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Filtered Bollinger Bands By @Tradingade

Script from: TradingView

Swing

Price action

Mean reversion

Reversal

Filtered Bollinger Bands is a strategy seeking reversal points via Bollinger Bands and a Trend filter. For long entries, it requires price to extend beyond the lower band and then closes above it. Shorts are the inverse. A key element is the filter based on the prior day's high or low extremes. Exits hinge on price crossing the bands or predefined percentage gains or losses, with percentage-based exits taking precedence over band-crossing conditions.

AAVE / TetherUS (AAVEUSDT)

+ Filtered Bollinger Bands By @Tradingade

@ Daily

1.58

Risk Reward

50.96 %

Total ROI

21

Total Trades

FTX Token (FTTUSD)

+ Filtered Bollinger Bands By @Tradingade

@ Daily

1.31

Risk Reward

29.08 %

Total ROI

16

Total Trades

Litecoin / TetherUS (LTCUSDT)

+ Filtered Bollinger Bands By @Tradingade

@ 2 h

1.20

Risk Reward

260.92 %

Total ROI

336

Total Trades

RENDER / TetherUS (RENDERUSDT)

+ Filtered Bollinger Bands By @Tradingade

@ 1 h

1.11

Risk Reward

112.69 %

Total ROI

379

Total Trades

LDO / TetherUS (LDOUSDT)

+ Filtered Bollinger Bands By @Tradingade

@ 2 h

1.09

Risk Reward

75.66 %

Total ROI

181

Total Trades

Premium users only

Premium users can access all backtests with a Risk/Reward Ratio > 3

@ 4 h

12.05

Risk Reward

988.34 %

Total ROI

16

Total Trades

Premium users only

Premium users can access all backtests with a Risk/Reward Ratio > 3

@ Daily

5.19

Risk Reward

946.81 %

Total ROI

87

Total Trades

Nu Holdings Ltd. (NU)

+ Filtered Bollinger Bands By @Tradingade

@ 2 h

2.89

Risk Reward

307.82 %

Total ROI

46

Total Trades

ServiceNow, Inc. (NOW)

+ Filtered Bollinger Bands By @Tradingade

@ 4 h

2.64

Risk Reward

2,798.24 %

Total ROI

91

Total Trades

Merck & Company, Inc. (MRK)

+ Filtered Bollinger Bands By @Tradingade

@ Daily

2.52

Risk Reward

365.01 %

Total ROI

83

Total Trades

Applovin Corporation (APP)

+ Filtered Bollinger Bands By @Tradingade

@ 2 h

2.52

Risk Reward

182.27 %

Total ROI

54

Total Trades

Credo Technology Group Holding Ltd (CRDO)

+ Filtered Bollinger Bands By @Tradingade

@ 4 h

2.50

Risk Reward

92.73 %

Total ROI

19

Total Trades
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Guide

How does the Filtered Bollinger Bands By @Tradingade strategy work ?

The Filtered Bollinger Bands strategy by @Tradingade combines traditional Bollinger Bands with a unique Trend filter designed to identify potential reversal points with higher precision. The Trend filter, being the core component, uses historical data to gauge whether the current price movement is reaching its exhaustion, hence improving entry conditions.

Entries for a long position occur when the price drops below the lower Bollinger Band followed by the close price rising above it. The Trend filter applies an additional condition, requiring yesterday's low to be the lowest of the previous X days. A similar approach is used for short positions, but with the focus on the high price. The strategy presets a stop loss and take profit as percentages, but an important exit condition is also set: a long position exits when the high price breaches the upper band, while a short position exits when the low price dips below the lower band.

The strategy offers flexibility with the "Exit Cond", allowing traders to prioritize either a percentage-based exit strategy or to rely solely on the band crossover condition. Trades are further customizable via input settings, which include the ability to modify the time frame and length of the historical data considered by the Trend filter.

How to use the Filtered Bollinger Bands By @Tradingade strategy ?

This trading strategy is unavailable due to a missing script error, which indicates that the content of the trading strategy script was not provided. Without the script content, it is impossible to detail how the strategy works or to explain how to implement it manually on TradingView.

To trade this strategy manually on TradingView, we would need specific information on the indicators, calculations, entry conditions, and exit conditions used in the script. These details are essential in replicating the trading strategy without access to the script itself.

How to optimize the Filtered Bollinger Bands By @Tradingade trading strategy ?

Improving the "Filtered Bollinger Bands" strategy manually on TradingView involves a detailed examination of its components, focusing on refining each aspect for better performance:

  • Enhance Trend Filter: Amend the trend filter sensitivity by adjusting the number of candles required to confirm the trend. Experiment with more or fewer candles than the current four-candle setting to better align with prevailing market conditions.
  • Optimize Filter Timeframe: The default trend filter operates on a one-day timeframe. To suit different trading styles, consider shorter timeframes for intraday trading, while maintaining robustness through backtesting for consistency in identifying optimal entries.
  • Refine Bollinger Bands Parameters: The default 20-period length with a standard deviation of 2 may not be optimal for all markets. Adjust the length and standard deviation based on volatility analysis and backtest to find a balance between too tight and too wide bands.
  • Adopt Discretionary Stop Losses and Take Profits: Rather than a fixed percentage, implement stop losses and take profits based on market structure, such as recent highs, lows, or dynamic support and resistance levels.
  • Diversify Entry Signals: Introduce additional indicators to confirm an entry, such as the Relative Strength Index (RSI) to verify overbought or oversold conditions or Moving Average Convergence Divergence (MACD) for momentum confirmation.
  • Customize Exit Criteria: While percentage exits are hard-set, using trailing stops or exiting at significant support/resistance levels before reaching the band could lock in profits more effectively.
  • Implement Position Sizing Strategy: Rather than a static order size, utilize a position sizing formula that adapts to the current account balance and the risk level of individual trades.
  • Conduct Periodic Strategy Reviews: On a quarterly or biannual basis, review the effectiveness of the strategy’s parameters and make necessary adjustments based on changes in market conditions.
  • Incorporate Fundamental Analysis: For assets with high fundamental impact, complement technical signals with fundamental events and economic indicators to reinforce trading decisions.
  • Manual Backtesting: Regular backtesting by hand can reveal nuances that automated backtesting might miss, allowing you to gauge market sentiment and reaction to various conditions.

Each of these steps must be tested against historical data and within a demo trading environment to validate performance before applying to a live trading scenario.

For which kind of traders is the Filtered Bollinger Bands By @Tradingade strategy suitable ?

The Filtered Bollinger Bands strategy is designed for traders who have a penchant for technical analysis and favor reversal trading. This strategy is particularly suitable for:

  • Swing Traders: Those who aim to capture price moves from an overextended state back to the mean, usually holding positions for several days.
  • Trend Reversal Seekers: Traders looking for potential points where the price movement is reaching exhaustion, indicating a possible reversal.
  • Adaptive Traders: Individuals who appreciate a strategy that can be customized based on the timeframe and market conditions—allowing for adjustments to the trend filter and Bollinger Band parameters.

The strategy accommodates a range of trading styles through its adjustable settings which can fine-tune the system for aggressive short-term day trading or more conservative long-term trend following. Its primary focus on trend reversal, however, makes it especially aligned with styles that capitalize on volatility and price corrections.

Key Takeaways of Filtered Bollinger Bands By @Tradingade

  • Strategy Essence: Utilizes Bollinger Bands and Trend filter to identify potential reversals; suitable for technical traders focusing on trend exhaustion.
  • Working Mechanism: Initiates long or short positions when price deviates from the Bollinger Bands, with the Trend filter evaluating historical price extremes.
  • Manual Trading: Traders can manually apply the strategy on TradingView by setting up corresponding Bollinger Bands and filtering based on the prior day's price highs or lows.
  • Optimization Approach: Fine-tuning involves altering the Trend filter settings, adjusting Bollinger Bands parameters, and introducing additional confirming indicators.
  • Automation vs. Manual: While the strategy can be automated, manual trading allows for flexible stop loss/take profit levels and combining with fundamental analysis.
  • Risk Management: Implement discretionary positions sizing and validate adjustments through backtesting to enhance the strategy's effectiveness.
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