We run a proprietary research and execution stack designed to source structured-yield opportunities where standardised issuer pricing diverges from our forward-looking risk view, then assemble them into a disciplined portfolio built for compounding rather than one-off trades.
Structured-product issuers rely on standardised pricing frameworks. Those frameworks are excellent at scaling issuance, but they are not designed to form a nuanced forward-looking view of how risk evolves after dislocations, regime changes, and price-path resets.
That gap creates a repeatable opportunity for investors with better underwriting, better execution, and better portfolio construction. Our edge is not a single signal; it is the combination of proprietary research, issuer selection, and disciplined compounding.
We focus on situations where standardised market pricing and our forward-looking risk view diverge materially, creating room for attractive income without heroic directional calls.
We treat execution as a source of alpha. Structure selection, issuer dispersion, and disciplined trade packaging matter as much as the initial idea.
We manage the strategy as a portfolio, not isolated notes. Recycling capital, pacing exposure, and controlling path risk are central to preserving downside quality.
Issuer models are built to quote efficiently and consistently across large product inventories.
Our research layer focuses on path, resilience, and portfolio fit rather than a single backward-looking statistic.
Disciplined underwriting plus disciplined execution creates repeatable mispricing capture.
The edge is not "AI" in the generic sense. It is a proprietary decision architecture that combines pattern recognition, adversarial review, and portfolio governance in a way standardised issuer models and simple screening tools do not replicate.
We identify opportunities that conventional screens miss by combining structural context with a forward-looking risk lens rather than relying on obvious crowding signals.
Candidate ideas are challenged through opposing views before capital is allocated. That keeps the process skeptical, reduces narrative drift, and improves consistency under stress.
The research stack adapts when conditions become ambiguous, but portfolio-level risk discipline remains constant. The objective is high-quality deployment with strong downside control.
Positions are executed in a standardised institutional format so the portfolio can be managed with consistent underwriting, transparent downside terms, and repeatable capital recycling.
| Parameter | Specification |
|---|---|
| Duration | Short-dated, standardised |
| Downside Terms | Defined-risk autocall format with contractual maturity protection mechanics |
| Observation Schedule | Regular early-redemption observations |
| Income Profile | Fixed contractual coupon, bank-calibrated, paid on redemption or maturity |
| Underlying Format | Diversified worst-of notes on liquid US equities |
| Currency Classes | USD, EUR, CHF, SEK, SGD |
| Minimum Ticket | USD 500,000 per position |
| Reinvestment | Systematic recycling of returned capital into the refreshed portfolio |
| Asset Focus | Institutional-quality liquid US equities |
The platform supports two distinct investment profiles from a single research and execution engine, allowing investors to choose the risk-return balance that fits their mandate.
Targets attractive gross income across a wider opportunity set. Accepts more portfolio positions to maximise capital deployment and compounding velocity. Risk controls adapt dynamically to market regime shifts, protecting capital during dislocations while staying growth-oriented during benign periods.
Targets higher individual position quality with tighter selection criteria. Runs a concentrated book of best-conviction ideas. Protective mechanisms activate earlier and more aggressively, prioritising capital preservation and smooth NAV paths over maximum yield.
The process runs on a recurring weekly cycle, governed as an investment system rather than a black box. Human oversight is concentrated on mandate discipline, risk boundaries, and release governance.
We refresh the opportunity set using proprietary research inputs and strict investability filters, keeping the live book aligned with the most attractive current setups.
Each candidate is assessed against downside, structure, and portfolio-fit criteria before it can compete for capital. Pricing is calibrated against real institutional dealer quotes.
High-conviction ideas are deliberately pressure-tested from multiple angles so that weak narratives are filtered out before they reach the portfolio.
Final allocations are made in the context of the whole book, balancing opportunity quality, exposure pacing, diversification, and capital recycling across all five currency classes.
Historical research from January 2016, using only information that would have been available at the time. Both risk profiles are currently running full-history simulations across all five currency classes.
Preliminary results are encouraging: both profiles show zero barrier knock-ins to date, with the conservative profile demonstrating particularly strong risk-adjusted returns. Detailed performance metrics are available upon request.
| Term | Detail |
|---|---|
| Vehicle | Managed Certificate or RAIF (Luxembourg) |
| Currency | USD, EUR, CHF, SEK, SGD |
| Risk Profiles | Two profiles available: growth-oriented and conservative |
| Minimum Investment | USD 500,000 |
| Target AuM | USD 10–50M initial |
| Management Fee | 1.0% p.a. |
| Performance Fee | 15% above 5% hurdle (high-water mark) |
| Liquidity | Monthly with 30-day notice |
| Counterparties | Tier-one global issuers |
The architecture is designed to scale across geographies and wrappers without changing the core underwriting discipline.
We are actively seeking strategic partners — investment banks, distributors, and anchor investors — to bring this institutional strategy to market.
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