Hazel nut BB Strategy, volume base- lite versionHazel nut BB Strategy, volume base — lite version
Having knowledge and information in financial markets is only useful when a trader operates with a well-defined trading strategy. Trading strategies assist in capital management, profit-taking, and reducing potential losses.
This strategy is built upon the core principle of supply and demand dynamics. Alongside this foundation, one of the widely used technical tools — the Bollinger Bands — is employed to structure a framework for profit management and risk control.
In this strategy, the interaction of these tools is explained in detail. A key point to note is that for calculating buy and sell volumes, a lower timeframe function is used. When applied with a tick-level resolution, this provides the most precise measurement of buyer/seller flows. However, this comes with a limitation of reduced historical depth. Users should be aware of this trade-off: if precise tick-level data is required, shorter timeframes should be considered to extend historical coverage .
The strategy offers multiple configuration options. Nevertheless, it should be treated strictly as a supportive tool rather than a standalone trading system. Decisions must integrate personal analysis and other instruments. For example, in highly volatile assets with narrow ranges, it is recommended to adjust profit-taking and stop-loss percentages to smaller values.
◉ Volume Settings
• Buyer and seller volume (up/down volume) are requested from a lower timeframe, with an option to override the automatic resolution.
• A global lookback period is applied to calculate moving averages and cumulative sums of buy/sell/delta volumes.
• Ratios of buyers/sellers to total volume are derived both on the current bar and across the lookback window.
◉ Bollinger Band
• Bands are computed using configurable moving averages (SMA, EMA, RMA, WMA, VWMA).
• Inputs allow control of length, standard deviation multiplier, and offset.
• The basis, upper, and lower bands are plotted, with a shaded background between them.
◉ Progress & Proximity
• Relative position of the price to the Bollinger basis is expressed as percentages (qPlus/qMinus).
• “Near band” conditions are triggered when price progress toward the upper or lower band exceeds a user-defined threshold (%).
• A signed score (sScore) represents how far the close has moved above or below the basis relative to band width.
◉ Info Table
• Optional compact table summarizing:
• - Upper/lower band margins
• - Buyer/seller volumes with moving averages
• - Delta and cumulative delta
• - Buyer/seller ratios per bar and across the window
• - Money flow values (buy/sell/delta × price) for bar-level and summed periods
• The table is neutral-colored and resizable for different chart layouts.
◉ Zone Event Gate
• Tracks entry into and exit from “near band” zones.
• Arming logic: a side is armed when price enters a band proximity zone.
• Trigger logic: on exit, a trade event is generated if cumulative buyer or seller volume dominates over a configurable window.
◉ Trading Logic
• Orders are placed only on zone-exit events, conditional on volume dominance.
• Position sizing is defined as a fixed percentage of strategy equity.
• Long entries occur when leaving the lower zone with buyer dominance; short entries occur when leaving the upper zone with seller dominance.
◉ Exit Rules
• Open positions are managed by a strict priority sequence:
• 1. Stop-loss (% of entry price)
• 2. Take-profit (% of entry price)
• 3. Opposite-side event (zone exit with dominance in the other direction)
• Stop-loss and take-profit levels are configurable
◉ Notes
• This lite version is intended to demonstrate the interaction of Bollinger Bands and volume-based dominance logic.
• It provides a framework to observe how price reacts at band boundaries under varying buy/sell pressure, and how zone exits can be systematically converted into entry/exit signals.
When configuring this strategy, it is essential to carefully review the settings within the Strategy Tester. Ensure that the chosen parameters and historical data options are correctly aligned with the intended use. Accurate back testing depends on applying proper configurations for historical reference. The figure below illustrates sample result and configuration type.
Takeprofittrader
Triple EMA Trend TP Strategy (Filtered Entries + Dynamic Exit)Overview
The Triple EMA Trend TP Strategy is a robust trend-following approach designed for clear, disciplined entries and exits. It leverages a triple EMA crossover for entry signals, combined with a long‑term SMA trend filter, a fixed take‑profit percentage, and a dynamic dual‑EMA exit mechanism to optimize performance and risk management.
Key Features
Triple EMA Crossover Entry
Detects momentum shifts by waiting for the fast EMA to cross above the slow EMA, signaling bullish momentum buildup.
Trend Filter (SMA)
Ensures trades are only taken when price is above the long-term trend (SMA), filtering out low-probability setups.
Take Profit (TP)
Applies a customizable fixed TP, e.g., defaulting to 9.8%, allowing disciplined profit-taking.
Dual EMA Exit
Uses two EMAs on a separate exit logic—if the short exit EMA undercuts the mid exit EMA, the strategy closes the position.
Adjustable Parameters
All key lengths—including fast, mid, slow entry EMAs, trend SMA, exit EMAs, and TP percentage—are user-configurable to suit different assets and timeframes.
Date Range Control
Users can define a backtest window with start and end dates, preventing misleading performance outside intended periods.
Flexible Position Management
Supports full‑equity position sizing, pyramiding up to 10 entries, and runs every tick for high precision.
Setup & Inputs
fastLen: Entry Fast EMA
midLen: Entry Mid EMA
slowLen: Entry Slow EMA
trendLen: Trend Filter SMA
tpPercent: Take Profit Percentage
exitFastLen: Exit Fast EMA
exitMidLen: Exit Mid EMA
startDate / endDate: Backtest time range
Why This Strategy Stands Out
This strategy marries classic trend-following principles with modern risk-control tactics, making it both intuitive and advanced. It balances aggressive entry signals with safety checks via trend validation and layered exit logic. The inclusion of a TP ensures profits are locked in, while the dual EMA exit adds adaptive flexibility to close positions when momentum fades.
How to Use & Customize
Configure Inputs
Adjust EMAs, trend length, and TP percentage to fit your asset and timeframe. For example, shorter EMAs suit intraday trading; longer ones work well for swing strategies.
Set Backtest Range
Use the start/end date fields to limit your testing to the most relevant data, reducing noise from irrelevant market periods.
Backtest & Optimize
Review the Strategy Tester’s performance metrics—Equity curve, drawdown, profit factor, trade list—to assess effectiveness.
Fine‑Tune
Tweak TP, EMAs, or trend length to optimize drawdowns, win rate, or return profile.
