Sylvia Jablonski

Sylvia Jablonski is the CEO and CIO of Defiance ETFs. Her background spans delta one sales and trading, equity derivatives, and over a decade at Direxion ETFs (the leveraged and inverse ETF issuer) before she helped build Defiance alongside founder and chairman Matt Bielski. The firm offers a variety of products across leveraged single stock ETFs, income products, and thematics. On this episode of Behind the Ticker, the conversation focuses on QTUM, their quantum computing and machine learning ETF, and why that space represents one of the most exciting long-term investment themes in the market.

From Direxion Derivatives to Defiance

Sylvia's path to Defiance is rooted in the derivatives world. She started at major banks doing delta one sales trading, covering ETF issuers and hedge funds for swap trades. Around 2007-2008, the financial crisis, she was working heavily with swap-based products and ETF structures. That experience led to Direxion, where she spent over a decade building expertise in leveraged and inverse ETFs. Matt Bielski worked alongside her during those years, and when the opportunity came to build something from scratch, they launched Defiance.

The firm has also built a separate marketing company that started organically. When Defiance began having disproportionate success getting its brand out relative to its small size, other ETF issuers started calling to ask how they were doing it. That led to a marketing business that now serves some of the largest ETF providers in the industry. The marketing arm was eventually separated from Defiance ETFs into its own entity, creating a second revenue stream while keeping the two businesses complementary.

QTUM: Quantum Computing, Machine Learning, and AI

QTUM was designed to capture the broad ecosystem around quantum computing, machine learning, and artificial intelligence. Defiance worked with BlueStar to create the underlying index, which identifies companies that attribute at least 50% of their revenue, commercialization, or research to super computing, machine learning, and AI. The fund holds about 72 names on an equal-weighted basis and includes semiconductor companies, hardware manufacturers, cloud computing providers, and pure-play quantum computing and AI firms.

The holdings span from household names like NVIDIA and Microsoft to less obvious picks like IBM (a major investor in quantum computing), Hewlett Packard Enterprise, and various semiconductor companies powering the AI infrastructure buildout. Equal weighting means the fund isn't dominated by the mega-caps the way a cap-weighted tech fund would be. This gives investors broader exposure to the theme rather than just buying a concentrated bet on the largest names they probably already own through the S&P 500.

Why Quantum Computing Matters

Sylvia makes the case that quantum computing has the potential to transform every major industry. Quantum computers process data in fundamentally different ways than traditional computers, allowing them to handle computations that would be practically impossible for classical machines. The applications span drug discovery and biomedical research (processing the massive datasets needed for cancer research and genomics), materials science (designing new materials at the molecular level), financial modeling (running portfolio optimization and risk simulations that currently take hours in fractions of a second), cryptography, and climate modeling.

The recent excitement comes from companies like Google demonstrating quantum supremacy, where a quantum computer solved a problem that would take classical supercomputers thousands of years. While commercial quantum computing is still in early stages, the investment in the ecosystem (hardware, software, error correction, cloud quantum services) is accelerating rapidly. Sylvia argues that even if full-scale commercial quantum computing is years away, the companies building the infrastructure, chips, and software tools are investable now and benefiting from the spending cycle.

Levered Products, Volatility, and Who's Buying

Brad also asked about Defiance's single stock leveraged ETF products, and Sylvia shared insights from the demand side. She pushes back on the idea that these products are "dangerous." The typical user is not a naive retail investor. These are high-conviction day traders and sophisticated investors who know exactly what they're buying. They often hold for short periods, have hedging strategies in place, or are using the products for specific tactical bets. From the issuer's perspective, volatile markets are actually good for volume in leveraged products because that's when the high-conviction traders are most active.

Key Takeaways

• QTUM holds about 72 equal-weighted names across the quantum computing, machine learning, and AI ecosystem, selected by companies attributing 50%+ of revenue or R&D to these fields.
• Equal weighting prevents mega-cap domination, giving investors broader thematic exposure versus a cap-weighted approach that would heavily concentrate in names they likely already own.
• Quantum computing can transform drug discovery, financial modeling, materials science, and cryptography by processing computations impossible for classical machines.
• Defiance also built a separate marketing company that now serves major ETF providers, born from other issuers asking how Defiance achieved disproportionate brand awareness relative to its size.
• Sylvia spent over a decade at Direxion building expertise in leveraged and derivative-based ETFs before co-building Defiance with chairman Matt Bielski.

Listen to the full conversation on Spotify, Apple Podcasts, or YouTube.