RiskCalc FX & GoldRiskCalc FX & Gold is a multi-market position sizing tool designed to help you manage risk quickly and accurately. With this script, simply enter your account capital, the percentage of risk you wish to take, and your stop in ticks. Depending on the selected market—Forex or XAUUSD—the script automatically adjusts its calculations:
Forex: Assumes 1 lot equals 100,000 units.
XAUUSD: Assumes 1 lot equals 100 ounces.
The script calculates your risk in dollars and, using a fixed value of 1 USD per tick per lot, determines the ideal position size in both lots and total contracts. Results are displayed in a clear, centralized table at the top of the chart for real-time decision-making.
Perfect for traders operating across multiple markets who need an automated and consistent approach to risk management.
Cari dalam skrip untuk "文华财经tick价格"
Bullish Reversal Bar Strategy [Skyrexio]Overview
Bullish Reversal Bar Strategy leverages the combination of candlestick pattern Bullish Reversal Bar (description in Methodology and Justification of Methodology), Williams Alligator indicator and Williams Fractals to create the high probability setups. Candlestick pattern is used for the entering into trade, while the combination of Williams Alligator and Fractals is used for the trend approximation as close condition. Strategy uses only long trades.
Unique Features
No fixed stop-loss and take profit: Instead of fixed stop-loss level strategy utilizes technical condition obtained by Fractals and Alligator or the candlestick pattern invalidation to identify when current uptrend is likely to be over (more information in "Methodology" and "Justification of Methodology" paragraphs)
Configurable Trading Periods: Users can tailor the strategy to specific market windows, adapting to different market conditions.
Trend Trade Filter: strategy uses Alligator and Fractal combination as high probability trend filter.
Methodology
The strategy opens long trade when the following price met the conditions:
1.Current candle's high shall be below the Williams Alligator's lines (Jaw, Lips, Teeth)(all details in "Justification of Methodology" paragraph)
2.Price shall create the candlestick pattern "Bullish Reversal Bar". Optionally if MFI and AO filters are enabled current candle shall have the decreasing AO and at least one of three recent bars shall have the squat state on the MFI (all details in "Justification of Methodology" paragraph)
3.If price breaks through the high of the candle marked as the "Bullish Reversal Bar" the long trade is open at the price one tick above the candle's high
4.Initial stop loss is placed at the Bullish Reversal Bar's candle's low
5.If price hit the Bullish Reversal Bar's low before hitting the entry price potential trade is cancelled
6.If trade is active and initial stop loss has not been hit, trade is closed when the combination of Alligator and Williams Fractals shall consider current trend change from upward to downward.
Strategy settings
In the inputs window user can setup strategy setting:
Enable MFI (if true trades are filtered using Market Facilitation Index (MFI) condition all details in "Justification of Methodology" paragraph), by default = false)
Enable AO (if true trades are filtered using Awesome Oscillator (AO) condition all details in "Justification of Methodology" paragraph), by default = false)
Justification of Methodology
Let's explore the key concepts of this strategy and understand how they work together. The first and key concept is the Bullish Reversal Bar candlestick pattern. This is just the single bar pattern. The rules are simple:
Candle shall be closed in it's upper half
High of this candle shall be below all three Alligator's lines (Jaw, Lips, Teeth)
Next, let’s discuss the short-term trend filter, which combines the Williams Alligator and Williams Fractals. Williams Alligator
Developed by Bill Williams, the Alligator is a technical indicator that identifies trends and potential market reversals. It consists of three smoothed moving averages:
Jaw (Blue Line): The slowest of the three, based on a 13-period smoothed moving average shifted 8 bars ahead.
Teeth (Red Line): The medium-speed line, derived from an 8-period smoothed moving average shifted 5 bars forward.
Lips (Green Line): The fastest line, calculated using a 5-period smoothed moving average shifted 3 bars forward.
When the lines diverge and align in order, the "Alligator" is "awake," signaling a strong trend. When the lines overlap or intertwine, the "Alligator" is "asleep," indicating a range-bound or sideways market. This indicator helps traders determine when to enter or avoid trades.
Fractals, another tool by Bill Williams, help identify potential reversal points on a price chart. A fractal forms over at least five consecutive bars, with the middle bar showing either:
Up Fractal: Occurs when the middle bar has a higher high than the two preceding and two following bars, suggesting a potential downward reversal.
Down Fractal: Happens when the middle bar shows a lower low than the surrounding two bars, hinting at a possible upward reversal.
Traders often use fractals alongside other indicators to confirm trends or reversals, enhancing decision-making accuracy.
How do these tools work together in this strategy? Let’s consider an example of an uptrend.
When the price breaks above an up fractal, it signals a potential bullish trend. This occurs because the up fractal represents a shift in market behavior, where a temporary high was formed due to selling pressure. If the price revisits this level and breaks through, it suggests the market sentiment has turned bullish.
The breakout must occur above the Alligator’s teeth line to confirm the trend. A breakout below the teeth is considered invalid, and the downtrend might still persist. Conversely, in a downtrend, the same logic applies with down fractals.
How we can use all these indicators in this strategy? This strategy is a counter trend one. Candle's high shall be below all Alligator's lines. During this market stage the bullish reversal bar candlestick pattern shall be printed. This bar during the downtrend is a high probability setup for the potential reversal to the upside: bulls were able to close the price in the upper half of a candle. The breaking of its high is a high probability signal that trend change is confirmed and script opens long trade. If market continues going down and break down the bullish reversal bar's low potential trend change has been invalidated and strategy close long trade.
If market really reversed and started moving to the upside strategy waits for the trend change form the downtrend to the uptrend according to approximation of Alligator and Fractals combination. If this change happens strategy close the trade. This approach helps to stay in the long trade while the uptrend continuation is likely and close it if there is a high probability of the uptrend finish.
Optionally users can enable MFI and AO filters. First of all, let's briefly explain what are these two indicators. The Awesome Oscillator (AO), created by Bill Williams, is a momentum-based indicator that evaluates market momentum by comparing recent price activity to a broader historical context. It assists traders in identifying potential trend reversals and gauging trend strength.
AO = SMA5(Median Price) − SMA34(Median Price)
where:
Median Price = (High + Low) / 2
SMA5 = 5-period Simple Moving Average of the Median Price
SMA 34 = 34-period Simple Moving Average of the Median Price
This indicator is filtering signals in the following way: if current AO bar is decreasing this candle can be interpreted as a bullish reversal bar. This logic is applicable because initially this strategy is a trend reversal, it is searching for the high probability setup against the current trend. Decreasing AO is the additional high probability filter of a downtrend.
Let's briefly look what is MFI. The Market Facilitation Index (MFI) is a technical indicator that measures the price movement per unit of volume, helping traders gauge the efficiency of price movement in relation to trading volume. Here's how you can calculate it:
MFI = (High−Low)/Volume
MFI can be used in combination with volume, so we can divide 4 states. Bill Williams introduced these to help traders interpret the interaction between volume and price movement. Here’s a quick summary:
Green Window (Increased MFI & Increased Volume): Indicates strong momentum with both price and volume increasing. Often a sign of trend continuation, as both buying and selling interest are rising.
Fake Window (Increased MFI & Decreased Volume): Shows that price is moving but with lower volume, suggesting weak support for the trend. This can signal a potential end of the current trend.
Squat Window (Decreased MFI & Increased Volume): Shows high volume but little price movement, indicating a tug-of-war between buyers and sellers. This often precedes a breakout as the pressure builds.
Fade Window (Decreased MFI & Decreased Volume): Indicates a lack of interest from both buyers and sellers, leading to lower momentum. This typically happens in range-bound markets and may signal consolidation before a new move.
For our purposes we are interested in squat bars. This is the sign that volume cannot move the price easily. This type of bar increases the probability of trend reversal. In this indicator we added to enable the MFI filter of reversal bars. If potential reversal bar or two preceding bars have squat state this bar can be interpret as a reversal one.
Backtest Results
Operating window: Date range of backtests is 2023.01.01 - 2024.12.31. It is chosen to let the strategy to close all opened positions.
Commission and Slippage: Includes a standard Binance commission of 0.1% and accounts for possible slippage over 5 ticks.
Initial capital: 10000 USDT
Percent of capital used in every trade: 50%
Maximum Single Position Loss: -5.29%
Maximum Single Profit: +29.99%
Net Profit: +5472.66 USDT (+54.73%)
Total Trades: 103 (33.98% win rate)
Profit Factor: 1.634
Maximum Accumulated Loss: 1231.15 USDT (-8.32%)
Average Profit per Trade: 53.13 USDT (+0.94%)
Average Trade Duration: 76 hours
How to Use
Add the script to favorites for easy access.
Apply to the desired timeframe and chart (optimal performance observed on 4h ETH/USDT).
Configure settings using the dropdown choice list in the built-in menu.
Set up alerts to automate strategy positions through web hook with the text: {{strategy.order.alert_message}}
Disclaimer:
Educational and informational tool reflecting Skyrex commitment to informed trading. Past performance does not guarantee future results. Test strategies in a simulated environment before live implementation
These results are obtained with realistic parameters representing trading conditions observed at major exchanges such as Binance and with realistic trading portfolio usage parameters.
Cryptocurrency SentimentOverview
This script focuses on calculating and visualizing the sentiment difference between LONG positions and SHORT positions for a selected cryptocurrency pair on the Bitfinex exchange. It provides a clean and clear visual representation of the sentiment, helping traders analyze market behavior.
Key Features
Dynamic Symbol Selection:
The script automatically detects the cryptocurrency symbol from the chart (syminfo.basecurrency) and dynamically constructs the LONGS and SHORTS ticker symbols.
Works seamlessly for pairs like BTCUSD, ETHUSD, and others available on Bitfinex.
Sentiment Calculation:
The sentiment difference is calculated as:
Sentiment Difference=−1×(100− SHORTS/LONGS ×100)
LONGS : The total number of long positions.
SHORTS : The total number of short positions.
If SHORTS is 0, the value is safely skipped to avoid division errors.
Color Coding:
The script visually highlights the sentiment difference:
Green Line: Indicates that LONG positions are dominant (bullish sentiment).
Red Line: Indicates that SHORT positions are dominant (bearish sentiment).
Zero Reference Line:
A gray horizontal line at 0 helps users quickly identify the transition between bullish (above zero) and bearish (below zero) sentiment.
How It Works
Fetching Data:
The script uses request.security to fetch LONGS and SHORTS data at the current chart timeframe (timeframe.period) for the dynamically generated Bitfinex tickers.
Handling Data:
Missing or invalid data (NaN) is filtered out to prevent errors.
Extreme spikes or irregular values are safely avoided.
Visualization:
The sentiment difference is plotted with dynamic color coding:
Green when LONGS > SHORTS (bullish sentiment).
Red when SHORTS > LONGS (bearish sentiment).
Benefits
Market Sentiment Insight: Helps traders quickly identify if the market is leaning towards bullish or bearish sentiment based on actual LONG and SHORT position data.
Dynamic and Adaptive: Automatically adjusts to the selected cryptocurrency symbol on the chart.
Clean Visualization: Focuses solely on sentiment difference with color-coded signals, making it easy to interpret.
Best Use Cases
Trend Confirmation: Use the sentiment difference to confirm trends during bullish or bearish moves.
Market Reversals: Identify potential reversals when sentiment shifts from positive (green) to negative (red) or vice versa.
Sentiment Monitoring: Monitor the overall market bias for cryptocurrencies like BTC, ETH, XRP, etc., in real-time.
Sample Chart Output
Above Zero → Green Line: Bullish sentiment dominates.
Below Zero → Red Line: Bearish sentiment dominates.
Zero Line → Transition point for shifts in sentiment.
Normalized and Smoothed Cumulative Delta for Top 5 NASDAQ StocksThis script is designed to create a TradingView indicator called **"Normalized and Smoothed Cumulative Delta for Top 5 NASDAQ Stocks."** The purpose of this indicator is to track and visualize the cumulative price delta (the change in price from one period to the next) for the top five NASDAQ stocks: Apple Inc. (AAPL), Microsoft Corporation (MSFT), Alphabet Inc. (GOOGL), Amazon.com Inc. (AMZN), and Meta Platforms Inc. (FB).
### Key Features of the Script:
1. **Ticker Selection**:
- The script focuses on the top five NASDAQ stocks by automatically setting their tickers.
2. **Price Data Retrieval**:
- It fetches the closing prices for each of these stocks using the `request.security` function for the current timeframe.
3. **Delta Calculation**:
- The script calculates the delta for each stock, which is simply the difference between the current closing price and the previous closing price.
4. **Cumulative Delta Calculation**:
- It calculates the cumulative delta for each stock by adding the current delta to the previous cumulative delta. This helps track the total change in price over time.
5. **Summing and Smoothing**:
- The cumulative deltas for all five stocks are summed together.
- The script then applies an Exponential Moving Average (EMA) with a period of 5 to smooth the summed cumulative delta, making the indicator less sensitive to short-term fluctuations.
6. **Normalization**:
- To ensure the cumulative delta is easy to interpret, the script normalizes it to a range of 0 to 1. This is done by tracking the minimum and maximum values of the smoothed cumulative delta and scaling the data accordingly.
7. **Visualization**:
- The normalized cumulative delta is plotted as a smooth line, allowing users to see the overall trend of the cumulative price changes for the top five NASDAQ stocks.
- A horizontal line is added at 0.5, serving as a midline reference, which can help traders quickly assess whether the normalized cumulative delta is above or below its midpoint.
### Usage:
This indicator is particularly useful for traders and investors who want to monitor the aggregated price movements of the top NASDAQ stocks, providing a high-level view of market sentiment and trends. By smoothing and normalizing the data, it offers a clear and concise visualization that can be used to identify potential market turning points or confirm ongoing trends.
Volume Gaps and ImbalancesThis Pine script indicator is designed to visually depict price inefficiencies, as identified by Volume Imbalances (VI) or Gaps. A Volume Gap is a scenario where the wicks of two successive candles don’t intersect, while an Imbalance occurs when only the wicks overlap, leaving the bodies apart. These zones of inefficiency frequently act as magnets for price, with the market striving rebalance in accordance with ICT principles.
Relevance:
Volume Gaps/Imbalances are zones of highly inefficient price delivery as per ICT concepts and represent a very strong draw to price. Price will often seek to rebalance those zones to ensure efficient price delivery. Consequently, these zones can provide good targets for entries in the opposite direction or take profit targets for previous entries in the direction of the Gap/Imbalance.
How It Works:
The indicator keeps track of all Gaps/Imbalances from the beginning of the available history. It automatically removes all mitigated Gaps/Imbalances, which are situations where the price has at least reached the bottom of a bullish gap or the top of a bearish gap.
On the last bar, the most recent valid gaps are highlighted with a box drawn from the start to the end of the gap. The start of a bullish gap is determined by the highest price of the previous candle’s open or close, while for bearish gaps, it’s the lowest price of the previous candle’s open or close. Conversely, the end of a bullish gap is the lowest price of the current candle’s open or close, and for bearish gaps, it’s the highest price of the current candle’s open or close.
To enhance the indicator’s speed and minimize chart noise, only the most recent gaps will be displayed, up to the limit set in the indicator settings.
Each displayed VI/GAP will indicate the size of the imbalance in ticks. For imbalances greater than 3 ticks, which represent stronger draws of liquidity, the color transparency will be reduced, and the text will be made more prominent. Volume Gaps are also marked with a 🧲 emoji for easy visual identification.
The indicator will automatically extend the boxes representing valid imbalances to the current bar for as long as the imbalance is not mitigated.
If an imbalance has been tapped, but not mitigated, the indicator will append 🚩emoji to denote that the imbalance has been partially mitigated and may no longer have as strong of a draw for price.
Configurability:
A user may configure the number of imbalances to show, the setting applies to bullish/bearish imbalances individually. This setting can be set to any value from 1 – 50.
Appearance wise, color, style and color transparency of each box representing an imbalance can be configured. The imbalance box label can be configured by setting the text size, along with the vertical & horizontal alignment.
What makes this indicator different:
Designed with high performance in mind, to reduce impact on chart render time.
Only keeps valid imbalances on the chart, with a limit on the # drawn
Indicates the size of the gap and provides visual markets to denote stronger, weaker and partially mitigated gaps
swinglibraryLibrary "swinglibrary"
This library is for calculating non-repainting swings for further calculation on them.
These swings can later be drawn, but drawing is not part of this library, only the calculation.
What do I need to use the library?
You better include the following constants into your script using this library:
int SWING_NO_ACTION = 0
int SWING_FLIP = 1
int SWING_FLIP_NEW_SWING = 2
int SWING_FLIP_UPDATED = 3
int RELATION_HIGHER = 1
int RELATION_EQUAL = 0
int RELATION_LOWER = -1
Choosing the function, that fits your needs
This library contains 4 functions for calculating swings, the difference between them are the data you get for every swing point and additional average values for length and duration:
swings()
swingsR()
swingsL()
swingsLDR()
The naming scheme of these functions is the following:
The base version swings() is only for the swings containing the following swingPoint type:
swingPoint
Fields:
x (integer) : bar index
y (float) : price
hilo (integer) 1 -> high, -1 -> low
and the return type:
swingReturn
Fields:
swings (array) : array of the last x swing points
newSwingHigh (integer) : flag to detect changes for swing highs see constants (SWING_NO_ACTION, SWING_FLIP_NEW_SWING, SWING_FLIP_UPDATED)
newSwingLow (integer) : flag to detect changes for swing lows see constants (SWING_NO_ACTION, SWING_FLIP_NEW_SWING, SWING_FLIP_UPDATED)
The R in swingsR() stands for relation where the previously shown types do also contain the relation between the swings of the same swing type (highs and lows respectively).
The same goes for L in swingsL() for length containing the price difference between the current and previous swing point in ticks.
And in the following version swingsLDR() there is also the duration between the current and previous point included.
The parameters for the other functions and type definitions include only the ones, that are needed, the "full" version of the function is described here:
swingsLDR(swingSize, dtbStrength, init, SWING_HISTORY_NUM)
Parameters:
swingSize (int) This parameter defines the size of the swings to look after, meaning higher values will lead to bigger swings
dtbStrength (int) Value between 0 and 100 is a factor (%) to the ATR that is used to calculate equal highs/lows (double tops / bottoms).
Higher values will result in a higher tolerance of price difference between the swings.
init (bool) This value is usually set to false on default.
It has a special use case, where we need to reduce memory usage and calculation time on the script using this library by start calculating at x bars back instead of the beginning of the chart.
In this case, we set init = true on the first bar we start calculating the swings on to perform the correct initialization.
SWING_HISTORY_NUM (int) This is the max number of swings that are stored in the array, so only the last SWING_HISTORY_NUM swings are stored in the array to reduce the memory usage.
New ones remove the oldest ones like in a ring buffer.
This is also influencing the average duration and average swing length.
swingPointLDR
Fields:
x (integer) : bar index
y (float) : price
hilo (integer) : 1 -> high, -1 -> low
length (float) : price difference to the previous swing point in ticks
duration (integer) : duration difference to the previous swing point in number of bars
relation (integer) : see constants RELATION_HIGHER, RELATION_EQUAL, RELATION_LOWER: reelation to the previous swing points of the same type (previous high or previous low respectively)
swingReturnLDR
Fields:
swings (array) : array of the last x swing points
newSwingHigh (integer) : flag to detect changes for swing highs see constants (SWING_NO_ACTION, SWING_FLIP_NEW_SWING, SWING_FLIP_UPDATED)
newSwingLow (integer) : flag to detect changes for swing lows see constants (SWING_NO_ACTION, SWING_FLIP_NEW_SWING, SWING_FLIP_UPDATED)
avSwLength (float) : average swing length for the last x swings (depending on the max number of swings)
avSwingDuration (float) : average swing duration for the last x swings (depending on the max number of swings)
EMA 9/21 with Target Price [SS]Hey everyone,
Coming back with my EMA 9/21 indicator.
My original one was removed a long time ago because I didn't really realize that there were already plenty of similar indicators (my bad!) but this one is my unique, Steversteves edition haha.
About the Indicator:
Essentially, it just combines the 2 only EMA's I ever really use (the 9 and 21) with an ATR based analysis to calculate the average range a ticker undergoes after an EMA 9 / 21 Cross-over and Cross-under.
You can see the major example being in the chart above. I use this for dramatic effect as SPY just happened to have topped at the second expected bull target on the daily. But obviously the intention for this indicator is to be used on the smaller timeframes. Let's take a look at some examples with various tickers.
TSLA:
So let's just use the previous day as example (which was Friday). If we look to the chart below:
TSLA did an EMA 9/21 crossover (bullish) in premarket. This put the immediate TP at 234.59. If we play out the chart:
We shot right to it at open.
We then did a cross under with a TP of 225.93, but that was not realized as the sentiment was too bullish. We then cross back over to the upside, putthing next TP at 238.88 which was realized:
NVDA:
On Friday, NVDA was a bit of a mess, lots of whipsaw off open. But once we finally had a cross under with 3 consecutive closes below the EMA9/21 on the 5 minute chart, it solidified the likelihood of a short:
And this was the result:
We came down to the first target, held it actually as support before finally crossing back over, setting the next TP at 475.05. We got 3 consecutive closes above the EMA 9/21, so let's see what happened:
Nothing really, we closed before we got there, but we did make progress towards it.
And last but not least SPY:
We opened the day with a bullish crossover and 3 consecutive closes above the EMA9/21, making our TP 441.38 (chart above). Let's see what happened:
We came just shy of it after the fed release volatility slammed it down, where we got a crossunder (bearish) to a TP of 436.21:
This ended up playing out, we did get a bullish crossover later in the day and so let's see what happened then:
So those are the real examples, most recent examples of trading using this. They are not all perfect, which is intentional because you need to use a bit of your own analysis, of course, when you are using this type of strategy or indicator. The EMA 9/21 is not sufficient generally on its own, but it is very helpful to gauge the immediate PA and whether the expected move aligns with your overall thesis on the day in terms of realistic target prices.
Customizability:
In terms of the customizability, this is a very basic indicator aside from the assessment of ranges. So there really is not a lot to customize.
You can toggle off and on the labels if you do not want them, you can also adjust the lookback length for the ATR assessment. The lookback length is defaulted to 500, I do really highly suggest you leave it at 500 because this has worked well for me and in back-testing, it has performed above my own expectations.
But, that said, you can take this and back-test as you wish with whatever parameters you feel are most appropriate. I haven't back-tested this on every stock known to man, my go to's are SPY, QQQ, sometimes MSFT and so it works well on those. But perhaps some others will have differing results.
Final Thoughts:
That is the indicator in a nutshell! It is really self explanatory and its likely a strategy most of you already know. This just helps to add realistic price targets and context to those cross-overs and cross-unders.
It also works fine on larger timeframes. We can see it on the 1 hour with MSFT:
On the 2 hour hour with QQQ:
And I am sure you can find other examples!
That's it everyone, safe trades!
ATR GOD Strategy by TradeSmart (PineConnector-compatible)This is a highly-customizable trading strategy made by TradeSmart, focusing mainly on ATR-based indicators and filters. The strategy is mainly intended for trading forex , and has been optimized using the Deep Backtest feature on the 2018.01.01 - 2023.06.01 interval on the EUR/USD (FXCM) 15M chart, with a Slippage value of 3, and a Commission set to 0.00004 USD per contract. The strategy is also made compatible with PineConnector , to provide an easy option to automate the strategy using a connection to MetaTrader. See tooltips for details on how to set up the bot, and check out our website for a detailed guide with images on how to automate the strategy.
The strategy was implemented using the following logic:
Entry strategy:
A total of 4 Supertrend values can be used to determine the entry logic. There is option to set up all 4 Supertrend parameters individually, as well as their potential to be used as an entry signal/or a trend filter. Long/Short entry signals will be determined based on the selected potential Supertrend entry signals, and filtered based on them being in an uptrend/downtrend (also available for setup). Please use the provided tooltips for each setup to see every detail.
Exit strategy:
4 different types of Stop Losses are available: ATR-based/Candle Low/High Based/Percentage Based/Pip Based. Additionally, Force exiting can also be applied, where there is option to set up 4 custom sessions, and exits will happen after the session has closed.
Parameters of every indicator used in the strategy can be tuned in the strategy settings as follows:
Plot settings:
Plot Signals: true by default, Show all Long and Short signals on the signal candle
Plot SL/TP lines: false by default, Checking this option will result in the TP and SL lines to be plotted on the chart.
Supertrend 1-4:
All the parameters of the Supertrends can be set up here, as well as their individual role in the entry logic.
Exit Strategy:
ATR Based Stop Loss: true by default
ATR Length (of the SL): 100 by default
ATR Smoothing (of the SL): RMA/SMMA by default
Candle Low/High Based Stop Loss: false by default, recent lowest or highest point (depending on long/short position) will be used to calculate stop loss value. Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Candle Lookback (of the SL): 50 by default
Percentage Based Stop Loss: false by default, Set the stop loss to current price - % of current price (long) or price + % of current price (short).
Percentage (of the SL): 0.3 by default
Pip Based Stop Loss: Set the stop loss to current price - x pips (long) or price + x pips (short). Set 'Base Risk Multiplier' to 1 if you would like to use the calculated value as is. Setting it to a different value will count as an additional multiplier.
Pip (of the SL): 10 by default
Base Risk Multiplier: 4.5 by default, the stop loss will be placed at this risk level (meaning in case of ATR SL that the ATR value will be multiplied by this factor and the SL will be placed that value away from the entry level)
Risk to Reward Ratio: 1.5 by default, the take profit level will be placed such as this Risk/Reward ratio is met
Force Exiting:
4 total Force exit on custom session close options: none applied by default. If enabled, trades will close automatically after the set session is closed (on next candle's open).
Base Setups:
Allow Long Entries: true by default
Allow Short Entries: true by default
Order Size: 10 by default
Order Type: Capital Percentage by default, allows adjustment on how the position size is calculated: Cash: only the set cash amount will be used for each trade Contract(s): the adjusted number of contracts will be used for each trade Capital Percentage: a % of the current available capital will be used for each trade
ATR Limiter:
Use ATR Limiter: true by default, Only enter into any position (long/short) if ATR value is higher than the Low Boundary and lower than the High Boundary.
ATR Limiter Length: 50 by default
ATR Limiter Smoothing: RMA/SMMA by default
High Boundary: 1000 by default
Low Boundary: 0.0003 by default
MA based calculation: ATR value under MA by default, If not Unspecified, an MA is calculated with the ATR value as source. Only enter into position (long/short) if ATR value is higher/lower than the MA.
MA Type: RMA/SMMA by default
MA Length: 400 by default
Waddah Attar Filter:
Explosion/Deadzone relation: Not specified by default, Explosion over Deadzone: trades will only happen if the explosion line is over the deadzone line; Explosion under Deadzone: trades will only happen if the explosion line is under the deadzone line; Not specified: the opening of trades will not be based on the relation between the explosion and deadzone lines.
Limit trades based on trends: Not specified by default, Strong Trends: only enter long if the WA bar is colored green (there is an uptrend and the current bar is higher then the previous); only enter short if the WA bar is colored red (there is a downtrend and the current bar is higher then the previous); Soft Trends: only enter long if the WA bar is colored lime (there is an uptrend and the current bar is lower then the previous); only enter short if the WA bar is colored orange (there is a downtrend and the current bar is lower then the previous); All Trends: only enter long if the WA bar is colored green or lime (there is an uptrend); only enter short if the WA bar is colored red or orange (there is a downtrend); Not specified: the color of the WA bar (trend) is not relevant when considering entries.
WA bar value: Not specified by default, Over Explosion and Deadzone: only enter trades when the WA bar value is over the Explosion and Deadzone lines; Not specified: the relation between the explosion/deadzone lines to the value of the WA bar will not be used to filter opening trades.
Sensitivity: 150 by default
Fast MA Type: SMA by default
Fast MA Length: 10 by default
Slow MA Type: SMA
Slow MA Length: 20 by default
Channel MA Type: EMA by default
BB Channel Length: 20 by default
BB Stdev Multiplier: 2 by default
Trend Filter:
Use long trend filter 1: false by default, Only enter long if price is above Long MA.
Show long trend filter 1: false by default, Plot the selected MA on the chart.
TF1 - MA Type: EMA by default
TF1 - MA Length: 120 by default
TF1 - MA Source: close by default
Use short trend filter 1: false by default, Only enter long if price is above Long MA.
Show short trend filter 1: false by default, Plot the selected MA on the chart.
TF2 - MA Type: EMA by default
TF2 - MA Length: 120 by default
TF2 - MA Source: close by default
Volume Filter:
Only enter trades where volume is higher then the volume-based MA: true by default, a set type of MA will be calculated with the volume as source, and set length
MA Type: RMA/SMMA by default
MA Length: 200 by default
Date Range Limiter:
Limit Between Dates: false by default
Start Date: Jan 01 2023 00:00:00 by default
End Date: Jun 24 2023 00:00:00 by default
Session Limiter:
Show session plots: false by default, show market sessions on chart: Sidney (red), Tokyo (orange), London (yellow), New York (green)
Use session limiter: false by default, if enabled, trades will only happen in the ticked sessions below.
Sidney session: false by default, session between: 15:00 - 00:00 (EST)
Tokyo session: false by default, session between: 19:00 - 04:00 (EST)
London session: false by default, session between: 03:00 - 11:00 (EST)
New York session: false by default, session between: 08:00 - 17:00 (EST)
Trading Time:
Limit Trading Time: true by default, tick this together with the options below to enable limiting based on day and time
Valid Trading Days Global: 123567 by default, if the Limit Trading Time is on, trades will only happen on days that are present in this field. If any of the not global Valid Trading Days is used, this field will be neglected. Values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) To trade on all days use: 123457
(1) Valid Trading Days: false, 123456 by default, values represent days: Sunday (1), Monday (2), ..., Friday (6), Saturday(7) The script will trade on days that are present in this field. Please make sure that this field and also (1) Valid Trading Hours Between is checked
(1) Valid Trading Hours Between: false, 1800-2000 by default, hours between which the trades can happen. The time is always in the exchange's timezone
All other options are also disabled by default
PineConnector Automation:
Use PineConnector Automation: false by default, In order for the connection to MetaTrader to work, you will need do perform prerequisite steps, you can follow our full guide at our website, or refer to the official PineConnector Documentation. To set up PineConnector Automation on the TradingView side, you will need to do the following:
1. Fill out the License ID field with your PineConnector License ID;
2. Fill out the Risk (trading volume) with the desired volume to be traded in each trade (the meaning of this value depends on the EA settings in Metatrader. Follow the detailed guide for additional information);
3. After filling out the fields, you need to enable the 'Use PineConnector Automation' option (check the box in the strategy settings);
4. Check if the chart has updated and you can see the appropriate order comments on your chart;
5. Create an alert with the strategy selected as Condition, and the Message as {{strategy.order.comment}} (should be there by default);
6. Enable the Webhook URL in the Notifications section, set it as the official PineConnector webhook address and enjoy your connection with MetaTrader.
License ID: 60123456789 by default
Risk (trading volume): 1 by default
NOTE! Fine-tuning/re-optimization is highly recommended when using other asset/timeframe combinations.
Accumulation Stage Identifier and Strategy around for TradingIn the psychology of trading at any market condition, there are four stage usually occurs on any tickers.
Stage 1 -> Neglect phase or consolidation phase
It occurs when the company does not produce the expected result and waiting for next result.
It can extend for days, weeks, months and years. Never give entry at this stage though that blue-chip told to be cheaper in price.
Stage 2 -> Accumulation
It occurs when the company's earning and sales consistently grows.
It can extend for days, weeks, months but should not expect the continues increase in price, as there will be potential pull-back which can be considered as opportunity to accumulate.
If the company fundamental is good, just give some space at the time of pullback.
Most of the time, the pullback volume will be low to compare to volume at the time of increase.
Usually, the stock that is going through accumulation stage will definitely trade above 200SMA and short term MA will be greater than long term moving average.
Continues the highest high and highest low along with volume.
Stage 3 -> Distribution
It occurs when the company's earning and sales stagnated due to certain reason.
It can extend for days, weeks while the price and volume highly volatile.
High volume while the price low
Typically, the stock that is going through distribution stage will certainly trade below 200SMA and short term MA will be lesser than long term moving average.
Continues the lowest high and lowest low along with volume.
Stage 4 -> Capitalization
Price reaches the 52W low while volume spikes on big down.
In each stage, the price & volume are perfect indicator to highlight the situation and the trader with proper discipline and patients can certainly reap the fruitful outcome of accumulation stage.
Based on this explanation, here is the strategy that is created with 50,90 & 200 Simple moving average and price volume trends (PVT) indicator applied on MACD to signal whenever the PVT convergence and divergence.
Note:
As the indicator designed to signal on the ticker that trade above 200 moving average, it is good to use this strategy on companies that are fundamental strong.
Whenever, there is pull back happens, the strategy might signal for exit, however, here comes the traders patient based on the conviction on the particular chosen stocks.
White being patient is good, disciplinary in following the strategy also important. Hence, consider the action when the stock goes opposite direction from your expectation.
Hope this strategy would help you find the profit.
Happy investing.
T3 Volatility Quality Index (VQI) w/ DSL & Pips Filtering [Loxx]T3 Volatility Quality Index (VQI) w/ DSL & Pips Filtering is a VQI indicator that uses T3 smoothing and discontinued signal lines to determine breakouts and breakdowns. This also allows filtering by pips.***
What is the Volatility Quality Index ( VQI )?
The idea behind the volatility quality index is to point out the difference between bad and good volatility in order to identify better trade opportunities in the market. This forex indicator works using the True Range algorithm in combination with the open, close, high and low prices.
What are DSL Discontinued Signal Line?
A lot of indicators are using signal lines in order to determine the trend (or some desired state of the indicator) easier. The idea of the signal line is easy : comparing the value to it's smoothed (slightly lagging) state, the idea of current momentum/state is made.
Discontinued signal line is inheriting that simple signal line idea and it is extending it : instead of having one signal line, more lines depending on the current value of the indicator.
"Signal" line is calculated the following way :
When a certain level is crossed into the desired direction, the EMA of that value is calculated for the desired signal line
When that level is crossed into the opposite direction, the previous "signal" line value is simply "inherited" and it becomes a kind of a level
This way it becomes a combination of signal lines and levels that are trying to combine both the good from both methods.
In simple terms, DSL uses the concept of a signal line and betters it by inheriting the previous signal line's value & makes it a level.
What is the T3 moving average?
Better Moving Averages Tim Tillson
November 1, 1998
Tim Tillson is a software project manager at Hewlett-Packard, with degrees in Mathematics and Computer Science. He has privately traded options and equities for 15 years.
Introduction
"Digital filtering includes the process of smoothing, predicting, differentiating, integrating, separation of signals, and removal of noise from a signal. Thus many people who do such things are actually using digital filters without realizing that they are; being unacquainted with the theory, they neither understand what they have done nor the possibilities of what they might have done."
This quote from R. W. Hamming applies to the vast majority of indicators in technical analysis . Moving averages, be they simple, weighted, or exponential, are lowpass filters; low frequency components in the signal pass through with little attenuation, while high frequencies are severely reduced.
"Oscillator" type indicators (such as MACD , Momentum, Relative Strength Index ) are another type of digital filter called a differentiator.
Tushar Chande has observed that many popular oscillators are highly correlated, which is sensible because they are trying to measure the rate of change of the underlying time series, i.e., are trying to be the first and second derivatives we all learned about in Calculus.
We use moving averages (lowpass filters) in technical analysis to remove the random noise from a time series, to discern the underlying trend or to determine prices at which we will take action. A perfect moving average would have two attributes:
It would be smooth, not sensitive to random noise in the underlying time series. Another way of saying this is that its derivative would not spuriously alternate between positive and negative values.
It would not lag behind the time series it is computed from. Lag, of course, produces late buy or sell signals that kill profits.
The only way one can compute a perfect moving average is to have knowledge of the future, and if we had that, we would buy one lottery ticket a week rather than trade!
Having said this, we can still improve on the conventional simple, weighted, or exponential moving averages. Here's how:
Two Interesting Moving Averages
We will examine two benchmark moving averages based on Linear Regression analysis.
In both cases, a Linear Regression line of length n is fitted to price data.
I call the first moving average ILRS, which stands for Integral of Linear Regression Slope. One simply integrates the slope of a linear regression line as it is successively fitted in a moving window of length n across the data, with the constant of integration being a simple moving average of the first n points. Put another way, the derivative of ILRS is the linear regression slope. Note that ILRS is not the same as a SMA ( simple moving average ) of length n, which is actually the midpoint of the linear regression line as it moves across the data.
We can measure the lag of moving averages with respect to a linear trend by computing how they behave when the input is a line with unit slope. Both SMA (n) and ILRS(n) have lag of n/2, but ILRS is much smoother than SMA .
Our second benchmark moving average is well known, called EPMA or End Point Moving Average. It is the endpoint of the linear regression line of length n as it is fitted across the data. EPMA hugs the data more closely than a simple or exponential moving average of the same length. The price we pay for this is that it is much noisier (less smooth) than ILRS, and it also has the annoying property that it overshoots the data when linear trends are present.
However, EPMA has a lag of 0 with respect to linear input! This makes sense because a linear regression line will fit linear input perfectly, and the endpoint of the LR line will be on the input line.
These two moving averages frame the tradeoffs that we are facing. On one extreme we have ILRS, which is very smooth and has considerable phase lag. EPMA has 0 phase lag, but is too noisy and overshoots. We would like to construct a better moving average which is as smooth as ILRS, but runs closer to where EPMA lies, without the overshoot.
A easy way to attempt this is to split the difference, i.e. use (ILRS(n)+EPMA(n))/2. This will give us a moving average (call it IE /2) which runs in between the two, has phase lag of n/4 but still inherits considerable noise from EPMA. IE /2 is inspirational, however. Can we build something that is comparable, but smoother? Figure 1 shows ILRS, EPMA, and IE /2.
Filter Techniques
Any thoughtful student of filter theory (or resolute experimenter) will have noticed that you can improve the smoothness of a filter by running it through itself multiple times, at the cost of increasing phase lag.
There is a complementary technique (called twicing by J.W. Tukey) which can be used to improve phase lag. If L stands for the operation of running data through a low pass filter, then twicing can be described by:
L' = L(time series) + L(time series - L(time series))
That is, we add a moving average of the difference between the input and the moving average to the moving average. This is algebraically equivalent to:
2L-L(L)
This is the Double Exponential Moving Average or DEMA , popularized by Patrick Mulloy in TASAC (January/February 1994).
In our taxonomy, DEMA has some phase lag (although it exponentially approaches 0) and is somewhat noisy, comparable to IE /2 indicator.
We will use these two techniques to construct our better moving average, after we explore the first one a little more closely.
Fixing Overshoot
An n-day EMA has smoothing constant alpha=2/(n+1) and a lag of (n-1)/2.
Thus EMA (3) has lag 1, and EMA (11) has lag 5. Figure 2 shows that, if I am willing to incur 5 days of lag, I get a smoother moving average if I run EMA (3) through itself 5 times than if I just take EMA (11) once.
This suggests that if EPMA and DEMA have 0 or low lag, why not run fast versions (eg DEMA (3)) through themselves many times to achieve a smooth result? The problem is that multiple runs though these filters increase their tendency to overshoot the data, giving an unusable result. This is because the amplitude response of DEMA and EPMA is greater than 1 at certain frequencies, giving a gain of much greater than 1 at these frequencies when run though themselves multiple times. Figure 3 shows DEMA (7) and EPMA(7) run through themselves 3 times. DEMA^3 has serious overshoot, and EPMA^3 is terrible.
The solution to the overshoot problem is to recall what we are doing with twicing:
DEMA (n) = EMA (n) + EMA (time series - EMA (n))
The second term is adding, in effect, a smooth version of the derivative to the EMA to achieve DEMA . The derivative term determines how hot the moving average's response to linear trends will be. We need to simply turn down the volume to achieve our basic building block:
EMA (n) + EMA (time series - EMA (n))*.7;
This is algebraically the same as:
EMA (n)*1.7-EMA( EMA (n))*.7;
I have chosen .7 as my volume factor, but the general formula (which I call "Generalized Dema") is:
GD (n,v) = EMA (n)*(1+v)-EMA( EMA (n))*v,
Where v ranges between 0 and 1. When v=0, GD is just an EMA , and when v=1, GD is DEMA . In between, GD is a cooler DEMA . By using a value for v less than 1 (I like .7), we cure the multiple DEMA overshoot problem, at the cost of accepting some additional phase delay. Now we can run GD through itself multiple times to define a new, smoother moving average T3 that does not overshoot the data:
T3(n) = GD ( GD ( GD (n)))
In filter theory parlance, T3 is a six-pole non-linear Kalman filter. Kalman filters are ones which use the error (in this case (time series - EMA (n)) to correct themselves. In Technical Analysis , these are called Adaptive Moving Averages; they track the time series more aggressively when it is making large moves.
Included
Signals
Alerts
Related indicators
Zero-line Volatility Quality Index (VQI)
Volatility Quality Index w/ Pips Filtering
Variety Moving Average Waddah Attar Explosion (WAE)
***This indicator is tuned to Forex. If you want to make it useful for other tickers, you must change the pip filtering value to match the asset. This means that for BTC, for example, you likely need to use a value of 10,000 or more for pips filter.
Modified Covariance Autoregressive Estimator of Price [Loxx]What is the Modified Covariance AR Estimator?
The Modified Covariance AR Estimator uses the modified covariance method to fit an autoregressive (AR) model to the input data. This method minimizes the forward and backward prediction errors in the least squares sense. The input is a frame of consecutive time samples, which is assumed to be the output of an AR system driven by white noise. The block computes the normalized estimate of the AR system parameters, A(z), independently for each successive input.
Characteristics of Modified Covariance AR Estimator
Minimizes the forward prediction error in the least squares sense
Minimizes the forward and backward prediction errors in the least squares sense
High resolution for short data records
Able to extract frequencies from data consisting of p or more pure sinusoids
Does not suffer spectral line-splitting
May produce unstable models
Peak locations slightly dependent on initial phase
Minor frequency bias for estimates of sinusoids in noise
Order must be less than or equal to 2/3 the input frame size
Purpose
This indicator calculates a prediction of price. This will NOT work on all tickers. To see whether this works on a ticker for the settings you have chosen, you must check the label message on the lower right of the chart. The label will show either a pass or fail. If it passes, then it's green, if it fails, it's red. The reason for this is because the Modified Covariance method produce unstable models
H(z)= G / A(z) = G / (1+. a(2)z −1 +…+a(p+1)z)
You specify the order, "ip", of the all-pole model in the Estimation order parameter. To guarantee a valid output, you must set the Estimation order parameter to be less than or equal to two thirds the input vector length.
The output port labeled "a" outputs the normalized estimate of the AR model coefficients in descending powers of z.
The implementation of the Modified Covariance AR Estimator in this indicator is the fast algorithm for the solution of the modified covariance least squares normal equations.
Inputs
x - Array of complex data samples X(1) through X(N)
ip - Order of linear prediction model (integer)
Notable local variables
v - Real linear prediction variance at order IP
Outputs
a - Array of complex linear prediction coefficients
stop - value at time of exit, with error message
false - for normal exit (no numerical ill-conditioning)
true - if v is not a positive value
true - if delta and gamma do not lie in the range 0 to 1
true - if v is not a positive value
true - if delta and gamma do not lie in the range 0 to 1
errormessage - an error message based on "stop" parameter; this message will be displayed in the lower righthand corner of the chart. If you see a green "passed" then the analysis is valid, otherwise the test failed.
Indicator inputs
LastBar = bars backward from current bar to test estimate reliability
PastBars = how many bars are we going to analyze
LPOrder = Order of Linear Prediction, and for Modified Covariance AR method, this must be less than or equal to 2/3 the input frame size, so this number has a max value of 0.67
FutBars = how many bars you'd like to show in the future. This algorithm will either accept or reject your value input here and then project forward
Further reading
Spectrum Analysis-A Modern Perspective 1380 PROCEEDINGS OF THE IEEE, VOL. 69, NO. 11, NOVEMBER 1981
Related indicators
Levinson-Durbin Autocorrelation Extrapolation of Price
Weighted Burg AR Spectral Estimate Extrapolation of Price
Helme-Nikias Weighted Burg AR-SE Extra. of Price
Itakura-Saito Autoregressive Extrapolation of Price
Modified Covariance Autoregressive Estimator of Price
intraday_bondsStatistics for assisting with intraday bond trading, using five minute periods and one hour ranges. There are two tables, a volatility table and a correlation table. The correlation table shows the correlation of five minute returns (absolute) between the four different bond contracts that trade on the CME. The volatility table shows for each contract:
- The current realized volatility, based on the previous one hour of realized volatility. This figure is annualized for easy comparison with options contracts.
- The current realized volatility's z-score, based on all available data.
- The tick range of an "N" standard deviation move over one hour. Choose "N" using the stdevs input.
- The previous hour's true range (high - low).
The ranges are expressed in ticks.
Intrabar OBV/PVTI got this idea from @fikira's script Intrabar-Price-Volume-Change-experimental
The indicator calculates OBV and PVT based on ticks. Since, the indicator relies on live ticks, it only starts execution after it is put on the charts. The script can be useful in analysing intraday buy and sell pressure. Details are color coded based on the values.
Data is presented in simple tabular format.
Formula for OBV and PVT can be found here:
www.investopedia.com
www.investopedia.com
Volume Prism RibbonNASDAQ:SPWR
The purpose of this script is to give insight into the volume action. The relative volume is calculated (based on 400 ticks) with the volume of down days (close-close <0) being given a negative value. This function is then summed over 100 ticks. WMA's are used to generate a rainbow ribbon who's color order is easily recognized buy all of us. Watch and Warning points are added using crossover points. I find it to be a good supplement to my favorite Buy/Sell indicator. In addition to the wrapping of the ribbon, pay attention to where the zero line is as well.
Technical Analysis Consulting Table (TACT)Inspired by Tradingview's own "Technical Analysis Summary", I present to you a table with analogous logic.
You can track any ticker you want, no matter your chart. You can even have multiple tables to track multiple tickers. By default it tracks the Total Crypto Cap.
You can change the resolution you want to track. By default it is the same as the chart.
You can position the table to whichever corner of the chart you want. By default it draws in the bottom right corner.
Background colors and text size can be adjusted.
Indicators Used:
Oscillators
RSI(14)
STOCH(14, 3, 3)
CCI(20)
ADX(14)
AO
Momentum(10)
MACD(12, 26)
STOCH RSI(3, 3, 14, 14)
%R(14)
Bull Bear Power
UO(7,14,28)
Moving Averages
EMA(5)
SMA(5)
EMA(10)
SMA(10)
EMA(20)
SMA(20)
EMA(30)
SMA(30)
EMA(50)
SMA(50)
EMA(100)
SMA(100)
EMA(200)
SMA(200)
Ichimoku Cloud(9, 26, 52, 26)
VMWA(20)
HMA(9)
Pivots
Traditional
Fibonacci
Camarilla
Woodie
WARNING: I have observed up to a couple of seconds of signal jitter/delay, so use it with caution in very small resolutions (1s to 1m).
I hope you enjoy this and good luck with your trading. Suggestions and feedback are most welcome.
Bitcoin CME Gaps [NeoButane]Simple script that checks for gaps in price from CME. tickerid(x, y, sess) doesn't seem to be applying correctly for the ticker specified at the moment so there are a couple of 'gaps' peppered on lower timeframes.
Gaps are legitimate price levels to look as a support or resistance. The theory is that volume needs to be gap filled, but I currently believe it's an easy entry/exit trade for those who can move the market. I don't think there is sound analysis behind the why, but it is real.
QuantNomad - Simple Custom Screener in PineScriptQuite often I need to run screeners with the custom condition, but unfortunately, in TradingView it's impossible.
I created an example script to show how you can create a simple custom screener in Pine Script on your own.
It's not very good, it requires some manual adjustments, it can be improved in some ways, but I think it might work for some tasks.
What do you think? Do you have a better way to implement custom screeners in TradingView?
To run your own conditions you need to implement them in:
customFunc() function and for every ticker you want to include in your search add 2 lines like these with newly defined variable:
s1 = security('BTCUSD', '1', customFunc())
and
scr_label := s1 ? scr_label + 'BTCUSD\n' : scr_label
I'm not sure that it will work well for more than a few dozen tickers.
But I hope it will be helpful for you.
And remember:
Past performance does not guarantee future results.
ec tEST cODE FOR pERCENT DIFERENCE ////////////////////////////////////////////////////////////
// Copyright by HPotter v1.0 04/04/2015
// Percent difference between price and MA
////////////////////////////////////////////////////////////
study(title="Percent difference between price and MA")
source = close
useCurrentRes = input(true, title="Use Current Chart Resolution?")
resCustom = input(title="Use Different Timeframe? Uncheck Box Above", type=resolution, defval="60")
smd = input(true, title="Show MacD & Signal Line? Also Turn Off Dots Below")
sd = input(true, title="Show Dots When MacD Crosses Signal Line?")
sh = input(true, title="Show Histogram?")
macd_colorChange = input(true,title="Change MacD Line Color-Signal Line Cross?")
hist_colorChange = input(true,title="MacD Histogram 4 Colors?")
res = useCurrentRes ? period : resCustom
fastLength = input(12, minval=1), slowLength=input(26,minval=1)
signalLength=input(9,minval=1)
fastMA = ema(source, fastLength)
slowMA = ema(source, slowLength)
Length = input(9, minval=1)
Length2= input(36,minval=1)
Length3= input(81,minval=1)
AveragePrice= input(9,minval=1)
Length5= input(3,minval=1)
xSMA = (sma(close, Length)+sma(close, Length2)+sma(close, Length3))/3
pSAM=sma(close, AveragePrice)
nRes = (pSAM - xSMA) * 100 / close
signalnRes = sma(nRes, signalLength)
macd = nRes
signal = sma(macd, signalLength)
hist = macd - signal
outMacD = security(tickerid, res, macd)
outSignal = security(tickerid, res, signal)
outHist = security(tickerid, res, hist)
histA_IsUp = outHist > outHist and outHist > 0
histA_IsDown = outHist < outHist and outHist > 0
histB_IsDown = outHist < outHist and outHist <= 0
histB_IsUp = outHist > outHist and outHist <= 0
//MacD Color Definitions
macd_IsAbove = outMacD >= outSignal
macd_IsBelow = outMacD < outSignal
plot_color = hist_colorChange ? histA_IsUp ? aqua : histA_IsDown ? blue : histB_IsDown ? red : histB_IsUp ? maroon :yellow :gray
macd_color = macd_colorChange ? macd_IsAbove ? lime : red : red
signal_color = macd_colorChange ? macd_IsAbove ? yellow : yellow : lime
circleYPosition = outSignal
// MA COLOR DEFINITION
maColor = change(nRes)>0 ? green : change(nRes)<0 ? red : na
mA_IsAbove = nRes> 0
mA_IsBelow = nRes< 0
plot( nRes, color=maColor, style=line, title="MMA", linewidth=2)
//plot(smd and signalnRes ? signalnRes : na, title="Signal Line", color=signal_color, style=line ,linewidth=2)
//plot(smd and outMacD ? outMacD : na, title="MACD", color=macd_color, linewidth=4)
//plot(smd and outSignal ? outSignal : na, title="Signal Line", color=signal_color, style=line ,linewidth=2)
//plot(sh and outHist ? outHist : na, title="Histogram", color=plot_color, style=histogram, linewidth=4)
plot(sd and cross(outMacD, outSignal) ? circleYPosition : na, title="Cross", style=circles, linewidth=4, color=macd_color)
hline(0, '0 Line', linestyle=solid, linewidth=2, color=white)
//////ALERT cONDITION////
src = input(close)
ma_1 = sma(src, 20)
ma_2 = sma(src, 10)
c = cross(ma_1, ma_2)
alertcondition(c, title='Red crosses blue', message='Red and blue have crossed!')
d = cross(outMacD, outSignal)
alertcondition(d, title='GOING DOWN', message='SELL!')
//
//e = cross(outSignal, outMacD)
//alertcondition(E, title='GOING UP', message='BUY!')
BTC World Price: Multi-Exchange VWAPBTC World Price: Multi-Exchange VWAP
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WHAT IT DOES
What you see above are not Bitmex candles, but this indicator's.
Bitcoin is listed on multiple exchanges. Many people have called for a single global index that would quote BTC price and volume across all exchanges: this script is such a virtual aggregate (formerly: Multi-Listed , Volume-Weighted Average Price ).
It will, independently for each tick, for any time-frame:
- Quote the price (O, H, L, C) and volume from Bitfinex (USD), Binance (USDT), bitFlyer (Yen), Bithumb (S. Korean Won), Coinbase (USD), Kraken (EUR) and even Bitmex (USD Contracts).
- Weight each price with the corresponding volume of the exchange.
- Quote the FOREX conversion rate in USD for each currency (USDJPY etc.)
- Finally return global average price (candles) in USD.
- Additionally provide (H+L)/2 etc. values.
No more "on Coinbase this" or "on Bitstamp that", you've now got a global overview!
See CoinMarketCap: Markets for reference. I've included alternative exchanges in the comments at the top of the script.
__________________________
HOW TO USE IT
Basically just add it to your chart and use the indicator's candles instead of the chart's main ticker.
By default, BTC World Price will display candles only, but you can also display OHLC & averages (in whichever style you want).
You may indeed want to hide the main symbol (top-left corner, click the 'eye' button next to its name), or switch it to something else than candles/bars (e.g. line).
Make sure "Scale Price Chart Only" is disabled if you want to use the auto-zoom feature. (if other indicators are messing your zoom, you can try to select "Line with Breaks" or "Area with Breaks" to allow these to overflow from the main window)
By clicking the triangle next to the indicator's name, you can select "Visual Order" (e.g "Bring to Front").
You can select regular Candles or Heikin-Ashi in Options.
In the Format > Inputs tab, you can select which exchanges to quote. By default, all of them are enabled.
The script also exposes the following typical values to the backend, which you can use as Price Source for other indicators: (e.g. MA, RSI, in their "Format > Input" tab)
Open Price (grey)
High Price (green)
Low Price (red)
Close Price (white)
(H + L)/2 (light blue)
(H + L + C)/3 (blue)
(O + H + L + C)/4 (purple)
They are all hidden by default (by means of maximum transparency).
In the Format > Style tab, you can change their color, transparency and style (line, area, etc), as well as uncheck Candles and Wicks to hide these.
If you are using "Indicator Last Value" and want to clear the clutter from all these values, simply uncheck them in Style. They will still be available as Price Source for other indicators.
You can also choose to scale it to the left, right (default) or "screen" (no scaling).
Once you're satisfied with your Style, you may click "Default"> "Save as default" in the botton-left. Everytime you load the indicator, it will look the same. ("Reset Settings" will reset to the script's defaults)
__________________________
Please leave feedback below in comments or pm me directly for bugs and suggestions.
SMART4TRADER-Margin ZONEIndicator based on marginal zones (according to Mityukov Sergey). In open source.
Formula for calculating the margin:
Margin size / cost tick * minimum price change
Example:
EURUSD = 2100 $ / 6.25 $ * 0.00005 points = 0.01680 points
....
For currency pairs where USD is in the first place it is necessary to write so that the indicator is taken away from zero
Iff (ticker == "USDCAD", (0- (950/5 * 0.00005)),
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Индикатор на основе маржинальных зон (по Митюкову Сергею). В открытом исходном коде.
Формула рассчета маржи:
размер маржи / стоимость тика * минимальное ценовое изменение
Пример:
EURUSD = 2100 $ / 6.25 $ * 0.00005 points = 0.01680 points
....
Для валютных пар где USD стоит на первом месте нужно писать так, чтобы показатель отнимался от нуля
iff (ticker=="USDCAD", (0-(950/5*0.00005)),
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Convert Yuan value symbols to USDIGNORE PREVIOUS SCRIPT/POST (titled: "yuan normiz")
If you like to look add symbols that are valued in China's Yuan and want to convert them to USD accurately then this is the perfect script for you.
"I'm not sure if this script is for me. Does my setup apply here?"
If either of these resemble your chart setup then this is for you:
Example 1: You have COINBASE:BTCUSD on your main chart often add to compare Bitstamp:btcusd and Okcoin:btccny.
Example 2: You have SPY or SPX (or DJIA etc) as your main chart but like to add other composites to compare like SSE(Shanghai Stock Exchange index) to your main chart.
This takes the symbol of your choice (default is BTCCHINA:BTCCNY) that is expressed in Yuan and divides it by the corresponding value of IDC's USDCNH ticker. Not the last value of USDCNH, but the respective tick mark----BTCCNY's close 3 months ago is divided by USDCNH's close 3 months ago.
FlowSpike ES — BB • RSI • VWAP + AVWAP + News MuteThis indicator is purpose-built for E-mini S&P 500 (ES) futures traders, combining volatility bands, momentum filters, and session-anchored levels into a streamlined tool for intraday execution.
Key Features:
• ES-Tuned Presets
Automatically optimized settings for scalping (1–2m), daytrading (5m), and swing trading (15–60m) timeframes.
• Bollinger Band & RSI Signals
Entry signals trigger only at statistically significant extremes, with RSI filters to reduce false moves.
• VWAP & Anchored VWAPs
Session VWAP plus anchored VWAPs (RTH open, weekly, monthly, and custom) provide high-confidence reference levels used by professional order-flow traders.
• Volatility Filter (ATR in ticks)
Ensures signals are only shown when the ES is moving enough to offer tradable edges.
• News-Time Mute
Suppresses signals around scheduled economic releases (customizable windows in ET), helping traders avoid whipsaw conditions.
• Clean Alerts
Long/short alerts are generated only when all conditions align, with optional bar-close confirmation.
Why It’s Tailored for ES Futures:
• Designed around ES tick size (0.25) and volatility structure.
• Session settings respect RTH hours (09:30–16:00 ET), the period where most liquidity and institutional flows concentrate.
• ATR thresholds and RSI bands are pre-tuned for ES market behavior, reducing the need for manual optimization.
⸻
This is not a generic indicator—it’s a futures-focused tool created to align with the way ES trades day after day. Whether you scalp the open, manage intraday swings, or align to weekly/monthly anchored flows, FlowSpike ES gives you a clear, rules-based signal framework.
US Net Liquidity + M2 / US Debt (FRED)US Net Liquidity + M2 / US Debt
🧩 What this chart shows
This indicator plots the ratio of US Net Liquidity + M2 Money Supply divided by Total Public Debt.
US Net Liquidity is defined here as the Federal Reserve Balance Sheet (WALCL) minus the Treasury General Account (TGA) and the Overnight Reverse Repo facility (ON RRP).
M2 Money Supply represents the broad pool of liquid money circulating in the economy.
US Debt uses the Federal Government’s total outstanding debt.
By combining net liquidity with M2, then dividing by total debt, this chart provides a structural view of how much monetary “fuel” is in the system relative to the size of the federal debt load.
🧮 Formula
Ratio
=
(
Fed Balance Sheet
−
(
TGA
+
ON RRP
)
)
+
M2
Total Public Debt
Ratio=
Total Public Debt
(Fed Balance Sheet−(TGA+ON RRP))+M2
An optional normalization feature scales the ratio to start at 100 on the first valid bar, making long-term trends easier to compare.
🔎 Why it matters
Liquidity vs. Debt Growth: The numerator (Net Liquidity + M2) captures the monetary resources available to markets, while the denominator (Debt) reflects the expanding obligation of the federal government.
Market Signal: Historically, shifts in net liquidity and money supply relative to debt have coincided with major turning points in risk assets like equities and Bitcoin.
Context: A rising ratio may suggest that liquidity conditions are improving relative to debt expansion, which can be supportive for risk assets. Conversely, a falling ratio may highlight tightening conditions or debt outpacing liquidity growth.
⚙️ How to use it
Overlay this chart against S&P 500, Bitcoin, or gold to analyze correlations with asset performance.
Watch for trend inflections—does the ratio bottom before equities rally, or peak before risk-off periods?
Use normalization for long historical comparisons, or raw values to see the absolute ratio.
📊 Data sources
This indicator pulls from FRED (Federal Reserve Economic Data) tickers available in TradingView:
WALCL: Fed balance sheet
RRPONTSYD: Overnight Reverse Repo
WTREGEN: Treasury General Account
M2SL: M2 money stock
GFDEBTN: Total federal public debt
⚠️ Notes
Some FRED series are updated weekly, others monthly—set your chart timeframe accordingly.
If any ticker is unavailable in your plan, replace it with the equivalent FRED symbol provided in TradingView.
This indicator is intended for macro analysis, not short-term trading signals.
