Chloi Karyda — The Implementation Edge

How QIS has evolved from a product set into a portfolio toolkit — and why implementation is now the source of the real edge.

This article is based on a conversation between Vincent Weber, CEO & Head of Research at Resonanz Capital, and Chloi Karyda, Managing Director and Global Head of QIS Solutions at J.P. Morgan. The episode is part of the Resonanz Spotlight podcast series.

The views expressed in this podcast are those of the individual speakers and do not constitute investment advice, a recommendation, or an offer to buy or sell any financial instrument or product. They do not necessarily represent the views of J.P. Morgan or any of its affiliates. This content is for informational purposes only and should not be relied upon as the basis for any investment decision. Listeners should seek independent professional advice before making any investment.

What Is QIS — and Why Does Implementation Matter So Much?

Quantitative investment strategies (QIS) were once understood as a relatively narrow category: systematic, rules-based products offering liquid exposure to hedge-fund-like return streams. That framing no longer captures the space.

Over the past decade, QIS has expanded in every dimension — products, instruments, use cases, and collaboration models. Today, it serves as a modular portfolio toolkit that institutional investors deploy for inflation hedging, tail-risk management, income generation, market access, and execution outsourcing.

But the most important shift is subtler. As the product set has broadened and as investors have grown more sophisticated, implementation has emerged as the primary differentiator. Two strategies that look identical on paper can produce materially different outcomes in practice. The difference lies in the craft of execution.

That is the central insight from this conversation with Chloi Karyda.

Who Is Chloi Karyda?

Chloi Karyda is Managing Director and Global Head of QIS Solutions at J.P. Morgan. Her team sits at the intersection of client needs, product capabilities, and market execution — functioning, as she describes it, as an internal task force that works within the bank on behalf of the client.

That vantage point gives her an unusually complete picture of how institutional investors think about systematic tools, how those needs have shifted over time, and where the next edges in the space are likely to emerge.

From "Give Me a Diversifier" to "Solve My Specific Problem"

One of the clearest signals of how much the QIS space has matured is the change in how investors frame their requests.

Early-stage investors would typically arrive looking for a clever diversifier — something uncorrelated, liquid, and structurally different from their existing book.

Today's institutional investors arrive with specific mandates. The brief might be: help me protect against sticky inflation, or help me hedge tail risk without sacrificing too much carry, or help me access a market I find operationally cumbersome to run. Sometimes the problem is not investment-objective-led at all — it is operational. Help me deploy cash efficiently. Help me minimise margin.

This evolution in client sophistication has directly driven the expansion of QIS capabilities. Banks have had to respond by decomposing the QIS value chain — proprietary IP, data, execution, technology — into modular components that investors can interact with selectively, according to what they actually need.

The Three Dimensions of QIS Evolution

When Chloi reflects on how the space has changed, she identifies three distinct dimensions:

1. Product and platform capabilities New instruments, new data sets, enhanced intraday risk monitoring, bespoke analytics and reporting tools — the underlying infrastructure has advanced substantially. This is the dimension most commonly discussed.

2. Breadth of use cases The expansion from plain diversification to portfolio completion, hedging for specific risks, market access, and objective-driven structures. QIS is no longer a satellite allocation; for many institutions it is now a core part of the construction toolkit.

3. The collaboration model This is the evolution most people miss. Advances in platform technology have enabled things like custom strategy code development, dynamic parameter adjustment within live strategies, and execution outsourcing. These capabilities have opened the QIS space not just to traditional allocators but to active asset managers and hedge funds as well.

The common thread across all three? Breadth. The space has expanded in every direction simultaneously.

Why Implementation Is Make or Break

Here is the part of the conversation that matters most for anyone deploying QIS in a portfolio.

Two strategies can be structurally similar — same signal logic, same broad asset class exposure — and end up with very different live risk profiles. The variables that create that divergence are almost entirely implementation choices:

• Instrument selection — the exact instruments used to express the signal
• Sizing and calibration — how much risk is taken and on what schedule
• Signal-to-execution lag — how quickly the portfolio responds to new information
• Execution timing — when, and how, trades are placed
• Risk management — how drawdowns are managed and how the strategy behaves under stress

These choices determine the carry, the drawdown profile, the rebound characteristics after a stress event, and ultimately the lived experience of holding the strategy versus the theoretical expectation. That gap between theory and live experience is where most QIS investments either succeed or disappoint.

"Implementation choices are make or break. There is a very important edge available from the craft of implementation." — Chloi Karyda

Access format matters for a different reason. The choice of investment structure — UCITS, total return swap, note format, protected loss format — can determine whether an investor can obtain internal approval to enter the space at all. For institutions with strict risk controls, the structure is not a secondary consideration. It is the gating decision.

Applying QIS Across Macro Regimes

The conversation turns to specific market environments where systematic tools offer a structurally interesting edge over directional alternatives.

Sticky Inflation

Inflation creates two distinct portfolio challenges. First, the correlation structures that underpin multi-asset construction can shift significantly in a high, persistent inflation environment. Second, upside inflation surprises make the path of rates more volatile and therefore harder to position around with a single view.

A systematic approach offers more flexibility here than a directional call. Rather than committing to a specific rates path, a QIS framework can provide convex exposure — through long volatility in rates, inflation, or commodities, or through delta-replication structures — that benefits from realised moves in either direction while continuing to harvest premium in range-bound conditions. The asymmetric payoff profile is harder to achieve with a straightforward long or short.

Equities in a Thematic Market

Markets shaped by a dominant theme — the AI buildout being the current example — often mask significant dispersion beneath the headline direction. Winners versus losers, CapEx efficiency, crowding and reversal risk: the edge is in the micro, not the index.

Structures that target correlation dynamics or factor rotations can capture this dispersion without requiring a binary call on the index. And the two approaches are not mutually exclusive. A fundamental tilt toward AI beneficiaries can be coupled with systematic dispersion exposure — targeting implied correlation across the sector — to combine thematic conviction with a structural market microstructure edge.

Commodities

Commodities are frequently discussed as a single asset class. They are not. Each commodity sub-sector is driven by its own engine: metals by capital expenditure and electrification themes; energy by geopolitics and supply policy; agriculture by inventories, crops, and weather. Even within a single commodity, idiosyncratic factors can dominate at any given moment — and then there is the curve.

A systematic approach can address this complexity directly. Rather than relying on a single directional view, it can simultaneously target carry, trend, fundamental value reversion, and curve dynamics on a commodity-by-commodity basis — managing each idiosyncrasy independently while overseeing risk holistically. A directional call on the front-month contract, even a granular one, can still lose on the curve if a geopolitical shock reprices the term structure unexpectedly.

The Most Underestimated Risk in QIS Investing

When asked what investors most consistently underestimate when entering the QIS space, Chloi's answer is not about strategy design or product selection. It is about organisational alignment.

Internal education that extends beyond the portfolio management team — to risk, compliance, governance, senior leadership — is where many QIS programmes succeed or fail. Without it, the gap between the theoretical investment horizon and the lived investment horizon tends to widen. Review cycles trigger at the wrong moments. Organisations exit strategies that were working exactly as designed.

The fix is a roadmap built for the specific institutional context: one that sets out objectives, risks, risk tolerance under different scenarios, periodicity of reviews, and expected behaviour across market regimes. And crucially, one that the full organisation has bought into before the first trade is placed.

What Will Shape the Next Phase of QIS?

Looking ahead, two forces stand out.

The macro environment will continue to set the agenda for what investors care about at any given time. The path of rates shapes how important carry and income generation are. The level of volatility and concentration risk shapes the demand for protection. Macro regimes create tactical opportunities, and QIS is well positioned to respond to them.

Artificial intelligence is the more structurally interesting question. If AI tools continue to commoditise signal generation and screening — making IP creation more widely accessible — then the edge migrates further toward execution, liquidity management, risk control, and platform quality. In that scenario, what you know matters less than how well you can implement it. The craft of implementation becomes even more central than it already is.

What Twenty Years in QIS Actually Looks Like

The observation Chloi finds most striking, looking back, is not any single strategy or market moment. It is the adaptability of the QIS infrastructure itself.

QIS was always data-heavy, technology-heavy, and execution-heavy. That architecture — built for precision, not flexibility — turned out to produce platforms that could recalibrate quickly as investor needs shifted. That adaptability was not necessarily the goal when the platforms were built. It has turned out to be their most valuable characteristic.

The lesson: the edge in this space has never been one smart, evergreen model. It has been the machinery that allows rapid recalibration — the ability to meet investors where they are, as the environment changes around them.

Key Takeaways

• QIS has evolved from a product category into a modular portfolio toolkit, useful across a wide range of investment objectives and operational constraints.
• Implementation choices — instrument selection, sizing, execution lag, risk management — determine the difference between the theoretical and lived experience of a strategy.
• Systematic tools offer a structural advantage in complex macro regimes (sticky inflation, thematic equity markets, commodities) precisely because they do not require a single correct directional view to add value.
• The most underestimated risk in QIS investing is organisational: insufficient internal alignment before the first trade is placed.
• If AI commoditises signal generation, the implementation edge becomes the primary source of alpha. Execution craft, liquidity management, and platform quality matter more, not less.

Resonanz Spotlight is the podcast series hosted by Vincent Weber, CEO & Head of Research at Resonanz Capital. Each episode explores investment strategy, systematic design, and portfolio construction through conversations with practitioners shaping the space.

Resonanz Capital is an investment manager specialising in multi-strategy investing and portfolio solutions. Alternatives, engineered.