Bitcoin vs. The Stock Market

Every cyclical top in bitcoin’s history was visible as a top in real time. Every cycle floor was visible as a floor. The pattern isn’t subtle when you plot bitcoin’s price against its long-run Power Law trend — tops register as measurable deviations above trend; floors register as measurable deviations below it. The chart below plots both across 16 years of price history, plus today’s position.

Two things are immediately visible in the chart that qualitative narratives about bitcoin tend to miss.

First, tops are getting smaller. Bitcoin’s cyclical peaks have compressed dramatically: 12.1× over trend in 2013, 6.4× in 2017, 2.8× in 2021, and just 1.1× in both the March 2024 top and the October 2025 all-time high. (The 12.1× in 2013 reflects early bitcoin’s pre-institutional regime, when retail-driven overshoots were far more violent than anything since — and the compression from 12× to 1.1× is the maturation evidence.) The euphoric overshoots that defined the early asset have faded every cycle. This is the maturation thesis — institutional capital, regulated ETF flows, roughly 6.4% of supply held in ETPs, treasury allocations at 49+ public companies, 23 nation-state holders — rendered as a single visual fact: tops aren’t what they used to be.

Second, floors have stayed structurally stable. Across four different cycles spanning a 90× range of absolute prices, the cycle bottoms have all registered between 0.41× and 0.66× trend — a tight band. The downside reference hasn’t moved while the upside has compressed toward it. The within-cycle entry-price spread has gone from 22× (2013 top vs. 2015 floor) to 1.7× (2024 March top vs. 2024 August dip). Timing matters less now than it used to; the boundaries are tighter on both sides.

By the framework’s own logic, low-channel readings have historically been structurally favorable entry territory: bitcoin’s trend-relative discount tends to compress over multi-year horizons (mean reversion plus continued absolute trend growth). The October 2025 all-time high only managed 12% above trend, and bitcoin has spent more “distance” below trend than above it in this cycle. The relationship inverts when bitcoin trades above trend — at upper-channel positions the prudent read is the same framework running in the opposite direction.

The chart isn’t a forecast — the Power Law is a central-tendency expectation, not a prediction, and the asset can stay below or above trend for extended periods. The point is that you have a structural reference for reading entry quality in real time. The scenarios below stress-test that reference against entries the framework itself would flag as upper-channel: what would have happened if you’d actually bought at cyclical tops like these? The answer rhymes across every cycle — and it isn’t what the “what if I’d bought the top” objection assumes.

Four of the cyclical tops marked on the §1 chart are reflected in the calculator below as preset entries — three obvious above-trend overshoots (2013 at 12.1× trend, 2017 at 6.4×, 2021 at 2.8×) plus the most recent local high (2025 ATH at 1.12×). The 2024 March top is omitted from the preset row: at 1.14× trend it’s barely above trend, normal cycle behavior rather than a stress test worth running in isolation. The calculator runs two scenarios per entry: a single lump sum held to today, or weekly DCA from that day forward. Compare against the same dollar amount or weekly cadence in the S&P 500 (total return, with dividends reinvested) and the NASDAQ-100 (total return). What’s being tested is the framework’s strict-conservatism claim: even at entries the Power Law would flag as upper-channel — entries you wouldn’t make if you were using the framework — the horizons that matter still produced wealth.

DCA mode smooths the worst-timing risk because most of the dollars get deployed at prices other than the peak. Lump-sum mode shows the rawest version of the stress test: a single buy on the worst day. The verdict text below each result calls out where the page’s argument depends on long-enough holding periods — particularly for the most recent 2025 ATH preset, where the hold has only had a handful of months to play out. The pattern stabilizes at horizons longer than ~3 years, and decisively at horizons longer than ~5; the older the entry, the more the pattern has had time to assert itself.

The 2025 ATH preset deserves a specific caveat in either mode. It’s the most recent cyclical high covered here and has had the least time to play out — bitcoin reached its all-time high of approximately $126K on October 6, 2025; on September 29, 2026 the price sat roughly a third below that level (about $83,500). If you started from that scenario in lump-sum mode, your hold is only about a year old, and the calculator shows where it stands against the S&P 500 today; it may well be behind. The page’s argument depends on long-enough holding periods. The 2017-top and 2021-top presets show what the same scenario tends to look like after five-plus years of patience.

A note on DCA versus lump-sum, since the page is being fair to the reader who’d ease in: Vanguard’s research on this question — across decades of equity-market history — finds that lump-sum investing beats dollar-cost averaging in roughly two-thirds of historical 12-month windows. The mechanism is simple: markets spend more time going up than down, so deploying capital later (on average) means buying at higher prices. DCA’s value is real, but it’s primarily a regret-minimization tool that prevents the worst single-day-entry outcome, not a return-maximization strategy. The page leads with the lump-sum-at-the-top scenarios precisely because they’re the most-feared outcome — if the historical record handles even those cases at the horizons that matter, the case for DCA-as-a-better-alternative gets weaker, not stronger.

One entry date proves nothing; fifteen hundred of them prove something. The finding is in the rows, not the cells — past a long enough horizon, the colour stops depending on when you started.

The calculator above runs one scenario at a time. The grid below runs every scenario at once: every monthly start date from January 2010 through today, against every common holding horizon. Each cell is one window — one entry, one horizon — and the color shows whether bitcoin outperformed the chosen comparator over that window, and by how much.

Two patterns surface immediately. At short horizons (six months, one year) there are real losses to find — visible red pockets that line up with cyclical-top entries. At long horizons (seven years and up) every cell is amber: there is no historical window over which a 7+ year holder failed to outperform the index. The page's argument across the prose chapters above is the same argument the heatmap makes visually — the horizons that matter still produced wealth, even from the worst entries.

The retrospective evidence above answers the question for someone considering a position who would have started at any of the dates the page covers. The forward question for someone deciding right now is: over the horizon I’ll actually hold this, where is the trend headed?

The chart below plots two bitcoin paths against the long-run trend lines for the S&P 500 and the NASDAQ-100: the same two scenarios for bitcoin’s price that every forward calculator on the site uses. In the first (solid), bitcoin stays as far from its Power Law trend as it is today and grows at the trend’s own rate: the conservative read when bitcoin is below trend, since nothing in it depends on a recovery, and the optimistic one when it is above. In the second (dashed), the gap closes in a straight line over 3 years and bitcoin then follows the trend: the historical pattern, since every earlier stretch on either side of the trend has ended with bitcoin back at it. Both start at the amount invested today, so the distance that opens between them over the first 3 years is what today’s position against the trend amounts to if that pattern holds: the dashed line pulls ahead when bitcoin starts below trend and falls behind when it starts above. Neither is a forecast. Bitcoin has spent long stretches on either side of the trend, and deviations within cycles can be very large in either direction. The stock lines run at their long-run averages; the stress test above the chart switches them to their own record since 2010, the years bitcoin has had a market price, which makes the stock market’s case stronger.

For an investor with a typical decision horizon — 10 to 15 years — both bitcoin lines stay meaningfully above both comparators, with the gap measured in multiples rather than basis points. Each comparator’s line, compounding from the same amount today, catches bitcoin’s only many decades from now; the dates, and how they move with bitcoin’s price, are in the methodology at the foot of the page. Even at the 40-year horizon, bitcoin’s trendline expected returns remain substantially higher than any conventional stock-market comparator.

Volatility is a horizon-dependent concern. A 50% drawdown is terrifying at six-month horizons and noise at ten-year horizons. The historical record in §2 above is the empirical version of this claim: every worst-timed lump-sum entry the page tests at horizons of seven years or longer produced more wealth than the S&P 500 over the same period. The 2021 top has not reached that horizon, and at just under five years it trails — and the heatmap’s five-year row shows most 2021 entries trailing so far, though not all (January 2021, for one, finished ahead).

The horizon-dependence shows up sharply when the recent past is sliced at different windows. Through September 2026: at one year, the S&P 500 is up about 17% and bitcoin down about 27%. At five years the two are almost level, bitcoin up about 91% and the S&P about 90%. At ten, bitcoin’s roughly 13,600% dwarfs the S&P’s 318%. Same asset, same comparator, three completely different stories — the drama isn’t in the asset, it’s in the horizon you use to measure it.

Time in market applies differently at different CAGRs. A 10%-CAGR asset doubles in about seven years. A 25%-CAGR asset doubles in under three. Compounding advantage over long horizons is exponential, not linear — which is why a relatively small allocation to a high-trend asset, held across years, can materially shift a portfolio outcome even when most of the portfolio is in conventional assets. The relevant question isn’t whether bitcoin is volatile (it is) or risky (it is) or might fail (it might). It’s whether a small position, held long enough, with a clear understanding of the trend, compounds to something that materially changes the holder’s financial picture. The historical record says yes at every horizon the page tests.

Bitcoin vs. gold is its own argument. Gold has rallied strongly over recent years on central-bank buying and currency-debasement concerns — the same long-cycle store-of-value rotation bitcoiners argue eventually benefits bitcoin disproportionately, given gold’s ~$25T market cap versus bitcoin’s roughly an order of magnitude smaller. The mechanics, the relative cycles, the ETP-cost asymmetry (GLDM vs. GLD), and the structural overlap with bitcoin’s thesis all deserve a dedicated treatment rather than a sidebar here; see the forthcoming Bitcoin vs. Gold page. This page’s comparison set is bitcoin vs. the equity indexes a typical retail or institutional investor would otherwise hold.

Bitcoin’s volatility itself is changing structurally. A pattern emerged in 2025 that didn’t appear in earlier cycles: bitcoin posted a fresh all-time high (~$126K in October) while realized volatility printed decade-lows in the same window — new ATH and new ATL volatility, simultaneously. The MVRV ratio (market value to realized cost basis) has held steady around 2.0× through the recent top, against 4–6× peaks at the 2017 and 2021 highs. The institutional infrastructure has thickened: roughly 6.4% of supply now sits in spot bitcoin ETPs; 23 nation-states are net accumulators; 49+ public companies hold corporate treasury positions of more than 1,000 BTC each. None of this guarantees the trend continues; all of it makes a sudden mean-reversion to earlier-cycle volatility behavior less likely. The asset that the ten-year backtests on this page are measuring is empirically migrating — slowly but visibly — from speculative-crypto behavior toward something closer to a high-vol equity allocation with a structural tailwind.

As with the rest of this site, the right reading isn’t “this is the answer.” The right reading is: here’s the historical record and the trend the model expects from here — including the cases where the picture is less favorable. The decision about whether to take a position, how large, and over what horizon is yours. The page has done its job by giving you enough structural detail to make that decision with eyes open.