[SGM Ordinal Patterns]An ordinal pattern is a concept used in mathematics and time series analysis. It is a way of describing the relative order of values in a sequence. Rather than focusing on the exact values, we are interested in how they compare to each other.
An ordinal pattern will tell you how these values are positioned relative to each other.
We do not look at the exact values, but only their order.
Concrete Example
• 4 (position 1 in the original sequence) is in position 2 in the ordered sequence.
• 7 (position 2 in the original sequence) is in position 3 in the ordered sequence.
• 2 (position 3 in the original sequence) is in position 1 in the ordered sequence.
The ordinal pattern for this sequence is then (2,3,1)(2, 3, 1)(2,3,1).
Script Explanation
This script analyzes ordinal patterns based on the closing prices of the last three bars and calculates the future gains associated with each ordinal pattern.
The main elements of the script are:
1. ordinal_pattern Function:
o Determines the ordinal pattern based on three past closing values.
o Returns an index (from 0 to 5) corresponding to one of the six possible ordinal patterns.
2. Calculations and Storage:
o For each new bar, the last three closes are used to identify the ordinal pattern.
o Future gains are calculated and associated with the previous ordinal pattern.
o Return statistics (mean, standard deviation and Sharpe ratio) are calculated for each pattern.
3. Visualization:
o Draws lines connecting the last three closes.
o Tables displaying the number of occurrences, distributions, and return statistics for each ordinal pattern.
What the Script Shows:
• Table motifs_table : Number of occurrences and distribution of each ordinal pattern. An uneven distribution between patterns (different by one sixth for each pattern) can indicate market inefficiency.
• Table pattern_analysis : Analysis of returns (mean, standard deviation, Sharpe ratio) for each ordinal pattern.
• Table current_motif_table : Ordinal pattern of the last bar.
This script helps to understand and visualize how ordinal patterns influence future returns of financial asset prices. An uneven distribution of patterns can indicate market inefficiencies.
Cari skrip untuk " TABLE "
ICT New Day Opening GapNew Day Opening Gap
The New Day Opening Gap (NDOG) is defined by The Inner Circle Trader (ICT) as the separation in time/price that is caused by the 1-hour break that occurs each day in the futures market. The opening price of the gap is the very first tick that occurs at the 6:00pm restart; then we look at the 5:00pm closing price of the previous session. This New Day Opening Gap forms every day from Monday to Friday, but it does not include the gap between Friday's close and Sunday's open (because that is instead referred to as a New Week Opening Gap).
This is an example of a New Day Opening Gap (NDOG) for Wednesday, May 22, 2024 in CME_MINI:ES1!
How To Use NDOG
When an NDOG forms, it can be extended into future price action. One way to use these gaps is to look for it to be filled in by price action. Another usage for these gaps is to look for support & resistance to come in at the high and low of these NDOGs (as well as the midpoint).
Disclaimer
This indicator is mainly intended to work for Futures markets, and specifically the following Index Futures markets: E-mini S&P 500 Futures, E-mini NASDAQ-100 Futures, E-mini DOW Futures.
Given that, the indicator still supports various other markets/assets out-of-the-box, such as other types of Futures Markets, Forex markets, Stocks, Options, and more. The main difference will be that other markets may have NDOGs forming at different times, rather than the 5pm-6pm gap that occurs in the Index Futures.
Indicator Features
This indicator is 100% custom-built, not using code from any other existing NDOG plotting indicators. The purpose of this indicator was to overcome many shortcomings from other existing indicators. Therefore, this indicator has many UNIQUE features, such as:
Ability to maintain accuracy of the closing/opening prices even when changing chart settings (e.g., toggling ETH/RTH sessions, toggling BACK-ADJUSTMENT on futures contracts, toggling SETTLEMENT prices, etc.).
Draw up to 25 previous NDOGs, even on ultra-low timeframes like the 1-minute or 1-second chart.
Automatically or manually choose which NDOGs to hide/show on the chart.
Highly customizable, including a different color scheme to easily distinguish between the Current and Previous NDOGs.
Modified price values to correctly display prices that use a format like 109'32 (e.g., Bond Futures or Wheat Futures).
Helpful tooltips to provide more detailed information about the NDOGs or about the current Input Settings.
Error Messages
There are some conditions which can cause the script to fail and display an error message (by clicking the red exclamation mark next to the indicator.)
Error messages:
Use a Standard Chart Type : this will occur when using a non-standard chart such as Heikin Ashi, Renko, Point & Figure, etc.
Use a Daily or Lower Timeframe : this error will appear when using a higher timeframe chart like weekly or monthly, because it can clutter the chart since NDOGs can form every day.
NDOG was not detected : this means that no NDOG was found, for example if the chart did not have enough bars/candles (e.g., some Options markets).
Exceeded the maximum lookback for Bar Replay mode : when using bar replay mode; this can depend on the amount of historical bars available in different account subscription types.
Unable to Activate Bar Replay mode : if the indicator could not be used in Bar Replay mode.
Restart Bar Replay : if the indicator works in Bar Replay but it detected an error that would cause NDOGs to be plotted incorrectly.
NDOG was not detected. Toggle "Error Handling" Option at your own discretion : this is more of a warning message that will appear when the indicator does not detect any actual gap between the days (e.g., Forex markets where it is continuously traded through each day, without any gap forming in between). But the warning can be dismissed by toggling the checkbox at the bottom of the Indicator's Input Settings.
This is an example of what a script error would look like.
Indicator Settings
Most settings are self-explanatory or have a tooltip with information on what the setting does, so this section will only briefly cover the available settings.
The "Extend to End of Week" option is enabled by default, which will extend each NDOG only up to the end of the week that it belongs to. This option can be toggled OFF to automatically extend all NDOGs to the right-most candle on the chart.
Previous NDOGs: Between 1 and 25 previous NDOGs can be displayed. The checkbox can be toggled to quickly hide all previous NDOGs (but the same effect would be reached by setting the value to 0).
Hide Current NDOG: the current NDOG (colored in Green in the example above), can be optionally hidden from being plotted.
These settings are used to customize the visual style of the most recent NDOG (also known as the "Current" NDOG). Note: the exact same set of settings are available for the Previous NDOGs. The text next to each NDOG can be optionally hidden to clean the chart a little.
These are settings to customize the appearance of the Price Table on the right, including the ability to hide it completely.
One of 7 available overlap handling options can be used to filter which NDOGs are plotted on the chart. By default, the "None" option will be selected, meaning that all valid NDOGs are plotted on the chart.
Date Format : select the format of the date that is shown next to each NDOG.
Timezone : choose the timezone for the NDOG closing/opening date-times that are displayed (only in tooltips when you hover over an NDOG label).
NDOG Label : choose the details to display next to each NDOG (e.g., date, or NDOG number, or both).
Price Format : only two options: Auto/Decimal. "Auto" uses custom processing to allow displaying values such as 109'32 for Bond futures.
This option can be toggled to allow displaying NDOGs for markets that may not have an actual gap between days, such as Forex markets, or BTC/USD (which is traded 24/7). Note: this option must be used at your own discretion because the opening/closing times for the NDOGs are not guaranteed to be accurate.
Tooltips
The indicator provides additional details about an NDOG when you hover over a row in the Price Table.
Note: the same information can be found by hovering over the Text Label that is to the right of each NDOG.
Overlap Handling
The tooltip next to "Select a Strategy" in the options will provide details on each overlap handling strategy. Additionally, when a strategy is selected, a new row in the Price Table will appear; hovering over that will show details about the currently selected strategy, as well as any suggestions in case the inputs were invalid. When a strategy hides an NDOG, the number in the Price Table will be replaced with an "Eye" icon, indicating that it is not currently plotted on the chart.
Available strategies are:
Option 1 (Gradients) : select the percentage opacity to shade NDOGs in. The more recent NDOGs will be closer to the maximum opacity defined, while the older NDOGs will appear more transparent, closer to the minimum opacity defined. Note: only affects previous NDOGs, not the current NDOG.
Option 2 (Week Extension) : select the number of weeks to extend each NDOG up to. Note: this will override the "Extend to End of Week" setting, regardless whether it is toggled ON or OFF.
Option 3 (Nested Gaps) : hides nested gaps, i.e., NDOGs that are enclosed within another NDOG. Note: this option is only available when the "Extend to End of Week" setting is disabled .
Option 4 (Intersecting Gaps) : hides intersecting/overlapping gaps, i.e., NDOGs that overlap one another (this may also include, but is not limited to, nested gaps). The drop-down next to this option allows choosing the priority of which NDOGs to hide first. Note: this option is only available when the "Extend to End of Week" setting is disabled .
Option 5 (Gap Width) : the chart will only show NDOGs that have a width between the defined parameters. This can be useful to filter out NDOGs that are deemed "insignificant". For example, the Inner Circle Trader will generally filter out of his analysis any NDOGs that are less than a point (4 ticks) for Index futures.
Option 6 (Close Proximity) : the chart will only show the NDOGs that are within a certain range from the market price. This can be useful when plotting multiple NDOGs while using auto-scaling on the chart. By only showing nearby NDOGs, it will prevent the auto-scaling from having to compress the candles to fit the far-away NDOGs onto the screen.
Option 7 (CSV) : this option is used if none of the others suit you well; it allows specifically choosing which NDOGs to hide or show on the chart.
This is an example that chooses the Overlap Handling Strategy Option 6. Note that in this example, the tooltip in the price table shows a warning that the Input Number should be increased to plot some NDOGs on the chart.
Tips
Chart settings can be toggled to "Scale price chart only" to prevent the auto-scaling of TradingView from compressing the chart if there are NDOGs that are far away from the current market action.
If you change a lot of indicator settings such as NDOG color schemes, you can save the settings as the Default to prevent your settings from resetting the next time you use the indicator.
Multi Asset Histogram [ChartPrime]Multi Asset Histogram Indicator
Overview:
The "Multi Asset Histogram" indicator provides a comprehensive visualization of the performance of multiple assets relative to each other. By calculating a score for each asset and displaying it in a histogram format, this indicator helps traders quickly identify the trends, dominant asset and the average performance of the assets in the selected group.
Key Features:
◆ Multi-Asset Score Calculation:
The indicator calculates a trend score for each selected asset based on the price source (e.g., hl2).
The trend score is determined by comparing the current price to the prices over the past bars back defined by user, adding or subtracting points based on whether the current price is higher or lower than previous prices.
// Score Function
trscore(src) =>
total = 0.0
for i = 1 to 50
total += (src >= nz(src ) ? 1 : -1)
total
◆ Flexible Symbol Input:
Traders can input up to 10 different symbols (e.g., BTCUSD, ETHUSD, etc.) to be included in the histogram analysis.
◆ Dynamic Visualization:
A histogram is plotted for each asset, with bars colored based on the score, providing a clear visual representation of the relative performance.
Color gradients from red to aqua indicate the performance, with red representing negative scores and aqua representing positive scores.
◆ Adaptive Histogram Lines:
The width and placement of histogram lines adapt based on the calculated scores, ensuring clear visualization regardless of the values.
Dashed lines represent the mean score of all assets, helping traders identify the overall market trend.
◆Detailed Labels and Values:
Labels are placed on the histogram to display the exact score for each asset.
Mean value and zero line labels provide additional context for the overall performance.
◆ Visual Scaling Lines:
Zero line and mean line are clearly marked, helping traders understand the distribution and scale of scores.
Scales on the left and right of the histogram indicate the performance range.
◆ Informative Table:
A table is displayed on the chart, showing the dominant asset (the one with the highest score) and the mean score of all assets.
The table updates dynamically to reflect real-time changes in asset performance.
◆ Settings:
Length: The value of number bars back is greater or less than the current value of the source
Source: The price source to be used for score calculation (e.g., hl2).
Symbols: Up to 10 different asset symbols can be input for analysis.
Usage Notes:
This indicator is useful for traders who monitor multiple assets simultaneously and need a quick visual reference to identify the strongest and weakest performers.
The color coding and dynamic labels make it easy to interpret the relative performance and make informed trading decisions.
This indicator is designed to enhance multi-asset analysis by providing a clear, visual representation of each asset's performance relative to the others, making it easier to identify trends and dominant assets in the market.
MetaFOX DCA (ASAP-RSI-BB%B-TV)Welcome To ' MetaFOX DCA (ASAP-RSI-BB%B-TV) ' Indicator.
This is not a Buy/Sell signals indicator, this is an indicator to help you create your own strategy using a variety of technical analyzing options within the indicator settings with the ability to do DCA (Dollar Cost Average) with up to 100 safety orders.
It is important when backtesting to get a real results, but this is impossible, especially when the time frame is large, because we don't know the real price action inside each candle, as we don't know whether the price reached the high or low first. but what I can say is that I present to you a backtest results in the worst possible case, meaning that if the same chart is repeated during the next period and you traded for the same period and with the same settings, the real results will be either identical to the results in the indicator or better (not worst). There will be no other factors except the slippage in the price when executing orders in the real trading, So I created a feature for that to increase the accuracy rate of the results. For more information, read this description.
Below I will explain all the properties and settings of the indicator:
A) 'Buy Strategies' Section: Your choices of strategies to Start a new trade: (All the conditions works as (And) not (OR), You have to choose one at least and you can choose more than one).
- 'ASAP (New Candle)': Start a trade as soon as possible at the opening of a new candle after exiting the previous trade.
- 'RSI': Using RSI as a technical analysis condition to start a trade.
- 'BB %B': Using BB %B as a technical analysis condition to start a trade.
- 'TV': Using tradingview crypto screener as a technical analysis condition to start a trade.
B) 'Exit Strategies' Section: Your choices of strategies to Exit the trades: (All the conditions works as (And) not (OR), You can choose more than one, But if you don't want to use any of them you have to activate the 'Use TP:' at least).
- 'ASAP (New Candle)': Exit a trade as soon as possible at the opening of a new candle after opening the previous trade.
- 'RSI': Using RSI as a technical analysis condition to exit a trade.
- 'BB %B': Using BB %B as a technical analysis condition to exit a trade.
- 'TV': Using tradingview crypto screener as a technical analysis condition to exit a trade.
C) 'Main Settings' Section:
- 'Trading Fees %': The Exchange trading fees in percentage (trading Commission).
- 'Entry Price Slippage %': Since real trading differs from backtest calculations, while in backtest results are calculated based on the open price of the candle, but in real trading there is a slippage from the open price of the candle resulting from the supply and demand in the real time trading, so this feature is to determine the slippage Which you think it is appropriate, then the entry prices of the trades will calculated higher than the open price of the start candle by the percentage of slippage that you set. If you don't want to calculate any slippage, just set it to zero, but I don't recommend that if you want the most realistic results.
Note: If (open price + slippage) is higher than the high of the candle then don't worry, I've kept this in consideration.
- 'Use SL': Activate to use stop loss percentage.
- 'SL %': Stop loss percentage.
- 'SL settings options box':
'SL From Base Price': Calculate the SL from the base order price (from the trade first entry price).
'SL From Avg. Price': Calculate the SL from the average price in case you use safety orders.
'SL From Last SO.': Calculate the SL from the last (lowest) safety order deviation.
ex: If you choose 'SL From Avg. Price' and SL% is 5, then the SL will be lower than the average price by 5% (in this case your SL will be dynamic until the price reaches all the safety orders unlike the other two SL options).
Note: This indicator programmed to be compatible with '3COMMAS' platform, but I added more options that came to my mind.
'3COMMAS' DCA bots uses 'SL From Base Price'.
- 'Use TP': Activate to use take profit percentage.
- 'TP %': Take profit percentage.
- 'Pure TP,SL': This feature was created due to the differences in the method of calculations between API tools trading platforms:
If the feature is not activated and (for example) the TP is 5%, this means that the price must move upward by only 5%, but you will not achieve a net profit of 5% due to the trading fees. but If the feature is activated, this means that you will get a net profit of 5%, and this means that the price must move upward by (5% for the TP + the equivalent of trading fees). The same idea is applied to the SL.
Note: '3COMMAS' DCA bots uses activated 'Pure TP,SL'.
- 'SO. Price Deviation %': Determines the decline percentage for the first safety order from the trade start entry price.
- 'SO. Step Scale': Determines the deviation multiplier for the safety orders.
Note: I'm using the same method of calculations for SO. (safety orders) levels that '3COMMAS' platform is using. If there is any difference between the '3COMMAS' calculations and the platform that you are using, please let me know.
'3COMMAS' DCA bots minimum 'SO. Price Deviation %' is (0.21)
'3COMMAS' DCA bots minimum 'SO. Step Scale' is (0.1)
- 'SO. Volume Scale': Determines the base order size multiplier for the safety orders sizes.
ex: If you used 10$ to buy at the trade start (base order size) and your 'SO. Volume Scale' is 2, then the 1st SO. size will be 20, the 2nd SO. size will be 40 and so on.
- 'SO. Count': Determines the number of safety orders that you want. If you want to trade without safety orders set it to zero.
'3COMMAS' DCA bots minimum 'SO. Volume Scale' is (0.1)
- 'Exchange Min. Size': The exchange minimum size per trade, It's important to prevent you from setting the base order Size less than the exchange limit. It's also important for the backtest results calculations.
ex: If you setup your strategy settings and it led to a loss to the point that you can't trade any more due to insufficient funds and your base order size share from the strategy becomes less than the exchange minimum trade size, then the indicator will show you a warning and will show you the point where you stopped the trading (It works in compatible with the initial capital). I recommend to set it a little bit higher than the real exchange minimum trade size especially if you trade without safety orders to not stuck in the trade if you hit the stop loss
- 'BO. Size': The base order size (funds you use at the trade entry).
- 'Initial Capital': The total funds allocated for trading using your strategy settings, It can be more than what is required in the strategy to cover the deficit in case of a loss, but it should not exceed the funds that you actually have for trading using this strategy settings, It's important to prevent you from setting up a strategy which requires funds more than what you have. It's also has other important benefits (refer to 'Exchange Min. Size' for more information).
- 'Accumulative Results': This feature is also called re-invest profits & risk reduction. If it's not activated then you will use the same funds size in each new trade whether you are in profit or loss till the (initial capitals + net results) turns insufficient. If it's activated then you will reuse your profits and losses in each new trade.
ex: The feature is active and your first trade ended with a net profit of 1000$, the next trade will add the 1000$ to the trade funds size and it will be distributed as a percentage to the BO. & SO.s according to your strategy settings. The same idea in case of a loss, the trade funds size will be reduced.
D) 'RSI Strategy' Section:
- 'Buy': RSI technical condition to start a trade. Has no effect if you don't choose 'RSI' option in 'Buy Strategies'.
- 'Exit': RSI technical condition to exit a trade. Has no effect if you don't choose 'RSI' option in 'Exit Strategies'.
E) 'TV Strategy' Section:
- 'Buy': TradingView Crypto Screener technical condition to start a trade. Has no effect if you don't choose 'TV' option in 'Buy Strategies'.
- 'Exit': TradingView Crypto Screener technical condition to exit a trade. Has no effect if you don't choose 'TV' option in 'Exit Strategies'.
F) 'BB %B Strategy' Section:
- 'Buy': BB %B technical condition to start a trade. Has no effect if you don't choose 'BB %B' option in 'Buy Strategies'.
- 'Exit': BB %B technical condition to exit a trade. Has no effect if you don't choose 'BB %B' option in 'Exit Strategies'.
G) 'Plot' Section:
- 'Signals': Plots buy and exit signals.
- 'BO': Plots the trade entry price (base order price).
- 'AVG': Plots the trade average price.
- 'AVG options box': Your choice to plot the trade average price type:
'Avg. With Fees': The trade average price including the trading fees, If you exit the trade at this price the trade net profit will be 0.00
'Avg. Without Fees': The trade average price but not including the trading fees, If you exit the trade at this price the trade net profit will be a loss equivalent to the trading fees.
- 'TP': Plots the trade take profit price.
- 'SL': Plots the trade stop loss price.
- 'Last SO': Plots the trade last safety order that the price reached.
- 'Exit Price': Plots a mark on the trade exit price, It plots in 3 colors as below:
Red (Default): Trade exit at a loss.
Green (Default): Trade exit at a profit.
Yellow (Default): Trade exit at a profit but this is a special case where we have to calculate the profits before reaching the safety orders (if any) on that candle (compatible with the idea of getting strategy results at the worst case).
- 'Result Table': Plots your strategy result table. The net profit percentage shown is a percentage of the 'initial capital'.
- 'TA Values': Plots your used strategies Technical analysis values. (Green cells means valid condition).
- 'Help Table': Plots a table to help you discover 100 safety orders with its deviations and the total funds needed for your strategy settings. Deviations shown in red is impossible to use because its price is <= 0.00
- 'Portfolio Chart': Plots your Portfolio status during the entire trading period in addition to the highest and lowest level reached. It's important when evaluating any strategy not only to look at the final result, but also to look at the change in results over the entire trading period. Perhaps the results were worryingly negative at some point before they rose again and made a profit. This feature helps you to see the whole picture.
- 'Welcome Message': Plots a welcome message and showing you the idea behind this indicator.
- 'Green Net Profit %': It plots the 'Net Profit %' in the result table in green color if the result is equal to or above the value that you entered.
- 'Green Win Rate %': It plots the 'Win Rate %' in the result table in green color if the result is equal to or above the value that you entered.
- 'User Notes Area': An empty text area, Feel free to use this area to write your notes so you don't forget them.
The indicator will take care of you. In some cases, warning messages will appear for you. Read them carefully, as they mean that you have done an illogical error in the indicator settings. Also, the indicator will sometimes stop working for the same reason mentioned above. If that happens then click on the red (!) next to the indicator name and read the message to find out what illogical error you have done.
Please enjoy the indicator and let me know your thoughts in the comments below.
Market Cap / Revenue RatioA variation of the P/S ratio, this script takes the future estimated revenue of the current stock versus it's Market Cap. It then compares the aforementioned Market Cap:Revenue ratio against a market bellwether's corresponding ratio (MSFT by default) to determine the following:
- Light green when the ratio is extremely low (Stock is very undervalued)
- Green when the ratio is low (Stock's multiple is lower by 20-50%)
- Blue when the ratio is close to the benchmark (Stock is fairly valued to benchmark multiple)
- Red when the ratio is high (Stock's mulitple is higher by 50% or more)
- Dark red when the ratio is extremely high (Stock is very overvalued)
CONFIGURABLE
- Full Table: Show the entire calculation table
- Minimalist: Go minimal and show only the ratio and color code
- Show Benchmark Multiple: Show the multiple ratio calculated between the current stock and the benchmark stock (MSFT by default)
NOTES
- When calculating the Market Cap, TradingView sometimes under-reports the number of shares and thus skews the Market Cap too low. This seems to happen for stocks with multiple share classes like GOOGL so be mindful that the data can be wrong for these kinds of stocks. You can check on this by going into the Indicator's Settings and select Show Full Table which will show the number of shares outstanding reported by TradingView.
- For certain stocks such as foreign ADRs, there won't be a future revenue estimate so the script will automatically use the Total Revenue for the most recent Quarter in these cases
Divergence Detector [TradingFinder] RSI + MACD + AO Oscillator 🔵 Introduction
🟣 Understanding Divergence
As mentioned, divergence occurs in technical analysis when a stock's price behaves contrary to indicators on the price chart. Divergence can signify either a reversal of the stock's trend or a continuation of the previous trend correction.
Divergences can act as reversal patterns or continuation patterns. Moreover, divergences can be utilized to identify potential support and resistance levels.
For instance, when an indicator is trending upwards and positive, but the price is declining and trending downwards, divergence occurs. Divergence in a stock indicates trader indecision in buying and selling and warns traders to reconsider their decisions regarding buying or holding the stock.
Divergence aids analysts in identifying critical price points. In indicator divergences, it serves as a potent signal in the realm of technical analysis.
🟣 Types of Divergence
1.Regular Divergence
o Positive Regular Divergence (RD+)
o Negative Regular Divergence (RD-)
2.Hidden Divergence
o Positive Hidden Divergence (HD+)
o Negative Hidden Divergence (HD-)
3.Time Divergence
Key Note : This indicator is specifically designed to identify "Regular Divergence" only. Therefore, the following explanation pertains to this type of divergence.
🔵 Regular Divergence/Convergence
Regular Divergence(Convergence) occurs due to conflicting behavior between the indicator and the price chart, typically at the end of a trend. Recognizing Regular Divergence suggests an anticipation of a trend reversal or a pattern resembling a reversal.
🟣 Positive Regular Divergence (RD+)
In contrast to negative divergence, positive Regular Divergence occurs at the end of a downtrend and between two price lows. It manifests when the price forms a new low on the price chart, but the indicator fails to recognize it.
Positive Regular Divergence indicates strong buying pressure and weak selling pressure. Following the identification of positive divergence on the chart, one can anticipate a price increase for the examined stock.
🟣 Negative Regular Divergence (RD-)
This type of Regular Divergence emerges between two price highs during an uptrend. A new high is formed on the price chart, but the indicator fails to acknowledge it. This scenario indicates negative Regular Divergence.
The likelihood of a subsequent market downturn is high. Negative divergence signifies strong selling pressure and weak buying pressure, suggesting an unfavorable future for the stock.
🔵 How to use
By utilizing the "Fractal Period" input, you can specify your desired periods for identifying divergences.
Additionally, through the "Divergence Detect Method" feature, you can choose which oscillators (MACD, RSI, or AO) to base divergence identification on.
Divergence in MACD Oscillator :
Divergence in the MACD indicator occurs when the price chart and the MACD line form a noticeable opposing pattern, meaning the price moves contrary to the MACD line. In this scenario, one expects a reversal in price direction.
Divergence in RSI Oscillator :
If divergence occurs during a downtrend on the price chart (two consecutive lows, with the second low being lower) and on the corresponding RSI point (two consecutive lows, with the second low being higher), it signifies positive Regular Divergence and implies a buying signal.
Conversely, if divergence occurs during an uptrend on the price chart (two consecutive highs, with the second high being higher) and on the corresponding RSI point (two consecutive highs, with the second high being lower), it indicates negative Regular Divergence, signaling a selling opportunity.
Divergence in AO Oscillator :
The AO indicator calculates histograms similar to the AO base. It calculates the difference between the simple moving averages of 5 and 34 periods based on the median of each bar. Then, it plots the bars based on the difference.
It then compares the histograms to detect peaks and troughs in the AO histograms and compares the identified peaks and troughs to the price. Whenever divergence is detected, it plots lines and arrows.
🔵 Table
The table contains information on the functional features of this oscillator that you can utilize. Four categories of information are presented in the table: "Exist," "Consecutive," "Divergence Quality," and "Change Phase Indicator."
Exist :
If divergence exists, you'll see "+" in this row.
Consecutive :
Divergences may occur consecutively. If same-type divergences form within short intervals, you can observe the count in this row.
Divergence Quality : Based on the number of consecutive divergences, their quality can be evaluated. If one divergence exists, its quality is considered "Normal." If two divergences exist, the quality is "Good," and if three or more divergences exist, the quality is considered "Strong."
Change Phase Indicator : If a phase change occurs between two oscillation peaks formed based on divergence, this change is identified and displayed in this row.
WTI Crude Oil Lot Size Calculator by AdrianFx94Indicator on Trading Chart: Once you add this script to your trading chart (specifically a WTI Crude Oil chart), it appears as an indicator. This means it runs alongside the price data and other technical analysis tools you might be using.
Input Your Trading Parameters:
Balance (USD): You need to enter your trading account balance in USD. This is the amount of money you have in your account.
Risk Percentage (%): This is where you define the percentage of your account balance that you're willing to risk in a single trade. For example, if your account balance is $5000 and you set the risk percentage to 1%, you're willing to risk $50 on a trade.
Stop Loss Pip Size (Pip): Here, you enter the size of your stop loss in pips. A pip is a small measure of change in a currency pair in the forex market. In the context of WTI Crude Oil trading, it represents a small change in the price.
Automated Lot Size Calculation: Based on the inputs you provide, the script automatically calculates the lot size you should use for your trade. The calculation takes into account the balance you're willing to risk, the percentage of risk, and the stop loss size. This helps in managing risk by suggesting the amount of WTI Crude Oil you should trade (in lots) that aligns with your risk tolerance.
Display Results in a Table: The script generates a table displayed on the top right corner of your chart. This table shows:
Your entered balance (in USD).
The risk percentage you've set.
The calculated lot size, which indicates how many lots of WTI Crude Oil you can trade based on your risk management parameters.
Real-Time Updates: As this script is part of an indicator on your chart, it updates in real time. This means if your account balance changes or if you decide to adjust your risk parameters, you can re-enter these values, and the script will update the lot size accordingly.
This tool is particularly useful for WTI Crude Oil traders who follow strict risk management rules. By automating the calculation of the lot size, it saves time and helps in making informed and disciplined trading decisions.
Day/Week/Month Metrics (Zeiierman)█ Overview
The Day/Week/Month Metrics (Zeiierman) indicator is a powerful tool for traders looking to incorporate historical performance into their trading strategy. It computes statistical metrics related to the performance of a trading instrument on different time scales: daily, weekly, and monthly. Breaking down the performance into daily, weekly, and monthly metrics provides a granular view of the instrument's behavior.
The indicator requires the chart to be set on a daily timeframe.
█ Key Statistics
⚪ Day in month
The performance of financial markets can show variability across different days within a month. This phenomenon, often referred to as the "monthly effect" or "turn-of-the-month effect," suggests that certain days of the month, especially the first and last days, tend to exhibit higher than average returns in many stock markets around the world. This effect is attributed to various factors including payroll contributions, investment of monthly dividends, and psychological factors among traders and investors.
⚪ Edge
The Edge calculation identifies days within a month that consistently outperform the average monthly trading performance. It provides a statistical advantage by quantifying how often trading on these specific days yields better returns than the overall monthly average. This insight helps traders understand not just when returns might be higher, but also how reliable these patterns are over time. By focusing on days with a higher "Edge," traders can potentially increase their chances of success by aligning their strategies with historically more profitable days.
⚪ Month
Historically, the stock market has exhibited seasonal trends, with certain months showing distinct patterns of performance. One of the most well-documented patterns is the "Sell in May and go away" phenomenon, suggesting that the period from November to April has historically brought significantly stronger gains in many major stock indices compared to the period from May to October. This pattern highlights the potential impact of seasonal investor sentiment and activities on market performance.
⚪ Day in week
Various studies have identified the "day-of-the-week effect," where certain days of the week, particularly Monday and Friday, show different average returns compared to other weekdays. Historically, Mondays have been associated with lower or negative average returns in many markets, a phenomenon often linked to the settlement of trades from the previous week and negative news accumulation over the weekend. Fridays, on the other hand, might exhibit positive bias as investors adjust positions ahead of the weekend.
⚪ Week in month
The performance of markets can also vary within different weeks of the month, with some studies suggesting a "week of the month effect." Typically, the first and the last week of the month may show stronger performance compared to the middle weeks. This pattern can be influenced by factors such as the timing of economic reports, monthly investment flows, and options and futures expiration dates which tend to cluster around these periods, affecting investor behavior and market liquidity.
█ How It Works
⚪ Day in Month
For each day of the month (1-31), the script calculates the average percentage change between the opening and closing prices of a trading instrument. This metric helps identify which days have historically been more volatile or profitable.
It uses arrays to store the sum of percentage changes for each day and the total occurrences of each day to calculate the average percentage change.
⚪ Month
The script calculates the overall gain for each month (January-December) by comparing the closing price at the start of a month to the closing price at the end, expressed as a percentage. This metric offers insights into which months might offer better trading opportunities based on historical performance.
Monthly gains are tracked using arrays that store the sum of these gains for each month and the count of occurrences to calculate the average monthly gain.
⚪ Day in Week
Similar to the day in the month analysis, the script evaluates the average percentage change between the opening and closing prices for each day of the week (Monday-Sunday). This information can be used to assess which days of the week are typically more favorable for trading.
The script uses arrays to accumulate percentage changes and occurrences for each weekday, allowing for the calculation of average changes per day of the week.
⚪ Week in Month
The script assesses the performance of each week within a month, identifying the gain from the start to the end of each week, expressed as a percentage. This can help traders understand which weeks within a month may have historically presented better trading conditions.
It employs arrays to track the weekly gains and the number of weeks, using a counter to identify which week of the month it is (1-4), allowing for the calculation of average weekly gains.
█ How to Use
Traders can use this indicator to identify patterns or trends in the instrument's performance. For example, if a particular day of the week consistently shows a higher percentage of bullish closes, a trader might consider this in their strategy. Similarly, if certain months show stronger performance historically, this information could influence trading decisions.
Identifying High-Performance Days and Periods
Day in Month & Day in Week Analysis: By examining the average percentage change for each day of the month and week, traders can identify specific days that historically have shown higher volatility or profitability. This allows for targeted trading strategies, focusing on these high-performance days to maximize potential gains.
Month Analysis: Understanding which months have historically provided better returns enables traders to adjust their trading intensity or capital allocation in anticipation of seasonally stronger or weaker periods.
Week in Month Analysis: Identifying which weeks within a month have historically been more profitable can help traders plan their trades around these periods, potentially increasing their chances of success.
█ Settings
Enable or disable the types of statistics you want to display in the table.
Table Size: Users can select the size of the table displayed on the chart, ranging from "Tiny" to "Auto," which adjusts based on screen size.
Table Position: Users can choose the location of the table on the chart
-----------------
Disclaimer
The information contained in my Scripts/Indicators/Ideas/Algos/Systems does not constitute financial advice or a solicitation to buy or sell any securities of any type. I will not accept liability for any loss or damage, including without limitation any loss of profit, which may arise directly or indirectly from the use of or reliance on such information.
All investments involve risk, and the past performance of a security, industry, sector, market, financial product, trading strategy, backtest, or individual's trading does not guarantee future results or returns. Investors are fully responsible for any investment decisions they make. Such decisions should be based solely on an evaluation of their financial circumstances, investment objectives, risk tolerance, and liquidity needs.
My Scripts/Indicators/Ideas/Algos/Systems are only for educational purposes!
MACD_TRIGGER_CROSS_TRIANGLEMACD Triangle Trigger Indicator by thebearfib
Overview
The MACD Cross Triangle Indicator is a powerful tool for traders who rely on the MACD's signal line crossovers to make informed trading decisions. This indicator enhances the traditional MACD by allowing users to customize triggers for bullish and bearish signals and by displaying these signals directly on the chart with visually distinctive labels.
Features
Customizable Color Scheme: Choose distinct colors for bullish and bearish signals to fit your chart's theme or your personal preference.
Flexible Trigger Conditions: Select from a variety of trigger conditions based on MACD and signal line behaviors over a specified number of bars back.
Visual Signal Indicators: Bullish and bearish signals are marked with upward and downward triangles, making it easy to spot potential entry or exit points.
Detailed Trigger Descriptions: A comprehensive table lists all available triggers and their descriptions, aiding in selection and understanding of each trigger's mechanism.
Configuration Options
Bullish and Bearish Colors: Customize the color of the labels for bullish (upward) and bearish (downward) signals.
Trend Lookback Period: Choose how far back (in bars) the indicator should look to determine the trend, affecting the calculation of certain triggers.
Trigger Selection for Bullish and Bearish Signals: Pick specific triggers for both bullish and bearish conditions from a list of 10 different criteria, ranging from MACD crossovers to historical comparisons of MACD, signal line, and histogram values.
Label Size and Font Settings: Adjust the size of the signal labels on the chart and the font size of the trigger descriptions table to ensure readability and fit with your chart layout.
Trigger Descriptions Table Position and Color: Customize the position and color of the trigger descriptions table to match your chart's aesthetic and layout preferences.
Trigger Mechanisms
Trigger 1 to 10: Each trigger corresponds to a specific condition involving the MACD line, signal line, and histogram. These include crossovers, directional changes compared to previous bars, and comparisons of current values to historical values.
Usage
1. Select Trigger Conditions: Choose the desired triggers for bullish and bearish signals based on your trading strategy.
2. Customize Visuals: Set your preferred colors for the bullish and bearish labels, adjust label and font sizes, and configure the trigger descriptions table.
3. Analyze Signals: Watch for the upward (bullish) and downward (bearish) triangles to identify potential trading opportunities based on MACD crossover signals.
Conclusion
The MACD Cross Triangle Indicator offers a customizable and visually intuitive way to leverage MACD crossover signals for trading. With its flexible settings and clear signal indicators, traders can tailor the indicator to fit their strategy and improve their decision-making process on TradingView.
Smart DCA StrategyINSPIRATION
While Dollar Cost Averaging (DCA) is a popular and stress-free investment approach, I noticed an opportunity for enhancement. Standard DCA involves buying consistently, regardless of market conditions, which can sometimes mean missing out on optimal investment opportunities. This led me to develop the Smart DCA Strategy – a 'set and forget' method like traditional DCA, but with an intelligent twist to boost its effectiveness.
The goal was to build something more profitable than a standard DCA strategy so it was equally important that this indicator could backtest its own results in an A/B test manner against the regular DCA strategy.
WHY IS IT SMART?
The key to this strategy is its dynamic approach: buying aggressively when the market shows signs of being oversold, and sitting on the sidelines when it's not. This approach aims to optimize entry points, enhancing the potential for better returns while maintaining the simplicity and low stress of DCA.
WHAT THIS STRATEGY IS, AND IS NOT
This is an investment style strategy. It is designed to improve upon the common standard DCA investment strategy. It is therefore NOT a day trading strategy. Feel free to experiment with various timeframes, but it was designed to be used on a daily timeframe and that's how I recommend it to be used.
You may also go months without any buy signals during bull markets, but remember that is exactly the point of the strategy - to keep your buying power on the sidelines until the markets have significantly pulled back. You need to be patient and trust in the historical backtesting you have performed.
HOW IT WORKS
The Smart DCA Strategy leverages a creative approach to using Moving Averages to identify the most opportune moments to buy. A trigger occurs when a daily candle, in its entirety including the high wick, closes below the threshold line or box plotted on the chart. The indicator is designed to facilitate both backtesting and live trading.
HOW TO USE
Settings:
The input parameters for tuning have been intentionally simplified in an effort to prevent users falling into the overfitting trap.
The main control is the Buying strictness scale setting. Setting this to a lower value will provide more buying days (less strict) while higher values mean less buying days (more strict). In my testing I've found level 9 to provide good all round results.
Validation days is a setting to prevent triggering entries until the asset has spent a given number of days (candles) in the overbought state. Increasing this makes entries stricter. I've found 0 to give the best results across most assets.
In the backtest settings you can also configure how much to buy for each day an entry triggers. Blind buy size is the amount you would buy every day in a standard DCA strategy. Smart buy size is the amount you would buy each day a Smart DCA entry is triggered.
You can also experiment with backtesting your strategy over different historical datasets by using the Start date and End date settings. The results table will not calculate for any trades outside what you've set in the date range settings.
Backtesting:
When backtesting you should use the results table on the top right to tune and optimise the results of your strategy. As with all backtests, be careful to avoid overfitting the parameters. It's better to have a setup which works well across many currencies and historical periods than a setup which is excellent on one dataset but bad on most others. This gives a much higher probability that it will be effective when you move to live trading.
The results table provides a clear visual representation as to which strategy, standard or smart, is more profitable for the given dataset. You will notice the columns are dynamically coloured red and green. Their colour changes based on which strategy is more profitable in the A/B style backtest - green wins, red loses. The key metrics to focus on are GOA (Gain on Account) and Avg Cost .
Live Trading:
After you've finished backtesting you can proceed with configuring your alerts for live trading.
But first, you need to estimate the amount you should buy on each Smart DCA entry. We can use the Total invested row in the results table to calculate this. Assuming we're looking to trade on BITSTAMP:BTCUSD
Decide how much USD you would spend each day to buy BTC if you were using a standard DCA strategy. Lets say that is $5 per day
Enter that USD amount in the Blind buy size settings box
Check the Blind Buy column in the results table. If we set the backtest date range to the last 10 years, we would expect the amount spent on blind buys over 10 years to be $18,250 given $5 each day
Next we need to tweak the value of the Smart buy size parameter in setting to get it as close as we can to the Total Invested amount for Blind Buy
By following this approach it means we will invest roughly the same amount into our Smart DCA strategy as we would have into a standard DCA strategy over any given time period.
After you have calculated the Smart buy size , you can go ahead and set up alerts on Smart DCA buy triggers.
BOT AUTOMATION
In an effort to maintain the 'set and forget' stress-free benefits of a standard DCA strategy, I have set my personal Smart DCA Strategy up to be automated. The bot runs on AWS and I have a fully functional project for the bot on my GitHub account. Just reach out if you would like me to point you towards it. You can also hook this into any other 3rd party trade automation system of your choice using the pre-configured alerts within the indicator.
PLANNED FUTURE DEVELOPMENTS
Currently this is purely an accumulation strategy. It does not have any sell signals right now but I have ideas on how I will build upon it to incorporate an algorithm for selling. The strategy should gradually offload profits in bull markets which generates more USD which gives more buying power to rinse and repeat the same process in the next cycle only with a bigger starting capital. Watch this space!
MARKETS
Crypto:
This strategy has been specifically built to work on the crypto markets. It has been developed, backtested and tuned against crypto markets and I personally only run it on crypto markets to accumulate more of the coins I believe in for the long term. In the section below I will provide some backtest results from some of the top crypto assets.
Stocks:
I've found it is generally more profitable than a standard DCA strategy on the majority of stocks, however the results proved to be a lot more impressive on crypto. This is mainly due to the volatility and cycles found in crypto markets. The strategy makes its profits from capitalising on pullbacks in price. Good stocks on the other hand tend to move up and to the right with less significant pullbacks, therefore giving this strategy less opportunity to flourish.
Forex:
As this is an accumulation style investment strategy, I do not recommend that you use it to trade Forex.
STRATEGY IN ACTION
Here you see the indicator running on the BITSTAMP:BTCUSD pair. You can read the indicator as follows:
Vertical green bands on historical candles represents where buy signals triggered in the past
Table on the top right represents the results of the A/B backtest against a standard DCA strategy
Green Smart Buy column shows that Smart DCA was more profitable than standard DCA on this backtest. That is shown by the percentage GOA (Gain on Account) and the Avg Cost
Smart Buy Zone label marks the threshold which the entire candle must be below to trigger a buy signal (line can be changed to a box under plotting settings)
Green color of Smart Buy Zone label represents that the open candle is still valid for a buy signal. A signal will only be generated if the candle closes while this label is still green
Below is the same BITSTAMP:BTCUSD chart a couple of days later. Notice how the threshold has been broken and the Smart Buy Zone label has turned from green to red. No buy signal can be triggered for this day - even if the candle retraced and closed below the threshold before daily candle close.
Notice how the green vertical bands tend to be present after significant pullbacks in price. This is the reason the strategy works! Below is the same BITSTAMP:BTCUSD chart, but this time zoomed out to present a clearer picture of the times it would invest vs times it would sit out of the market. You will notice it invests heavily in bear markets and significant pullbacks, and does not buy anything during bull markets.
Finally, to visually demonstrate the indicator on an asset other than BTC, here is an example on CRYPTO:ETHUSD . In this case the current daily high has not touched the threshold so it is still possible for this to be a valid buy trigger on daily candle close. The vertical green band will not print until the buy trigger is confirmed.
BACKTEST RESULTS
Now for some backtest results to demonstrate the improved performance over a standard DCA strategy using all non-stablecoin assets in the top 30 cryptos by marketcap.
I've used the TradingView ticker (exchange name denoted as CRYPTO in the symbol search) for every symbol tested with the exception of BTCUSD because there was some dodgy data at the beginning of the TradingView BTCUSD chart which overinflated the effectiveness of the Smart DCA strategy on that ticker. For BTCUSD I've used the BITSTAMP exchange data. The symbol links below will take you to the correct chart and exchange used for the test.
I'm using the GOA (Gain on Account) values to present how each strategy performed.
The value on the left side is the standard DCA result and the right is the Smart DCA result.
✅ means Smart DCA strategy outperformed the standard DCA strategy
❌ means standard DCA strategy outperformed the Smart DCA strategy
To avoid overfitting, and to prove that this strategy does not suffer from overfitting, I've used the exact same input parameters for every symbol tested below. The settings used in these backtests are:
Buying strictness scale: 9
Validation days: 0
You can absolutely tweak the values per symbol to further improve the results of each, however I think using identical settings on every pair tested demonstrates a higher likelihood that the results will be similar in the live markets.
I'm presenting results for two time periods:
First price data available for trading pair -> closing candle on Friday 26th Jan 2024 (ALL TIME)
Opening candle on Sunday 1st Jan 2023 -> closing candle on Friday 26th Jan 2024 (JAN 2023 -> JAN 2024)
ALL TIME:
BITSTAMP:BTCUSD 80,884% / 133,582% ✅
CRYPTO:ETHUSD 17,231% / 36,146% ✅
CRYPTO:BNBUSD 5,314% / 2,702% ❌
CRYPTO:SOLUSD 1,745% / 1,171% ❌
CRYPTO:XRPUSD 2,585% / 4,544% ✅
CRYPTO:ADAUSD 338% / 353% ✅
CRYPTO:AVAXUSD 130% / 160% ✅
CRYPTO:DOGEUSD 13,690% / 16,432% ✅
CRYPTO:TRXUSD 414% / 466% ✅
CRYPTO:DOTUSD -16% / -7% ✅
CRYPTO:LINKUSD 1,161% / 2,164% ✅
CRYPTO:TONUSD 25% / 47% ✅
CRYPTO:MATICUSD 1,769% / 1,587% ❌
CRYPTO:ICPUSD 70% / 50% ❌
CRYPTO:SHIBUSD -20% / -19% ✅
CRYPTO:LTCUSD 486% / 718% ✅
CRYPTO:BCHUSD -4% / 3% ✅
CRYPTO:LEOUSD 102% / 151% ✅
CRYPTO:ATOMUSD 46% / 91% ✅
CRYPTO:UNIUSD -16% / 1% ✅
CRYPTO:ETCUSD 283% / 414% ✅
CRYPTO:OKBUSD 1,286% / 1,935% ✅
CRYPTO:XLMUSD 1,471% / 1,592% ✅
CRYPTO:INJUSD 830% / 1,035% ✅
CRYPTO:OPUSD 138% / 195% ✅
CRYPTO:NEARUSD 23% / 44% ✅
Backtest result analysis:
Assuming we have an initial investment amount of $10,000 spread evenly across each asset since the creation of each asset, it would have provided the following results.
Standard DCA Strategy results:
Average percent return: 4,998.65%
Profit: $499,865
Closing balance: $509,865
Smart DCA Strategy results:
Average percent return: 7,906.03%
Profit: $790,603
Closing balance: $800,603
JAN 2023 -> JAN 2024:
BITSTAMP:BTCUSD 47% / 66% ✅
CRYPTO:ETHUSD 26% / 33% ✅
CRYPTO:BNBUSD 15% / 17% ✅
CRYPTO:SOLUSD 272% / 394% ✅
CRYPTO:XRPUSD 7% / 12% ✅
CRYPTO:ADAUSD 43% / 59% ✅
CRYPTO:AVAXUSD 116% / 151% ✅
CRYPTO:DOGEUSD 8% / 14% ✅
CRYPTO:TRXUSD 48% / 65% ✅
CRYPTO:DOTUSD 24% / 35% ✅
CRYPTO:LINKUSD 83% / 124% ✅
CRYPTO:TONUSD 7% / 21% ✅
CRYPTO:MATICUSD -3% / 7% ✅
CRYPTO:ICPUSD 161% / 196% ✅
CRYPTO:SHIBUSD 1% / 8% ✅
CRYPTO:LTCUSD -15% / -7% ✅
CRYPTO:BCHUSD 47% / 68% ✅
CRYPTO:LEOUSD 9% / 11% ✅
CRYPTO:ATOMUSD 1% / 15% ✅
CRYPTO:UNIUSD 9% / 23% ✅
CRYPTO:ETCUSD 27% / 40% ✅
CRYPTO:OKBUSD 21% / 30% ✅
CRYPTO:XLMUSD 11% / 19% ✅
CRYPTO:INJUSD 477% / 446% ❌
CRYPTO:OPUSD 77% / 91% ✅
CRYPTO:NEARUSD 78% / 95% ✅
Backtest result analysis:
Assuming we have an initial investment amount of $10,000 spread evenly across each asset for the duration of 2023, it would have provided the following results.
Standard DCA Strategy results:
Average percent return: 61.42%
Profit: $6,142
Closing balance: $16,142
Smart DCA Strategy results:
Average percent return: 78.19%
Profit: $7,819
Closing balance: $17,819
Divergence AnalyzerUnlock the potential of your trading strategy with the Divergence Analyzer, a sophisticated indicator designed to identify divergence patterns between two financial instruments. Whether you're a seasoned trader or just starting, this tool provides valuable insights into market trends and potential trading opportunities.
Key Features:
1. Versatility in Symbol Selection:
- Choose from a wide range of symbols for comparison, including popular indices like XAUUSD and SPX.
- Seamlessly toggle between symbols to analyze divergences and make informed trading decisions.
2. Flexible Calculation Options:
- Customizable options allow you to use a different symbol for calculation instead of the chart symbol.
- Fine-tune your analysis by selecting specific symbols for comparison based on your trading preferences.
3. Logarithmic Scale Analysis:
- Utilizes logarithmic scales for accurate representation of price movements.
- Linear regression coefficients are calculated on the logarithmic scale, providing a comprehensive view of trend strength.
4. Dynamic Length and Smoothing:
- Adjust the length parameter to adapt the indicator to different market conditions.
- Smoothed linear regression with exponential moving averages enhances clarity and reduces noise.
5. Standard Deviation Normalization:
- Normalizes standard deviations over 200 periods, offering a standardized view of price volatility.
- Easily compare volatility levels across different symbols for effective divergence analysis.
6. Color-Coded Divergence Visualization:
- Clearly distinguish positive and negative divergences with customizable color options.
- Visualize divergence deltas with an intuitive color scheme for quick and effective interpretation.
7. Symbol Information Table:
- An included table provides at-a-glance information about the selected symbols.
- Identify Symbol 1 and Symbol 2, along with their corresponding positive and negative divergence colors.
How to Use:
1. Select symbols for analysis using the user-friendly inputs.
2. Customize calculation options based on your preferences.
3. Analyze the divergence delta plot for clear visual indications.
4. Refer to the symbol information table for a quick overview of selected instruments.
Empower your trading strategy with the Divergence Analyzer and gain a competitive edge in the dynamic world of financial markets. Start making more informed decisions today!
SandTigerSandTiger is an auto-counting tool that counts naturally occurring events in a price series. This version has been reduced to 377 lines of code and should run faster than previous versions. Although not shown here, I highly recommend running my 'ELB' script with SandTiger. ELB is an 'event locator' and will mark all points that SandTiger numbers - giving you visual cues as to where these points are located. ELB also displays support/resistance levels.
SandTiger is designed to be used with MAGENTA - a counting system for Forex and other markets.
MAGENTA is a free and open framework for understanding and explaining price movement in financial markets. Any materials associated with MAGENTA are strictly for educational purposes only.
SandTiger tracks Component Values, Dyads, and Sum Table Values (STV's) over straight and curved trends, allowing a trader to discern where directional shifts are likely to occur.
SandTiger requires just 3 things to function accurately:
1) A correct starting point (this will typically be an obvious trend turn high or low in a series of price moves).
2) A 'push 1' count ('push 1' runs from the starting point to the event prior to the first terminal of the first FCT or Fractured Counter-Trend).
3) A 'high prime' value (the high prime count runs from the starting point through to the second terminal of the first FCT with no skips).
FRAMEWORK OVERVIEW: 'Component' values are filtered from the prime set (including the half prime and further reductions). Once we have the comp table we add the values to get a 'total'. With the 'total' we divide and multiply by two to get two additional values. 'Derivatives' are based on various calculations using these three values.
We're looking for 'total/2' to count into either itself, 'total', 'total*2', or a derivative. Comp counts are in Tx form and counted from trend start. If the trend doesn't turn on a comp value it will likely turn on a Dyad or STV value. If that also doesn't happen it's likely you have a 'curved' trend/sequence that will turn on one of the above after moving away from its high/low. This can also be traded using SandTiger's 'Seg Terminals' skip option.
Sum tables and Dyad values are drawn from the 'primes' and Dyads use the 'push1' value as well. In a structural trend, primes are gotten by counting pushpulls 1 & 2 in 'Ti' form. Comps, Sum table values, and Dyads are equivalent, sequences can turn on either value type belonging to the 1st or 2nd prime set. Both STV's and Dyads are counted in 'Tx' form (except where count-through signals occur).
Types and antitypes correlate and are associated with a 12-count 'cycle.' (Ti = 'Terminals Included'; Tx = 'Terminals eXcluded'; both refer to FCT terminals)
THE STRATEGY:
For Structures: Trade Comps, Dyads, and STV's from sets 1 (all) and 2 (Dyads and STV's only) in the 'main' segment then on the 'carry-over' by skipping segment terminals. If a PC or cycle caps the sequence, trade that as well.
For NSM's: Trade movements that flash a signal prior to the end of the initial cycle. The mark will be the push1 value. Twelve will be the 'high prime.' Skip interrupts and trade carry-over values.
The first version of SandTiger was conceived/planned/authored by Erek A.D. and coded by Erek A.D. and @SimpleCryptoLife beginning in August 2022 and finishing in Dec. 2022
The current version was written and developed July 3, 2023 and has been refined and upgraded by Erek A.D. through Jan. 2024...
Z-ScoreThe "Z-Score" indicator is a unique and powerful tool designed to help traders identify overbought and oversold conditions in the market. Below is an explanation of its features, usefulness, and what makes it special:
Features:
Z-Score Calculation: The indicator calculates the Z-Score, a statistical measure that represents how far the current price is from the moving average (MA) in terms of standard deviations. It helps identify extreme price movements.
Customizable Parameters: Traders can adjust key parameters such as the Z-Score threshold, the type of MA (e.g., SMA, EMA), and the length of the moving average to suit their trading preferences.
Signal Options: The indicator offers flexibility in terms of signaling. Traders can choose whether to trigger signals when the Z-Score crosses the specified threshold or when it moves away from the threshold.
Visual Signals : Z-Score conditions are represented visually on the chart with color-coded background highlights. Overbought conditions are marked with a red background, while oversold conditions are indicated with a green background.
Information Table: A dynamic information table displays essential details, including the MA type, MA length, MA value, standard deviation, current price, and Z-Score. This information table helps traders make informed decisions.
Usefulness:
Overbought and Oversold Signals: Z-Score is particularly valuable for identifying overbought and oversold market conditions. Traders can use this information to potentially enter or exit positions.
Statistical Analysis: The Z-Score provides a statistical measure of price deviation, offering a data-driven approach to market analysis.
Customization: Traders can customize the indicator to match their trading strategies and preferences, enhancing its adaptability to different trading styles.
Visual Clarity: The visual signals make it easy for traders to quickly spot potential trade opportunities on the price chart.
In summary, the Z-Score indicator is a valuable tool for traders looking to incorporate statistical analysis into their trading strategies. Its customizability, visual signals, and unique statistical approach make it an exceptional choice for identifying overbought and oversold market conditions and potential trading opportunities.
Time Matrix [Pro+] (DRxICT)Description:
The Time Matrix Pro is an automated Time-based trading tool adaptable to futures, forex, and bond markets. This indicator is inspired by concepts taught by the Inner Circle Trader (ICT) and ICT_Concepts.
ICT’s repertoire encompasses the concepts of liquidity and couples them with Time. The Time Matrix helps the analyst to locate key Time-based price levels to determine bias and recurring price patterns within the market. Analysts can use levels like Previous Day’s Highs and Lows, Weekly Highs and Lows, Session Openings, and Macros to base and qualify Premium and Discount arrays in intraday analysis.
Session Boxes are Time opportunities of the day that identify the market mechanics of consolidation, expansion, retracement, and reversals.
ICT_Concepts's Session Boxes are described as the Premarket, AM Session, PM session:
Premarket is defined as 9:30pm to 1:30am
AM session is defined as 4:00am to 11:00am
PM Session is defined as 11:30am to 2:15pm
Understanding how Time is crucial for identifying intraday profiling, the analyst is able to toggle price levels in conjunction with Time-based macros. These help analyze key market turning points that can correspond to unique market mechanics.
Beyond the Time-based liquidity levels, and the Time macros, there are also predefined Time clusters.
These clusters highlight a significant lower Timeframe candle which was found to hold significant value by ICT_Concepts. Very much alike Time-based liquidity levels, analysts will notice how price reacts to support or negate existing orderflow, trend and direction.
Key Features:
Customizable Extension: the analyst is given the choice to toggle the ending Time Offset to either Noon NY Time or at the end of the trading day.
Time-Based Toggles: choose individual Time-based prices to highlight on your chart.
Time Table: depending on the Timeframe, the Time Table will display the number of bars and the Time elapsed since the Time-based liquidity levels were established.
Other Features
Customize Session Boxes Color
Customize Time-Based Liquidity Line Style
Customize Time-Based Liquidity Level Color
Customize Time-Based Liquidity Line Width
Customize Table Size and Location
Usage Guidance:
Add Time Matrix to your Tradingview chart.
Customize your desired settings of Time-Based Liquidity Levels to align with your personal preference.
Observe where the Time-Based Liquidity Levels as well as Previous Day, Week, and Macros play a role in intraday narrative.
Analysts can choose to utilize Time-Based Liquidity Levels as automated framework to organize models and layouts.
These tools are available ONLY on the TradingView platform.
Terms and Conditions
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3x MTF MACD v3.0MACD's on 3 different Time Frames
Indicator Information
- Each Time Frame shows start of Trend and end of trend of the MACD vs the Signal Cross
- They are labled 1,2,3 with respective up or down triangle for possible direction.
User Inputs
- configure the indicator by specifying various inputs. These inputs include colors for bullish
and bearish conditions, the time frame to use, whether to show a Simple Moving Average
(SMA) line, and other parameters.
- Users can choose time frames for analysis (like 30 minutes, 1 hour, etc.)
but they must be in mintues.
- The code also allows users to customize how the indicator looks on the chart by providing
options for position and color.
Main Calculations
- The script calculates the Simple Moving Average (SMA) based on the user-defined time
frame.
- It then determines the color of the plot (line) based on certain conditions, such as whether
the SMA is rising or falling. These conditions help users quickly identify market trends.
Label Creation
- The code creates labels that can be displayed on the chart.
These labels indicate whether there's a bullish or bearish signal.
Level Detection
- The script determines and labels key levels or points of interest in the chart based on
certain conditions.
- It can show labels like "①" and "▲" for bullish conditions and "▼" for bearish conditions.
Table Display
- There's an option to show a table on the chart that displays information about the MACD
indicator Chosen and the NUmber Bubble assocated with that time frame
- The table can include information like which time frame is being analyzed, whether the SMA
line is shown, and other relevant data.
Plotting on the Chart
- The script plots the Simple Moving Average (SMA) on the chart. The color of this line
changes based on the calculated trend conditions.
ATR (Average True Range)
- The script also plots the Average True Range (ATR) on the chart. ATR is used to measure
market volatility.
"In essence, this script is a highly customizable MACD and SMA indicator for traders. It assists traders in comprehending market trends, offering insights into different MACD cycles concerning various timeframes.
Users can configure it to match their trading strategies, and it presents information in a user-friendly manner with colors, labels, and tables.
This simplifies market analysis, allowing traders to make more informed decisions without the distraction of multiple indicators."
Quadratic & Linear Time Series Regression [SS]Hey everyone,
Releasing the Quadratic/Linear Time Series regression indicator.
About the indicator:
Most of you will be familiar with the conventional linear regression trend boxes (see below):
This is an awesome feature in Tradingview and there are quite a few indicators that follow this same principle.
However, because of the exponential and cyclical nature of stocks, linear regression tends to not be the best fit for stock time series data. From my experience, stocks tend to fit better with quadratic (or curvlinear) regression, which there really isn't a lot of resources for.
To put it into perspective, let's take SPX on the 1 month timeframe and plot a linear regression trend from 1930 till now:
You can see that its not really a great fit because of the exponential growth that SPX has endured since the 1930s. However, if we take a quadratic approach to the time series data, this is what we get:
This is a quadratic time series version, extended by up to 3 standard deviations. You can see that it is a bit more fitting.
Quadratic regression can also be helpful for looking at cycle patterns. For example, if we wanted to plot out how the S&P has performed from its COVID crash till now, this is how it would look using a linear regression approach:
But this is how it would look using the quadratic approach:
So which is better?
Both linear regression and quadratic regression are pivotal and important tools for traders. Sometimes, linear regression is more appropriate and others quadratic regression is more appropriate.
In general, if you are long dating your analysis and you want to see the trajectory of a ticker further back (over the course of say, 10 or 15 years), quadratic regression is likely going to be better for most stocks.
If you are looking for short term trades and short term trend assessments, linear regression is going to be the most appropriate.
The indicator will do both and it will fit the linear regression model to the data, which is different from other linreg indicators. Most will only find the start of the strongest trend and draw from there, this will fit the model to whatever period of time you wish, it just may not be that significant.
But, to keep it easy, the indicator will actually tell you which model will work better for the data you are selecting. You can see it in the example in the main chart, and here:
Here we see that the indicator indicates a better fit on the quadratic model.
And SPY during its recent uptrend:
For that, let's take a look at the Quadratic Vs the Linear, to see how they compare:
Quadratic:
Linear:
Functions:
You will see that you have 2 optional tables. The statistics table which shows you:
The R Squared to assess for Variance.
The Correlation to assess for the strength of the trend.
The Confidence interval which is set at a default of 1.96 but can be toggled to adjust for the confidence reading in the settings menu. (The confidence interval gives us a range of values that is likely to contain the true value of the coefficient with a certain level of confidence).
The strongest relationship (quadratic or linear).
Then there is the range table, which shows you the anticipated price ranges based on the distance in standard deviations from the mean.
The range table will also display to you how often a ticker has spent in each corresponding range, whether that be within the anticipated range, within 1 SD, 2 SD or 3 SD.
You can select up to 3 additional standard deviations to plot on the chart and you can manually select the 3 standard deviations you want to plot. Whether that be 1, 2, 3, or 1.5, 2.5 or 3.5, or any combination, you just enter the standard deviations in the settings menu and the indicator will adjust the price targets and plotted bands according to your preferences. It will also count the amount of time the ticker spent in that range based on your own selected standard deviation inputs.
Tips on Use:
This works best on the larger timeframes (1 hour and up), with RTH enabled.
The max lookback is 5,000 candles.
If you want to ascertain a longer term trend (over years to months), its best to adjust your chart timeframe to the weekly and/or monthly perspective.
And that's the indicator! Hopefully you all find it helpful.
Let me know your questions and suggestions below!
Safe trades to all!
