How Much Can You Make DCA into NASDAQ for 20 Years? Dissecting a Viral Zhihu Answer

The Original Argument

Zhihu user @hello world, in the top answer to “Should you DCA into NASDAQ with 10K RMB/month for 20 years?”, makes three main claims:

1. DCA “numbness effect”: Once your principal grows large, monthly contributions of 10K have negligible impact on your average cost
2. DCA raises costs in a bull market: Since NASDAQ trends up long-term, DCA keeps buying at higher and higher prices
3. A better approach: Build a 30% base position, then go all-in when the CNN Fear & Greed Index hits “Extreme Fear”

The answer received 676 upvotes, ranking first on the thread.

Let’s Do the Math First

The original answer dodges the key question: how much does 20 years of DCA actually return?

Assumptions:

• 10,000 RMB monthly contribution
• NASDAQ 100 long-term annualized return: 12% (including dividend reinvestment; historical range is 12-15%)
• Monthly rate = 12% ÷ 12 = 1%

Using the future value of annuity formula:

FV = PMT × [(1+r)^n - 1] / r
FV = 10,000 × [(1.01)^240 - 1] / 0.01
FV ≈ 9.99 million RMB

Bottom line: conservatively ~10M RMB, optimistically ~15M. Either way, compound interest does serious work on that 2.4M principal.

What the Author Gets Right

1. The Numbness Effect Is Real

Mathematically sound. Once your principal reaches 1M RMB, a monthly 10K contribution only affects 1% of your cost basis. At 2M, it’s 0.5%. DCA’s cost-averaging effect genuinely diminishes over time.

2. Lump Sum Has Higher Expected Returns

If you know for certain an asset will trend upward, lump-sum investing mathematically outperforms DCA. This is textbook finance — no dispute.

What the Author Gets Wrong

1. “All-In at 25,000 Beats 20 Years of DCA” — Hindsight Bias

This is the article’s biggest logical flaw.

The author argues that since NASDAQ 25,000 will look cheap in 20 years, you should go all-in now. Two fatal problems:

Problem 1: You don’t know how it’ll look in 20 years. In March 2000, NASDAQ hit 5,000 — also “near all-time highs.” If you went all-in then:

• October 2002: dropped to 1,100, a 78% loss
• Took until 2015 to recover — 15 years underwater
• 2.4M invested in early 2000 would have become ~530K by late 2002

Problem 2: “Long-term up” is not a law of nature. The Nikkei 225 hit 39,000 in 1989. Thirty-five years later (2026), it’s only just reclaimed that level. “Long-term upward” is an assumption that needs validation, not an axiom.

2. “Go All-In When Fear & Greed Hits Extreme Fear” — Armchair Quarterbacking

Sounds great in theory. Three practical problems:

Execution difficulty: During extreme fear, 99% of people are selling, not buying. On March 23, 2020 (NASDAQ bottom), the CNN Fear Index read “Extreme Fear,” and headlines screamed “global economic collapse” and “second Great Depression.” Can you overcome human nature to go all-in at that exact moment?

Signal ambiguity: Extreme fear can be followed by even more extreme fear. When Lehman collapsed in September 2008, fear indices were already at extremes — but markets fell another 40% before bottoming. When do you pull the trigger? First extreme reading? Second? Third?

No empirical backing: The author provides zero backtesting data for the “Fear & Greed Index timing” strategy. Academic research consistently shows that most timing strategies underperform buy-and-hold after accounting for transaction costs and psychological costs.

3. Zero Risk Discussion

A serious investment analysis that mentions “risk” exactly zero times.

NASDAQ’s major drawdowns:

If you went all-in with 2.4M at the 2000 peak, you’d have ~530K by late 2002. You’d need to wait until 2015 to break even. Meanwhile, a DCA investor continuing to buy through the crash would accumulate shares at rock-bottom prices, profiting far more on the rebound.

The Real Value of DCA

DCA’s merit isn’t being “mathematically optimal.” It’s about behavioral finance discipline:

1. Executability: An average person investing 10K/month from salary is entirely feasible. “Wait for extreme fear then go all-in” means holding large cash piles while bearing opportunity cost and inflation erosion.

2. Anti-fragility: DCA naturally buys more shares when prices are low and fewer when prices are high. In down markets, a DCA investor’s average cost significantly undercuts the market average.

3. Avoiding timing failure: Retail investors’ biggest source of losses isn’t “buying the wrong stock” — it’s “buying and selling at the wrong time.” DCA eliminates this risk through discipline.

4. Psychological sustainability: A strategy you can stick with for 20 years beats an “optimal” strategy you can’t stick with. DCA’s automation makes it one of the most sustainable strategies available.

When the Author’s Advice Actually Makes Sense

To be fair, the author’s logic isn’t entirely wrong — but its applicability is narrow:

• You genuinely have a large lump sum (not salary-dependent investing)
• You have extraordinary psychological resilience (can add positions during 50% drawdowns instead of panic-selling)
• You have reliable timing signals (whether CNN Fear & Greed qualifies is debatable)
• Your investment horizon is long enough (10+ years)

People who meet all four criteria? Probably less than 5%.

Conclusion

Score: 5.5/10

The author understands DCA’s mathematical properties correctly but commits the most common error in investment analysis: deriving the unknown future from the known history. “NASDAQ 25,000 will look cheap in 20 years” can only be verified 20 years from now. Until then, DCA’s value as a risk-diversification tool is irreplaceable.

Advice for ordinary investors: DCA isn’t the optimal strategy, but it’s the strategy most people can stick with. A strategy you can always stick with beats an “optimal” strategy you can’t.