AI-Driven Yield From
Structured Product Mispricing

We utilise proprietary artificial intelligence to systematically identify worst-of autocall pairs where quantitative models overpay for historical volatility that no longer reflects actual forward-looking risk.

9.29%
10-Year Simulated CAGR
-3.48%
Max Drawdown
500+
US Equities Screened Weekly
80,000+
Pairs Analysed
The Opportunity

Banks Price Risk Backwards.
We Look Forward.

Structured product issuers (e.g., HSBC, Barclays, Citi, Morgan Stanley) price worst-of autocall coupons using automated engines driven primarily by trailing historical volatility. A stock that experienced a severe drawdown six months ago carries extreme trailing volatility — generating a rich coupon — even if the equity has since completely stabilised and the risk has passed.

This creates a systematic, repeatable spread between the coupon the bank is mathematically forced to pay (driven by past volatility) and the actual risk of barrier breach (visible in the forward-looking chart). Our AI visualises the chart and captures this spread.

1. Arbitrage the Model

Identify "blind spots" where trailing vol forces the bank to offer massive coupons, but forward-looking structural risk is actually low (e.g., a stock that crashed but has formed a firm base). The 50% barrier is set against a derisked floor.

2. Harvest Issuer Dispersion

Banks have completely different pricing for the exact same risk based on their internal derivatives books. By screening for $10B+ mega-caps and putting the structure out to competitive bidding among 5+ issuers, we naturally capture the top end of the spread.

3. Coupon-as-Buffer

When a bank's model flags extreme volatility and offers a >25% p.a. yield, the spread itself becomes capital protection. The accumulated income effectively absorbs potential downside risk at maturity.

Bank Pricing Engine

18% p.a.

Trailing 180-day volatility sees the crash. Pays a rich coupon automatically.

AI Chart Analysis

Low Risk

Stock has bottomed and formed a base. Barrier is far below the structural floor.

The Spread

Alpha

High coupon + low actual risk = systematic mispricing capture.

Our Edge

What Quantitative Models Cannot See

Investment banks rely on quantitative models. We use quantitative models plus advanced foundation models that visually analyse 5-year price charts — exactly as an experienced trader would, but applied simultaneously across 80,000+ pairs every week.

Unconstrained Discovery

Before quantitative screening, creative models (Claude Sonnet) brainstorm non-obvious, cross-sector, and supply-chain relationships. This uncovers "hidden gem" pairs where yield is not yet priced out by crowded trades.

Multi-Agent Debate

Every top-ranked pair undergoes a rigorous "Judge and Advocates" review. Fast, specialized AI agents (Claude Haiku) are strictly incentivised to build relentless Bear and Bull cases, eliminating AI bias and sycophancy.

Multimodal Chart Intelligence

A heavyweight reasoning model (Claude Opus or Amazon Nova) acts as the final Judge. It reviews the Bear/Bull debate alongside fundamental data and visually analyses 5-year and 1-year overlay charts to identify structural risks that raw volatility numbers miss entirely.

Product Structure

The Autocall Mechanism

Each position is executed as a worst-of autocall on two US equities. The structure is strictly standardised across all positions to enable systematic, risk-managed portfolio construction.

ParameterSpecification
Tenor6 or 12 months (Dynamic)
Knock-In Barrier50% European (Capital protected unless worst-of falls below 50% at maturity)
Autocall Trigger70% at quarterly observations (Early redemption if both stocks remain above 70%)
CouponFixed, paid at maturity or autocall event
Underlying AssetsWorst-of on 2 US large/mid-cap equities
Minimum TicketEUR 500,000 per position
ReinvestmentImmediate upon autocall — driving continuous compounding
Equity Universe500+ US equities, $2B+ market cap, strictly screened for liquidity
Investment Strategy

Unified Portfolio Approach

A single, consolidated strategy designed to exploit the pricing spread across the entire volatility spectrum, dynamically adjusting to market conditions.

Valhalla Fund

AI-Driven Autocall Fund — Target 10-14% gross p.a.

A unified AI-driven strategy that exploits the spread between bank-priced volatility and forward-looking chart risk. The AI selects pairs across the full coupon spectrum — from conservative 8% anchors (stable names 10-30% off highs) to aggressive 20%+ yield plays (crashed names with high residual vol) — and builds a diversified portfolio targeting 10-14% gross yield with controlled breach risk.

50% Barrier • Dynamic Tenor (6M/12M) • Tiered AI Portfolio Construction
Investment Process

Autonomous Selection Pipeline

The entire pipeline operates autonomously on a weekly cycle. Human oversight is strictly focused on model parameter governance and enforcing portfolio-level risk limits.

01

AI Discovery & Universe Screen

Creative models brainstorm thematic, cross-sector relationships to find non-obvious pairs. These are combined with a 500+ US equity universe and filtered for liquidity.

02

Quantitative Scoring

Pairs are scored mathematically on combined volatility, correlation, barrier breach probability, and bank-calibrated coupon estimates to find the best yield-to-risk ratios.

03

Multi-Agent Debate

Fast, specialized AI agents act as relentless Bear and Bull advocates, generating targeted arguments for and against the pair's resilience to eliminate AI bias.

04

Multimodal Judge

A heavyweight reasoning model (Opus/Nova) reviews the debate, fundamentals, and visually analyses 5-year price charts to make the final portfolio selection.

Historical Simulation

10-Year Backtest Results

Rigorous AI-driven portfolio simulation from January 2016 to February 2026, utilising strictly point-in-time data. The simulation operates without hindsight bias — the AI is blind to calendar dates, relying exclusively on prevailing market statistics and price charts.

Key Achievements: Across a 10-year period encompassing the COVID-19 crash and the 2022 bear market, the strategy achieved a sustainable ~9-10% CAGR while maintaining an exceptionally low maximum drawdown of under 7%. By dynamically filtering for structural safety, the AI successfully deployed capital into hundreds of high-yield autocall positions with a near-zero barrier breach rate.

Valhalla Fund

Unified AI Strategy
147.74%
Total Return (9.29% CAGR)
Sharpe Ratio:
1.708
Max Drawdown:
-3.48%
Total Positions:
489
Breach Rate:
2.0%
Disclaimer: Historical simulations utilise model-estimated coupons, not executed trades. Actual issuer pricing may differ. Past performance, whether simulated or actual, is not indicative of future results. Simulations do not account for structuring fees, AuM fees, or administrative costs.
Fund Structure

Proposed Institutional Vehicle

TermDetail
VehicleManaged Certificate or RAIF (Luxembourg)
CurrencyEUR (USD share class available)
Minimum InvestmentEUR 500,000
Target AuMEUR 10-50M initial
Management Fee1.0% p.a.
Performance Fee15% above 5% hurdle (High-water mark)
LiquidityMonthly with 30-day notice
CounterpartiesHSBC, Barclays, Citi, Natixis, Morgan Stanley

The architecture is designed to scale across geographies: Global, US, EU, Asia ex-Japan, and Japan. The US strategy is fully operational and backtested. Other geographies follow the identical methodology with regional equity universes.

Let's Explore the Opportunity

We are actively seeking strategic partners — investment banks, distributors, and anchor investors — to bring this institutional strategy to market.

Contact Management