Potential Roles and Engagements

Within a hedge fund, asset manager, or clearing member, I can:

• Establish a centralised optimisation framework to allocate and distribute trading intelligently — maximising market capacity while minimising XVA and RWA footprints.
• Serve as Chief Risk Officer, Head of Market Risk, or Strategic Adviser on derivative risk and capital optimisation.

Within a bank, I could:

• Design or refine CVA, FVA, and KVA frameworks, along with funding-risk and OIS discounting infrastructure.

Career Highlights

• JPMorgan: Led a transformation of the Clearing and F&O business by introducing front-office risk management and pricing discipline to what had historically been a pure “agency” model — doubling revenue while reducing capital usage, GSIB metrics, and residual interest exposure.
• Contributed to JPMorgan winning Risk Magazine’s Best OTC Client Clearer award in 2019 and 2021.
• Designed and implemented FVA and KVA frameworks across the global derivatives franchise.
• Introduced single and multi-currency OIS discounting firm-wide, creating a centralised funding-risk utility.

Illustrative Trade Concepts

The following examples highlight some of the XVA-related and convexity-driven opportunities I focus on — areas where detailed analysis and structured implementation can uncover material value.

1. Collateral Optimisation and Differential Discounting

The ability to capture value through recognition of differential discounting (DD) and eligible collateral assets — first identified during the transition from LIBOR to OIS discounting — has been known for over a decade. Around 2009–10, one major Wall Street bank reportedly generated a substantial share of its FICC revenue by exploiting this effect. As the market evolved, most dealers upgraded their systems to eliminate this arbitrage internally, crystallising costs for those that were slower to adapt.

Even today, however, the process is not fully efficient. Trades executed “given-in” under Clearing Agreements are typically processed through post-trade approval systems that are DD-agnostic, leaving persistent arbitrage gaps. When a client executes a trade, the executing broker (EB) prices it using discount curves aligned with its own clearing relationship — curves that often differ from those used by the clearing agent (CA) in its valuation of the same position.

The result is that trades can be priced on inconsistent discount curves, creating systematic valuation mismatches. For trades with large funding deltas, this can produce backwardation opportunities, where clients can extract value by recognising and exploiting how discounting conventions vary across market participants.

2. CVA Mining and Initial Margin Optimisation

For hedge funds, asset managers, or corporates with uncollateralised derivative exposure, significant latent value is often hidden in how banks manage their CVA reserves and Initial Margin (IM) requirements. A centralised XVA Hub can systematically identify and recover this value by managing exposures across all counterparties, rather than trade by trade.

CVA “mining” arises because each dealer calibrates its credit reserves to its own exposure and counterparty profile. Where a buy-side participant holds offsetting exposures across several dealers, these reserves can be rebalanced to reduce overall CVA charges and associated funding costs.

The same logic applies to IM optimisation under the Non-Cleared Margin Rules (NCMR). Because the $50 million uncollateralised threshold applies per counterparty group, not in aggregate, redistributing trades across multiple dealers can materially reduce total IM. With funding costs at 5%, spreading exposure evenly across five dealers could save roughly $12.5 million per year (5 × $50 million × 5%).

Further gains can be achieved by transforming cleared exposures into bilateral ones using swaptions that replicate the delta of cleared swaps. These bilateral structures allow negotiated and offset IM, effectively creating free funding for part of the portfolio.

Several large hedge funds now operate centralised hubs that manage their XVA footprint across all dealer relationships. For smaller or less systemically connected institutions, adopting a similar framework can yield recurring savings and greater transparency over balance-sheet usage.

3. X-Gamma DD (OIS-Libor) Trade

Beyond conventional XVA effects, there exists an overlooked class of convexity opportunities arising from the interaction between currency basis risk and OIS discounting. While often treated as independent, these risks are correlated through funding behaviour and liquidity transmission, creating what is effectively a form of funding wayness, analogous to wrong-way credit risk.

In practice, non-USD discounting curves depend on both the OIS–LIBOR spread and the currency basis. When a portfolio’s funding delta is sensitive to either factor, a second-order convexity effect appears that is not properly captured in most market models. This omission means current valuations often overlook a meaningful source of asymmetric P&L potential.

By constructing offsetting exposures across OIS discounting and cross-currency basis, one can create positions where funding deltas move favourably in both directions — generating a positive annuity-like return regardless of near-term market direction. In essence, it is possible to capture value from the non-linear interaction between funding and discounting curves — an opportunity still largely untapped because most participants model these factors independently.

4. Contingent CCP Trades

In a clearing-member default, central counterparties (CCPs) auction the defaulting member’s portfolio to flatten their risk exposure. All non-defaulting members must bid on the entire portfolio as a single package, and failure to do so risks forfeiting default-fund contributions.

The challenge is that large, complex portfolios often contain contracts that some members cannot or will not price. Many bids are therefore incomplete, causing auctions to fail and exposing the CCP to potential loss.

A contingent bidder model could address this. Here, a third-party trading entity provides conditional bids for contracts where members lack capacity. These bids could be structured as credit-contingent agreements, offering a defensive tool for clearing members and an asymmetric opportunity for the bidder.

Alternatively, a hedge fund could act directly as a liquidity provider in CCP auctions, effectively “plugging the gaps” in dealer bids. This improves auction efficiency while capturing the widest bid–offer spreads available in the market. A CCP auction following a major default represents one of the most concentrated trading opportunities imaginable — yet the market remains poorly prepared for it.

In Summary

I combine front-office trading experience with deep risk-infrastructure knowledge and strategic insight into how regulation, funding, and capital mechanics shape market behaviour.

My goal is to help institutions unlock value from complexity — optimising capital, managing XVA exposures, and identifying structural sources of convexity and inefficiency across the derivatives landscape.

If you would like to discuss potential collaborations, advisory roles, or implementation of any of the concepts above, I would welcome the conversation.