CSA Launches Consultation on ETF Regulation Based on OSC Report

CSA launches consultation on ETF regulation based on OSC report – covering liquidity, NAV accuracy, APs, and overall market structure. The study covered 933 Canadian ETFs with a combined $355 billion in assets and evaluated their performance from 2019 to 2023. It revealed several notable patterns in how the key mechanisms of ETF functioning operate. By the way, I highly recommend our in-depth guide on what crypto ETFs are and how they work.

Specifically, the study identified dynamics in mechanisms such as secondary market liquidity, price accuracy relative to NAV (PD-NAV), and arbitrage through the involvement of APs (authorized participants).

There is particular attention to segments with varying levels of transparency and management structure: index-based vs. actively managed, small vs. large-scale, simple vs. multi-component. The study also included regression models to identify the factors affecting fund resilience during market stress and pricing accuracy.

The open consultation, based on this aggregated data, is expected to gather feedback from market participants on issues such as access to foreign ETFs, disclosure requirements, assessment of arbitrage resilience, and the development of a regulatory basis for new asset classes, including digital and cryptocurrency-based ETFs.

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Market Structure: Volume Growth, Dominance of Large Funds, and Increasing Product Complexity

As of the end of the review period in December 2023, total assets under management across all Canadian ETFs stood at $372 billion, of which $355 billion were held by the 933 funds included in the study sample.

This indicates that since 2015, the market has grown more than fourfold, from $90 billion, supported by steady interest from both retail and institutional investors. However, this growth has been uneven, and internally, there is a clear shift toward more complex structures and increasing concentration of assets among a limited number of funds and providers.

The OSC emphasizes that the market remains oligopolistic: there are 45 ETF providers present, but only 5 of them – including iShares, BMO, Vanguard, and Horizons – account for 91% of total AUM and 82% of secondary market trading volume.

Such concentration increases the systemic importance of a small number of products and platforms, and any disruptions in their operations could impact not only liquidity but also the integrity of NAV-oriented instruments as a whole.

The ETF market is highly fragmented across strategies and asset types, yet a few segments still dominate. As of the end of 2023, equity ETFs made up 61% of AUM (down from 70% in 2015), while fixed-income ETFs accounted for 32%, up from 21% in 2015. The remaining share consists of commodities, multi-asset products, and notably, alternative strategies (liquid alts). Over five years, the number of actively managed ETFs has doubled: from 142 to 283 funds, and their share among all products has reached 30%.

However, alongside the expansion of product offerings, the issue of scalability has intensified. Nearly half of all funds remain undercapitalized: 47% of all ETFs have AUM under $100 million, and 23% – under $25 million. Combined, this group manages less than 2% of the market. Meanwhile, the top 16% of funds concentrate 79% of total assets and virtually all secondary market turnover.

This confirms the critical need for a differentiated regulatory approach: requirements justified for large, liquid funds may be economically inefficient or even harmful if directly applied to small ETF structures.

The report also documents a sustained trend toward consolidation through mergers. The number of ETFs with AUM over $1 billion rose from 38 in 2019 to 59 by 2023. At the same time, the average asset size among the 10 largest funds increased by more than 40%. This reinforces the issue of regulatory balance between rule universality and adaptation to different scales of operational and market risk.

Finally, the report notes the growth in the number of cross-listed and multi-class structures, as well as the use of currency hedges and synthetic instruments. These elements still represent a small portion of the market but require separate consideration, particularly in the context of jurisdictional interoperability and the prospects of international products, including crypto ETFs.

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ETF Liquidity: Quoted Spreads and Stress Resilience

The quoted spread (QS), as a key indicator of ETF liquidity on the secondary market, reflects the cost of entering/exiting a position and is sensitive to both market conditions and the structural characteristics of the fund itself. The report uses the OSC QS as a primary proxy metric, stratifying funds by asset class, size, and strategy, and comparing behavior during calm and stress phases.

Under normal market conditions, the median QS across all ETFs was 18 bps, though there is considerable variation: equity ETFs tracking broad-based indices had spreads around 4–10 bps, while fixed income ETFs were significantly wider, up to 40–50 bps, and liquid alts – above 70 bps.

Yet it is behavior under stress that reveals the most critical aspects of liquidity. For example, March 2020, according to the OSC, was a unique stress test for the Canadian ETF segment. Quoted spreads rose 5–10x over historical levels, especially in fixed income, where liquidity in underlying securities dried up sharply.

For some products, QS exceeded 200–250 bps, making the secondary market nearly unusable for executing large orders without significant slippage.

Even within a single asset class, performance varied. ETFs tracking government bonds with short maturities maintained more stable liquidity than funds with exposure to corporate bonds or emerging markets debt. In equities, ETFs tracking large indices were more resilient, while thematic or sector-based products deteriorated rapidly.

Interestingly, QS recovery occurred at different speeds. According to OSC, equity ETFs returned to pre-crisis levels within 2–3 months, while fixed-income ETFs recovered only by mid-2021. Funds using alternative structures (futures, derivatives, currency hedges) continued to show persistently wider spreads even after market normalization.

The report also confirms a logical but critical correlation between fund size and liquidity: ETFs with AUM over $1 billion had, on average, 2–3x narrower QS than those with AUM under $100 million. This underscores scalability and operational quality as defining factors of market resilience.

Thus, QS serves as a critical indicator of an ETF’s trading efficiency and simultaneously reflects order book depth, market maker activity, and valuation transparency of underlying assets. This means it requires close attention when designing new funds, including crypto and tokenized ETF structures.

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Arbitrage and Pricing Accuracy: PD-NAV Behavior

A key indicator of ETF pricing accuracy is the PD-NAV metric – the daily deviation of the fund’s market price from its Net Asset Value. Under normal conditions, arbitrage between these figures ensures that the ETF price on the secondary market remains close to NAV, due to AP participation in creation and redemption operations. According to the OSC, the median absolute PD-NAV deviation across all ETFs under normal conditions is 9 bps, confirming secondary market stability in standard regimes.

However, during market stress, this mechanism breaks down. For example, in March 2020, across the entire sample, PD-NAV averaged 119 bps, and for fixed-income ETFs, up to 2.6%, 25–30 times the normal range. The reason is that NAV is based on the pricing of underlying assets, which in panic phases are traded infrequently or at stale prices.

Meanwhile, the ETF market updates in real time, and the NAV lags behind. This creates a temporary situation in which the ETF market price becomes a more accurate indicator of value than NAV, especially for illiquid or hard-to-value assets, potentially including future funds with exposure to tokenized or crypto assets.

Interestingly, even in calm periods, some segments show systematically higher PD-NAV. According to the OSC, actively managed and liquid alt ETFs have above-market deviations due to lower transparency and benchmark complexity.

Moreover, OSC highlights the importance not only of absolute PD-NAV values but also of their stability: volatility-adjusted PD-NAV shows how systematically the ETF price deviates from NAV under the same market conditions. This is particularly relevant for funds on complex or volatile assets, where sustained arbitrage may not be feasible.

Thus, under stress, the ETF price may temporarily act as a forward-looking proxy, rather than NAV, which requires regulators to define clear rules on NAV methodology disclosure, update frequency, and allowable deviation thresholds.

APs: Presence Doesn’t Equal Participation – Structural Arbitrage Risk

Formally, 89% of ETFs in the OSC sample have two or more APs. However, this does not imply actual participation in arbitrage.

OSC emphasizes: that many APs remain passive even during market stress, failing to perform the arbitrage function. This creates asymmetry – a fund may formally have the infrastructure but lack a real mechanism for smoothing NAV deviations.

The report also presents regression model results for 2021 and 2023, showing a negative correlation between the number of active APs and PD-NAV: more engaged APs statistically reduce the likelihood of persistent pricing distortions.

Portfolio Transparency: Limited Link to Liquidity and Price

It was expected that funds with full daily holdings disclosure would demonstrate better liquidity and smaller NAV deviations. However, OSC presents empirical data disproving this assumption.

Among the 933 ETFs sampled, 61% conduct full daily disclosure, 30% – partial, and 9% – monthly only. Nevertheless, liquidity (QS) and pricing accuracy (PD-NAV) did not correlate with the degree of transparency.

OSC interprets this as confirmation that asset structure, market maker, and AP behavior, and market conditions matter more than disclosure per se. This is especially relevant for actively managed strategies, where disclosure may affect alpha generation but doesn’t necessarily improve liquidity.

Statistical Conclusions and Regulatory Implications

The final section of the report includes regression and multivariate analysis of all factors: AUM size, number of APs, level of disclosure, asset class, strategy, and management structure. Key conclusions here are: the most significant predictors of pricing stability are underlying asset liquidity and AP activity.

Potential areas for regulatory discussion: establishing minimum requirements for AP count and activity, enhanced NAV stress-testing protocols, and possibly revised definitions of market maker roles.

Within the same CSA framework, the potential admission of digital asset–based ETFs and their regulatory compatibility with the current model is under discussion. Thus, these OSC findings provide an empirical basis for identifying specific risks and requirements of such funds in regulatory dialogues.

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How This Study Can Influence Crypto ETFs and Digital Assets

The OSC covered almost the entire Canadian ETF market, using multi-year data on infrastructure quality, AP behavior, underlying asset liquidity, and stress resilience. All of these are critical for any ETF to function, regardless of the underlying asset. These principles are universal and may be directly applied to the further development of crypto ETFs.

The arbitrage mechanism is not automatic – it is a live system sensitive to structure and participant behavior. NAV is not always accurate, especially during high volatility, and the role of the secondary market as a real-time value indicator is growing.

Finally, not all models require providers, intermediaries, and arbitrage layers. One of the most direct, verifiable, and transparent approaches is self-managed custody and self-directed asset management in open networks – especially if market access is enabled via licensed, verified platforms with on-chain transparency and minimal infrastructure reliance.