Improving risk return profiles through advanced AI analytics
F9 RMAG MACRO BOND FUND
Bloomberg: BBG01TYZ33L7
ISIN: AE000A4195M9
Quantitative AI Strategies boost performance by improving portfolio’s risk return profiles
Our AI and machine learning powered proprietary statistical models provide superior precision and reliability, supported by a comprehensive database covering most of the fixed-income securities across developed and emerging markets.

The Risk Management Analytics Group, RMAG, is backed by a team of experts, including multiple PhD holders, our research is driven by advanced statistical methodologies and proprietary AI/ML components integrated across multiple layers. Our Quantitative Strategies team specializes in global fixed income.

F9 RMAG Identifies corporates with the strongest cashflow and debt metrics relative to the pricing.
Quantitative AI Macro Bond Portfolio
  • -1-
    Investment Universe
    • Investable universe is US IG and HY corporate bonds drawing from the benchmarks with composite credit rating maximum of A+ and minimum of B-.
    • Bonds are filtered for both credit quality and liquidity.
    • We use the latest LLM’s to classify the risk of issuers.
    • 70% Investment Grade
    • 30% High Yield
  • -2-
    Portfolio Constraints
    • Constraints such as concentration risk, or allocation quotas are written into code to optimise the portfolio against.
    • The approach ensures unbiased investment decisions prioritising total returns and risk mitigation.
    • Risk Control
    • Liquidity
  • -3-
    Portfolio Selection
    • We identify dislocations in the universe and identify risk adjusted opportunities.
    • The portfolio is constructed for best potential returns based of both yield to maturity and potential short-term misprised instruments for trading profits.
    • Total Returns
    • Diversification
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  • Transparent Benchmarking
    • The Bloomberg U.S. Corporate Investment Grade Benchmark is used to measure portfolio performance.
    • The portfolio will deviate substantially from the benchmark as we do not aim to achieve index replication but can only select bonds from the index.
  • Portfolio Rebalancing
    • Total and Investment universes are screened daily.
    • Portfolio is balanced regularly when thresholds are met considering both liquidity and market spreads.
    • Estimated portfolio turnover ca 1.2-1.5x per year depending on market volatility
  • Multi Asset Inputs
    • In addition to screening actual investment universe, the correlated asset prices are systematically analysed
    • Finding hidden cross correlations and delayed price transmission across the asset classes to have early warning signals
  • Portfolio Constraints
    • Portfolios are optimised to match the target credit profile. Flexible duration, concentration and industry limits allows the portfolio to remain liquid in most market scenarios.
    • The optimization process allocates across sectors and durations to enhance returns, avoiding index replication.
  • Liquidity Considerations
    • We aim to invest in bonds that are in the top 50th percentile most liquid bonds for their respective asset class.
    • The quantitative analysis dynamically allocates more to US Treasuries in market downturn or stressed environments.
  • Diversification
    • Maximum allocation to single issuer is 5% of the portfolio indicating minimum portfolio size of 20 issuers.
    • Target portfolio size 35-40 issuers
Portfolio Selection Process
Driving Alpha through Intelligent Portfolio Construction
  • Initial Filtering
    • High level portfolio investment constraints defined in code.
    • Proprietary risk scores given to each issuer.
    • Ability to add issuers to “blocked list” to have oversight of risk allocation.
  • Sample Inputs
    • Trend Cycle & market momentum.
    • Resistance levels and recovery values.
    • Asset correlations and volatilities.
    • Sensitivity to cross-asset prices.
    • Projected yields and trading profits.
  • Portfolio Construction
    • Effort made to enhance best potential return both through yield and trading profits.
    • Continuous monitoring to take advantage of asset movements and market risk changes.
Advantages of Quantitative Strategies
Enhancing Returns through Quantitative Strategies
  • Consistency & Repeatability
    • Strategies consistently apply defined rules, ensuring repeatability over long periods.
    • Eliminates dependence on individual decision-making and reduces variability in outcomes.
  • Speed & Efficiency
    • Can process vast amounts of data rapidly, far exceeding human analytical capabilities.
    • Quickly adapt to new information, capturing opportunities faster than traditional analysis.
  • Backtesting & Validation
    • Quantitative strategies can be thoroughly backtested against historical data to validate effectiveness.
    • Provides clear metrics for strategy refinement before committing capital.
  • Risk Management
    • Enhanced ability to quantify and systematically control risk through defined limits and constraints.
    • Continuously monitors risk, adjusting exposures proactively rather than reactively.
  • Objectivity in Decision Making
    • Removes subjective opinions, biases, or emotional responses to market volatility.
    • Ensures decision-making remains disciplined, focused purely on data-driven signals.
  • Scalability
    • Easily expanded to new markets, asset classes, or investment universes without significantly increasing resource costs.
    • Allows rapid diversification and adaptation to changing market opportunities.
Advantages of Quantitative Strategies
Capability to Analyze Over 100,000 Datapoints Simultaneously
  • Global Screening
    Global screening of all corporate financial data available.
  • Simultaneous Risk Inputs
    Simultaneous incorporation of both spot and forward interest rates, foreign exchange rates, credit metrics and commodity pricing enables a multidimensional portfolio optimization to desired risk parameters.
  • Rebalancing
    Portfolio rebalancing with desired parameters to avoid over trading and loss of performance.
  • Global Market Overlay
    Systematic market stress indicators together with traditional macro data and fast moving proxies provide layer of safety in credit and duration exposures.
  • Real-time On-going Monitoring
    Non-stop real time screening of the portfolio and investable universe.
    Screening parameters designed to minimize risk of defaults.
    Forensic Accounting methods applied for constant portfolio monitoring.