Portfolio Optimization System
Optimize Portfolio Construction by Integrating Liquidity Risk into Trade Selection
Projected Impact for Credit Portfolio Managers
Backtested results show measurable P&L improvements by incorporating real-world execution probabilities into portfolio construction.
By avoiding failed searches and ghost liquidity
Capturing spread typically lost to poor fills
Reduced cash drag via faster allocation and fewer failed RFQs
THE PROBLEM
In illiquid credit markets, standard portfolio optimizers fail because they assume execution certainty. A “perfect” trade on paper is worthless if it cannot be filled without excessive slippage.
THE SOLUTION
The AXOR Portfolio Optimization System moves beyond theoretical pricing. We rank corporate bond opportunities by Expected Value (EV)—mathematically fusing your alpha signals with the real-world Chance to Fill (CTF) at every quote level—before orders are generated.
Beyond Price: The Power of Expected Value
Most systems optimize for yield or spread. AXOR optimizes for realized portfolio impact.
By leveraging a proprietary 80M-parameter Deep Neural Network, AXOR calculates the specific probability of execution for every bond, conditioned on trade size, side, and current ATS dynamics.
- Standard View: “Bond A offers 150bps spread. Buy.”
- AXOR View: “Bond A offers 150bps but has only a 12% CTF at target price. Bond B offers 145bps with an 82% CTF. Bond B offers superior Risk-Adjusted Expected Value.”
Core Capabilities
1. Deep Learning Liquidity Modeling
Unlike linear regression models used by legacy providers, AXOR utilizes Quantile Regression on a deep neural network trained on 2,000+ features (TRACE, ETF flows, RFQ metadata).
Performance: Internal benchmarks show AXOR’s pricing and fill-probability accuracy outperforms legacy CP+ models by 40–50% in illiquid tiers.
2. Probabilistic Portfolio Construction
Build portfolios that actually clear the market. AXOR simulates execution paths to fill your target risk/duration buckets in fewer cycles. It automatically identifies “backup trades”—correlated substitutes that maintain your portfolio’s objective function if primary liquidity dries up.
3. API-First Integration
Designed for the modern desk. Feed AXOR’s signals directly into Bloomberg, Aladdin, or proprietary OMS/EMS via low-latency API. Supports both real-time pre-trade analysis and batch portfolio rebalancing.
4. Customizable Objective Functions
Tune the system to your firm's specific mandate. Whether you are maximizing yield, minimizing turnover, or targeting specific convexity profiles, AXOR weighs your alpha against execution probability to deliver the optimal trade list.
Modeled Case Study
In a simulation of a $5B high-turnover credit strategy, integrating AXOR’s CTF-weighted logic reduced slippage by approximately 30%. Over a 12-month period, this efficiency compounded to add 23 bps to total fund returns—equivalent to $11.5M in preserved value.
Take the Next Step
Stop treating execution as a cost center. Turn liquidity intelligence into a source of alpha.
Contact us for a quantitative backtest of your recent trade lists.
Book a Demo NowNathan Powell
Founder & CEO, Deep Market Making
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