Bear Market Defender [QuantraSystems]

Bear Market Defender
A system to short Altcoins when BTC is ranging or falling - benefit from Altcoin bleed or collapse.

QuantraSystems guarantees that the information created and published within this document and on the TradingView platform is fully compliant with applicable regulations, does not constitute investment advice, and is not exclusively intended for qualified investors.



Important Note!

• The system equity curve presented here has been generated as part of the process of testing and verifying the methodology behind this script.
  
  
• Crucially, it was developed after the system was conceptualized, designed, and created, which helps to mitigate the risk of overfitting to historical data. In other words, the system was built for robustness, not for simply optimizing past performance.
  
  
• This ensures that the system is less likely to degrade in performance over time, compared to hyper-optimized systems that are tailored to past data. No tweaks or optimizations were made to this system post-backtest.
  Even More Important Note!!
• The nature of markets is that they change quickly and unpredictably. Past performance does not guarantee future results - this is a fundamental rule in trading and investing.
  
  
• While this system is designed with broad, flexible conditions to adapt quickly to a range of market environments, it is essential to understand that no assumptions should be made about future returns based on historical data. Markets are inherently uncertain, and this system - like all trading systems - cannot predict future outcomes.
  
  
  
  INTRODUCTION TO THE STAR FRAMEWORK
  
  The STAR Framework – an abbreviation for Strategic Trading with Adaptive Risk - is a bespoke portfolio-level infrastructure for dynamic, multi-asset crypto trading systems. It combines systematic position management, adaptive sizing, and “intra-system” diversification, all built on a rigorous foundation of Risk-based position sizing.
  
  At its core, STAR is designed to facilitate:
  
  
  • Adaptive position sizing based on user-defined maximum portfolio risk
    
  • Capital allocation across multiple assets with dynamic weight adjustment
    
  • Execution-aware trading with robust fee and slippage adjustment
    
  • Realistic equity curve logic based on a compounding realized PnL and additive unrealized PnL
    
  
  
  The STAR Framework is intended for use as both a standalone portfolio system or preferred as a modular component within a broader trading “global portfolio” - delivering a balance of robustness and scalability across strategy types, timeframes, and market regimes.
  
  
  
  RISK ALLOCATION VIA "R" CALCULATIONS
  
  The foundational concept behind STAR is the use of the R unit - a dynamic representation of risk per trade. R is defined by the distance between a trade's entry and its stoploss, making it an intuitive and universally adaptive sizing unit across any token, timeframe, or market.
  
  Example: Suppose the entry price is $100, and the stoploss is $95. A $5 move against the position represents a 1R loss. A 15% price increase to $115 would equal a +3R gain.
  
  This makes R-based systems highly flexible: the user defines the percentage of capital that is put at risk per R and all positions are scaled accordingly - whether the token is volatile, illiquid, or slow-moving.
  
  R is an advantageous method for determine position sizing - instead of being tied to complex value at risk mechanisms with having layered exit criteria, or continuous volatility-based sizing criteria that need to be adjusted while in an open trade, R allows for very straightforward sizing, invalidation and especially risk control – which is the most fundamental.
  
  
  REALIZED BALANCE, FEES & SLIPPAGE ACCOUNTING
  
  All position sizing, risk metrics, and the base equity curve within STAR are calculated based on realized balance only.
  This means:
  
  • No sizing adjustments are made based on unrealized profit and loss ✅
    
  • No active positions are included in the system's realized equity until fully closed ✅
    
  • Every trade is sized precisely according to current locked-in realized portfolio balance ✅
    
  
  
  This creates the safest risk profile - especially when multiple trades are open. Unrealized gains are not used to inflate sizing, ensuring margin safety across all assets.
  
  All calculations also incorporate slippage and fees, based on user-defined estimates – which can and should be based upon user-collected data - and updated frequently forwards in time. These are not cosmetic, or simply applied to the final equity curve - they are fully integrated into the dynamic position sizing and equity performance, ensuring:
  
  • Stoploss hits result in exactly a −1R loss, even after slippage and fees ✅
    
  • Winners are discounted based on realistic execution costs ✅
    
  • No trade is oversized due to unaccounted execution costs ✅
    
  Example - Slippage in R Units:
  
  Let R be defined as the distance from entry to stoploss.
  
  Suppose that distance is $1, and the trade is closed at a win of +$2.
  
  If execution slippage leads to a 50 cent worse entry and a 50 cent worse exit, you’ve lost $1 extra - which is an additional 1R in execution slippage. This makes the effective return 1.0R instead of the intended 2.0R.
  
  This is equivalent to a slippage value of 50%.
  
  Thus, slippage in STAR is tracked and modelled on an R-adjusted basis, enabling more accurate long-term performance modelling.
  
  
  
  MULTI-ASSET, LONG/SHORT SUPPORT
  
  STAR supports concurrent long and short positions across multiple tokens. This can sometimes result in partially hedged exposure - for example, being long one asset and short another.
  
  This structure has key benefits:
  
  • Diversifies idiosyncratic risk by distributing exposure across multiple tokens
    
  • Allows simultaneous exploitation of relative strength and weakness
    
  • Reduces portfolio volatility via natural hedging during reduced trending periods
    
  Even in a highly correlated market like crypto, short-term momentum behaviour often varies between tokens - making diversified, multi-directional exposure a strategic advantage.
  
  
  
  EQUITY CURVE
  
  The STAR framework only updates the underlying realized equity when a position is closed, and the trade outcome is known. This approach ensures:
  
  • True representation of actual capital available for trading
    
  • No exposure distortion due to unrealized gains
    
  • Risk remains tightly linked to realized results
    
  
  
  This trade-to-trade basis for realized equity modelling eliminates the common pitfall of overallocation based on unrealized profits.
  
  The visual equity curve represents an accurate visualization of the Total Equity however, which is equivalent to what would be the realized equity if all trades were closed on the prior bar close.
  
  
  
  TIMEFRAME CONSIDERATIONS
  
  Lower timeframes typically yield better performance for STAR due to:
  
  • Greater data density per day - more observations = better statistical inference
    
  • Faster compounding - more trades per week = faster capital rotation
    
  
  However, lower timeframes also suffer from increased slippage and fees. STAR's execution-aware structure helps mitigate this, but users must still choose timeframes appropriate to their liquidity, costs, and operational availability.
  
  
  
  INPUT OPTIONS
  • Fees (direct trading costs - the percentage of capital removed from the initial position size)
    
  • Slippage (execution delay, as a percentage. In practice, the fill price is often worse than the signal price. This directly affects R and hence position sizing)
    
  • Risk % (Please note: this is the risk level if every position is opened at once. 5% risk for 5 assets is 1% risk per position)
    
  • System Start date
    
  • Float Precision value of displayed numbers
    
  • Table visualization - positioning and table sizes
    
  • Adjustable color options
    
  VISUAL SIMPLICITY
  
  To avoid usual unnecessary complexity and empower fast at-a-glance action taking, as well as enable mobile compatibility, only the most relevant information is presented.
  This includes all information required to open positions in one table.
  
  
  As well as a quick and straightforward overview for the system stats
  
  Lastly, there is an optional table that can be enabled
  displaying more detailed information if desired:
  USAGE GUIDELINES
  
  To use STAR effectively:
  
  • Input your average slippage and fees %
    
  • Input your maximum portfolio risk % (this controls overall leverage and is equivalent to the maximum loss that the allocation to STAR would bring if ALL positions are allocated AND hit their stop loss at the same time)
    
  • Wait for signal alerts with entry, stop, and size details
    
  
  
  STAR will dynamically calculate sizing, risk exposure, and portfolio allocation on your behalf. Position multipliers, stop placement, and asset-specific risk are all embedded in the system logic.
  
  Note: Leverage must be manually set to ISOLATED on your exchange platform to prevent unwanted position linking.
  
  
  
  
  ABOUT THE BEAR MARKET DEFENDER STRATEGY
  
  The first strategy to launch on the STAR Framework is the BEAR MARKET DEFENDER (BMD) - a fast-acting, trend following system based upon the Trend Titan NEUTRONSTAR. For the details of the logic behind NEUTRONSTAR, please refer to the methodology and trend aggregation section of the following indicator: https://www.tradingview.com/script/FoDdisZB-Trend-Titan-Neutronstar-QuantraSystems/
  
  The BMD’s short side exit calculation methodology is slightly improved compared to NEUTRONSTAR, to capture downtrends more consistently and also cut positions faster – which is crucial when considering general jump risk in the Crypto space.
  
  Accordingly, the only focus of the BMD is to capture trends to the short side, providing the benefit of being in a spectrum from no correlation to being negatively correlated in risk and return behavior to classical Crypto long exposure.
  
  More precisely, Crypto behavior showcases that when Bitcoin is in a ranging/mean reverting environment, most tokens that don’t fall into the “Blue-Chip” category tend to find themselves in a trend towards 0.
  Typically during this period most Crypto portfolios suffer heavily due to a “Crypto-long” biased exposure.
  
  The Bear Market Defender thrives in these chaotic, high volatility markets where most coins trend towards zero while the traditional Crypto long exposure is either flat or in a drawdown, therefore the BMD adds a source of uncorrelated risk and returns to hedge typical long exposure and bolster portfolio volatility.
  
  
  Because of the BMD's short-only exposure, it will often suffer small losses during strong uptrends. During these periods, long exposure performs the best and the goal is to outperform the temporary underperformance in the BMD.
  
  To take advantage of the abovementioned behavior of most tokens trending to zero, assets traded in the BMD are systematically updated on a quarterly basis with available liquidity being an important consideration for the tokens to be eligible for selection.
  
  
  
  
  FINAL SUMMARY
  
  The STAR Framework represents a new generation of portfolio grade trading infrastructure, built around disciplined execution, realized equity, and adaptive position sizing. It is designed to support any number of future methodologies - beginning with BMD.
  
  The Bear Market Defender is here to hedge out commonly long biased portfolio allocations in the Crypto market, specializing in bringing uncorrelated returns during periods of sideways price action on Bitcoin, or whole-market downturns.
  
  
  
  Together, STAR + BMD deliver a scalable, volatility tuned system that prioritizes capital preservation, signal accuracy, and adaptive risk allocation. Whether deployed standalone or within a broader portfolio, this framework is engineered for high performance, longevity, and adaptability in the ever-evolving crypto landscape.