Polyphase Stochastic RSI (PSRSI)The Polyphase Stochastic RSI (PSRSI) provides a continuous estimate of higher timeframe Stochastic RSI behavior by using polyphase decimation. The number of phases represents the timeframe multiplier - for example, 3 phases approximates a 3x higher timeframe.
While traditional higher timeframe indicators only update at the completion of each higher timeframe bar, the PSRSI creates a continuous signal by maintaining multiple phase-shifted calculations and combining them with appropriate anti-aliasing filters. This approach eliminates the gaps and discontinuities typically seen in higher timeframe indicators, though the resulting signal may sometimes deviate from the true higher timeframe values due to its estimative nature.
The indicator processes data through parallel phase calculations, each handling a different subset of price data offset in time. These phases are then filtered and combined to prevent aliasing artifacts that occur in simple timeframe conversions. The result is a smooth, continuous signal that starts providing meaningful values immediately, without requiring a warm-up period of higher timeframe bars.
Users can choose between RSI and Stochastic RSI modes, with both benefiting from the same polyphase processing technique. The indicator maintains the standard interpretation of overbought and oversold conditions while providing a more continuous view of higher timeframe momentum.
Educational
Weighted Fourier Transform: Spectral Gating & Main Frequency🙏🏻 This drop has 2 purposes:
1) to inform every1 who'd ever see it that Weighted Fourier Tranform does exist, while being available nowhere online, not even in papers, yet there's nothing incredibly complicated about it, and it can/should be used in certain cases;
2) to show TradingView users how they can use it now in dem endevours, to show em what spectral filtering is, and what can they do with all of it in diy mode.
... so we gonna have 2 sections in the description
Section 1: Weighted Fourier Transform
It's quite easy to include weights in Fourier analysis: you just premultiply each datapoint by its corresponding weight -> feed to direct Fourier Transform, and then divide by weights after inverse Fourier transform. Alternatevely, in direct transform you just multiply contributions of each data point to the real and imaginary parts of the Fourier transform by corresponding weights (in accumulation phase), and in inverse transform you divide by weights instead during the accumulation phase. Everything else stays the same just like in non-weighted version.
If you're from the first target group let's say, you prolly know a thing or deux about how to code & about Fourier Transform, so you can just check lines of code to see the implementation of Weighted Discrete version of Fourier Transform, and port it to to any technology you desire. Pine Script is a developing technology that is incredibly comfortable in use for quant-related tasks and anything involving time series in general. While also using Python for research and C++ for development, every time I can do what I want in Pine Script, I reach for it and never touch matlab, python, R, or anything else.
Weighted version allows you to explicetly include order/time information into the operation, which is essential with every time series, although not widely used in mainstream just as many other obvious and right things. If you think deeply, you'll understand that you can apply a usual non-weighted Fourier to any 2d+ data you can (even if none of these dimensions represent time), because this is a geometric tool in essence. By applying linearly decaying weights inside Fourier transform, you're explicetly saying, "one of these dimensions is Time, and weights represent the order". And obviously you can combine multiple weightings, eg time and another characteristic of each datum, allows you to include another non-spatial dimension in your model.
By doing that, on properly processed (not only stationary but Also centered around zero data), you can get some interesting results that you won't be able to recreate without weights:
^^ A sine wave, centered around zero, period of 16. Gray line made by: DWFT (direct weighted Fourier transform) -> spectral gating -> IWFT (inverse weighted Fourier transform) -> plotting the last value of gated reconstructed data, all applied to expanding window. Look how precisely it follows the original data (the sine wave) with no lag at all. This can't be done by using non-weighted version of Fourier transform.
^^ spectral filtering applied to the whole dataset, calculated on the latest data update
And you should never forget about Fast Fourier Transform, tho it needs recursion...
Section 2: About use cases for quant trading, about this particular implementaion in Pine Script 6 (currently the latest version as of Friday 13, December 2k24).
Given the current state of things, we have certain limits on matrix size on TradingView (and we need big dope matrixes to calculate polynomial regression -> detrend & center our data before Fourier), and recursion is not yet available in Pine Script, so the script works on short datasets only, and requires some time.
A note on detrending. For quality results, Fourier Transform should be applied to not only stationary but also centered around zero data. The rightest way to do detrending of time series
is to fit Cumulative Weighted Moving Polynomial Regression (known as WLSMA in some narrow circles xD) and calculate the deltas between datapoint at time t and this wonderful fit at time t. That's exactly what you see on the main chart of script description: notice the distances between chart and WLSMA, now look lower and see how it matches the distances between zero and purple line in WFT study. Using residuals of one regression fit of the whole dataset makes less sense in time series context, we break some 'time' and order rules in a way, tho not many understand/cares abouit it in mainstream quant industry.
Two ways of using the script:
Spectral Gating aka Spectral filtering. Frequency domain filtering is quite responsive and for a greater computational cost does not introduce a lag the way it works with time-domain filtering. Works this way: direct Fourier transform your data to get frequency & phase info -> compute power spectrum out of it -> zero out all dem freqs that ain't hit your threshold -> inverse Fourier tranform what's left -> repeat at each datapoint plotting the very first value of reconstructed array*. With this you can watch for zero crossings to make appropriate trading decisions.
^^ plot Freq pass to use the script this way, use Level setting to control the intensity of gating. These 3 only available values: -1, 0 and 1, are the general & natural ones.
* if you turn on labels in script's style settings, you see the gray dots perfectly fitting your data. They get recalculated (for the whole dataset) at each update. You call it repainting, this is for analytical & aesthetic purposes. Included for demonstration only.
Finding main/dominant frequency & period. You can use it to set up Length for your other studies, and for analytical purposes simply to understand the periodicity of your data.
^^ plot main frequency/main period to use the script this way. On the screenshot, you can see the script applied to sine wave of period 16, notice how many datapoints it took the algo to figure out the signal's period quite good in expanding window mode
Now what's the next step? You can try applying signal windowing techniques to make it all less data-driven but your ego-driven, make a weighted periodogram or autocorrelogram (check Wiener-Khinchin Theorem ), and maybe whole shiny spectrogram?
... you decide, choice is yours,
The butterfly reflect the doors ...
∞
Multi TimeFrame OHLC Overlay @MaxMaseratiMulti TimeFrame OHLC Overlay @MaxMaserati
A powerful and versatile indicator that displays OHLC (Open, High, Low, Close) data across multiple timeframes with enhanced visualization features. Perfect for traders who need to analyze price action across different time periods simultaneously.
Key Features:
Customizable multi-timeframe OHLC visualization with box and line overlays
Extended OHLC lines from higher timeframes with clear labeling
Distinct bullish and bearish candle representations
Fully configurable color schemes and display options
Real-time timeframe information display
Main Components:
Multi-Timeframe Display
Primary timeframe OHLC visualization with boxes and lines
Extended timeframe overlay for broader market context
Clear visual distinction between timeframes
Customizable Visuals
Separate color settings for bullish and bearish patterns
Adjustable transparency for both body and wick components
Configurable OHLC line colors and visibility
Extended Lines Features
Higher timeframe OHLC level overlay
Custom labels with timeframe identification
Adjustable line properties and visibility
Information Display
Current timeframe indicator
Extended timeframe reference
Clean and unobtrusive interface
Settings Groups:
Extended OHLC Lines
Labels Options
Display Options
Bullish/Bearish Candle Settings
OHLC Lines Configuration
Usage Tips:
Start with the default 240-minute timeframe or adjust to your preferred interval
Use the extended lines feature to view higher timeframe levels
Customize colors and transparency to match your chart theme
Enable/disable specific components based on your analysis needs
Perfect For:
Multi-timeframe analysis
Support/Resistance identification
Price action trading
Trend following strategies
Market structure analysis
This indicator combines powerful multi-timeframe analysis capabilities with clean visualization, making it an essential tool for traders who need to maintain awareness of price action across different time periods.
Note:
For optimal performance, adjust the visual settings according to your chart's timeframe and color scheme. The indicator is designed to work seamlessly across all trading instruments and timeframes.
Custom Strategy: ETH Martingale 2.0Strategic characteristics
ETH Little Martin 2.0 is a self-developed trading strategy based on the Martingale strategy, mainly used for trading ETH (Ethereum). The core idea of this strategy is to place orders in the same direction at a fixed price interval, and then use Martin's multiple investment principle to reduce losses, but this is also the main source of losses.
Parameter description:
1 Interval： The minimum spacing for taking profit, stop loss, and opening/closing of orders. Different targets have different spacing. Taking ETH as an example, it is generally recommended to have a spacing of 2% for fluctuations in the target.
2 Base Price： This is the price at which you triggered the first order. Similarly, I am using ETH as an example. If you have other targets, I suggest using the initial value of a price that can be backtesting. The Base Price is only an initial order price and has no impact on subsequent orders.
3 Initial Order Amount： Users can set an initial order amount to control the risk of each transaction. If the stop loss is reached, we will double the amount based on this value. This refers to the value of the position held, not the number of positions held.
4 Loss Multiplier： The strategy will increase the next order amount based on the set multiple after the stop loss, in order to make up for the previous losses through a larger position. Note that after taking profit, it will be reset to 1 times the Initial Order Amount.
5. Long Short Operation: The first order of the strategy is a multiple entry, and in subsequent orders, if the stop loss is reached, a reverse order will be opened. The position value of a one-way order is based on the Loss Multiplier multiple investment, so it is generally recommended that the Loss Multiplier default to 2.
Improvement direction
Although this strategy already has a certain trading logic, there are still some improvement directions that can be considered:
1. Dynamic adjustment of spacing: Currently, the spacing is fixed, and it can be considered to dynamically adjust the spacing based on market volatility to improve the adaptability of the strategy. Try using dynamic spacing, which may be more suitable for the actual market situation.
2. Filtering criteria: Orders and no orders can be optimized separately. The biggest problem with this strategy is that it will result in continuous losses during fluctuations, and eventually increase the investment amount. You can consider filtering out some fluctuations or only focusing on trend trends.
3. Risk management: Add more risk management measures, such as setting a maximum loss limit to avoid huge losses caused by continuous stop loss.
4. Optimize the stop loss multiple: Currently, the stop loss multiple is fixed, and it can be considered to dynamically adjust the multiple according to market conditions to reduce risk.
Employee Portfolio Generator [By MUQWISHI]▋ INTRODUCTION :
The “Employee Portfolio Generator” simplifies the process of building a long-term investment portfolio tailored for employees seeking to build wealth through investments rather than traditional bank savings. The tool empowers employees to set up recurring deposits at customizable intervals, enabling to make additional purchases in a list of preferred holdings, with the ability to define the purchasing investment weight for each security. The tool serves as a comprehensive solution for tracking portfolio performance, conducting research, and analyzing specific aspects of portfolio investments. The output includes an index value, a table of holdings, and chart plots, providing a deeper understanding of the portfolio's historical movements.
_______________________
▋ OVERVIEW:
● Scenario (The chart above can be taken as an example) :
Let say, in 2010, a newly employed individual committed to saving $1,000 each month. Rather than relying on a traditional savings account, chose to invest the majority of monthly savings in stable well-established stocks. Allocating 30% of monthly saving to AMEX:SPY and another 30% to NASDAQ:QQQ , recognizing these as reliable options for steady growth. Additionally, there was an admired toward innovative business models of NASDAQ:AAPL , NASDAQ:MSFT , NASDAQ:AMZN , and NASDAQ:EBAY , leading to invest 10% in each of those companies. By the end of 2024, after 15 years, the total monthly deposits amounted to $179,000, which would have been the result of traditional saving alone. However, by sticking into long term invest, the value of the portfolio assets grew, reaching nearly $900,000.
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▋ OUTPUTS:
The table can be displayed in three formats:
1. Portfolio Index Title: displays the index name at the top, and at the bottom, it shows the index value, along with the chart timeframe, e.g., daily change in points and percentage.
2. Specifications: displays the essential information on portfolio performance, including the investment date range, total deposits, free cash, returns, and assets.
3. Holdings: a list of the holding securities inside a table that contains the ticker, last price, entry price, return percentage of the portfolio's total deposits, and latest weighted percentage of the portfolio. Additionally, a tooltip appears when the user passes the cursor over a ticker's cell, showing brief information about the company, such as the company's name, exchange market, country, sector, and industry.
4. Indication of New Deposit: An indication of a new deposit added to the portfolio for additional purchasing.
5. Chart: The portfolio's historical movements can be visualized in a plot, displayed as a bar chart, candlestick chart, or line chart, depending on the preferred format, as shown below.
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▋ INDICATOR SETTINGS:
Section(1): Table Settings
(1) Naming the index.
(2) Table location on the chart and cell size.
(3) Sorting Holdings Table. By securities’ {Return(%) Portfolio, Weight(%) Portfolio, or Ticker Alphabetical} order.
(4) Choose the type of index: {Assets, Return, or Return (%)}, and the plot type for the portfolio index: {Candle, Bar, or Line}.
(5) Positive/Negative colors.
(6) Table Colors (Title, Cell, and Text).
(7) To show/hide any of selected indicator’s components.
Section(2): Recurring Deposit Settings
(1) From DateTime of starting the investment.
(2) To DateTime of ending the investment
(3) The amount of recurring deposit into portfolio and currency.
(4) The frequency of recurring deposits into the portfolio {Weekly, 2-Weeks, Monthly, Quarterly, Yearly}
(5) The Depositing Model:
● Fixed: The amount for recurring deposits remains constant throughout the entire investment period.
● Increased %: The recurring deposit amount increases at the selected frequency and percentage throughout the entire investment period.
(5B) If the user selects “ Depositing Model: Increased % ”, specify the growth model (linear or exponential) and define the rate of increase.
Section(3): Portfolio Holdings
(1) Enable a ticker in the investment portfolio.
(2) The selected deposit frequency weight for a ticker. For example, if the monthly deposit is $1,000 and the selected weight for XYZ stock is 30%, $300 will be used to purchase shares of XYZ stock.
(3) Select up to 6 tickers that the investor is interested in for long-term investment.
Please let me know if you have any questions
DCA Order Info PlannerDescription :
This script is a Dollar-Cost Averaging (DCA) order planner designed for SPOT, LONG, and SHORT markets. It automatically calculates the optimal price levels for your orders based on configurable parameters, while also considering leverage and liquidation price.
🔹 Key Features:
1. Automatic Order Planning:
- The script calculates price levels for your orders based on an adjustable scaling coefficient (default: 1.5).
- You can set the percentage interval between each order (default: 2%).
- Displays the number of units to buy/sell at each level.
2.Leverage Management:
- Integrates a configurable leverage and computes the liquidation price for LONG and SHORT positions.
3.Clear Visual Display:
- Markers on the chart indicating order levels with customizable labels.
- A summary table shows price levels and corresponding quantities.
- Visualizes Stop Loss and Take Profit levels if defined.
4.Automatic Alerts:
- Sends alerts when the price reaches an order level.
🔹 Customizable Parameters:
- Starting Price: Initial price for calculating orders.
- Budget: Total budget for DCA orders.
- Leverage: Multiplier for LONG/SHORT positions.
- Scaling Coefficient: Adjusts the spacing between order levels.
- Maximum DCA Levels: Limits the number of generated orders.
🔹 How to Use:
1. Configure the parameters according to your strategy.
2. The script displays order levels and quantities on the chart.
3. Use the summary table to manually input orders on your favorite trading platform.
This script is particularly useful in volatile market conditions to average your entry or exit price and manage risk effectively.
Overnight High/LowThe script identifies the Overnight High (the highest price) and Overnight Low (the lowest price) for a trading instrument during a specified overnight session. It then plots these levels on the chart for reference in subsequent trading sessions.
Key Features:
Time Settings:
The script defines the start (startHour) and end (endHour + endMinute) times for the overnight session.
The session spans across two calendar days, such as 5:00 PM (17:00) to 9:30 AM (09:30).
Tracking High and Low:
During the overnight session, the script dynamically tracks:
Overnight High: The highest price reached during the session.
Overnight Low: The lowest price reached during the session.
Reset Mechanism:
After the overnight session ends (at the specified end time), the script resets the overnightHigh and overnightLow variables, preparing for the next session.
Visual Representation:
The script uses horizontal dotted lines to plot:
A green line for the Overnight High.
A red line for the Overnight Low.
These lines extend to the right of the chart, providing visual reference points for traders.
How It Works:
Session Detection:
The script checks whether the current time falls within the overnight session:
If the hour is greater than or equal to the start hour (e.g., 17:00).
Or if the hour is less than or equal to the end hour (e.g., 09:30), considering the next day.
The end minute (e.g., 30 minutes past the hour) is also considered for precision.
High and Low Calculation:
During the overnight session:
If the overnightHigh is not yet defined, it initializes with the current candle's high.
If already defined, it updates by comparing the current candle's high to the existing overnightHigh using the math.max function.
Similarly, overnightLow is initialized or updated using the math.min function.
Post-Session Reset:
After the session ends, the script clears the overnightHigh and overnightLow variables by setting them to na (not available).
Line Drawing:
The script draws horizontal dotted lines for the Overnight High and Low during and after the session.
The lines extend indefinitely to the right of the chart.
Benefits:
Visual Aid: Helps traders quickly identify overnight support and resistance levels, which are critical for intraday trading.
Automation: Removes the need for manually plotting these levels each day.
Customizable: Time settings can be adjusted to match different markets or trading strategies.
This script is ideal for traders who use the overnight range as part of their analysis for breakouts, reversals, or trend continuation strategies.
IU Opening range Breakout StrategyIU Opening Range Breakout Strategy
This Pine Script strategy is designed to capitalize on the breakout of the opening range, which is a popular trading approach. The strategy identifies the high and low prices of the opening session and takes trades based on price crossing these levels, with built-in risk management and trade limits for intraday trading.
Key Features:
1. Risk Management:
- Risk-to-Reward Ratio (RTR):
Set a customizable risk-to-reward ratio to calculate target prices based on stop-loss levels.
Default: 2:1
- Max Trades in a Day:
Specify the maximum number of trades allowed per day to avoid overtrading.
Default: 2 trades in a day.
- End-of-Day Close:
Automatically closes all open positions at a user-defined session end time to ensure no overnight exposure.
Default: 3:15 PM
2. Opening Range Identification
- Opening Range High and Low:
The script detects the high and low of the first trading session using Pine Script's session functions.
These levels are plotted as visual guides on the chart:
- High: Lime-colored circles.
- Low: Red-colored circles.
3. Trade Entry Logic
- Long Entry:
A long trade is triggered when the price closes above the opening range high.
- Entry condition: Crossover of the price above the opening range high.
-Short Entry:
A short trade is triggered when the price closes below the opening range low.
- Entry condition: Crossunder of the price below the opening range low.
Both entries are conditional on the absence of an existing position.
4. Stop Loss and Take Profit
- Long Position:
- Stop Loss: Previous candle's low.
- Take Profit: Calculated based on the RTR.
- **Short Position:**
- **Stop Loss:** Previous candle's high.
- **Take Profit:** Calculated based on the RTR.
The strategy plots these levels for visual reference:
- Stop Loss: Red dashed lines.
- Take Profit: Green dashed lines.
5. Visual Enhancements
-Trade Level Highlighting:
The script dynamically shades the areas between the entry price and SL/TP levels:
- Red shading for the stop-loss region.
- Green shading for the take-profit region.
- Entry Price Line:
A silver-colored line marks the average entry price for active trades.
How to Use:
1.Input Configuration:
Adjust the Risk-to-Reward ratio, max trades per day, and session end time to suit your trading preferences.
2.Visual Cues:
Use the opening range high/low lines and shading to identify potential breakout opportunities.
3.Execution:
The strategy will automatically enter and exit trades based on the conditions. Review the plotted SL and TP levels to monitor the risk-reward setup.
Important Notes:
- This strategy is designed for intraday trading and works best in markets with high volatility during the opening session.
- Backtest the strategy on your preferred market and timeframe to ensure compatibility.
- Proper risk management and position sizing are essential when using this strategy in live markets.
ATR% multiple historyThe average true range (ATR) is a technical analysis indicator introduced by market technician J. Welles Wilder Jr. in his book New Concepts in Technical Trading Systems. It measures market volatility by decomposing the entire range of an asset's price for that period.
The true range is calculated as the greatest of the following: the current high minus the current low; the absolute value of the current high minus the previous close; and the absolute value of the current low minus the previous close.
The ATR is then a moving average, generally using 14 days, of the true ranges. Therefore, the parameter "Length" in this indicator is set to 14 by default.
This indicator offers three "Smoothing" techniques: RMA, SMA, and EMA, to calculate ATR. RMA is set as the default.
ATR% is calculated by dividing the ATR by the close of the latest bar.
The ATR% multiple builds on ATR%, serving as a measurable gauge of price extension from 50-MA. It is calculated by dividing the distance between the price and the 50-MA by ATR%. Users can change how the distance between the price and the 50-MA is calculated by switching the "Price" parameter among the high, close, and open of the bar.
Each security has a historical ATR% multiple at which it tends to retrace. This is not necessarily a "short" signal. Instead, it can be used as a signal to sell further into strength or avoid initiating new/additional entries.
ATR% multiples from the 50-MA can also be used as a tool for monitoring market indices, assessing technical headwinds versus tailwinds, and determining whether to take on risk or hold positions and wait.
This indicator can show the real-time ATR% multiple from the 50-MA as well as historical data. As shown in the chart above, SPY usually pulls back at over a 5X ATR% multiple in its history, so new exposures can be avoided at that time.
There are five horizontal lines in this indicator, with values of 0, 4, 6, 8, and 10. These five lines can be hidden, and their colors and line widths can be customized. When the ATR% multiple drops below zero, the line's color turns red.
Asset Correlation CheckThis indicator evaluates how your current chart symbol interacts with key markets such as stock indices NASDAQ:NDX SP:SPX AMEX:IWM XETR:DAX PEPPERSTONE:CN50 , commodities CAPITALCOM:GOLD CAPITALCOM:SILVER , bonds NASDAQ:TLT NASDAQ:SHY , and cryptocurrencies BINANCE:BTCUSD , and displays the results in a compact, interactive table. It allows you to adjust the analysis period and select one of three correlation calculation methods (Index, Relative, and Beta) to gain different perspectives on the relationships between assets.
Index Correlation
Advantages: Provides a classic statistical correlation value, making it easy to understand overall directional alignment.
Drawbacks: Less reliable for highly volatile or short-term conditions, as temporary spikes can distort the correlation.
When to use: Ideal if you want a clear overview of whether two markets generally move together, for example to assess diversification effects.
Relative Correlation
Advantages: Focuses on percentage changes rather than absolute prices, offering a more dynamic view of short-term shifts.
Drawbacks: More prone to noise due to emphasizing daily or intra-period fluctuations.
When to use: Useful for timing-sensitive strategies, helping you quickly identify if one asset consistently outpaces or lags another in the short run.
Beta Correlation
Advantages: Examines how strongly one asset responds to changes in another, factoring in volatility and sensitivity, helpful for risk profiling.
Drawbacks: More abstract since it does not convey simple directional similarity but how intensely an asset reacts to market movements.
When to use: Ideal if you need to understand how a security may amplify or dampen broader market-level shifts, aiding in portfolio risk management.
Additionally, a Bull-Market Filter narrows the analysis to upward-trending phases, potentially delivering more meaningful insights. The indicator also computes average correlation values over your selected period, so you are not misled by brief fluctuations. It shows the percentage of positive versus negative readings to reveal if markets generally move in tandem or counter to each other.
For stock pickers, this tool is particularly valuable. It helps determine whether individual equities follow broader market forces, move with specific sectors, or behave independently. With this knowledge, you can refine stock selection, balance sector exposures, and seek opportunities that complement existing positions.
The indicator also facilitates the detection of patterns and anomalies, enabling early recognition of shifts in sentiment or new trend impulses. By visualizing how benchmarks, commodities, bonds, and digital assets relate, you gain deeper insight into key drivers that influence your investments.
Regarding rapid changes in correlation, keep in mind that correlation can frequently flip between positive and negative. Such volatility can create confusion if you rely on single readings. One moment, two assets may seem perfectly aligned; the next, they diverge. This does not necessarily indicate a lack of an underlying pattern; short-term factors can distort the picture. By looking at averages and the frequency of positive and negative occurrences, you confirm whether a correlation trend is genuine or simply a result of temporary noise. In other words, these additional metrics ensure that short-lived swings do not overshadow the true, longer-term relationship between the assets.
In essence, this indicator condenses complex intermarket analysis into a practical resource. By leveraging its insights, you can make data-driven decisions, adapt strategies to evolving market conditions, and lay a stronger foundation for long-term trading success.
Custom Sign [Alert + Marker]Custom Sign
An indicator that detects crossovers between two values and displays them with customizable markers and colors on your TradingView chart.
Key Features
Detection of crossover, crossunder, and cross (both) events
Two display modes: Oscillator and Indicator
Customizable markers and colors
Bar-close alerts
Settings
Source Settings
Source 1: Select the first value to compare
Cross Type: Select cross type (⏫up, ⏬down, 🔀both)
Source 2: Select the second value to compare
Oscillator Side
Use Unified Signal: Toggle unified marker
Unified: Shape for unified marker
CrossOver: Marker for upward cross
CrossUnder: Marker for downward cross
Location: Marker position (Top/Bottom/Invisible)
Indicator Side
Use Unified Signal: Toggle unified marker
Unified: Shape for unified marker
CrossOver: Marker for upward cross
CrossUnder: Marker for downward cross
Location: Marker position (Auto/Top/Bottom/AboveBar/BelowBar/Invisible)
Color Settings
Oscillator
* Use Unified Color: Toggle single color mode
* Unified: Color for unified mode
* CrossOver: Color for upward cross
* CrossUnder: Color for downward cross
Indicator
* Use Unified Color: Toggle single color mode
* Unified: Color for unified mode
* CrossOver: Color for upward cross
* CrossUnder: Color for downward cross
Alert Settings
Alert Message: Customize alert message
Notes
Oscillator and Indicator sides can be configured independently
Different markers and colors can be used for each side
Alerts trigger once per bar at close
Price Delivery Bias @MaxMaserati Price Delivery Bias (PDB) Indicator @ MaxMaserati
The Price Delivery Bias (PDB) indicator is a powerful tool designed to identify and track market structure shifts through price action analysis. It helps traders identify potential trend changes and continuation patterns by monitoring price delivery sequences.
Key Features:
- Automatically detects and labels Change of Delivery Long (CDL) and Change of Delivery Short (CDS) points
- Tracks subsequent Delivery sequences (LD1, LD2, LD3... for longs; SD1, SD2, SD3... for shorts)
- Dynamic support and resistance lines for active buyers and sellers
- Real-time bias status display with delivery count
- Customizable colors and display options
How It Works:
The indicator analyzes price action using fractal patterns to identify significant structural points where the market bias changes or continues. When price breaks above a key level, it marks a CDL (Change of Delivery Long), followed by subsequent long deliveries (LD1, LD2, etc.). Similarly, breaks below key levels are marked as CDS (Change of Delivery Short), followed by short deliveries (SD1, SD2, etc.).
Use Cases:
- Trend Direction: Identify potential trend changes through CDL and CDS signals
- Trend Strength: Monitor delivery sequences (LD/SD count) to gauge trend strength
- Support/Resistance: Track active buyer and seller levels
- Trade Management: Use delivery sequences for managing entries, stops, and targets
Customization Options:
- Adjust the look back period for structure detection
- Customize colors for long and short bias signals
- Toggle label visibility for CDL/CDS and delivery sequences
- Modify text size for better visibility
- Show/hide buyer and seller lines
- Customize table position and appearance
Settings Guide:
1. Length: Determines the look back period for structure detection (default: 5)
2. CDL/CDS Colors: Set colors for bullish and bearish signals
3. Label Controls: Toggle visibility of CDL/CDS and delivery labels
4. Text Size: Choose between Tiny, Small, and Normal for label text
5. Buyer/Seller Lines: Toggle and customize dashed lines showing active levels
6. Bias Table: Configure position and visibility of the status table
#### Pro Tips:
- Use the delivery count to gauge trend strength - higher counts often indicate stronger trends
- Watch for bias changes (CDL/CDS) after extended delivery sequences
- Combine with volume and momentum indicators for confirmation
- Use buyer/seller lines as dynamic support/resistance levels
- Monitor label sequences for potential exhaustion points
#### Notes:
- The indicator works best on higher timeframes (1H and above)
- Signals are more reliable in trending markets
- Multiple delivery sequences often indicate strong trend continuations
- Consider using with other indicators for confirmation
This indicator is ideal for both trend traders and swing traders who want to understand market structure and bias through price action analysis. It provides clear visual cues for potential trend changes and continuation patterns while offering extensive customization options to suit different trading styles.
Realistic Position Sizing Calculator @MaxMaseratiA professional position sizing calculator designed for futures traders who want to trade safely and manage risk effectively. This tool helps you determine exactly how many contracts you can trade based on your capital.
🎯 Main Features:
• Real-time position size calculations for 8 major futures contracts:
- E-mini: ES, NQ, YM, RTY
- Micro E-mini: MES, MNQ, MYM, M2K
• Smart Risk Management:
- Automatic safe lot size calculations
- Daily/Weekly/Bi-weekly/Monthly risk tracking
- Built-in margin safety buffer
- Stop loss point value calculator
- Risk percentage controls (0.01% to 10%)
• Advanced Capital Protection:
- Intraday vs. overnight margin calculations
- Conservative position sizing recommendations
- Real-time margin usage warnings
- Visual risk status indicators (Safe/Caution/High Risk)
• Flexible Settings:
- Adjustable capital amount
- Customizable risk periods
- Point-based stop loss inputs
- Option to use specific trading amounts
Perfect for both new and experienced futures traders who want to:
✓ Avoid overtrading
✓ Protect their capital
✓ Make informed position sizing decisions
✓ Manage multiple contract types safely
The indicator displays all calculations in an easy-to-read table, helping you make quick, safe trading decisions while keeping your risk in check.
Created by @MaxMaserati
Candle Countdown Timer @MaxMaserati
Candle Countdown Timer is a professional-grade time management tool designed for precision traders who need to track multiple timeframes simultaneously. This versatile indicator combines market hours monitoring, multi-timeframe tracking, and visual alerts in one clean interface.
Key Features:
• Custom Multi-Timeframe Display
- Track up to 5 custom timeframes simultaneously
- Supports timeframes from 15 seconds to 1 month
- Standardized format (S15, M5, H1, D1, 1M etc.)
- Configurable default timeframe highlighting
⏰ Precision Time Tracking
- Real-time countdown for each timeframe
- Visual warning system (red text) for candle closing
- Synchronized NY and CME time display
- Automatic market status updates
🎯 Market Status Monitoring
- Clear market open/closed status
- Maintenance period alerts
- CME trading hours integration
- Color-coded status indicators
🎨 Customizable Interface
- Adjustable table position (9 positions available)
- Three size options (Tiny, Small, Normal)
- Customizable colors for all elements
- Clean, non-intrusive design
Perfect For:
• Day traders tracking multiple timeframes
• CME futures traders
• Swing traders managing multiple positions
• Anyone needing precise market timing
This indicator helps you:
✓ Never miss a candle close
✓ Maintain awareness of market status
✓ Manage multiple timeframe strategies
✓ Stay synchronized with market hours
Multi TimelinesMulti Timeline Indicator
The Customizable Multi-Line Indicator is a versatile tool designed to help traders mark specific dates and times directly on their charts with visually distinct vertical lines. This indicator provides three fully customizable lines, each equipped with its own unique settings for visibility, color, style, and width. It is ideal for traders who want to highlight key events, track important price levels, or organize their charts around time-based triggers.
Features:
Three Customizable Lines:
Each line can be toggled on or off independently, allowing for a clutter-free chart.
Fully configurable settings for each line:
Date and Time: Specify the exact timestamp for the line placement.
Color: Choose any color to distinguish between the lines.
Line Width: Adjustable line thickness for better visibility.
Line Style: Options include solid, dashed, and dotted lines.
User-Friendly Inputs:
Intuitive input settings enable quick customization without needing to modify the script.
Simple checkboxes to control line visibility.
Clean and Efficient Design:
No labels or annotations clutter the chart.
The indicator ensures all lines are drawn precisely at the specified timestamps.
Lightweight and Optimized:
Designed to run efficiently without slowing down your chart, even with multiple lines.
Use Cases:
Mark Key Events: Highlight earnings dates, news events, or market open/close times.
Track Important Price Levels: Align lines with specific price action triggers for enhanced analysis.
Organize Trading Sessions: Define the start and end of trading sessions with visual markers.
Reminders for Strategy Execution: Use lines as visual reminders for executing trading strategies at predefined times.
How to Use:
Add the indicator to your chart.
Use the input panel to configure each line:
Toggle visibility with the checkbox.
Set the desired timestamp for each line.
Customize the color, style, and width.
Adjust your chart view to align with your analysis.
Compliance with TradingView Guidelines:
This indicator:
Does not include proprietary calculations or intellectual property from other indicators.
Avoids misleading titles or claims of guaranteed performance.
Does not use or reference any external data feeds or signals.
Focuses solely on providing charting tools for visual organization and analysis.
Disclaimer:
This tool is intended for informational purposes only and should not be considered financial advice. Always perform your due diligence and consult a financial advisor before making trading decisions.
linreg-gridbotLinreg-GridBot
>release note version 1<
Introduction
This script is a powerful trading strategy tool designed to help users identify market reversal points and make smarter trading decisions using grid thinking.
Background
Traditional grid/martingale strategies have several drawbacks: inefficient use of capital, premature grid boundaries, and trading at fixed intervals, all of which significantly reduce profitability. Since, there is not a gridbot can trail-stop at each level, stay close with the trend, and do better capital usage, tradalive has created this advanced gridbot to address these issues, and enhance the profitability.
How does it work?
Imagine plotting closes on a graph, where the x-axis represents the time-intervals and the y-axis represents the price. Linear regression would fit a straight line through these points that best represents the trend of the data.
In this script utilize the built-in to find consecutive slopes at each moment, and combine them to a smooth trend line. When turning point censored, an entry is placed right after the next bar. Then the gridbot starts working, the upper limit and lower limit is calculated by built-in , for example 3 ATRs above and under the entry price.
There is a 0.2 trailing stop for each step level. Also, when built-in VWMA is rising, this script uses built-in ROC to find the average change of lookback length, then move the grid upwards accordingly.
Size trading is crucial, in gridbot all-in when beginning the trade is risky, because turning point does not guarantee a reversal market upcoming. As a grid trader, we believe the price is relatively cheap near the lower limit, and the price is relatively expensive near the upper limit. Properly sized orders help prevent overexposure and reduce the potential for significant losses.
Features
Trend Detection: Utilizes linear regression to differentiate between upward and downward trends, displaying them as (orange) trend lines on the chart.
Signal Generation: Provides buy or sell signals at reversal points, helping users trade at optimal times.
Adjustable Parameters: Allows users to customize different indicator parameters to fit various trading strategies.
Backtested Device Parameters (see appendix)
Grid Parameters
🔃: Cyclic Trading
💰: Capital Turnover Ratio (Grid capital difference per level: 0.5 to 2)
⬆️ / ⬇️ Expected Number of Upward and Downward Grids.
The minimum number of grids is three: one level above and below the current price.
The maximum number of grids is seven: three levels above and below the current price.
🧭: Trade Signal: Controls the trading direction, long or short;
📏: Linear regression length value.
⏳⌛Backtest Period: Set the time range for users to analyze the performance of the strategy over different periods.
Analytic Toolbox (upper right corner) :
Usage Instructions
Add this script to your TradingView account.
Apply the script to your chart.
Adjust the parameters to fit your trading needs.
Make trading decisions based on the buy and sell signals.
Manually place orders on your trading platform using the parameters provided.
Enter grid parameters according to the highest and lowest prices.
Fill in the number of grid levels (the number of grids equals the number of upward grids plus the number of downward grids plus one).
Set stop-loss and take-profit values.
Alternatively, use a webhook to connect to your trading platform for automated trading.
Important Notes
This script currently only supports 4-hour and daily charts!
This script relies on historical data for calculations and may not be suitable for all market conditions.
Trading carries risks, so please use this script cautiously for trading decisions.
User has to update the backtest period, or else the strategy might not be seen.
Demostration
Phase one, the orange line is about to turn up.
Phase two, the reversal point is located, and right after the next bar start an entry of gridbot.
Phase Three, the gridbot operates, once level touches, then a 0.2ATR trailing stop is applied on each step.
Phase four, when vwma rises, the grid window follows it by the rate of change of lookback price. If vwma does not move up, then the grid boundaries remain.
Phase five, either side when the current price breaks through the white limits, the gridbot stops. And the trading strategy is done for this round.
3 Timeframe MACD3 Timeframe MACD Indicator
This indicator provides a multi-timeframe visualization of the MACD (Moving Average Convergence Divergence), enabling traders to analyze momentum and trend signals effectively across different timeframes.
Key Features:
Multi-Timeframe Capability:
Timeframe 1: Automatically uses the chart's current timeframe and displays the MACD Histogram along with the MACD line and Signal line.
Timeframe 2: A user-defined timeframe (default: 4 hours) displays both the MACD line and Signal line for trend and crossover analysis.
Timeframe 3: Another user-defined timeframe (default: 1 day) also displays the MACD line and Signal line, with increased line thickness for emphasis.
Dynamic Histogram Plot:
Timeframe 1's histogram is color-coded:
Green shades for positive values (brighter for increasing momentum).
Red shades for negative values (darker for increasing negative momentum).
Customizable MACD Parameters:
Adjustable Fast Length, Slow Length, and Signal Length to tailor the MACD calculation to specific trading styles or assets.
Clear and Distinct Visualizations:
Timeframe 1 includes the MACD Histogram with MACD and Signal lines for a detailed momentum view.
Timeframes 2 and 3 highlight the MACD and Signal lines in distinct colors for easy differentiation.
Use Case:
Ideal for traders seeking to monitor momentum changes (via Histogram) and trend/crossover signals (via MACD and Signal lines) across the current and two higher/lower timeframes.
Enhances decision-making by providing multi-timeframe confluence for trend-following or countertrend strategies.
This indicator is particularly useful for traders looking for a streamlined way to incorporate multi-timeframe analysis into their trading workflow.
Intraday Trend CandlesThe Intraday Trend Candles (ITC) indicator is a Pine Script-based tool designed for traders seeking to visualize market trends effectively. Using a combination of the Look Back Period, a multiplier for true range, and linearly weighted moving averages (LWMA), this indicator calculates dynamic trend limits that adapt to price movements. It identifies key trend shifts by comparing the current price to these dynamic thresholds, resulting in a visually intuitive display of market bias directly on the chart. The indicator is particularly well-suited for intraday trading, as it provides responsive insights tailored to short-term price action.
The ITC plots color-coded candles, highlighting bullish trends in blue and bearish trends in yellow, with gray indicating indecision or trend continuation. This color-coded approach makes it easy to identify reversals and trend dynamics at a glance. Additionally, a trend line is plotted to enhance clarity, signaling whether the price is favoring the upper or lower threshold of the calculated range. With built-in alerts for trend reversals, traders can stay informed about critical market shifts without constantly monitoring the chart. This combination of visual cues and alerts makes the ITC a versatile and powerful tool for traders focusing on momentum and trend-following strategies.
Bar Replay Fix - Smooth Candle Transition for TradingViewThe Bar Replay Fix indicator addresses a known issue in TradingView’s Bar Replay mode, where the last completed candle is incorrectly drawn when switching from a lower timeframe to a higher one. This issue can create confusion during analysis, especially when replaying historical price action.
Key Features:
Accurate Candle Rendering: Ensures that candles are displayed correctly in Bar Replay mode by referencing and plotting the previous candle data.
Customizable Appearance: Configure the candle body, wick, and border colors for bullish, bearish, and doji candles to match your chart theme.
Seamless Integration: Works invisibly in the background to provide a smoother and more reliable replay experience.
Use Cases:
Enhance your backtesting accuracy by eliminating incorrect candle rendering during Bar Replay.
Maintain consistency in candle visualization when transitioning between timeframes in Replay mode.
Disclaimer: This indicator is specifically designed to resolve a visual issue in Bar Replay mode and does not provide any trading signals or analysis recommendations.
Hidden SMT Divergence ICT 01 [TradingFinder] HSMT SMC Technique🔵 Introduction
Hidden SMT Divergence, an advanced concept within the Smart Money Technique (SMT), identifies discrepancies between correlated assets by focusing on their closing prices.
Unlike the standard SMT Divergence, which uses high and low prices for analysis, Hidden SMT Divergence uncovers subtle signals by examining divergences based on the assets' closing values.
These divergences often highlight potential reversals or trend continuations, making this technique a valuable tool for traders aiming to anticipate market movements.
This approach applies across various markets and asset classes, including :
Commodities : CAPITALCOM:GOLD vs. CAPITALCOM:SILVER or BLACKBULL:BRENT vs. BLACKBULL:WTI .
Indices : NASDAQ:NDX vs. TVC:SPX vs. FX:US30 .
FOREX : FX:EURUSD vs. OANDA:GBPUSD vs. TVC:DXY (US Dollar Index).
Cryptocurrencies : BITSTAMP:BTCUSD vs. COINBASE:ETHUSD vs. KUCOIN:SOLUSDT vs. CRYPTOCAP:TOTAL3 .
Volatility Measures : FOREXCOM:XAUUSD vs. TVC:VIX (Volatility Index).
By identifying divergences within these asset groups, traders can gain actionable insights into potential market reversals or shifts in trend direction. Hidden SMT Divergence is particularly effective for pinpointing subtle market signals that traditional methods may overlook.
Bullish Hidden SMT Divergence : This divergence emerges when one asset forms a higher low, while the correlated asset creates a lower low in terms of their closing prices. It often signals weakening downward momentum and a potential reversal to the upside.
Bearish Hidden SMT Divergence : This occurs when one asset establishes a higher high, while the correlated asset forms a lower high based on their closing prices. It typically reflects declining upward momentum and a probable shift to the downside.
🔵 How to Use
The Hidden SMT Divergence indicator provides traders with a systematic approach to identify market reversals or trend continuations through divergences in closing prices between two correlated assets.
🟣 Bullish Hidden SMT Divergence
Bullish Hidden SMT Divergence occurs when the closing price of the primary asset forms a higher low, while the correlated asset creates a lower low. This pattern indicates weakening downward momentum and signals a potential reversal to the upside.
After identifying the divergence, confirm it using additional tools like support levels, volume trends, or indicators such as RSI and MACD. Enter a buy position as the price shows signs of reversal near support zones, ensuring proper risk management by placing a stop-loss below the support level.
Bearish Hidden SMT Divergence
Bearish Hidden SMT Divergence is identified when the closing price of the primary asset forms a higher high, while the correlated asset creates a lower high. This divergence suggests a weakening uptrend and a likely reversal to the downside.
Validate the signal by examining resistance levels, declining volume, or complementary indicators. Consider entering a sell position as the price starts declining from resistance levels, and set a stop-loss above the resistance zone to limit potential losses.
🔵 Setting
Second Symbol : Select the secondary asset to compare with the primary asset. By default, "XAUUSD" (Gold) is used, but it can be customized to any stock, cryptocurrency, or currency pair.
Divergence Fractal Periods : Defines the number of past candles considered for identifying divergences. The default value is 2, but traders can adjust it for greater precision.
Bullish Divergence Line : Displays a dashed line connecting the points of bullish divergence.
Bearish Divergence Line : Shows a similar line for bearish divergence points.
Bullish Divergence Label : Marks areas of bullish divergence with a "+SMT" label.
Bearish Divergence Label : Highlights bearish divergences with a "-SMT" label.
Chart Type : Choose between Line or Candle charts for enhanced visualization.
🔵 Conclusion
Hidden SMT Divergence offers traders a refined method for identifying market reversals by analyzing closing price discrepancies between correlated assets. Its ability to uncover subtle divergences makes it an essential tool for traders who aim to stay ahead of market trends.
By integrating this technique with other technical analysis tools and sound risk management, traders can enhance their decision-making process and capitalize on market opportunities with greater confidence.
Hidden SMT Divergence’s focus on closing prices ensures more precise signals, helping traders refine their strategies across various markets, including Forex, commodities, indices, and cryptocurrencies.
Its open-source nature allows for customization and verification, providing transparency and flexibility to suit diverse trading needs. Hidden SMT Divergence stands as a powerful addition to the arsenal of any trader seeking to unlock hidden opportunities in dynamic financial markets.
Advanced MA and MACD PercentageIntroduction
The "Advanced MA and MACD Percentage" indicator is a powerful and innovative tool designed to help traders analyze financial markets with ease and precision. This indicator combines Moving Averages (MA) with the MACD indicator to assess the market’s overall trend and calculate the percentage of buy and sell signals based on current data.
Features
Multi-Timeframe Analysis:
Allows selecting your preferred timeframe for trend analysis, such as minute, hourly, daily, or weekly charts.
Support for Multiple Moving Average Types:
Offers the option to use either Simple Moving Average (SMA) or Exponential Moving Average (EMA), based on user preference.
Comprehensive MACD Analysis:
Analyzes the relationship between multiple moving averages (e.g., 20/50, 50/100) using MACD to provide deeper insights into market dynamics.
Calculation of Buy and Sell Percentages:
Computes the percentage of indicators signaling buy or sell conditions, providing a clear summary to assist trading decisions.
Intuitive Visual Interface:
Displays buy and sell percentages as two visible lines (green and red) on the chart.
Includes reference lines to clarify the range of percentages (100% to 0%).
How It Works
Moving Averages Calculation:
Calculates moving averages (20, 50, 100, 150, and 200) for the selected timeframe.
MACD Pair Analysis:
Computes the MACD to compare the performance between various moving average pairs, such as (20/50) and (50/100).
Identifying Buy and Sell Signals:
Counts the number of indicators signaling buy (price above MAs or positive MACD histogram).
Converts the count into percentages for both buy and sell signals.
Visual Representation:
Plots buy and sell percentages as clear lines (green for buy, red for sell).
Adds reference lines (100% and 0%) for easier interpretation.
How to Use the Indicator?
Settings:
Choose the type of moving average (SMA or EMA).
Select the timeframe that suits your strategy (e.g., 15 minutes, 1 hour, or daily).
Reading the Results:
If the buy percentage (green line) is above 50%, the overall trend is bullish (buy).
If the sell percentage (red line) is above 50%, the overall trend is bearish (sell).
Integrating Into Your Strategy:
Combine it with other indicators to confirm entry and exit signals.
Use it to quickly understand the market’s overall trend without needing complex manual analysis.
Benefits of the Indicator
Simplified Analysis: Provides a straightforward summary of the market's overall trend.
Adaptable to All Timeframes: Works perfectly on all timeframes.
Customizable: Allows users to adjust settings according to their needs.
Important Notes
This indicator does not provide direct buy or sell signals. Instead, it offers a summary of the market’s condition based on a combination of indicators.
It is recommended to use it alongside other technical analysis tools for precise trading signals.
Conclusion
The "Advanced MA and MACD Percentage" indicator is an ideal tool for traders who want to analyze the market using a combination of Moving Averages and MACD. It gives you a comprehensive overview of the overall trend, helping you make informed and quick trading decisions. Try it now and see the difference!
MES Position Sizing EstimatorDescription and Use:
Here is an indicator which aims to help all Micro-ES futures traders who struggle with risk management! I created this indicator designed as a general guideline to help short term traders (designed for 1 minute candles) determine how many contracts to trade on the MES for their desired profit target.
To use the indicator, simply go to MES on the 1 minute timeframe, apply the indicator, and enter your Holding Period (how long you want to have your position open for), Value Per Tick
(usually 1.25 for MES since one point is $5) and your target PnL for the trade in the inputs tab.
It will then show in a table the recommended position sizing, as well as the estimated price change for your holding period. Additionally, there are two plotted lines also showing the position sizing and estimated price change historically.
How the indicator works
On the technical level, I made calculations for this indicator using Python. I downloaded 82 days of 1 minute OHLC data from TradingView, and then ran regression (log-transformed linear regression specifically) to calculate how the average price change in MES futures scales with the amount of time a position is held for, and then ran these regressions for every hour of the day. I then copied the equations from those regressions into Pinescript, and used the assumption that:
position size = target PnL / (estimated price change for time * tick value)
Therefore, Choosing the number of contracts to trade position sizing for Micro E-mini S&P 500 Futures (MES) based on time of day, holding period, and tick value. This tool leverages historical volatility patterns and log-transformed linear regression models to provide precise recommendations tailored to your trading strategy.
If you want to check out how the regression code worked in python, it is all open source and available on my Github repository for it .
Notes:
The script assumes a log-normal distribution of price movements and is intended as an educational tool to aid in risk management.
It is not a standalone trading system and should be used in conjunction with other trading strategies and risk assessments.
Past performance is not indicative of future results, and traders should exercise caution and adjust their strategies based on personal risk tolerance.
This script is open-source and available for use and modification by the TradingView community. It aims to provide a valuable resource for traders seeking to enhance their risk management practices through data-driven insights.
LETF Leveraged Edge Strategy v1.5Overview
The strategy is based on Stochastics to detect trends and then makes Buys and Sell based on custom entry and exit criteria as described below in the Execution Logic Rules section. It will NOT work with standard Stochastics.
This is not a standard Stochastics implementation. It has been customized and modified, and does not match any widely known Stochastics variations (like Fast, Slow, or Full Stochastics) in its smoothing and iterative calculation process with:
• A unique smoothing mechanism.
• Iterative calculations.
• Additional conditional logic for strategy execution.
This strategy is designed to focus on volatile, liquid leveraged ETFs to capture gains equal to or better than Buy and Hold, and mitigate the risk of trading with a goal of reducing drawdown to a lot less than Buy and Hold. It has had successful backtest performance to varying degrees with TQQQ, SOXL, FNGU, TECL, FAS, UPRO, NAIL and SPXL. Results have not been good on other LETFs that have been backtested.
Performance
In this backtest the Net Profit shows to be $4,561 or 45.61%. Considering the initial order size was $1,000 I have to wonder if the Strategy Tester is calculating this correctly. The Strategy Tester Performance Summary shows the Buy and Hold Return at $61,165 or 611.7%. Based on calculating the price of the last shares sold, less the price paid, times the number of initial shares purchased, my math shows the Buy and Hold Gain at $4,572 or about equal with the strategy performance in this case. The Performance Summary also states the strategy had a Max DD of 3.46% which I believe is incorrect. Based on other backtests I’ve done, I believe the strategy drawdown here was closer to 28.4% and the Buy and Hold Drawdown at 82.7%. I manually calculated the Buy and Hold drawdown.
How it Works
The author provides training and support resource materials for this at his website. The strategy execution logic is driven by these rules:
Execution Logic Rules
Buy the LETF When:
BR #1a) The Daily Fast Line (FL) crosses above the Daily Slow Line (SL) and the FL is between the Low (L*) and High (H*) Range set (often referred to as Oversold and Overbought Lines). This can execute (Buy) any trading day of the week.
BR #1b) Re-Buy the next day after any Stop or Take Profit Sell if the Buy Rule condition is true (FL is above SL), if not, remain in cash and wait for the next Buy Signal.
Sell the LETF When:
SR #1a) The Daily Fast Line (FL) crosses below Daily Slow Line (SL) within the Low (L*) and High (H*) Range (often referred to as Oversold and Overbought Lines). “Crossunder Range Exit” This can execute (Sell) any trading day of the week.
SR #1b) If the (FL) crosses Below the SL above the Exit Level*, wait. Only Sell if the FL drops down below the Exit Level* “Crossunder Level Exit” This can execute (Sell) any trading day of the week.
SR #2a) Sell at the open any day the gap-down price is at or below the 1-Day Stop%*, based on previous day’s closing price (Execute on the day it happens.)
SR #2b) Sell intraday any day the price is at or below the 1-Day Stop %*, based on previous day’s closing price (Execute on the day it happens.)
SR #3a) Sell at the open any day the price is at or below the Trailing Stop %*, based on highest intraday price since Buy date (Execute on the day it happens.)
SR #3b) Sell intraday any day the price is at or below the Trailing Stop%*, based on highest intraday price since Buy date (Execute on the day it happens.)
SR #4) Sell any day when the opening price exceeds, or intraday price meets the Profit Target % price* (Execute on the day it happens.)
SR #5) After each Sell go to Rule BR #1b to determine if a Re-Buy should occur the next day, or stay in cash until next Buy Signal
Settings:
Properties Tab – Initial Capital has been set to $10,000 and order size 10% of Equity, 0.1% commission and 3 Ticks for slippage. Net order size is $1,000
Input Tab:
Stochastic
Timeframe is selected to Daily or Weekly based on preference. Daily has more trades, but on average higher profitability.
Type: Proprietary (best selection for most LETFs, but a few will work better with the Full selection
%k Length 20, %K Smoothing 14, %D Smoothing (many LETFs work better with a specific Stoch setting, often each different) A List of these is provided for your starting point.
Trade Settings
Direction: Longs (This strategy only works on the Long side)
Stop Type: Trailing is recommended, but Fixed is an option.
Stop % (based on user risk tolerance)
PD Stop % (Suggest start at 5%. Based on volatility of LETF and is a stop percentage from prior day’s close. Designed to protect against sudden market volatility. Will need to balance between strategy performance and user risk tolerance)
Profit Target: User preference. (I can help with suggestions based on historical performance)
Entry/Exit Conditions
Enter on Tie: Default Checked – if a Fast line crosses a Slow line for a Buy signal, but doesn’t do so in the range set, this will trigger if it crosses at a tie.
Renter – Default Checked – If stopped out of a position, this tells the strategy to re-buy the position the next day if the conditions are still positive.
Exit Level: This is a exit level for a Fast cross below a Slow line that takes place above the Sell Range, but only happens if the Fast continues down to the level set. These usually don’t happen often, but can have a significant impact on performance. Unfortunately, it’s a trial and error process starting with 90 and working down to see if there’s any positive impact.
Trade Range
Buy Range: Start at typical 20 to 80. Expand the low end down first to check on performance impact. Normally a wide buying range is better for performance.
Sell Range: Start at 20 to 80 and tighten gradually to see performance impact. In some cases a very tight sell range does better. I have worked on our primary LETFs for many months to determine ranges for each that typically produce better results.
External Indicator: Some additional indicators have a positive impact on the strategy performance by increasing P/l, reducing drawdown and reducing the number of trades. This is not always the case and each LETF and time period for the LETF will have a bearing on whether the secondary indicator will help or not. Two that have helped are the MACD Histogram, and the Sloe-Velocity Indicator by Kamleshkumar43. Sometimes a couple of different indicators will have a positive impact, then it’s a personal preference which you pick to use with the strategy.
Since this strategy is focused on a very narrow selection of liquid LETFs, I have a lot of experience experimenting with the settings for the primary ones and can suggest things that will help. Additional training on the rules, working with the settings, and mitigating some of the negative trades during choppy markets is available at the website.
Chart
The strategy can be selected to use either a Daily or Weekly version of stochastic. This is important because the characteristics are different while still generating very good gains and minimal drawdowns. Generally, the daily stochastic will have a greater number of, and certainly more frequent, trades than the weekly stochastic. However, on average the daily version of the stochastic will generates greater profitability.
The Settings tabs have tooltip icons that will assist in inputting values that correspond to the written rules for the strategy, and some include specific rule detail.
Buying
The strategy generates Buy signals with the Fast line crossing over the Slow line within a “Buy Range” which is adjusted based on volatility of the leveraged ETF. This is unique in that a default is set for these entries to occur if the values are tied and doesn’t need to be within the high and low range if that occurs. The trader can select in the strategy for this to occur the same day, if he’s selected a Daily Stochastic timeframe, or at the end of the trading week if he’s selected a Weekly stochastic timeframe. The volatility of a leveraged ETF will sometimes cause a shake-out exit, a trailing stop can be hit, or there can be an exit based on taking a profit. A big part of the timing challenge was how to handle these. The strategy normally (set as a default) will immediately re-buy the next day only if the original buy conditions are still true. This helps capture gains when conditions are still favorable but keeps the trader out when they’re not.
Selling
Exits are handled in several ways. The strategy will exit if there is a fast line cross below a slow line within the “range”. The range is adjusted based on volatility of the leveraged ETF. The exit occurs at the close of the day if the trader has selected to use a Daily stochastic setting. The exit will occur at the end of the trading week if the trader has chosen a weekly stochastic strategy. The trader will set a level based on the instrument and volatility for another exit type. The level will sometimes coincide with the range exit high level but does not need to. If a fast line crosses down through a slow line above the level set, and then comes down to that level, the strategy will exit the position.
Another unique aspect of the strategy is the PD Stop setting. This is short for “Prior Day”, Rather than a normal stop based on the price paid for a position, the PD Stop is based on a percentage drop from the previous day’s closing price. This helps account for the volatility of the leveraged ETF and will cause an exit quickly if there’s a market, or index moving event. This helps capture gains and reduce risk should there be continued pullback.
Exits will also occur based on setting a trailing stop level and profit taking level. These are adjusted based on the leveraged ETFs volatility and historical performance.
Limitations
Choppy, or sideways markets are the most prone to poor performance and potential for being stopped out multiple times. If stopped out two consecutive times, make sure you’re monitoring market health and there are clear signs of a new uptrend such as a 10D and 21D MA in proper alignment and moving up. If you get a Buy signal from the strategy and you’re not confident yet about market and price direction then it’s fine to wait a day, or several days, to enter after the Buy signal when you have greater confidence about market direction. The author can help with a short list of tactical rules developed for these sideways or choppy markets.
This strategy has proven successful backtest results with a very limited set of LETFs as discussed earlier. The author does not know if it will prove successful with any others, or other types of ETFs such as 2X or plain ETFs. A lot more testing needs to be done.
The strategy buys and sells , excluding stops or take profit, at the market close. It can be very challenging to enter an order at market close.
Disclaimer
Please remember that past performance may not be indicative of future results.
Due to various factors, including changing market conditions, the strategy may no longer perform as well as in historical backtesting. This post and the script do not provide any financial advice and are for educational and entertainment purposes only.
