Where does return history from before an ETF existed come from?

Most of the ETFs a DMS strategy trades are younger than the track record shown for that strategy. A broad commodity ETF may have launched in 2014, an international equity ETF in 2011, a Nasdaq-100 fund in 1999. If a backtest could only use the period where every holding actually existed, the entire test would be truncated to the youngest fund in the lineup - and a strategy tested only on the post-2014 era has never been shown a rate-shock, a commodity boom, or a 1970s-style inflation regime.

To avoid that, DMS uses extended return series: each asset class is reconstructed backwards to January 1979 from the best available source for each stretch of history. The strategy is then tested against that longer record.

The waterfall

Every asset class is built from a prioritized chain of sources. The engine walks the chain from best to worst and takes each date's return from the highest-ranked source that actually has data for that date. In order of preference:

1. The real ETF itself. Wherever the fund exists and has traded, its own total-return history is used. No modeling, no substitution.
2. An older share class of the same fund. Many ETFs are the newer wrapper on a mutual fund that has been running for decades. When that's the case, the older share class is a near-exact extension of the same portfolio, differing only in fee structure.
3. A comparable fund tracking the same universe. Where no earlier share class exists, an older mutual fund with the same mandate and credit/duration/geographic profile fills the gap.
4. A total return index. When no traded fund reaches far enough back, an index is used. It must be a total return index, not a price or excess-return index - otherwise the yield or dividend component is silently dropped and the whole series understates the asset.
5. A modeled reconstruction. Bond-pricing math from published yield curves, or a regression-based estimate. Last resort, used only where nothing above is available.

The chain is a splice, not a blend. Two adjacent tiers are never averaged together; each date is sourced from exactly one place.

Substitutions are held to a standard

A fund only earns a place in a chain if it is genuinely tracking the same thing. This is where most of the judgment sits, and it cuts both ways: a corporate-bond fund is not a proxy for a broad aggregate bond index even though both are "bonds," and a high-yield fund is a different asset class entirely rather than a longer-history version of investment grade. Tiers get removed when they fail that test, even when removing them shortens the history.

Everything is total return

Price history alone is not usable. Every source in every chain is dividend- and distribution-adjusted, so the series represents what an investor would actually have earned holding the position. For bond and commodity series in particular, the income component is most of the return, and a price-only source would be badly wrong rather than slightly wrong.

Expenses are handled tier by tier

Each source in a chain carries its own expense ratio, and the reconstruction accounts for that source's actual fee for the dates it supplies - not a single blanket fee applied across the whole history. A 1990s mutual fund charging 0.90% and a modern ETF charging 0.05% are not interchangeable on cost, and using one fee across both eras would leave a small permanent drag or boost baked into the older half of the record.

Leveraged series are rebuilt, not borrowed

For 2x and 3x series, no leveraged fund existed before roughly 2006-2010, so those histories are constructed rather than sourced. Each day's unlevered return is multiplied by the leverage factor, then charged a financing cost derived from the prevailing overnight rate plus a spread, then charged the real leveraged fund's own published expense ratio. This is daily-reset leverage, matching how the actual products work - which means the reconstruction reproduces volatility decay in choppy markets rather than papering over it.

Monthly history often reaches further back than daily history

Daily price history and monthly return history come from different places and stop at different points. A fund may have thirty years of published monthly returns but only twenty years of usable daily prices. Where that's true, the monthly series is extended using the monthly data while the daily series stops at the last date with trustworthy daily prices.

The practical consequence: for some asset classes, monthly-resolution results start earlier than daily-resolution results. A strategy rebalancing monthly may therefore show a longer track record than the same strategy tested at daily granularity.

Regression-based tiers

Where an asset class has no fund and no clean index reaching far enough back, one remaining option is to estimate its returns from the assets it is statistically related to - regressing the target series on factors or on other markets with longer histories, then using that relationship to project the missing period.

This produces a plausible series, not a real one, and it is treated with more suspicion than every tier above it. A regression fit on one era's correlations can behave badly in an era where those correlations broke down, which is precisely the period a long backtest is meant to stress. Regression tiers are used sparingly, sit at the bottom of the chain, and are retired when a better source appears or when the reconstruction fails review.

Real data always wins

Where the actual ETF has traded, its own returns are used - always. Synthetic history exists only to fill the space before that, and the moment real data begins it takes over completely. The two are stitched at the fund's inception, not blended across it.

What synthetic history is and isn't

It is a careful reconstruction of what an asset class returned. It is not a record of what an investor experienced.

Specifically, it excludes: bid-ask spreads and market impact, tracking error against the index, securities-lending revenue, borrow availability, and the practical reality that many of these strategies would have been difficult or impossible to run in 1979. Reconstructed leveraged series in particular assume idealized daily rebalancing at zero cost, which real leveraged funds do not achieve.

It is also worth remembering that the deepest tiers of any chain are the least reliable, and they sit in the oldest and most unusual part of the record - the stretch doing the most work in a long backtest. Treat the earliest years as directionally informative about how a strategy behaves in an unfamiliar regime, not as a precise measurement.

How to read results that use it

Results built on extended history are best used to answer "does this approach survive conditions the last fifteen years never produced?" rather than "what exactly would I have made?" Where a strategy's edge depends heavily on the pre-ETF era, that is worth knowing and worth discounting.