CNagda Anchor2EntryCNagda Anchor2Entry Pine Script v6 overlay indicator pulls higher-timeframe (HTF) signal events to define anchor high/low levels and then projects visual entry labels on the lower-timeframe (LTF). It also draws auto-oriented Fibonacci retracement/extension levels for context, but it does not execute orders, stops, or targets—only visual guidance.
Inputs
Key inputs include Lookback Length for HTF scanning and a Signal Timeframe used with request.security to import HTF events onto the active chart.
Entry behavior can be set to “Confirm only” or “Wait candle,” trade side can be restricted to Buy/Sell/Both, and individual strategies (Buy WAIT/S1; Sell REV/S1/S2/S3) can be toggled.
HTF logic
The script defines WAIT/BUY setup and confirmation, SELL reversal on breaking the WAIT BUY low, and several volume/candle-based patterns (Sell S1/S2/S3, Buy S1).
It captures the associated highs/lows at those events with ta.valuewhen and imports them via request.security to form anchors (anc_hi/anc_lo) and “new trigger” booleans that gate label creation on the LTF.
Flip entries
When enabled, “Flip entries” generate contrarian labels based on breaking or confirming HTF anchors: crossing above anc_hi can trigger a flip-to-sell label, and crossing below anc_lo can trigger a flip-to-buy label.
The flip mode supports Immediate (on cross) or Confirm (on sustained break) to control how strict the trigger is.
Fibonacci drawing
User-specified Fib levels are parsed from a string, safely converted to floats, and drawn as dotted horizontal lines only when they fall inside an approximate visible viewport. Orientation (up or down) is decided automatically from pending signal direction and a simple context score (candle bias, trend, and price vs. mid), with efficient redraw/clear guards to avoid clutter.
Dynamic anchors
If HTF anchors are missing or too far from current price (checked with an ATR-based threshold), the script falls back to local swing highs/lows to keep the reference range relevant. This dynamic switch helps Fib levels and labels remain close to current market structure without manual intervention.
Signal labels
Labels are created only on confirmed bars to avoid repainting noise, with one “latest” label kept by deleting the previous one. The script places BUY/SELL labels for WAIT/CONFIRM, direct HTF patterns (Buy S1, Sell S1/S2/S3), and contrarian flip events, offset slightly from highs/lows with clear coloring and configurable sizes.
Visual context
Bars are softly colored (lime tint for bullish, orange tint for bearish) for quick context, and everything renders as an overlay on the price chart. Fib labels include a Δ readout (distance from current close), and line extension length, label sizes, and viewport padding are adjustable.
How to use
Set the Signal Timeframe and Lookback Length to establish which HTF structures and ranges will drive the anchors and entry conditions. Choose entry flow (Wait vs Confirm), enable Flip if contrarian triggers are desired, select the trade side, toggle strategies, and customize Fibonacci levels plus dynamic-anchor fallback for practical on-chart guidance.
Notes
This is a visual decision-support tool; it does not place trades, stops, or targets and should be validated on charts before live use. It is written for Pine Script v6 and relies heavily on request.security for HTF-to-LTF transfer of signals and anchors.
Systemtrader
Trendline Breaks with Multi Fibonacci Supertrend StrategyTMFS Strategy: Advanced Trendline Breakouts with Multi-Fibonacci Supertrend
Elevate your algorithmic trading with institutional-grade signal confluence
Strategy Genesis & Evolution
This advanced trading system represents the culmination of a personal research journey, evolving from my custom " Multi Fibonacci Supertrend with Signals " indicator into a comprehensive trading strategy. Built upon the exceptional trendline detection methodology pioneered by LuxAlgo in their " Trendlines with Breaks " indicator, I've engineered a systematic framework that integrates multiple technical factors into a cohesive trading system.
Core Fibonacci Principles
At the heart of this strategy lies the Fibonacci sequence application to volatility measurement:
// Fibonacci-based factors for multiple Supertrend calculations
factor1 = input.float(0.618, 'Factor 1 (Weak/Fibonacci)', minval = 0.01, step = 0.01)
factor2 = input.float(1.618, 'Factor 2 (Medium/Golden Ratio)', minval = 0.01, step = 0.01)
factor3 = input.float(2.618, 'Factor 3 (Strong/Extended Fib)', minval = 0.01, step = 0.01)
These precise Fibonacci ratios create a dynamic volatility envelope that adapts to changing market conditions while maintaining mathematical harmony with natural price movements.
Dynamic Trendline Detection
The strategy incorporates LuxAlgo's pioneering approach to trendline detection:
// Pivotal swing detection (inspired by LuxAlgo)
pivot_high = ta.pivothigh(swing_length, swing_length)
pivot_low = ta.pivotlow(swing_length, swing_length)
// Dynamic slope calculation using ATR
slope = atr_value / swing_length * atr_multiplier
// Update trendlines based on pivot detection
if bool(pivot_high)
upper_slope := slope
upper_trendline := pivot_high
else
upper_trendline := nz(upper_trendline) - nz(upper_slope)
This adaptive trendline approach automatically identifies key structural market boundaries, adjusting in real-time to evolving chart patterns.
Breakout State Management
The strategy implements sophisticated state tracking for breakout detection:
// Track breakouts with state variables
var int upper_breakout_state = 0
var int lower_breakout_state = 0
// Update breakout state when price crosses trendlines
upper_breakout_state := bool(pivot_high) ? 0 : close > upper_trendline ? 1 : upper_breakout_state
lower_breakout_state := bool(pivot_low) ? 0 : close < lower_trendline ? 1 : lower_breakout_state
// Detect new breakouts (state transitions)
bool new_upper_breakout = upper_breakout_state > upper_breakout_state
bool new_lower_breakout = lower_breakout_state > lower_breakout_state
This state-based approach enables precise identification of the exact moment when price breaks through a significant trendline.
Multi-Factor Signal Confluence
Entry signals require confirmation from multiple technical factors:
// Define entry conditions with multi-factor confluence
long_entry_condition = enable_long_positions and
upper_breakout_state > upper_breakout_state and // New trendline breakout
di_plus > di_minus and // Bullish DMI confirmation
close > smoothed_trend // Price above Supertrend envelope
// Execute trades only with full confirmation
if long_entry_condition
strategy.entry('L', strategy.long, comment = "LONG")
This strict requirement for confluence significantly reduces false signals and improves the quality of trade entries.
Advanced Risk Management
The strategy includes sophisticated risk controls with multiple methodologies:
// Calculate stop loss based on selected method
get_long_stop_loss_price(base_price) =>
switch stop_loss_method
'PERC' => base_price * (1 - long_stop_loss_percent)
'ATR' => base_price - long_stop_loss_atr_multiplier * entry_atr
'RR' => base_price - (get_long_take_profit_price() - base_price) / long_risk_reward_ratio
=> na
// Implement trailing functionality
strategy.exit(
id = 'Long Take Profit / Stop Loss',
from_entry = 'L',
qty_percent = take_profit_quantity_percent,
limit = trailing_take_profit_enabled ? na : long_take_profit_price,
stop = long_stop_loss_price,
trail_price = trailing_take_profit_enabled ? long_take_profit_price : na,
trail_offset = trailing_take_profit_enabled ? long_trailing_tp_step_ticks : na,
comment = "TP/SL Triggered"
)
This flexible approach adapts to varying market conditions while providing comprehensive downside protection.
Performance Characteristics
Rigorous backtesting demonstrates exceptional capital appreciation potential with impressive risk-adjusted metrics:
Remarkable total return profile (1,517%+)
Strong Sortino ratio (3.691) indicating superior downside risk control
Profit factor of 1.924 across all trades (2.153 for long positions)
Win rate exceeding 35% with balanced distribution across varied market conditions
Institutional Considerations
The strategy architecture addresses execution complexities faced by institutional participants with temporal filtering and date-range capabilities:
// Time Filter settings with flexible timezone support
import jason5480/time_filters/5 as time_filter
src_timezone = input.string(defval = 'Exchange', title = 'Source Timezone')
dst_timezone = input.string(defval = 'Exchange', title = 'Destination Timezone')
// Date range filtering for precise execution windows
use_from_date = input.bool(defval = true, title = 'Enable Start Date')
from_date = input.time(defval = timestamp('01 Jan 2022 00:00'), title = 'Start Date')
// Validate trading permission based on temporal constraints
date_filter_approved = time_filter.is_in_date_range(
use_from_date, from_date, use_to_date, to_date, src_timezone, dst_timezone
)
These capabilities enable precise execution timing and market session optimization critical for larger market participants.
Acknowledgments
Special thanks to LuxAlgo for the pioneering work on trendline detection and breakout identification that inspired elements of this strategy. Their innovative approach to technical analysis provided a valuable foundation upon which I could build my Fibonacci-based methodology.
This strategy is shared under the same Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) license as LuxAlgo's original work.
Past performance is not indicative of future results. Conduct thorough analysis before implementing any algorithmic strategy.
