allows the user to select how many most recent Swing Order Blocks appear on the chart. Equal Highs & Lows: Displays EQH/EQL labels on chart for detecting equal highs & lows. Bars Confirmation: Allows the user to select how many bars are needed to confirm an EQH/EQL symbol on chart. Fair Value Gaps: Displays boxes to highlight imbalance areas on the chart. Auto Threshold: Filter out non-significant fair value gaps. Timeframe: Allows the user to select the timeframe for the Fair Value Gap detection. Extend FVG: Allows the user to choose how many bars to extend the Fair Value Gap boxes on the chart. Highs & Lows MTF: Allows the user to display previous highs & lows from daily, weekly, & monthly timeframes as significant levels. Premium/Discount Zones: Allows the user to display Premium, Discount, and Equilibrium zones on the chart Usage Users can see automatic CHoCH and BOS labels to highlight breakouts of market structure, which allows to determine the market trend. In the chart below we can see the internal structure which displays more frequent labels within larger structures. We can also see equal highs & lows (EQH/EQL) labels plotted alongside the internal structure to frequently give indications of potential reversals. In the chart below we can see the swing market structure labels. These are also labeled as BOS and CHoCH but with a solid line & larger text to show larger market structure breakouts & trend reversals. Users can be mindful of these larger structure labels while trading internal structures as displayed in the previous chart. Order blocks highlight areas where institutional market participants open positions, one can use order blocks to determine confirmation entries or potential targets as we can expect there is a large amount of liquidity at these order blocks. In the chart below we can see 2 potential trade setups with confirmation entries. The path outlined in red would be a potential short entry targeting the blue order block below, and the path outlined in green would be a potential long entry, targeting the red order blocks above. As we can see in the chart below, the bullish confirmation entry played out in this scenario with the green path outlined in hindsight. As price breaks though the order blocks above, the indicator will consider them mitigated causing them to disappear, and as per the logic of these order blocks they will always display 5 (by default) on the chart so we can now see more actionable levels. The Smart Money Concepts indicator has many other features and here we can see how they can also help a user find potential levels for price action trading. In the screenshot below we can see a trade setup using the Previous Monthly High, Strong High, and a Swing Order Block as a stop loss. Accompanied by the Premium from the Discount/Premium zones feature being used as a potential entry. A potential take profit level for this trade setup that a user could easily identify would be the 50% mark labeled with the Fair Value Gap & the Equilibrium all displayed automatically by the indicator. Conclusion This indicator highlights all relevant components of Smart Money Concepts which can be a very useful interpretation of market structure, liquidity, & more simply put, price action. The term was coined & popularized primarily within the forex community & by ICT while making its way to become a part of many traders' analysis. These concepts, with or without this indicator do not guarantee a trader to be trading within the presence of institutional or "bank-level" liquidity, there is no supporting data regarding the validity of these teachings.
Penunjuk Skrip Pine™
406
Harmonic Patterns Based Trend FollowerEarlier this week, published an idea on how harmonic patterns can be used for trend following. This script is an attempt to implement the same. 🎲 Process 🎯 Derive Zigzag and scan harmonic patterns for last 5 confirmed pivots 🎯 If a pattern is found, highest point of pattern will become the bullish zone and lower point of the pattern will become bearish zone. 🎯 Since it is trend following method, when price reaches bullish zone, then the trend is considered as bullish and when price reaches bearish zone, the trend is considered as bearish. 🎯 If price does not touch both regions, then trend remains unchanged. 🎯 Bullish and bearish zone will change as and when new patterns are formed. 🎲 Note Patterns are not created on latest pivot as last pivot will be unconfirmed and moving. Due to this, patterns appear after certain delay - patterns will not be real time. But, this is expected and does not impact the overall process. When new pattern formed When price breaks over the zones 🎲 Output 🎯 Patterns formed are drawn in blue coloured lines. Due to pine limitation of max 500 lines, older patterns automatically get deleted when new ones come. 🎯 Bullish Zone and Bearish Zone are plotted in green and red colours and the zone will change whenever new pattern comes along. 🎯 Bar colors are changed according to calculated trend. Trend value can be 1 or -1 based on the current trend. You can also find the value in data window. 🎯 For simplicity purpose, input option for selection of specific patterns are not provided and also pattern names are not displayed on the chart.
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Penunjuk Skrip Pine™
26
Musashi_Fractal_Dimension === Musashi-Fractal-Dimension === This tool is part of my research on the fractal nature of the markets and understanding the relation between fractal dimension and chaos theory. To take full advantage of this indicator, you need to incorporate some principles and concepts: - Traditional Technical Analysis is linear and Euclidean, which makes very difficult its modeling. - Linear techniques cannot quantify non-linear behavior - Is it possible to measure accurately a wave or the surface of a mountain with a simple ruler? - Fractals quantify what Euclidean Geometry can’t, they measure chaos, as they identify order in apparent randomness. - Remember: Chaos is order disguised as randomness. - Chaos is the study of unstable aperiodic behavior in deterministic non-linear dynamic systems - Order and randomness can coexist, allowing predictability. - There is a reason why Fractal Dimension was invented, we had no way of measuring fractal-based structures. - Benoit Mandelbrot used to explain it by asking: How do we measure the coast of Great Britain? - An easy way of getting the need of a dimension in between is looking at the Koch snowflake. - Market prices tend to seek natural levels of ranges of balance. These levels can be described as attractors and are determinant. Fractal Dimension Index ('FDI') Determines the persistence or anti-persistence of a market. - A persistent market follows a market trend. An anti-persistent market results in substantial volatility around the trend (with a low r2), and is more vulnerable to price reversals - An easy way to see this is to think that fractal dimension measures what is in between mainstream dimensions. These are: - One dimension: a line - Two dimensions: a square - Three dimensions: a cube. --> This will hint you that at certain moment, if the market has a Fractal Dimension of 1.25 (which is low), the market is behaving more “line-like”, while if the market has a high Fractal Dimension, it could be interpreted as “square-like”. - 'FDI' is trend agnostic, which means that doesn't consider trend. This makes it super useful as gives you clean information about the market without trying to include trend stuff. Question: If we have a game where you must choose between two options. 1. a horizontal line 2. a vertical line. Each iteration a Horizontal Line or a Square will appear as continuation of a figure. If it that iteration shows a square and you bet vertical you win, same as if it is horizontal and it is a line. - Wouldn’t be useful to know that Fractal dimension is 1.8? This will hint square. In the markets you can use 'FD' to filter mean-reversal signals like Bollinger bands, stochastics, Regular RSI divergences, etc. - Wouldn’t be useful to know that Fractal dimension is 1.2? This will hint Line. In the markets you can use 'FD' to confirm trend following strategies like Moving averages, MACD, Hidden RSI divergences. Calculation method: Fractal dimension is obtained from the ‘hurst exponent’. 'FDI' = 2 - 'Hurst Exponent' Musashi version of the Classic 'OG' Fractal Dimension Index ('FDI') - By default, you get 3 fast 'FDI's (11,12,13) + 1 Slow 'FDI' (21), their interaction gives useful information. - Fast 'FDI' cross will give you gray or red dots while Slow 'FDI' cross with the slowest of the fast 'FDI's will give white and orange dots. This are great to early spot trend beginnings or trend ends. - A baseline (purple) is also provided, this is calculated using a 21 period Bollinger bands with 1.618 'SD', once calculated, you just take midpoint, this is the 'TDI's (Traders Dynamic Index) way. The indicator will print purple dots when Slow 'FDI' and baseline crosses, I see them as Short-Term cycle changes. - Negative slope 'FDI' means trending asset. - Positive most of the times hints correction, but if it got overextended it might hint a rocket-shot. TDI Ranges: - 'FDI' between 1.0≤ 'FDI' ≤1.4 will confirm trend following continuation signals. - 'FDI' between 1.6≥ 'FDI' ≥2.0 will confirm reversal signals. - 'FDI' == 1.5 hints a random unpredictable market. Fractal Attractors - As you must know, fractals tend orbit certain spots, this are named Attractors, this happens with any fractal behavior. The market of course also shows them, in form of Support & Resistance, Supply Demand, etc. It’s obvious they are there, but now we understand that they’re not linear, as the market is fractal, so simple trendline might not be the best tool to model this. - I’ve noticed that when the Musashi version of the 'FDI' indicator start making a cluster of multicolor dots, this end up being an attractor, I tend to draw a rectangle as that area as price tend to come back (I still researching here). Extra useful stuff - Momentum / speed: Included by checking RSI Study in the indicator properties. This will add two RSI’s (9 and a 7 periods) plus a baseline calculated same way as explained for 'FDI'. This gives accurate short-term trends. It also includes RSI divergences (regular and hidden), deactivate with a simple check in the RSI section of the properties. - BBWP (Bollinger Bands with Percentile): Efficient way of visualizing volatility as the percentile of Bollinger bands expansion. This line varies color from Iced blue when low volatility and magma red when high. By default, comes with the High vols deactivated for better view of 'FDI' and RSI while all studies are included. DDWP is trend agnostic, just like 'FDI', which make it very clean at providing information. - Ultra Slow 'FDI': I noticed that while using BBWP and RSI, the indicator gets overcrowded, so there is the possibility of adding only one 'FDI' + its baseline. Final Note: I’ve shown you few ways of using this indicator, please backtest before using in real trading. As you know trading is more about risk and trade management than the strategy used. This still a work in progress, I really hope you find value out of it. I use it combination with a tool named “Musashi_Katana” (also found in TradingView). Best! Musashi
Pilihan Editor
Penunjuk Skrip Pine™
24
Hurst Diamond Notation PivotsThis is a fairly simple indicator for diamond notation of past hi/lo pivot points, a common method in Hurst analysis. The diamonds mark the troughs/peaks of each cycle. They are offset by their lookback and thus will not 'paint' until after they happen so anticipate accordingly. Practically, traders can use the average length of past pivot periods to forecast future pivot periods in time🔮. For example, if the average/dominant number of bars in an 80-bar pivot point period/cycle is 76, then a trader might forecast that the next pivot could occur 76-ish bars after the last confirmed pivot. The numbers/labels on the y-axis display the cycle length used for pivot detection. This indicator doesn't repaint, but it has a lot of lag; Please use it for forecasting instead of entry signals. This indicator scans for new pivots in the form of a rainbow line and circle; once the hi/lo has happened and the lookback has passed then the pivot will be plotted. The rainbow color per wavelength theme seems to be authentic to Hurst (or modern Hurst software) and has been included as a default.
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Penunjuk Skrip Pine™
21
Machine Learning: Lorentzian Classification█ OVERVIEW A Lorentzian Distance Classifier (LDC) is a Machine Learning classification algorithm capable of categorizing historical data from a multi-dimensional feature space. This indicator demonstrates how Lorentzian Classification can also be used to predict the direction of future price movements when used as the distance metric for a novel implementation of an Approximate Nearest Neighbors (ANN) algorithm. █ BACKGROUND In physics, Lorentzian space is perhaps best known for its role in describing the curvature of space-time in Einstein's theory of General Relativity (2). Interestingly, however, this abstract concept from theoretical physics also has tangible real-world applications in trading. Recently, it was hypothesized that Lorentzian space was also well-suited for analyzing time-series data (4), (5). This hypothesis has been supported by several empirical studies that demonstrate that Lorentzian distance is more robust to outliers and noise than the more commonly used Euclidean distance (1), (3), (6). Furthermore, Lorentzian distance was also shown to outperform dozens of other highly regarded distance metrics, including Manhattan distance, Bhattacharyya similarity, and Cosine similarity (1), (3). Outside of Dynamic Time Warping based approaches, which are unfortunately too computationally intensive for PineScript at this time, the Lorentzian Distance metric consistently scores the highest mean accuracy over a wide variety of time series data sets (1). Euclidean distance is commonly used as the default distance metric for NN-based search algorithms, but it may not always be the best choice when dealing with financial market data. This is because financial market data can be significantly impacted by proximity to major world events such as FOMC Meetings and Black Swan events. This event-based distortion of market data can be framed as similar to the gravitational warping caused by a massive object on the space-time continuum. For financial markets, the analogous continuum that experiences warping can be referred to as "price-time". Below is a side-by-side comparison of how neighborhoods of similar historical points appear in three-dimensional Euclidean Space and Lorentzian Space: This figure demonstrates how Lorentzian space can better accommodate the warping of price-time since the Lorentzian distance function compresses the Euclidean neighborhood in such a way that the new neighborhood distribution in Lorentzian space tends to cluster around each of the major feature axes in addition to the origin itself. This means that, even though some nearest neighbors will be the same regardless of the distance metric used, Lorentzian space will also allow for the consideration of historical points that would otherwise never be considered with a Euclidean distance metric. Intuitively, the advantage inherent in the Lorentzian distance metric makes sense. For example, it is logical that the price action that occurs in the hours after Chairman Powell finishes delivering a speech would resemble at least some of the previous times when he finished delivering a speech. This may be true regardless of other factors, such as whether or not the market was overbought or oversold at the time or if the macro conditions were more bullish or bearish overall. These historical reference points are extremely valuable for predictive models, yet the Euclidean distance metric would miss these neighbors entirely, often in favor of irrelevant data points from the day before the event. By using Lorentzian distance as a metric, the ML model is instead able to consider the warping of price-time caused by the event and, ultimately, transcend the temporal bias imposed on it by the time series. For more information on the implementation details of the Approximate Nearest Neighbors (ANN) algorithm used in this indicator, please refer to the detailed comments in the source code. █ HOW TO USE Below is an explanatory breakdown of the different parts of this indicator as it appears in the interface: Below is an explanation of the different settings for this indicator: General Settings: Source - This has a default value of "hlc3" and is used to control the input data source. Neighbors Count - This has a default value of 8, a minimum value of 1, a maximum value of 100, and a step of 1. It is used to control the number of neighbors to consider. Max Bars Back - This has a default value of 2000. Feature Count - This has a default value of 5, a minimum value of 2, and a maximum value of 5. It controls the number of features to use for ML predictions. Color Compression - This has a default value of 1, a minimum value of 1, and a maximum value of 10. It is used to control the compression factor for adjusting the intensity of the color scale. Show Exits - This has a default value of false. It controls whether to show the exit threshold on the chart. Use Dynamic Exits - This has a default value of false. It is used to control whether to attempt to let profits ride by dynamically adjusting the exit threshold based on kernel regression. Feature Engineering Settings: Note: The Feature Engineering section is for fine-tuning the features used for ML predictions. The default values are optimized for the 4H to 12H timeframes for most charts, but they should also work reasonably well for other timeframes. By default, the model can support features that accept two parameters (Parameter A and Parameter B, respectively). Even though there are only 4 features provided by default, the same feature with different settings counts as two separate features. If the feature only accepts one parameter, then the second parameter will default to EMA-based smoothing with a default value of 1. These features represent the most effective combination I have encountered in my testing, but additional features may be added as additional options in the future. Feature 1 - This has a default value of "RSI" and options are: "RSI", "WT", "CCI", "ADX". Feature 2 - This has a default value of "WT" and options are: "RSI", "WT", "CCI", "ADX". Feature 3 - This has a default value of "CCI" and options are: "RSI", "WT", "CCI", "ADX". Feature 4 - This has a default value of "ADX" and options are: "RSI", "WT", "CCI", "ADX". Feature 5 - This has a default value of "RSI" and options are: "RSI", "WT", "CCI", "ADX". Filters Settings: Use Volatility Filter - This has a default value of true. It is used to control whether to use the volatility filter. Use Regime Filter - This has a default value of true. It is used to control whether to use the trend detection filter. Use ADX Filter - This has a default value of false. It is used to control whether to use the ADX filter. Regime Threshold - This has a default value of -0.1, a minimum value of -10, a maximum value of 10, and a step of 0.1. It is used to control the Regime Detection filter for detecting Trending/Ranging markets. ADX Threshold - This has a default value of 20, a minimum value of 0, a maximum value of 100, and a step of 1. It is used to control the threshold for detecting Trending/Ranging markets. Kernel Regression Settings: Trade with Kernel - This has a default value of true. It is used to control whether to trade with the kernel. Show Kernel Estimate - This has a default value of true. It is used to control whether to show the kernel estimate. Lookback Window - This has a default value of 8 and a minimum value of 3. It is used to control the number of bars used for the estimation. Recommended range: 3-50 Relative Weighting - This has a default value of 8 and a step size of 0.25. It is used to control the relative weighting of time frames. Recommended range: 0.25-25 Start Regression at Bar - This has a default value of 25. It is used to control the bar index on which to start regression. Recommended range: 0-25 Display Settings: Show Bar Colors - This has a default value of true. It is used to control whether to show the bar colors. Show Bar Prediction Values - This has a default value of true. It controls whether to show the ML model's evaluation of each bar as an integer. Use ATR Offset - This has a default value of false. It controls whether to use the ATR offset instead of the bar prediction offset. Bar Prediction Offset - This has a default value of 0 and a minimum value of 0. It is used to control the offset of the bar predictions as a percentage from the bar high or close. Backtesting Settings: Show Backtest Results - This has a default value of true. It is used to control whether to display the win rate of the given configuration. █ WORKS CITED (1) R. Giusti and G. E. A. P. A. Batista, "An Empirical Comparison of Dissimilarity Measures for Time Series Classification," 2013 Brazilian Conference on Intelligent Systems, Oct. 2013, DOI: 10.1109/bracis.2013.22. (2) Y. Kerimbekov, H. Ş. Bilge, and H. H. Uğurlu, "The use of Lorentzian distance metric in classification problems," Pattern Recognition Letters, vol. 84, 170–176, Dec. 2016, DOI: 10.1016/j.patrec.2016.09.006. (3) A. Bagnall, A. Bostrom, J. Large, and J. Lines, "The Great Time Series Classification Bake Off: An Experimental Evaluation of Recently Proposed Algorithms." ResearchGate, Feb. 04, 2016. (4) H. Ş. Bilge, Yerzhan Kerimbekov, and Hasan Hüseyin Uğurlu, "A new classification method by using Lorentzian distance metric," ResearchGate, Sep. 02, 2015. (5) Y. Kerimbekov and H. Şakir Bilge, "Lorentzian Distance Classifier for Multiple Features," Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods, 2017, DOI: 10.5220/0006197004930501. (6) V. Surya Prasath et al., "Effects of Distance Measure Choice on KNN Classifier Performance - A Review." . █ ACKNOWLEDGEMENTS @veryfid - For many invaluable insights, discussions, and advice that helped to shape this project. @capissimo - For open sourcing his interesting ideas regarding various KNN implementations in PineScript, several of which helped inspire my original undertaking of this project. @RikkiTavi - For many invaluable physics-related conversations and for his helping me develop a mechanism for visualizing various distance algorithms in 3D using JavaScript @jlaurel - For invaluable literature recommendations that helped me to understand the underlying subject matter of this project. @annutara - For help in beta-testing this indicator and for sharing many helpful ideas and insights early on in its development. @jasontaylor7 - For helping to beta-test this indicator and for many helpful conversations that helped to shape my backtesting workflow @meddymarkusvanhala - For helping to beta-test this indicator @dlbnext - For incredibly detailed backtesting testing of this indicator and for sharing numerous ideas on how the user experience could be improved.
Pilihan Editor
Penunjuk Skrip Pine™
35
Dynamic Linear Regression ChannelsPlots new linear regression channels from points where a previous channel is broken thus keeping the length of bars in the trend dynamic. Regression channels are useful in detecting trend changes, support and resistance levels and to trade mean reversions. Note: Setting higher values of upper and lower deviation may result in error if the price never breaks the channel and the script references too many bars than supported.
Pilihan Editor
Penunjuk Skrip Pine™
34
RedK K-MACD : a MACD with some more musclesMoving Averages are probably the most commonly used analysis tools, and MACD is possibly the first charting indicator a trader gets to learn about. MACD Basic concept ---------------------------- Without repeating all the tons of documentation about what MACD does, let's quickly re-visit the MACD concept from a 10-mile altitude (note we're keen on simplifying here rather than being technically accurate - so please forgive the use of any "common lingos") - MACD goal is to represent the distance between 2 Moving Averages (MAs) - one fast and one slow, relatively - as an unrestricted zero-based oscillator. - The value of the main MACD line is the distance, or the displacement between the 2 MA's - usually a signal line is used (which is another MA of that distance value) to enable better visualization of the change (and rate of change, since this is all depicted on a time axis) of that displacement - this represents price momentum (price movement in the recent period versus movements for a relatively longer period). - the difference between the main MACD line and its signal is then represented as a histogram above and below the zero line. in this case, that histogram is really redundant, since it shows a value that is already represented visually by the main line and its signal line. How K-MACD is different --------------------------------- K-MACD takes that simple concept of the classic MACD and expands around it - the idea is to use the same simple approach to representing price momentum while bringing in more insight to price moves in the short, medium and long terms, ability to represent more than 2 MA's and to enable better identification of tradeable patterns (like Volatility Contraction and others) - while still keeping things simple and visually clean. K-MACD is an indicator that allows us to view how price moves against 3 moving averages: a fast / slow pair, and a "market" Filter or Baseline (very long) that will be used as a flag for Bear/Bull market mode. Many traders and trading literature use the 200 day (40 week) SMA as that key filter so in total, there are 4 MA lines in K-MACD (excluding the "orange" signal line): * Price Proxy: Which is a very fast moving average that will represent the price itself - let's use a WMA(3) or something close to that here - there will be a signal line to enable better visualization of this similar to a classic MACD - that's the orange line * Fast & Slow MA's : Use whatever represents the "medium term" momentum for your trading - Some traders use 20 and 50, others use 10 and 20 .. if on your price chart, you keep using a pair of MA's for this, use the same settings in K-MACD - these will be represented by the 3-color Momentum Bars that fluctuate above and below the baseline * Filter/Baseline MA: Should be your long (Bullish/Bearish Mode) MA. so 100 or 200 or any other value you consider your market to be bearish below and bullish above. on K-MACD this is actually the blue zero line - everything else is "relative" to it Review the sample chart which explains various elements and the "price chart" setup that K-MACD represents. With K-MACD you can clean up your chart from those various Moving Averages - or use a different set than the ones you already have K-MACD represent - or other indicators (like ATR channels..etc) Other "muscles" in the K-MACD --------------------------------------------- - Relative vs Classic Calculation Mode A key issue with the classic MACD is that the displacement between the 2 moving averages is represented as "absolute or direct" values - as the price of the underlying increases with time, you can't really use these values to make useful comparison between the past and now (see below example) - also you can't use them to compare 2 different instruments. - The "Relative" calculation option in K-MACD addresses that issue by relating all "distances" to the Baseline MA as percentage (above or below) - you can see this clear when you look at the above chart the far left versus the far right and compare K-MACD with the classic MACD - the Classic option is still available - More MA "type" options for all MA lines: choose between SMA, EMA, WMA, and RSS_WMA (which i use a lot in my trading and is my default for the Price Proxy) - More Alerts: a total or 9 alerts (in 3 groups) are available with K-MACD (Momentum above or below baseline, Price Proxy crossing signal line, and Price Proxy crossing baseline) - New 52 week High / Low markers: These will show as Green/red circles on the zero line in K-MACD. this will only work for 1D timeframe and above, i'm just using a simple approach and would like to keep it that way. - i know i added some more features not covered above :) -- if you have questions about any of the settings, feel free to ask below Closing thoughts ------------------------- K-MACD is a combination of couple of indicators i published in the past (xMACD and Mo_Bars) - so you can go back and read about them if needed - I then added improvements to accommodate ideas from swing trading literature and common practices that i plan to focus on in future. So K-MACD is really part of my own trading setup. I assume here that most traders are familiar with what a MACD is - so kept this post short - if you thing we should expand more about the concepts covered here let me know in the comments - i can make some separate posts with examples and more details. I hope many fellow traders find this work useful - and feel free let me know in comments below if you do.
Penunjuk Skrip Pine™
11
Multi-timeframe Harmonic PatternsHello friends. In recent months I have been busy with my academic research and haven't had much time to publish new scripts. To fill the gap of these months, I decided to publish the indicator Multi-timeframe Harmonic Patterns . Harmonic technical chart patterns can predict the next price trend and provide traders with clues to the price direction, which is one of the indicators widely used by professional traders. (1) Indicator description This indicator is built on ZigZag Multi Time Frame with Fibonacci Retracement@LonesomeTheBlue . Thanks to LonesomeTheBlue for contributing the awesome indicator The indicator supports 6 different timeframes , and 25 different harmonic patterns This indicator supports indicating key indicator prices: entry price, stop loss price, and two take profit prices (2) Key parameters timeframe resolution: The timeframe of the harmonic pattern pivot high/low source: Calculation method of high/low pivot points timeframe pivot period: Minimum period of high/low pivot points delay for confirmations: Wait for N candles to confirm the chart pattern bullish/bearish colors: Bullish/bearish pattern colors enable harmonic patterns: Enable current harmonic patterns show harmonic patterns: Show harmonic patterns found show trading prices of patterns: Show key prices of harmonic patterns (3) Supported Patterns: Gartlay Cypher Bat Deepcrab Crab Butterfly Shark 0-5 AB=CD 3-Drives Anti-Gartlay Anti-Cypher Anti-Bat Anti-Crab Anti-Butterfly Anti-Shark Black-Swan White-Swan Descending-Triangle Ascending-Triangle Symmetrical-Triangle Headers&Shoulders Inverse-Headers&Shoulders Double-Top Double-Bottom ———————————————————————————————————————— 各位朋友大家好。最近几个月我忙于自己的学术研究没有过多时间更新脚本。为弥补这几个月的空缺，我决定发布该 多时间周期的谐波指标 。谐波技术图表形态在一定程度上可以预测下一个价格走势，为交易者提供价格方向的线索，是广大专业交易人员广泛使用的指标之一。 (1) 指标说明 该指标建立于 ZigZag Multi Time Frame with Fibonacci Retracement@LonesomeTheBlue ，感谢LonesomeTheBlue贡献的出色指标 该指标支持 6种不同的时间周期 ，以及 25种不同的谐波形态 该指标支持指示关键的指标价格：入场价格、止损价格、以及两种止盈价格 (2) 关键参数 timeframe resolution: 谐波形态的时间周期 pivot high/low source: 高/低枢纽点的计算方式 timeframe pivot period: 高/低枢纽点的最小周期 delay for confirmations: 等待N个蜡烛以确认图表形态 bullish/bearish colors: 看涨/看跌的形态颜色 enable harmonic patterns: 使能当前的谐波形态 show harmonic patterns: 显示被发现的谐波形态 show trading prices of patterns: 显示谐波形态的关键价格 (3) 支持形态: Gartlay Cypher Bat Deepcrab Crab Butterfly Shark 0-5 AB=CD 3-Drives Anti-Gartlay Anti-Cypher Anti-Bat Anti-Crab Anti-Butterfly Anti-Shark Black-Swan White-Swan Descending-Triangle Ascending-Triangle Symmetrical-Triangle Headers&Shoulders Inverse-Headers&Shoulders Double-Top Double-Bottom
Penunjuk Skrip Pine™
18
DRM StrategyOne of the ways I go when I develop strategies is by reducing the number of parameters and removing fixed parameters and levels. In this strategy, I'm trying to create an RSI indicator with a dynamic length. Length is computed based on the correlation between Price and its momentum. You can set min and max values for the RSI, and if the correlation is close to 1, we'll be at a min RSI value. When it's -1, we'll be at the max level. I got this idea from Sofien Kaabar's book. The strategy is super simple, and there might be much room for improvement. Performance on the deep backtesting is not excellent, so I think the strategy needs some filters for regimes, etc. Thanks to @MUQWISHI for helping me code it. Disclaimer Please remember that past performance may not indicate future results. Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting. This post and the script don’t provide any financial advice.
Strategi Skrip Pine™
5

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BAGAIMANA MENCARI SUMBU ROKETSeperti yang kita lihat dalam carta, bagaimana kaunter SYSCORP membuat kenaikan dalam kadar yang tinggi hampir 90% dalam jangka singkat ( 12 hari )pada bulan Ogos lepas. Kita boleh dan akan menjumpai kaunter sebegini dengan sedikit usaha dan teknikal sebelum ia membuat perubahan ketara yang kita panggil " MEROKET". Sebelum itu, berdasarkan carta harga SYSCORP ia berada dalam downtrend dan mula uptrend pada akhir 2020. Ini ditunjukkan oleh garisan Exponential Moving Average(EMA) iaitu harga mula berada di atas EMA200. Ketika ini ia mencapai 137 % kenaikan. Kenaikan ini ditunjukkan oleh isyarat ST. Kemudian ia membuat pergerakan SIDEWAY lebih kurang 1 tahun 6 bulan dimana jarak nilai support & resistance lebih kurang 10sen. * jika kita amati kaunter seumpamanya nilai ini lebih kurang sama. Dan bulan ogos lepas ia breaks resistance dan meroket sebanyak 85% dalam masa 12 hari. Keadaan sebeginilah yang kita hendak cari...!!! Adakah sukar??? Tidak sukar dengan sedikit kerajinan, teknikal asas dan kesabaran... BAGAIMANA? STEPS; 1. Cari kaunter nilai harga 30sen ke atas, yang UPTREND dan bergerak SIDEWAY selepas uptrend tadi. Atau cari kaunter DOWNTREND dan bergerak SIDEWAY. 2. Kenalpasti jarak/range harga antara support & resistance ketika ia bergerak SIDEWAY tadi. Jarak yang signifikan ialah 10 sen. 3. Permulaan sumbu apabila EMA30 cross-up EMA100. Marking dan observe. Masukkan dalam list atau alert. Harga tidak akan meroket terus. Di sini ia menuntu kesabaran. kebiasaannya ia membuat " test" di resistance, dan pullback, beberapa kali. Kemudian harga sedikit demi sedikit menaik ke resistance dan mula BREAKS reistance seterusnya meroket ke awan. *NOTA 1. ST di carta ialah signal SUPER TREND iaitu EMA30 cross-up EMA100. Ini ialah permulaan sebelum ia bull/membuat kenaikan. 2. KESABARAN. Ingat, harga bukannya terus meroket pada ST. 3. PULLBACK. Retailer akan out kerana harga mula turun. Whales akan in/sambut di support. 4. Jika harga pecah support SIDEWAY maka teknikal ini terbatal. Jarang berlaku tetapi tidak mustahil. STRONG support sangat penting untuk dinilai. PENAFIAN : CATATAN INI BUKANLAH BUY/SELL CALL, HANYA IDEA DAN ANALISIS KAJIAN UNTUK PENDIDIKAN. TAKE AT YOUR OWN RISK.
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Bagaimana membina pelan dagangan yang mantapHai semua! 👋 Pada hari ini, kita akan melihat kepada bagaimana untuk membina satu pelan dagangan yang mantap di dalam beberapa langkah mudah. Pada masa ramai pedagang yang berjaya selalunya menggunakan pelbagai 'pembolehubah' yang berbeza apabila mengenalpasti dagangan, keputusan utama dalam melakukan proses pemilihan untuk semua pelan dagangan yang bagus akan selalunya kekal sama. Jadi, kami akan melihat kepada beberapa perkara utama yang anda sepatutnya pertimbangkan untuk pelan dagangan anda sendiri. Jom kita bermula 👇 Pemilihan Aset 🏦🏦 Semua pelan dagangan yang bagus perlu mendefinasikan bagaimana mereka akan memilih jenis aset untuk di dagangkan. Untuk pedagang Pasaran Hadapan dan FX, ini ialah satu proses yang mudah kerana kepelbagaian simbol yang boleh didagangkan adalah kecil. Akan tetapi, untuk pedagang Ekuiti dan Kripto, kepelbagaian simbol adalah sangat besar. Bagaimanakah anda mengetahui simbol yang mana mewakili peluang yang paling besar dan risiko/ganjaran terbaik? Mempunyai satu set kriteria untuk mencari peluang yang anda mahu dagangkan adalah sangat penting untuk memaksimumkan nilai jangkaan strategi anda. Sebagai contoh, seorang pedagang harian saham mungkin mencari saham-saham yang membuat lonjakan jurang semalaman yang lebih dari 4%, pada X jumlah volum/saham didagangkan. Atau, seorang pedagang ayunan kripto mungkin mencari matawang kripto yang cair dengan keadaan terlebih jual atau terlebih beli yang boleh memberikan satu peluang balikan yang bagus. Tidak kira apapun aset, untuk pedagang selalunya ada dua perkara utama yang perlu anda perhatikan: Ketidakstabilan ✅ Kecairan ✅ Jika satu aset tidak mempunyai kecairan yang cukup, ia akan menyukarkan anda untuk masuk dan keluar dari posisi dagangan yang besar dari masa ke semasa. Jika satu aset tidak mempunyai ketidakstabilan yang cukup, ia akan menjadi sukar untuk menjana keuntungan mutlak dari julat dagangan yang kecil. Namun ini bukanlah selalunya terjadi, kerana ada beberapa pilihan strategi untuk mendapat keuntungan daripada ketidakstabilan yang kecil, tetapi untuk pedagang semerta, perkara ini sangat penting. Logik Pelaksanaan 🧠🧠 Sebaik sahaja anda mengetahui apakah aset yang anda mahu dagangkan, langkah seterusnya adalah untuk menentukan apakah yang dianggap sebagai peluang dagangan. Hampir semua aset bergerak setiap hari - apakah "persediaan" yang anda boleh definasikan untuk diri anda yang dapat menawarkan risiko/ganjaran terbaik? Pelan dagangan terbaik mempunyai logik yang kelihatan seperti satu salasilah keputusan, supaya pedagang tidak perlu memikirkan terlalu banyak mengenai proses - kesemua keputusan sukar telah dilakukan sebelum situasi semasa berlaku. Salasilah keputusan ini boleh menjadi sangat kompleks, tetapi selagi mana anda mencipta dan selesa dengan logik pelaksaan anda sendiri, anda akan boleh mengikutinya dan menambahbaik dari masa ke semasa. Ada dua elemen penting untuk diambilkira apabila mencipta logik keputusan: Arah ✅ Pelaksanaan ✅ Ada beberapa pedagang selesa melakukan dagangan di mana-mana arah, akan tetapi ramai pedagang yang hanya selesa melakukan satu arah dagangan sahaja, kerana ia adalah lebih mudah untuk meringkaskan apa yang anda cari dalam satu dagangan. Disebabkan ini, kebanyakan dana dan pedagang akan mendapatkan satu "pandangan" dahulu. Sebagai contoh: "Saya hanya akan mencari dagangan panjang apabila aset lebih tinggi daripada moving average 20 hari nya." ATAU "Jika ISM PMI ialah lebih besar daripada 50, ketika itu baru saya akan mula memikirkan untuk membeli saham." Kemudian, sebaik sahaja anda tahu arah mana yang anda mahu dagangkan (boleh jadi kedua-dua arah!), memikirkan secara TEPAT apa yang menyebabkan anda masuk dan keluar satu dagangan menjadi kepentingan untuk anda. Sebagai contoh: "Jika saya mencari satu masukan panjang di dalam satu aset menaik, saya hanya akan membeli pada 30 hari tertinggi dan menetapkan henti saya pada 30 hari terendah." Mempunyai kedua-dua arah dan pelaksanaan membantu menjelaskan dengan lebih tepat apakah yang dimaksudkan dengan satu peluang dagangan, dan apakah ia hanya satu corak yang wujud di dalam fikiran anda sahaja. Ia juga penting untuk mengawal risiko anda dan mengeluarkan anda dari keadaan yang buruk sekiranya ia terjadi. Pengurusan Tunai 💵💵 Mencari aset untuk didagangkan dan mendagangkan mereka mengikut pelan berkualiti tinggi tidak memberikan makna sekiranya anda kehilangan semuanya di dalam satu dagangan yang anda letakkan posisi saiz terlalu besar. Disebabkan ini, pelan dagangan terbaik akan memasukkan elemen risiko dan penurunan dengan merancang untuk senario terburuk. Strategi biasa yang digunakan untuk mengawal risiko berkisar dalam membina saiz posisi (sebagai contoh, merisikokan tidak lebih daripada 1-5% modal anda pada satu-satu masa) menggunakan had tema, had sektor dan lain-lain. Risiko ialah satu keputusan yang anda lakukan semasa perjalanan masuk, bukannya pada perjalanan keluar. Apabila meletakkan satu dagangan, mengetahui ~ dengan tepat apa yang anda risikokan, dan bagaimana ini memenuhi strategi pengurusan posisi menyeluruh anda. Lihat artikel ini untuk maklumat lebih lanjut. Itu dia! Tiga langkah pantas untuk membina satu pelan dagangan gagah yang sedia untuk menerima tumbuk terajang pasaran. Jadi, apa lagi anda tunggu? Pergi bekerja 😉 -Pasukan TradingView ❤️
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Holy Grail Pelabur - Kitaran Perniagaan/EkonomiKitaran perniagaan menerangkan bagaimana ekonomi berkembang dan menguncup dari semasa ke semasa. Ia adalah pergerakan menaik dan menurun keluaran dalam negara kasar bersama-sama dengan kadar pertumbuhan jangka panjangnya. Kitaran perniagaan terdiri daripada 6 fasa/peringkat: 1. Pengembangan 2. Puncak 3. Kemelesetan 4. Kemurungan 5. BAWAH 6. Pemulihan 1) Pengembangan Sektor Terjejas : Teknologi, budi bicara Pengguna Pengembangan adalah peringkat pertama kitaran perniagaan. Ekonomi bergerak perlahan ke atas, dan kitaran bermula. Kerajaan mengukuhkan ekonomi: * Menurunkan cukai * Tingkatkan perbelanjaan. - Apabila pertumbuhan perlahan, bank pusat mengurangkan kadar untuk menggalakkan perniagaan meminjam. - Apabila ekonomi berkembang, penunjuk ekonomi berkemungkinan menunjukkan isyarat positif, seperti pekerjaan, pendapatan, upah, keuntungan, permintaan dan penawaran. - Peningkatan dalam pekerjaan meningkatkan keyakinan pengguna meningkatkan aktiviti dalam pasaran perumahan, dan pertumbuhan menjadi positif. Tahap permintaan yang tinggi dan bekalan yang tidak mencukupi menyebabkan kenaikan harga pengeluaran. Pelabur mengambil pinjaman dengan kadar yang tinggi untuk mengisi tekanan permintaan. Proses ini berterusan sehingga ekonomi menjadi baik untuk pengembangan. 2) Puncak: Sektor Terjejas : Kewangan, tenaga, bahan - Peringkat kedua kitaran perniagaan ialah puncak yang menunjukkan pertumbuhan maksimum ekonomi. Mengenal pasti titik akhir pengembangan adalah tugas yang paling kompleks kerana ia boleh bertahan selama bertahun-tahun. - Fasa ini menunjukkan pengurangan dalam kadar pengangguran. Pasaran meneruskan tinjauan positifnya. Semasa pengembangan, bank pusat mencari tanda-tanda tekanan harga bangunan, dan peningkatan kadar boleh menyumbang kepada kemuncak ini. Bank pusat juga cuba melindungi ekonomi daripada inflasi pada peringkat ini. - Memandangkan kadar pekerjaan, pendapatan, gaji, keuntungan, permintaan & penawaran sudah tinggi, tiada kenaikan lagi. - Pelabur akan menghasilkan lebih banyak lagi untuk mengisi tekanan permintaan. Oleh itu, pelaburan dan produk akan menjadi mahal. Pada ketika ini, pelabur tidak akan mendapat pulangan disebabkan oleh inflasi. Harga jauh lebih tinggi untuk pembeli membeli. Daripada situasi ini, kemelesetan berlaku. Ekonomi berbalik dari peringkat ini. 3) Kemelesetan: Sektor Terjejas : Utiliti, penjagaan kesihatan, keperluan pengguna - Dua suku berturut-turut penurunan berturut-turut dalam keluaran dalam negara kasar membentuk kemelesetan. - Kemelesetan diikuti oleh fasa puncak. Dalam fasa ini penunjuk ekonomi mula lebur. Permintaan terhadap barangan tersebut menurun kerana harga yang mahal. Bekalan akan terus meningkat, dan sebaliknya, permintaan akan mula merosot. Itu menyebabkan "lebihan bekalan" dan akan menyebabkan kejatuhan harga. 4) Kemurungan: - Dalam kemelesetan yang lebih berpanjangan, ekonomi memasuki fasa kemurungan. Tempoh malaise dipanggil kemurungan. Kemurungan tidak kerap berlaku, tetapi apabila ia berlaku, nampaknya tiada jumlah rangsangan dasar yang boleh mengangkat pengguna dan perniagaan keluar daripada kemerosotan mereka. Apabila ekonomi merosot dan jatuh di bawah pertumbuhan yang stabil, peringkat ini dipanggil kemurungan. - Pengguna tidak meminjam atau berbelanja kerana mereka pesimis terhadap prospek ekonomi. Apabila bank pusat mengurangkan kadar faedah, pinjaman menjadi murah, tetapi perniagaan gagal memanfaatkan pinjaman kerana mereka tidak dapat melihat gambaran yang jelas tentang bila permintaan akan mula meningkat. Permintaan untuk pinjaman akan berkurangan. Perniagaan akhirnya bergantung pada inventori & pengeluaran pare back, yang telah mereka hasilkan. - Syarikat memberhentikan semakin ramai pekerja, dan kadar pengangguran meningkat dan keyakinan semakin mendatar. 5) BAWAH: - Apabila pertumbuhan ekonomi menjadi negatif, prospek kelihatan tiada harapan. Kemerosotan selanjutnya dalam permintaan dan penawaran barangan dan perkhidmatan akan menyebabkan lebih banyak kejatuhan harga. - Ia menunjukkan keadaan negatif maksimum apabila ekonomi mencapai titik terendah. Semua penunjuk ekonomi akan menjadi lebih teruk. Cth. Kadar pengangguran tertinggi, dan Tiada permintaan untuk barangan dan perkhidmatan(paling rendah), dsb. Selepas selesai, masa yang baik bermula dengan fasa pemulihan. 6) Pemulihan Sektor yang terjejas : Perindustrian, bahan, hartanah - Akibat harga yang rendah, ekonomi mula pulih daripada kadar pertumbuhan negatif, dan permintaan dan pengeluaran kedua-duanya mula meningkat. - Syarikat berhenti membuang pekerja dan mula mencari untuk memenuhi tahap permintaan semasa. Akibatnya, mereka terpaksa mengupah. Apabila bulan berlalu, ekonomi sedang berkembang. - Kitaran perniagaan adalah penting kerana pelabur cuba menumpukan pelaburan mereka kepada pelaburan yang dijangka akan berjaya pada masa tertentu kitaran. - Kerajaan dan bank pusat juga mengambil tindakan untuk mewujudkan ekonomi yang sihat. Kerajaan akan meningkatkan perbelanjaan dan juga mengambil langkah untuk meningkatkan pengeluaran. Selepas fasa pemulihan, ekonomi kembali memasuki fasa pengembangan. Syurga Selamat/Stok Defensif - Ia mengekalkan atau menjangkakan nilainya semasa krisis, kemudian melakukannya dengan baik. Kita juga boleh mengharapkan pulangan yang baik dalam kelas aset ini. Cth. utiliti, penjagaan kesihatan, barang keperluan pengguna, dsb. ("KITA AKAN MEMBINCANGKAN LEBIH LANJUT DALAM ARTIKEL AKAN DATANG AKIBAT PANJANG ARTIKEL.") Maafkan saya atas halangan komunikasi. @Money_Dictators
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contoh kenal pasti salah satu CIRI2 asas 'bullish flag pattern'NOTE: ini bukan BUY CALL . ini memerlukan kajian bersama DAN tolong kaji ikut pemahaman masing-masing dan tidak bertanggungjawap sebarang kerugian. Penafian : Kajian diatas bertujuan untuk KITA bersama sama mengkaji dan bukanlah bertujuan untuk membeli atau menjual instrumen ini . Berdagang Diatas Risiko Sendiri #strong&loyal #ma100ma50ZZL&goldencross #4eDucationOnly #KISS 1.abaikan konter di carta kerana bukan konter ini yang hendak di berikan tumpuan TETAPI apa yang sudah berlaku DAN MUNGKIN akan berlaku mengikut apa yang di maksudkan dengan Bullish Flag Pattern. Kebiasaannya contoh bullish flag pattern di di'hidangkan' kepada kita semua SETELAH berlakunya/complete pattern ini , tetapi kali ini mungkin berbeza sedikit. Berlaku atau tidak bukanlah menjadi keutamaan , yang kita semua termasuk iols dapat pelajari sesuatu. 2.APA yang iols faham secara asasnya dan se'simple' , untuk corak ini harus bermula dengan adanya kenaikan mendadak diikuti volume relatif yang luarbiasa/ meyakinkan. 3.terbahagi kepada 2 elemen : pole dan flag pole : kenaikan harga yang mendadak dengan body candle yang besar dan volume yang kuat flag : berlaku pullback yang lemah , candle kecil & volume sell yang tinggi memungkinkan pentanda seperti ciri2 perkara yang dibincangkan.Pada peringkat ini juga carta akan menyaksikan munculnya konsolidasi 4. selebihnya boleh rujuk aliran seperti carta ( 1 , 2 & 3) Untuk semua perkara di atas eloklah kita kaji bersama sebelum membuat apa jua keputusan ,kerana kitalah yang bertanggungjawap diatas segala keputusan. b egitulah dunia TA, perkara sama tetapi lihat berbeza2 tiada yang betul atau salah kerana ianya belum berlaku .
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crvbtc- membuat falling wedge bo beserta rebounce sempurna ?NOTE: ini bukan BUY CALL . ini memerlukan kajian bersama DAN tolong kaji ikut pemahaman masing-masing dan tidak bertanggungjawap sebarang kerugian. Penafian : Kajian diatas bertujuan untuk KITA bersama sama mengkaji dan bukanlah be yangrtujuan untuk membeli atau menjual instrumen ini . Berdagang Diatas Risiko Sendiri #strong&loyal #ma100ma50ZZL&goldencross #4eDucationOnly #KISS -posting kedua menggunakan video ( jika ada salah silap mohon tunjuk ajar ku sifu) -segala penerangan ada di video -R/R ratio 1:3 begitulah dunia TA, perkara sama tetapi lihat berbeza2 . tiada yang betul atau salah kerana ianya belum berlaku
IFCAMSC ANALISA Gelombang Ellliot PENDIDIKAN GELOMBANG ELLIOT CARA MUDAH ASAS PERMULAAN PENGIRAAN GELOMBANG ELLIOT 1. Buka Chart Trading View 2. Pilih Kaunter 3. Buka “Time Frame” Mingguan (Weekly) 4. Kenal Pasti Struktur Pergerakan Harga Pasaran (High & Low- HH -LL) 5. Kenal Pasti Corak Struktur Pergerakan Harga Pasaran 6. Kenal Pasti Arah Pergerakan Harga Pasaran ( Uptrend @ Downtrend) 7. Kenal Pasti & tandakan Harga Tertinggi & terendah di Chart 8. Selepas itu buka “Time Frame” Harian -Daily 9. Sila Guna Alat “Lanjutan Fib Berdasarkan arah Aliran ( Fibonacci Extension ) 10. Klik Alat Fibo Extension i. Pertama - klik pada Harga terendah (LL), ii. Kedua – Klik pada Harga Tertinggi (HH) iii. Ketiga – Klik pada Harga rendah (HL) 11. Fibonacci extension akan memberikan tahap aras sebagai panduan sahaja 12. Pengiraan untuk gelombang satu adalah dengan mengenal pasti corak yang kerap berlaku iaitu Pepenjuru Awal ( Leading Diagonal ) 13. Peraturan nya adalah seperti IDEA Pendidikan Terdahulu : 14. 15. 16. 17. 18. 19. Sila rujuk Video ini & selalu mengikuti saya utk Video PENDIDIKAN EW akan datang 20. Semoga Bermanfaat kepada Semua *Penafian : Semua Idea Pelan dagangan ( Trading Plan Idea) ini adalah bertujuan pembelajaran & kajian Penulis semata-mata, *Bagi tujuan pembelian & jual saham sila rujuk kepada pihak wakil " Remiser atau Perunding pakar Saham " . *Segala pembelian atau penjualan atau juga kerugian atas transaksi saham , adalah tanggungjawab sendiri . Peringatan Mesra : Kawal emosi , Jaga kapital & displin dagangan Mulakan dengan Bismillah & Selawat sebelum dagangan . Sekian Terima kasih . Dean Mentari
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